Essec\Faculty\Model\Profile {#2216
#_id: "B00024825"
#_source: array:40 [
"bid" => "B00024825"
"academId" => "2028"
"slug" => "de-bruyn-arnaud"
"fullName" => "Arnaud de BRUYN"
"lastName" => "de BRUYN"
"firstName" => "Arnaud"
"title" => array:2 [
"fr" => "Professeur"
"en" => "Professor"
]
"email" => "debruyn@essec.edu"
"status" => "ACTIF"
"campus" => "Campus de Cergy"
"departments" => []
"phone" => "+33 (0)1 34 43 32 46"
"sites" => []
"facNumber" => "2028"
"externalCvUrl" => "https://faculty.essec.edu/en/cv/de-bruyn-arnaud/pdf"
"googleScholarUrl" => "https://scholar.google.com/citations?user=4rVAgWUAAAAJ"
"facOrcId" => "https://orcid.org/0000-0002-4413-6167"
"career" => array:18 [
0 => Essec\Faculty\Model\CareerItem {#2251
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2004-07-01"
"endDate" => "2008-08-31"
"isInternalPosition" => true
"type" => array:2 [
"fr" => "Positions académiques principales"
"en" => "Full-time academic appointments"
]
"label" => array:2 [
"fr" => "Professeur assistant"
"en" => "Assistant Professor"
]
"institution" => array:2 [
"fr" => "ESSEC Business School"
"en" => "ESSEC Business School"
]
"country" => array:2 [
"fr" => "France"
"en" => "France"
]
]
+lang: "en"
+"parent": Essec\Faculty\Model\Profile {#2216}
}
1 => Essec\Faculty\Model\CareerItem {#2252
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2008-09-01"
"endDate" => "2011-08-31"
"isInternalPosition" => true
"type" => array:2 [
"fr" => "Positions académiques principales"
"en" => "Full-time academic appointments"
]
"label" => array:2 [
"fr" => "Professeur associé"
"en" => "Associate Professor"
]
"institution" => array:2 [
"fr" => "ESSEC Business School"
"en" => "ESSEC Business School"
]
"country" => array:2 [
"fr" => "France"
"en" => "France"
]
]
+lang: "en"
+"parent": Essec\Faculty\Model\Profile {#2216}
}
2 => Essec\Faculty\Model\CareerItem {#2253
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2011-09-01"
"endDate" => null
"isInternalPosition" => true
"type" => array:2 [
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"en" => "Full-time academic appointments"
]
"label" => array:2 [
"fr" => "Professeur"
"en" => "Professor"
]
"institution" => array:2 [
"fr" => "ESSEC Business School"
"en" => "ESSEC Business School"
]
"country" => array:2 [
"fr" => "France"
"en" => "France"
]
]
+lang: "en"
+"parent": Essec\Faculty\Model\Profile {#2216}
}
3 => Essec\Faculty\Model\CareerItem {#2254
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2011-09-01"
"endDate" => "2014-08-31"
"isInternalPosition" => true
"type" => array:2 [
"en" => "Other appointments"
"fr" => "Autres positions"
]
"label" => array:2 [
"fr" => "Responsable du Département Marketing"
"en" => "Head of the Marketing Department"
]
"institution" => array:2 [
"fr" => "ESSEC Business School"
"en" => "ESSEC Business School"
]
"country" => array:2 [
"fr" => "France"
"en" => "France"
]
]
+lang: "en"
+"parent": Essec\Faculty\Model\Profile {#2216}
}
4 => Essec\Faculty\Model\CareerItem {#2255
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2015-01-01"
"endDate" => null
"isInternalPosition" => true
"type" => array:2 [
"en" => "Other appointments"
"fr" => "Autres positions"
]
"label" => array:2 [
"fr" => "Chercheur Invité Eminent, Institute for the Study of Business Markets"
"en" => "Distinguished Visiting Research Scholar, Institute for the Study of Business Markets"
]
"institution" => array:2 [
"fr" => "Penn State University"
"en" => "Penn State University"
]
"country" => array:2 [
"fr" => "États-Unis"
"en" => "United States of America"
]
]
+lang: "en"
+"parent": Essec\Faculty\Model\Profile {#2216}
}
5 => Essec\Faculty\Model\CareerItem {#2256
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2005-01-01"
"endDate" => "2014-12-31"
"isInternalPosition" => true
"type" => array:2 [
"en" => "Other appointments"
"fr" => "Autres positions"
]
"label" => array:2 [
"fr" => "Chercheur Invité, Institute for the Study of Business Markets"
"en" => "Visiting Research Scholar, Institute for the Study of Business Markets"
]
"institution" => array:2 [
"fr" => "Penn State University"
"en" => "Penn State University"
]
"country" => array:2 [
"fr" => "États-Unis"
"en" => "United States of America"
]
]
+lang: "en"
+"parent": Essec\Faculty\Model\Profile {#2216}
}
6 => Essec\Faculty\Model\CareerItem {#2257
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2000-01-01"
"endDate" => "2004-12-31"
"isInternalPosition" => true
"type" => array:2 [
"en" => "Other appointments"
"fr" => "Autres positions"
]
"label" => array:2 [
"fr" => "Assistant de Recherche"
"en" => "Research Assistant"
]
"institution" => array:2 [
"fr" => "Penn State University"
"en" => "Penn State University"
]
"country" => array:2 [
"fr" => "États-Unis"
"en" => "United States of America"
]
]
+lang: "en"
+"parent": Essec\Faculty\Model\Profile {#2216}
}
7 => Essec\Faculty\Model\CareerItem {#2258
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "1994-01-01"
"endDate" => "1997-12-31"
"isInternalPosition" => true
"type" => array:2 [
"en" => "Other Academic Appointments"
"fr" => "Autres positions académiques"
]
"label" => array:2 [
"fr" => "Assistant au Professeur"
"en" => "Teaching Assistant"
]
"institution" => array:2 [
"fr" => "Université de Liège"
"en" => "Université de Liège"
]
"country" => array:2 [
"fr" => "Belgique"
"en" => "Belgium"
]
]
+lang: "en"
+"parent": Essec\Faculty\Model\Profile {#2216}
}
8 => Essec\Faculty\Model\CareerItem {#2259
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2013-01-01"
"endDate" => null
"isInternalPosition" => true
"type" => array:2 [
"en" => "Professional appointments"
"fr" => "Positions professionnelles"
]
"label" => array:2 [
"fr" => "Fondateur"
"en" => "Founder"
]
"institution" => array:2 [
"fr" => "DECISIVE SYSTEM s.p.r.l."
"en" => "DECISIVE SYSTEM s.p.r.l."
]
"country" => array:2 [
"fr" => "Belgique"
"en" => "Belgium"
]
]
+lang: "en"
+"parent": Essec\Faculty\Model\Profile {#2216}
}
9 => Essec\Faculty\Model\CareerItem {#2260
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2011-01-01"
"endDate" => "2016-12-31"
"isInternalPosition" => true
"type" => array:2 [
"en" => "Professional appointments"
"fr" => "Positions professionnelles"
]
"label" => array:2 [
"fr" => "Co-fondateur"
"en" => "Co-founder"
]
"institution" => array:2 [
"fr" => "île aux trésors s.p.r.l."
"en" => "île aux trésors s.p.r.l."
]
"country" => array:2 [
"fr" => "Belgique"
"en" => "Belgium"
]
]
+lang: "en"
+"parent": Essec\Faculty\Model\Profile {#2216}
}
10 => Essec\Faculty\Model\CareerItem {#2261
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2016-01-01"
"endDate" => null
"isInternalPosition" => true
"type" => array:2 [
"en" => "Professional appointments"
"fr" => "Positions professionnelles"
]
"label" => array:2 [
"fr" => "Principal & Chef de Projet (Solution Architect)"
"en" => "Principal & Lead Solution Architect"
]
"institution" => array:2 [
"fr" => "DecisionPro, Inc."
"en" => "DecisionPro, Inc."
]
"country" => array:2 [
"fr" => "États-Unis"
"en" => "United States of America"
]
]
+lang: "en"
+"parent": Essec\Faculty\Model\Profile {#2216}
}
11 => Essec\Faculty\Model\CareerItem {#2262
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2014-01-01"
"endDate" => null
"isInternalPosition" => true
"type" => array:2 [
"en" => "Professional appointments"
"fr" => "Positions professionnelles"
]
"label" => array:2 [
"fr" => "Membre du Conseil d'Administration"
"en" => "Board Member"
]
"institution" => array:2 [
"fr" => "DecisionPro, Inc."
"en" => "DecisionPro, Inc."
]
"country" => array:2 [
"fr" => "États-Unis"
"en" => "United States of America"
]
]
+lang: "en"
+"parent": Essec\Faculty\Model\Profile {#2216}
}
12 => Essec\Faculty\Model\CareerItem {#2263
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2006-01-01"
"endDate" => "2014-12-31"
"isInternalPosition" => true
"type" => array:2 [
"en" => "Professional appointments"
"fr" => "Positions professionnelles"
]
"label" => array:2 [
"fr" => "Consultant Senior"
"en" => "Senior Consultant"
]
"institution" => array:2 [
"fr" => "DecisionPro, Inc."
"en" => "DecisionPro, Inc."
