Essec\Faculty\Model\Profile {#2233
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0 => Essec\Faculty\Model\CareerItem {#2376
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3 => Essec\Faculty\Model\CareerItem {#2379
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4 => Essec\Faculty\Model\CareerItem {#2380
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"fr" => "République tchèque"
"en" => "Czechia"
]
]
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5 => Essec\Faculty\Model\CareerItem {#2381
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6 => Essec\Faculty\Model\CareerItem {#2382
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0 => Essec\Faculty\Model\Diplome {#2235
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#_id: null
#_source: array:6 [
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1 => Essec\Faculty\Model\Diplome {#2237
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"bio" => array:2 [
"fr" => """
<p dir="ltr" style="margin-right:-14.3pt"><span style="background-color:transparent; color:rgb(34, 34, 34)">Vincenzo Vinzi possède un doctorat en statistique et informatique de l'Université Federico II de Naples. </span><span style="background-color:transparent; color:rgb(34, 34, 34)">Il fut professeur de statistique à l'Université Federico II jusqu'en 2007, professeur invité et conférencier dans nombreuses universités et centres de recherche à travers l'Europe, les Etats-Unis et l’Asie.</span></p>\n
\n
<p dir="ltr" style="margin-right:-14.3pt"><span style="background-color:transparent; color:rgb(34, 34, 34)">Vincenzo Vinzi est aujourd'hui directeur général de l'ESSEC Business School.</span></p>\n
\n
<p dir="ltr" style="margin-right:-14.3pt"><span style="background-color:transparent; color:rgb(34, 34, 34)">Il est l’auteur d’environ 80 articles scientifiques publiés dans les revues internationales, rédacteur associé de revues internationales correspondant à ses domaines de recherche ainsi que rédacteur en chef et coauteur d’ouvrages spécialisés publiés par des maisons d’éditions internationales comme Wiley et Springer.</span></p>\n
\n
<p dir="ltr" style="margin-right:-14.3pt"><span style="background-color:transparent; color:rgb(34, 34, 34)">Il a été le lauréat du “Teaching Awards 2005” Pierre Vernimmen - BNP Paribas (catégorie Professeurs visitants) à HEC Paris. Deux de ses publications ont reçu le “Top Cited Article 2005-2010 Award” dans la revue internationale Computational Statistics and Data Analysis publiée par Elsevier.</span></p>\n
\n
<p dir="ltr" style="margin-right:-14.3pt"><span style="background-color:transparent; color:rgb(34, 34, 34)">Vincenzo Vinzi a été président de la Société Internationale de la Statistique pour l’Industrie et le Business (ISBIS), du Conseil européen de l'Association Internationale pour la Statistique et l’Informatique (IASC). Il est actuellement membre du conseil de l’ISI (Institut International de Statistique) et de l’IFCS (International Federation of Classification Societies).</span></p>\n
\n
<p dir="ltr" style="margin-right:-14.3pt"><span style="background-color:transparent; color:rgb(34, 34, 34)">Vincenzo Vinzi siège aussi aux conseils d’administration de l'Ecole CentraleSupélec, de l'Alliance Française Paris Ile de France (AFPIF), de l’AmCham et de l’Ecole. </span></p>\n
\n
<p dir="ltr" style="margin-right:-14.3pt"><span style="background-color:transparent; color:rgb(34, 34, 34)">Il est également membre de l'International Advisory Board de la Solvay Business School, </span><span style="color:rgb(34, 34, 34)">d’ Antai College of Economics and Management, de Shanghai Jiao Tong University et de </span><span style="background-color:transparent; color:rgb(34, 34, 34)">l'International Advisory Council de l'Université Pompeu Fabra - Barcelona School of Management. Il est membre d’honneur du board de France Digitale.</span></p>\n
\n
<p dir="ltr" style="margin-right:-14.3pt"><span style="background-color:transparent; color:rgb(34, 34, 34)">Il fait partie des équipes d'évaluation d'EQUIS et de l'AACSB dont il est aussi président du conseil consultatif européen. A compter du 1er juillet 2024 il sert un mandat d’un an en tant que membre du “</span><span style="color:rgb(34, 34, 34)">Business Accreditation Policy Committee” de l’AACSB. </span><span style="background-color:transparent; color:rgb(34, 34, 34)">Il est aussi membre du programme "Business for Inclusive Growth" (B4IG) de l’OCDE. </span></p>\n
\n
<p dir="ltr" style="margin-right:-14.3pt"><span style="background-color:transparent; color:rgb(34, 34, 34)">En mars 2024, il a été réélu pour un second mandat en tant que Vice-Président de la Conférence des Directeurs d'Ecoles Françaises de Management (CDEFM) avant d’en devenir Président par intérim en juillet 2024. Enfin, Vincenzo Vinzi est président de la Commission Diversité de la CGE et du Concours Sésame.</span></p>\n
"""
"en" => """
<p><span style="color:rgb(34, 34, 34)">Vincenzo Vinzi has been the Dean and President of ESSEC Business School since January </span><span style="color:rgb(34, 34, 34)">2018. </span></p>\n
\n
<p><span style="color:rgb(34, 34, 34)">Born in 1970, he was a professor of statistics at the University of Naples Federico II in Italy </span><span style="color:rgb(34, 34, 34)">and has been a visiting professor and lecturer at several universities and research centers </span><span style="color:rgb(34, 34, 34)">throughout Europe, the United States and Asia. He holds a Doctorate in Computational </span><span style="color:rgb(34, 34, 34)">Statistics from the University of Naples Federico II as well as a Master’s in Business and </span><span style="color:rgb(34, 34, 34)">Economics from the same institution. In 2007 he joined ESSEC as a professor of statistics </span><span style="color:rgb(34, 34, 34)">and was elected Dean of Faculty in December 2011. As the Dean of Academic Affairs, and </span><span style="color:rgb(34, 34, 34)">consequently a member of ESSEC's Executive Committee, he was responsible for the </span><span style="color:rgb(34, 34, 34)">management and development of the faculty. </span></p>\n
\n
<p><span style="color:rgb(34, 34, 34)">Recognized internationally for his expertise, Vinzi is the author of approximately 80 scientific </span><span style="color:rgb(34, 34, 34)">articles that have received more than 19,000 citations, published in international journals on </span><span style="color:rgb(34, 34, 34)">topics ranging from Big Data to Business Analytics. </span></p>\n
\n
<p><span style="color:rgb(34, 34, 34)">Between 2012 and 2015, Vincenzo Vinzi </span><span style="color:rgb(34, 34, 34)">served as President of the International Society of Business and Industrial Statistics (ISBIS). </span></p>\n
\n
<p><span style="color:rgb(34, 34, 34)">Mr. Vinzi sits on several Boards of Directors : CentraleSupélec Engineering School, the </span><span style="color:rgb(34, 34, 34)">Alliance Française Ile-de-France Paris (AFPIF), the American Chamber of Commerce in </span><span style="color:rgb(34, 34, 34)">France, the Conférence des Grandes Ecoles (CGE) and l’Ecole.</span></p>\n
\n
<p><span style="color:rgb(34, 34, 34)">He is a member of the International Advisory Board of Solvay Business School and Antai </span><span style="color:rgb(34, 34, 34)">College of Economics and Management, Shanghai Jiao Tong University. He is also a member </span><span style="color:rgb(34, 34, 34)">of the International Advisory Council of Universitat Pompeu Fabra - Barcelona School of </span><span style="color:rgb(34, 34, 34)">Management and he is honorary member of the board of France Digitale.</span></p>\n
\n
<p><span style="color:rgb(34, 34, 34)">Professor Vinzi serves as a member of the EQUIS and AACSB peer review teams and he is </span><span style="color:rgb(34, 34, 34)">chair of the AACSB European Advisory Council. Since July 1, 2024 he has been serving a </span><span style="color:rgb(34, 34, 34)">one-year term on the Business Accreditation Policy Committee (BAPC) of the AACSB.</span></p>\n
\n
<p><span style="color:rgb(34, 34, 34)">He is also a member of the OECD Business for Inclusive Growth (B4IG) partnership. Finally, </span><span style="color:rgb(34, 34, 34)">he is president of the Diversity Commission of the CGE and of Concours Sésame, a </span><span style="color:rgb(34, 34, 34)">competitive entrance exam for French business school undergraduate programs, as well as </span><span style="color:rgb(34, 34, 34)">acting President of the CDEFM (Conference of Directors of French Business Schools).</span></p>\n
"""
]
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"industrrySectors" => array:2 [
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"en" => "Telecommunication Services - Hospitality and Tourism Services - Agricultural and Food Products"
]
"researchFields" => array:2 [
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"distinctions" => array:8 [
0 => Essec\Faculty\Model\Distinction {#2383
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1 => Essec\Faculty\Model\Distinction {#2384
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#_id: null
#_source: array:6 [
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"fr" => "Highly Commended Award Winner au Literati Network Awards for Excellence 2012, pour l'article (avec Guy Assaker) intitulé, “Modeling a Causality Network for Tourism Development: An Empirical Analysis” publié dans Journal of Modelling in Management."
"en" => "Literati Network Award for Excellence 2012: Highly Commended Award, for the article “Modeling a Causality Network for Tourism Development: An Empirical Analysis,” Journal of Modelling in Management (co-authored with Guy Assaker)"
]
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}
2 => Essec\Faculty\Model\Distinction {#2385
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#_id: null
#_source: array:6 [
"date" => "2005-06-07"
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"fr" => "Lauréat du prix de l'enseignement "Pierre Vernimmen-BNP Paris Teaching Awards" 2005 à HEC School of Management pour la qualité de la relation pédagogique avec les élèves ( programmes MBA et Doctorants), la méthode d'enseignement, la maîtrise des sujets enseignés, des qualités innovatives de leurs cours et de la qualités des outils d'enseignement utilisés"
"en" => "Winner of the "Pierre Vernimmen-BNP Paris Teaching Awards" 2005 at the HEC School of Management for the quality of the pedagogical relationships with students (MBA and Doctoral programmes), the teaching method, the mastery of the taught subjects, the innovative features of the course and the quality of the used teaching tools"
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+"parent": Essec\Faculty\Model\Profile {#2233}
}
3 => Essec\Faculty\Model\Distinction {#2386
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#_id: null
#_source: array:6 [
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"fr" => "Honoré lors de la cérémonie des prix de l'enseignement "Pierre Vernimmen-BNP Paris" 2001 à HEC School of Management"
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]
]
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}
4 => Essec\Faculty\Model\Distinction {#2387
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#_id: null
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"fr" => "Prix de l'Article le plus cité 2005-2010. Computational Statistics and Data Analysis. PLS Path Modeling, Elsevier"
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5 => Essec\Faculty\Model\Distinction {#2388
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#_id: null
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"fr" => "Prix ISOSS (Islamic Society of Statistical Sciences) en reconnaissance de sa contribution au développement des sciences statistiques"
"en" => "Decorated with the ISOSS (Islamic Society of Statistical Sciences) Award in recognition of his contribution to the development of statistical sciences"
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]
]
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}
6 => Essec\Faculty\Model\Distinction {#2389
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"fr" => "Article le plus cité (2005-2010) publié dans la revue “Computational Statistics and Data Analysis”: PLS Generalised Linear Regression, Elsevier"
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7 => Essec\Faculty\Model\Distinction {#2390
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#_id: null
#_source: array:6 [
"date" => "2014-05-28"
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"fr" => "Mention honorable, 8th International Conference on Partial Least Squares and Related Methods, pour son article "Quantile PLS Path Modeling" (avec C. Davino)."
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]
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0 => Essec\Faculty\Model\TeachingItem {#2371
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}
1 => Essec\Faculty\Model\TeachingItem {#2320
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"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "Università degli Studi di Cagliari"
"en" => "Università degli Studi di Cagliari"
]
"country" => array:2 [
"fr" => "Italie"
"en" => "Italy"
]
]
+lang: "fr"
}
2 => Essec\Faculty\Model\TeachingItem {#2321
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2014"
"endDate" => "2014"
"program" => null
"label" => array:2 [
"fr" => ""Component-based Path Modeling", Tutoriel pour une audience expérimentée à la 7ème Conférence Internationale du ERCIM Working Group on Computational and Methodological Statistics"
"en" => ""Component-based Path Modeling", Tutorial for specialized audience at the 7th International Conference of the ERCIM Working Group on Computational and Methodological Statistics"Component-based Path Modeling", Tutoriel pour une audience expérimentée à la 7ème Conférence Internationale du ERCIM Working Group on Computational and Methodological Statistics"
]
"type" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "European Research Consortium for Informatics and Mathematics (ERCIM)"
"en" => "European Research Consortium for Informatics and Mathematics (ERCIM)"
]
"country" => array:2 [
"fr" => "France"
"en" => "France"
]
]
+lang: "fr"
}
3 => Essec\Faculty\Model\TeachingItem {#2370
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2007"
"endDate" => "2014"
"program" => null
"label" => array:2 [
"fr" => "Four essays on novel heuristic algorithms in data mining with applications in healthcare analytics"
"en" => "Four essays on novel heuristic algorithms in data mining with applications in healthcare analytics"
]
"type" => array:2 [
"fr" => "Directeur de thèse"
"en" => "Thesis director"
]
"institution" => array:2 [
"fr" => "ESSEC Business School"
"en" => "ESSEC Business School"
]
"country" => array:2 [
"fr" => "France"
"en" => "France"
]
]
+lang: "fr"
}
4 => Essec\Faculty\Model\TeachingItem {#2322
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2012"
"endDate" => "2012"
"program" => null
"label" => array:2 [
"fr" => ""PLS Path Modeling and PLS Regression", Pré-Conférence, PLS 2012 Doctoral Workshop"
"en" => ""PLS Path Modeling and PLS Regression", Pre-Conference PLS 2012 Doctoral Workshop"
]
"type" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "The Sensometric Society"
"en" => "The Sensometric Society"
]
"country" => array:2 [
"fr" => "États-Unis"
"en" => "United States of America"
]
]
+lang: "fr"
}
5 => Essec\Faculty\Model\TeachingItem {#2327
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2012"
"endDate" => "2012"
"program" => null
"label" => array:2 [
"fr" => ""A 3-day Course on PLS Path Modeling: Basic Concepts and Foundations, Advances and Applications". Cours de Formation pour des Chercheurs et Cadres"
"en" => ""A 3-day Course on PLS Path Modeling: Basic Concepts and Foundations, Advances and Applications". Training course for Researchers and Executives"
]
"type" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "Association for Information Systems (AIS)"
"en" => "Association for Information Systems (AIS)"
]
"country" => array:2 [
"fr" => "États-Unis"
"en" => "United States of America"
]
]
+lang: "fr"
}
6 => Essec\Faculty\Model\TeachingItem {#2323
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2011"
"endDate" => "2011"
"program" => null
"label" => array:2 [
"fr" => ""PLS Predictive Path Models with applications to Customer Satisfaction Measurement and Sensory Data Analysis", ISBIS Sardegna International Statistics Summer School"
"en" => ""PLS Predictive Path Models with applications to Customer Satisfaction Measurement and Sensory Data Analysis", ISBIS Sardegna International Statistics Summer School"
]
"type" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "Università degli Studi di Cagliari"
"en" => "Università degli Studi di Cagliari"
]
"country" => array:2 [
"fr" => "Italie"
"en" => "Italy"
]
]
+lang: "fr"
}
7 => Essec\Faculty\Model\TeachingItem {#2324
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2011"
"endDate" => "2011"
"program" => null
"label" => array:2 [
"fr" => ""Statistical Soft Modeling for Measuring Customer Satisfaction via Composite Indicators", Post-graduate course"
"en" => ""Statistical Soft Modeling for Measuring Customer Satisfaction via Composite Indicators", Post-graduate course"
]
"type" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "Università degli Studi di Cagliari"
"en" => "Università degli Studi di Cagliari"
]
"country" => array:2 [
"fr" => "Italie"
"en" => "Italy"
]
]
+lang: "fr"
}
8 => Essec\Faculty\Model\TeachingItem {#2375
#_index: null
#_id: null
#_source: array:7 [
"startDate" => null
"endDate" => "2010"
"program" => null
"label" => array:2 [
"fr" => "Four Essays on the Interface between Marketing and Operations in Supply Chain Management"
"en" => "Four Essays on the Interface between Marketing and Operations in Supply Chain Management"
]
"type" => array:2 [
"fr" => "Membre de jury"
"en" => "Thesis jury member"
]
"institution" => array:2 [
"fr" => "ESSEC Business School"
"en" => "ESSEC Business School"
]
"country" => array:2 [
"fr" => "France"
"en" => "France"
]
]
+lang: "fr"
}
9 => Essec\Faculty\Model\TeachingItem {#2325
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2010"
"endDate" => "2010"
"program" => null
"label" => array:2 [
"fr" => ""PLS Path Modeling with XLSTAT-PLSPM", Atelier Pré-Conférence Sensometrics'10"
"en" => ""PLS Path Modeling with XLSTAT-PLSPM", Pre-Conference Sensometrics'10 Workshop"
]
"type" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "The Sensometric Society"
"en" => "The Sensometric Society"
]
"country" => array:2 [
"fr" => "Pays-Bas"
"en" => "Netherlands"
]
]
+lang: "fr"
}
10 => Essec\Faculty\Model\TeachingItem {#2329
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2008"
"endDate" => "2010"
"program" => null
"label" => array:2 [
"fr" => "“Regression and Analysis of Variance” – Cours de formation pour les cadres juniors et seniors de EUROSTAT (Statistical Office of the European Union)"
"en" => "“Regression and Analysis of Variance” – Training course for the EUROSTAT (Statistical Office of the European Union) junior and senior executives"
]
"type" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "Eurostat"
"en" => "Eurostat"
]
"country" => array:2 [
"fr" => "Luxembourg"
"en" => "Luxembourg"
]
]
+lang: "fr"
}
11 => Essec\Faculty\Model\TeachingItem {#2328
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2008"
"endDate" => "2010"
"program" => null
"label" => array:2 [
"fr" => "“Factor Analysis and Classification” – Cours de formation pour les cadres juniors et seniors de EUROSTAT (Statistical Office of the European Union)"
"en" => "“Factor Analysis and Classification” – Training course for the EUROSTAT (Statistical Office of the European Union) junior and senior executives"
]
"type" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "Eurostat"
"en" => "Eurostat"
]
"country" => array:2 [
"fr" => "Luxembourg"
"en" => "Luxembourg"
]
]
+lang: "fr"
}
12 => Essec\Faculty\Model\TeachingItem {#2369
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2006"
"endDate" => "2010"
"program" => null
"label" => array:2 [
"fr" => "Insights into tourism demand and tourism behavior: four papers using multiple perspectives and structural equation modeling"
"en" => "Insights into tourism demand and tourism behavior: four papers using multiple perspectives and structural equation modeling"
]
"type" => array:2 [
"fr" => "Directeur de thèse"
"en" => "Thesis director"
]
"institution" => array:2 [
"fr" => "ESSEC Business School"
"en" => "ESSEC Business School"
]
"country" => array:2 [
"fr" => "France"
"en" => "France"
]
]
+lang: "fr"
}
13 => Essec\Faculty\Model\TeachingItem {#2330
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2009"
"endDate" => "2009"
"program" => null
"label" => array:2 [
"fr" => ""A Joint Partial Least Squares Component-based Approach to Structural Equation Modeling and Multi-block Data Analysis" - Institut de Recherche Mathématique Avancée, Université de Strasbourg"
"en" => ""A Joint Partial Least Squares Component-based Approach to Structural Equation Modeling and Multi-block Data Analysis" - Institut de Recherche Mathématique Avancée, Université de Strasbourg"
]
"type" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "Université Strasbourg I"
"en" => "Université Strasbourg I"
]
"country" => array:2 [
"fr" => "France"
"en" => "France"
]
]
+lang: "fr"
}
14 => Essec\Faculty\Model\TeachingItem {#2374
#_index: null
#_id: null
#_source: array:7 [
"startDate" => null
"endDate" => "2009"
"program" => null
"label" => array:2 [
"fr" => "PATHMOX Approach: Segmentation Trees in Partial Least Squares Path Modeling"
"en" => "PATHMOX Approach: Segmentation Trees in Partial Least Squares Path Modeling"
]
"type" => array:2 [
"fr" => "Rapporteur"
"en" => "Thesis referee"
]
"institution" => array:2 [
"fr" => "Universitat Politècnica de Catalunya"
"en" => "Universitat Politècnica de Catalunya"
]
"country" => array:2 [
"fr" => "Espagne"
"en" => "Spain"
]
]
+lang: "fr"
}
15 => Essec\Faculty\Model\TeachingItem {#2326
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2009"
"endDate" => "2009"
"program" => null
"label" => array:2 [
"fr" => ""A 3-day Course on PLS Path Modeling: Basic Concepts and Foundations, Advances and Applications".Cours de Formation pour des Chercheurs et Cadres"
"en" => ""A 3-day Course on PLS Path Modeling: Basic Concepts and Foundations, Advances and Applications". Training course for Researchers and Executives"
]
"type" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "Addinsoft"
"en" => "Addinsoft"
]
"country" => array:2 [
"fr" => "France"
"en" => "France"
]
]
+lang: "fr"
}
16 => Essec\Faculty\Model\TeachingItem {#2336
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2009"
"endDate" => "2009"
"program" => null
"label" => array:2 [
"fr" => "“Component-based Structural Equation Models: the PLS Path Modelling Approach”"
"en" => "“Component-based Structural Equation Models: the PLS Path Modelling Approach”"
]
"type" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "Sorbonne Université"
"en" => "Sorbonne Université"
]
"country" => array:2 [
"fr" => "France"
"en" => "France"
]
]
+lang: "fr"
}
17 => Essec\Faculty\Model\TeachingItem {#2331
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2009"
"endDate" => "2009"
"program" => null
"label" => array:2 [
"fr" => ""PLS Path Modeling: A Comprehensive Course""
"en" => ""PLS Path Modeling: A Comprehensive Course""
]
"type" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "Lillehammer University College"
"en" => "Lillehammer University College"
]
"country" => array:2 [
"fr" => "Norvège"
"en" => "Norway"
]
]
+lang: "fr"
}
18 => Essec\Faculty\Model\TeachingItem {#2332
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2009"
"endDate" => "2009"
"program" => null
"label" => array:2 [
"fr" => ""PLS Path Modeling: Methodological Foundations, Recent Developments and Software Applications" - Tutoriel à 6th International Conference on Partial Least Squares and Related Methods"
"en" => ""PLS Path Modeling: Methodological Foundations, Recent Developments and Software Applications" - Tutorial at the 6th International Conference on Partial Least Squares and Related Methods"
]
"type" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "Peking University"
"en" => "Peking University"
]
"country" => array:2 [
"fr" => "Chine"
"en" => "China"
]
]
+lang: "fr"
}
19 => Essec\Faculty\Model\TeachingItem {#2333
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2009"
"endDate" => "2009"
"program" => null
"label" => array:2 [
"fr" => "“PLS Path Modeling for Consumer Analysis: estimation algorithm, assessment tools and applications with XLSTAT-PLSPM software” Summer School de la Italian Statistical Society (SIS) sur PLS Methods for Structured Data Tables in Consumer Analysis"
"en" => "“PLS Path Modeling for Consumer Analysis: estimation algorithm, assessment tools and applications with XLSTAT-PLSPM software” Summer School of the Italian Statistical Society (SIS) on PLS Methods for Structured Data Tables in Consumer Analysis"
]
"type" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "Università di Macerata"
"en" => "Università di Macerata"
]
"country" => array:2 [
"fr" => "Italie"
"en" => "Italy"
]
]
+lang: "fr"
}
20 => Essec\Faculty\Model\TeachingItem {#2335
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#_id: null
#_source: array:7 [
"startDate" => "2009"
"endDate" => "2009"
"program" => null
"label" => array:2 [
"fr" => "“A Comprehensive PLS-based Environment to Structural Equation Modeling”"
"en" => "“A Comprehensive PLS-based Environment to Structural Equation Modeling”"
]
"type" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "Conservatoire National des Arts & Métiers (CNAM)"
"en" => "Conservatoire National des Arts & Métiers (CNAM)"
]
"country" => array:2 [
"fr" => "France"
"en" => "France"
]
]
+lang: "fr"
}
21 => Essec\Faculty\Model\TeachingItem {#2334
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2009"
"endDate" => "2009"
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"label" => array:2 [
"fr" => "“The PLS Path Modeling approach to Structural Equation Modeling: Methodological Foundations, Recent Decelopments and Software Applications” Tutoriel à la 11th Conference of the International Federation of Classification Societies (IFCS)"
"en" => "“The PLS Path Modeling approach to Structural Equation Modeling: Methodological Foundations, Recent Decelopments and Software Applications” Tutorial at the 11th Conference of the International Federation of Classification Societies (IFCS)"
]
"type" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "International Federation of Classification Societies (IFCS)"
"en" => "International Federation of Classification Societies (IFCS)"
]
"country" => array:2 [
"fr" => "Allemagne"
"en" => "Germany"
]
]
+lang: "fr"
}
22 => Essec\Faculty\Model\TeachingItem {#2337
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2008"
"endDate" => "2008"
"program" => null
"label" => array:2 [
"fr" => ""A Comprehensive PLS Environment to Structural Equation Modeling""
"en" => ""A Comprehensive PLS Environment to Structural Equation Modeling""
]
"type" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "Università di Napoli Federico II"
"en" => "Università di Napoli Federico II"
]
"country" => array:2 [
"fr" => "Italie"
"en" => "Italy"
]
]
+lang: "fr"
}
23 => Essec\Faculty\Model\TeachingItem {#2373
#_index: null
#_id: null
#_source: array:7 [
"startDate" => null
"endDate" => "2008"
"program" => null
"label" => array:2 [
"fr" => "Unobserved Heterogeneity in Structural Equation Models: a new approach to latent class detection in PLS Path Modeling"
"en" => "Unobserved Heterogeneity in Structural Equation Models: a new approach to latent class detection in PLS Path Modeling"
]
"type" => array:2 [
"fr" => "Directeur de thèse"
"en" => "Thesis director"
]
"institution" => array:2 [
"fr" => "Università di Napoli Federico II"
"en" => "Università di Napoli Federico II"
]
"country" => array:2 [
"fr" => "Italie"
"en" => "Italy"
]
]
+lang: "fr"
}
24 => Essec\Faculty\Model\TeachingItem {#2342
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2008"
"endDate" => "2008"
"program" => null
"label" => array:2 [
"fr" => "“Introduction to Categorical Data Analysis: Chi-square test of independence for cross-tabs, binary correspondence analysis for the association between two categorical variables, multiple correspondence analysis for the analysis of survey data” – Cours de formation pour les cadres juniors et seniors de EUROSTAT (Statistical Office of the European Union)"
"en" => "“Introduction to Categorical Data Analysis: Chi-square test of independence for cross-tabs, binary correspondence analysis for the association between two categorical variables, multiple correspondence analysis for the analysis of survey data” – Training course for the EUROSTAT (Statistical Office of the European Union) junior and senior executives"
]
"type" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "Eurostat"
"en" => "Eurostat"
]
"country" => array:2 [
"fr" => "Luxembourg"
"en" => "Luxembourg"
]
]
+lang: "fr"
}
25 => Essec\Faculty\Model\TeachingItem {#2344
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2008"
"endDate" => "2008"
"program" => null
"label" => array:2 [
"fr" => "“Path Analysis, Confirmatory Factor Analysis and Structural Equation Modelling”"
"en" => "“Path Analysis, Confirmatory Factor Analysis and Structural Equation Modelling”"
]
"type" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "Sorbonne Université"
"en" => "Sorbonne Université"
]
"country" => array:2 [
"fr" => "France"
"en" => "France"
]
]
+lang: "fr"
}
26 => Essec\Faculty\Model\TeachingItem {#2343
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2008"
"endDate" => "2008"
"program" => null
"label" => array:2 [
"fr" => "“Statistical Modelling for Measuring Customer Satisfaction”"
"en" => "“Statistical Modelling for Measuring Customer Satisfaction”"
]
"type" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "Università degli Studi di Cagliari"
"en" => "Università degli Studi di Cagliari"
]
"country" => array:2 [
"fr" => "Italie"
"en" => "Italy"
]
]
+lang: "fr"
}
27 => Essec\Faculty\Model\TeachingItem {#2341
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2008"
"endDate" => "2008"
"program" => null
"label" => array:2 [
"fr" => "“Component-based Structural Equation Models” – Journées d'Etudes en Statistique (JES) de la Société Française de Statistique (SFdS)"
"en" => "“Component-based Structural Equation Models” – Journées d'Etudes en Statistique (JES) of the Société Française de Statistique (SFdS)"
]
"type" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "Société Française de Statistique (SFdS)"
"en" => "Société Française de Statistique (SFdS)"
]
"country" => array:2 [
"fr" => "France"
"en" => "France"
]
]
+lang: "fr"
}
28 => Essec\Faculty\Model\TeachingItem {#2340
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2008"
"endDate" => "2008"
"program" => null
"label" => array:2 [
"fr" => "“Local Model in Component-based SEM” – Journées d'Etudes en Statistique (JES) de la Société Française de Statistique (SFdS)"
"en" => "“Local Model in Component-based SEM” – Journées d'Etudes en Statistique (JES) of the Société Française de Statistique (SFdS)"
]
"type" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "Société Française de Statistique (SFdS)"
"en" => "Société Française de Statistique (SFdS)"
]
"country" => array:2 [
"fr" => "France"
"en" => "France"
]
]
+lang: "fr"
}
29 => Essec\Faculty\Model\TeachingItem {#2339
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2008"
"endDate" => "2008"
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"label" => array:2 [
"fr" => ""Model assessment and multi-group comparison in PLS Path Modeling: methodological foundations and the XLSTAT-PLSPM software""
"en" => ""Model assessment and multi-group comparison in PLS Path Modeling: methodological foundations and the XLSTAT-PLSPM software""
]
"type" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "Università di Napoli Federico II"
"en" => "Università di Napoli Federico II"
]
"country" => array:2 [
"fr" => "Italie"
"en" => "Italy"
]
]
+lang: "fr"
}
30 => Essec\Faculty\Model\TeachingItem {#2338
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2008"
"endDate" => "2008"
"program" => null
"label" => array:2 [
"fr" => ""Detection and Assessment of Local Models in PLS Path Modeling""
"en" => ""Detection and Assessment of Local Models in PLS Path Modeling""
]
"type" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "Università di Napoli Federico II"
"en" => "Università di Napoli Federico II"
]
"country" => array:2 [
"fr" => "Italie"
"en" => "Italy"
]
]
+lang: "fr"
}
31 => Essec\Faculty\Model\TeachingItem {#2346
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2007"
"endDate" => "2007"
"program" => null
"label" => array:2 [
"fr" => "“PLS Path Modeling for Causal Networks: Recent Contributions with Applications to Customer Satisfaction Surveys and Sensory Data Analysis”– Séminaire de Recherche, Département Marketing, à HEC Paris"
"en" => "“PLS Path Modeling for Causal Networks: Recent Contributions with Applications to Customer Satisfaction Surveys and Sensory Data Analysis”– Research Seminar – Marketing Department at the HEC School of Management,"
]
"type" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "HEC Paris"
"en" => "HEC Paris"
]
"country" => array:2 [
"fr" => "France"
"en" => "France"
]
]
+lang: "fr"
}
32 => Essec\Faculty\Model\TeachingItem {#2347
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2007"
"endDate" => "2007"
"program" => null
"label" => array:2 [
"fr" => "“Recent Contributions to PLS (Partial Least Squares) Regression and Path Modeling for the Analysis of Dependence Relationships, Causal Networks and Multiple Tables”– Séminaire de Recherche"
"en" => "“Recent Contributions to PLS (Partial Least Squares) Regression and Path Modeling for the Analysis of Dependence Relationships, Causal Networks and Multiple Tables”– Research Seminar"
]
"type" => array:2 [
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"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "HEC Paris"
"en" => "HEC Paris"
]
"country" => array:2 [
"fr" => "France"
"en" => "France"
]
]
+lang: "fr"
}
33 => Essec\Faculty\Model\TeachingItem {#2372
#_index: null
#_id: null
#_source: array:7 [
"startDate" => null
"endDate" => "2007"
"program" => null
"label" => array:2 [
"fr" => "Contribution aux modèles d'équations tructurelles à variables latentes"
"en" => "Contribution aux modèles d'équations tructurelles à variables latentes"
]
"type" => array:2 [
"fr" => "Rapporteur"
"en" => "Thesis referee"
]
"institution" => array:2 [
"fr" => "Conservatoire National des Arts & Métiers (CNAM)"
"en" => "Conservatoire National des Arts & Métiers (CNAM)"
]
"country" => array:2 [
"fr" => "France"
"en" => "France"
]
]
+lang: "fr"
}
34 => Essec\Faculty\Model\TeachingItem {#2345
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2007"
"endDate" => "2007"
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"label" => array:2 [
"fr" => "“PLS (Partial Least Squares) Path Modeling” – 11ème Cours du programme ECAS (European Courses in Advanced Statistics) sur le thème: “Structural Equation Models”"
"en" => "“PLS (Partial Least Squares) Path Modeling” – 11th Course in the ECAS (European Courses in Advanced Statistics) Program on the theme: “Structural Equation Models”"
]
"type" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "Université Grenoble Alpes"
"en" => "Université Grenoble Alpes"
]
"country" => array:2 [
"fr" => "France"
"en" => "France"
]
]
+lang: "fr"
}
35 => Essec\Faculty\Model\TeachingItem {#2348
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2001"
"endDate" => "2006"
"program" => null
"label" => array:2 [
"fr" => "“PLS Methods: from regression to structural equation models” – course pour le "Master in Quantitative Methods for the Social Research and the Market Analysis" de University of Naples “Federico II”"
"en" => "“PLS Methods: from regression to structural equation models” – course for the Master in Quantitative Methods for the Social Research and the Market Analysis of the University of Naples “Federico II”"
]
"type" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "Università di Napoli Federico II"
"en" => "Università di Napoli Federico II"
]
"country" => array:2 [
"fr" => "Italie"
"en" => "Italy"
]
]
+lang: "fr"
}
36 => Essec\Faculty\Model\TeachingItem {#2349
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2005"
"endDate" => "2005"
"program" => null
"label" => array:2 [
"fr" => "“The Classical (ML) and the Partial Least Squares Approaches to Study Causality Relationships by Structural Equation Modeling”– Séminaire de Finance Quantitative"
"en" => "“The Classical (ML) and the Partial Least Squares Approaches to Study Causality Relationships by Structural Equation Modeling”– Quantitative Finance Seminar"
]
"type" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "Humboldt-Universität zu Berlin"
"en" => "Humboldt-Universität zu Berlin"
]
"country" => array:2 [
"fr" => "Allemagne"
"en" => "Germany"
]
]
+lang: "fr"
}
37 => Essec\Faculty\Model\TeachingItem {#2350
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2005"
"endDate" => "2005"
"program" => null
"label" => array:2 [
"fr" => "“The Classical Approach (SEM-ML) to the Study of Causality by Modeling Structural Relationships between Latent Variables”– Atelier Statistique de la Société Française de Statistique “Modèles structurels et applications”"
"en" => "“The Classical Approach (SEM-ML) to the Study of Causality by Modeling Structural Relationships between Latent Variables”– Statistics Workshop of the Société Française de Statistique “Modèles structurels et applications”"
]
"type" => array:2 [
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"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "Société Française de Statistique (SFdS)"
"en" => "Société Française de Statistique (SFdS)"
]
"country" => array:2 [
"fr" => "France"
"en" => "France"
]
]
+lang: "fr"
}
38 => Essec\Faculty\Model\TeachingItem {#2351
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2005"
"endDate" => "2005"
"program" => null
"label" => array:2 [
"fr" => "“The PLS approach to the analysis of latent variables: regression techniques (PLS1, PLS2), analysis of disjoint matrices (L-PLS, U-PLS)and multiblock analysis by means of causal networks (PLS-PM, Domino PLS)” – Course on “Sensory Evaluation of Food Products: test planning and data analysis” Italian Society of Sensory Sciences"
"en" => "“The PLS approach to the analysis of latent variables: regression techniques (PLS1, PLS2), analysis of disjoint matrices (L-PLS, U-PLS)and multiblock analysis by means of causal networks (PLS-PM, Domino PLS)” – Course on “Sensory Evaluation of Food Products: test planning and data analysis” Italian Society of Sensory Sciences"
]
"type" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "Italian Sensory Sciences Society (SISS)"
"en" => "Italian Sensory Sciences Society (SISS)"
]
"country" => array:2 [
"fr" => "Italie"
"en" => "Italy"
]
]
+lang: "fr"
}
39 => Essec\Faculty\Model\TeachingItem {#2352
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2004"
"endDate" => "2004"
"program" => null
"label" => array:2 [
"fr" => "Use of PLS Graph for the European Customer Satisfaction Index – PLS Summer School, Technical University of Berlin"
"en" => "Use of PLS Graph for the European Customer Satisfaction Index – PLS Summer School, Technical University of Berlin"
]
"type" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "Technische Universität Berlin"
"en" => "Technische Universität Berlin"
]
"country" => array:2 [
"fr" => "Allemagne"
"en" => "Germany"
]
]
+lang: "fr"
}
40 => Essec\Faculty\Model\TeachingItem {#2353
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2004"
"endDate" => "2004"
"program" => null
"label" => array:2 [
"fr" => "PLS Model Evaluation and Comparisons with LISREL – PLS Summer School, Technical University of Berlin"
"en" => "PLS Model Evaluation and Comparisons with LISREL – PLS Summer School, Technical University of Berlin"
]
"type" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "Technische Universität Berlin"
"en" => "Technische Universität Berlin"
]
"country" => array:2 [
"fr" => "Allemagne"
"en" => "Germany"
]
]
+lang: "fr"
}
41 => Essec\Faculty\Model\TeachingItem {#2354
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#_id: null
#_source: array:7 [
"startDate" => "2004"
"endDate" => "2004"
"program" => null
"label" => array:2 [
"fr" => "A Modeling Approach for measuring Customer Satisfaction – Cours de Statistiques à la Faculté de Sciences Politiques, University of Macerata"
"en" => "A Modeling Approach for measuring Customer Satisfaction – Statistics course at the Faculty of Political Sciences, University of Macerata"
]
"type" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "Università di Macerata"
"en" => "Università di Macerata"
]
"country" => array:2 [
"fr" => "Italie"
"en" => "Italy"
]
]
+lang: "fr"
}
42 => Essec\Faculty\Model\TeachingItem {#2357
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2003"
"endDate" => "2003"
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"label" => array:2 [
"fr" => "PLS (Partial Least Squares) methods: from regression to structural equations models – Master in Quantitative Methods for Social Research and Market Analysis , Department of Mathematics and Statistics"
"en" => "PLS (Partial Least Squares) methods: from regression to structural equations models – Master in Quantitative Methods for Social Research and Market Analysis , Department of Mathematics and Statistics"
]
"type" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "Università di Napoli Federico II"
"en" => "Università di Napoli Federico II"
]
"country" => array:2 [
"fr" => "Italie"
"en" => "Italy"
]
]
+lang: "fr"
}
43 => Essec\Faculty\Model\TeachingItem {#2355
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#_id: null
#_source: array:7 [
"startDate" => "2003"
"endDate" => "2003"
"program" => null
"label" => array:2 [
"fr" => "PLS (Partial Least Squares) Path Modeling: Methodological Innovations, the use of PLS-SPAD software and applications to the Customer Satisfaction Index – (avec Y.M. Chatelin) Tutoriel à PLS and Related Methods – Focus on Customers Conference (Lisbonne, 16 Septembre 2003)."