]
"country" => array:2 [
"fr" => "États-Unis"
"en" => "United States of America"
]
]
+lang: "en"
+"parent": Essec\Faculty\Model\Profile {#2216}
}
13 => Essec\Faculty\Model\CareerItem {#2264
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2005-01-01"
"endDate" => "2006-12-31"
"isInternalPosition" => true
"type" => array:2 [
"en" => "Professional appointments"
"fr" => "Positions professionnelles"
]
"label" => array:2 [
"fr" => "Director de Recherche et Développement Marketing"
"en" => "Director of Marketing Research & Development"
]
"institution" => array:2 [
"fr" => "QualiData"
"en" => "QualiData"
]
"country" => array:2 [
"fr" => "France"
"en" => "France"
]
]
+lang: "en"
+"parent": Essec\Faculty\Model\Profile {#2216}
}
14 => Essec\Faculty\Model\CareerItem {#2265
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "1998-07-01"
"endDate" => "2000-12-31"
"isInternalPosition" => true
"type" => array:2 [
"en" => "Professional appointments"
"fr" => "Positions professionnelles"
]
"label" => array:2 [
"fr" => "Chef Analyste, Directeur du Développement"
"en" => "Head Analyst, Director of Development"
]
"institution" => array:2 [
"fr" => "QualiData"
"en" => "QualiData"
]
"country" => array:2 [
"fr" => "France"
"en" => "France"
]
]
+lang: "en"
+"parent": Essec\Faculty\Model\Profile {#2216}
}
15 => Essec\Faculty\Model\CareerItem {#2266
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "1997-07-01"
"endDate" => "1998-07-01"
"isInternalPosition" => true
"type" => array:2 [
"en" => "Professional appointments"
"fr" => "Positions professionnelles"
]
"label" => array:2 [
"fr" => "Analyste Data, Assistant de Développement"
"en" => "Data Analyst, Development Assistant"
]
"institution" => array:2 [
"fr" => "QualiData"
"en" => "QualiData"
]
"country" => array:2 [
"fr" => "France"
"en" => "France"
]
]
+lang: "en"
+"parent": Essec\Faculty\Model\Profile {#2216}
}
16 => Essec\Faculty\Model\CareerItem {#2267
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "1997-01-01"
"endDate" => "1997-06-30"
"isInternalPosition" => true
"type" => array:2 [
"en" => "Professional appointments"
"fr" => "Positions professionnelles"
]
"label" => array:2 [
"fr" => "Analyste Programmation"
"en" => "Programmer-Analyst"
]
"institution" => array:2 [
"fr" => "Optimus"
"en" => "Optimus"
]
"country" => array:2 [
"fr" => "France"
"en" => "France"
]
]
+lang: "en"
+"parent": Essec\Faculty\Model\Profile {#2216}
}
17 => Essec\Faculty\Model\CareerItem {#2268
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2021-09-01"
"endDate" => "2024-08-31"
"isInternalPosition" => true
"type" => array:2 [
"en" => "Other appointments"
"fr" => "Autres positions"
]
"label" => array:2 [
"fr" => "Doyen Associé en charge du programme doctoral"
"en" => "Associate Dean for PhD program"
]
"institution" => array:2 [
"fr" => "ESSEC Business School"
"en" => "ESSEC Business School"
]
"country" => array:2 [
"fr" => "France"
"en" => "France"
]
]
+lang: "en"
+"parent": Essec\Faculty\Model\Profile {#2216}
}
]
"diplomes" => array:2 [
0 => Essec\Faculty\Model\Diplome {#2218
#_index: null
#_id: null
#_source: array:6 [
"diplome" => "DIPLOMA"
"type" => array:2 [
"fr" => "Diplômes"
"en" => "Diplomas"
]
"year" => "2004"
"label" => array:2 [
"en" => "Ph.D. in Business Administration"
"fr" => "Ph.D. en Administration Commerciale"
]
"institution" => array:2 [
"fr" => "Penn State University"
"en" => "Penn State University"
]
"country" => array:2 [
"fr" => "États-Unis"
"en" => "United States of America"
]
]
+lang: "en"
+"parent": Essec\Faculty\Model\Profile {#2216}
}
1 => Essec\Faculty\Model\Diplome {#2220
#_index: null
#_id: null
#_source: array:6 [
"diplome" => "DIPLOMA"
"type" => array:2 [
"fr" => "Diplômes"
"en" => "Diplomas"
]
"year" => "1997"
"label" => array:2 [
"en" => "Master in Economics"
"fr" => "Master en Economie"
]
"institution" => array:2 [
"fr" => "Université de Liège"
"en" => "Université de Liège"
]
"country" => array:2 [
"fr" => "Belgique"
"en" => "Belgium"
]
]
+lang: "en"
+"parent": Essec\Faculty\Model\Profile {#2216}
}
]
"bio" => array:2 [
"fr" => null
"en" => """
<p>I am Professor of Marketing and Associate Dean for the Ph.D. Program at ESSEC Business School, near Paris, France. I am also Distinguished Visiting Research Scholar at the Institute for the Study of Business Markets (Penn State University), Founder of DECISIVE SYSTEM (a European fundraising analytics company), and Principal at DecisionPro inc. (a U.S.-based marketing analytics software company).</p>\n
\n
<p>I’m passionate about marketing analytics, especially as it applies to fundraising analytics, marketing engineering, and artificial intelligence. I am a teacher, a researcher, a consultant, a business developer, and even a software architect, depending on the time of day (or night).</p>\n
\n
<p>In terms of research and publications, our work has been published in Journal of Marketing Research, Marketing Science, Management Science, Information Systems Research, International Journal of Research in Marketing (best paper award, Jan-Benedict Steenkamp Award for Long-Term Impact, and Emerald citation excellence award), and a few others. I am a member of the editorial review board of the International Journal of Research in Marketing (IJRM) and the Journal of Interactive Marketing.</p>\n
\n
<p>My teaching focuses on data-driven marketing decision-making, marketing analytics and marketing models. I have developed a MOOC on marketing analytics with Coursera, and have won the Marketing Beast Teacher Award at ESSEC.</p>\n
\n
<p>As a personal note, I was born in Belgium in 1973, and my native language is French.</p>\n
"""
]
"department" => array:2 [
"fr" => "Marketing"
"en" => "Marketing"
]
"site" => array:2 [
"fr" => null
"en" => null
]
"industrrySectors" => array:2 [
"fr" => null
"en" => null
]
"researchFields" => array:2 [
"fr" => "Marketing et analyses des données - Modèles marketing"
"en" => "Marketing and Data Analytics - Marketing Models"
]
"teachingFields" => array:2 [
"fr" => "Marketing et analyses des données - Modèles marketing"
"en" => "Marketing and Data Analytics - Marketing Models"
]
"distinctions" => array:19 [
0 => Essec\Faculty\Model\Distinction {#2269
#_index: null
#_id: null
#_source: array:6 [
"date" => "2008-01-01"
"label" => array:2 [
"fr" => "Bourse de Recherche, ESSEC Research Center: How to Profile and Target your Customers Using Collaborative Database Profiling"
"en" => "Grant, How to Profile and Target your Customers Using Collaborative Database Profiling ESSEC Research Center"
]
"type" => array:2 [
"fr" => "Bourses"
"en" => "Grants"
]
"tri" => " 2 "
"institution" => array:2 [
"fr" => "ESSEC Business School"
"en" => "ESSEC Business School"
]
"country" => array:2 [
"fr" => "France"
"en" => "France"
]
]
+lang: "en"
+"parent": Essec\Faculty\Model\Profile {#2216}
}
1 => Essec\Faculty\Model\Distinction {#2270
#_index: null
#_id: null
#_source: array:6 [
"date" => "2008-01-01"
"label" => array:2 [
"fr" => "Bourse de Recherche, ESSEC Research Center: Greed, Fear, Vision: How Organizational Incentives Affect Marketing Decision Support System Adoption"
"en" => "Grant: Greed, Fear, Vision: How Organizational Incentives Affect Marketing Decision Support System Adoption ESSEC Research Center"
]
"type" => array:2 [
"fr" => "Bourses"
"en" => "Grants"
]
"tri" => " 2 "
"institution" => array:2 [
"fr" => "ESSEC Business School"
"en" => "ESSEC Business School"
]
"country" => array:2 [
"fr" => "France"
"en" => "France"
]
]
+lang: "en"
+"parent": Essec\Faculty\Model\Profile {#2216}
}
2 => Essec\Faculty\Model\Distinction {#2271
#_index: null
#_id: null
#_source: array:6 [
"date" => "2005-01-01"
"label" => array:2 [
"fr" => "Bourse de Recherche, ESSEC Research Center: Online Recommender Systems and the Design of Virtual Sales Agents"
"en" => "Grant: Online Recommender Systems and the Design of Virtual Sales Agents ESSEC Research Center"
]
"type" => array:2 [
"fr" => "Bourses"
"en" => "Grants"
]
"tri" => " 2 "
"institution" => array:2 [
"fr" => "ESSEC Business School"
"en" => "ESSEC Business School"
]
"country" => array:2 [
"fr" => "France"
"en" => "France"
]
]
+lang: "en"
+"parent": Essec\Faculty\Model\Profile {#2216}
}
3 => Essec\Faculty\Model\Distinction {#2272
#_index: null
#_id: null
#_source: array:6 [
"date" => "2004-01-01"
"label" => array:2 [
"fr" => "Bourse de Recherche: Online Recommender Systems e-Business Research Center"
"en" => "Grant: Online Recommender Systems e-Business Research Center"
]
"type" => array:2 [
"fr" => "Bourses"
"en" => "Grants"
]
"tri" => " 2 "
"institution" => array:2 [
"fr" => "Penn State University"
"en" => "Penn State University"
]
"country" => array:2 [
"fr" => "États-Unis"
"en" => "United States of America"
]
]
+lang: "en"
+"parent": Essec\Faculty\Model\Profile {#2216}
}
4 => Essec\Faculty\Model\Distinction {#2273
#_index: null
#_id: null
#_source: array:6 [
"date" => "2002-01-01"
"label" => array:2 [
"fr" => "Bourse de Recherche: Is The Small World Even Smaller Online (And Is It So Small After All)? e-Business Research Center"
"en" => "Grant: Is The Small World Even Smaller Online (And Is It So Small After All)? e-Business Research Center"
]
"type" => array:2 [
"fr" => "Bourses"
"en" => "Grants"
]
"tri" => " 2 "
"institution" => array:2 [
"fr" => "Penn State University"
"en" => "Penn State University"
]
"country" => array:2 [
"fr" => "États-Unis"
"en" => "United States of America"
]
]
+lang: "en"
+"parent": Essec\Faculty\Model\Profile {#2216}
}
5 => Essec\Faculty\Model\Distinction {#2274
#_index: null
#_id: null
#_source: array:6 [
"date" => "2001-01-01"
"label" => array:2 [
"fr" => "Bourse de Recherche: Antecedents of Wireless Internet Adoption in the US, in the UK and in Japan e-Business Research Center"
"en" => "Grant: Antecedents of Wireless Internet Adoption in the US, in the UK and in Japan e-Business Research Center"
]
"type" => array:2 [
"fr" => "Bourses"
"en" => "Grants"
]
"tri" => " 2 "
"institution" => array:2 [
"fr" => "Penn State University"
"en" => "Penn State University"
]
"country" => array:2 [
"fr" => "États-Unis"
"en" => "United States of America"
]
]
+lang: "en"
+"parent": Essec\Faculty\Model\Profile {#2216}
}
6 => Essec\Faculty\Model\Distinction {#2275
#_index: null
#_id: null
#_source: array:6 [
"date" => "2000-01-01"
"label" => array:2 [
"fr" => "Bourse de Recherche: Improving Conjoint by Incorporating Uncertainty (co-applicant) Institute for the Study of Business Markets"
"en" => "Grant: Improving Conjoint by Incorporating Uncertainty (co-applicant) Institute for the Study of Business Markets"
]
"type" => array:2 [
"fr" => "Bourses"
"en" => "Grants"
]
"tri" => " 2 "
"institution" => array:2 [
"fr" => "Penn State University"
"en" => "Penn State University"
]
"country" => array:2 [
"fr" => "États-Unis"
"en" => "United States of America"
]
]
+lang: "en"
+"parent": Essec\Faculty\Model\Profile {#2216}
}
7 => Essec\Faculty\Model\Distinction {#2276
#_index: null
#_id: null
#_source: array:6 [
"date" => "2012-07-01"
"label" => array:2 [
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]
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]
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"institution" => array:2 [
"fr" => null
"en" => null
]
"country" => array:2 [
"fr" => null
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]
]
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+"parent": Essec\Faculty\Model\Profile {#2216}
}
8 => Essec\Faculty\Model\Distinction {#2277
#_index: null
#_id: null
#_source: array:6 [
"date" => "2018-06-21"
"label" => array:2 [
"fr" => "2018 Jan-Benedict E.M. Steenkamp Award for Long-Term Impact pour son article "A multi-stage model of word-of-mouth influence through viral marketing", International Journal of Research in Marketing, vol. 25(3), pp. 151-163."
"en" => "2018 Jan-Benedict E.M. Steenkamp Award for Long-Term Impact, (2008), A multi-stage model of word-of-mouth influence through viral marketing, International Journal of Research in Marketing, vol. 25(3), pp. 151-163."
]
"type" => array:2 [
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]
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]
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}
9 => Essec\Faculty\Model\Distinction {#2278
#_index: null
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"label" => array:2 [
"fr" => "Prix d'Excellence en Enseignement"
"en" => "Excellence in Teaching Award"
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"fr" => "Prix"
"en" => "Awards"
]
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"en" => "ESSEC Business School"
]
"country" => array:2 [
"fr" => "France"
"en" => "France"
]
]
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+"parent": Essec\Faculty\Model\Profile {#2216}
}
10 => Essec\Faculty\Model\Distinction {#2279
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"label" => array:2 [
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"en" => "Best Paper Award International Journal of Research in Marketing"
]
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"en" => "Awards"
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"institution" => array:2 [
"fr" => null
"en" => null
]
"country" => array:2 [
"fr" => null
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]
]
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}
11 => Essec\Faculty\Model\Distinction {#2280
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"fr" => "Fondation ESSEC, Prix de l'Enseignement, seconde position, sélectionné par les élèves et les participants comme un de leurs "Professeurs Favoris""
"en" => "ESSEC Foundation Teaching Award, Runner-Up Selected by students and participants as one of their "favorite professors""
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"en" => "Fondation ESSEC"
]
"country" => array:2 [
"fr" => null
"en" => null
]
]
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}
12 => Essec\Faculty\Model\Distinction {#2281
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"fr" => "Prix du Meilleur Article, Finaliste Prix Académique Syntec Conseil en Management"
"en" => "Best Paper Award, Finalist Prix Académique Syntec Conseil en Management"
]
"type" => array:2 [
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"en" => "Awards"
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"institution" => array:2 [
"fr" => null
"en" => null
]
"country" => array:2 [
"fr" => null
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]
]
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}
13 => Essec\Faculty\Model\Distinction {#2282
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"fr" => "Finaliste, e-Business Research Center Doctoral Award Competition"
"en" => "Finalist e-Business Research Center Doctoral Award Competition"
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"en" => null
]
"country" => array:2 [
"fr" => null
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]
]
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}
14 => Essec\Faculty\Model\Distinction {#2283
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"label" => array:2 [
"fr" => "Finalist for the Best Paper Award 2023 for Sarkar, Mainak, and Arnaud De Bruyn (2021), “LSTM Response Models for Direct Marketing Analytics: Replacing Feature Engineering with Deep Learning,” Journal of Interactive Marketing, 53, 80-95."
"en" => "Finalist for the Best Paper Award 2023 for Sarkar, Mainak, and Arnaud De Bruyn (2021), “LSTM Response Models for Direct Marketing Analytics: Replacing Feature Engineering with Deep Learning,” Journal of Interactive Marketing, 53, 80-95."
]
"type" => array:2 [
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"fr" => "Journal of Interactive Marketing"
"en" => "Journal of Interactive Marketing"
]
"country" => array:2 [
"fr" => "États-Unis"
"en" => "United States of America"
]
]
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}
15 => Essec\Faculty\Model\Distinction {#2284
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"en" => "Doctoral Fellow AMA Sheth Foundation Doctoral Consortium"
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"fr" => "Bourses"
"en" => "Grants"
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]
"country" => array:2 [
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]
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}
16 => Essec\Faculty\Model\Distinction {#2285
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"label" => array:2 [
"fr" => "Doctoral Fellow Marketing Science Doctoral Consortium"
"en" => "Doctoral Fellow Marketing Science Doctoral Consortium"
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"type" => array:2 [
"fr" => "Bourses"
"en" => "Grants"
]
"tri" => " 2 "
"institution" => array:2 [
"fr" => null
"en" => null
]
"country" => array:2 [
"fr" => null
"en" => null
]
]
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}
17 => Essec\Faculty\Model\Distinction {#2286
#_index: null
#_id: null
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"fr" => "ISBM Fellowship Institute for the Study of Business Markets ($150 000)"
"en" => "ISBM Fellowship Institute for the Study of Business Markets ($150 000)"
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"en" => "Grants"
]
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"institution" => array:2 [
"fr" => "Penn State University"
"en" => "Penn State University"
]
"country" => array:2 [
"fr" => "États-Unis"
"en" => "United States of America"
]
]
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}
18 => Essec\Faculty\Model\Distinction {#2287
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"en" => "Executive Program Scholarship ($15 000)"
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"en" => "Grants"
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"en" => "Penn State University"
]
"country" => array:2 [
"fr" => "États-Unis"
"en" => "United States of America"
]
]
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+"parent": Essec\Faculty\Model\Profile {#2216}
}
]
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0 => Essec\Faculty\Model\TeachingItem {#2250
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"label" => array:2 [
"fr" => "Customer Engagement in a Multichannel context"
"en" => "Customer Engagement in a Multichannel context"
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"type" => array:2 [
"fr" => "Co-directeur de thèse"
"en" => "Thesis co-director"
]
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"fr" => "ESSEC Business School"
"en" => "ESSEC Business School"
]
"country" => array:2 [
"fr" => "France"
"en" => "France"
]
]
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}
1 => Essec\Faculty\Model\TeachingItem {#2249
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#_id: null
#_source: array:7 [
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"endDate" => "2014"
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"fr" => "Modeling complex Decision Processes"
"en" => "Modeling complex Decision Processes"
]
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"en" => "Thesis director"
]
"institution" => array:2 [
"fr" => "ESSEC Business School"
"en" => "ESSEC Business School"
]
"country" => array:2 [
"fr" => "France"
"en" => "France"
]
]
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}
2 => Essec\Faculty\Model\TeachingItem {#2248
#_index: null
#_id: null
#_source: array:7 [
"startDate" => "2009"
"endDate" => "2014"
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"label" => array:2 [
"fr" => "Three Essays on Biases in Decision Making"
"en" => "Three Essays on Biases in Decision Making"
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"en" => "Thesis director"
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"fr" => "ESSEC Business School"
"en" => "ESSEC Business School"
]
"country" => array:2 [
"fr" => "France"
"en" => "France"
]
]
+lang: "en"
}
3 => Essec\Faculty\Model\TeachingItem {#2247
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#_source: array:7 [
"startDate" => "2007"
"endDate" => "2012"
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"fr" => "The Interactive Effects of Formal and Informal Information Exchanges on Team Performance and Team Satisfaction: A Multilevel Model Study"
"en" => "The Interactive Effects of Formal and Informal Information Exchanges on Team Performance and Team Satisfaction: A Multilevel Model Study"
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"fr" => "ESSEC Business School"
"en" => "ESSEC Business School"
]
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]
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}
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0 => Essec\Faculty\Model\ExtraActivity {#2217
#_index: null
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#_source: array:9 [
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}
1 => Essec\Faculty\Model\ExtraActivity {#2221
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}
2 => Essec\Faculty\Model\ExtraActivity {#2215
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3 => Essec\Faculty\Model\ExtraActivity {#2219
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}
4 => Essec\Faculty\Model\ExtraActivity {#2222
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}
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}
8 => Essec\Faculty\Model\ExtraActivity {#2226
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}
9 => Essec\Faculty\Model\ExtraActivity {#2227
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}
10 => Essec\Faculty\Model\ExtraActivity {#2228
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0 => Essec\Faculty\Model\These {#2288
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1 => Essec\Faculty\Model\These {#2289
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3 => Essec\Faculty\Model\These {#2291
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0 => Essec\Faculty\Model\Contribution {#2293
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"year" => "2008"
"title" => "A Multi-stage Model of Word-of-mouth Influence through Viral Marketing"
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1 => Essec\Faculty\Model\Contribution {#2295
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"slug" => "assimilation-contrast-theory-in-action-operationalization-and-managerial-impact-in-a-fundraising-context"
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"year" => "2017"
"title" => "Assimilation-contrast theory in action: Operationalization and managerial impact in a fundraising context"
"description" => "DE BRUYN, A. et PROKOPEC, S. (2017). Assimilation-contrast theory in action: Operationalization and managerial impact in a fundraising context. <i>International Journal of Research in Marketing</i>, 34(2), pp. 367-381."