"en" => "PLS (Partial Least Squares) Path Modeling: Methodological Innovations, the use of PLS-SPAD software and applications to the Customer Satisfaction Index – (with Y.M. Chatelin) Tutorial at the PLS and Related Methods – Focus on Customers Conference (Lisbon, September, 16th 2003)."
]
"type" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "International Conference on Partial Least Squares and Related Methods"
"en" => "International Conference on Partial Least Squares and Related Methods"
]
"country" => array:2 [
"fr" => "Portugal"
"en" => "Portugal"
]
]
+lang: "fr"
}
44 => Essec\Faculty\Model\TeachingItem {#2356
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2003"
"endDate" => "2003"
"program" => null
"label" => array:2 [
"fr" => "Latent Variables Soft Modeling (PLS) – séries de cours à l'IASC-IFCS Joint International Summer School on Classification and Data Mining in Business, Industry and Applied Research: Methodological and Computational Issues"
"en" => "Latent Variables Soft Modeling (PLS) – series of lectures at the IASC-IFCS Joint International Summer School on Classification and Data Mining in Business, Industry and Applied Research: Methodological and Computational Issues"
]
"type" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "International Association for Statistical Computing (IASC)"
"en" => "International Association for Statistical Computing (IASC)"
]
"country" => array:2 [
"fr" => "Portugal"
"en" => "Portugal"
]
]
+lang: "fr"
}
45 => Essec\Faculty\Model\TeachingItem {#2358
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2003"
"endDate" => "2003"
"program" => null
"label" => array:2 [
"fr" => "The LISREL and the PLS approach to Structural Equation Modeling – serie de séminaires pour le Doctorat en Statistiques et le Doctorat en Informatique de Universitat Politecnica de Catalunya"
"en" => "The LISREL and the PLS approach to Structural Equation Modeling – series of seminars at the Doctorate in Statistics and the Doctorate in Informatics of the Universitat Politecnica de Catalunya"
]
"type" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "Universitat Politècnica de Catalunya"
"en" => "Universitat Politècnica de Catalunya"
]
"country" => array:2 [
"fr" => "Espagne"
"en" => "Spain"
]
]
+lang: "fr"
}
46 => Essec\Faculty\Model\TeachingItem {#2359
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2001"
"endDate" => "2001"
"program" => null
"label" => array:2 [
"fr" => "LISREL and PLS Path Modeling – series of lectures at the IASC-IASS Joint International Summer School on Knowledge Discovery & Large Surveys Design and Analysis"
"en" => "LISREL and PLS Path Modeling – series of lectures at the IASC-IASS Joint International Summer School on Knowledge Discovery & Large Surveys Design and Analysis"
]
"type" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "International Association for Statistical Computing (IASC)"
"en" => "International Association for Statistical Computing (IASC)"
]
"country" => array:2 [
"fr" => "Italie"
"en" => "Italy"
]
]
+lang: "fr"
}
47 => Essec\Faculty\Model\TeachingItem {#2360
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2001"
"endDate" => "2001"
"program" => null
"label" => array:2 [
"fr" => "Explanatory Analyses – Module du cours sur l'analyse de données multidimensionnelle pour le Master en Marketing, LUISS Management University"
"en" => "Explanatory Analyses – module of the course on Multidimensional Data Analysis for the Master in Marketing of the LUISS Management University"
]
"type" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "Luiss University"
"en" => "Luiss University"
]
"country" => array:2 [
"fr" => "Italie"
"en" => "Italy"
]
]
+lang: "fr"
}
48 => Essec\Faculty\Model\TeachingItem {#2361
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2000"
"endDate" => "2000"
"program" => null
"label" => array:2 [
"fr" => "The analysis of complex systems in Epidemiology and Biomedicine –Cours pour la Post-Graduate School on Biostatistics for Clinical and Epidemiological Research by the Faculty of Medicine of the University of Naples Federico II"
"en" => "The analysis of complex systems in Epidemiology and Biomedicine – course in the Post-Graduate School on Biostatistics for Clinical and Epidemiological Research by the Faculty of Medicine of the University of Naples Federico II"
]
"type" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "Università di Napoli Federico II"
"en" => "Università di Napoli Federico II"
]
"country" => array:2 [
"fr" => "Italie"
"en" => "Italy"
]
]
+lang: "fr"
}
49 => Essec\Faculty\Model\TeachingItem {#2364
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#_id: null
#_source: array:7 [
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"endDate" => "2000"
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"label" => array:2 [
"fr" => "Analysts of Scenarios on International Markets (post-graduate course). Module Statistiques"
"en" => "Analysts of Scenarios on International Markets (post-graduate course). Statistics module"
]
"type" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
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"en" => "Università di Napoli Federico II"
]
"country" => array:2 [
"fr" => "Italie"
"en" => "Italy"
]
]
+lang: "fr"
}
50 => Essec\Faculty\Model\TeachingItem {#2362
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "1999"
"endDate" => "1999"
"program" => null
"label" => array:2 [
"fr" => "Multivariate Statistical Analyses for Total Quality Measurement – séries de cours à la V International Summer School in Computational Statistics organisé par IASC sur le thème: 3rd Millenium Challenge for Industrial Statistics"
"en" => "Multivariate Statistical Analyses for Total Quality Measurement – series of lectures at the V International Summer School in Computational Statistics organised by IASC on the theme: 3rd Millenium Challenge for Industrial Statistics"
]
"type" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "International Association for Statistical Computing (IASC)"
"en" => "International Association for Statistical Computing (IASC)"
]
"country" => array:2 [
"fr" => "Grèce"
"en" => "Greece"
]
]
+lang: "fr"
}
51 => Essec\Faculty\Model\TeachingItem {#2365
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "1998"
"endDate" => "1998"
"program" => null
"label" => array:2 [
"fr" => "Experts of Tourism Marketing (post-graduate course). Module Statistiques"
"en" => "Experts of Tourism Marketing (post-graduate course). Statistics module"
]
"type" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "Università di Napoli Federico II"
"en" => "Università di Napoli Federico II"
]
"country" => array:2 [
"fr" => "Italie"
"en" => "Italy"
]
]
+lang: "fr"
}
52 => Essec\Faculty\Model\TeachingItem {#2366
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "1998"
"endDate" => "1998"
"program" => null
"label" => array:2 [
"fr" => "Experts of Typical Food Products Marketing (post-graduate course). Module Statistiques"
"en" => "Experts of Typical Food Products Marketing (post-graduate course). Statistics module"
]
"type" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "Università di Napoli Federico II"
"en" => "Università di Napoli Federico II"
]
"country" => array:2 [
"fr" => "Italie"
"en" => "Italy"
]
]
+lang: "fr"
}
53 => Essec\Faculty\Model\TeachingItem {#2367
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "1997"
"endDate" => "1997"
"program" => null
"label" => array:2 [
"fr" => "Experts in Quality Management for Small Enterprises (post-graduate course). Module Statistiques"
"en" => "Experts in Quality Management for Small Enterprises (post-graduate course). Statistics module"
]
"type" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "Università di Napoli Federico II"
"en" => "Università di Napoli Federico II"
]
"country" => array:2 [
"fr" => "Italie"
"en" => "Italy"
]
]
+lang: "fr"
}
54 => Essec\Faculty\Model\TeachingItem {#2368
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "1997"
"endDate" => "1997"
"program" => null
"label" => array:2 [
"fr" => "Market Analysts: Methodologies and Experiences supporting Small Enterprises (post-graduate course). Module Statistiques"
"en" => "Market Analysts: Methodologies and Experiences supporting Small Enterprises (post-graduate course). Statistics module"
]
"type" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"institution" => array:2 [
"fr" => "Università di Napoli Federico II"
"en" => "Università di Napoli Federico II"
]
"country" => array:2 [
"fr" => "Italie"
"en" => "Italy"
]
]
+lang: "fr"
}
55 => Essec\Faculty\Model\TeachingItem {#2363
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}
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"en" => "Organiser of the Second Workshop in the ESSEC-HEC Research WorkshopSeries on "PLS Developments": Structural Equation Models, PLs PathModeling and Multi-block Techniques in Sensory and Consumer Analysis -Methods, Applications and Software""
]
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]
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"fr" => "France"
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]
]
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}
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]
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]
"country" => array:2 [
"fr" => "Finlande"
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]
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}
23 => Essec\Faculty\Model\ExtraActivity {#2258
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"fr" => null
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]
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"fr" => "Portugal"
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]
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}
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]
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]
]
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}
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]
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"fr" => "Italie"
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]
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}
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]
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}
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]
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}
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]
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]
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}
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]
"country" => array:2 [
"fr" => "Slovénie"
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]
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}
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]
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"fr" => "Chypre"
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]
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}
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"en" => "Member of the Steering Committee for PLS'05, 4th International Symposium on PLS and Related Methods - Focus on Marketing"
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]
"country" => array:2 [
"fr" => "Espagne"
"en" => "Spain"
]
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}
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]
"country" => array:2 [
"fr" => "Australie"
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]
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}
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]
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}
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]
"country" => array:2 [
"fr" => "Allemagne"
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]
]
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}
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]
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]
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}
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]
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]
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}
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]
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]
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}
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]
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]
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}
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]
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]
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}
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"en" => "Programme Committee Member for the organisation of the IASC-IFCS Summer School on the theme: "Data Mining and Classification for Business and Industry: methods, computational issues and applications""
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"en" => null
]
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]
]
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}
41 => Essec\Faculty\Model\ExtraActivity {#2276
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"en" => null
]
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]
]
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+"parent": Essec\Faculty\Model\Profile {#2233}
}
42 => Essec\Faculty\Model\ExtraActivity {#2277
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1 => Essec\Faculty\Model\These {#2392
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2 => Essec\Faculty\Model\These {#2393
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3 => Essec\Faculty\Model\These {#2394
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4 => Essec\Faculty\Model\These {#2395
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5 => Essec\Faculty\Model\These {#2396
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6 => Essec\Faculty\Model\These {#2397
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0 => Essec\Faculty\Model\Contribution {#2399
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"title" => "The Benefits of a Monitoring Strategy for Firms Subject to the Emissions Trading System"
"description" => "DE GIOVANNI, P. et ESPOSITO VINZI, V. (2014). The Benefits of a Monitoring Strategy for Firms Subject to the Emissions Trading System. <i>Transportation Research Part D: Transport and Environment</i>, 33, pp. 220-233."
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"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "This study tests the impact of Internal and External Environmental Management on performance in firms subject to the European Union’s Emissions Trading System (ETS). A conceptual model is drawn up based on the existing literature, and tested on a large sample of Italian firms. The unit of analysis is single firms subject to the ETS that are involved in Green Supply Chain Management (GSCM). The ETS mechanism has been shown to be marginally beneficial for some firms while supply chain relationships are also influenced by such system. Firms need to identify suitable practices to boost the effectiveness of their environmental strategies. We propose the implementation of a monitoring strategy as a useful practice for firms to be environmentally and economically better off. Our results show that firms subject to the ETS should rely on their own (internal) Environmental Management alone for improving environmental performance, as collaboration with suppliers only has a positive impact on economic performance. However, implementation of a monitoring strategy allows a firm subject to the ETS to partially offset the inefficiency created by the system. We show that environmental collaboration does not become more effective when a monitoring practice is put in place."
"en" => "This study tests the impact of Internal and External Environmental Management on performance in firms subject to the European Union’s Emissions Trading System (ETS). A conceptual model is drawn up based on the existing literature, and tested on a large sample of Italian firms. The unit of analysis is single firms subject to the ETS that are involved in Green Supply Chain Management (GSCM). The ETS mechanism has been shown to be marginally beneficial for some firms while supply chain relationships are also influenced by such system. Firms need to identify suitable practices to boost the effectiveness of their environmental strategies. We propose the implementation of a monitoring strategy as a useful practice for firms to be environmentally and economically better off. Our results show that firms subject to the ETS should rely on their own (internal) Environmental Management alone for improving environmental performance, as collaboration with suppliers only has a positive impact on economic performance. However, implementation of a monitoring strategy allows a firm subject to the ETS to partially offset the inefficiency created by the system. We show that environmental collaboration does not become more effective when a monitoring practice is put in place."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
1 => Essec\Faculty\Model\Contribution {#2401
#_index: "academ_contributions"
#_id: "2598"
#_source: array:18 [
"id" => "2598"
"slug" => "the-benefits-of-the-emissions-trading-mechanism-for-italian-firms-a-multi-group-analysis"
"yearMonth" => "2014-05"
"year" => "2014"
"title" => "The Benefits of the Emissions Trading Mechanism for Italian Firms: A Multi-Group Analysis"
"description" => "DE GIOVANNI, P. et ESPOSITO VINZI, V. (2014). The Benefits of the Emissions Trading Mechanism for Italian Firms: A Multi-Group Analysis. <i>International Journal of Physical Distribution and Logistics Management</i>, 44(4), pp. 305-324."
"authors" => array:2 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "DE GIOVANNI Pietro"
]
]
"ouvrage" => ""
"keywords" => []
"updatedAt" => "2021-02-02 16:16:18"
"publicationUrl" => "https://www.researchgate.net/publication/262574749_The_benefits_of_the_emissions_trading_mechanism_for_Italian_firms_A_multi-group_analysis"
"publicationInfo" => array:3 [
"pages" => "305-324"
"volume" => "44"
"number" => "4"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "The purpose of this paper is to test the impact of internal and external environmental management (EM) on performance to verify the emission trading (ET) mechanism’s effectiveness. It aims to investigate whether EM that is carried out by ET firms has a higher influence on performance than EM that is carried out by no-ET firms. A conceptual model is drawn up based on the existing literature in green supply chain management (GSCM) and is tested on a large sample of Italian firms. A multi-group analysis in structural equation modeling allows for the estimation of the impact of internal and external EM on economic and environmental performance over the two groups. Firms under ET regime do not perform better than no-ET firms environmentally or economically; moreover, environmental collaboration is significantly less effective for ET firms. Although the ET mechanism has been introduced by the European Union to combat and reduce the emissions, research has shown its marginal effectiveness. Data comprises only data about Italian firms. Items in the questionnaire allow for a two-year lag period. Interviewed firms have been selected according to EM criteria only. Firms subjected to the ET mechanism should find more effective and efficient practices to improve their environmental performance because the ET is marginally beneficial. The findings supply insights to managers about the real effectiveness of ET as well as to decision planners for the development of future sustainable mechanisms."
"en" => "The purpose of this paper is to test the impact of internal and external environmental management (EM) on performance to verify the emission trading (ET) mechanism’s effectiveness. It aims to investigate whether EM that is carried out by ET firms has a higher influence on performance than EM that is carried out by no-ET firms. A conceptual model is drawn up based on the existing literature in green supply chain management (GSCM) and is tested on a large sample of Italian firms. A multi-group analysis in structural equation modeling allows for the estimation of the impact of internal and external EM on economic and environmental performance over the two groups. Firms under ET regime do not perform better than no-ET firms environmentally or economically; moreover, environmental collaboration is significantly less effective for ET firms. Although the ET mechanism has been introduced by the European Union to combat and reduce the emissions, research has shown its marginal effectiveness. Data comprises only data about Italian firms. Items in the questionnaire allow for a two-year lag period. Interviewed firms have been selected according to EM criteria only. Firms subjected to the ET mechanism should find more effective and efficient practices to improve their environmental performance because the ET is marginally beneficial. The findings supply insights to managers about the real effectiveness of ET as well as to decision planners for the development of future sustainable mechanisms."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
2 => Essec\Faculty\Model\Contribution {#2403
#_index: "academ_contributions"
#_id: "2778"
#_source: array:18 [
"id" => "2778"
"slug" => "two-step-pls-regression-for-l-structured-data-an-application-in-the-cosmetic-industry"
"yearMonth" => "2007-08"
"year" => "2007"
"title" => "Two-step PLS Regression for L-structured Data: An Application in the Cosmetic Industry"
"description" => "ESPOSITO VINZI, V., GUINOT, C. et SQUILLACCIOTTI, S. (2007). Two-step PLS Regression for L-structured Data: An Application in the Cosmetic Industry. <i>Statistical Methods and Applications</i>, pp. 263-278."
"authors" => array:3 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "GUINOT C."
]
2 => array:1 [
"name" => "SQUILLACCIOTTI S."
]
]
"ouvrage" => ""
"keywords" => []
"updatedAt" => "2021-07-13 14:31:02"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "263-278"
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "The present paper proposes a PLS-based methodology for the study of so called "L" data-structures, where external information on both the rows and the columns of a dependent variable matrix is available. L-structures are frequently encountered in consumer preference analysis. In this domain it may be desirable to study the influence of both product and consumer descriptors on consumer preferences. The proposed methodology has been applied on data from the cosmetic industry. The preference scores from 142 consumers on 9 products were explained with respect to the products' physico-chemical and sensory descriptors, and the consumers' socio-demographic and behavioural characteristics."
"en" => "The present paper proposes a PLS-based methodology for the study of so called "L" data-structures, where external information on both the rows and the columns of a dependent variable matrix is available. L-structures are frequently encountered in consumer preference analysis. In this domain it may be desirable to study the influence of both product and consumer descriptors on consumer preferences. The proposed methodology has been applied on data from the cosmetic industry. The preference scores from 142 consumers on 9 products were explained with respect to the products' physico-chemical and sensory descriptors, and the consumers' socio-demographic and behavioural characteristics."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
3 => Essec\Faculty\Model\Contribution {#2400
#_index: "academ_contributions"
#_id: "8566"
#_source: array:18 [
"id" => "8566"
"slug" => "eurisbis-09-book-of-abstracts"
"yearMonth" => "2009-01"
"year" => "2009"
"title" => "EURISBIS' 09 - Book of Abstracts"
"description" => "MOLA, F., CONVERSANO, C., ESPOSITO VINZI, V. et FISHER, N. (2009). EURISBIS' 09 - Book of Abstracts. Tilapia, Italie."
"authors" => array:4 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "MOLA F."
]
2 => array:1 [
"name" => "CONVERSANO C."
]
3 => array:1 [
"name" => "FISHER N."
]
]
"ouvrage" => ""
"keywords" => []
"updatedAt" => "2020-12-17 18:37:46"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Editeur d'actes de conférence"
"en" => "Conference proceedings editor"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
4 => Essec\Faculty\Model\Contribution {#2404
#_index: "academ_contributions"
#_id: "3412"
#_source: array:18 [
"id" => "3412"
"slug" => "assessment-and-validation-in-quantile-composite-based-path-modeling"
"yearMonth" => "2016-12"
"year" => "2016"
"title" => "Assessment and Validation in Quantile Composite-Based Path Modeling"
"description" => "DAVINO, C., ESPOSITO VINZI, V. et DOLCE, P. (2016). Assessment and Validation in Quantile Composite-Based Path Modeling. Dans: <i>The Multiple Facets of Partial Least Squares and Related Methods</i>. 1st ed. Springer, pp. 169-180."
"authors" => array:3 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "DAVINO C."
]
2 => array:1 [
"name" => "DOLCE P."
]
]
"ouvrage" => "The Multiple Facets of Partial Least Squares and Related Methods"
"keywords" => []
"updatedAt" => "2021-09-24 10:33:27"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "169-180"
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Chapitres"
"en" => "Book chapters"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "PLS-PM presents some inconsistencies in terms of coherence with the direction of the relationships specified in the path diagram (i.e. the path directions). The PLS-PM iterative algorithm analyses interdependence among blocks and misses to distinguish explicitly between dependent and explanatory blocks in the structural model. This inconsistency of PLS-PM is illustrated by using the simple two-blocks model. For the case of more than two blocks of variables, it is necessary a close look at the different criteria optimized by PLS-PM in order to show this issue. In general, the role of latent variables in the structural model depends on the way the outer weights are calculated. A recently proposed method, called Non-Symmetrical Component-based Path Modeling, which is based on the optimization of a redundancy-related criterion in a multi-block framework, respects the direction of the relationships specified in the structural model. In order to assess the quality of the model, we provide a new goodness-of-fit index based on redundancy criterion and prediction capability. Furthermore, we provide a procedure to address the problem of multicollinearity within blocks of variables."
"en" => "PLS-PM presents some inconsistencies in terms of coherence with the direction of the relationships specified in the path diagram (i.e. the path directions). The PLS-PM iterative algorithm analyses interdependence among blocks and misses to distinguish explicitly between dependent and explanatory blocks in the structural model. This inconsistency of PLS-PM is illustrated by using the simple two-blocks model. For the case of more than two blocks of variables, it is necessary a close look at the different criteria optimized by PLS-PM in order to show this issue. In general, the role of latent variables in the structural model depends on the way the outer weights are calculated. A recently proposed method, called Non-Symmetrical Component-based Path Modeling, which is based on the optimization of a redundancy-related criterion in a multi-block framework, respects the direction of the relationships specified in the structural model. In order to assess the quality of the model, we provide a new goodness-of-fit index based on redundancy criterion and prediction capability. Furthermore, we provide a procedure to address the problem of multicollinearity within blocks of variables."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
5 => Essec\Faculty\Model\Contribution {#2398
#_index: "academ_contributions"
#_id: "5607"
#_source: array:18 [
"id" => "5607"
"slug" => "component-based-redundancy-path-modeling"
"yearMonth" => "2014-06"
"year" => "2014"
"title" => "Component-Based Redundancy Path-Modeling"
"description" => "ESPOSITO VINZI, V. (2014). Component-Based Redundancy Path-Modeling. Dans: 2014 International Symposium on Business and Industrial Statistics."
"authors" => array:1 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
]
"ouvrage" => "2014 International Symposium on Business and Industrial Statistics"
"keywords" => []
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
6 => Essec\Faculty\Model\Contribution {#2402
#_index: "academ_contributions"
#_id: "1420"
#_source: array:18 [
"id" => "1420"
"slug" => "is-environmental-management-an-economically-sustainable-business"
"yearMonth" => "2014-11"
"year" => "2014"
"title" => "Is Environmental Management an Economically Sustainable Business?"
"description" => "GOTSCHOL, A., DE GIOVANNI, P. et ESPOSITO VINZI, V. (2014). Is Environmental Management an Economically Sustainable Business? <i>Journal of Environmental Management</i>, 144(1), pp. 73-82."
"authors" => array:3 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "GOTSCHOL A."
]
2 => array:1 [
"name" => "DE GIOVANNI Pietro"
]
]
"ouvrage" => ""
"keywords" => array:5 [
0 => "Green supply chain management"
1 => "Green production"
2 => "Environmental performance"
3 => "Economic performance"
4 => "Structural equation modeling"
]
"updatedAt" => "2021-02-02 16:16:18"
"publicationUrl" => "https://www.sciencedirect.com/science/article/pii/S0301479714002266"
"publicationInfo" => array:3 [
"pages" => "73-82"
"volume" => "144"
"number" => "1"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "This paper investigates whether environmental management is an economically sustainable business. While firms invest in green production and green supply chain activities with the primary purpose of reducing their environmental impact, the reciprocal relationships with economic performance need to be clarified. We found out that environmental management positively influences economic performance as second order (long term) target, to be reached conditioned by higher environmental performance; in addition, firms can increase their performance if they reinvest the higher economic value gained through environmental management in green practices. While investing in environmental management programs is a short term strategy, economic rewards can be obtained only with some delays. Consequently, environmental management is an economically sustainable business only for patient firms. In the evaluation of these reciprocal relationships, we discovered that green supply chain initiatives are more effective and more economically sustainable than internal actions."
"en" => "This paper investigates whether environmental management is an economically sustainable business. While firms invest in green production and green supply chain activities with the primary purpose of reducing their environmental impact, the reciprocal relationships with economic performance need to be clarified. We found out that environmental management positively influences economic performance as second order (long term) target, to be reached conditioned by higher environmental performance; in addition, firms can increase their performance if they reinvest the higher economic value gained through environmental management in green practices. While investing in environmental management programs is a short term strategy, economic rewards can be obtained only with some delays. Consequently, environmental management is an economically sustainable business only for patient firms. In the evaluation of these reciprocal relationships, we discovered that green supply chain initiatives are more effective and more economically sustainable than internal actions."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
7 => Essec\Faculty\Model\Contribution {#2405
#_index: "academ_contributions"
#_id: "1421"
#_source: array:18 [
"id" => "1421"
"slug" => "is-investing-in-social-media-really-worth-it-how-brand-actions-and-user-actions-influence-brand-value"
"yearMonth" => "2016-06"
"year" => "2016"
"title" => "Is Investing in Social Media Really Worth It? How Brand Actions and User Actions Influence Brand Value"
"description" => "COLICEV, A., O'CONNOR, P. et ESPOSITO VINZI, V. (2016). Is Investing in Social Media Really Worth It? How Brand Actions and User Actions Influence Brand Value. <i>Service Science</i>, 8(2), pp. 152-168."
"authors" => array:3 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "COLICEV A."
]
2 => array:1 [
"name" => "O'CONNOR Peter"
]
]
"ouvrage" => ""
"keywords" => array:5 [
0 => "Social media"
1 => "Branding"
2 => "Brand value"
3 => "Partial least squares (PLS)"
4 => "Return on investment"
]
"updatedAt" => "2021-02-02 16:16:18"
"publicationUrl" => "https://pubsonline.informs.org/doi/10.1287/serv.2016.0143"
"publicationInfo" => array:3 [
"pages" => "152-168"
"volume" => "8"
"number" => "2"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "Although previous studies have documented a positive link between traditional media and brand performance, how social media is related to brand value has not yet been comprehensively explored. We propose a conceptual model to address this research gap, collecting a unique data set that captures information on user and brand actions on three social media platforms (Facebook, Twitter, and YouTube), word-of-mouth, and brand value for 87 brands in 17 industries. We empirically test our model with partial least squares path modeling (PLS-PM). First, we test the direct effects and find that user actions on YouTube and brand actions on Facebook have a positive influence on brand value. Second, we enrich our model by including word-of-mouth as a mediator, finding that the effect of social media goes above and beyond pure word-of-mouth spread. We test for alternative models, by first accounting for sample heterogeneity and second by including brand strength as a control variable, finding that the main model results’ are indeed robust. Our study demonstrates that making use of social media positively relates to brand value, as well as validates a set of objective metrics to measure social media actions, thus advancing knowledge on social media marketing for both academics and practitioners."
"en" => "Although previous studies have documented a positive link between traditional media and brand performance, how social media is related to brand value has not yet been comprehensively explored. We propose a conceptual model to address this research gap, collecting a unique data set that captures information on user and brand actions on three social media platforms (Facebook, Twitter, and YouTube), word-of-mouth, and brand value for 87 brands in 17 industries. We empirically test our model with partial least squares path modeling (PLS-PM). First, we test the direct effects and find that user actions on YouTube and brand actions on Facebook have a positive influence on brand value. Second, we enrich our model by including word-of-mouth as a mediator, finding that the effect of social media goes above and beyond pure word-of-mouth spread. We test for alternative models, by first accounting for sample heterogeneity and second by including brand strength as a control variable, finding that the main model results’ are indeed robust. Our study demonstrates that making use of social media positively relates to brand value, as well as validates a set of objective metrics to measure social media actions, thus advancing knowledge on social media marketing for both academics and practitioners."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
8 => Essec\Faculty\Model\Contribution {#2406
#_index: "academ_contributions"
#_id: "6269"
#_source: array:18 [
"id" => "6269"
"slug" => "knowledge-extraction-through-predictive-path-modeling"
"yearMonth" => "2012-08"
"year" => "2012"
"title" => "Knowledge Extraction Through Predictive Path Modeling"
"description" => "ESPOSITO VINZI, V. (2012). Knowledge Extraction Through Predictive Path Modeling. Dans: 20th International Conference on Computational Statistics 2012."
"authors" => array:1 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
]
"ouvrage" => "20th International Conference on Computational Statistics 2012"
"keywords" => []
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
9 => Essec\Faculty\Model\Contribution {#2407
#_index: "academ_contributions"
#_id: "2023"
#_source: array:18 [
"id" => "2023"
"slug" => "mapping-corporate-responsibility-and-sustainable-supply-chains-an-exploratory-perspective"
"yearMonth" => "2012-12"
"year" => "2012"
"title" => "Mapping Corporate Responsibility and Sustainable Supply Chains: An Exploratory Perspective"
"description" => "CARBONE, V., MOATTI, V. et ESPOSITO VINZI, V. (2012). Mapping Corporate Responsibility and Sustainable Supply Chains: An Exploratory Perspective. <i>Business Strategy and the Environment</i>, 21(7), pp. 475-494."
"authors" => array:3 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "CARBONE V."
]
2 => array:1 [
"name" => "MOATTI V."
]
]
"ouvrage" => ""
"keywords" => array:6 [
0 => "Corporate social responsability (CSR)"
1 => "Corporate environmental responsability (CER)"
2 => "Sustainable development"
3 => "Supply chain management"
4 => "Longtudinal study"
5 => "Socially responsible investment (SRI)"
]
"updatedAt" => "2021-02-02 16:16:18"
"publicationUrl" => "https://onlinelibrary.wiley.com/doi/abs/10.1002/bse.1736"
"publicationInfo" => array:3 [
"pages" => "475-494"
"volume" => "21"
"number" => "7"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "Corporate responsibility (CR) in general, and sustainable supply chain management in particular, have been a growing concern for companies and researchers over the past decade. However, in scholarly work, sustainability has often been dealt with in a generic fashion or from an anecdotal point of view. Further, research works examining CR on the one hand and sustainable supply chains on the other have been conducted separately. We undertake the multiple factor analysis of a CR rating database (Innovest) which reports longitudinal scores for both the social and environmental performance of 1198 companies in different countries and distinct industries, to demonstrate a strong relationship between CR and a sustainable supply chain. Our findings from exploratory analysis also illustrate the role of country of origin and industry in shaping CR behavior, highlighting isomorphic as well as allomorphic trends for CR trough time."
"en" => "Corporate responsibility (CR) in general, and sustainable supply chain management in particular, have been a growing concern for companies and researchers over the past decade. However, in scholarly work, sustainability has often been dealt with in a generic fashion or from an anecdotal point of view. Further, research works examining CR on the one hand and sustainable supply chains on the other have been conducted separately. We undertake the multiple factor analysis of a CR rating database (Innovest) which reports longitudinal scores for both the social and environmental performance of 1198 companies in different countries and distinct industries, to demonstrate a strong relationship between CR and a sustainable supply chain. Our findings from exploratory analysis also illustrate the role of country of origin and industry in shaping CR behavior, highlighting isomorphic as well as allomorphic trends for CR trough time."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
10 => Essec\Faculty\Model\Contribution {#2408
#_index: "academ_contributions"
#_id: "2069"
#_source: array:18 [
"id" => "2069"
"slug" => "modeling-a-causality-network-for-tourism-an-empirical-analysis"
"yearMonth" => "2011-11"
"year" => "2011"
"title" => "Modeling a Causality Network for Tourism: An Empirical Analysis"
"description" => "ASSAKER, G., ESPOSITO VINZI, V. et O'CONNOR, P. (2011). Modeling a Causality Network for Tourism: An Empirical Analysis. <i>Journal of Modelling in Management</i>, 6(3), pp. 258-278."
"authors" => array:3 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "ASSAKER Guy"
]
2 => array:1 [
"name" => "O'CONNOR Peter"
]
]
"ouvrage" => ""
"keywords" => array:6 [
0 => "Covariance-based structural equation modeling"
1 => "Reflective indicators"
2 => "Formative indicators"
3 => "Tourism development"
4 => "Tourism"
5 => "Forecasting"
]
"updatedAt" => "2021-02-09 11:57:54"
"publicationUrl" => "https://www.emerald.com/insight/content/doi/10.1108/17465661111183685/full/html"
"publicationInfo" => array:3 [
"pages" => "258-278"
"volume" => "6"
"number" => "3"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "Le but de cet article est de capturer les relations causales entre les constituants principaux du paradigme de destination du tourisme – à savoir, l'économie, la société et les environnements naturels et infra structuraux– et la demande pour le tourisme à cette destination. L'étude utilise la méthodologie de l’équation structurelle modélisante (SEM) avec un échantillon de données croisées de 162 pays, afin d'évaluer les mesures proposées a priori et les modèles structurels. Les résultats indiquent que bien que les données construites sur l'économie se sont avérées comme n’ayant aucune influence directe sur le tourisme, il y a vraiment un impact positif sur le tourisme par le biais sociétal et environnemental, le sociétal parallèlement à l'infrastructure. De plus, la société et l'environnement se sont avérés avoir un impact direct et positif sur la génération d’activités touristiques et de revenus."
"en" => "The purpose of this paper is to capture the causal relationships between the primary constituents of the tourism destination paradigm – namely, the economy, society, and the natural and infrastructural environments – and demand for tourism at that destination. The study uses structural equation modeling (SEM) methodologies with a cross-sectional data sample from 162 countries, to evaluate a priori proposed measurement and structural models. The results indicate that although the economy construct was found to have no direct influence on tourism, it does have a mediating, positive impact on tourism through the society and environment constructs, with the society construct paralleling the condition of the infrastructure. Moreover, society and environment were found to have a direct, positive impact on generating tourism activities, and revenues."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
11 => Essec\Faculty\Model\Contribution {#2409
#_index: "academ_contributions"
#_id: "2103"
#_source: array:18 [
"id" => "2103"
"slug" => "non-symmetrical-composite-based-path-modeling"
"yearMonth" => "2017-11"
"year" => "2017"
"title" => "Non-Symmetrical Composite-Based Path Modeling"
"description" => "DOLCE, P., ESPOSITO VINZI, V. et LAURO, N.C. (2017). Non-Symmetrical Composite-Based Path Modeling. <i>Advances in Data Analysis and Classification</i>, 12(4), pp. 759-784."
"authors" => array:3 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "DOLCE P."
]
2 => array:1 [
"name" => "LAURO N.-C."
]
]
"ouvrage" => ""
"keywords" => array:3 [
0 => "PLS path modeling"
1 => "Non-symmetrical analysis"
2 => "Predictive composite-based methods"
]
"updatedAt" => "2021-09-24 10:33:27"
"publicationUrl" => "https://link.springer.com/article/10.1007/s11634-017-0302-1"
"publicationInfo" => array:3 [
"pages" => "759-784"
"volume" => "12"
"number" => "4"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => """
Partial least squares path modeling presents some inconsistencies in terms of coherence with the predictive directions specified in the inner model (i.e. the path\n
directions), because the directions of the links in the inner model are not taken into account in the iterative algorithm. In fact, the procedure amplifies interdependence among blocks and fails to distinguish between dependent and explanatory blocks. The method proposed in this paper takes into account and respects the specified path directions, with the aim of improving the predictive ability of the model and to maintain the hypothesized theoretical inner model. To highlight its properties, the proposed method is compared to the classical PLS path modeling in terms of explained variability, predictive relevance and interpretation using artificial data through a real data application. A further development of the method allows to treat multi-dimensional blocks in composite-based path modeling.
"""
"en" => "Partial least squares path modeling presents some inconsistencies in terms of coherence with the predictive directions specified in the inner model (i.e. the path directions), because the directions of the links in the inner model are not taken into account in the iterative algorithm. In fact, the procedure amplifies interdependence among blocks and fails to distinguish between dependent and explanatory blocks. The method proposed in this paper takes into account and respects the specified path directions, with the aim of improving the predictive ability of the model and to maintain the hypothesized theoretical inner model. To highlight its properties, the proposed method is compared to the classical PLS path modeling in terms of explained variability, predictive relevance and interpretation using artificial data through a real data application. A further development of the method allows to treat multi-dimensional blocks in composite-based path modeling."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
12 => Essec\Faculty\Model\Contribution {#2410
#_index: "academ_contributions"
#_id: "2194"
#_source: array:18 [
"id" => "2194"
"slug" => "partial-least-squares-algorithms-and-methods"
"yearMonth" => "2014-11"
"year" => "2014"
"title" => "Partial Least Squares Algorithms and Methods"
"description" => "ESPOSITO VINZI, V. et RUSOLILLO, G. (2014). Partial Least Squares Algorithms and Methods. <i>Wires Computational Statistics</i>, 5, pp. 1-19."