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]
"abstract" => array:2 [
"fr" => "Charities often suggest specific donation amounts in their fundraising appeals, and the assimilation-contrast theory has been well-established as the explanation behind the impact of such anchors on donors' behavior. Yet, researchers who tested it in field studies have reported contradictory findings, and despite its proven reliability in the labs, this theory has had limited impact on managerial practice. Drawing on multiple streams of research, we develop a multi-step strategy to operationalize the assimilation-contrast theory in a fundraising context, and report the results of a large field experiment in which a charity used anchors to influence the behavior of 23,500 of its donors. We found that average donation amount increased by 22% and net margins increased by 36%. We report as one of the key managerial implications that the effects of the assimilation-contrast theory are largely asymmetric, implying that it is far easier for a firm to nudge customers in the direction of increased losses than in the direction of increased profit. We conclude by offering decision heuristics to those managers who do not have the resources to build an econometric model, but wish nonetheless to benefit from our findings."
"en" => "Charities often suggest specific donation amounts in their fundraising appeals, and the assimilation-contrast theory has been well-established as the explanation behind the impact of such anchors on donors' behavior. Yet, researchers who tested it in field studies have reported contradictory findings, and despite its proven reliability in the labs, this theory has had limited impact on managerial practice. Drawing on multiple streams of research, we develop a multi-step strategy to operationalize the assimilation-contrast theory in a fundraising context, and report the results of a large field experiment in which a charity used anchors to influence the behavior of 23,500 of its donors. We found that average donation amount increased by 22% and net margins increased by 36%. We report as one of the key managerial implications that the effects of the assimilation-contrast theory are largely asymmetric, implying that it is far easier for a firm to nudge customers in the direction of increased losses than in the direction of increased profit. We conclude by offering decision heuristics to those managers who do not have the resources to build an econometric model, but wish nonetheless to benefit from our findings."
]
"authors_fields" => array:2 [
"fr" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
2 => Essec\Faculty\Model\Contribution {#2297
#_index: "academ_contributions"
#_id: "3266"
#_source: array:18 [
"id" => "3266"
"slug" => "principles-of-marketing-engineering"
"yearMonth" => "2007-01"
"year" => "2007"
"title" => "Principles of Marketing Engineering"
"description" => "LILIEN, G.L., RANGASWAMY, A. et DE BRUYN, A. (2007). <i>Principles of Marketing Engineering</i>. Trafford Publishing, 232 pages."
"authors" => array:3 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:1 [
"name" => "LILIEN G.L"
]
2 => array:1 [
"name" => "RANGASWAMY A."
]
]
"ouvrage" => ""
"keywords" => array:1 [
0 => "Ingéniérie marketing"
]
"updatedAt" => "2021-09-06 14:06:32"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Livres"
"en" => "Books"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "Cet ouvrage, destiné aux professionels du marketing et étudiants d'école de commerce, présente différentes techniques d'ingéniérie marketing."
"en" => "This book, aimed at marketing professionals and business students, presents many marketing engineering techniques in a non-technical way."
]
"authors_fields" => array:2 [
"fr" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
3 => Essec\Faculty\Model\Contribution {#2294
#_index: "academ_contributions"
#_id: "1115"
#_source: array:18 [
"id" => "1115"
"slug" => "estimating-the-influence-of-fairness-on-bargaining-behavior"
"yearMonth" => "2008-01"
"year" => "2008"
"title" => "Estimating the Influence of Fairness on Bargaining Behavior"
"description" => "DE BRUYN, A. et BOLTON, G. (2008). Estimating the Influence of Fairness on Bargaining Behavior. <i>Management Science</i>, 54(10), pp. 1774-1791."
"authors" => array:2 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:1 [
"name" => "BOLTON G."
]
]
"ouvrage" => ""
"keywords" => array:4 [
0 => "Equité"
1 => "Games"
2 => "Négociation"
3 => "Théorie des jeux"
]
"updatedAt" => "2020-12-17 17:55:06"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "1774-1791"
"volume" => "54"
"number" => "10"
]
"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" => "En situations de négociations, les acteurs ne jugent pas le résultat à la seule lumière de leur intérêt matériel financier, mais tiennent également en compte des facteurs tels que réciprocité et équité de la répartition. Nous construisons un modèle permettant de quantifier ces motivations non-financières, et comparons les prédictions faites par le modèle à 20 expérimentations de négociations séquentielles. Les prédictions permettent d'expliquer 95% de la variance dans les offres faites."
"en" => "In bargaining situations, buyers and sellers do not gauge offers solely at the light of their self-interested material gains, but also seem to take into account non-monetary considerations such as fairness or reciprocity. This paper attempts to quantify these non-monetary motives in a buyer-seller context. We fit a model to a simple negotiation game data to quantify the role of fairness considerations in negotiation behavior, and then use the model to obtain out-of-sample estimates of play in more complex, sequential negotiation games. The model embeds a social utility function, a probabilistic decision rule, and captures experience effects. The out-of-sample test data comes from 6 previously reported studies, encompassing 20 distinct parameterizations of the sequential negotiation game. The model is remarkably accurate with respect to directional findings and to out-of-sample estimates of average first offers, accounting for 95% of the variability in the data. Out-of-sample estimates of rejection behavior account for more than half the variability. The results suggest that the influence of non-monetary considerations on bargainer decision can be reliably quantified to predict negotiations outcomes."
]
"authors_fields" => array:2 [
"fr" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
4 => Essec\Faculty\Model\Contribution {#2298
#_index: "academ_contributions"
#_id: "2490"
#_source: array:18 [
"id" => "2490"
"slug" => "so-you-want-to-delight-your-customers-the-perils-of-ignoring-heterogeneity-in-customer-evaluations-of-discretionary-preferential-treatments"
"yearMonth" => "2013-12"
"year" => "2013"
"title" => "So You Want to Delight Your Customers: The Perils of Ignoring Heterogeneity in Customer Evaluations of Discretionary Preferential Treatments"
"description" => "BUTORI, R. et DE BRUYN, A. (2013). So You Want to Delight Your Customers: The Perils of Ignoring Heterogeneity in Customer Evaluations of Discretionary Preferential Treatments. <i>International Journal of Research in Marketing</i>, 30(4), pp. 358-367."
"authors" => array:2 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:1 [
"name" => "BUTORI Raphaëlle"
]
]
"ouvrage" => ""
"keywords" => array:8 [
0 => "Discretionary preferential treatment"
1 => "Preference heterogeneity"
2 => "Justification"
3 => "Imposition"
4 => "Visibility"
5 => "Surprise"
6 => "Need for distinction"
7 => "Negotiation proneness"
]
"updatedAt" => "2021-02-02 16:16:18"
"publicationUrl" => "https://doi.org/10.1016/j.ijresmar.2013.03.004"
"publicationInfo" => array:3 [
"pages" => "358-367"
"volume" => "30"
"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" => "Many firms assume that customers like to feel special and to receive discretionary preferential treatments (DPT). This research argues that the reality is more complicated: the same preferential treatment may delight one customer but enrage or embarrass another. To help companies align their DPT with their customers’ preferences, this article identifies four dimensions along which consumers positively or negatively evaluate DPT: justification, imposition, visibility, and surprise. This article then introduces customer heterogeneity in the form of two individual traits that moderate DPT evaluations. Through two studies, the article shows that distinction seekers prefer visible rewards that impose on other customers, but negotiators prefer unjustified, non-surprising privileges. Finally, by tying consumer preferences to two readily available variables (age and gender), this article concludes with a set of practical guidelines for the companies that hope to align their DPT strategy with customer profiles."
"en" => "Many firms assume that customers like to feel special and to receive discretionary preferential treatments (DPT). This research argues that the reality is more complicated: the same preferential treatment may delight one customer but enrage or embarrass another. To help companies align their DPT with their customers’ preferences, this article identifies four dimensions along which consumers positively or negatively evaluate DPT: justification, imposition, visibility, and surprise. This article then introduces customer heterogeneity in the form of two individual traits that moderate DPT evaluations. Through two studies, the article shows that distinction seekers prefer visible rewards that impose on other customers, but negotiators prefer unjustified, non-surprising privileges. Finally, by tying consumer preferences to two readily available variables (age and gender), this article concludes with a set of practical guidelines for the companies that hope to align their DPT strategy with customer profiles."
]
"authors_fields" => array:2 [
"fr" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
5 => Essec\Faculty\Model\Contribution {#2292
#_index: "academ_contributions"
#_id: "7236"
#_source: array:18 [
"id" => "7236"
"slug" => "teaching-marketing-analytics-sharing-experiences-lessons-recommendations"
"yearMonth" => "2019-08"
"year" => "2019"
"title" => "Teaching Marketing Analytics: Sharing Experiences, Lessons, Recommendations"
"description" => "DE BRUYN, A. (2019). Teaching Marketing Analytics: Sharing Experiences, Lessons, Recommendations. Dans: 2019 American Marketing Association Summer Conference."
"authors" => array:1 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
]
"ouvrage" => "2019 American Marketing Association Summer Conference"
"keywords" => []
"updatedAt" => "2021-09-24 10:33:27"
"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" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
6 => Essec\Faculty\Model\Contribution {#2296
#_index: "academ_contributions"
#_id: "7449"
#_source: array:18 [
"id" => "7449"
"slug" => "the-spillover-effects-of-online-word-of-mouth-on-rival-brands"
"yearMonth" => "2017-07"
"year" => "2017"
"title" => "The Spillover Effects of Online Word-of-Mouth on Rival Brands"
"description" => "DE BRUYN, A. (2017). The Spillover Effects of Online Word-of-Mouth on Rival Brands. Dans: 39th ISMS Marketing Science Conference."
"authors" => array:1 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
]
"ouvrage" => "39th ISMS Marketing Science Conference"
"keywords" => []
"updatedAt" => "2021-09-24 10:33:27"
"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" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
7 => Essec\Faculty\Model\Contribution {#2299
#_index: "academ_contributions"
#_id: "7543"
#_source: array:18 [
"id" => "7543"
"slug" => "understanding-managers-tradeoffs-between-exploration-and-exploitation"
"yearMonth" => "2016-06"
"year" => "2016"
"title" => "Understanding Managers’ Tradeoffs Between Exploration and Exploitation"
"description" => "FERECATU, A. et DE BRUYN, A. (2016). Understanding Managers’ Tradeoffs Between Exploration and Exploitation. Dans: 2016 INFORMS Marketing Science Conference."
"authors" => array:2 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:1 [
"name" => "FERECATU A."
]
]
"ouvrage" => "2016 INFORMS Marketing Science Conference"
"keywords" => []
"updatedAt" => "2021-07-13 14:31:13"
"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" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
8 => Essec\Faculty\Model\Contribution {#2300
#_index: "academ_contributions"
#_id: "7545"
#_source: array:18 [
"id" => "7545"
"slug" => "understanding-the-normative-role-of-industry-standards-in-channel-negotiations"
"yearMonth" => "2014-06"
"year" => "2014"
"title" => "Understanding the Normative Role of Industry Standards in Channel Negotiations"
"description" => "DE BRUYN, A., BOLTON, G. et ROSS, B. (2014). Understanding the Normative Role of Industry Standards in Channel Negotiations. Dans: 43rd European Marketing Academy (EMAC) Annual Conference 2014."
"authors" => array:3 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:1 [
"name" => "BOLTON G."
]
2 => array:1 [
"name" => "ROSS B."
]
]
"ouvrage" => "43rd European Marketing Academy (EMAC) Annual Conference 2014"
"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" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
9 => Essec\Faculty\Model\Contribution {#2301
#_index: "academ_contributions"
#_id: "7546"
#_source: array:18 [
"id" => "7546"
"slug" => "understanding-the-normative-role-of-industry-standards-in-channel-negotiations"
"yearMonth" => "2014-06"
"year" => "2014"
"title" => "Understanding the Normative Role of Industry Standards in Channel Negotiations"
"description" => "DE BRUYN, A., BOLTON, G. et ROSS, B. (2014). Understanding the Normative Role of Industry Standards in Channel Negotiations. Dans: INFORMS Annual Meeting 2014."
"authors" => array:3 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:1 [
"name" => "BOLTON G."
]
2 => array:1 [
"name" => "ROSS B."
]
]
"ouvrage" => "INFORMS Annual Meeting 2014"
"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" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
10 => Essec\Faculty\Model\Contribution {#2302
#_index: "academ_contributions"
#_id: "3267"
#_source: array:18 [
"id" => "3267"
"slug" => "principles-of-marketing-engineering-2nd-edition"
"yearMonth" => "2013-07"
"year" => "2013"
"title" => "Principles of Marketing Engineering (2nd Edition)"
"description" => "LILIEN, G.L., RANGASWAMY, A. et DE BRUYN, A. (2013). <i>Principles of Marketing Engineering (2nd Edition)</i>. DecisionPro Inc. 263 pages."
"authors" => array:3 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:1 [
"name" => "LILIEN G. L."
]
2 => array:1 [
"name" => "RANGASWAMY A."
]
]
"ouvrage" => ""
"keywords" => []
"updatedAt" => "2021-09-06 14:06:32"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Livres"
"en" => "Books"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "The 21st century business environment demands more analysis and rigor in marketing decision making. Increasingly, marketing decision making resembles design engineering – putting together concepts, data, analyses, and simulations to learn about the marketplace and to design effective marketing plans. While many view traditional marketing as art and some view it as science, the new marketing increasingly looks like engineering (that is, combining art and science to solve specific problems)."
"en" => "The 21st century business environment demands more analysis and rigor in marketing decision making. Increasingly, marketing decision making resembles design engineering – putting together concepts, data, analyses, and simulations to learn about the marketplace and to design effective marketing plans. While many view traditional marketing as art and some view it as science, the new marketing increasingly looks like engineering (that is, combining art and science to solve specific problems)."
]
"authors_fields" => array:2 [
"fr" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
11 => Essec\Faculty\Model\Contribution {#2303
#_index: "academ_contributions"
#_id: "3268"
#_source: array:18 [
"id" => "3268"
"slug" => "principles-of-marketing-engineering-and-analytics-3rd-edition"
"yearMonth" => "2017-04"
"year" => "2017"
"title" => "Principles of Marketing Engineering and Analytics [3rd Edition]"
"description" => "LILIEN, G.L., RANGASWAMY, A. et DE BRUYN, A. (2017). <i>Principles of Marketing Engineering and Analytics [3rd Edition]</i>. DecisionPro Inc. 305 pages."
"authors" => array:3 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:1 [
"name" => "LILIEN G. L."
]
2 => array:1 [
"name" => "RANGASWAMY A."
]
]
"ouvrage" => ""
"keywords" => array:2 [
0 => "Ingénierie marketing"
1 => "Marketing analytique"
]
"updatedAt" => "2021-09-24 10:33:27"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"volume" => null
"number" => null
]
"type" => array:2 [
"fr" => "Livres"
"en" => "Books"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => "The 21st century business environment demands more analysis and rigor in marketing decision making. Increasingly, marketing decision making resembles design engineering – putting together concepts, data, analyses, and simulations to learn about the marketplace and to design effective marketing plans. While many view traditional marketing as art and some view it as science, the new marketing increasingly looks like engineering (that is, combining art and science to solve specific problems)."
"en" => "The 21st century business environment demands more analysis and rigor in marketing decision making. Increasingly, marketing decision making resembles design engineering – putting together concepts, data, analyses, and simulations to learn about the marketplace and to design effective marketing plans. While many view traditional marketing as art and some view it as science, the new marketing increasingly looks like engineering (that is, combining art and science to solve specific problems)."
]
"authors_fields" => array:2 [
"fr" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
12 => Essec\Faculty\Model\Contribution {#2304
#_index: "academ_contributions"
#_id: "9987"
#_source: array:18 [
"id" => "9987"
"slug" => "a-multi-stage-model-of-word-of-mouth-through-electronic-referrals"
"yearMonth" => "2004-01"
"year" => "2004"
"title" => "A Multi-Stage Model of Word of Mouth through Electronic Referrals"
"description" => "DE BRUYN, A. et LILIEN, G. (2004). <i>A Multi-Stage Model of Word of Mouth through Electronic Referrals</i>."
"authors" => array:2 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:1 [
"name" => "LILIEN G."
]
]
"ouvrage" => ""
"keywords" => []
"updatedAt" => "2021-07-13 14:31:24"
"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" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
13 => Essec\Faculty\Model\Contribution {#2305
#_index: "academ_contributions"
#_id: "10024"
#_source: array:18 [
"id" => "10024"
"slug" => "predicting-bargaining-behavior-out-of-sample-estimates-from-a-social-utility-model-with-quantal-response"
"yearMonth" => "2004-01"
"year" => "2004"
"title" => "Predicting Bargaining Behavior: Out-of-Sample Estimates from a Social Utility Model with Quantal Response"
"description" => "DE BRUYN, A. et BOLTON, G.E. (2004). <i>Predicting Bargaining Behavior: Out-of-Sample Estimates from a Social Utility Model with Quantal Response</i>."
"authors" => array:2 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:1 [
"name" => "BOLTON G.E."