"authors" => array:2 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "RUSOLILLO G."
]
]
"ouvrage" => ""
"keywords" => array:3 [
0 => "Modèles à équations structurelles"
1 => "Régression"
2 => "Tableaux multiples"
]
"updatedAt" => "2021-02-02 16:16:18"
"publicationUrl" => "https://doi.org/10.1002/wics.1239"
"publicationInfo" => array:3 [
"pages" => "1-19"
"volume" => "5"
"number" => null
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "Partial least squares (PLS) refers to a set of iterative algorithms based on least squares that implement a broad spectrum of both explanatory and exploratory multivariate techniques, from regression to path modeling, and from principal component to multi-block data analysis. This article focuses on PLS regression and PLS path modeling, which are PLS approaches to regularized regression and to predictive path modeling. The computational flows and the optimization criteria of these methods are reviewed in detail, as well as the tools for the assessment and interpretation of PLS models. The most recent developments and some of the most promising on going researches are enhanced."
"en" => "Partial least squares (PLS) refers to a set of iterative algorithms based on least squares that implement a broad spectrum of both explanatory and exploratory multivariate techniques, from regression to path modeling, and from principal component to multi-block data analysis. This article focuses on PLS regression and PLS path modeling, which are PLS approaches to regularized regression and to predictive path modeling. The computational flows and the optimization criteria of these methods are reviewed in detail, as well as the tools for the assessment and interpretation of PLS models. The most recent developments and some of the most promising on going researches are enhanced."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
13 => Essec\Faculty\Model\Contribution {#2411
#_index: "academ_contributions"
#_id: "2329"
#_source: array:18 [
"id" => "2329"
"slug" => "quantile-composite-based-path-modeling"
"yearMonth" => "2016-12"
"year" => "2016"
"title" => "Quantile Composite-Based Path Modeling"
"description" => "DAVINO, C. et ESPOSITO VINZI, V. (2016). Quantile Composite-Based Path Modeling. <i>Advances in Data Analysis and Classification</i>, 10(4), pp. 491-520."
"authors" => array:2 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "DAVINO C."
]
]
"ouvrage" => ""
"keywords" => array:3 [
0 => "Quantile regression"
1 => "PLS path modeling"
2 => "Multi-block data"
]
"updatedAt" => "2021-09-24 10:33:27"
"publicationUrl" => "https://link.springer.com/article/10.1007/s11634-015-0231-9"
"publicationInfo" => array:3 [
"pages" => "491-520"
"volume" => "10"
"number" => "4"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "The paper aims at introducing a quantile approach in the Partial Least Squares path modeling framework. This is a well known composite-based method for the analysis of complex phenomena measurable through a network of relationships among observed and unobserved variables. The proposal intends to enhance potentialities of the Partial Least Squares path models overcoming the classical exploration of average effects. The introduction of Quantile Regression and Correlation in the estimationphases of the model allows highlighting how and if the relationships among observed and unobserved variables change according to the explored quantile of interest. The proposed method is applied to two real datasets in the customer satisfaction measurement and in the sensory analysis framework but it proves to be useful also in other applicative contexts."
"en" => "The paper aims at introducing a quantile approach in the Partial Least Squares path modeling framework. This is a well known composite-based method for the analysis of complex phenomena measurable through a network of relationships among observed and unobserved variables. The proposal intends to enhance potentialities of the Partial Least Squares path models overcoming the classical exploration of average effects. The introduction of Quantile Regression and Correlation in the estimationphases of the model allows highlighting how and if the relationships among observed and unobserved variables change according to the explored quantile of interest. The proposed method is applied to two real datasets in the customer satisfaction measurement and in the sensory analysis framework but it proves to be useful also in other applicative contexts."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
14 => Essec\Faculty\Model\Contribution {#2412
#_index: "academ_contributions"
#_id: "2374"
#_source: array:18 [
"id" => "2374"
"slug" => "rebus-pls-a-response-based-procedure-for-detecting-unit-segments-in-pls-path-modelling"
"yearMonth" => "2008-09"
"year" => "2008"
"title" => "REBUS-PLS: A Response-based Procedure for Detecting Unit Segments in PLS Path Modelling"
"description" => "ESPOSITO VINZI, V., TRINCHERA, L., SQUILLACCIOTTI, S. et TENENHAUS, M. (2008). REBUS-PLS: A Response-based Procedure for Detecting Unit Segments in PLS Path Modelling. <i>Applied Stochastic Models in Business and Industry</i>, 24(5), pp. 439-458."
"authors" => array:4 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "TRINCHERA L."
]
2 => array:1 [
"name" => "SQUILLACCIOTTI S."
]
3 => array:1 [
"name" => "TENENHAUS M."
]
]
"ouvrage" => ""
"keywords" => array:3 [
0 => "Classification"
1 => "Latent Classes"
2 => "Moderating Effects"
]
"updatedAt" => "2020-12-17 17:55:06"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "439-458"
"volume" => "24"
"number" => "5"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "Structural equation models (SEMs) make it possible to estimate the causal relationships, defined according to a theoretical model, linking two or more latent complex concepts, each measured through a number of observable indicators, usually called manifest variables. Traditionally, the component-based estimation of SEMs by means of partial least squares (PLS path modelling, PLS-PM) assumes homogeneity over the observed set of units: all units are supposed to be well represented by a unique model estimated on the overall data set. In many cases, however, it is reasonable to expect classes made of units showing heterogeneous behaviours to exist. Two different kinds of heterogeneity could be affecting the data: observed and unobserved heterogeneity. The first refers to the case of a priori existing classes, whereas in unobserved heterogeneity no information is available either on the number of classes or on their composition. If a group structure for the statistical units is given, the aim of the analysis is to search for any differences in the behaviours of the a priori given classes. In PLS-PM this would mean studying the effect of directly observed moderating variables, i.e. estimating as many (local) models as there are classes. Unobserved heterogeneity, instead, implies identifying classes of units (a priori unknown) having similar behaviours. Such heterogeneity is captured by an unobserved (latent) discrete moderating variable defining both the number of classes and the class membership. A new method for unobserved heterogeneity detection in PLS-PM is proposed in this paper: response-based procedure for detecting unit segments in PLS-PM (REBUS-PLS). REBUS-PLS, according to PLS-PM features, does not require distributional hypotheses and may lead to local models that are different in terms of both structural and measurement models. An application of REBUS-PLS on real data will be shown."
"en" => "Structural equation models (SEMs) make it possible to estimate the causal relationships, defined according to a theoretical model, linking two or more latent complex concepts, each measured through a number of observable indicators, usually called manifest variables. Traditionally, the component-based estimation of SEMs by means of partial least squares (PLS path modelling, PLS-PM) assumes homogeneity over the observed set of units: all units are supposed to be well represented by a unique model estimated on the overall data set. In many cases, however, it is reasonable to expect classes made of units showing heterogeneous behaviours to exist. Two different kinds of heterogeneity could be affecting the data: observed and unobserved heterogeneity. The first refers to the case of a priori existing classes, whereas in unobserved heterogeneity no information is available either on the number of classes or on their composition. If a group structure for the statistical units is given, the aim of the analysis is to search for any differences in the behaviours of the a priori given classes. In PLS-PM this would mean studying the effect of directly observed moderating variables, i.e. estimating as many (local) models as there are classes. Unobserved heterogeneity, instead, implies identifying classes of units (a priori unknown) having similar behaviours. Such heterogeneity is captured by an unobserved (latent) discrete moderating variable defining both the number of classes and the class membership. A new method for unobserved heterogeneity detection in PLS-PM is proposed in this paper: response-based procedure for detecting unit segments in PLS-PM (REBUS-PLS). REBUS-PLS, according to PLS-PM features, does not require distributional hypotheses and may lead to local models that are different in terms of both structural and measurement models. An application of REBUS-PLS on real data will be shown."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
15 => Essec\Faculty\Model\Contribution {#2413
#_index: "academ_contributions"
#_id: "2395"
#_source: array:18 [
"id" => "2395"
"slug" => "refund-depth-effects-on-the-impact-of-price-beating-guarantees"
"yearMonth" => "2012-05"
"year" => "2012"
"title" => "Refund Depth Effects on the Impact of Price-Beating Guarantees"
"description" => "DESMET, P., LE NAGARD, E. et ESPOSITO VINZI, V. (2012). Refund Depth Effects on the Impact of Price-Beating Guarantees. <i>Journal of Business Research</i>, 65(5), pp. 603-608."
"authors" => array:3 [
0 => array:3 [
"name" => "DESMET Pierre"
"bid" => "B00000155"
"slug" => "desmet-pierre"
]
1 => array:3 [
"name" => "LE NAGARD Emmanuelle"
"bid" => "B00000304"
"slug" => "le-nagard-emmanuelle"
]
2 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
]
"ouvrage" => ""
"keywords" => array:5 [
0 => "Price-matching guarantees"
1 => "Price image"
2 => "Retailing"
3 => "Price-beating guarantees"
4 => "Retail pricing"
]
"updatedAt" => "2021-02-02 16:16:18"
"publicationUrl" => "https://doi.org/10.1016/j.jbusres.2011.02.034"
"publicationInfo" => array:3 [
"pages" => "603-608"
"volume" => "65"
"number" => "5"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "Refund depth may influence the effectiveness of a price guarantee when a store offers to reimburse customers more than the price difference. Using an experimental study that features real stores with high credibility, this article shows that a simple price-matching guarantee has no effect on either the perceived value of an offer or intentions to visit the store. Low and high penalty levels have smaller effects than intermediate penalties, but the believability of price guarantee offers that contain a penalty remain constant; this finding may reflect a general distrust of additional penalties."
"en" => "Refund depth may influence the effectiveness of a price guarantee when a store offers to reimburse customers more than the price difference. Using an experimental study that features real stores with high credibility, this article shows that a simple price-matching guarantee has no effect on either the perceived value of an offer or intentions to visit the store. Low and high penalty levels have smaller effects than intermediate penalties, but the believability of price guarantee offers that contain a penalty remain constant; this finding may reflect a general distrust of additional penalties."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
16 => Essec\Faculty\Model\Contribution {#2414
#_index: "academ_contributions"
#_id: "6928"
#_source: array:18 [
"id" => "6928"
"slug" => "predictive-component-based-multi-block-path-modeling"
"yearMonth" => "2014-08"
"year" => "2014"
"title" => "Predictive Component-based Multi-block Path Modeling"
"description" => "DOLCE, P., ESPOSITO VINZI, V. et LAURO, C. (2014). Predictive Component-based Multi-block Path Modeling. Dans: 21st International Conference on Computational Statistics."
"authors" => array:3 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "DOLCE P."
]
2 => array:1 [
"name" => "LAURO C."
]
]
"ouvrage" => "21st International Conference on Computational Statistics"
"keywords" => []
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
17 => Essec\Faculty\Model\Contribution {#2415
#_index: "academ_contributions"
#_id: "9852"
#_source: array:18 [
"id" => "9852"
"slug" => "explanatory-methods-for-comparative-analyses"
"yearMonth" => "1999-06"
"year" => "1999"
"title" => "Explanatory Methods for Comparative Analyses"
"description" => "ESPOSITO VINZI, V. (1999). Explanatory Methods for Comparative Analyses. Dans: <i>Proceedings of Les Methodes PLS</i>. Montreuil: CISIA, pp. 41-60."
"authors" => array:1 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
]
"ouvrage" => "Proceedings of Les Methodes PLS"
"keywords" => array:1 [
0 => "Explanatory Methods -Comparative Analyses"
]
"updatedAt" => "2021-07-13 14:31:21"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "41-60"
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Actes d'une conférence"
"en" => "Conference Proceedings"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "Explanatory Methods for Comparative Analyses"
"en" => "Explanatory Methods for Comparative Analyses"
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
18 => Essec\Faculty\Model\Contribution {#2416
#_index: "academ_contributions"
#_id: "9911"
#_source: array:18 [
"id" => "9911"
"slug" => "pls-logistic-regression"
"yearMonth" => "2001-06"
"year" => "2001"
"title" => "PLS Logistic Regression"
"description" => "ESPOSITO VINZI, V. et TENENHAUS, M. (2001). PLS Logistic Regression. Dans: <i>PLS and Related Methods</i>. Paris: CISIA, pp. 117-130."
"authors" => array:2 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "TENENHAUS Michel"
]
]
"ouvrage" => "PLS and Related Methods"
"keywords" => array:2 [
0 => "PLS"
1 => "Logistic Regression"
]
"updatedAt" => "2021-07-13 14:31:23"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "117-130"
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Actes d'une conférence"
"en" => "Conference Proceedings"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "PLS Logistic Regression"
"en" => "PLS Logistic Regression"
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
19 => Essec\Faculty\Model\Contribution {#2417
#_index: "academ_contributions"
#_id: "4027"
#_source: array:18 [
"id" => "4027"
"slug" => "modeles-dequations-structurelles-approches-basees-sur-les-composantes"
"yearMonth" => "2013-04"
"year" => "2013"
"title" => "Modèles d'Equations Structurelles, Approches basées sur les Composantes"
"description" => "ESPOSITO VINZI, V. et TRINCHERA, L. (2013). Modèles d'Equations Structurelles, Approches basées sur les Composantes. Dans: <i>Modèles à variables latentes et modèles de mélange</i>. 1st ed. Éditions TECHNIP, pp. 153-176."
"authors" => array:2 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "TRINCHERA L."
]
]
"ouvrage" => "Modèles à variables latentes et modèles de mélange"
"keywords" => array:2 [
0 => "Analyse en Composantes Structurelles Généralisée"
1 => "Approche PLS"
]
"updatedAt" => "2021-09-06 14:06:32"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "153-176"
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Chapitres"
"en" => "Book chapters"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "Ce chapitre décrit les approches aux équations structurelles qui utilisent des techniques d’estimation fondées sur les composantes où l’estimation des variables latentes joue un rôle central. On introduira d’abord les modèles à équations structurelles classiques, puis on présentera les algorithmes liés à l’approche PLS et à l’analyse en composantes structurelles généralisée, ainsi que les indices de qualité. Enfin on présentera une application à des données réelles."
"en" => "This chapter presents the so-called component-based methods to Structural Equation Modeling. First we introduce Structural Equation Models and we present the used notation. Then, the PLS Path Modeling algorithm and the Generalized Structured Component Analysis, as well the relative quality indexes will be discussed . To conclude, an application of PLS Path Modeling on real data will be presented."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
20 => Essec\Faculty\Model\Contribution {#2418
#_index: "academ_contributions"
#_id: "4028"
#_source: array:18 [
"id" => "4028"
"slug" => "modeles-locaux-issus-dun-modele-dequations-structurelles"
"yearMonth" => "2013-04"
"year" => "2013"
"title" => "Modèles locaux issus d'un modèle d'équations structurelles"
"description" => "ESPOSITO VINZI, V. et TRINCHERA, L. (2013). Modèles locaux issus d'un modèle d'équations structurelles. Dans: <i>Modèles à variables latentes et modèles de mélange</i>. 1st ed. Éditions TECHNIP, pp. 177-214."
"authors" => array:2 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "TRINCHERA L."
]
]
"ouvrage" => "Modèles à variables latentes et modèles de mélange"
"keywords" => array:5 [
0 => "Analyse multi-groupe"
1 => "FIMIX-PLS"
2 => "Hétérogénéité des unités observées"
3 => "PATHMOX"
4 => "REBUS-PLS"
]
"updatedAt" => "2021-09-06 14:06:32"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "177-214"
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Chapitres"
"en" => "Book chapters"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "Ce chapitre se concentre sur des techniques de détection de sous-populations dans le cas où existent des variables latentes modératrices inconnues, donc dans le cas où le nombre des classes et leurs structures sont inconnus."
"en" => "This chapter focuses on techniques for detecting unit segments in component-based approaches to SEMs by response-based techniques in the case of unknown (latent) moderating effects, i.e. when both the number and the structure of the classes are not a priori known."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
21 => Essec\Faculty\Model\Contribution {#2419
#_index: "academ_contributions"
#_id: "4061"
#_source: array:18 [
"id" => "4061"
"slug" => "path-directions-incoherence-in-pls-path-modeling-a-prediction-oriented-solution"
"yearMonth" => "2016-12"
"year" => "2016"
"title" => "Path Directions Incoherence in PLS Path Modeling: A Prediction-Oriented Solution"
"description" => "DOLCE, P., ESPOSITO VINZI, V. et LAURO, C. (2016). Path Directions Incoherence in PLS Path Modeling: A Prediction-Oriented Solution. Dans: <i>The Multiple Facets of Partial Least Squares and Related Methods</i>. 1st ed. Springer, pp. 59-70."
"authors" => array:3 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "DOLCE P."
]
2 => array:1 [
"name" => "LAURO C."
]
]
"ouvrage" => "The Multiple Facets of Partial Least Squares and Related Methods"
"keywords" => []
"updatedAt" => "2021-09-24 10:33:27"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "59-70"
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Chapitres"
"en" => "Book chapters"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "PLS-PM presents some inconsistencies in terms of coherence with the direction of the relationships specified in the path diagram (i.e. the path directions). The PLS-PM iterative algorithm analyses interdependence among blocks and misses to distinguish explicitly between dependent and explanatory blocks in the structural model. This inconsistency of PLS-PM is illustrated by using the simple two-blocks model. For the case of more than two blocks of variables, it is necessary a close look at the different criteria optimized by PLS-PM in order to show this issue. In general, the role of latent variables in the structural model depends on the way the outer weights are calculated. A recently proposed method, called Non-Symmetrical Component-based Path Modeling, which is based on the optimization of a redundancy-related criterion in a multi-block framework, respects the direction of the relationships specified in the structural model. In order to assess the quality of the model, we provide a new goodness-of-fit index based on redundancy criterion and prediction capability. Furthermore, we provide a procedure to address the problem of multicollinearity within blocks of variables."
"en" => "PLS-PM presents some inconsistencies in terms of coherence with the direction of the relationships specified in the path diagram (i.e. the path directions). The PLS-PM iterative algorithm analyses interdependence among blocks and misses to distinguish explicitly between dependent and explanatory blocks in the structural model. This inconsistency of PLS-PM is illustrated by using the simple two-blocks model. For the case of more than two blocks of variables, it is necessary a close look at the different criteria optimized by PLS-PM in order to show this issue. In general, the role of latent variables in the structural model depends on the way the outer weights are calculated. A recently proposed method, called Non-Symmetrical Component-based Path Modeling, which is based on the optimization of a redundancy-related criterion in a multi-block framework, respects the direction of the relationships specified in the structural model. In order to assess the quality of the model, we provide a new goodness-of-fit index based on redundancy criterion and prediction capability. Furthermore, we provide a procedure to address the problem of multicollinearity within blocks of variables."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
22 => Essec\Faculty\Model\Contribution {#2420
#_index: "academ_contributions"
#_id: "4070"
#_source: array:18 [
"id" => "4070"
"slug" => "pls-path-modeling-from-foundations-to-recent-developments-and-open-issues-for-model-assessment-and-improvement"
"yearMonth" => "2010-03"
"year" => "2010"
"title" => "PLS Path Modeling: From Foundations to Recent Developments and Open Issues for Model Assessment and Improvement"
"description" => "ESPOSITO VINZI, V., TRINCHERA, L. et AMATO, S. (2010). PLS Path Modeling: From Foundations to Recent Developments and Open Issues for Model Assessment and Improvement. Dans: <i>Handbook of Partial Least Squares: Concepts, Methods and Applications</i>. 1st ed. Springer, pp. 47-82."
"authors" => array:3 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "TRINCHERA L."
]
2 => array:1 [
"name" => "AMATO S."
]
]
"ouvrage" => "Handbook of Partial Least Squares: Concepts, Methods and Applications"
"keywords" => array:2 [
0 => "Mosel Validation"
1 => "Unobserved Heterogeneity"
]
"updatedAt" => "2021-09-06 14:06:32"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "47-82"
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Chapitres"
"en" => "Book chapters"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "In this chapter the authors first present the basic algorithm of PLS Path Modeling by discussing some recently proposed estimation options. Namely, they introduce the development of new estimation modes and schemes for multidimensional (formative) constructs, i.e. the use of PLS Regression for formative indicators, and the use of path analysis on latent variable scores to estimate path coefficients. Furthermore, they focus on the quality indexes classically used to assess the performance of the model in terms of explained variances. They also present some recent developments in PLS PathModeling framework for model assessment and improvement, including a non-parametric GoF-based procedure for assessing the statistical significance of path coefficients. Finally, they discuss the REBUS-PLS algorithm that enables to improve the prediction performance of the model by capturing unobserved heterogeneity. The chapter ends with a brief sketch of open issues in the area that, in the Authors' opinion, currently represent major research challenges."
"en" => "In this chapter the authors first present the basic algorithm of PLS Path Modeling by discussing some recently proposed estimation options. Namely, they introduce the development of new estimation modes and schemes for multidimensional (formative) constructs, i.e. the use of PLS Regression for formative indicators, and the use of path analysis on latent variable scores to estimate path coefficients. Furthermore, they focus on the quality indexes classically used to assess the performance of the model in terms of explained variances. They also present some recent developments in PLS PathModeling framework for model assessment and improvement, including a non-parametric GoF-based procedure for assessing the statistical significance of path coefficients. Finally, they discuss the REBUS-PLS algorithm that enables to improve the prediction performance of the model by capturing unobserved heterogeneity. The chapter ends with a brief sketch of open issues in the area that, in the Authors' opinion, currently represent major research challenges."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
23 => Essec\Faculty\Model\Contribution {#2421
#_index: "academ_contributions"
#_id: "4088"
#_source: array:18 [
"id" => "4088"
"slug" => "predictive-path-modeling-through-pls-and-other-component-based-approaches-methodological-issues-and-performance-evaluation"
"yearMonth" => "2017-11"
"year" => "2017"
"title" => "Predictive Path Modeling Through PLS and Other Component-Based Approaches: Methodological Issues and Performance Evaluation"
"description" => "DOLCE, P., ESPOSITO VINZI, V. et CARLO, L. (2017). Predictive Path Modeling Through PLS and Other Component-Based Approaches: Methodological Issues and Performance Evaluation. Dans: <i>Partial Least Squares Path Modeling: Basic Concepts, Methodological Issues and Applications</i>. 1st ed. Springer, pp. 153-172."
"authors" => array:3 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "DOLCE P."
]
2 => array:1 [
"name" => "CARLO L."
]
]
"ouvrage" => "Partial Least Squares Path Modeling: Basic Concepts, Methodological Issues and Applications"
"keywords" => []
"updatedAt" => "2021-09-24 10:33:27"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "153-172"
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Chapitres"
"en" => "Book chapters"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => """
This paper deals with the predictive use of PLS-PM and related\n
component-based methods in an attempt to contribute to the recent debates on the suitability of PLS-PM for predictive purposes. Appropriate measures and evaluation criteria for the assessment of models in terms of predictive ability are more and more desirable in PLS-PM. The performance of the models can be improved by choosing the appropriate parameter estimation procedure among the different existing ones or by making developments and modifications of the latter. A recent example of this type of work is the non-symmetrical approach for component-based path modeling, which leads to a new method, called non-symmetrical composite-based path modeling. In the composites construction stage, this new method explicitly takes into account the directions of the relationships in the inner model. Results are promising for this new method, especially in terms of predictive relevance.
"""
"en" => """
This paper deals with the predictive use of PLS-PM and related\n
component-based methods in an attempt to contribute to the recent debates on the suitability of PLS-PM for predictive purposes. Appropriate measures and evaluation criteria for the assessment of models in terms of predictive ability are more and more desirable in PLS-PM. The performance of the models can be improved by choosing the appropriate parameter estimation procedure among the different existing ones or by making developments and modifications of the latter. A recent example of this type of work is the non-symmetrical approach for component-based path modeling, which leads to a new method, called non-symmetrical composite-based path modeling. In the composites construction stage, this new method explicitly takes into account the directions of the relationships in the inner model. Results are promising for this new method, especially in terms of predictive relevance.
"""
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
24 => Essec\Faculty\Model\Contribution {#2422
#_index: "academ_contributions"
#_id: "4236"
#_source: array:18 [
"id" => "4236"
"slug" => "the-use-of-partial-least-squares-methods-in-new-food-product-development"
"yearMonth" => "2007-01"
"year" => "2007"
"title" => "The Use of Partial Least Squares Methods in New Food Product Development"
"description" => "MARTENS, M., TENENHAUS, M., ESPOSITO VINZI, V. et MARTENS, H. (2007). The Use of Partial Least Squares Methods in New Food Product Development. Dans: <i>Consumer-led Food Product Development</i>. 1st ed. Woodhead Publishing, pp. 492-523."
"authors" => array:4 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "MARTENS M."
]
2 => array:1 [
"name" => "TENENHAUS M."
]
3 => array:1 [
"name" => "MARTENS H."
]
]
"ouvrage" => "Consumer-led Food Product Development"
"keywords" => []
"updatedAt" => "2021-09-06 14:06:32"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "492-523"
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Chapitres"
"en" => "Book chapters"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "Successful food product development requires a clear vision and understanding of the interaction between consumers and product in a context and time perspective. PLS represents a certain modelling principle that describes multivariate observations in terms of their patterns of co-variation. This chapter first gives a short historical and motivational overview of PLS methods followed by a user-friendly theopretical introduction. A layperson's guide to the PLS methods then corresponds to examples in practice and reflections upon future trends."
"en" => "Successful food product development requires a clear vision and understanding of the interaction between consumers and product in a context and time perspective. PLS represents a certain modelling principle that describes multivariate observations in terms of their patterns of co-variation. This chapter first gives a short historical and motivational overview of PLS methods followed by a user-friendly theopretical introduction. A layperson's guide to the PLS methods then corresponds to examples in practice and reflections upon future trends."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
25 => Essec\Faculty\Model\Contribution {#2423
#_index: "academ_contributions"
#_id: "4334"
#_source: array:18 [
"id" => "4334"
"slug" => "a-non-linear-regularized-component-based-approach-to-structural-equation-modeling"
"yearMonth" => "2009-01"
"year" => "2009"
"title" => "A Non Linear Regularized Component-based Approach to Structural Equation Modeling"
"description" => "RUSSOLILLO, G., TRINCHERA, L. et ESPOSITO VINZI, V. (2009). A Non Linear Regularized Component-based Approach to Structural Equation Modeling. Dans: <i>Statistical Methods for the Analysis of Large Data-sets</i>. CLEUP, pp. 195-198."
"authors" => array:3 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "RUSSOLILLO G."
]
2 => array:1 [
"name" => "TRINCHERA L."
]
]
"ouvrage" => "Statistical Methods for the Analysis of Large Data-sets"
"keywords" => array:1 [
0 => "Structural Equation Modeling"
]
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "195-198"
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Actes d'une conférence"
"en" => "Conference Proceedings"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "Structural Equation Models (SEM) are widely used to model complex causal relations as the ones defining human behaviors. Several techniques exist to estimate SEM parameters. Among them the PLS Path Modeling (PLS- PM) algorithm is the most widely used technique. In particular, PLS-PM allows taking into account formative blocks of manifest variables. A new way to compute outer weights in the case of formative block of manifest variables has been recently proposed. This approach involves using PLS Regression (PLS-R) in order to compute outer weights even in the case of multicollinearity among the manifest variables of the same block. However, PLS Regression supposes linearity in relations between variables. Following the previous work, we decide to use a non-linear approach to PLS-R in order to estimate measurement model parameters in a non-linear PLS-PM approach to SEM."
"en" => "Structural Equation Models (SEM) are widely used to model complex causal relations as the ones defining human behaviors. Several techniques exist to estimate SEM parameters. Among them the PLS Path Modeling (PLS- PM) algorithm is the most widely used technique. In particular, PLS-PM allows taking into account formative blocks of manifest variables. A new way to compute outer weights in the case of formative block of manifest variables has been recently proposed. This approach involves using PLS Regression (PLS-R) in order to compute outer weights even in the case of multicollinearity among the manifest variables of the same block. However, PLS Regression supposes linearity in relations between variables. Following the previous work, we decide to use a non-linear approach to PLS-R in order to estimate measurement model parameters in a non-linear PLS-PM approach to SEM."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
26 => Essec\Faculty\Model\Contribution {#2424
#_index: "academ_contributions"
#_id: "4371"
#_source: array:18 [
"id" => "4371"
"slug" => "an-integrated-pls-regression-based-approach-for-multidimensional-blocks-in-pls-path-modeling"
"yearMonth" => "2010-06"
"year" => "2010"
"title" => "An Integrated PLS Regression-based Approach for Multidimensional Blocks in PLS Path Modeling"
"description" => "ESPOSITO VINZI, V., RUSSOLILO, G. et TRINCHERA, L. (2010). An Integrated PLS Regression-based Approach for Multidimensional Blocks in PLS Path Modeling. Dans: <i>42èmes Journées de Statistique de la Société Française de Statistique</i>. SFdS, Société Française de Statistique."
"authors" => array:3 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "RUSSOLILO G."
]
2 => array:1 [
"name" => "TRINCHERA L."
]
]
"ouvrage" => "42èmes Journées de Statistique de la Société Française de Statistique"
"keywords" => array:2 [
0 => "Analyse des données"
1 => "Problèmes de régressions inverses"
]
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Actes d'une conférence"
"en" => "Conference Proceedings"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "L'approche PLS aux modèles à équations structurelles (PLS Path Modeling, PLSPM) est couramment considérée comme une approche basée sur les composantes. Cette méthode a été récemment revisité en tant que cadre général pour l'analyse des tableaux multiples. Nous proposons ici deux nouvelles méthodes d'estimation des poids externes dans le cadre de la PLS-PM: le Mode PLScore et le Mode PLScow. Chaque mode est fondé sur l'utilisation de la régression PLS pour l'étape d'estimation externe. Toutefois, en Mode PLScore une régression PLS est exécutée sous les contraintes classiques de la PLS-PM de variance unitaire pour les scores des variables latentes , tandis que dans le Mode PLScow les poids externes sont contraints d'avoir une norme unitaire. Cette dernière contrainte est la contrainte classique de normalisation dans le cadre de la régression PLS. Nous montrons comment les deux nouveaux modes sont liées aux méthodes d'estimation externe classiques de la PLS-PM, c.-à-d. au Mode A et au Mode B, ainsi qu'au nouveau Mode A récemment proposé par Tenenhaus & Tenenhaus (2009)."
"en" => "PLS Path Modeling (PLS-PM) is classically regarded as a component-based approach to Structural Equation Models and has been more recently revisited as a general framework for multiple table analysis. Here we propose two new modes for estimating outer weights in PLS-PM: the PLScore Mode and the PLScow Mode. Both modes involve integrating a PLS Regression as an estimation technique within the outer estimation phase of PLS-PM. However, in PLScore Mode a PLS Regression is run under the classical PLS-PM constraints of unitary variance for the latent variable scores, while in PLScow Mode the outer weights are constrained to have a unitary norm thus importing the classical normalization constraints of PLS Regression. Moreover, we show how the newly proposed modes are linked to the standard Mode A and Mode B outer estimates in PLS-PM as well as to the New Mode A recently proposed in a criterion-based approach by Tenenhaus & Tenenhaus (2009)."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
27 => Essec\Faculty\Model\Contribution {#2425
#_index: "academ_contributions"
#_id: "4397"
#_source: array:18 [
"id" => "4397"
"slug" => "assessment-of-latent-class-detection-in-component-based-structural-equation-modeling-the-group-quality-index"
"yearMonth" => "2008-06"
"year" => "2008"
"title" => "Assessment of Latent Class Detection in Component-based Structural Equation Modeling: The Group Quality Index"
"description" => "TRINCHERA, L. et ESPOSITO VINZI, V. (2008). Assessment of Latent Class Detection in Component-based Structural Equation Modeling: The Group Quality Index. Dans: <i>First Joint Meeting of the Société Francophone de Classification and the Classification and Data Analysis Group of the Italian Statistical Society</i>. Edizioni Scientifiche Italiane, pp. 425-428."
"authors" => array:2 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "TRINCHERA L."
]
]
"ouvrage" => "First Joint Meeting of the Société Francophone de Classification and the Classification and Data Analysis Group of the Italian Statistical Society"
"keywords" => []
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "425-428"
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Actes d'une conférence"
"en" => "Conference Proceedings"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "Structural Equation Models assume homogeneity across the entire sample. In other words, all the units are supposed to be well represented by a unique model. Does not take into account heterogeneity among units may lead to biased results in terms of model parameters. That is why, nowadays, more attention is focused on techniques able to detect unobserved heterogeneity in Structural Equation Models. In particular, new techniques are been presented in PLS-PM framework, i.e. in a component-based Structural Equation Model framework. Among them REBUS-PLS is the unique that is completely coherent with the "soft" modeling spirit of PLS-PM. Here, a new index to assess detected unit partition will be presented: the Group Quality Index."
"en" => "Structural Equation Models assume homogeneity across the entire sample. In other words, all the units are supposed to be well represented by a unique model. Does not take into account heterogeneity among units may lead to biased results in terms of model parameters. That is why, nowadays, more attention is focused on techniques able to detect unobserved heterogeneity in Structural Equation Models. In particular, new techniques are been presented in PLS-PM framework, i.e. in a component-based Structural Equation Model framework. Among them REBUS-PLS is the unique that is completely coherent with the "soft" modeling spirit of PLS-PM. Here, a new index to assess detected unit partition will be presented: the Group Quality Index."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
28 => Essec\Faculty\Model\Contribution {#2426
#_index: "academ_contributions"
#_id: "4759"
#_source: array:18 [
"id" => "4759"
"slug" => "latent-class-detection-in-component-based-structural-equation-modeling"
"yearMonth" => "2008-06"
"year" => "2008"
"title" => "Latent Class Detection in Component-Based Structural Equation Modeling"
"description" => "ESPOSITO VINZI, V. et TRINCHERA, L. (2008). Latent Class Detection in Component-Based Structural Equation Modeling. Dans: <i>XLIV Scientific Meeting of the Italian Statistical Society (SIS). Proceedings of the XLIV SIS Scientific Meeting</i>. CLEUP, pp. 147-154."
"authors" => array:2 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "TRINCHERA L."
]
]
"ouvrage" => "XLIV Scientific Meeting of the Italian Statistical Society (SIS). Proceedings of the XLIV SIS Scientific Meeting"
"keywords" => array:1 [
0 => "Unobserved Heterogeneity"
]
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "147-154"
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Actes d'une conférence"
"en" => "Conference Proceedings"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "The paper focuses on techniques for detecting unit segments in component-based SEM byresponse-based techniques in the case of unknown (latent) discrete moderating factors,i.e. when both the number and the structure of the classes are not a priori known. The first part of the work briefly introduces both PLS Path Modeling and Generalized Structured Component Analysis (GSCA). Further, the paper presents ways to handle unobserved heterogeneity in component-based approaches to SEM. In this framework, the methods allowing response-based clustering in PLS Path Modeling framework are discussed, and then Fuzzy Clusterwise Generalized Structured Component Analysis of Hwang et al. (2007) is investigated as a technique for response-based clustering in GSCA."
"en" => "The paper focuses on techniques for detecting unit segments in component-based SEM byresponse-based techniques in the case of unknown (latent) discrete moderating factors,i.e. when both the number and the structure of the classes are not a priori known. The first part of the work briefly introduces both PLS Path Modeling and Generalized Structured Component Analysis (GSCA). Further, the paper presents ways to handle unobserved heterogeneity in component-based approaches to SEM. In this framework, the methods allowing response-based clustering in PLS Path Modeling framework are discussed, and then Fuzzy Clusterwise Generalized Structured Component Analysis of Hwang et al. (2007) is investigated as a technique for response-based clustering in GSCA."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
29 => Essec\Faculty\Model\Contribution {#2427
#_index: "academ_contributions"
#_id: "572"
#_source: array:18 [
"id" => "572"
"slug" => "a-quantile-composite-indicator-approach-for-the-measurement-of-equitable-and-sustainable-well-being-a-case-study-of-the-italian-provinces"
"yearMonth" => "2016-09"
"year" => "2016"
"title" => "A Quantile Composite-Indicator Approach for the Measurement of Equitable and Sustainable Well-Being: A Case Study of the Italian Provinces"
"description" => "DAVINO, C., DOLCE, P., TARALLI, S. et ESPOSITO VINZI, V. (2016). A Quantile Composite-Indicator Approach for the Measurement of Equitable and Sustainable Well-Being: A Case Study of the Italian Provinces. <i>Social Indicators Research</i>, 136(3), pp. 999-1029."
"authors" => array:4 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "DAVINO C."
]
2 => array:1 [
"name" => "DOLCE P."
]
3 => array:1 [
"name" => "TARALLI S."
]
]
"ouvrage" => ""
"keywords" => []
"updatedAt" => "2021-09-24 10:33:27"
"publicationUrl" => "https://link.springer.com/article/10.1007%2Fs11205-016-1453-8"
"publicationInfo" => array:3 [
"pages" => "999-1029"
"volume" => "136"
"number" => "3"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "An interesting measure for equitable and sustainable well-being has been proposed recently by the National Institute of Statistics in Italy and the National Council for Economy and Labour. It is called BES (from the Italian Benessere Equo e Sostenibile). A set of indicators, partitioned into several domains and themes, is used for measuring the BES. Taking into account prior knowledge of both the structure of this set of indicators and the relationships among them, the paper proposes a hierarchical composite model for measuring and modeling the BES of the Italian provinces. This hierarchical model allows us to synthesize individual indicators into single indexes in order to construct composite indicators at a global and a partial level. Moreover, we analyze the relationships among the different domains and themes as well as the effects of these on equitable and sustainable well-being, in order to search for strongly influential factors. In order to estimate the parameters of the model, we use both Partial Least Squares path modeling and a new method, called Quantile Composite-based path modeling. In particular, Partial Least Squares path modeling is used to estimate average effects in the network of relationships between variables, while with Quantile Composite-based path modeling we investigate whether the magnitude of these effects changes across different parts of the variable distributions, providing a more complete picture and uncovering specific local leveraging factors for improvement. A final ranking of the Italian provinces, according to the BES composite indicator, is also provided at the national level and for different geographic areas of Italy."
"en" => "An interesting measure for equitable and sustainable well-being has been proposed recently by the National Institute of Statistics in Italy and the National Council for Economy and Labour. It is called BES (from the Italian Benessere Equo e Sostenibile). A set of indicators, partitioned into several domains and themes, is used for measuring the BES. Taking into account prior knowledge of both the structure of this set of indicators and the relationships among them, the paper proposes a hierarchical composite model for measuring and modeling the BES of the Italian provinces. This hierarchical model allows us to synthesize individual indicators into single indexes in order to construct composite indicators at a global and a partial level. Moreover, we analyze the relationships among the different domains and themes as well as the effects of these on equitable and sustainable well-being, in order to search for strongly influential factors. In order to estimate the parameters of the model, we use both Partial Least Squares path modeling and a new method, called Quantile Composite-based path modeling. In particular, Partial Least Squares path modeling is used to estimate average effects in the network of relationships between variables, while with Quantile Composite-based path modeling we investigate whether the magnitude of these effects changes across different parts of the variable distributions, providing a more complete picture and uncovering specific local leveraging factors for improvement. A final ranking of the Italian provinces, according to the BES composite indicator, is also provided at the national level and for different geographic areas of Italy."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
30 => Essec\Faculty\Model\Contribution {#2428
#_index: "academ_contributions"
#_id: "621"
#_source: array:18 [
"id" => "621"
"slug" => "an-attitude-model-of-environmental-action-evidence-from-developing-and-developed-countries"
"yearMonth" => "2019-06"
"year" => "2019"
"title" => "An Attitude Model of Environmental Action: Evidence from Developing and Developed Countries"
"description" => "DAVINO, C., ESPOSITO VINZI, V., SANTACREU VASUT, E. et VRANCEANU, R. (2019). An Attitude Model of Environmental Action: Evidence from Developing and Developed Countries. <i>Social Indicators Research</i>, 143(2), pp. 811-838."
"authors" => array:4 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:3 [
"name" => "SANTACREU VASUT Estefania"
"bid" => "B00318975"
"slug" => "santacreu-vasut-estefania"
]
2 => array:3 [
"name" => "VRANCEANU Radu"
"bid" => "B00000524"
"slug" => "vranceanu-radu"
]
3 => array:1 [
"name" => "DAVINO Cristina"
]
]
"ouvrage" => ""
"keywords" => array:5 [
0 => "Environmental attitudes"
1 => "Development"
2 => "Culture"
3 => "Multivariate analysis"
4 => "Partial least squares"
]
"updatedAt" => "2021-09-24 10:33:27"
"publicationUrl" => "https://link.springer.com/article/10.1007%2Fs11205-018-1983-3"
"publicationInfo" => array:3 [
"pages" => "811-838"
"volume" => "143"
"number" => "2"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "This paper analyzes the determinants of stated individual support towards environmental action. The analysis is realized by means of an original Partial Least Squares Path model of Environmental Awareness-Social Capital-Action and it is based on survey data provided in the fifth wave of the World Values Survey (2005–2009) regarding 34.612 individuals from 42 different countries. Besides the global estimates obtained on the whole set of countries, the paper proposes a subsample analysis for developed and developing countries, as well as country analyses for four major economies: China, India, Germany and the United States. We find that environmental awareness and trust in not-for-profit organizations are important determinants of individual action in support of environmentally friendly policies. In general, trust in science and technology does not crowd-out individual support towards the environment."
"en" => "This paper analyzes the determinants of stated individual support towards environmental action. The analysis is realized by means of an original Partial Least Squares Path model of Environmental Awareness-Social Capital-Action and it is based on survey data provided in the fifth wave of the World Values Survey (2005–2009) regarding 34.612 individuals from 42 different countries. Besides the global estimates obtained on the whole set of countries, the paper proposes a subsample analysis for developed and developing countries, as well as country analyses for four major economies: China, India, Germany and the United States. We find that environmental awareness and trust in not-for-profit organizations are important determinants of individual action in support of environmentally friendly policies. In general, trust in science and technology does not crowd-out individual support towards the environment."
]
"authors_fields" => array:2 [
"fr" => "Economie"
"en" => "Economics"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
31 => Essec\Faculty\Model\Contribution {#2429
#_index: "academ_contributions"
#_id: "626"
#_source: array:18 [
"id" => "626"
"slug" => "an-empirical-investigation-of-the-antecedents-of-partnering-capability"
"yearMonth" => "2016-08"
"year" => "2016"
"title" => "An Empirical Investigation of the Antecedents of Partnering Capability"
"description" => "DE GIOVANNI, P., ESPOSITO VINZI, V. et COLICEV, A. (2016). An Empirical Investigation of the Antecedents of Partnering Capability. <i>International Journal of Production Economics</i>, 178, pp. 144-153."
"authors" => array:3 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "DE GIOVANNI Pietro"
]
2 => array:1 [
"name" => "COLICEV A."
]
]
"ouvrage" => ""
"keywords" => array:6 [
0 => "Partnering capability"
1 => "Departmental integration"
2 => "Customer service"
3 => "Performance"
4 => "PLS-PM"
5 => "IMPA"
]
"updatedAt" => "2021-02-02 16:16:18"
"publicationUrl" => "https://www.sciencedirect.com/science/article/abs/pii/S0925527316300846"
"publicationInfo" => array:3 [
"pages" => "144-153"
"volume" => "178"
"number" => null
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "In this paper, we propose a new approach to evaluating firms’ Partnering Capability. While previous research treats Partnering Capability as an exogenous factor, we take into account its antecedents and thus conceive it as endogenous. Our motivations are driven by the fact that firms ex-ante evaluate their partners by assessing their Partnering Capability. We focus on departmental integration, customer service, and economic and operational performance as key antecedents of Partnering Capability. Our empirical findings show that Partnering Capability is directly induced by operational performance and departmental integration. In addition, customer service along with departmental integration generates a chain of indirect effects due to economic and operational performance. Finally, we investigate the importance-performance matrix analysis (IMPA) that further identifies the managerial levers to enhance Partnering Capability."
"en" => "In this paper, we propose a new approach to evaluating firms’ Partnering Capability. While previous research treats Partnering Capability as an exogenous factor, we take into account its antecedents and thus conceive it as endogenous. Our motivations are driven by the fact that firms ex-ante evaluate their partners by assessing their Partnering Capability. We focus on departmental integration, customer service, and economic and operational performance as key antecedents of Partnering Capability. Our empirical findings show that Partnering Capability is directly induced by operational performance and departmental integration. In addition, customer service along with departmental integration generates a chain of indirect effects due to economic and operational performance. Finally, we investigate the importance-performance matrix analysis (IMPA) that further identifies the managerial levers to enhance Partnering Capability."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
32 => Essec\Faculty\Model\Contribution {#2430
#_index: "academ_contributions"
#_id: "629"
#_source: array:18 [
"id" => "629"
"slug" => "an-empirical-operationalization-of-countries-destination-competitiveness-using-partial-least-squares-modelling"
"yearMonth" => "2013-10"
"year" => "2013"
"title" => "An Empirical Operationalization of Countries' Destination Competitiveness Using Partial Least Squares Modelling"
"description" => "ASSAKER, G., HALLAK, R., ESPOSITO VINZI, V. et O'CONNOR, P. (2013). An Empirical Operationalization of Countries' Destination Competitiveness Using Partial Least Squares Modelling. <i>Journal of Travel Research</i>, 53(1), pp. 26-43."
"authors" => array:4 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "ASSAKER G."
]
2 => array:1 [
"name" => "HALLAK R."
]
3 => array:1 [
"name" => "O'CONNOR Peter"
]
]
"ouvrage" => ""
"keywords" => array:5 [
0 => "Destination competitiveness"
1 => "Partial least squares modeling (PLSPM)"
2 => "Structural equation modeling (SEM)"
3 => "Latent variables (LVs) scores"
4 => "Cause indicators"
]
"updatedAt" => "2021-02-02 16:16:18"
"publicationUrl" => "https://journals.sagepub.com/doi/10.1177/0047287513481275"
"publicationInfo" => array:3 [
"pages" => "26-43"
"volume" => "53"
"number" => "1"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "Growth in tourism has resulted in escalating competition among destinations. Understanding destination competitiveness and its determinant factors is thus critical to tourism researchers and policy makers. Using partial least squares path modeling (PLSPM) on a cross-sectional sample of 154 countries, this study examines relationships among destination competitiveness and its predictors, including the economy, natural environment, and infrastructure."
"en" => "Growth in tourism has resulted in escalating competition among destinations. Understanding destination competitiveness and its determinant factors is thus critical to tourism researchers and policy makers. Using partial least squares path modeling (PLSPM) on a cross-sectional sample of 154 countries, this study examines relationships among destination competitiveness and its predictors, including the economy, natural environment, and infrastructure."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
33 => Essec\Faculty\Model\Contribution {#2431
#_index: "academ_contributions"
#_id: "2280"
#_source: array:18 [
"id" => "2280"
"slug" => "preface-special-issue-on-the-6th-international-symposium-on-business-and-industrial-statistics-isbis-6"
"yearMonth" => "2009-08"
"year" => "2009"
"title" => "Préface : Special issue on the 6th International Symposium on Business and Industrial Statistics (ISBIS-6)"
"description" => "ESPOSITO VINZI, V. (2009). Préface : Special issue on the 6th International Symposium on Business and Industrial Statistics (ISBIS-6)., 4(25), pp. 421-424."
"authors" => array:1 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
]
"ouvrage" => ""
"keywords" => []
"updatedAt" => "2020-12-17 17:55:06"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "421-424"
"volume" => "4"
"number" => "25"
]
"type" => array:2 [
"fr" => "Préfaces / Introductions de revue"
"en" => "Prefaces of a journal"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
34 => Essec\Faculty\Model\Contribution {#2432
#_index: "academ_contributions"
#_id: "2575"
#_source: array:18 [
"id" => "2575"
"slug" => "teaching-and-research-in-an-international-context"
"yearMonth" => "2016-04"
"year" => "2016"
"title" => "Teaching and Research in an International Context"
"description" => "ESPOSITO VINZI, V. (2016). Teaching and Research in an International Context. <i>Reflets Hors-Série ESSEC Knowledge</i>, (2), pp. 16-17."
"authors" => array:1 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
]
"ouvrage" => ""
"keywords" => []
"updatedAt" => "2021-07-13 14:30:56"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "16-17"
"volume" => null
"number" => "2"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue professionnelle"
"en" => "Professional journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
35 => Essec\Faculty\Model\Contribution {#2433
#_index: "academ_contributions"
#_id: "896"
#_source: array:18 [
"id" => "896"
"slug" => "covariance-versus-component-based-estimations-of-performance-in-green-supply-chain-management"
"yearMonth" => "2012-02"
"year" => "2012"
"title" => "Covariance versus Component-Based Estimations of Performance in Green Supply Chain Management"
"description" => "DE GIOVANNI, P. et ESPOSITO VINZI, V. (2012). Covariance versus Component-Based Estimations of Performance in Green Supply Chain Management. <i>International Journal of Production Economics</i>, 135(2), pp. 907-916."
"authors" => array:2 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "DE GIOVANNI Pietro"
]
]
"ouvrage" => ""
"keywords" => array:5 [
0 => "Green supply chain management"
1 => "Environmental performance"
2 => "Economic performance"
3 => "PLS Path Modeling"
4 => "Formative indicators"
]
"updatedAt" => "2021-02-02 16:16:18"
"publicationUrl" => "https://www.sciencedirect.com/science/article/abs/pii/S0925527311004634"
"publicationInfo" => array:3 [
"pages" => "907-916"
"volume" => "135"
"number" => "2"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "We investigate the relationships between environmental management (EM) and performance to verify: whether the implementation of an effective internal environmental is a firm’s pre-condition to belong to a green supply chain; which type of environmental practices (either internal or external) contribute the most to increasing a firm’s performances; and whether performing the environment translates into higher economic performance. We use structural equation modeling for testing our research hypotheses on a large sample of Italian firms and estimate the structural paths between constructs by means of both covariance- and component-based approaches."
"en" => "We investigate the relationships between environmental management (EM) and performance to verify: whether the implementation of an effective internal environmental is a firm’s pre-condition to belong to a green supply chain; which type of environmental practices (either internal or external) contribute the most to increasing a firm’s performances; and whether performing the environment translates into higher economic performance. We use structural equation modeling for testing our research hypotheses on a large sample of Italian firms and estimate the structural paths between constructs by means of both covariance- and component-based approaches."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
36 => Essec\Faculty\Model\Contribution {#2434
#_index: "academ_contributions"
#_id: "1162"
#_source: array:18 [
"id" => "1162"
"slug" => "examining-the-effect-of-novelty-seeking-satisfaction-and-destination-image-on-tourists-return-pattern-a-two-factor-non-linear-latent-growth-model"
"yearMonth" => "2011-08"
"year" => "2011"
"title" => "Examining the Effect of Novelty Seeking, Satisfaction, and Destination Image on Tourists' Return Pattern: A Two Factor, Non-linear Latent Growth Model"
"description" => "ASSAKER, G., ESPOSITO VINZI, V. et O'CONNOR, P. (2011). Examining the Effect of Novelty Seeking, Satisfaction, and Destination Image on Tourists' Return Pattern: A Two Factor, Non-linear Latent Growth Model. <i>Tourism Management</i>, 32(4), pp. 890-901."
"authors" => array:3 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "ASSAKER G."
]
2 => array:1 [
"name" => "O'CONNOR Peter"
]
]
"ouvrage" => ""
"keywords" => array:5 [
0 => "Destination image"
1 => "Latent growth model"
2 => "Novelty seeking"
3 => "Revisit intention"
4 => "Satisfaction"
]
"updatedAt" => "2021-02-02 16:16:18"
"publicationUrl" => "https://www.sciencedirect.com/science/article/abs/pii/S0261517710001627"
"publicationInfo" => array:3 [
"pages" => "890-901"
"volume" => "32"
"number" => "4"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "Avec beaucoup de destinations dépendantes de la fidélisation de leur clientèle, l’intention de retourner sur un même lieu est devenue un sujet de recherche important. Alors que les facteurs qui motivent les raisons d’un retour à une destination évoluent dans le temps, ce report propose l’usage d’une courbe de croissance latente afin de modéliser la trajectoire du développement concernant les comportements liés à la fidélisation. Le modèle proposé a été testé dans AMOS 16.0 en se servant des méthodologies SEM afin d’enquêter sur les effets de la recherche de la nouveauté, l’image de la destination et le niveau général de satisfaction concernant l’intention de revisiter une destination en se servant des informations récoltées parmi les voyageurs français, anglais, et allemand. Les résultats indiquent que la recherche de nouveauté et un niveau de satisfaction bas parmi des voyages réduit l’intention d’un retour immédiat. Contrairement, une image positive de la destination renforce les intentions d’un retour immédiat et futur."
"en" => "With many destinations relying on repeat business, intention to revisit has become an important research topic. As revisit intention changes over time, this paper proposes the use of a latent growth curve to model the developmental trajectory of return behavior. The proposed model was tested in two steps in AMOS 16.0 using SEM methodologies to investigate the effects of novelty seeking, destination image and overall satisfaction levels across intent to revisit trajectories using data collected among French, English, and German travelers. Findings indicate that both novelty seeking and low satisfaction among travelers temper immediate intent to return. Conversely, a positive image of the destination enhances both immediate and future intentions to return."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
37 => Essec\Faculty\Model\Contribution {#2435
#_index: "academ_contributions"
#_id: "1182"
#_source: array:18 [
"id" => "1182"
"slug" => "extending-a-tourism-causality-network-a-cross-country-multigroup-empirical-analysis"
"yearMonth" => "2011-11"
"year" => "2011"
"title" => "Extending a Tourism Causality Network: A Cross-Country, Multigroup Empirical Analysis"
"description" => "ASSAKER, G., ESPOSITO VINZI, V. et O'CONNOR, P. (2011). Extending a Tourism Causality Network: A Cross-Country, Multigroup Empirical Analysis. <i>Tourism and Hospitality Research (formerly International Journal of Tourism and Hospitality Research: The Surrey Quarterly Review)</i>, 11(4), pp. 258-277."
"authors" => array:3 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "ASSAKER G."
]
2 => array:1 [
"name" => "O'CONNOR Peter"
]
]
"ouvrage" => ""
"keywords" => array:5 [
0 => "Developed countries"
1 => "Less-developed countries"
2 => "Moderating effect"
3 => "Multigroup analysis"
4 => "Supply-side variables"
]
"updatedAt" => "2021-02-02 16:16:18"
"publicationUrl" => "https://journals.sagepub.com/doi/abs/10.1177/1467358411418815"
"publicationInfo" => array:3 [
"pages" => "258-277"
"volume" => "11"
"number" => "4"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => """
Cette étude donne un aperçu d'une technique statistique puissante pour tester l'invariance de modèle à travers plusieurs groupes. De cette manière, elle fournit des indications pour les décideurs et contribue à la littérature sur la prévision des demandes de tourisme par la validation et l'extension des résultats antérieurs sur les facteurs de l'offre comment l’offre influence la demande en matière de tourisme. Plus précisément, cette étude prend en considération un modèle structurel a priori validé pour les relations entre des données construites dans l'économie, la société, l’environnement et le tourisme dans 162 pays, examinant la mesure dans laquelle le modèle a été invariant à travers deux groupes d'observations isolées : pays développés et moins développés. Lors de tests, le modèle a priori n'a pas été reproduit à travers les deux groupes. Au lieu de cela on a utilisé un modèle réduit, incorporant des données construites concernant la société, l'environnement et le tourisme afin de comparer et tester les écarts des paramètres à travers les deux groupes à l'aide d’analyse d'échantillonnage multi-groupes AMOS 16.0. Les résultats indiquent que le chemin des coefficients est égal à travers les groupes.\n
Il existe une relation positive entre les données concernant la société et l'environnement, alors qu'il existait une relation significative positive semblable entre les données concernant la société et l'environnement et le tourisme, respectivement.
"""
"en" => "This study provides insights into a powerful statistical technique to test model invariance across multiple groups. In doing so, it provides insights for policymakers and contributes to the literature on tourism demand forecasting by validating and extending previous results on how supply-side factors influence tourism demand. Specifically, this study considered an a priori validated structural model for relationships among the economy, society, environment and tourism constructs in 162 countries, examining the extent to which the model was invariant across two groups of isolated observations: developed and less-developed countries. Upon testing, the a priori model did not replicate across both groups. Instead a reduced model, incorporating the society, environment and tourism constructs only was used to compare and test for variances in parameters across the two groups using multigroup analysis sampling in AMOS 16.0. The results indicated that path coefficients were equal across groups. A positive relationship existed between the society and environment constructs, while a similar positive significant relationship existed between the society and environment constructs from one side and tourism, respectively."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
"en" => "Information Systems, Decision Sciences and Statistics"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
38 => Essec\Faculty\Model\Contribution {#2436
#_index: "academ_contributions"
#_id: "4969"
#_source: array:18 [
"id" => "4969"
"slug" => "pls-path-modeling-some-recent-methodological-developments-a-software-integrated-in-xlstat-and-its-application-to-customer-satisfaction-studies"
"yearMonth" => "2007-01"
"year" => "2007"
"title" => "PLS Path Modeling: Some Recent Methodological Developments, a Software Integrated in XLSTAT and its Application to Customer Satisfaction Studies"
"description" => "ESPOSITO VINZI, V., FAHMY, T., CHATELIN, Y.M. et TENENHAUS, M. (2007). PLS Path Modeling: Some Recent Methodological Developments, a Software Integrated in XLSTAT and its Application to Customer Satisfaction Studies. Dans: <i>2007 World Marketing Congress (CD-Rom)</i>. Academy of Marketing Science (AMS)."
"authors" => array:4 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "FAHMY T."
]
2 => array:1 [
"name" => "CHATELIN Y.M."
]
3 => array:1 [
"name" => "TENENHAUS M."
]
]
"ouvrage" => "2007 World Marketing Congress (CD-Rom)"
"keywords" => array:2 [
0 => "Customer Satisfaction"
1 => "Structural Equation Modeling"
]
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Actes d'une conférence"
"en" => "Conference Proceedings"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "With structural equation modeling based on the PLS Path Modeling and the XLSTAT-PLeaSure software, we show a way to represent and model how customer satisfaction is related to manifest and latent variables, using data that are available through different sources, and respecting the conceptual logics of marketing in a mathematical framework."
"en" => "With structural equation modeling based on the PLS Path Modeling and the XLSTAT-PLeaSure software, we show a way to represent and model how customer satisfaction is related to manifest and latent variables, using data that are available through different sources, and respecting the conceptual logics of marketing in a mathematical framework."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
39 => Essec\Faculty\Model\Contribution {#2437
#_index: "academ_contributions"
#_id: "5286"
#_source: array:18 [
"id" => "5286"
"slug" => "a-comprehensive-partial-least-squares-approach-to-component-based-structural-equation-modeling"
"yearMonth" => "2008-07"
"year" => "2008"
"title" => "A Comprehensive Partial Least Squares Approach to Component-Based Structural Equation Modeling"
"description" => "TRINCHERA, L. et ESPOSITO VINZI, V. (2008). A Comprehensive Partial Least Squares Approach to Component-Based Structural Equation Modeling. Dans: 32nd Annual Conference of the German Classification Society (GfKl)."
"authors" => array:2 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "TRINCHERA L."
]
]
"ouvrage" => "32nd Annual Conference of the German Classification Society (GfKl)"
"keywords" => array:1 [
0 => "Multicollinearity"
]
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "PLS Path Modeling (PLS-PM) is generally meant as a component-based approach to structural equation modeling that privileges a prediction oriented discovery process to the statistical testing of causal hypotheses. Nowadays, formative relationships are more and more used in real applications but pose a few problems for the statistical estimation and interpretation. It seems quite natural to introduce a PLS Regression (PLS-R) external estimation mode within the PLS-PM algorithm so as to overcome the mentioned problems, preserve the formative relationships and still remain coherent with the component-based and prediction-oriented nature of PLS-PM. Here, the main issues concerning the use of formative indicators in PLS-PM are investigated."
"en" => "PLS Path Modeling (PLS-PM) is generally meant as a component-based approach to structural equation modeling that privileges a prediction oriented discovery process to the statistical testing of causal hypotheses. Nowadays, formative relationships are more and more used in real applications but pose a few problems for the statistical estimation and interpretation. It seems quite natural to introduce a PLS Regression (PLS-R) external estimation mode within the PLS-PM algorithm so as to overcome the mentioned problems, preserve the formative relationships and still remain coherent with the component-based and prediction-oriented nature of PLS-PM. Here, the main issues concerning the use of formative indicators in PLS-PM are investigated."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
40 => Essec\Faculty\Model\Contribution {#2438
#_index: "academ_contributions"
#_id: "5287"
#_source: array:18 [
"id" => "5287"
"slug" => "a-comprehensive-pls-rationale-for-multidimensional-blocks-in-predictive-path-models"
"yearMonth" => "2010-07"
"year" => "2010"
"title" => "A Comprehensive PLS Rationale for Multidimensional Blocks in Predictive Path Models"
"description" => "ESPOSITO VINZI, V. et RUSSOLILLO, G. (2010). A Comprehensive PLS Rationale for Multidimensional Blocks in Predictive Path Models. Dans: ISBIS-2010: International Symposium on Business and Industrial Statistics."
"authors" => array:2 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "RUSSOLILLO G."
]
]
"ouvrage" => "ISBIS-2010: International Symposium on Business and Industrial Statistics"
"keywords" => []
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "When studying complex systems, the difficulty of analysis is mainly due to the theoretically hypothesized network of somehow hidden causal relationships. This leads to the problem of extracting information from uncertain models rather than modeling uncertainty. PLS Path Modeling (PLS-PM) is classically regarded as a component-based approach to causal networks and has been more recently revisited as a general framework for multi-block data analysis. We propose two new modes for estimating outer weights in PLS-PM by PLS Regression: the PLScore Mode and the PLScow Mode. Both modes involve integrating a PLS Regression as an estimation technique within the outer estimation phase of PLS-PM. However, in PLScore Mode a PLS Regression is run under the classical PLS-PM constraints of unitary variance for the LV scores, while in PLScow Mode the outer weights are constrained to have a unitary norm thus importing the classical normalization constraints of PLS Regression."
"en" => "When studying complex systems, the difficulty of analysis is mainly due to the theoretically hypothesized network of somehow hidden causal relationships. This leads to the problem of extracting information from uncertain models rather than modeling uncertainty. PLS Path Modeling (PLS-PM) is classically regarded as a component-based approach to causal networks and has been more recently revisited as a general framework for multi-block data analysis. We propose two new modes for estimating outer weights in PLS-PM by PLS Regression: the PLScore Mode and the PLScow Mode. Both modes involve integrating a PLS Regression as an estimation technique within the outer estimation phase of PLS-PM. However, in PLScore Mode a PLS Regression is run under the classical PLS-PM constraints of unitary variance for the LV scores, while in PLScow Mode the outer weights are constrained to have a unitary norm thus importing the classical normalization constraints of PLS Regression."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
41 => Essec\Faculty\Model\Contribution {#2439
#_index: "academ_contributions"
#_id: "5308"
#_source: array:18 [
"id" => "5308"
"slug" => "a-joint-partial-least-squares-component-based-approach-to-structural-equation-modeling-and-multi-block-data-analysis"
"yearMonth" => "2009-09"
"year" => "2009"
"title" => "A Joint Partial Least Squares Component-based Approach to Structural Equation Modeling and Multi-block Data Analysis"
"description" => "ESPOSITO VINZI, V. (2009). A Joint Partial Least Squares Component-based Approach to Structural Equation Modeling and Multi-block Data Analysis. Dans: PLS'09 - 6th International Conference on Partial Least Squares and Related Methods."
"authors" => array:1 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
]
"ouvrage" => "PLS'09 - 6th International Conference on Partial Least Squares and Related Methods"
"keywords" => array:2 [
0 => "Multicollinerity"
1 => "Multidimensional Blocks"
]
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "Partial Least Squares Path Modelling (PLS-PM) is generally meant as a component-based approach to structural equation models and multi-block data analysis that privileges a prediction oriented discovery process to the statistical testing of causal hypotheses. In case of formative relationships in the measurement model between the manifest variables and their corresponding latent ones, PLS-PM estimates the outer weights by means of multiple OLS regressions. These regressions might often yield unstable results in case of strong correlations between manifest variables while being not feasible when the number of observations is smaller than the number of variables or in presence of missing data. An external estimation mode based on PLS regression (PLS-R) may overcome these problems while preserving the formative nature of the measurement model. At the same time, this innovative estimation mode provides new tools for interpreting the components, validating the results and improving the predictions in PLS-PM. PLS-R is also profitably extended to: the internal estimation step of PLS-PM as a generalization of path weighting scheme, the estimation of path coefficients in structural models affected by strongly correlated latent variables or missing scores. Finally, the implementation of PLS regression in the estimation steps of PLS Path Modeling defines a regularized comprehensive PLS approach that yields more stable and robust results while enriching interpretation."
"en" => "Partial Least Squares Path Modelling (PLS-PM) is generally meant as a component-based approach to structural equation models and multi-block data analysis that privileges a prediction oriented discovery process to the statistical testing of causal hypotheses. In case of formative relationships in the measurement model between the manifest variables and their corresponding latent ones, PLS-PM estimates the outer weights by means of multiple OLS regressions. These regressions might often yield unstable results in case of strong correlations between manifest variables while being not feasible when the number of observations is smaller than the number of variables or in presence of missing data. An external estimation mode based on PLS regression (PLS-R) may overcome these problems while preserving the formative nature of the measurement model. At the same time, this innovative estimation mode provides new tools for interpreting the components, validating the results and improving the predictions in PLS-PM. PLS-R is also profitably extended to: the internal estimation step of PLS-PM as a generalization of path weighting scheme, the estimation of path coefficients in structural models affected by strongly correlated latent variables or missing scores. Finally, the implementation of PLS regression in the estimation steps of PLS Path Modeling defines a regularized comprehensive PLS approach that yields more stable and robust results while enriching interpretation."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
42 => Essec\Faculty\Model\Contribution {#2440
#_index: "academ_contributions"
#_id: "5309"
#_source: array:18 [
"id" => "5309"
"slug" => "a-joint-use-of-pls-regression-and-pls-path-modelling-for-a-data-analysis-approach-to-latent-variable-modelling"
"yearMonth" => "2009-08"
"year" => "2009"
"title" => "A Joint Use of PLS Regression and PLS Path Modelling for a Data Analysis Approach to Latent Variable Modelling"
"description" => "ESPOSITO VINZI, V., RUSSOLILLO, G. et TRINCHERA, L. (2009). A Joint Use of PLS Regression and PLS Path Modelling for a Data Analysis Approach to Latent Variable Modelling. Dans: 57th Session of the International Statistical Institute (ISI)."
"authors" => array:3 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "RUSSOLILLO G."
]
2 => array:1 [
"name" => "TRINCHERA L."
]
]
"ouvrage" => "57th Session of the International Statistical Institute (ISI)"
"keywords" => []
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "Structural Equation Models (SEMs) are widely used to model complex causal relations as the ones de?ning human behaviors. Several techniques exist to estimate SEM parameters. Among them the PLS Path Modeling (PLS- PM) algorithm is the most widely used technique. In particular, PLS-PM allows taking into account formative blocks of manifest variables. A new way to compute outer weights in the case of formative block of manifest variables has been recently proposed by Esposito Vinzi et al. [2009]. This approach involves using PLS Regression (PLS-R) in order to compute outer weights even in the case of multicollinearity among the manifest variables of the same block. However, PLS Regression supposes linearity in relations between variables. Following the work by Esposito Vinzi et al. [2009], we decide to use a non-linear approach to PLS-R in order to estimate measurement model parameters in a non-linear PLS-PM approach to SEMs."
"en" => "Structural Equation Models (SEMs) are widely used to model complex causal relations as the ones de?ning human behaviors. Several techniques exist to estimate SEM parameters. Among them the PLS Path Modeling (PLS- PM) algorithm is the most widely used technique. In particular, PLS-PM allows taking into account formative blocks of manifest variables. A new way to compute outer weights in the case of formative block of manifest variables has been recently proposed by Esposito Vinzi et al. [2009]. This approach involves using PLS Regression (PLS-R) in order to compute outer weights even in the case of multicollinearity among the manifest variables of the same block. However, PLS Regression supposes linearity in relations between variables. Following the work by Esposito Vinzi et al. [2009], we decide to use a non-linear approach to PLS-R in order to estimate measurement model parameters in a non-linear PLS-PM approach to SEMs."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
43 => Essec\Faculty\Model\Contribution {#2441
#_index: "academ_contributions"
#_id: "5320"
#_source: array:18 [
"id" => "5320"
"slug" => "a-non-linear-regularized-component-based-approach-to-structural-equation-modeling"
"yearMonth" => "2009-09"
"year" => "2009"
"title" => "A Non Linear Regularized Component-based Approach to Structural Equation Modeling"
"description" => "ESPOSITO VINZI, V., RUSSOLILLO, G. et TRINCHERA, L. (2009). A Non Linear Regularized Component-based Approach to Structural Equation Modeling."
"authors" => array:3 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "RUSSOLILLO G."
]
2 => array:1 [
"name" => "TRINCHERA L."
]
]
"ouvrage" => ""
"keywords" => []
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "We propose an extension of the PLS Path Modeling algorithm for dealing with non linear relationships as well as with problematic covariance structures that need regularization."
"en" => "We propose an extension of the PLS Path Modeling algorithm for dealing with non linear relationships as well as with problematic covariance structures that need regularization."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
44 => Essec\Faculty\Model\Contribution {#2442
#_index: "academ_contributions"
#_id: "5322"
#_source: array:18 [
"id" => "5322"
"slug" => "a-partial-least-squares-comprehensive-environment"
"yearMonth" => "2008-09"
"year" => "2008"
"title" => "A Partial Least Squares Comprehensive Environment:"
"description" => "ESPOSITO VINZI, V. (2008). A Partial Least Squares Comprehensive Environment: Dans: 7th International Conference on Social Science Methodology, RC33 - Logic and Methodology in Sociology."
"authors" => array:1 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
]
"ouvrage" => "7th International Conference on Social Science Methodology, RC33 - Logic and Methodology in Sociology"
"keywords" => array:1 [
0 => "Multicollinearity"
]
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "PLS Path Modelling (PLS-PM) is generally meant as a component-based approach to structural equation modelling that privileges a prediction oriented discovery process to the statistical testing of causal hypotheses. In case of formative relationships between manifest and latent variables, PLS-PM implies multiple OLS regressions. They might yield unstable results in case of strong correlations between manifest variables while being not feasible when the number of observations is smaller than the number of variables nor in case of missing data. We explore PLS regression (PLS-R) as an external estimation mode to overcome the mentioned problems while preserving formative relationships and being coherent with the component-based and prediction-oriented nature of PLS-PM. PLS-R is also fruitfully extended to the path weighting internal estimation scheme and the estimation of path coefficients."
"en" => "PLS Path Modelling (PLS-PM) is generally meant as a component-based approach to structural equation modelling that privileges a prediction oriented discovery process to the statistical testing of causal hypotheses. In case of formative relationships between manifest and latent variables, PLS-PM implies multiple OLS regressions. They might yield unstable results in case of strong correlations between manifest variables while being not feasible when the number of observations is smaller than the number of variables nor in case of missing data. We explore PLS regression (PLS-R) as an external estimation mode to overcome the mentioned problems while preserving formative relationships and being coherent with the component-based and prediction-oriented nature of PLS-PM. PLS-R is also fruitfully extended to the path weighting internal estimation scheme and the estimation of path coefficients."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
45 => Essec\Faculty\Model\Contribution {#2443
#_index: "academ_contributions"
#_id: "5374"
#_source: array:18 [
"id" => "5374"
"slug" => "advances-in-composite-based-path-modeling-for-synthetic-indicators"
"yearMonth" => "2015-10"
"year" => "2015"
"title" => "Advances in Composite-Based Path Modeling for Synthetic Indicators"
"description" => "ESPOSITO VINZI, V., TRINCHERA, L. et RUSSOLILLO, G. (2015). Advances in Composite-Based Path Modeling for Synthetic Indicators. Dans: 10th Scientific Meeting of the Classification and Data Analysis Group."
"authors" => array:3 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "TRINCHERA L."
]
2 => array:1 [
"name" => "RUSSOLILLO G."
]
]
"ouvrage" => "10th Scientific Meeting of the Classification and Data Analysis Group"
"keywords" => []
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
46 => Essec\Faculty\Model\Contribution {#2444
#_index: "academ_contributions"
#_id: "5414"
#_source: array:18 [
"id" => "5414"
"slug" => "an-integrated-pls-regression-based-approach-for-multidimensional-blocks-in-pls-path-modeling"
"yearMonth" => "2010-05"
"year" => "2010"
"title" => "An integrated PLS Regression-based approach for multidimensional blocks in PLS Path Modeling"
"description" => "ESPOSITO VINZI, V., RUSSOLILLO, G. et TRINCHERA, L. (2010). An integrated PLS Regression-based approach for multidimensional blocks in PLS Path Modeling."
"authors" => array:3 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "RUSSOLILLO G."
]
2 => array:1 [
"name" => "TRINCHERA L."
]
]
"ouvrage" => ""
"keywords" => []
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "We present how the integration of PLS regression modules within the algorithm of PLS Path Modeling can be very helpful to improve performance of predictive path models between blocks of variables related to different concepts. The objective is to develop analyses that take into account the multidimensionality of the different blocks as well as the prediction performance of the specified model."
"en" => "We present how the integration of PLS regression modules within the algorithm of PLS Path Modeling can be very helpful to improve performance of predictive path models between blocks of variables related to different concepts. The objective is to develop analyses that take into account the multidimensionality of the different blocks as well as the prediction performance of the specified model."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
47 => Essec\Faculty\Model\Contribution {#2445
#_index: "academ_contributions"
#_id: "5448"
#_source: array:18 [
"id" => "5448"
"slug" => "assessing-the-performance-of-rebus-pls-for-latent-class-identification-in-pls-path-modeling-a-simulation-study"
"yearMonth" => "2008-06"
"year" => "2008"
"title" => "Assessing the Performance of REBUS-PLS for Latent Class Identification in PLS Path Modeling: a Simulation Study"
"description" => "TRINCHERA, L. et ESPOSITO VINZI, V. (2008). Assessing the Performance of REBUS-PLS for Latent Class Identification in PLS Path Modeling: a Simulation Study. Dans: XLIV Scientific Meeting of the Italian Statistical Society."