]
]
"ouvrage" => ""
"keywords" => []
"updatedAt" => "2021-07-13 14:31:25"
"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" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
14 => Essec\Faculty\Model\Contribution {#2306
#_index: "academ_contributions"
#_id: "10073"
#_source: array:18 [
"id" => "10073"
"slug" => "offering-online-recommendations-to-impatient-first-time-customers-with-conjoint-based-segmentation-trees"
"yearMonth" => "2005-01"
"year" => "2005"
"title" => "Offering Online Recommendations to Impatient, First-Time Customers with Conjoint Based Segmentation Trees"
"description" => "DE BRUYN, A., LIECHTY, J., HUIZINGH, E. et LILIEN, G. (2005). <i>Offering Online Recommendations to Impatient, First-Time Customers with Conjoint Based Segmentation Trees</i>."
"authors" => array:4 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:1 [
"name" => "LIECHTY J."
]
2 => array:1 [
"name" => "HUIZINGH E."
]
3 => array:1 [
"name" => "LILIEN G."
]
]
"ouvrage" => ""
"keywords" => []
"updatedAt" => "2021-07-13 14:31:26"
"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" => null
"en" => null
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
15 => Essec\Faculty\Model\Contribution {#2307
#_index: "academ_contributions"
#_id: "4671"
#_source: array:18 [
"id" => "4671"
"slug" => "how-to-profile-your-customers-using-collaborative-database-profiling-an-application-to-age-estimation"
"yearMonth" => "2008-05"
"year" => "2008"
"title" => "How to Profile your Customers Using Collaborative Database Profiling: An Application to Age Estimation"
"description" => "DE BRUYN, A. et TRAMONTE, N. (2008). How to Profile your Customers Using Collaborative Database Profiling: An Application to Age Estimation. Dans: <i>Proceedings of the 37th EMAC Conference</i>. European Marketing Academy (EMAC)."
"authors" => array:2 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:1 [
"name" => "TRAMONTE N."
]
]
"ouvrage" => "Proceedings of the 37th EMAC Conference"
"keywords" => array:3 [
0 => "Estimation de l'âge"
1 => "Prénom"
2 => "Profiling collaboratif"
]
"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" => "CD-Rom Les entreprises utilisent des bases de données commerciales externes pour enrichir la connaissance qu'elles ont de leurs clients et prospects. Cet article présente une méthodologie pour améliorer cette approche."
"en" => "Firms use external data sources (e.g., Census Bureau data) to infer the most likely age, income, housing situation or marital status of their customers, and better portray their profiles and needs. In this paper, we show that the methodology commonly used in the industry is severely biased towards average national figures. We discuss a maximum likelihood approach to correct for these biases. Taking the example of first name analysis to infer customers'age, we show that the approach we suggest gives much more precise and unbiased estimates, allowing marketers to better profile their customers and tailor their marketing strategy more precisely to their customers' characteristics."
]
"authors_fields" => array:2 [
"fr" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
16 => Essec\Faculty\Model\Contribution {#2308
#_index: "academ_contributions"
#_id: "4863"
#_source: array:18 [
"id" => "4863"
"slug" => "marketing-management-support-systems-when-help-is-not-recognized"
"yearMonth" => "2010-06"
"year" => "2010"
"title" => "Marketing Management Support Systems: When Help is Not Recognized"
"description" => "ALTHUIZEN, N., WIERENGA, B., VAN BRUGGEN, G. et DE BRUYN, A. (2010). Marketing Management Support Systems: When Help is Not Recognized. Dans: <i>EMAC Conference Proceedings: The Six Senses - The Essentials of Marketing</i>. European Marketing Academy (EMAC)."
"authors" => array:4 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:1 [
"name" => "ALTHUIZEN Niek"
]
2 => array:1 [
"name" => "WIERENGA B."
]
3 => array:1 [
"name" => "VAN BRUGGEN G."
]
]
"ouvrage" => "EMAC Conference Proceedings: The Six Senses - The Essentials of Marketing"
"keywords" => array:1 [
0 => "Marketing Management Support Systems"
]
"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" => "Marketing Management Support Systems (MMSS) are designed to improve managerial decision making, but to be able to do so these systems have to be used in practice. Perceived usefulness is an important driver of MMSS use intentions. Prior research suggests that decision makers may have difficulty recognizing objective improvements in task performance due to the MMSS. This lack of connection between subjective evaluation and objective performance may hamper MMSS adoption and use. In a large-scale study with prospective users, we investigate the drivers of perceived usefulness and the conditions under which the "lack of connection" phenomenon is likely to occur. To test our hypotheses, we set up a 2 (prior task experience) x 4 (MMSS quality) between-subject experiment with repeated measures. This study should lead to recommendations for interventions that result in greater acceptance and utilization of MMSS."
"en" => "Marketing Management Support Systems (MMSS) are designed to improve managerial decision making, but to be able to do so these systems have to be used in practice. Perceived usefulness is an important driver of MMSS use intentions. Prior research suggests that decision makers may have difficulty recognizing objective improvements in task performance due to the MMSS. This lack of connection between subjective evaluation and objective performance may hamper MMSS adoption and use. In a large-scale study with prospective users, we investigate the drivers of perceived usefulness and the conditions under which the "lack of connection" phenomenon is likely to occur. To test our hypotheses, we set up a 2 (prior task experience) x 4 (MMSS quality) between-subject experiment with repeated measures. This study should lead to recommendations for interventions that result in greater acceptance and utilization of MMSS."
]
"authors_fields" => array:2 [
"fr" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
17 => Essec\Faculty\Model\Contribution {#2309
#_index: "academ_contributions"
#_id: "4867"
#_source: array:18 [
"id" => "4867"
"slug" => "maximizing-vs-satisficing-how-managers-psychological-traits-influence-strategic-trade-offs-between-exploration-and-exploitation"
"yearMonth" => "2011-05"
"year" => "2011"
"title" => "Maximizing vs. Satisficing: How Managers' Psychological Traits Influence Strategic Trade-Offs Between Exploration and Exploitation"
"description" => "FERECATU, A. et DE BRUYN, A. (2011). Maximizing vs. Satisficing: How Managers' Psychological Traits Influence Strategic Trade-Offs Between Exploration and Exploitation. Dans: <i>Proceedings of the 40th EMAC Conference</i>. European Marketing Academy (EMAC)."
"authors" => array:2 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:1 [
"name" => "FERECATU A."
]
]
"ouvrage" => "Proceedings of the 40th EMAC Conference"
"keywords" => []
"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" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
18 => Essec\Faculty\Model\Contribution {#2310
#_index: "academ_contributions"
#_id: "4868"
#_source: array:18 [
"id" => "4868"
"slug" => "maximizing-vs-satisficing-understanding-managers-tradeoffs-between-exploration-and-exploitation"
"yearMonth" => "2013-08"
"year" => "2013"
"title" => "Maximizing vs. Satisficing: Understanding Managers' Tradeoffs Between Exploration and Exploitation"
"description" => "DE BRUYN, A. et FERECATU, A. (2013). Maximizing vs. Satisficing: Understanding Managers' Tradeoffs Between Exploration and Exploitation. Dans: <i>2013 AMA Summer Educators’ Conference Proceedings</i>. American Marketing Association (AMA)."
"authors" => array:2 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:1 [
"name" => "FERECATU A."
]
]
"ouvrage" => "2013 AMA Summer Educators’ Conference Proceedings"
"keywords" => []
"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" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
19 => Essec\Faculty\Model\Contribution {#2311
#_index: "academ_contributions"
#_id: "4889"
#_source: array:18 [
"id" => "4889"
"slug" => "modeling-unobserved-drop-out-rate-to-optimize-e-panelist-lifetime-value"
"yearMonth" => "2011-05"
"year" => "2011"
"title" => "Modeling Unobserved Drop-Out Rate To Optimize E-Panelist Lifetime Value"
"description" => "DE BRUYN, A. et TRAMONTE, N. (2011). Modeling Unobserved Drop-Out Rate To Optimize E-Panelist Lifetime Value. Dans: <i>Proceedings of the 40th EMAC Conference</i>. European Marketing Academy (EMAC)."
"authors" => array:2 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:1 [
"name" => "TRAMONTE N."
]
]
"ouvrage" => "Proceedings of the 40th EMAC Conference"
"keywords" => []
"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" => "Online access panels are becoming of paramount importance in marketing research, and constitute a great asset for market research firms. In this paper, we show that traditional models fail to quantify the true “cost” of an electronic solicitation, and we demonstrate that each additional solicitation not only decreases the likelihood of future participation, but might even increase the drop-out rate (a mostly unobserved phenomenon that has a dramatic impact on the lifetime value of an e-panelist). Our model estimates the likelihood that an e-panelist will respond positively to a new solicitation, as a function of his past behavior and how many times he has been solicited so far, and integrates a latent “wear out” effect. We fit the model on a sample of more than 700,000 e-mail solicitations sent over a period of 3 years, and demonstrate that each additional solicitation contributes to a long-lasting wear-out effect; the unobserved drop-out rate can reach up to 10% at each additional solicitation."
"en" => "Online access panels are becoming of paramount importance in marketing research, and constitute a great asset for market research firms. In this paper, we show that traditional models fail to quantify the true “cost” of an electronic solicitation, and we demonstrate that each additional solicitation not only decreases the likelihood of future participation, but might even increase the drop-out rate (a mostly unobserved phenomenon that has a dramatic impact on the lifetime value of an e-panelist). Our model estimates the likelihood that an e-panelist will respond positively to a new solicitation, as a function of his past behavior and how many times he has been solicited so far, and integrates a latent “wear out” effect. We fit the model on a sample of more than 700,000 e-mail solicitations sent over a period of 3 years, and demonstrate that each additional solicitation contributes to a long-lasting wear-out effect; the unobserved drop-out rate can reach up to 10% at each additional solicitation."