"authors" => array:2 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "TRINCHERA L."
]
]
"ouvrage" => "XLIV Scientific Meeting of the Italian Statistical Society"
"keywords" => []
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "A simple marketing type model is the reference model to assess the REBUS-PLS capability to identify a priori unknown (latent) classes of units. Two latent classes showing different local models are supposed to exist. Each one is composed of 200 units. Four different situations are investigated: i.e. when the unobserved heterogeneity is focused only on the structural model, when it concerns only the measurement model, when units are heterogeneous as regards both the structural and the measurement models, and when the data are homogeneous as regards the model parameters. REBUS-PLS algorithm has shown to be able to detect unobserved heterogeneity not only when it affects the whole model, but also when it focuses only on the structural model or on the measurement model."
"en" => "A simple marketing type model is the reference model to assess the REBUS-PLS capability to identify a priori unknown (latent) classes of units. Two latent classes showing different local models are supposed to exist. Each one is composed of 200 units. Four different situations are investigated: i.e. when the unobserved heterogeneity is focused only on the structural model, when it concerns only the measurement model, when units are heterogeneous as regards both the structural and the measurement models, and when the data are homogeneous as regards the model parameters. REBUS-PLS algorithm has shown to be able to detect unobserved heterogeneity not only when it affects the whole model, but also when it focuses only on the structural model or on the measurement model."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
48 => Essec\Faculty\Model\Contribution {#2446
#_index: "academ_contributions"
#_id: "5601"
#_source: array:18 [
"id" => "5601"
"slug" => "component-based-approaches-to-multi-block-path-modeling-with-business-and-industrial-applications"
"yearMonth" => "2012-06"
"year" => "2012"
"title" => "Component-Based Approaches to Multi-Block Path Modeling with Business and Industrial Applications"
"description" => "ESPOSITO VINZI, V. (2012). Component-Based Approaches to Multi-Block Path Modeling with Business and Industrial Applications. Dans: International Symposium on Business and Industrial Statistics 2012 (ISBIS 2012)."
"authors" => array:1 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
]
"ouvrage" => "International Symposium on Business and Industrial Statistics 2012 (ISBIS 2012)"
"keywords" => []
"updatedAt" => "2021-07-13 14:31:07"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
49 => Essec\Faculty\Model\Contribution {#2447
#_index: "academ_contributions"
#_id: "5602"
#_source: array:18 [
"id" => "5602"
"slug" => "component-based-approaches-to-structural-equation-modeling-and-multi-block-analysis-a-comparative-study"
"yearMonth" => "2011-05"
"year" => "2011"
"title" => "Component-based approaches to Structural Equation Modeling and Multi-Block Analysis: A Comparative Study"
"description" => "ESPOSITO VINZI, V. et TRINCHERA, L. (2011). Component-based approaches to Structural Equation Modeling and Multi-Block Analysis: A Comparative Study. Dans: ESSEC-SUPELEC Workshop Series on “PLS Developments” #5."
"authors" => array:2 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "TRINCHERA L."
]
]
"ouvrage" => "ESSEC-SUPELEC Workshop Series on “PLS Developments” #5"
"keywords" => []
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
50 => Essec\Faculty\Model\Contribution {#2448
#_index: "academ_contributions"
#_id: "5603"
#_source: array:18 [
"id" => "5603"
"slug" => "component-based-approaches-to-structural-equation-models-methodological-issues-and-empirical-performances"
"yearMonth" => "2012-06"
"year" => "2012"
"title" => "Component-based Approaches to Structural Equation Models: Methodological Issues and Empirical Performances"
"description" => "ESPOSITO VINZI, V. (2012). Component-based Approaches to Structural Equation Models: Methodological Issues and Empirical Performances. Dans: International Symposium on Business and Industrial Statistics."
"authors" => array:1 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
]
"ouvrage" => "International Symposium on Business and Industrial Statistics"
"keywords" => []
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
51 => Essec\Faculty\Model\Contribution {#2449
#_index: "academ_contributions"
#_id: "5604"
#_source: array:18 [
"id" => "5604"
"slug" => "component-based-multi-block-path-modeling-for-building-composite-indicators"
"yearMonth" => "2014-11"
"year" => "2014"
"title" => "Component-based Multi-block Path Modeling for building Composite Indicators"
"description" => "TRINCHERA, L., RUSSOLILLO, G. et ESPOSITO VINZI, V. (2014). Component-based Multi-block Path Modeling for building Composite Indicators. Dans: Conference of European Statistics Stakeholders."
"authors" => array:3 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "TRINCHERA L."
]
2 => array:1 [
"name" => "RUSSOLILLO G."
]
]
"ouvrage" => "Conference of European Statistics Stakeholders"
"keywords" => []
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
52 => Essec\Faculty\Model\Contribution {#2450
#_index: "academ_contributions"
#_id: "5605"
#_source: array:18 [
"id" => "5605"
"slug" => "component-based-predictive-and-exploratory-path-modeling-and-multi-block-data-analysis"
"yearMonth" => "2013-08"
"year" => "2013"
"title" => "Component-based Predictive and Exploratory Path Modeling and Multi-block Data Analysis"
"description" => "TRINCHERA, L. et ESPOSITO VINZI, V. (2013). Component-based Predictive and Exploratory Path Modeling and Multi-block Data Analysis. Dans: 59th World Statistics Congress of the International Statistical Institute (ISI)."
"authors" => array:2 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "TRINCHERA L."
]
]
"ouvrage" => "59th World Statistics Congress of the International Statistical Institute (ISI)"
"keywords" => []
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
53 => Essec\Faculty\Model\Contribution {#2451
#_index: "academ_contributions"
#_id: "5606"
#_source: array:18 [
"id" => "5606"
"slug" => "component-based-predictive-path-modeling-by-means-of-projections-to-latent-structures-model-assessment-and-interpretation-features-with-business-related-applications"
"yearMonth" => "2014-11"
"year" => "2014"
"title" => "Component-based Predictive Path Modeling by means of Projections to Latent Structures: Model Assessment and Interpretation Features with Business-related Applications"
"description" => "ESPOSITO VINZI, V., TRINCHERA, L. et RUSSOLILL0, G. (2014). Component-based Predictive Path Modeling by means of Projections to Latent Structures: Model Assessment and Interpretation Features with Business-related Applications. Dans: ISI Regional Statistics Conference 2014 (ISI-RSC 2014): Statistical Science for a Better Tomorrow."
"authors" => array:3 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "TRINCHERA L."
]
2 => array:1 [
"name" => "RUSSOLILL0 G."
]
]
"ouvrage" => "ISI Regional Statistics Conference 2014 (ISI-RSC 2014): Statistical Science for a Better Tomorrow"
"keywords" => []
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
54 => Essec\Faculty\Model\Contribution {#2452
#_index: "academ_contributions"
#_id: "5665"
#_source: array:18 [
"id" => "5665"
"slug" => "correlated-component-pls-type-regression-with-variable-selection-features-for-large-datasets"
"yearMonth" => "2010-12"
"year" => "2010"
"title" => "Correlated Component PLS-type Regression with Variable Selection Features for Large Datasets"
"description" => "TRINCHERA, L., ESPOSITO VINZI, V., TENENHAUS, A. et TENENHAUS, M. (2010). Correlated Component PLS-type Regression with Variable Selection Features for Large Datasets. Dans: Computing & Statistics (ERCIM'10)."
"authors" => array:4 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "TRINCHERA L."
]
2 => array:1 [
"name" => "TENENHAUS A."
]
3 => array:1 [
"name" => "TENENHAUS M."
]
]
"ouvrage" => "Computing & Statistics (ERCIM'10)"
"keywords" => []
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => """
The analysis of landscape matrices, i.e. matrices having more columns (variables) than rows (observations), is a challenging task in several domains.\n
Two different kinds of problems arise when dealing with landscape matrices. The first refers to computational and numerical problems.\n
The second deals with the difficulty in assessing and understanding the results. Partial Least Squares (PLS) methods are classical feature extraction tools that work in the case of high-dimensional data sets. Since PLS methods do not require matrices inversion or diagonalization, they allow us to solve computational problems. However, results interpretation is still a hard problem when facing with very high-dimensional data sets. Nowadays interest is increasing in developing new PLS methods able to be, at the same time, a feature extraction tool and a feature selection method (i.e. a variable selection method). Here a new PLS-type algorithm including variable selection and correlated components will be presented. The use of correlated components instead of orthogonal components allows us to take into account so called suppressor variables, i.e. variables having no direct effect on the response variables but improving prediction by suppressing irrelevant variation in the lower-order components. This is of main importance in order to obtain predictive variable selection.
"""
"en" => """
The analysis of landscape matrices, i.e. matrices having more columns (variables) than rows (observations), is a challenging task in several domains.\n
Two different kinds of problems arise when dealing with landscape matrices. The first refers to computational and numerical problems.\n
The second deals with the difficulty in assessing and understanding the results. Partial Least Squares (PLS) methods are classical feature extraction tools that work in the case of high-dimensional data sets. Since PLS methods do not require matrices inversion or diagonalization, they allow us to solve computational problems. However, results interpretation is still a hard problem when facing with very high-dimensional data sets. Nowadays interest is increasing in developing new PLS methods able to be, at the same time, a feature extraction tool and a feature selection method (i.e. a variable selection method). Here a new PLS-type algorithm including variable selection and correlated components will be presented. The use of correlated components instead of orthogonal components allows us to take into account so called suppressor variables, i.e. variables having no direct effect on the response variables but improving prediction by suppressing irrelevant variation in the lower-order components. This is of main importance in order to obtain predictive variable selection.
"""
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
55 => Essec\Faculty\Model\Contribution {#2453
#_index: "academ_contributions"
#_id: "5688"
#_source: array:18 [
"id" => "5688"
"slug" => "current-issues-and-future-challenges-in-component-based-structure"
"yearMonth" => "2008-09"
"year" => "2008"
"title" => "Current Issues and Future Challenges in Component-based Structure"
"description" => "ESPOSITO VINZI, V. (2008). Current Issues and Future Challenges in Component-based Structure. Dans: 7th International Conference on Social Science Methodology, RC33 - Logic and Methodology in Sociology."
"authors" => array:1 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
]
"ouvrage" => "7th International Conference on Social Science Methodology, RC33 - Logic and Methodology in Sociology"
"keywords" => array:2 [
0 => "GSCA"
1 => "PLSMP"
]
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "The component-based approach to Structural Equation Modeling (SEM) was initiated by Herman Wold under the name "PLS" (Partial Least Squares). Hwang and Takane (Psychometrika, 2004) have recently proposed a new component-based SEM method named Generalized Structured Component Analysis. Generally speaking, component-based SEM can be considered as a generalized data analysis approach to multiple tables connected by a network of "causal" relationships. As such, this approach is mainly used for scores computation and privileges a prediction oriented discovery process to the statistical testing of causal hypotheses. More specifically, PLS is a limited information two-step method essentially based on a set of interdependent simple and multiple OLS regressions both for the measurement and the structural model. The simplicity of the PLS algorithm makes it feasible also for (very) small samples. The recently proposed GSCA is, instead, a full information method that optimizes a global criterion. A few comparisons between covariance-based and component-based SEM have shown reasons in favour of one approach or the other depending on different factors such as, for instance, the nature of the model, the research objective, the sample size, the definition of latent variables by means of reflective or formative manifest variables, the estimation and practical meaning of factor scores. With reference to component-based SEM and, specifically, to PLS Path Modeling, we focus on current important issues such as the optimization of a criterion, the measurement model misspecification, the treatment of formative relationships between manifest and latent variables, the estimation and the intepretation of scores in presence of strongly correlated latent variables, the possibility of constraining parameter estimates as well as on some other open issues representing interesting themes for current and future researches."
"en" => "The component-based approach to Structural Equation Modeling (SEM) was initiated by Herman Wold under the name "PLS" (Partial Least Squares). Hwang and Takane (Psychometrika, 2004) have recently proposed a new component-based SEM method named Generalized Structured Component Analysis. Generally speaking, component-based SEM can be considered as a generalized data analysis approach to multiple tables connected by a network of "causal" relationships. As such, this approach is mainly used for scores computation and privileges a prediction oriented discovery process to the statistical testing of causal hypotheses. More specifically, PLS is a limited information two-step method essentially based on a set of interdependent simple and multiple OLS regressions both for the measurement and the structural model. The simplicity of the PLS algorithm makes it feasible also for (very) small samples. The recently proposed GSCA is, instead, a full information method that optimizes a global criterion. A few comparisons between covariance-based and component-based SEM have shown reasons in favour of one approach or the other depending on different factors such as, for instance, the nature of the model, the research objective, the sample size, the definition of latent variables by means of reflective or formative manifest variables, the estimation and practical meaning of factor scores. With reference to component-based SEM and, specifically, to PLS Path Modeling, we focus on current important issues such as the optimization of a criterion, the measurement model misspecification, the treatment of formative relationships between manifest and latent variables, the estimation and the intepretation of scores in presence of strongly correlated latent variables, the possibility of constraining parameter estimates as well as on some other open issues representing interesting themes for current and future researches."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
56 => Essec\Faculty\Model\Contribution {#2454
#_index: "academ_contributions"
#_id: "5741"
#_source: array:18 [
"id" => "5741"
"slug" => "different-approaches-to-structural-equation-modelling-in-presence-of-a-group-structure-contributions-to-the-analysis-of-environmental-initiatives-and-performances-of-italian-firms"
"yearMonth" => "2009-05"
"year" => "2009"
"title" => "Different Approaches to Structural Equation Modelling in Presence of a Group Structure: Contributions to the Analysis of Environmental Initiatives and Performances of Italian Firms"
"description" => "ESPOSITO VINZI, V. et DE GIOVANNI, P. (2009). Different Approaches to Structural Equation Modelling in Presence of a Group Structure: Contributions to the Analysis of Environmental Initiatives and Performances of Italian Firms. Dans: EURISBIS'09 - European Regional Meeting of the International Society for Business and Industrial Statistics."
"authors" => array:2 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "DE GIOVANNI Pietro"
]
]
"ouvrage" => "EURISBIS'09 - European Regional Meeting of the International Society for Business and Industrial Statistics"
"keywords" => array:2 [
0 => "Multi-group Analysis"
1 => "Structural Equation Modeling"
]
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "In spite of its valuable effectiveness, the use of Multi-group Analysis in Structural Equation Modelling (SEM) appears quite new in operations management and business and somehow limited to the contribution by Koufteros and Marcoulides (2006). This paper extends this methodology by introducing a Two-Way Multi-group Analysis for analyzing the performances of Italian firms subjected/not subjected to Emission Trading (ET) regime, and characterized by Green Supply Chain Management (GSCM) with environmental collaboration/monitoring. The presence of these two classification criteria (ET regime and GSCM) implies the need of developing a two-way analysis of variance on latent variables defined by the economic performance and its driving factors. This research addresses this issue by investigating a sample of 335 Italian firms and proposing a Two-Way Multi-group Analysis in SEM."
"en" => "In spite of its valuable effectiveness, the use of Multi-group Analysis in Structural Equation Modelling (SEM) appears quite new in operations management and business and somehow limited to the contribution by Koufteros and Marcoulides (2006). This paper extends this methodology by introducing a Two-Way Multi-group Analysis for analyzing the performances of Italian firms subjected/not subjected to Emission Trading (ET) regime, and characterized by Green Supply Chain Management (GSCM) with environmental collaboration/monitoring. The presence of these two classification criteria (ET regime and GSCM) implies the need of developing a two-way analysis of variance on latent variables defined by the economic performance and its driving factors. This research addresses this issue by investigating a sample of 335 Italian firms and proposing a Two-Way Multi-group Analysis in SEM."
]
"authors_fields" => array:2 [
"fr" => "Management"
"en" => "Management"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
57 => Essec\Faculty\Model\Contribution {#2455
#_index: "academ_contributions"
#_id: "6010"
#_source: array:18 [
"id" => "6010"
"slug" => "formative-indicators-in-structural-equation-models-and-highly-correlated-latent-variable-scores-a-full-pls-based-approach"
"yearMonth" => "2008-07"
"year" => "2008"
"title" => "Formative Indicators in Structural Equation Models and Highly Correlated Latent Variable Scores: a Full PLS-based Approach"
"description" => "ESPOSITO VINZI, V. et TRINCHERA, L. (2008). Formative Indicators in Structural Equation Models and Highly Correlated Latent Variable Scores: a Full PLS-based Approach. Dans: International Symposium on Business and Industrial Statistics with emphasis on Quantitative Analytics for Banking, Finance and Insurance."
"authors" => array:2 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "TRINCHERA L."
]
]
"ouvrage" => "International Symposium on Business and Industrial Statistics with emphasis on Quantitative Analytics for Banking, Finance and Insurance"
"keywords" => array:1 [
0 => "Collinearity"
]
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "This work considers the implementation of PLS regression principles within the PLS Path Modeling framework in order to cope with two problems often encountered in component-based structural equation modeling: correlated formative indicators and latent variable scores. The proposal shows to be profitably usable in application related to business and related areas."
"en" => "This work considers the implementation of PLS regression principles within the PLS Path Modeling framework in order to cope with two problems often encountered in component-based structural equation modeling: correlated formative indicators and latent variable scores. The proposal shows to be profitably usable in application related to business and related areas."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
58 => Essec\Faculty\Model\Contribution {#2456
#_index: "academ_contributions"
#_id: "6033"
#_source: array:18 [
"id" => "6033"
"slug" => "fuzzy-pls-path-modeling-for-crisp-and-interval-data-a-new-tool-for-handling-sensory-data"
"yearMonth" => "2007-03"
"year" => "2007"
"title" => "Fuzzy PLS Path Modeling for Crisp and Interval Data: A New Tool for Handling Sensory Data"
"description" => "ROMANO, R., ESPOSITO VINZI, V. et PALUMBO, F. (2007). Fuzzy PLS Path Modeling for Crisp and Interval Data: A New Tool for Handling Sensory Data."
"authors" => array:3 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "ROMANO R."
]
2 => array:1 [
"name" => "PALUMBO F."
]
]
"ouvrage" => ""
"keywords" => array:1 [
0 => "Multi-block Statistical Methods"
]
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "In sensory analysis a panel of assessors scores blocks of sensory attributes for profiling products, thus yielding a three-way table crossing assessors, attributes and products. In this context, it is important to evaluate the panel performance as well as to synthesize the scores into a global assessment to investigate differences between products. This paper shows the advantages of either interval/fuzzy coding and fuzzy PLS path modeling in the context of sensory analysis. Specifically, as many path models as assessors are considered and compared in terms of fuzzy path coefficients so as to detect eventual differences between assessors. Furthermore, an ad hoc interval coding is used to collapse the tables over the assessors into a two-way table partitioned by the ttributes. A fuzzy PLS path modeling provides two sets of synthesized assessments: the overall latent scores for each product and the partial latent scores for the different blocks of attributes."
"en" => "In sensory analysis a panel of assessors scores blocks of sensory attributes for profiling products, thus yielding a three-way table crossing assessors, attributes and products. In this context, it is important to evaluate the panel performance as well as to synthesize the scores into a global assessment to investigate differences between products. This paper shows the advantages of either interval/fuzzy coding and fuzzy PLS path modeling in the context of sensory analysis. Specifically, as many path models as assessors are considered and compared in terms of fuzzy path coefficients so as to detect eventual differences between assessors. Furthermore, an ad hoc interval coding is used to collapse the tables over the assessors into a two-way table partitioned by the ttributes. A fuzzy PLS path modeling provides two sets of synthesized assessments: the overall latent scores for each product and the partial latent scores for the different blocks of attributes."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
59 => Essec\Faculty\Model\Contribution {#2457
#_index: "academ_contributions"
#_id: "6034"
#_source: array:18 [
"id" => "6034"
"slug" => "fuzzy-pls-path-modeling-for-latent-class-analysis-capturing-unobserved-heterogeneity-in-consumers-preference"
"yearMonth" => "2007-08"
"year" => "2007"
"title" => "Fuzzy PLS Path Modeling for Latent Class Analysis: Capturing Unobserved Heterogeneity in Consumers' Preference"
"description" => "ESPOSITO VINZI, V., ROMANO, R. et TRINCHERA, L. (2007). Fuzzy PLS Path Modeling for Latent Class Analysis: Capturing Unobserved Heterogeneity in Consumers' Preference."
"authors" => array:3 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "ROMANO R."
]
2 => array:1 [
"name" => "TRINCHERA L."
]
]
"ouvrage" => ""
"keywords" => array:1 [
0 => "Customer Satisfaction"
]
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "PLS Path Modeling represents a useful tool to model consumer's preferences. Nevertheless, the definition of a unique model for all the consumers may hide differences in their behaviour. Hence, models accounting for such heterogeneity afford more efficient strategies. Unobserved heterogeneity among statistical units requires to look for latent classes as well as to estimate local models. In the present work, a new method is proposed to overcome a few shortcomings of the already existing methods, such as the strong normality assumption on latent variables in the case of finite mixture models, or the lack of an optimizing criterion in the Typological approach. The goal will be achieved combining fuzzy approach to PLS Path Modeling and PLS-TPM. As a matter of fact, the fuzzy approach embeds residual information inside the model coefficients (expressed as intervals) thus permitting to search for latent classes by referring to the fuzziness of coefficients."
"en" => "PLS Path Modeling represents a useful tool to model consumer's preferences. Nevertheless, the definition of a unique model for all the consumers may hide differences in their behaviour. Hence, models accounting for such heterogeneity afford more efficient strategies. Unobserved heterogeneity among statistical units requires to look for latent classes as well as to estimate local models. In the present work, a new method is proposed to overcome a few shortcomings of the already existing methods, such as the strong normality assumption on latent variables in the case of finite mixture models, or the lack of an optimizing criterion in the Typological approach. The goal will be achieved combining fuzzy approach to PLS Path Modeling and PLS-TPM. As a matter of fact, the fuzzy approach embeds residual information inside the model coefficients (expressed as intervals) thus permitting to search for latent classes by referring to the fuzziness of coefficients."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
60 => Essec\Faculty\Model\Contribution {#2458
#_index: "academ_contributions"
#_id: "6035"
#_source: array:18 [
"id" => "6035"
"slug" => "fuzzy-pls-path-modeling-for-latent-class-detection"
"yearMonth" => "2007-03"
"year" => "2007"
"title" => "Fuzzy PLS Path Modeling for Latent Class Detection"
"description" => "ESPOSITO VINZI, V., TRINCHERA, L. et ROMANO, R. (2007). Fuzzy PLS Path Modeling for Latent Class Detection."
"authors" => array:3 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "TRINCHERA L."
]
2 => array:1 [
"name" => "ROMANO R."
]
]
"ouvrage" => ""
"keywords" => array:3 [
0 => "Heterogeneity of Behaviours"
1 => "Latent Classes"
2 => "Statistical Models for Structural Equations"
]
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "PLS Path Modeling is a component-based technique to study linear relations among multiple blocks of indicators in a structural equation model. This approach assumes homogeneity among statistical units thus preventing the detection of latent classes. This paper proposes to combine the fuzzy approach to PLS Path Modeling in order to overcome a few shortcomings of already existing methods, such as the strong normality assumption on latent variables in the case of finite mixture models, or the lack of an optimizing criterion in the Typological approach. As a matter of fact, the fuzzy approach embeds residual information inside the model coefficients (expressed as intervals) thus permitting to search for latent classes by referring to the fuzziness of coefficients."
"en" => "PLS Path Modeling is a component-based technique to study linear relations among multiple blocks of indicators in a structural equation model. This approach assumes homogeneity among statistical units thus preventing the detection of latent classes. This paper proposes to combine the fuzzy approach to PLS Path Modeling in order to overcome a few shortcomings of already existing methods, such as the strong normality assumption on latent variables in the case of finite mixture models, or the lack of an optimizing criterion in the Typological approach. As a matter of fact, the fuzzy approach embeds residual information inside the model coefficients (expressed as intervals) thus permitting to search for latent classes by referring to the fuzziness of coefficients."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
61 => Essec\Faculty\Model\Contribution {#2459
#_index: "academ_contributions"
#_id: "6202"
#_source: array:18 [
"id" => "6202"
"slug" => "integrated-approaches-for-pls-path-modeling-pls-regression-estimation-modes-and-probabilistic-networks"
"yearMonth" => "2010-07"
"year" => "2010"
"title" => "Integrated Approaches for PLS Path Modeling: PLS Regression Estimation Modes and Probabilistic Networks"
"description" => "ESPOSITO VINZI, V., JOUFFE, L., RUSSOLILLO, G., TRINCHERA, L. et ZARGOUSH, M. (2010). Integrated Approaches for PLS Path Modeling: PLS Regression Estimation Modes and Probabilistic Networks. Dans: 10th SENSOMETRICS Meeting."
"authors" => array:5 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "JOUFFE L."
]
2 => array:1 [
"name" => "RUSSOLILLO G."
]
3 => array:1 [
"name" => "TRINCHERA L."
]
4 => array:1 [
"name" => "ZARGOUSH M."
]
]
"ouvrage" => "10th SENSOMETRICS Meeting"
"keywords" => array:1 [
0 => "Latent Variables"
]
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "The study of complex multi-block systems, as the ones relevant for sensometrics, may imply the analysis of a network of hypothesized, but often hidden, "causal" or predictive relationships between blocks of manifest variables summarized by latent variables. PLS Path Modeling (PLS-PM) is classically regarded as a component-based approach to Structural Equation Models (SEM) and has been more recently revisited as a general framework for multi-block data analysis. Both the measurement model (manifest-latent links) and the structural model (latent-latent links) are usually specified by theoretical hypotheses of the researcher and can be eventually (but only slightly) modified in case the statistical modeling of empirical data provides a different evidence. A PLS regression-based approach integrated within PLS-PM allows estimating outer weights and path coefficients in presence of multidimensional blocks (with uni-dimensionality and full-dimensionality as special cases), multicollinearity, missing data or landscape tables (e.g., few products as compared to the multitude of judges expressing preferences). Causal or predictive modeling based on SEM or PLS-PM may be limited for diagnosis by the theoretically hypothesized causal network. Bayesian probabilistic networks are instead limited in differentiating between manifest and latent variables as well as between causal and spurious relationships. These two approaches can be combined with the objective of discovering and validating a hidden network of relationships between manifest variables based on probabilistic causation. Such unsupervised learning approach can be applied to manifest variables prior to PLS-PM or to latent variable scores yielded by PLS-PM with different insights for both theory and practice in terms of diagnosis and prediction."
"en" => "The study of complex multi-block systems, as the ones relevant for sensometrics, may imply the analysis of a network of hypothesized, but often hidden, "causal" or predictive relationships between blocks of manifest variables summarized by latent variables. PLS Path Modeling (PLS-PM) is classically regarded as a component-based approach to Structural Equation Models (SEM) and has been more recently revisited as a general framework for multi-block data analysis. Both the measurement model (manifest-latent links) and the structural model (latent-latent links) are usually specified by theoretical hypotheses of the researcher and can be eventually (but only slightly) modified in case the statistical modeling of empirical data provides a different evidence. A PLS regression-based approach integrated within PLS-PM allows estimating outer weights and path coefficients in presence of multidimensional blocks (with uni-dimensionality and full-dimensionality as special cases), multicollinearity, missing data or landscape tables (e.g., few products as compared to the multitude of judges expressing preferences). Causal or predictive modeling based on SEM or PLS-PM may be limited for diagnosis by the theoretically hypothesized causal network. Bayesian probabilistic networks are instead limited in differentiating between manifest and latent variables as well as between causal and spurious relationships. These two approaches can be combined with the objective of discovering and validating a hidden network of relationships between manifest variables based on probabilistic causation. Such unsupervised learning approach can be applied to manifest variables prior to PLS-PM or to latent variable scores yielded by PLS-PM with different insights for both theory and practice in terms of diagnosis and prediction."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
62 => Essec\Faculty\Model\Contribution {#2460
#_index: "academ_contributions"
#_id: "6268"
#_source: array:18 [
"id" => "6268"
"slug" => "knowledge-extraction-by-investigating-model-uncertainty-thorugh-predictive-path-modeling-and-probabilistic-networks"
"yearMonth" => "2010-09"
"year" => "2010"
"title" => "Knowledge Extraction by Investigating Model Uncertainty thorugh Predictive Path Modeling and Probabilistic Networks"
"description" => "ESPOSITO VINZI, V. et ZARGOUSH, M. (2010). Knowledge Extraction by Investigating Model Uncertainty thorugh Predictive Path Modeling and Probabilistic Networks. Dans: Joint Meeting (GfKj-CLADAG'10)."
"authors" => array:2 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "ZARGOUSH M."
]
]
"ouvrage" => "Joint Meeting (GfKj-CLADAG'10)"
"keywords" => []
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => """
When studying complex systems the difficulty of analysis is mainly due to the complex network of hypothesized, but often hidden, and presumably causal (or at least predictive) relationships between tangible (i.e. manifest and directly observed) phenomena or intangible (i.e. theoretical and indirectly observed) concepts. It is somehow the problem of extracting knowledge from uncertain models rather than\n
modeling uncertainty in a specific model defined on some a priori available information.\n
The basic elements of causal networks (in a covariance-based framework) or predictive path models (in a component-based approach) are the manifest variables,\n
the corresponding latent variables (or factors) and the network of dependence/causal relationships between the latter ones. Both the measurement model (manifest-latent\n
links) and the structural model (latent-latent links) are usually specified according to theoretical hypotheses of the researcher and can be eventually (but only slightly)\n
modified in case the statistical modeling of empirical data does not confirm the whole set of hypotheses thus providing a different or new evidence. Further knowledge\n
may be extracted if induction by automatic learning is merged to the evaluation of probabilistic networks.
"""
"en" => """
When studying complex systems the difficulty of analysis is mainly due to the complex network of hypothesized, but often hidden, and presumably causal (or at least predictive) relationships between tangible (i.e. manifest and directly observed) phenomena or intangible (i.e. theoretical and indirectly observed) concepts. It is somehow the problem of extracting knowledge from uncertain models rather than\n
modeling uncertainty in a specific model defined on some a priori available information.\n
The basic elements of causal networks (in a covariance-based framework) or predictive path models (in a component-based approach) are the manifest variables,\n
the corresponding latent variables (or factors) and the network of dependence/causal relationships between the latter ones. Both the measurement model (manifest-latent\n
links) and the structural model (latent-latent links) are usually specified according to theoretical hypotheses of the researcher and can be eventually (but only slightly)\n
modified in case the statistical modeling of empirical data does not confirm the whole set of hypotheses thus providing a different or new evidence. Further knowledge\n
may be extracted if induction by automatic learning is merged to the evaluation of probabilistic networks.
"""
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
63 => Essec\Faculty\Model\Contribution {#2461
#_index: "academ_contributions"
#_id: "6373"
#_source: array:18 [
"id" => "6373"
"slug" => "latent-segments-detection-in-pls-path-modeling-a-tool-to-capture-unobserved-heterogeneity-in-customers-preferences"
"yearMonth" => "2007-09"
"year" => "2007"
"title" => "Latent Segments Detection in PLS Path Modeling: A Tool to Capture Unobserved Heterogeneity in Customers' Preferences"
"description" => "TRINCHERA, L., ROMANO, R. et ESPOSITO VINZI, V. (2007). Latent Segments Detection in PLS Path Modeling: A Tool to Capture Unobserved Heterogeneity in Customers' Preferences."
"authors" => array:3 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "TRINCHERA L."
]
2 => array:1 [
"name" => "ROMANO R."
]
]
"ouvrage" => ""
"keywords" => array:3 [
0 => "REBUS"
1 => "Response Based Classification"
2 => "Unobserved Heterogeneity"
]
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "PLS Path Modeling represents a useful tool to model complex causal relations between blocks of variables in customers' preferences studies. When customers do have different behaviors, models accounting for unobserved heterogeneity permit to outline targeted and more efficient strategies, while a single model for all the customers might hide relevant differences in their behaviors. Unobserved heterogeneity implies to identify segments of units that exhibit similar behaviors, i.e. a response-based classification. This approach requires to look for latent segments as well as to estimate 'local' models. Different methods have been proposed for capturing unobserved heterogeneity in PLS Path Modeling. In this paper, the REsponse Based Units Segmentation (REBUS-PLS) approach is presented. REBUS-PLS is a distribution-free approach that aims to yield a classification of units which leads to 'local' models with an improved predictive performance as compared to a global model."
"en" => "PLS Path Modeling represents a useful tool to model complex causal relations between blocks of variables in customers' preferences studies. When customers do have different behaviors, models accounting for unobserved heterogeneity permit to outline targeted and more efficient strategies, while a single model for all the customers might hide relevant differences in their behaviors. Unobserved heterogeneity implies to identify segments of units that exhibit similar behaviors, i.e. a response-based classification. This approach requires to look for latent segments as well as to estimate 'local' models. Different methods have been proposed for capturing unobserved heterogeneity in PLS Path Modeling. In this paper, the REsponse Based Units Segmentation (REBUS-PLS) approach is presented. REBUS-PLS is a distribution-free approach that aims to yield a classification of units which leads to 'local' models with an improved predictive performance as compared to a global model."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
64 => Essec\Faculty\Model\Contribution {#2462
#_index: "academ_contributions"
#_id: "6677"
#_source: array:18 [
"id" => "6677"
"slug" => "methodological-links-and-empirical-comparisons-between-generalized-structured-component-analysis-pls-path-modeling-and-maximum-sum-of-explained-variance"
"yearMonth" => "2012-05"
"year" => "2012"
"title" => "Methodological links and empirical comparisons between Generalized Structured Component Analysis, PLS Path Modeling and Maximum Sum of Explained Variance"
"description" => "ESPOSITO VINZI, V., TRINCHERA, L., CHIN, W. et HENSELER, J. (2012). Methodological links and empirical comparisons between Generalized Structured Component Analysis, PLS Path Modeling and Maximum Sum of Explained Variance. Dans: 7th International Conference on Partial Least Squares and Related Methods."
"authors" => array:4 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "TRINCHERA L."
]
2 => array:1 [
"name" => "CHIN W."
]
3 => array:1 [
"name" => "HENSELER J."
]
]
"ouvrage" => "7th International Conference on Partial Least Squares and Related Methods"
"keywords" => []
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
65 => Essec\Faculty\Model\Contribution {#2463
#_index: "academ_contributions"
#_id: "6718"
#_source: array:18 [
"id" => "6718"
"slug" => "multi-component-estimation-of-pls-predictive-path-modeling"
"yearMonth" => "2011-08"
"year" => "2011"
"title" => "Multi-component Estimation of PLS Predictive Path Modeling"
"description" => "TRINCHERA, L., RUSSOLILLO, G. et ESPOSITO VINZI, V. (2011). Multi-component Estimation of PLS Predictive Path Modeling. Dans: 58th World Statistics Congress of the International Statistical Institute (ISI 2011)."
"authors" => array:3 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "TRINCHERA L."
]
2 => array:1 [
"name" => "RUSSOLILLO G."
]
]
"ouvrage" => "58th World Statistics Congress of the International Statistical Institute (ISI 2011)"
"keywords" => []
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => """
We present a new approach to estimating outer weights in PLS Path Modeling that is fully based on the PLS principle. Two new modes are presented for estimating the measurement model: PLScore Mode with standardized scores and oriented to maximizing correlations between\n
latent variables (LVs); PLScow Mode with constrained weights and oriented to maximizing covariances between LVs. Both modes involve integrating a PLS Regression as an estimation technique within the outer estimation phase of PLS-PM. However, in PLScore Mode a PLS Regression is run under the classical PLS-PM constraints of unitary variance for the LV scores, while in PLScow Mode the outer weights are constrained to have a unitary norm thus importing the classical normalization constraints of PLS Regression.
"""
"en" => """
We present a new approach to estimating outer weights in PLS Path Modeling that is fully based on the PLS principle. Two new modes are presented for estimating the measurement model: PLScore Mode with standardized scores and oriented to maximizing correlations between\n
latent variables (LVs); PLScow Mode with constrained weights and oriented to maximizing covariances between LVs. Both modes involve integrating a PLS Regression as an estimation technique within the outer estimation phase of PLS-PM. However, in PLScore Mode a PLS Regression is run under the classical PLS-PM constraints of unitary variance for the LV scores, while in PLScow Mode the outer weights are constrained to have a unitary norm thus importing the classical normalization constraints of PLS Regression.
"""
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
66 => Essec\Faculty\Model\Contribution {#2464
#_index: "academ_contributions"
#_id: "6719"
#_source: array:18 [
"id" => "6719"
"slug" => "multidimensional-and-non-metric-extensions-of-pls-path-modeling-for-synthetic-indicators"
"yearMonth" => "2015-05"
"year" => "2015"
"title" => "Multidimensional and Non-Metric Extensions of PLS Path Modeling for Synthetic Indicators"
"description" => "ESPOSITO VINZI, V., TRINCHERA, L. et RUSSOLILLO, G. (2015). Multidimensional and Non-Metric Extensions of PLS Path Modeling for Synthetic Indicators. Dans: Dealing with Complexity in Society: from Plurality of Data to Synthetic Indicators."
"authors" => array:3 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "TRINCHERA L."
]
2 => array:1 [
"name" => "RUSSOLILLO G."
]
]
"ouvrage" => "Dealing with Complexity in Society: from Plurality of Data to Synthetic Indicators"
"keywords" => []
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "A composite indicator is a mathematical combination of single indicators that represent different dimensions of a concept whose description is the objective of the analysis. If all the indicators refer to a single latent concept, classical MDA techniques, like Factorial Analysis or Principal Component Analysis, can be used. These techniques allow us to assess the impact of each indicator on the composite indicator. However, often the several indicators used in the construction of a composite indicator express different aspects of a complex phenomenon, and so they can be conceptually split in several blocks of indicators. Each block can be resumed by a composite indicator, which is considered causative with respect to a second-order composite indicator. We refer to this kind of index, which is a synthesis of composite indicators, as complex indicator."
"en" => "A composite indicator is a mathematical combination of single indicators that represent different dimensions of a concept whose description is the objective of the analysis. If all the indicators refer to a single latent concept, classical MDA techniques, like Factorial Analysis or Principal Component Analysis, can be used. These techniques allow us to assess the impact of each indicator on the composite indicator. However, often the several indicators used in the construction of a composite indicator express different aspects of a complex phenomenon, and so they can be conceptually split in several blocks of indicators. Each block can be resumed by a composite indicator, which is considered causative with respect to a second-order composite indicator. We refer to this kind of index, which is a synthesis of composite indicators, as complex indicator."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
67 => Essec\Faculty\Model\Contribution {#2465
#_index: "academ_contributions"
#_id: "6720"
#_source: array:18 [
"id" => "6720"
"slug" => "multidimensional-latent-variables-in-pls-path-modeling"
"yearMonth" => "2012-08"
"year" => "2012"
"title" => "Multidimensional Latent Variables in PLS Path Modeling"
"description" => "TRINCHERA, L., RUSSOLILLO, G., CAPELLINI, A. et ESPOSITO VINZI, V. (2012). Multidimensional Latent Variables in PLS Path Modeling. Dans: 20th International Conference on Computational Statistics 2012."
"authors" => array:4 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "TRINCHERA L."
]
2 => array:1 [
"name" => "RUSSOLILLO G."
]
3 => array:1 [
"name" => "CAPELLINI A."
]
]
"ouvrage" => "20th International Conference on Computational Statistics 2012"
"keywords" => []
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
68 => Essec\Faculty\Model\Contribution {#2466
#_index: "academ_contributions"
#_id: "6746"
#_source: array:18 [
"id" => "6746"
"slug" => "new-variable-selection-methods-in-case-of-many-predictors"
"yearMonth" => "2011-05"
"year" => "2011"
"title" => "New Variable Selection Methods in Case of Many Predictors"
"description" => "ESPOSITO VINZI, V., TRINCHERA, L., TENENHAUS, A. et TENENHAUS, M. (2011). New Variable Selection Methods in Case of Many Predictors. Dans: ESSEC-SUPELEC Workshop Series on “PLS Developments” #5."
"authors" => array:4 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "TRINCHERA L."
]
2 => array:1 [
"name" => "TENENHAUS A."
]
3 => array:1 [
"name" => "TENENHAUS M."
]
]
"ouvrage" => "ESSEC-SUPELEC Workshop Series on “PLS Developments” #5"
"keywords" => []
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
69 => Essec\Faculty\Model\Contribution {#2467
#_index: "academ_contributions"
#_id: "6895"
#_source: array:18 [
"id" => "6895"
"slug" => "pls-partial-least-squares-path-modeling-methodological-foundations-and-the-xlstat-plspm-software"
"yearMonth" => "2007-06"
"year" => "2007"
"title" => "PLS (Partial Least Squares) Path Modeling: Methodological Foundations and the XLSTAT-PLSPM Software"
"description" => "ESPOSITO VINZI, V. (2007). PLS (Partial Least Squares) Path Modeling: Methodological Foundations and the XLSTAT-PLSPM Software."
"authors" => array:1 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
]
"ouvrage" => ""
"keywords" => array:1 [
0 => "Structural Equation Modeling"
]
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "PLS (Partial Least Squares) Path Modeling (PLS-PM) is a statistical modeling technique with data analysis features linking several blocks of variables by means of a causality network. This general approach studies a system of linear relationships between latent (non observable) variables. Each latent variable is described by a set of manifest (observable) indicators. The nature of this approach is rather exploratory and data-driven than confirmatory. Therefore, it represents an alternative to the classical maximum likelihood-based approach to structural equation modeling, commonly known as LISREL. The features of PLS-PM methods make them very interesting for applications and developments in several domains of application. This presentation aims at providing the audience with an expository review of the PLS Path Modeling methodology, a presentation and a critical assessment of some of the most recent developments, a guide to applications run by means of the PLSPM module in XLSTAT."
"en" => "PLS (Partial Least Squares) Path Modeling (PLS-PM) is a statistical modeling technique with data analysis features linking several blocks of variables by means of a causality network. This general approach studies a system of linear relationships between latent (non observable) variables. Each latent variable is described by a set of manifest (observable) indicators. The nature of this approach is rather exploratory and data-driven than confirmatory. Therefore, it represents an alternative to the classical maximum likelihood-based approach to structural equation modeling, commonly known as LISREL. The features of PLS-PM methods make them very interesting for applications and developments in several domains of application. This presentation aims at providing the audience with an expository review of the PLS Path Modeling methodology, a presentation and a critical assessment of some of the most recent developments, a guide to applications run by means of the PLSPM module in XLSTAT."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
70 => Essec\Faculty\Model\Contribution {#2468
#_index: "academ_contributions"
#_id: "6897"
#_source: array:18 [
"id" => "6897"
"slug" => "pls-path-modeling-and-the-pleasure-partial-least-squares-structural-relationships-estimation-software"
"yearMonth" => "2007-05"
"year" => "2007"
"title" => "PLS Path Modeling and the PLEASURE (Partial LEAst Squares strUctural Relationships Estimation) Software"
"description" => "ESPOSITO VINZI, V. (2007). PLS Path Modeling and the PLEASURE (Partial LEAst Squares strUctural Relationships Estimation) Software."
"authors" => array:1 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
]
"ouvrage" => ""
"keywords" => array:2 [
0 => "Multi-group"
1 => "Structural Equation Modeling"
]
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "This contribution deals with the study of a causal network of relationships between latent variables by means of a component-based approach. A new software with advanced features is presented within the XLSTAT data analysis tool developed in Excel."
"en" => "This contribution deals with the study of a causal network of relationships between latent variables by means of a component-based approach. A new software with advanced features is presented within the XLSTAT data analysis tool developed in Excel."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
71 => Essec\Faculty\Model\Contribution {#2469
#_index: "academ_contributions"
#_id: "6896"
#_source: array:18 [
"id" => "6896"
"slug" => "pls-path-modeling-and-pls-regression-a-joint-partial-least-squares-component-based-approach-to-structural-equation-modeling"
"yearMonth" => "2009-03"
"year" => "2009"
"title" => "PLS Path Modeling and PLS Regression: a Joint Partial Least Squares Component-based Approach to Structural Equation Modeling"
"description" => "ESPOSITO VINZI, V. (2009). PLS Path Modeling and PLS Regression: a Joint Partial Least Squares Component-based Approach to Structural Equation Modeling. Dans: IFCS@GFKL - Classification as a Tool for Research (IFCS 2009)."
"authors" => array:1 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
]
"ouvrage" => "IFCS@GFKL - Classification as a Tool for Research (IFCS 2009)"
"keywords" => array:2 [
0 => "Multicollinearity"
1 => "Multidimensional Blocks"
]
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "Partial Least Squares Path Modelling (PLS-PM) is generally meant as a component-based approach to structural equation models and multi-block data analysis that privileges a prediction oriented discovery process to the statistical testing of causal hypotheses. In case of formative relationships in the measurement model between the manifest variables and their corresponding latent ones, PLS-PM estimates the outer weights by means of multiple OLS regressions. These regressions might often yield unstable results in case of strong correlations between manifest variables while being not feasible when the number of observations is smaller than the number of variables or in presence of missing data. An external estimation mode based on PLS regression (PLS-R) may overcome these problems while preserving the formative nature of the measurement model. At the same time, this innovative estimation mode provides new tools for interpreting the components, validating the results and improving the predictions in PLS-PM. PLS-R is also profitably extended to: the internal estimation step of PLS-PM as a generalization of path weighting scheme, the estimation of path coefficients in structural models affected by strongly correlated latent variables or missing scores. Finally, the implementation of PLS regression in the estimation steps of PLS Path Modeling defines a regularized comprehensive PLS approach that yields more stable and robust results while enriching interpretation."
"en" => "Partial Least Squares Path Modelling (PLS-PM) is generally meant as a component-based approach to structural equation models and multi-block data analysis that privileges a prediction oriented discovery process to the statistical testing of causal hypotheses. In case of formative relationships in the measurement model between the manifest variables and their corresponding latent ones, PLS-PM estimates the outer weights by means of multiple OLS regressions. These regressions might often yield unstable results in case of strong correlations between manifest variables while being not feasible when the number of observations is smaller than the number of variables or in presence of missing data. An external estimation mode based on PLS regression (PLS-R) may overcome these problems while preserving the formative nature of the measurement model. At the same time, this innovative estimation mode provides new tools for interpreting the components, validating the results and improving the predictions in PLS-PM. PLS-R is also profitably extended to: the internal estimation step of PLS-PM as a generalization of path weighting scheme, the estimation of path coefficients in structural models affected by strongly correlated latent variables or missing scores. Finally, the implementation of PLS regression in the estimation steps of PLS Path Modeling defines a regularized comprehensive PLS approach that yields more stable and robust results while enriching interpretation."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
72 => Essec\Faculty\Model\Contribution {#2470
#_index: "academ_contributions"
#_id: "6898"
#_source: array:18 [
"id" => "6898"
"slug" => "pls-path-modeling-some-recent-methodological-developments-a-software-integrated-in-xlstat-and-its-application-to-customer-satisfaction-studies"
"yearMonth" => "2007-07"
"year" => "2007"
"title" => "PLS Path Modeling: Some Recent Methodological Developments, a Software Integrated in XLSTAT and its Application to Customer Satisfaction Studies"
"description" => "ESPOSITO VINZI, V., FAHMY, T., CHATELIN, Y.M. et TENEHAUS, M. (2007). PLS Path Modeling: Some Recent Methodological Developments, a Software Integrated in XLSTAT and its Application to Customer Satisfaction Studies."
"authors" => array:4 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "FAHMY T."
]
2 => array:1 [
"name" => "CHATELIN Y.M."
]
3 => array:1 [
"name" => "TENEHAUS M."
]
]
"ouvrage" => ""
"keywords" => array:2 [
0 => "Customer Satisfaction"
1 => "Structural Equation Modeling"
]
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "With structural equation modeling based on the PLS Path Modeling and the XLSTAT-PLeaSure software, we show a way to represent and model how customer satisfaction is related to manifest and latent variables, using data that are available through different sources, and respecting the conceptual logics of marketing in a mathematical framework."
"en" => "With structural equation modeling based on the PLS Path Modeling and the XLSTAT-PLeaSure software, we show a way to represent and model how customer satisfaction is related to manifest and latent variables, using data that are available through different sources, and respecting the conceptual logics of marketing in a mathematical framework."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
73 => Essec\Faculty\Model\Contribution {#2471
#_index: "academ_contributions"
#_id: "6980"
#_source: array:18 [
"id" => "6980"
"slug" => "quantile-composite-based-path-modeling-for-measuring-equitable-and-sustainable-well-being"
"yearMonth" => "2015-09"
"year" => "2015"
"title" => "Quantile Composite-Based Path Modeling for Measuring Equitable and Sustainable Well-Being"
"description" => "DAVINO, C., DOLCE, P., ESPOSITO VINZI, V. et TARALLI, S. (2015). Quantile Composite-Based Path Modeling for Measuring Equitable and Sustainable Well-Being. Dans: Dealing with Complexity in Society: from Plurality of Data to Synthetic Indicators."
"authors" => array:4 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "DAVINO C."
]
2 => array:1 [
"name" => "DOLCE P."
]
3 => array:1 [
"name" => "TARALLI S."
]
]
"ouvrage" => "Dealing with Complexity in Society: from Plurality of Data to Synthetic Indicators"
"keywords" => []
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "A quantile approach to PLS Path Modeling is proposed to highlight differences in the impact played by the indicators and dimensions of the BES (Benessere Equo e Sostenibile - equitable and sustainable wellbeing) index according to different degrees of equitable and sustainable well-being. The method is able to explore the whole distribution of the composite indicators referred to each dimension and to the BES index as a whole, thus going beyond the classical investigation of the average effects."
"en" => "A quantile approach to PLS Path Modeling is proposed to highlight differences in the impact played by the indicators and dimensions of the BES (Benessere Equo e Sostenibile - equitable and sustainable wellbeing) index according to different degrees of equitable and sustainable well-being. The method is able to explore the whole distribution of the composite indicators referred to each dimension and to the BES index as a whole, thus going beyond the classical investigation of the average effects."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
74 => Essec\Faculty\Model\Contribution {#2472
#_index: "academ_contributions"
#_id: "6981"
#_source: array:18 [
"id" => "6981"
"slug" => "quantile-plspm-vs-classical-plspm-methods-performances-and-interpretations"
"yearMonth" => "2014-12"
"year" => "2014"
"title" => "Quantile PLSPM vs. Classical PLSPM: Methods, Performances and Interpretations"
"description" => "ESPOSITO VINZI, V., DAVINO, C. et DOLLE, P. (2014). Quantile PLSPM vs. Classical PLSPM: Methods, Performances and Interpretations. Dans: 7th International Conference of the ERCIM WG on Computational and Methodological Statistics."
"authors" => array:3 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "DAVINO C."
]
2 => array:1 [
"name" => "DOLLE P."
]
]
"ouvrage" => "7th International Conference of the ERCIM WG on Computational and Methodological Statistics"
"keywords" => []
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
75 => Essec\Faculty\Model\Contribution {#2473
#_index: "academ_contributions"
#_id: "7016"
#_source: array:18 [
"id" => "7016"
"slug" => "recent-developments-in-pls-path-modeling-methodological-issues-and-applications"
"yearMonth" => "2007-09"
"year" => "2007"
"title" => "Recent Developments in PLS Path Modeling: Methodological Issues and Applications"
"description" => "ESPOSITO VINZI, V. et FAHMY, T. (2007). Recent Developments in PLS Path Modeling: Methodological Issues and Applications."
"authors" => array:2 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "FAHMY T."
]
]
"ouvrage" => ""
"keywords" => array:1 [
0 => "Multicollinearity"
]
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "Partial Least Squares Path Modeling (PLS-PM) is a statistical approach, with an increasing popularity in several areas, for modeling complex multivariable relationships among observed and latent variables. From the standpoint of structural equation modeling, we look at PLS-PM as a component-based approach where the concept of causality is formulated in terms of linear conditional expectations, thus privileging a prediction-oriented discovery process to the statistical testing of causal hypotheses. From the standpoint of data analysis, we mean PLS-PM as a flexible approach to the analysis of multiple blocks of variables that are available for the same set of samples. This approach shows how the 'data-driven' tradition of multiple-table analysis can be merged with the 'theory-driven' tradition of structural equation modeling so as to allow researchers to run the analysis in light of the current knowledge on the conceptual relationships between tables and with known optimizing criteria. In both frameworks, PLS-PM may enhance potentialities even further, and provide effective added value, when exploited in the case of formative relationships between manifest variables and their respective latent variables. In such a case, we show how PLS regression and PLS-PM can profitably interplay and coherently merge, thus permitting further developments with applications to marketing."
"en" => "Partial Least Squares Path Modeling (PLS-PM) is a statistical approach, with an increasing popularity in several areas, for modeling complex multivariable relationships among observed and latent variables. From the standpoint of structural equation modeling, we look at PLS-PM as a component-based approach where the concept of causality is formulated in terms of linear conditional expectations, thus privileging a prediction-oriented discovery process to the statistical testing of causal hypotheses. From the standpoint of data analysis, we mean PLS-PM as a flexible approach to the analysis of multiple blocks of variables that are available for the same set of samples. This approach shows how the 'data-driven' tradition of multiple-table analysis can be merged with the 'theory-driven' tradition of structural equation modeling so as to allow researchers to run the analysis in light of the current knowledge on the conceptual relationships between tables and with known optimizing criteria. In both frameworks, PLS-PM may enhance potentialities even further, and provide effective added value, when exploited in the case of formative relationships between manifest variables and their respective latent variables. In such a case, we show how PLS regression and PLS-PM can profitably interplay and coherently merge, thus permitting further developments with applications to marketing."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
76 => Essec\Faculty\Model\Contribution {#2474
#_index: "academ_contributions"
#_id: "7018"
#_source: array:18 [
"id" => "7018"
"slug" => "recent-developments-on-formative-constructs-and-a-comprehensive-environment-for-pls-path-modelling"
"yearMonth" => "2008-05"
"year" => "2008"
"title" => "Recent Developments on Formative Constructs and a Comprehensive Environment for PLS Path Modelling"
"description" => "ESPOSITO VINZI, V. et DE GIOVANNI, P. (2008). Recent Developments on Formative Constructs and a Comprehensive Environment for PLS Path Modelling. Dans: Structural Equation Models, PLS Path Modeling and Multi-block Techniques in Sensory and Consumer Analysis."
"authors" => array:2 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "DE GIOVANNI Pietro"
]
]
"ouvrage" => "Structural Equation Models, PLS Path Modeling and Multi-block Techniques in Sensory and Consumer Analysis"
"keywords" => array:1 [
0 => "Multicollinearity"
]
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "In a structural equation modelling framework, most often measurement models are misspecified: indicators are supposed to be effects (reflective scheme) of the latent variables while they are actually their causes (formative scheme). We propose the implementation of PLS regression within PLS Path Modeling so as to cope with multicollinearity problems arising when using multiple regression in the case of formative indicators. This approach is also extended to the estimation of structural relations when latent concepts are also strongly correlated and make classical OLS estimates unstable. An application from sensory data analysis is shown."
"en" => "In a structural equation modelling framework, most often measurement models are misspecified: indicators are supposed to be effects (reflective scheme) of the latent variables while they are actually their causes (formative scheme). We propose the implementation of PLS regression within PLS Path Modeling so as to cope with multicollinearity problems arising when using multiple regression in the case of formative indicators. This approach is also extended to the estimation of structural relations when latent concepts are also strongly correlated and make classical OLS estimates unstable. An application from sensory data analysis is shown."
]
"authors_fields" => array:2 [
"fr" => "Management"
"en" => "Management"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
77 => Essec\Faculty\Model\Contribution {#2475
#_index: "academ_contributions"
#_id: "7283"
#_source: array:18 [
"id" => "7283"
"slug" => "the-contribution-of-pls-regression-to-pls-path-modelling-formative-measurement-model-and-causality-network-in-the-structural-model"
"yearMonth" => "2008-08"
"year" => "2008"
"title" => "The Contribution of PLS Regression to PLS Path Modelling: Formative Measurement Model and Causality Network in the Structural Model"
"description" => "ESPOSITO VINZI, V. (2008). The Contribution of PLS Regression to PLS Path Modelling: Formative Measurement Model and Causality Network in the Structural Model. Dans: Joint Statistical Meetings (JSM) 2008 - American Statistical Association."
"authors" => array:1 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
]
"ouvrage" => "Joint Statistical Meetings (JSM) 2008 - American Statistical Association"
"keywords" => array:2 [
0 => "Multicollinearity"
1 => "Multidimensional Blocks"
]
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "PLS Path Modelling (PLS-PM) is generally meant as a component-based approach to structural equation modelling that privileges a prediction oriented discovery process to the statistical testing of causal hypotheses. In case of formative relationships between manifest and latent variables, PLS-PM implies multiple OLS regressions. They might yield unstable results in case of strong correlations between manifest variables while being not feasible when the number of observations is smaller than the number of variables nor in case of missing data. We explore PLS regression (PLS-R) as an external estimation mode to overcome the mentioned problems while preserving formative relationships and being coherent with the component-based and prediction-oriented nature of PLS-PM. PLS-R is also fruitfully extended to the path weighting internal estimation scheme and the estimation of path coefficients."
"en" => "PLS Path Modelling (PLS-PM) is generally meant as a component-based approach to structural equation modelling that privileges a prediction oriented discovery process to the statistical testing of causal hypotheses. In case of formative relationships between manifest and latent variables, PLS-PM implies multiple OLS regressions. They might yield unstable results in case of strong correlations between manifest variables while being not feasible when the number of observations is smaller than the number of variables nor in case of missing data. We explore PLS regression (PLS-R) as an external estimation mode to overcome the mentioned problems while preserving formative relationships and being coherent with the component-based and prediction-oriented nature of PLS-PM. PLS-R is also fruitfully extended to the path weighting internal estimation scheme and the estimation of path coefficients."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
78 => Essec\Faculty\Model\Contribution {#2476
#_index: "academ_contributions"
#_id: "7400"
#_source: array:18 [
"id" => "7400"
"slug" => "the-pls-approach-to-data-exploration-and-modeling-an-everlasting-matter-of-dispute-or-a-playground-for-integrating-different-cultures"
"yearMonth" => "2007-09"
"year" => "2007"
"title" => "The PLS approach to data exploration and Modeling: An Everlasting Matter of Dispute or a Playground for Integrating Different Cultures?"
"description" => "ESPOSITO VINZI, V. (2007). The PLS approach to data exploration and Modeling: An Everlasting Matter of Dispute or a Playground for Integrating Different Cultures?"
"authors" => array:1 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
]
"ouvrage" => ""
"keywords" => array:1 [
0 => "Multicollinearity"
]
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "PLS-PM can provide effective added value when exploited in the case of formative epistemic relationships between manifest variables and their respective latent variables. In such a framework, the paper introduces a PLS Regression external estimation mode inside the PLS-PM algorithm so as to overcome problems of multi-collinearity, wide tables and missing data while being coherent with the component-based and prediction-oriented nature of PLS-PM. The implementation of PLS-R within PLS-PM is extended also to the internal estimation module (as an alternative OLS regression step in the Path Weighting estimation scheme) and to the estimation of path coefficients for the structural model upon convergence of the PLS-PM algorithm and estimation of the latent variable scores. Such an extensive implementation, that may well represent a playground towards the merging of the two PLS cultures, opens a wide range of new possibilities and further developments: different dimensions can be chosen for each block of latent variables, the number of retained components can be chosen by referring to the PLS-R criteria, the well established PLS-R validation and interpretation tools can be finally imported in PLS-PM, new optimizing criteria are envisaged for multi-block data."
"en" => "PLS-PM can provide effective added value when exploited in the case of formative epistemic relationships between manifest variables and their respective latent variables. In such a framework, the paper introduces a PLS Regression external estimation mode inside the PLS-PM algorithm so as to overcome problems of multi-collinearity, wide tables and missing data while being coherent with the component-based and prediction-oriented nature of PLS-PM. The implementation of PLS-R within PLS-PM is extended also to the internal estimation module (as an alternative OLS regression step in the Path Weighting estimation scheme) and to the estimation of path coefficients for the structural model upon convergence of the PLS-PM algorithm and estimation of the latent variable scores. Such an extensive implementation, that may well represent a playground towards the merging of the two PLS cultures, opens a wide range of new possibilities and further developments: different dimensions can be chosen for each block of latent variables, the number of retained components can be chosen by referring to the PLS-R criteria, the well established PLS-R validation and interpretation tools can be finally imported in PLS-PM, new optimizing criteria are envisaged for multi-block data."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
79 => Essec\Faculty\Model\Contribution {#2477
#_index: "academ_contributions"
#_id: "7701"
#_source: array:18 [
"id" => "7701"
"slug" => "handbook-of-partial-least-squares-concepts-methods-and-applications"
"yearMonth" => "2010-03"
"year" => "2010"
"title" => "Handbook of Partial Least Squares: Concepts, Methods and Applications"
"description" => "ESPOSITO VINZI, V., CHIN, W.W., HENSELER, J. et WANG, H. [Eds] (2010). <i>Handbook of Partial Least Squares: Concepts, Methods and Applications</i>. Springer, 798 pages."
"authors" => array:4 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "CHIN W.-W."
]
2 => array:1 [
"name" => "HENSELER J."
]
3 => array:1 [
"name" => "WANG H."
]
]
"ouvrage" => ""
"keywords" => []
"updatedAt" => "2020-12-17 21:00:33"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Direction d'ouvrage"
"en" => "Book editor"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "The "Handbook of Partial Least Squares (PLS): Concepts, Methods and Applications" is the second volume in the series of the Handbooks of Computational Statistics. This Handbook represents a comprehensive overview of PLS methods with specific reference to their use in Marketing and with a discussion of the directions of current research and perspectives. The Handbook covers the broad area of PLS Methods from Regression to Structural Equation Modeling, from methods to applications, from software to interpretation of results. The Handbook features papers on the use and the analysis of latent variables and indicators by means of the PLS Path Modeling approach from the design of the causal network to the model assessment and improvement. Moreover, within the PLS framework, the Handbook addresses, among others, special and advanced topics such as the analysis of multi-block, multi-group and multi-structured data, the use of categorical indicators, the study of interaction effects, the integration of classification issues, the validation aspects and the comparison between the component-based PLS approach and the covariance-based Structural Equation Modeling. Most chapters comprise a thorough discussion of applications to problems from Marketing and related areas. Furthermore, a few tutorials focus on some key aspects of PLS analysis with a didactic approach. This Handbook serves as both an introduction for those without prior knowledge of PLS as well as a comprehensive reference for researchers and practitioners interested in the most recent advances in PLS methodology."
"en" => "The "Handbook of Partial Least Squares (PLS): Concepts, Methods and Applications" is the second volume in the series of the Handbooks of Computational Statistics. This Handbook represents a comprehensive overview of PLS methods with specific reference to their use in Marketing and with a discussion of the directions of current research and perspectives. The Handbook covers the broad area of PLS Methods from Regression to Structural Equation Modeling, from methods to applications, from software to interpretation of results. The Handbook features papers on the use and the analysis of latent variables and indicators by means of the PLS Path Modeling approach from the design of the causal network to the model assessment and improvement. Moreover, within the PLS framework, the Handbook addresses, among others, special and advanced topics such as the analysis of multi-block, multi-group and multi-structured data, the use of categorical indicators, the study of interaction effects, the integration of classification issues, the validation aspects and the comparison between the component-based PLS approach and the covariance-based Structural Equation Modeling. Most chapters comprise a thorough discussion of applications to problems from Marketing and related areas. Furthermore, a few tutorials focus on some key aspects of PLS analysis with a didactic approach. This Handbook serves as both an introduction for those without prior knowledge of PLS as well as a comprehensive reference for researchers and practitioners interested in the most recent advances in PLS methodology."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
80 => Essec\Faculty\Model\Contribution {#2478
#_index: "academ_contributions"
#_id: "7736"
#_source: array:18 [
"id" => "7736"
"slug" => "new-perspectives-in-partial-least-squares-and-related-methods"
"yearMonth" => "2013-11"
"year" => "2013"
"title" => "New Perspectives in Partial Least Squares and Related Methods"
"description" => "ESPOSITO VINZI, V. [Ed] (2013). <i>New Perspectives in Partial Least Squares and Related Methods</i>. Springer, 344 pages."
"authors" => array:1 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
]
"ouvrage" => ""
"keywords" => []
"updatedAt" => "2020-12-17 21:00:33"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Direction d'ouvrage"
"en" => "Book editor"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "This book shares original, peer-reviewed research on PLS that is an abbreviation for Partial Least Squares and is also sometimes expanded as projection to latent structures. This is an approach for modeling relations between data matrices of different types of variables measured on the same set of objects. The twenty-two papers in this volume provide a comprehensive overview of the current state of the most advanced research related to PLS and related methods. These exciting theoretical developments range from partial least squares regression and correlation, component based path modeling to regularized regression and subspace visualization. These contributions also included a large variety of PLS approaches such as PLS metamodels, variable selection, sparse PLS regression, distance based PLS, significance vs. reliability, and non-linear PLS. Finally, these contributions applied PLS methods to data originating from the traditional econometric/economic data to genomics data, brain images, information systems, epidemiology, and chemical spectroscopy."
"en" => "This book shares original, peer-reviewed research on PLS that is an abbreviation for Partial Least Squares and is also sometimes expanded as projection to latent structures. This is an approach for modeling relations between data matrices of different types of variables measured on the same set of objects. The twenty-two papers in this volume provide a comprehensive overview of the current state of the most advanced research related to PLS and related methods. These exciting theoretical developments range from partial least squares regression and correlation, component based path modeling to regularized regression and subspace visualization. These contributions also included a large variety of PLS approaches such as PLS metamodels, variable selection, sparse PLS regression, distance based PLS, significance vs. reliability, and non-linear PLS. Finally, these contributions applied PLS methods to data originating from the traditional econometric/economic data to genomics data, brain images, information systems, epidemiology, and chemical spectroscopy."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
81 => Essec\Faculty\Model\Contribution {#2479
#_index: "academ_contributions"
#_id: "7752"
#_source: array:18 [
"id" => "7752"
"slug" => "the-multiple-facets-of-partial-least-squares-and-related-methods"
"yearMonth" => "2016-12"
"year" => "2016"
"title" => "The Multiple Facets of Partial Least Squares and Related Methods"
"description" => "ABDI, H., ESPOSITO VINZI, V., RUSSOLILLO, G., SAPORTA, G. et TRINCHERA, L. [Eds] (2016). <i>The Multiple Facets of Partial Least Squares and Related Methods</i>. Springer, 316 pages."
"authors" => array:5 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "ABDI Hervé"
]
2 => array:1 [
"name" => "RUSSOLILLO Georgio"
]
3 => array:1 [
"name" => "SAPORTA Gilbert"
]
4 => array:1 [
"name" => "TRINCHERA Laura"
]
]
"ouvrage" => ""
"keywords" => []
"updatedAt" => "2021-09-24 10:33:27"
"publicationUrl" => "https://www.springer.com/gp/book/9783319406411#aboutAuthors"
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Direction d'ouvrage"
"en" => "Book editor"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "This volume presents state of the art theories, new developments, and important applications of Partial Least Square (PLS) methods. The text begins with the invited communications of current leaders in the field who cover the history of PLS, an overview of methodological issues, and recent advances in regression and multi-block approaches. The rest of the volume comprises selected, reviewed contributions from the 8th International Conference on Partial Least Squares and Related Methods held in Paris, France, on 26-28 May, 2014. They are organized in four coherent sections: 1) new developments in genomics and brain imaging, 2) new and alternative methods for multi-table and path analysis, 3) advances in partial least square regression (PLSR), and 4) partial least square path modeling (PLS-PM) breakthroughs and applications. PLS methods are very versatile methods that are now used in areas as diverse as engineering, life science, sociology, psychology, brain imaging, genomics, and business among both academics and practitioners. The selected chapters here highlight this diversity with applied examples as well as the most recent advances."
"en" => "This volume presents state of the art theories, new developments, and important applications of Partial Least Square (PLS) methods. The text begins with the invited communications of current leaders in the field who cover the history of PLS, an overview of methodological issues, and recent advances in regression and multi-block approaches. The rest of the volume comprises selected, reviewed contributions from the 8th International Conference on Partial Least Squares and Related Methods held in Paris, France, on 26-28 May, 2014. They are organized in four coherent sections: 1) new developments in genomics and brain imaging, 2) new and alternative methods for multi-table and path analysis, 3) advances in partial least square regression (PLSR), and 4) partial least square path modeling (PLS-PM) breakthroughs and applications. PLS methods are very versatile methods that are now used in areas as diverse as engineering, life science, sociology, psychology, brain imaging, genomics, and business among both academics and practitioners. The selected chapters here highlight this diversity with applied examples as well as the most recent advances."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
82 => Essec\Faculty\Model\Contribution {#2480
#_index: "academ_contributions"
#_id: "7895"
#_source: array:18 [
"id" => "7895"
"slug" => "an-attitude-model-of-environmental-action-evidence-from-developing-and-developed-countries"
"yearMonth" => "2017-01"
"year" => "2017"
"title" => "An Attitude Model of Environmental Action: Evidence from Developing and Developed Countries"
"description" => "DAVINO, C., ESPOSITO VINZI, V., SANTACREU VASUT, E. et VRANCEANU, R. (2017). <i>An Attitude Model of Environmental Action: Evidence from Developing and Developed Countries</i>. ESSEC Business School."
"authors" => array:4 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:3 [
"name" => "SANTACREU VASUT Estefania"
"bid" => "B00318975"
"slug" => "santacreu-vasut-estefania"
]
2 => array:3 [
"name" => "VRANCEANU Radu"
"bid" => "B00000524"
"slug" => "vranceanu-radu"
]
3 => array:1 [
"name" => "DAVINO Cristina"
]
]
"ouvrage" => ""
"keywords" => array:4 [
0 => "Environmental attitudes"
1 => "Environmental policies -Development, Culture"
2 => "Multivariate Analysis"
3 => "Partial Least Squares."
]
"updatedAt" => "2021-09-24 10:33:27"
"publicationUrl" => "https://hal.archives-ouvertes.fr/hal-01457539"
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Documents de travail"
"en" => "Working Papers"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "This paper analyzes the determinants of individual attitudes towards environmental action by means of an original PLSPM model of Environmental Awareness-Social Capital-Action (EASCA). Estimates build on survey data on 34.612 individuals from 42 different countries, as provided in the fifth wave of the World Value Survey (2005-2009). Besides the benchmark global estimates, we perform subsample analysis for developed and developing countries, as well as country analyses for four major economies: China, India, Germany and the United States. Doing so allows us to underline structural differences between countries or main groups of countries. In particular, we find that environmental awareness and trust in not-for-profit organizations are the main determinants of individual action in support of environmentally friendly policies. The quality of environmental policymaking should improve if these cultural differences are better understood and taken into account."
"en" => "This paper analyzes the determinants of individual attitudes towards environmental action by means of an original PLSPM model of Environmental Awareness-Social Capital-Action (EASCA). Estimates build on survey data on 34.612 individuals from 42 different countries, as provided in the fifth wave of the World Value Survey (2005-2009). Besides the benchmark global estimates, we perform subsample analysis for developed and developing countries, as well as country analyses for four major economies: China, India, Germany and the United States. Doing so allows us to underline structural differences between countries or main groups of countries. In particular, we find that environmental awareness and trust in not-for-profit organizations are the main determinants of individual action in support of environmentally friendly policies. The quality of environmental policymaking should improve if these cultural differences are better understood and taken into account."
]
"authors_fields" => array:2 [
"fr" => "Economie"
"en" => "Economics"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
83 => Essec\Faculty\Model\Contribution {#2481
#_index: "academ_contributions"
#_id: "7934"
#_source: array:18 [
"id" => "7934"
"slug" => "capturing-and-treating-unobserved-heterogeneity-by-response-based-segmentation-in-pls-path-modeling-a-comparison-of-alternative-methods-by-computational-experiments"
"yearMonth" => "2007-07"
"year" => "2007"
"title" => "Capturing and Treating Unobserved Heterogeneity by Response Based Segmentation in PLS Path Modeling. A Comparison of Alternative Methods by Computational Experiments"
"description" => "ESPOSITO VINZI, V., RINGLE, C.M., SQUILLACCIOTTI, S. et TRINCHERA, L. (2007). <i>Capturing and Treating Unobserved Heterogeneity by Response Based Segmentation in PLS Path Modeling. A Comparison of Alternative Methods by Computational Experiments</i>. ESSEC Business School."
"authors" => array:4 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "RINGLE C.M."
]
2 => array:1 [
"name" => "SQUILLACCIOTTI S."
]
3 => array:1 [
"name" => "TRINCHERA L."
]
]
"ouvrage" => ""
"keywords" => array:1 [
0 => "Unobserved Heterogeneity"
]
"updatedAt" => "2020-12-17 21:00:33"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Documents de travail"
"en" => "Working Papers"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "De nos jours, les problématiques liées à la recherche d'hétérogénéité parmi les unités sont devenues critiques dans le cadre des modèles structurels PLS, notamment dans les sciences sociales. L'hypothèse de base de cette méthode, selon laquelle les données proviennent d'une population unique et homogène, s'avère souvent peu réaliste. Les techniques de classification séquentielles sur les variables manifestes sont fréquemment peu efficaces lorsque l'on veut découvrir l'hétérogénéité dans les estimations des paramètres des modèles structurels. Trois approches statistiques ont été développées comme solutions à ce problème dans le cadre des méthodes PLS. L'objectif de ce papier est de présenter une étude sur des jeux de données simulées, ayant différentes caractéristiques permettant une première évaluation des méthodes décrites. Par ces jeux de données, nous allons illustrer l'intérêt de découvrir l'hétérogénéité latente dans les applications des modèles structurels PLS, décrire les caractéristiques de chaque méthode, en comparer les points forts et les points faibles, et découvrir des aspects méthodologiques qui n'ont pas encore été traités. Ces contributions pourront aider chercheurs et praticiens à mieux comprendre les résultats parfois ambigus des modèles PLS, afin de parvenir à des conclusions analytiques plus efficaces."
"en" => "Segmentation in PLS path modeling framework results is a critical issue in social sciences. The assumption that data is collected from a single homogeneous population is often unrealistic. Sequential clustering techniques on the manifest variables level are ineffective to account for heterogeneity in path model estimates. Three PLS path model related statistical approaches have been developed as solutions for this problem. The purpose of this paper is to present a study on sets of simulated data with different characteristics that allows a primary assessment of these methodologies."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
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]
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}
84 => Essec\Faculty\Model\Contribution {#2482
#_index: "academ_contributions"
#_id: "8573"
#_source: array:18 [
"id" => "8573"
"slug" => "proceedings-of-the-6th-international-conference-on-partial-least-squares-and-related-methods"
"yearMonth" => "2009-01"
"year" => "2009"
"title" => "Proceedings of the 6th International Conference on Partial Least Squares and Related Methods"
"description" => "ESPOSITO VINZI, V., TENENHAUS, M. et GUAN, R. (2009). Proceedings of the 6th International Conference on Partial Least Squares and Related Methods. Publishing House of Electronics Industry, Chine."