]
"authors_fields" => array:2 [
"fr" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
20 => Essec\Faculty\Model\Contribution {#2312
#_index: "academ_contributions"
#_id: "4914"
#_source: array:18 [
"id" => "4914"
"slug" => "offering-collaborative-like-recommendationis-when-data-is-sparse-the-case-of-attraction-weighted-information-filtering"
"yearMonth" => "2004-01"
"year" => "2004"
"title" => "Offering Collaborative-like Recommendationis When Data is Sparse: The Case of Attraction-weighted Information Filtering"
"description" => "DE BRUYN, A., GILES, C.L. et PENNOCK, D.M. (2004). Offering Collaborative-like Recommendationis When Data is Sparse: The Case of Attraction-weighted Information Filtering. Dans: <i>Lectures Notes in Computer Science n° 3137. Proceedings of the Third International Conference on Adaptive Hypermedia and Adaptive Web-based Systems</i>. Springer, pp. 393-396."
"authors" => array:3 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:1 [
"name" => "GILES C.L."
]
2 => array:1 [
"name" => "PENNOCK D.M."
]
]
"ouvrage" => "Lectures Notes in Computer Science n° 3137. Proceedings of the Third International Conference on Adaptive Hypermedia and Adaptive Web-based Systems"
"keywords" => []
"updatedAt" => "2021-04-19 17:57:25"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "393-396"
"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" => "Nous proposons un algorithme de recommandations en ligne permettant de transformer des recommandations basées sur la similarité de contenus en recommandations collaboratives requérant moins de données que les systèmes classiques. Une première étude dans un contexte de vente de livres en ligne indique que notre approche est compétitive face à des systèmes collaboratifs plus lourds."
"en" => "We propose a low-dimensional weigthing scheme to map information filtering recommendations into more relevant, collaborative filtering-like recommendations where items are weigthed by attraction indexes representing existing customers' preferences. A first study conducted with consumers within an online bookseller context indicates that recommendations made by our system favorably compare to data-hungry collaborative filtering systems, while requiring much less data."
]
"authors_fields" => array:2 [
"fr" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
21 => Essec\Faculty\Model\Contribution {#2313
#_index: "academ_contributions"
#_id: "4932"
#_source: array:18 [
"id" => "4932"
"slug" => "optimizing-donations-with-individually-tailored-donation-grids-an-econometric-model-of-compliance-and-generosity"
"yearMonth" => "2010-06"
"year" => "2010"
"title" => "Optimizing Donations with Individually-tailored Donation Grids: An Econometric Model of Compliance and Generosity"
"description" => "PROKOPEC, S. et DE BRUYN, A. (2010). Optimizing Donations with Individually-tailored Donation Grids: An Econometric Model of Compliance and Generosity. Dans: <i>Proceedings of the 39th EMAC Conference</i>. European Marketing Academy (EMAC)."
"authors" => array:2 [
0 => array:3 [
"name" => "PROKOPEC Sonja"
"bid" => "B00145716"
"slug" => "prokopec-sonja"
]
1 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
]
"ouvrage" => "Proceedings of the 39th EMAC Conference"
"keywords" => []
"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" => "Charities and fundraising organizations use donation grids as anchors to influence donation amounts. In this paper, we show that the impact of these donation grids on the various components of donation behavior (compliance and donation amount) can be captured by an econometric model that taps into the social psychology literature, especially the contrast theory (Sherif, Taub, and Hovland, 1958) and the adaptation level theory (Helson, 1964). We develop two separate econometric models to estimate the impact of donation grids on (a) likelihood of donation and (b) donation amounts, and show that congruency of requests with donors? internal reference points plays an important role in determining the impact of charities? tactics. We then apply these models in a large field experiment, and individually tailor suggested donation grids to 100,000 solicited donors. Contrasted to the control group, optimizing donation grids at the individual level increased donation amounts by +22%, and net margins by +36%."
"en" => "Charities and fundraising organizations use donation grids as anchors to influence donation amounts. In this paper, we show that the impact of these donation grids on the various components of donation behavior (compliance and donation amount) can be captured by an econometric model that taps into the social psychology literature, especially the contrast theory (Sherif, Taub, and Hovland, 1958) and the adaptation level theory (Helson, 1964). We develop two separate econometric models to estimate the impact of donation grids on (a) likelihood of donation and (b) donation amounts, and show that congruency of requests with donors? internal reference points plays an important role in determining the impact of charities? tactics. We then apply these models in a large field experiment, and individually tailor suggested donation grids to 100,000 solicited donors. Contrasted to the control group, optimizing donation grids at the individual level increased donation amounts by +22%, and net margins by +36%."
]
"authors_fields" => array:2 [
"fr" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
22 => Essec\Faculty\Model\Contribution {#2314
#_index: "academ_contributions"
#_id: "4973"
#_source: array:18 [
"id" => "4973"
"slug" => "predicting-the-final-outcome-of-two-stage-elections-with-a-voter-choice-model"
"yearMonth" => "2006-05"
"year" => "2006"
"title" => "Predicting the Final Outcome of Two-stage Elections with a Voter-choice Model"
"description" => "KAMAKURA, W.A., MAZZON, J.A. et DE BRUYN, A. (2006). Predicting the Final Outcome of Two-stage Elections with a Voter-choice Model. Dans: <i>Proceedings of the 35th EMAC Conference: Sustainable Marketing Leadership</i>. European Marketing Academy (EMAC)."
"authors" => array:3 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:1 [
"name" => "KAMAKURA W.A."
]
2 => array:1 [
"name" => "MAZZON J.A."
]
]
"ouvrage" => "Proceedings of the 35th EMAC Conference: Sustainable Marketing Leadership"
"keywords" => array:4 [
0 => "Elections à deux tours"
1 => "Logit"
2 => "Marketing politique"
3 => "Modèle de vote"
]
"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" => "CD-Rom Lors d’élections à deux tours, l’analyse des résultats du premier tour permettent de mettre en évidence la structure de l’électorat et ses préférences, préférences qui peuvent ensuite être utilisées pour prédire le résultat des élections au second tour, en fonction des candidats restants. Le modèle est appliqué à des élections brésiliennes."
"en" => "In two-stage elections, voting data are available between the first and the second rounds to help politicians understand their position in relation to each other and to voter preferences and to help them predict the final outcome of the election. In this study, we develop a Nested Logit Factor Model of voter choice which we use to predict the final outcome of two stage elections and gain insights about the underlying political landscape."
]
"authors_fields" => array:2 [
"fr" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
23 => Essec\Faculty\Model\Contribution {#2315
#_index: "academ_contributions"
#_id: "5068"
#_source: array:18 [
"id" => "5068"
"slug" => "short-term-impact-long-term-doom-the-paradox-of-optimizing-the-number-of-solicitations-in-direct-marketing-fundraising"
"yearMonth" => "2006-05"
"year" => "2006"
"title" => "Short Term Impact, Long Term Doom: The Paradox of Optimizing the Number of Solicitations in Direct Marketing Fundraising"
"description" => "DE BRUYN, A. (2006). Short Term Impact, Long Term Doom: The Paradox of Optimizing the Number of Solicitations in Direct Marketing Fundraising. Dans: <i>Proceedings of the 35th EMAC Conference</i>. European Marketing Academy (EMAC)."
"authors" => array:1 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
]
"ouvrage" => "Proceedings of the 35th EMAC Conference"
"keywords" => array:3 [
0 => "Collecte de fonds"
1 => "Marketing caritatif"
2 => "Marketing direct"
]
"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" => "CD-Rom Ce papier discute la possibilité que l’optimisation de l’envoi des mailings, dans le cadre de campagnes de fundraising, puisse engendrer un effet adverse sur le long terme."
"en" => "This paper discussed the possibility that optimizing the Number of Solicitations in Direct Marketing Fundraising for maximizing short-term impact might actually diminish future returns in the long term."
]
"authors_fields" => array:2 [
"fr" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
24 => Essec\Faculty\Model\Contribution {#2316
#_index: "academ_contributions"
#_id: "5125"
#_source: array:18 [
"id" => "5125"
"slug" => "the-effect-of-feedback-and-learning-on-decision-support-system-adoption"
"yearMonth" => "2006-05"
"year" => "2006"
"title" => "The Effect of Feedback and Learning on Decision-support System Adoption"
"description" => "KAYANDE, U., DE BRUYN, A., LILIEN, G., RANGASWAMY, A. et VAN BRUGGEN, G.H. (2006). The Effect of Feedback and Learning on Decision-support System Adoption. Dans: <i>Proceedings of the 35th EMAC Conference: Sustainable Marketing Leadership</i>. European Marketing Academy (EMAC)."
"authors" => array:5 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:1 [
"name" => "KAYANDE U."
]
2 => array:1 [
"name" => "LILIEN G."
]
3 => array:1 [
"name" => "RANGASWAMY A."
]
4 => array:1 [
"name" => "VAN BRUGGEN G.H."
]
]
"ouvrage" => "Proceedings of the 35th EMAC Conference: Sustainable Marketing Leadership"
"keywords" => array:4 [
0 => "Adoption"
1 => "Apprentissage"
2 => "Feedback"
3 => "Système d'aide à la décision"
]
"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" => "CD-Rom Les auteurs montrent que pour être adoptés et utilisés, les systèmes d’aide à la décision doivent fournir aux managers à la fois des feedback correctifs, mais également de potentiel d’utilisation, pour aider à l’apprentissage du modèle."
"en" => "The authors show that providing both corrective and upside potential feedback increase the effectiveness and likelihood of decision-support systems to be adopted and used."