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0 => array:3 [
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1 => array:1 [
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2 => array:1 [
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"ouvrage" => ""
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"type" => array:2 [
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"support_type" => array:2 [
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"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
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}
85 => Essec\Faculty\Model\Contribution {#2483
#_index: "academ_contributions"
#_id: "8665"
#_source: array:18 [
"id" => "8665"
"slug" => "je-suis-un-chercheur-je-ne-suis-pas-capable-de-parler-de-tout-et-nimporte-quoi"
"yearMonth" => "2016-05"
"year" => "2016"
"title" => "« Je suis un chercheur ; je ne suis pas capable de parler de tout et n’importe quoi. »"
"description" => "ESPOSITO VINZI, V. et GASPAR, J.M. (2016). « Je suis un chercheur ; je ne suis pas capable de parler de tout et n’importe quoi. ». <i>Monde des Grandes Écoles Universités Le Magazine</i>."
"authors" => array:2 [
0 => array:3 [
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1 => array:3 [
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"ouvrage" => ""
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"updatedAt" => "2020-12-17 18:37:46"
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"type" => array:2 [
"fr" => "Articles ou vidéos de vulgarisation"
"en" => "Press article, video or other popular media"
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"support_type" => array:2 [
"fr" => "Presse"
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"countries" => array:2 [
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"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
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}
86 => Essec\Faculty\Model\Contribution {#2484
#_index: "academ_contributions"
#_id: "9750"
#_source: array:18 [
"id" => "9750"
"slug" => "inferential-aspects-and-relevance-of-metrics-in-the-models-for-principal-component-analysis-and-pca-onto-a-reference-subspace"
"yearMonth" => "1995-06"
"year" => "1995"
"title" => "Inferential aspects and relevance of metrics in the models for Principal Component Analysis and PCA onto a Reference Subspace"
"description" => "ESPOSITO VINZI, V. (1995). Inferential aspects and relevance of metrics in the models for Principal Component Analysis and PCA onto a Reference Subspace. Dans: <i>Workshop on Multidimensional Data Analysis</i>. Naples: pp. 91-92."
"authors" => array:1 [
0 => array:3 [
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"ouvrage" => "Workshop on Multidimensional Data Analysis"
"keywords" => array:2 [
0 => "PCA"
1 => "Reference Subspace"
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"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "91-92"
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"type" => array:2 [
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"support_type" => array:2 [
"fr" => null
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"countries" => array:2 [
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"abstract" => array:2 [
"fr" => "Inferential aspects and relevance of metrics in the models for Principal Component Analysis and PCA onto a Reference Subspace"
"en" => "Inferential aspects and relevance of metrics in the models for Principal Component Analysis and PCA onto a Reference Subspace"
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
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}
87 => Essec\Faculty\Model\Contribution {#2485
#_index: "academ_contributions"
#_id: "9764"
#_source: array:18 [
"id" => "9764"
"slug" => "allowing-for-structures-on-individuals-in-principal-component-analysis-onto-a-reference-subspace"
"yearMonth" => "1996-06"
"year" => "1996"
"title" => "Allowing for Structures on Individuals in Principal Component Analysis onto a Reference Subspace"
"description" => "ESPOSITO VINZI, V. (1996). Allowing for Structures on Individuals in Principal Component Analysis onto a Reference Subspace. Dans: <i>XII biannual Symposium in Computational Statistics</i>. Barcelona: Universitat Politècnica de Catalunya, pp. 45-46."
"authors" => array:1 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
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"ouvrage" => "XII biannual Symposium in Computational Statistics"
"keywords" => array:2 [
0 => "Structures on Individuals"
1 => "PCA -Reference Subspace"
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"updatedAt" => "2021-07-13 14:31:20"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "45-46"
"volume" => null
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"type" => array:2 [
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"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
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"countries" => array:2 [
"fr" => null
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"abstract" => array:2 [
"fr" => "Allowing for Structures on Individuals in Principal Component Analysis onto a Reference Subspace"
"en" => "Allowing for Structures on Individuals in Principal Component Analysis onto a Reference Subspace"
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
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}
88 => Essec\Faculty\Model\Contribution {#2486
#_index: "academ_contributions"
#_id: "9792"
#_source: array:18 [
"id" => "9792"
"slug" => "a-comparative-non-symmetrical-analysis-with-stratified-observations"
"yearMonth" => "1997-06"
"year" => "1997"
"title" => "A Comparative Non Symmetrical Analysis with Stratified Observations"
"description" => "ESPOSITO VINZI, V. (1997). A Comparative Non Symmetrical Analysis with Stratified Observations. Dans: <i>SIS Conference "Statistics for Enterprises"</i>. Torino: Tirrenia Stampatori, pp. 343-350."
"authors" => array:1 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
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]
]
"ouvrage" => "SIS Conference "Statistics for Enterprises""
"keywords" => array:1 [
0 => "Non Symmetrical Analysis"
]
"updatedAt" => "2021-07-13 14:31:20"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "343-350"
"volume" => null
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"type" => array:2 [
"fr" => "Actes d'une conférence"
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"support_type" => array:2 [
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"en" => "Publisher"
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"countries" => array:2 [
"fr" => null
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]
"abstract" => array:2 [
"fr" => "A Comparative Non Symmetrical Analysis with Stratified Observations"
"en" => "A Comparative Non Symmetrical Analysis with Stratified Observations"
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
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}
89 => Essec\Faculty\Model\Contribution {#2487
#_index: "academ_contributions"
#_id: "9818"
#_source: array:18 [
"id" => "9818"
"slug" => "representing-gaps-by-a-simultaneous-principal-component-analysis-onto-a-reference-subspace"
"yearMonth" => "1997-06"
"year" => "1997"
"title" => "Representing Gaps by a Simultaneous Principal Component Analysis onto a Reference Subspace"
"description" => "ESPOSITO VINZI, V. et BALBI, S. (1997). Representing Gaps by a Simultaneous Principal Component Analysis onto a Reference Subspace. Dans: <i>VIII International Symposium on Applied Stochastic Models and Data Analysis (ASMDA97)</i>. Naples: Rocco Curto Editore, pp. 135-140."
"authors" => array:2 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "BALBI Simona"
]
]
"ouvrage" => "VIII International Symposium on Applied Stochastic Models and Data Analysis (ASMDA97)"
"keywords" => array:1 [
0 => "Gaps -PCA"
]
"updatedAt" => "2021-07-13 14:31:21"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "135-140"
"volume" => null
"number" => null
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"type" => array:2 [
"fr" => "Actes d'une conférence"
"en" => "Conference Proceedings"
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"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
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"countries" => array:2 [
"fr" => null
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"abstract" => array:2 [
"fr" => "Representing Gaps by a Simultaneous Principal Component Analysis onto a Reference Subspace"
"en" => "Representing Gaps by a Simultaneous Principal Component Analysis onto a Reference Subspace"
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
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}
90 => Essec\Faculty\Model\Contribution {#2488
#_index: "academ_contributions"
#_id: "9819"
#_source: array:18 [
"id" => "9819"
"slug" => "rotated-canonical-analysis-onto-a-reference-subspace"
"yearMonth" => "1997-06"
"year" => "1997"
"title" => "Rotated Canonical Analysis onto a Reference Subspace"
"description" => "ESPOSITO VINZI, V. et BALBI, S. (1997). Rotated Canonical Analysis onto a Reference Subspace. Dans: <i>2nd World Conference of IASC</i>. Pasadena: University of Southern California, pp. 72-72."
"authors" => array:2 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "BALBI Simona"
]
]
"ouvrage" => "2nd World Conference of IASC"
"keywords" => array:1 [
0 => "Rotated Canonical Analysis -Reference Subspace"
]
"updatedAt" => "2021-07-13 14:31:21"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "72-72"
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Actes d'une conférence"
"en" => "Conference Proceedings"
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"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
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"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "Rotated Canonical Analysis onto a Reference Subspace"
"en" => "Rotated Canonical Analysis onto a Reference Subspace"
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
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+"parent": null
}
91 => Essec\Faculty\Model\Contribution {#2489
#_index: "academ_contributions"
#_id: "9826"
#_source: array:18 [
"id" => "9826"
"slug" => "visualising-quality-control-data-by-non-symmetrical-generalised-co-structure-analysis"
"yearMonth" => "1997-06"
"year" => "1997"
"title" => "Visualising Quality Control Data by Non Symmetrical Generalised Co-Structure Analysis"
"description" => "ESPOSITO VINZI, V. et SCEPI, G. (1997). Visualising Quality Control Data by Non Symmetrical Generalised Co-Structure Analysis. Dans: <i>Classification Group of the Italian Statistical Society associated with the International Federation of Classification Societies</i>. Pescara: La Stampa, pp. 53-56."
"authors" => array:2 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "SCEPI Germana"
]
]
"ouvrage" => "Classification Group of the Italian Statistical Society associated with the International Federation of Classification Societies"
"keywords" => array:1 [
0 => "Visualising Quality Control Data by Non Symmetrical Generalised Co-Visualising Quality Control Data"
]
"updatedAt" => "2021-07-13 14:31:21"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "53-56"
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Actes d'une conférence"
"en" => "Conference Proceedings"
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"support_type" => array:2 [
"fr" => "Presse"
"en" => "Press"
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"countries" => array:2 [
"fr" => null
"en" => null
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"abstract" => array:2 [
"fr" => "Visualising Quality Control Data by Non Symmetrical Generalised Co-Structure Analysis"
"en" => "Visualising Quality Control Data by Non Symmetrical Generalised Co-Structure Analysis"
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
92 => Essec\Faculty\Model\Contribution {#2490
#_index: "academ_contributions"
#_id: "9828"
#_source: array:18 [
"id" => "9828"
"slug" => "comparing-advertising-campaigns-by-means-of-textual-data-analysis-with-external-information"
"yearMonth" => "1998-06"
"year" => "1998"
"title" => "Comparing advertising campaigns by means of textual data analysis with external information"
"description" => "ESPOSITO VINZI, V. et BALBI, S. (1998). Comparing advertising campaigns by means of textual data analysis with external information. Dans: <i>Proceedings of 4èmes Journées Internationales d'Analyse Statistique des Données Textuelles (JADT'98)</i>. Nice: UPRESA, pp. 39-47."
"authors" => array:2 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "BALBI Simona"
]
]
"ouvrage" => "Proceedings of 4èmes Journées Internationales d'Analyse Statistique des Données Textuelles (JADT'98)"
"keywords" => array:1 [
0 => "Textual Data Analyses"
]
"updatedAt" => "2021-07-13 14:31:21"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "39-47"
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Actes d'une conférence"
"en" => "Conference Proceedings"
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"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
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"countries" => array:2 [
"fr" => null
"en" => null
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"abstract" => array:2 [
"fr" => "Journées Internationales d'Analyse Statistique des Données Textuelles (JADT'98)"
"en" => "Textual Data Analyses (JADT'98)"
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
93 => Essec\Faculty\Model\Contribution {#2491
#_index: "academ_contributions"
#_id: "9829"
#_source: array:18 [
"id" => "9829"
"slug" => "deterministic-and-probabilistic-models-for-symmetrical-and-non-symmetrical-principal-component-analysis"
"yearMonth" => "1998-12"
"year" => "1998"
"title" => "Deterministic and Probabilistic Models for Symmetrical and Non Symmetrical Principal Component Analysis"
"description" => "ESPOSITO VINZI, V. (1998). Deterministic and Probabilistic Models for Symmetrical and Non Symmetrical Principal Component Analysis. <i>Metron: international journal of statistics</i>, LVI(43924), pp. 139-154."
"authors" => array:1 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
]
"ouvrage" => ""
"keywords" => array:3 [
0 => "Models in Data AnalysisGeometrical models"
1 => "Probabilistic model"
2 => "Principal component analysis"
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"updatedAt" => "2021-07-13 14:31:21"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "139-154"
"volume" => "LVI"
"number" => "43924"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
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"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
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"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "This paper focuses on presenting geometrical and stochastic models for principal component analysis in both its classical and non-symmetrical (PCAR) versions."
"en" => "This paper focuses on presenting geometrical and stochastic models for principal component analysis in both its classical and non-symmetrical (PCAR) versions."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
94 => Essec\Faculty\Model\Contribution {#2492
#_index: "academ_contributions"
#_id: "9837"
#_source: array:18 [
"id" => "9837"
"slug" => "non-symmetrical-data-analysis-new-methods-and-applications"
"yearMonth" => "1998-06"
"year" => "1998"
"title" => "Non Symmetrical Data Analysis: New Methods and Applications"
"description" => "ESPOSITO VINZI, V. et LAURO, C. (1998). Non Symmetrical Data Analysis: New Methods and Applications. Dans: <i>Proceedings of 3rd conference on Statistical Computing of the Asian Regional Section (ARS) of IASC</i>. Manila: International Association for Statistical Computing (IASC), pp. 433-444."
"authors" => array:2 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "LAURO Carlo"
]
]
"ouvrage" => "Proceedings of 3rd conference on Statistical Computing of the Asian Regional Section (ARS) of IASC"
"keywords" => array:1 [
0 => "Non Symmetrical Data Analysis -New Methods -Applications"
]
"updatedAt" => "2021-07-13 14:31:21"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "433-444"
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Actes d'une conférence"
"en" => "Conference Proceedings"
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"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
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"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "Non Symmetrical Data Analysis: New Methods and Applications"
"en" => "Non Symmetrical Data Analysis: New Methods and Applications"
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
95 => Essec\Faculty\Model\Contribution {#2493
#_index: "academ_contributions"
#_id: "9845"
#_source: array:18 [
"id" => "9845"
"slug" => "a-non-symmetrical-generalised-co-structure-analysis-for-inspecting-quality-control-data"
"yearMonth" => "1999-04"
"year" => "1999"
"title" => "A Non Symmetrical Generalised Co-Structure Analysis for Inspecting Quality Control Data"
"description" => "ESPOSITO VINZI, V. et SCEPI, G. (1999). A Non Symmetrical Generalised Co-Structure Analysis for Inspecting Quality Control Data. Dans: <i>Classification and Data Analysis. Theory and Application</i>. 1st ed. Heidelberg: Springer, pp. 179-186."
"authors" => array:2 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "SCEPI Germana"
]
]
"ouvrage" => "Classification and Data Analysis. Theory and Application"
"keywords" => array:1 [
0 => "Co-Structure Analysis"
]
"updatedAt" => "2020-12-17 18:37:46"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "179-186"
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Chapitres"
"en" => "Book chapters"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "A Non Symmetrical Generalised Co-Structure Analysis for Inspecting Quality Control Data"
"en" => "A Non Symmetrical Generalised Co-Structure Analysis for Inspecting Quality Control Data"
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
96 => Essec\Faculty\Model\Contribution {#2494
#_index: "academ_contributions"
#_id: "9846"
#_source: array:18 [
"id" => "9846"
"slug" => "a-simultaneous-non-symmetrical-principal-component-analysis-with-a-group-structure"
"yearMonth" => "1999-10"
"year" => "1999"
"title" => "A Simultaneous Non-Symmetrical Principal Component Analysis with a Group Structure"
"description" => "ESPOSITO VINZI, V. et BALBI, S. (1999). A Simultaneous Non-Symmetrical Principal Component Analysis with a Group Structure. <i>Applied Stochastic Models in Business and Industry</i>, 15(4), pp. 301-309."
"authors" => array:2 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "BALBI Simona"
]
]
"ouvrage" => ""
"keywords" => array:3 [
0 => "Multiple sets"
1 => "Non-symmetrical analysisProcrustean rotation"
2 => "Sensory data"
]
"updatedAt" => "2021-07-13 14:31:21"
"publicationUrl" => "http://www3.interscience.wiley.com/cgi-bin/abstract/71500142/ABSTRACT"
"publicationInfo" => array:3 [
"pages" => "301-309"
"volume" => "15"
"number" => "4"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "The aim of this paper is to propose an extension of principal component analysis onto a reference subspace (PCAR) to the case where the same dependent variables have been measured on the same statistical units under two, or more, different observational conditions. As the units belong to the same multidimensional space, we profitably apply the orthogonal Procrustean rotations, jointly with PCAR, so as to enrich the interpretability of patterns on factorial planes. The proposed technique is applied to a problem of agreement in the area of sensory data analysis for representing evaluation gaps between the perception of quality by wine experts and ordinary consumers. The proposed approach allows to explain the eventually detected gaps in terms of the physical-chemical characteristics of wines."
"en" => "The aim of this paper is to propose an extension of principal component analysis onto a reference subspace (PCAR) to the case where the same dependent variables have been measured on the same statistical units under two, or more, different observational conditions. As the units belong to the same multidimensional space, we profitably apply the orthogonal Procrustean rotations, jointly with PCAR, so as to enrich the interpretability of patterns on factorial planes. The proposed technique is applied to a problem of agreement in the area of sensory data analysis for representing evaluation gaps between the perception of quality by wine experts and ordinary consumers. The proposed approach allows to explain the eventually detected gaps in terms of the physical-chemical characteristics of wines."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
97 => Essec\Faculty\Model\Contribution {#2495
#_index: "academ_contributions"
#_id: "9848"
#_source: array:18 [
"id" => "9848"
"slug" => "an-index-for-selecting-mixed-explanatory-variables-in-the-analysis-of-dependence"
"yearMonth" => "1999-08"
"year" => "1999"
"title" => "An Index for Selecting Mixed Explanatory Variables in the Analysis of Dependence"
"description" => "ESPOSITO VINZI, V. et PALUMBO, F. (1999). An Index for Selecting Mixed Explanatory Variables in the Analysis of Dependence. Dans: 52nd Session of the International Statistical Institute. Helsinki."
"authors" => array:2 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "PALUMBO Francesco"
]
]
"ouvrage" => "52nd Session of the International Statistical Institute"
"keywords" => array:1 [
0 => "Selecting Mixed Explanatory Variables"
]
"updatedAt" => "2021-07-13 14:31:21"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "An Index for Selecting Mixed Explanatory Variables in the Analysis of Dependence"
"en" => "An Index for Selecting Mixed Explanatory Variables in the Analysis of Dependence"
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
98 => Essec\Faculty\Model\Contribution {#2496
#_index: "academ_contributions"
#_id: "9860"
#_source: array:18 [
"id" => "9860"
"slug" => "multivariate-statistical-analyses-for-total-quality-measurement"
"yearMonth" => "1999-06"
"year" => "1999"
"title" => "Multivariate Statistical Analyses for Total Quality Measurement"
"description" => "ESPOSITO VINZI, V. et LAURO, C. (1999). Multivariate Statistical Analyses for Total Quality Measurement. Dans: <i>Proceedings of the IX International Symposium on Applied Stochastic Models and Data Analysis (ASMDA'99)</i>. Lisbon: Instituto Nacional De Estatistica (INE), pp. 5-12."
"authors" => array:2 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "LAURO Carlo"
]
]
"ouvrage" => "Proceedings of the IX International Symposium on Applied Stochastic Models and Data Analysis (ASMDA'99)"
"keywords" => array:1 [
0 => "Multivariate Statistical Analyses -Total Quality Measurement"
]
"updatedAt" => "2021-07-13 14:31:21"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "5-12"
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Actes d'une conférence"
"en" => "Conference Proceedings"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "Multivariate Statistical Analyses for Total Quality Measurement"
"en" => "Multivariate Statistical Analyses for Total Quality Measurement"
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
99 => Essec\Faculty\Model\Contribution {#2497
#_index: "academ_contributions"
#_id: "9861"
#_source: array:18 [
"id" => "9861"
"slug" => "multivariate-statistical-methods-for-total-quality-control-and-planning"
"yearMonth" => "1999-06"
"year" => "1999"
"title" => "Multivariate Statistical Methods for Total Quality Control and Planning"
"description" => "ESPOSITO VINZI, V. et LAURO, C. (1999). Multivariate Statistical Methods for Total Quality Control and Planning. Dans: <i>Proceedings of the VI Islamic Countries Conference on Statistical Sciences</i>. Lahore: Islamic Countries Society of Statistical Sciences (ISOSS), pp. 69-80."
"authors" => array:2 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "LAURO Carlo"
]
]
"ouvrage" => "Proceedings of the VI Islamic Countries Conference on Statistical Sciences"
"keywords" => array:1 [
0 => "Multivariate Statistical Methods -Total Quality Control -Planning"
]
"updatedAt" => "2021-07-13 14:31:21"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "69-80"
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Actes d'une conférence"
"en" => "Conference Proceedings"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "Multivariate Statistical Methods for Total Quality Control and Planning"
"en" => "Multivariate Statistical Methods for Total Quality Control and Planning"
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
100 => Essec\Faculty\Model\Contribution {#2498
#_index: "academ_contributions"
#_id: "9882"
#_source: array:18 [
"id" => "9882"
"slug" => "multivariate-approaches-for-aggregate-time-series"
"yearMonth" => "2000-06"
"year" => "2000"
"title" => "Multivariate Approaches for Aggregate Time Series"
"description" => "ESPOSITO VINZI, V. et DAVINO, C. (2000). Multivariate Approaches for Aggregate Time Series. Dans: <i>International Symposium on Computational Statistics</i>. Utrecht: Physica-Verlag, pp. 265-270."
"authors" => array:2 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "DAVINO Cristina"
]
]
"ouvrage" => "International Symposium on Computational Statistics"
"keywords" => array:1 [
0 => "Multivariate Approaches -Aggregate Time Series"
]
"updatedAt" => "2021-07-13 14:31:22"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "265-270"
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Actes d'une conférence"
"en" => "Conference Proceedings"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "Multivariate Approaches for Aggregate Time Series"
"en" => "Multivariate Approaches for Aggregate Time Series"
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
101 => Essec\Faculty\Model\Contribution {#2499
#_index: "academ_contributions"
#_id: "9884"
#_source: array:18 [
"id" => "9884"
"slug" => "non-symmetrical-data-analysis-approaches-recent-developments-and-perspectives"
"yearMonth" => "2000-03"
"year" => "2000"
"title" => "Non Symmetrical Data Analysis Approaches: Recent Developments and Perspectives"
"description" => "ESPOSITO VINZI, V. et LAURO, C. (2000). Non Symmetrical Data Analysis Approaches: Recent Developments and Perspectives. Dans: <i>Data Analysis, Scientific Modeling and Practical Application</i>. 1st ed. Heidelberg: Springer, pp. 219-232."
"authors" => array:2 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "LAURO Carlo"
]
]
"ouvrage" => "Data Analysis, Scientific Modeling and Practical Application"
"keywords" => array:2 [
0 => "Non Symmetrical Data AnalysisGeometrical approach to data analysis"
1 => "Complex Data Structures"
]
"updatedAt" => "2020-12-17 18:37:46"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "219-232"
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Chapitres"
"en" => "Book chapters"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => """
This paper initially intends to show the fundamental\n
ideas behind the methodological achievements of Non Symmetrical Data Analysis from a geometrical point of view. Then, the paper focuses on some of the most recent extensions by stressing and giving insights on their application aspects. Finally, the most promising directions of further research in this field our outlined.
"""
"en" => """
This paper initially intends to show the fundamental\n
ideas behind the methodological achievements of Non Symmetrical Data Analysis from a geometrical point of view. Then, the paper focuses on some of the most recent extensions by stressing and giving insights on their application aspects. Finally, the most promising directions of further research in this field our outlined.
"""
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
102 => Essec\Faculty\Model\Contribution {#2500
#_index: "academ_contributions"
#_id: "9885"
#_source: array:18 [
"id" => "9885"
"slug" => "non-symmetrical-multivariate-analyses-for-sensory-data"
"yearMonth" => "2000-06"
"year" => "2000"
"title" => "Non Symmetrical Multivariate Analyses for Sensory Data"
"description" => "ESPOSITO VINZI, V. et LAURO, C. (2000). Non Symmetrical Multivariate Analyses for Sensory Data. Dans: <i>Proceedings of Agro-Industrie et Statistique Conference</i>. Pau: Université de Pau et des pays de l’Adour (UPPA)."
"authors" => array:2 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "LAURO Carlo"
]
]
"ouvrage" => "Proceedings of Agro-Industrie et Statistique Conference"
"keywords" => array:1 [
0 => "Non Symmetrical Multivariate Analyses -Sensory Data"
]
"updatedAt" => "2021-07-13 14:31:22"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Actes d'une conférence"
"en" => "Conference Proceedings"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "Non Symmetrical Multivariate Analyses for Sensory Data"
"en" => "Non Symmetrical Multivariate Analyses for Sensory Data"
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
103 => Essec\Faculty\Model\Contribution {#2501
#_index: "academ_contributions"
#_id: "9886"
#_source: array:18 [
"id" => "9886"
"slug" => "non-symmetrical-comparative-analyses-for-quality-control"
"yearMonth" => "2000-06"
"year" => "2000"
"title" => "Non-Symmetrical Comparative Analyses for Quality Control"
"description" => "ESPOSITO VINZI, V. (2000). Non-Symmetrical Comparative Analyses for Quality Control. Dans: <i>3rd Millenium Challenge for Industrial Statistics</i>. Spetses: International Association for Statistical Computing (IASC)."
"authors" => array:1 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
]
"ouvrage" => "3rd Millenium Challenge for Industrial Statistics"
"keywords" => array:1 [
0 => "Non-Symmetrical Comparative Analyses"
]
"updatedAt" => "2021-07-13 14:31:22"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Actes d'une conférence"
"en" => "Conference Proceedings"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "Non-Symmetrical Comparative Analyses for Quality Control"
"en" => "Non-Symmetrical Comparative Analyses for Quality Control"
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
104 => Essec\Faculty\Model\Contribution {#2502
#_index: "academ_contributions"
#_id: "9887"
#_source: array:18 [
"id" => "9887"
"slug" => "rotated-canonical-analysis-onto-a-reference-subspace"
"yearMonth" => "2000-01"
"year" => "2000"
"title" => "Rotated Canonical Analysis onto a Reference Subspace"
"description" => "ESPOSITO VINZI, V. et BALBI, S. (2000). Rotated Canonical Analysis onto a Reference Subspace. <i>Computational Statistics and Data Analysis</i>, 32(43924), pp. 395-410."
"authors" => array:2 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "BALBI Simona"
]
]
"ouvrage" => ""
"keywords" => array:3 [
0 => "Analysis of Dependence Relationships"
1 => "Paired TablesPrincipal Component onto a Reference Subspace"
2 => "Procrustean Rotations"
]
"updatedAt" => "2021-07-13 14:31:22"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "395-410"
"volume" => "32"
"number" => "43924"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "This paper deals with a new approach to Procrustes rotations in factorial configurations. The aim is to investigate the agreement between dependence structures, relative to different conditions, with respect to a common set of explanatory variables. In this context, the definition of a common plane of representation is a relevant issue. A solution is proposed by referring to the geometrical features of both principal component analysis onto a reference subspace and Procrustes analysis. A practical example on sensory data regarding judgments on the Tocai friulano Italian wine finally helps in showing the feasibility of the proposed method and how well it suits the addressed problem."
"en" => "This paper deals with a new approach to Procrustes rotations in factorial configurations. The aim is to investigate the agreement between dependence structures, relative to different conditions, with respect to a common set of explanatory variables. In this context, the definition of a common plane of representation is a relevant issue. A solution is proposed by referring to the geometrical features of both principal component analysis onto a reference subspace and Procrustes analysis. A practical example on sensory data regarding judgments on the Tocai friulano Italian wine finally helps in showing the feasibility of the proposed method and how well it suits the addressed problem."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
105 => Essec\Faculty\Model\Contribution {#2503
#_index: "academ_contributions"
#_id: "9896"
#_source: array:18 [
"id" => "9896"
"slug" => "cross-validated-q2-bootstrap-distribution-estimated-for-the-choice-of-significant-components-in-partial-least-squared-regression"
"yearMonth" => "2001-06"
"year" => "2001"
"title" => "Cross validated Q2 bootstrap distribution estimated for the choice of significant components in Partial Least Squared Regression"
"description" => "ESPOSITO VINZI, V. et AMATO, S. (2001). Cross validated Q2 bootstrap distribution estimated for the choice of significant components in Partial Least Squared Regression. Dans: <i>PLS and Related Methods</i>. Paris: CISIA, pp. 344-356."
"authors" => array:2 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "AMATO Silvano"
]
]
"ouvrage" => "PLS and Related Methods"
"keywords" => array:1 [
0 => "Cross validated Q2 bootstrap distribution"
]
"updatedAt" => "2021-07-13 14:31:22"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "344-356"
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Actes d'une conférence"
"en" => "Conference Proceedings"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "Cross validated Q2 bootstrap distribution estimated for the choice of significant components in Partial Least Squared Regression"
"en" => "Cross validated Q2 bootstrap distribution estimated for the choice of significant components in Partial Least Squared Regression"
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
106 => Essec\Faculty\Model\Contribution {#2504
#_index: "academ_contributions"
#_id: "9899"
#_source: array:18 [
"id" => "9899"
"slug" => "explanatory-methods-for-comparative-analyses"
"yearMonth" => "2001-10"
"year" => "2001"
"title" => "Explanatory Methods for Comparative Analyses"
"description" => "ESPOSITO VINZI, V. (2001). Explanatory Methods for Comparative Analyses. <i>Chemometrics and Intelligent Laboratory Systems</i>, 58(2), pp. 275-286."
"authors" => array:1 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
]
"ouvrage" => ""
"keywords" => array:6 [
0 => "Dependence Relationships"
1 => "Multiple Tables"
2 => "Nonsymmetrical analysis"
3 => "Procrustes rotations"
4 => "Co-inertia"
5 => "Graphical representations"
]
"updatedAt" => "2021-07-13 14:31:22"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "275-286"
"volume" => "58"
"number" => "2"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "The aim of the paper is to give some insights into the different methods for the simultaneous and comparative analysis of particularly structured multiple matrices. These matrices are made up of multivariate multi-occasion data. These data relate to several variables collected on the same set of statistical units and under different observational conditions. The paper is set in a nonsymmetrical framework where external, usually condition-invariant, information on the variables' dependence structure is taken into account. Therefore, the paper proposes some extensions of the method called principal component analysis onto a reference subspace (PCAR) to the case of more than one response data sets. Finally, where they exist, the links between these methods and partial least squares (PLS) regression are presented. The geometrical aspects of such methods as well as their interpretative tools, useful in new specific fields of application, are the main focus of the paper."
"en" => "The aim of the paper is to give some insights into the different methods for the simultaneous and comparative analysis of particularly structured multiple matrices. These matrices are made up of multivariate multi-occasion data. These data relate to several variables collected on the same set of statistical units and under different observational conditions. The paper is set in a nonsymmetrical framework where external, usually condition-invariant, information on the variables' dependence structure is taken into account. Therefore, the paper proposes some extensions of the method called principal component analysis onto a reference subspace (PCAR) to the case of more than one response data sets. Finally, where they exist, the links between these methods and partial least squares (PLS) regression are presented. The geometrical aspects of such methods as well as their interpretative tools, useful in new specific fields of application, are the main focus of the paper."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
107 => Essec\Faculty\Model\Contribution {#2505
#_index: "academ_contributions"
#_id: "9919"
#_source: array:18 [
"id" => "9919"
"slug" => "visualisation-and-synthesis-of-customersatisfaction-in-terms-of-simbolic-data-analysis"
"yearMonth" => "2001-06"
"year" => "2001"
"title" => "Visualisation and Synthesis of CustomerSatisfaction in terms of Simbolic Data Analysis"
"description" => "ESPOSITO VINZI, V., LAURO, C. et SCEPI, G. (2001). Visualisation and Synthesis of CustomerSatisfaction in terms of Simbolic Data Analysis. Dans: <i>Processes and Statistical Methods for Evaluation</i>. Rome: Centro Italiano Studi Ufologici (CISU), pp. 129-136."
"authors" => array:3 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "LAURO Carlo"
]
2 => array:1 [
"name" => "SCEPI Germana"
]
]
"ouvrage" => "Processes and Statistical Methods for Evaluation"
"keywords" => array:1 [
0 => "Visualisation -Synthesis -CustomerSatisfaction"
]
"updatedAt" => "2021-07-13 14:31:23"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "129-136"
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Actes d'une conférence"
"en" => "Conference Proceedings"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "Visualisation and Synthesis of CustomerSatisfaction"
"en" => "Visualisation and Synthesis of CustomerSatisfaction"
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
108 => Essec\Faculty\Model\Contribution {#2506
#_index: "academ_contributions"
#_id: "9934"
#_source: array:18 [
"id" => "9934"
"slug" => "multivariate-total-quality-control-foundation-and-recent-advances"
"yearMonth" => "2002-01"
"year" => "2002"
"title" => "Multivariate Total Quality Control: Foundation and Recent Advances"
"description" => "ESPOSITO VINZI, V., LAURO, C., ANTOCH, J. et SAPORTA, G. [Eds] (2002). <i>Multivariate Total Quality Control: Foundation and Recent Advances</i>. Heidelberg: Physica-Verlag."
"authors" => array:4 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "LAURO Carlo"
]
2 => array:1 [
"name" => "ANTOCH Jaromir"
]
3 => array:1 [
"name" => "SAPORTA Gilbert"
]
]
"ouvrage" => ""
"keywords" => array:6 [
0 => "Multivariate Analysis"
1 => "Quality ControlOn-line and off-line process control"
2 => "robust and non-parametric approaches"
3 => "customer satisfaction"
4 => "interval data"
5 => "multioccasion observations"
]
"updatedAt" => "2020-12-17 18:37:46"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Direction d'ouvrage"
"en" => "Book editor"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "The major focus of the book is on using the methods suitable for an on-line and off-line process control both in the univariate and multivariate case. The authors not only concentrate on the standard situation when the errors accompanying the observed process are normally distributed, but also describe in detail the more general situations that call for the use of the robust and non-parametric approaches. Within these approaches, the use of recent methods of the multivariate analysis in the total quality control is enhanced with particular reference to the customer satisfaction area, the monitoring of interval data and the comparison of patterns generated from multioccasion observations. The authors cover both pratical computational aspects of the problem and the necessary mathematical background, taking into account requirements of total quality control."
"en" => "The major focus of the book is on using the methods suitable for an on-line and off-line process control both in the univariate and multivariate case. The authors not only concentrate on the standard situation when the errors accompanying the observed process are normally distributed, but also describe in detail the more general situations that call for the use of the robust and non-parametric approaches. Within these approaches, the use of recent methods of the multivariate analysis in the total quality control is enhanced with particular reference to the customer satisfaction area, the monitoring of interval data and the comparison of patterns generated from multioccasion observations. The authors cover both pratical computational aspects of the problem and the necessary mathematical background, taking into account requirements of total quality control."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
109 => Essec\Faculty\Model\Contribution {#2507
#_index: "academ_contributions"
#_id: "9935"
#_source: array:18 [
"id" => "9935"
"slug" => "non-symmetrical-multivariate-statistical-methods-for-quality-control-and-batch-processes-monitoring"
"yearMonth" => "2002-09"
"year" => "2002"
"title" => "Non Symmetrical Multivariate Statistical Methods for Quality Control and Batch Processes Monitoring"
"description" => "LAURO, C. et ESPOSITO VINZI, V. (2002). Non Symmetrical Multivariate Statistical Methods for Quality Control and Batch Processes Monitoring. Dans: <i>Analisi Multivariata per la Qualità Totale</i>. 1st ed. Milano: FrancoAngeli, pp. 45-65."
"authors" => array:2 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "LAURO Carlo"
]
]
"ouvrage" => "Analisi Multivariata per la Qualità Totale"
"keywords" => array:4 [
0 => "Quality Control"
1 => "Batch MonitoringNon symmetrical data analysis"
2 => "Partial Least Squares methods"
3 => "Visualization techniques"
]
"updatedAt" => "2020-12-17 18:37:46"
"publicationUrl" => "http://www.francoangeli.it/Ricerca/Scheda_Libro.asp?CodiceLibro=1340.71&bcsi_scan_008BB8921E145D2F=6NL+PC/vKCdNWEKBzThiHA0AAABGlPUF&bcsi_scan_filename=Scheda_Libro.asp"
"publicationInfo" => array:3 [
"pages" => "45-65"
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Chapitres"
"en" => "Book chapters"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "A brief outline of the evolution of the statistical techniques for the measurement of quality is firstly sketched. A critical overview of T2-based methods that require strong assumptions on the variables distribution is given. The need for multivariate procedures is justified from both the methodological and application point of view and a proposal of non parametric control charts is shown. The attention is then focused on visualising and monitoring quality rather than building control charts both at unit and batch level. The interpretation properties and visualisation facilities of Non Symmetrical Data Analysis and PLS-based methods are shown to fit quite naturally the demands arising when measuring and monitoring quality of multivariate industrial processes. Some research perspectives are finally enhanced."
"en" => "A brief outline of the evolution of the statistical techniques for the measurement of quality is firstly sketched. A critical overview of T2-based methods that require strong assumptions on the variables distribution is given. The need for multivariate procedures is justified from both the methodological and application point of view and a proposal of non parametric control charts is shown. The attention is then focused on visualising and monitoring quality rather than building control charts both at unit and batch level. The interpretation properties and visualisation facilities of Non Symmetrical Data Analysis and PLS-based methods are shown to fit quite naturally the demands arising when measuring and monitoring quality of multivariate industrial processes. Some research perspectives are finally enhanced."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
110 => Essec\Faculty\Model\Contribution {#2508
#_index: "academ_contributions"
#_id: "9936"
#_source: array:18 [
"id" => "9936"
"slug" => "non-symmetrical-comparative-analysis-for-quality-control"
"yearMonth" => "2002-01"
"year" => "2002"
"title" => "Non-Symmetrical Comparative Analysis for Quality Control"
"description" => "ESPOSITO VINZI, V. (2002). Non-Symmetrical Comparative Analysis for Quality Control. Dans: <i>Multivariate Total Quality Control: Foundation and Recent Advances</i>. 1st ed. Heidelberg: Springer, pp. 191-220."
"authors" => array:1 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
]
"ouvrage" => "Multivariate Total Quality Control: Foundation and Recent Advances"
"keywords" => array:4 [
0 => "Quality Control"
1 => "Non Symmetrical Data AnalysisComparative Analysis"
2 => "Procrustean Rotations"
3 => "Co-Inertia Analysis"
]
"updatedAt" => "2020-12-17 18:37:46"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "191-220"
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Chapitres"
"en" => "Book chapters"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "The first part of this paper intends to show the fundamental ideas behind the methodological achievements of Non--Symmetrical Data Analysis (NSDA) from a geometrical point of view. Then the paper focuses on some of the most recent extensions of NSDA which aim at studying multiple tables with comparative purposes by stressing their graphical aspects and giving insights on their interpretation tools. The methods presented in this part are then applied on a couple of data sets from the field of sensory analysis and water quality control. Finally, some of the most promising directions of further research in this field are outlined. S-Plus codes implement the four non--symmetrical comparative analyses presented in the paper."
"en" => "The first part of this paper intends to show the fundamental ideas behind the methodological achievements of Non--Symmetrical Data Analysis (NSDA) from a geometrical point of view. Then the paper focuses on some of the most recent extensions of NSDA which aim at studying multiple tables with comparative purposes by stressing their graphical aspects and giving insights on their interpretation tools. The methods presented in this part are then applied on a couple of data sets from the field of sensory analysis and water quality control. Finally, some of the most promising directions of further research in this field are outlined. S-Plus codes implement the four non--symmetrical comparative analyses presented in the paper."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
111 => Essec\Faculty\Model\Contribution {#2509
#_index: "academ_contributions"
#_id: "9937"
#_source: array:18 [
"id" => "9937"
"slug" => "proceedings-of-the-xli-sis-scientific-meetingand-a-system-for-the-european-customer-satisfaction"
"yearMonth" => "2002-06"
"year" => "2002"
"title" => "Proceedings of the XLI SIS Scientific Meetingand a System for the European Customer Satisfaction"
"description" => "ESPOSITO VINZI, V. et LAURO, C. (2002). Proceedings of the XLI SIS Scientific Meetingand a System for the European Customer Satisfaction. Dans: <i>Proceedings of the XLI SIS Scientific Meeting</i>. Milan: CLEUP, pp. 201-210."
"authors" => array:2 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "LAURO Carlo"
]
]
"ouvrage" => "Proceedings of the XLI SIS Scientific Meeting"
"keywords" => array:1 [
0 => "PLS Path Modeling -"
]
"updatedAt" => "2021-07-13 14:31:23"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "201-210"
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Actes d'une conférence"
"en" => "Conference Proceedings"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "PLS Path Modeling contributions"
"en" => "Proceedings of the XLI SIS Scientific Meeting"
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
112 => Essec\Faculty\Model\Contribution {#2510
#_index: "academ_contributions"
#_id: "9938"
#_source: array:18 [
"id" => "9938"
"slug" => "regression-lineaire-generalisee-pls"
"yearMonth" => "2002-06"
"year" => "2002"
"title" => "Régression linéaire généralisée PLS"
"description" => "ESPOSITO VINZI, V., BASTIEN, P. et TENENHAUS, M. (2002). Régression linéaire généralisée PLS. Dans: <i>HEC School of Business and Management</i>. Jouy-en-Josas: HEC."
"authors" => array:3 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "BASTIEN P."
]
2 => array:1 [
"name" => "TENENHAUS Michel"
]
]
"ouvrage" => "HEC School of Business and Management"
"keywords" => array:1 [
0 => "PLS generalised linear regression"
]
"updatedAt" => "2021-07-13 14:31:23"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Actes d'une conférence"
"en" => "Conference Proceedings"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "Régression linéaire généralisée PLS"
"en" => "PLS generalised linear regression"
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
113 => Essec\Faculty\Model\Contribution {#2511
#_index: "academ_contributions"
#_id: "9940"
#_source: array:18 [
"id" => "9940"
"slug" => "state-of-art-on-pls-path-modeling-through-the-available-software"
"yearMonth" => "2002-06"
"year" => "2002"
"title" => "State-of-art on PLS Path Modeling through the available software"
"description" => "ESPOSITO VINZI, V., CHATELIN, Y.M. et TENENHAUS, M. (2002). State-of-art on PLS Path Modeling through the available software. Dans: <i>HEC School of Business and Management</i>. Jouy-en-Josas: HEC."
"authors" => array:3 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "CHATELIN Y.M."
]
2 => array:1 [
"name" => "TENENHAUS Michel"
]
]
"ouvrage" => "HEC School of Business and Management"
"keywords" => array:1 [
0 => "PLS Path Modeling"
]
"updatedAt" => "2021-07-13 14:31:23"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Actes d'une conférence"
"en" => "Conference Proceedings"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "State-of-art on PLS Path Modeling through the available software"
"en" => "State-of-art on PLS Path Modeling through the available software"
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
114 => Essec\Faculty\Model\Contribution {#2512
#_index: "academ_contributions"
#_id: "9941"
#_source: array:18 [
"id" => "9941"
"slug" => "the-pls-approach-to-generalized-linear-models-and-casual-path-modeling-algorithms-and-applications"
"yearMonth" => "2002-06"
"year" => "2002"
"title" => "The PLS approach to Generalized Linear Models and Casual Path Modeling: Algorithms and Applications"
"description" => "ESPOSITO VINZI, V. (2002). The PLS approach to Generalized Linear Models and Casual Path Modeling: Algorithms and Applications. Dans: <i>Geoscience and Remote Sensing, Proceedings of the 34th Symposium on the Interface</i>. Washington DC: Interfaces, pp. 447-447."
"authors" => array:1 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
]
"ouvrage" => "Geoscience and Remote Sensing, Proceedings of the 34th Symposium on the Interface"
"keywords" => array:1 [
0 => "PLS approach -Generalized Linear Models -Casual Path Modeling"
]
"updatedAt" => "2021-07-13 14:31:23"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "447-447"
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Actes d'une conférence"
"en" => "Conference Proceedings"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "The PLS approach to Generalized Linear Models and Casual Path Modeling: Algorithms and Applications"
"en" => "The PLS approach to Generalized Linear Models and Casual Path Modeling: Algorithms and Applications"
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
115 => Essec\Faculty\Model\Contribution {#2513
#_index: "academ_contributions"
#_id: "9942"
#_source: array:18 [
"id" => "9942"
"slug" => "three-way-data-analysis-and-pls-path-modeling-for-estimating-components-of-a-temporal-process"
"yearMonth" => "2002-06"
"year" => "2002"
"title" => "Three-Way Data Analysis and PLS Path Modeling for Estimating Components of a Temporal Process"
"description" => "ESPOSITO VINZI, V. et SCEPI, G. (2002). Three-Way Data Analysis and PLS Path Modeling for Estimating Components of a Temporal Process. Dans: <i>Atti della XLI Riunione Scientifica SIS</i>. Milan: CLEUP, pp. 387-390."
"authors" => array:2 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "SCEPI Germama"
]
]
"ouvrage" => "Atti della XLI Riunione Scientifica SIS"
"keywords" => array:1 [
0 => "Three-Way Data Analysis -PLS Path Modeling"
]
"updatedAt" => "2021-07-13 14:31:23"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "387-390"
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Actes d'une conférence"
"en" => "Conference Proceedings"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "Three-Way Data Analysis and PLS Path Modeling for Estimating Components of a Temporal Process"
"en" => "Three-Way Data Analysis and PLS Path Modeling for Estimating Components of a Temporal Process"
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
116 => Essec\Faculty\Model\Contribution {#2514
#_index: "academ_contributions"
#_id: "9950"
#_source: array:18 [
"id" => "9950"
"slug" => "bootstrap-based-q%cc%82kh2-for-the-selection-of-components-and-variables-in-pls-regression"
"yearMonth" => "2003-10"
"year" => "2003"
"title" => "Bootstrap-based Q̂kh2 for the selection of components and variables in PLS regression"
"description" => "AMATO, S. et ESPOSITO VINZI, V. (2003). Bootstrap-based Q̂kh2 for the selection of components and variables in PLS regression. <i>Chemometrics and Intelligent Laboratory Systems</i>, 68(43862), pp. 5-16."
"authors" => array:2 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "AMATO Silvano"
]
]
"ouvrage" => ""
"keywords" => array:5 [
0 => "Variable and Component Selection"
1 => "RegressionPartial Least Squares Regression"
2 => "Irrelevant factors"
3 => "Bootstrap"
4 => "Cross-validation"
]
"updatedAt" => "2022-12-05 14:03:54"
"publicationUrl" => "https://doi.org/10.1016/S0169-7439(03)00083-2"
"publicationInfo" => array:3 [
"pages" => "5-16"
"volume" => "68"
"number" => "43862"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "The aim of this paper is to suggest a bootstrap-based method for choosing the number of components in Partial Least Squares Regression (PLSR). Cross-validated Qh2 statistic is used, for which is intended to derive a bootstrap distribution and to perform a hypothesis testing. Monte Carlo approximation is adopted. Applications on both artificial and real data are presented."
"en" => "The aim of this paper is to suggest a bootstrap-based method for choosing the number of components in Partial Least Squares Regression (PLSR). Cross-validated Qh2 statistic is used, for which is intended to derive a bootstrap distribution and to perform a hypothesis testing. Monte Carlo approximation is adopted. Applications on both artificial and real data are presented."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
117 => Essec\Faculty\Model\Contribution {#2515
#_index: "academ_contributions"
#_id: "9970"
#_source: array:18 [
"id" => "9970"
"slug" => "pls-path-modelling-and-multiple-tables-analysis-an-integrated-approach-for-time-dependent-data"
"yearMonth" => "2003-06"
"year" => "2003"
"title" => "PLS Path Modelling and Multiple Tables Analysis: an integrated approach for time dependent data"
"description" => "ESPOSITO VINZI, V. et SCEPI, G. (2003). PLS Path Modelling and Multiple Tables Analysis: an integrated approach for time dependent data. Dans: <i>PLS and Related Methods</i>. Paris: Decisia, pp. 453-463."
"authors" => array:2 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "SCEPI Germana"
]
]
"ouvrage" => "PLS and Related Methods"
"keywords" => array:3 [
0 => "PLS"
1 => "Path Modelling"
2 => "Multiple Tables Analysis"
]
"updatedAt" => "2021-07-13 14:31:24"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "453-463"
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Actes d'une conférence"
"en" => "Conference Proceedings"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "PLS Path Modelling and Multiple Tables Analysis"
"en" => "PLS Path Modelling and Multiple Tables Analysis"
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
118 => Essec\Faculty\Model\Contribution {#2516
#_index: "academ_contributions"
#_id: "9971"
#_source: array:18 [
"id" => "9971"
"slug" => "pls-regression-and-classification"
"yearMonth" => "2003-06"
"year" => "2003"
"title" => "PLS Regression and Classification"
"description" => "ESPOSITO VINZI, V. et LAURO, C. (2003). PLS Regression and Classification. Dans: <i>PLS and related methods, Proceedings of the PLS'03 International Symposium</i>. Paris: Decisia, pp. 45-56."
"authors" => array:2 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "LAURO Carlo"
]
]
"ouvrage" => "PLS and related methods, Proceedings of the PLS'03 International Symposium"
"keywords" => array:3 [
0 => "PLS"
1 => "Regression"
2 => "Classification"
]
"updatedAt" => "2021-07-13 14:31:24"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "45-56"
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Actes d'une conférence"
"en" => "Conference Proceedings"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "PLS regression et classification"
"en" => "PLS regression and classification"
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
119 => Essec\Faculty\Model\Contribution {#2517
#_index: "academ_contributions"
#_id: "9972"
#_source: array:18 [
"id" => "9972"
"slug" => "pls-typological-regression-algorithmic-validation-and-classification-issues"
"yearMonth" => "2003-09"
"year" => "2003"
"title" => "PLS Typological Regression: algorithmic, validation and classification issues"
"description" => "ESPOSITO VINZI, V., LAURO, C. et AMATO, S. (2003). PLS Typological Regression: algorithmic, validation and classification issues. Dans: <i>Riunione Scientifica del Gruppo di Classificazione e Analisi dei Dati della SIS</i>. Bologna: CLUEB, pp. 163-166."
"authors" => array:3 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "LAURO Carlo"
]
2 => array:1 [
"name" => "AMATO Silvano"
]
]
"ouvrage" => "Riunione Scientifica del Gruppo di Classificazione e Analisi dei Dati della SIS"
"keywords" => array:2 [
0 => "PLS"
1 => "Regression"
]
"updatedAt" => "2021-07-13 14:31:24"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "163-166"
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Actes d'une conférence"
"en" => "Conference Proceedings"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "PLS Typological Regression: algorithmic, validation and classification issues"
"en" => "PLS Typological Regression: algorithmic, validation and classification issues"
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
120 => Essec\Faculty\Model\Contribution {#2518
#_index: "academ_contributions"
#_id: "9973"
#_source: array:18 [
"id" => "9973"
"slug" => "pls-based-strategies-in-consumer-preferences-and-sensory-analysis-an-application-to-the-cosmetic-industry"
"yearMonth" => "2003-06"
"year" => "2003"
"title" => "PLS-based strategies in consumer preferences and sensory analysis: an application to the cosmetic industry"
"description" => "ESPOSITO VINZI, V., SQUILLACCIOTTI, S., GUINOT, C. et TENENHAUS, M. (2003). PLS-based strategies in consumer preferences and sensory analysis: an application to the cosmetic industry. Dans: <i>PLS and Related Methods</i>. Paris: Decisia, pp. 311-323."
"authors" => array:4 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "SQUILLACCIOTTI Silvia"
]
2 => array:1 [
"name" => "GUINOT Christiane"
]
3 => array:1 [
"name" => "TENENHAUS Michel"
]
]
"ouvrage" => "PLS and Related Methods"
"keywords" => array:2 [
0 => "PLS"
1 => "consumer preferences"
]
"updatedAt" => "2021-07-13 14:31:24"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "311-323"
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Actes d'une conférence"
"en" => "Conference Proceedings"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "PLS-based strategies in consumer preferences and sensory analysis"
"en" => "PLS-based strategies in consumer preferences and sensory analysis"
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
121 => Essec\Faculty\Model\Contribution {#2519
#_index: "academ_contributions"
#_id: "9983"
#_source: array:18 [
"id" => "9983"
"slug" => "two-step-pls-regression-for-l-structured-data-an-application-in-the-cosmetics-industry"
"yearMonth" => "2003-06"
"year" => "2003"
"title" => "Two-step PLS Regression for L-Structured Data: an application in the cosmetics industry"
"description" => "ESPOSITO VINZI, V., GUINOT, C. et SQUILLACCIOTTI, S. (2003). Two-step PLS Regression for L-Structured Data: an application in the cosmetics industry. Dans: <i>Proceedings of the SIS Conference on "Multivariate Statistical Analysis for Social Sciences, Economics, Natural Sciences and Technology</i>. Naples: RCE Edizioni, pp. 157-169."
"authors" => array:3 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "GUINOT Christiane"
]
2 => array:1 [
"name" => "SQUILLACCIOTTI Silvia"
]
]
"ouvrage" => "Proceedings of the SIS Conference on "Multivariate Statistical Analysis for Social Sciences, Economics, Natural Sciences and Technology"
"keywords" => array:2 [
0 => "Two-step"
1 => "PLS -Regression"
]
"updatedAt" => "2021-07-13 14:31:24"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "157-169"
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Actes d'une conférence"
"en" => "Conference Proceedings"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "Two-step PLS Regression for L-Structured Data"
"en" => "Two-step PLS Regression for L-Structured Data"
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
122 => Essec\Faculty\Model\Contribution {#2520
#_index: "academ_contributions"
#_id: "9986"
#_source: array:18 [
"id" => "9986"
"slug" => "a-global-goodness-of-fit-index-for-pls-structural-equation-modelling"
"yearMonth" => "2004-06"
"year" => "2004"
"title" => "A global Goodness-of-Fit index for PLS structural equation modelling"
"description" => "TENENHAUS, M., AMATO, S. et ESPOSITO VINZI, V. (2004). A global Goodness-of-Fit index for PLS structural equation modelling. Dans: <i>XLII SIS Scientific Meeting</i>. Padova: CLEUP, pp. 739-742."
"authors" => array:3 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "TENENHAUS Michel"
]
2 => array:1 [
"name" => "AMATO Silvano"
]
]
"ouvrage" => "XLII SIS Scientific Meeting"
"keywords" => array:1 [
0 => "PLS structural equation modelling"
]
"updatedAt" => "2021-07-13 14:31:24"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "739-742"
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Actes d'une conférence"
"en" => "Conference Proceedings"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "A global Goodness-of-Fit index for PLS structural equation modelling"
"en" => "A global Goodness-of-Fit index for PLS structural equation modelling"
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
123 => Essec\Faculty\Model\Contribution {#2521
#_index: "academ_contributions"
#_id: "10015"
#_source: array:18 [
"id" => "10015"
"slug" => "linear-and-non-linear-pls-models-for-the-prediction-of-consumer-preferences-using-the-notion-of-average-judge"
"yearMonth" => "2004-09"
"year" => "2004"
"title" => "Linear and Non-Linear PLS Models for the Prediction of Consumer Preferences using the notion of "Average Judge""
"description" => "ESPOSITO VINZI, V., TRINCHERA, L., AMBROISINE, L., SQUILLACCIOTTI, S. et TENENHAUS, M. (2004). Linear and Non-Linear PLS Models for the Prediction of Consumer Preferences using the notion of "Average Judge". Dans: A Sense of Identity, European Conference on Sensory Science of Food and Beverages. Florence."
"authors" => array:5 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "TRINCHERA Laura"
]
2 => array:1 [
"name" => "AMBROISINE Laurence"
]
3 => array:1 [
"name" => "SQUILLACCIOTTI Silvia"
]
4 => array:1 [
"name" => "TENENHAUS Michel"
]
]
"ouvrage" => "A Sense of Identity, European Conference on Sensory Science of Food and Beverages"
"keywords" => array:1 [
0 => "Linear and Non-Linear PLS Models"
]
"updatedAt" => "2021-07-13 14:31:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Communications dans une conférence"
"en" => "Presentations at an Academic or Professional conference"
]
"support_type" => array:2 [
"fr" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "Linear and Non-Linear PLS Models for the Prediction of Consumer Preferences using the notion of "Average Judge""
"en" => "Linear and Non-Linear PLS Models for the Prediction of Consumer Preferences using the notion of "Average Judge""
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
124 => Essec\Faculty\Model\Contribution {#2522
#_index: "academ_contributions"
#_id: "10021"
#_source: array:18 [
"id" => "10021"
"slug" => "orthogonal-projection-to-latent-structures-in-models-for-l-structured-data"
"yearMonth" => "2004-06"
"year" => "2004"
"title" => "Orthogonal Projection to Latent Structures in Models for L-structured Data"
"description" => "SQUILLACCIOTTI, S., GUINOT, C. et ESPOSITO VINZI, V. (2004). Orthogonal Projection to Latent Structures in Models for L-structured Data. Dans: <i>XLII SIS Scientific Meeting</i>. Padova: CLEUP, pp. 63-66."
"authors" => array:3 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "SQUILLACCIOTTI Silvia"
]
2 => array:1 [
"name" => "GUINOT Christiane"
]
]
"ouvrage" => "XLII SIS Scientific Meeting"
"keywords" => array:1 [
0 => "Projection to Latent Structures"
]
"updatedAt" => "2021-07-13 14:31:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "63-66"
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Actes d'une conférence"
"en" => "Conference Proceedings"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "Orthogonal Projection to Latent Structures in Models for L-structured Data"
"en" => "Orthogonal Projection to Latent Structures in Models for L-structured Data"
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
125 => Essec\Faculty\Model\Contribution {#2523
#_index: "academ_contributions"
#_id: "10028"
#_source: array:18 [
"id" => "10028"
"slug" => "strategie-de-comparaison-de-modeles-pls-pour-letude-des-preferences-des-consommateurs-avec-informations-externes"
"yearMonth" => "2004-02"
"year" => "2004"
"title" => "Stratégie de comparaison de modèles PLS pour l'étude des préférences des consommateurs avec informations externes"
"description" => "ESPOSITO VINZI, V., SQUILLACCIOTTI, S., AMATO, S. et GUINOT, C. (2004). Stratégie de comparaison de modèles PLS pour l'étude des préférences des consommateurs avec informations externes. Dans: <i>8émes Journées Européennes Agro-Industrie et Méthodes Statistiques</i>. Rennes: École nationale supérieure agronomique de Rennes (ENSAR), pp. 199-206."
"authors" => array:4 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "SQUILLACCIOTTI Silvia"
]
2 => array:1 [
"name" => "AMATO Silvano"
]
3 => array:1 [
"name" => "GUINOT Christiane"
]
]
"ouvrage" => "8émes Journées Européennes Agro-Industrie et Méthodes Statistiques"
"keywords" => array:2 [
0 => "PLS"
1 => "consumer preferences"
]
"updatedAt" => "2021-07-13 14:31:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "199-206"
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Actes d'une conférence"
"en" => "Conference Proceedings"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "Stratégie de comparaison de modèles PLS pour l'étude des préférences des consommateurs avec informations externes"
"en" => "Stratégie de comparaison de modèles PLS pour l'étude des préférences des consommateurs avec informations externes"
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
126 => Essec\Faculty\Model\Contribution {#2524
#_index: "academ_contributions"
#_id: "10079"
#_source: array:18 [
"id" => "10079"
"slug" => "pls-generalised-regression"
"yearMonth" => "2005-01"
"year" => "2005"
"title" => "PLS Generalised Regression"
"description" => "BASTIEN, P., ESPOSITO VINZI, V. et TENENHAUS, M. (2005). PLS Generalised Regression. <i>Computational Statistics and Data Analysis</i>, 48(1), pp. 17-46."
"authors" => array:3 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "BASTIEN Philippe"
]
2 => array:1 [
"name" => "TENENHAUS Michel"
]
]
"ouvrage" => ""
"keywords" => array:5 [
0 => "Partial Least Squares"
1 => "Generalised Linear RegressionPartial least squares regression"
2 => "Stepwise regression"
3 => "Variable selection"
4 => "Modified PLS regression"
]
"updatedAt" => "2021-07-13 14:31:26"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "17-46"
"volume" => "48"
"number" => "1"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "PLS univariate regression is a model linking a dependent variable y to a set X={x1,¿,xp} of (numerical or categorical) explanatory variables. It can be obtained as a series of simple and multiple regressions. By taking advantage from the statistical tests associated with linear regression, it is feasible to select the significant explanatory variables to include in PLS regression and to choose the number of PLS components to retain. The principle of the presented algorithm may be similarly used in order to yield an extension of PLS regression to PLS generalised linear regression. The modifications to classical PLS regression, the case of PLS logistic regression and the application of PLS generalised linear regression to survival data are studied in detail. Some examples show the use of the proposed methods in real practice. As a matter of fact, classical PLS univariate regression is the result of an iterated use of ordinary least squares (OLS) where PLS stands for partial least squares. PLS generalised linear regression retains the rationale of PLS while the criterion optimised at each step is based on maximum likelihood. Nevertheless, the acronym PLS is kept as a reference to a general methodology for relating a response variable to a set of predictors. The approach proposed for PLS generalised linear regression is simple and easy to implement. Moreover, it can be easily generalised to any model that is linear at the level of the explanatory variables."
"en" => "PLS univariate regression is a model linking a dependent variable y to a set X={x1,¿,xp} of (numerical or categorical) explanatory variables. It can be obtained as a series of simple and multiple regressions. By taking advantage from the statistical tests associated with linear regression, it is feasible to select the significant explanatory variables to include in PLS regression and to choose the number of PLS components to retain. The principle of the presented algorithm may be similarly used in order to yield an extension of PLS regression to PLS generalised linear regression. The modifications to classical PLS regression, the case of PLS logistic regression and the application of PLS generalised linear regression to survival data are studied in detail. Some examples show the use of the proposed methods in real practice. As a matter of fact, classical PLS univariate regression is the result of an iterated use of ordinary least squares (OLS) where PLS stands for partial least squares. PLS generalised linear regression retains the rationale of PLS while the criterion optimised at each step is based on maximum likelihood. Nevertheless, the acronym PLS is kept as a reference to a general methodology for relating a response variable to a set of predictors. The approach proposed for PLS generalised linear regression is simple and easy to implement. Moreover, it can be easily generalised to any model that is linear at the level of the explanatory variables."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
127 => Essec\Faculty\Model\Contribution {#2525
#_index: "academ_contributions"
#_id: "10080"
#_source: array:18 [
"id" => "10080"
"slug" => "pls-path-modeling"
"yearMonth" => "2005-01"
"year" => "2005"
"title" => "PLS Path Modeling"
"description" => "TENENHAUS, M., ESPOSITO VINZI, V., CHATELIN, Y.M. et LAURO, C. (2005). PLS Path Modeling. <i>Computational Statistics and Data Analysis</i>, 48(1), pp. 159-205."
"authors" => array:4 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "TENENHAUS Michel"
]
2 => array:1 [
"name" => "CHATELIN Yves-Marie"
]
3 => array:1 [
"name" => "LAURO Carlo"
]
]
"ouvrage" => ""
"keywords" => array:3 [
0 => "Structural Equation Modeling"
1 => "Partial least squaresPLS approach"
2 => "Multiple table analysis"
]
"updatedAt" => "2021-07-13 14:31:26"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "159-205"
"volume" => "48"
"number" => "1"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => """
A presentation of the Partial Least Squares approach to Structural Equation Modeling (or PLS\n
Path Modeling) is given together with a discussion of its extensions. This approach is compared\n
with the estimation of Structural Equation Modeling by means of maximum likelihood (SEM-ML).\n
Notwithstanding, this approach still shows some weaknesses. In this respect, some new\n
improvements are proposed. Furthermore, PLS path modeling can be used for analyzing multiple\n
tables so as to be related to more classical data analysis methods used in this field. Finally, a\n
complete treatment of a real example is shown through the available software.
"""
"en" => """
A presentation of the Partial Least Squares approach to Structural Equation Modeling (or PLS\n
Path Modeling) is given together with a discussion of its extensions. This approach is compared\n
with the estimation of Structural Equation Modeling by means of maximum likelihood (SEM-ML).\n
Notwithstanding, this approach still shows some weaknesses. In this respect, some new\n
improvements are proposed. Furthermore, PLS path modeling can be used for analyzing multiple\n
tables so as to be related to more classical data analysis methods used in this field. Finally, a\n
complete treatment of a real example is shown through the available software.
"""
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
128 => Essec\Faculty\Model\Contribution {#2526
#_index: "academ_contributions"
#_id: "10081"
#_source: array:18 [
"id" => "10081"
"slug" => "pls-regression-pls-path-modeling-and-generalized-procrustean-analysis-a-combined-approach-for-multiblock-analysis"
"yearMonth" => "2005-11"
"year" => "2005"
"title" => "PLS Regression, PLS Path Modeling and Generalized Procrustean Analysis: A Combined Approach for Multiblock Analysis"
"description" => "TENENHAUS, M. et ESPOSITO VINZI, V. (2005). PLS Regression, PLS Path Modeling and Generalized Procrustean Analysis: A Combined Approach for Multiblock Analysis. <i>Journal of Chemometrics</i>, 19, pp. 145-153."
"authors" => array:2 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "TENENHAUS Michel"
]
]
"ouvrage" => ""
"keywords" => array:6 [
0 => "Sensory Analysis"
1 => "Multiblock analysis"
2 => "Partial Least Squares ApproachPLS regression"
3 => "PLS path modeling"
4 => "Generalized canonical correlation analysis"
5 => "Generalized Procrustean analysis"
]
"updatedAt" => "2021-07-13 14:31:26"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "145-153"
"volume" => "19"
"number" => null
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "A situation where J blocks of variables are observed on the same set of individuals is considered in this paper. A factor analysis logic is applied to tables instead of variables. The latent variables of each block should well explain their own block and, at the same time, the latent variables of same order should be as positively correlated as possible to improve interpretation. The paper first (1) reviews the main methods for multiblock analysis based on a criterion to be optimized, (2) describes the hierarchical PLS path modeling algorithm and (3) recalls that it allows one to recover some usual multiblock analysis methods. It is then supposed that the number of latent variables can be different from one block to another and that these latent variables are orthogonal. PLS regression and PLS path modeling are used for this situation. The relation between Horst's generalized canonical correlation analysis and generalized Procrustean analysis for this specific application is also studied. The approach is illustrated by an example from sensory analysis."
"en" => "A situation where J blocks of variables are observed on the same set of individuals is considered in this paper. A factor analysis logic is applied to tables instead of variables. The latent variables of each block should well explain their own block and, at the same time, the latent variables of same order should be as positively correlated as possible to improve interpretation. The paper first (1) reviews the main methods for multiblock analysis based on a criterion to be optimized, (2) describes the hierarchical PLS path modeling algorithm and (3) recalls that it allows one to recover some usual multiblock analysis methods. It is then supposed that the number of latent variables can be different from one block to another and that these latent variables are orthogonal. PLS regression and PLS path modeling are used for this situation. The relation between Horst's generalized canonical correlation analysis and generalized Procrustean analysis for this specific application is also studied. The approach is illustrated by an example from sensory analysis."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
129 => Essec\Faculty\Model\Contribution {#2527
#_index: "academ_contributions"
#_id: "10082"
#_source: array:18 [
"id" => "10082"
"slug" => "pls-typological-regression-algorithmic-classification-and-validation-issues"
"yearMonth" => "2005-04"
"year" => "2005"
"title" => "PLS Typological Regression: Algorithmic, Classification and Validation Issues"
"description" => "ESPOSITO VINZI, V., LAURO, C. et AMATO, S. (2005). PLS Typological Regression: Algorithmic, Classification and Validation Issues. Dans: <i>New Developments in Classification and Data Analysis</i>. 1st ed. New York: Springer, pp. 133-140."
"authors" => array:3 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "LAURO Carlo"
]
2 => array:1 [
"name" => "AMATO Silvano"
]
]
"ouvrage" => "New Developments in Classification and Data Analysis"
"keywords" => array:4 [
0 => "Partial Least Squares"
1 => "Regression"
2 => "ClassificationDistance from the model"
3 => "Prediction-oriented classes"
]
"updatedAt" => "2020-12-17 18:37:46"
"publicationUrl" => "http://www.springer.com/west/home/statistics/business?SGWID=4-10135-22-40802327-0&bcsi_scan_FFDAA2550BA9B46D=XiU7zpker8w4jETC9+lRmQMAAADvAU4A"
"publicationInfo" => array:3 [
"pages" => "133-140"
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Chapitres"
"en" => "Book chapters"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => """
Classification, within a PLS regression framework, is classically meant in the sense of the SIMCA methodology, i.e. as the assignment of statistical units to a-priori defined classes. As a matter of fact, PLS components are built with\n
the double objective of describing the set of explanatory variables while predicting the set of response variables. Taking into account this objective, a classification\n
algorithm is developed that allows to build typologies of statistical units whose different local PLS models have an intrinsic explanatory power higher than the\n
initial global PLS model. The typology induced by the algorithm may undergo a non parametric validation procedure based on bootstrap. Finally, the definition of\n
a compromise model is investigated.
"""
"en" => """
Classification, within a PLS regression framework, is classically meant in the sense of the SIMCA methodology, i.e. as the assignment of statistical units to a-priori defined classes. As a matter of fact, PLS components are built with\n
the double objective of describing the set of explanatory variables while predicting the set of response variables. Taking into account this objective, a classification\n
algorithm is developed that allows to build typologies of statistical units whose different local PLS models have an intrinsic explanatory power higher than the\n
initial global PLS model. The typology induced by the algorithm may undergo a non parametric validation procedure based on bootstrap. Finally, the definition of\n
a compromise model is investigated.
"""
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
130 => Essec\Faculty\Model\Contribution {#2528
#_index: "academ_contributions"
#_id: "10149"
#_source: array:18 [
"id" => "10149"
"slug" => "pls-typological-path-modeling-a-model-based-approach-to-classification"
"yearMonth" => "2006-06"
"year" => "2006"
"title" => "PLS Typological Path Modeling: a model-based approach to classification"
"description" => "ESPOSITO VINZI, V., TRINCHERA, L. et SQUILLACCIOTTI, S. (2006). PLS Typological Path Modeling: a model-based approach to classification. Dans: <i>Knowledge Extraction and Modeling Workshop</i>. Naples: Tilapia, pp. 87-88."
"authors" => array:3 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "TRINCHERA Laura"
]
2 => array:1 [
"name" => "SQUILLACCIOTTI Silvia"
]
]
"ouvrage" => "Knowledge Extraction and Modeling Workshop"
"keywords" => array:1 [
0 => "PLS Typological Path Modeling -"
]
"updatedAt" => "2021-07-13 14:31:28"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "87-88"
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Actes d'une conférence"
"en" => "Conference Proceedings"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "PLS Typological Path Modeling: a model-based approach to classification"
"en" => "PLS Typological Path Modeling: a model-based approach to classification"
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
131 => Essec\Faculty\Model\Contribution {#2529
#_index: "academ_contributions"
#_id: "13384"
#_source: array:18 [
"id" => "13384"
"slug" => "a-psychological-approach-to-learning-causal-networks"
"yearMonth" => "2014-06"
"year" => "2014"
"title" => "A psychological approach to learning causal networks"
"description" => "ZARGOUSH, M., ALEMI, F., ESPOSITO VINZI, V., VANG, J. et KHEIRBEK, R. (2014). A psychological approach to learning causal networks. <i>Health Care Management Science</i>, 17(2), pp. 194-201."
"authors" => array:5 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "ZARGOUSH Manaf"
]
2 => array:1 [
"name" => "ALEMI Farrokh"
]
3 => array:1 [
"name" => "VANG Jee"
]
4 => array:1 [
"name" => "KHEIRBEK Raya"
]
]
"ouvrage" => ""
"keywords" => []
"updatedAt" => "2022-12-05 13:50:23"
"publicationUrl" => "https://doi.org/10.1007/s10729-013-9250-2"
"publicationInfo" => array:3 [
"pages" => "194-201"
"volume" => "17"
"number" => "2"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "We examine the role of a common cognitive heuristic in unsupervised learning of Bayesian probability networks from data. Human beings perceive a larger association between causal than diagnostic relationships. This psychological principal can be used to orient the arcs within Bayesian networks by prohibiting the direction that is less predictive. The heuristic increased predictive accuracy by an average of 0.51 % percent, a small amount. It also increased total agreement between different network learning algorithms (Max Spanning Tree, Taboo, EQ, SopLeq, and Taboo Order) by 25 %. Prior to use of the heuristic, the multiple raters Kappa between the algorithms was 0.60 (95 % confidence interval, CI, from 0.53 to 0.67) indicating moderate agreement among the networks learned through different algorithms. After the use of the heuristic, the multiple raters Kappa was 0.85 (95 % CI from 0.78 to 0.92). There was a statistically significant increase in agreement between the five algorithms (alpha < 0.05). These data suggest that the heuristic increased agreement between networks learned through use of different algorithms, without loss of predictive accuracy. Additional research is needed to see if findings persist in other data sets and to explain why a heuristic used by humans could improve construct validity of mathematical algorithms."
"en" => "We examine the role of a common cognitive heuristic in unsupervised learning of Bayesian probability networks from data. Human beings perceive a larger association between causal than diagnostic relationships. This psychological principal can be used to orient the arcs within Bayesian networks by prohibiting the direction that is less predictive. The heuristic increased predictive accuracy by an average of 0.51 % percent, a small amount. It also increased total agreement between different network learning algorithms (Max Spanning Tree, Taboo, EQ, SopLeq, and Taboo Order) by 25 %. Prior to use of the heuristic, the multiple raters Kappa between the algorithms was 0.60 (95 % confidence interval, CI, from 0.53 to 0.67) indicating moderate agreement among the networks learned through different algorithms. After the use of the heuristic, the multiple raters Kappa was 0.85 (95 % CI from 0.78 to 0.92). There was a statistically significant increase in agreement between the five algorithms (alpha < 0.05). These data suggest that the heuristic increased agreement between networks learned through use of different algorithms, without loss of predictive accuracy. Additional research is needed to see if findings persist in other data sets and to explain why a heuristic used by humans could improve construct validity of mathematical algorithms."
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2024-11-23T09:21:42.000Z"
]
+lang: "fr"
+"_type": "_doc"
+"_score": 4.4197
+"parent": null
}
]
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1 => "<a href="https://scholar.google.com/citations?user=Pn7LTYIAAAAJ" target="_blank">Google scholar</a>"
]
"docTitle" => "Vincenzo ESPOSITO VINZI"
"docSubtitle" => "Professeur"
"docDescription" => "Département: Systèmes d'Information, Data Analytics et Opérations<br>Campus de Cergy"
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]
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}