]
"authors_fields" => array:2 [
"fr" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
25 => Essec\Faculty\Model\Contribution {#2317
#_index: "academ_contributions"
#_id: "5140"
#_source: array:18 [
"id" => "5140"
"slug" => "the-impact-of-anchors-on-donors-behavior-a-field-experiment"
"yearMonth" => "2009-01"
"year" => "2009"
"title" => "The Impact of Anchors on Donors' Behavior: A Field Experiment"
"description" => "PROKOPEC, S. et DE BRUYN, A. (2009). The Impact of Anchors on Donors' Behavior: A Field Experiment. Dans: <i>Advances in Consumer Research, Volume 37</i>. Association for Consumer Research (ACR)."
"authors" => array:2 [
0 => array:3 [
"name" => "PROKOPEC Sonja"
"bid" => "B00145716"
"slug" => "prokopec-sonja"
]
1 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
]
"ouvrage" => "Advances in Consumer Research, Volume 37"
"keywords" => []
"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" => "Site internet."
"en" => "We ran a large field experiment in which a charity solicited 50,000 of its donors, and tailored suggested donation amounts based on their past behavior. Two anchoring mechanisms were manipulated, the size of the first amount on the donation grid relative to the previous donation (the left end of the grid), and the rate of the increase of the amounts on the rest of the donation grid (the right end). As expected, both anchoring mechanisms have positive influence on donation amounts, but only the size of the first amount on the donation grid negatively influences likelihood of donation."
]
"authors_fields" => array:2 [
"fr" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
26 => Essec\Faculty\Model\Contribution {#2318
#_index: "academ_contributions"
#_id: "5235"
#_source: array:18 [
"id" => "5235"
"slug" => "when-asking-for-more-leads-to-getting-nothing-the-impact-of-anchors-on-donors-behavior"
"yearMonth" => "2009-01"
"year" => "2009"
"title" => "When Asking for More Leads to Getting Nothing: The Impact of Anchors on Donor's Behavior"
"description" => "DE BRUYN, A. et PROKOPEC, S. (2009). When Asking for More Leads to Getting Nothing: The Impact of Anchors on Donor's Behavior. Dans: <i>Proceedings of the 38th EMAC: Marketing and the Core Disciplines: Rediscovering References?</i> European Marketing Academy (EMAC)."
"authors" => array:2 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:3 [
"name" => "PROKOPEC Sonja"
"bid" => "B00145716"
"slug" => "prokopec-sonja"
]
]
"ouvrage" => "Proceedings of the 38th EMAC: Marketing and the Core Disciplines: Rediscovering References?"
"keywords" => array:2 [
0 => "Grilles de dons"
1 => "Points de référence"
]
"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" => "Les organisations caritatives utilisent les grilles de dons pour influencer les comportements des donateurs. Dans ce papier, nous montrons que ces grilles de dons peuvent avoir des conséquences négatives sur les comportements. Nous démontrons également que les donateurs ayant des points de référence internes forts sont moins susceptibles à ce type d'influence."
"en" => "Fundraising organizations use donation grids as anchors to artificially influence donation amounts. In this paper, we show that these anchors can have adverse consequences on donation likelihood. We also show that donors with stronger internal reference points are less influenced by grid manipulations."
]
"authors_fields" => array:2 [
"fr" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
27 => Essec\Faculty\Model\Contribution {#2319
#_index: "academ_contributions"
#_id: "5443"
#_source: array:18 [
"id" => "5443"
"slug" => "artificial-intelligence-and-marketing"
"yearMonth" => "2019-03"
"year" => "2019"
"title" => "Artificial Intelligence and Marketing"
"description" => "DE BRUYN, A., VON WANGENHEIM, F., BROCK, J.K.U., VISWANATHAN, V. et BEH, Y.S. (2019). Artificial Intelligence and Marketing. Dans: 2019 Special conference on Big Data, Technology-Driven CRM & Artificial Intelligence."
"authors" => array:5 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:1 [
"name" => "VON WANGENHEIM Florian"
]
2 => array:1 [
"name" => "BROCK Jürgen Kai-Uwe"
]
3 => array:1 [
"name" => "VISWANATHAN Vijay"
]
4 => array:1 [
"name" => "BEH Yean Shan"
]
]
"ouvrage" => "2019 Special conference on Big Data, Technology-Driven CRM & Artificial Intelligence"
"keywords" => []
"updatedAt" => "2021-09-24 10:33:27"
"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" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
28 => Essec\Faculty\Model\Contribution {#2320
#_index: "academ_contributions"
#_id: "12688"
#_source: array:18 [
"id" => "12688"
"slug" => "marketing-and-artificial-intelligence-pitfalls-and-possibilities"
"yearMonth" => "2021-01"
"year" => "2021"
"title" => "Marketing and Artificial Intelligence: Pitfalls and Possibilities"
"description" => "DE BRUYN, A. (2021). Marketing and Artificial Intelligence: Pitfalls and Possibilities. <i>ESSEC Knowledge</i>."
"authors" => array:1 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
]
"ouvrage" => ""
"keywords" => []
"updatedAt" => "2023-02-02 16:55:13"
"publicationUrl" => "https://knowledge.essec.edu/en/leadership/marketing-and-artificial-intelligence.html"
"publicationInfo" => array:3 [
"pages" => ""
"volume" => ""
"number" => ""
]
"type" => array:2 [
"fr" => "Articles ou vidéos de vulgarisation"
"en" => "Press article, video or other popular media"
]
"support_type" => array:2 [
"fr" => "Presse"
"en" => "Press"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => ""
"en" => ""
]
"authors_fields" => array:2 [
"fr" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
29 => Essec\Faculty\Model\Contribution {#2321
#_index: "academ_contributions"
#_id: "6702"
#_source: array:18 [
"id" => "6702"
"slug" => "modeling-unobserved-drop-out-rate-to-optimize-e-panelist-lifetime-value"
"yearMonth" => "2013-10"
"year" => "2013"
"title" => "Modeling Unobserved Drop-out Rate to Optimize e-Panelist Lifetime Value"
"description" => "DE BRUYN, A. et MUKHERJEE, P. (2013). Modeling Unobserved Drop-out Rate to Optimize e-Panelist Lifetime Value. Dans: INFORMS Marketing Science Conference."
"authors" => array:2 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:1 [
"name" => "MUKHERJEE P."
]
]
"ouvrage" => "INFORMS Marketing Science Conference"
"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" => "Online access panels are becoming of paramount importance in marketing research, and constitute a great asset for market research firms. In this paper, we show that traditional models fail to quantify the true “cost” of an electronic solicitation, and we demonstrate that each additional solicitation not only decreases the likelihood of future participation, but might even increase the drop-out rate (a mostly unobserved phenomenon that has a dramatic impact on the lifetime value of an e-panelist). Our model estimates the likelihood that an e-panelist will respond positively to a new solicitation, as a function of his past behavior and how many times he has been solicited so far, and integrates a latent “wear out” effect. We fit the model on a sample of more than 700,000 e-mail solicitations sent over a period of 3 years, and demonstrate that each additional solicitation contributes to a long-lasting wear-out effect; the unobserved drop-out rate can reach up to 10% at each additional solicitation."
"en" => "Online access panels are becoming of paramount importance in marketing research, and constitute a great asset for market research firms. In this paper, we show that traditional models fail to quantify the true “cost” of an electronic solicitation, and we demonstrate that each additional solicitation not only decreases the likelihood of future participation, but might even increase the drop-out rate (a mostly unobserved phenomenon that has a dramatic impact on the lifetime value of an e-panelist). Our model estimates the likelihood that an e-panelist will respond positively to a new solicitation, as a function of his past behavior and how many times he has been solicited so far, and integrates a latent “wear out” effect. We fit the model on a sample of more than 700,000 e-mail solicitations sent over a period of 3 years, and demonstrate that each additional solicitation contributes to a long-lasting wear-out effect; the unobserved drop-out rate can reach up to 10% at each additional solicitation."
]
"authors_fields" => array:2 [
"fr" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
30 => Essec\Faculty\Model\Contribution {#2322
#_index: "academ_contributions"
#_id: "6923"
#_source: array:18 [
"id" => "6923"
"slug" => "predicting-bargaining-behavior-when-money-is-not-all-that-matters-the-role-of-fairness-considerations-in-shaping-price-agreements"
"yearMonth" => "2005-05"
"year" => "2005"
"title" => "Predicting Bargaining Behavior when Money is not All that Matters: The Role of Fairness Considerations in Shaping Price Agreements"
"description" => "DE BRUYN, A. et BOLTON, G.E. (2005). Predicting Bargaining Behavior when Money is not All that Matters: The Role of Fairness Considerations in Shaping Price Agreements."
"authors" => array:2 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:1 [
"name" => "BOLTON G.E."
]
]
"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" => "In bargaining situations, buyers and sellers do not gauge offers solely at the light of their self-interested material gains, but also seem to take into account non-monetary considerations such as fairness or reciprocity. This paper attemps to quantify these non-monetary motives in a buyer-seller context. We fit a model to a simple negotiation game data to quantify the role of fairness considerations in negotiation behavior, and then use the model to obtain out-of-sample estimates of play in more complex, sequential negotiation games. The model embeds a social utility function, a probabilistic decision rule, and captures experience effects. The out-of-sample test data comes from 6 previously reported studies, encompassing 20 distinct parameterizations of the sequential negotiation game. The model is remarkably accurate with respect to directional findings and to out-of-sample estimates of average first offers, accounting for 95% of the variability in the data. Out-of-sample estimates of rejection behavior account for more than half the variability. The results suggest that the influence of non-monetary considerations on bargainer decision can be reliably quantified to predict negotiations outcomes."
"en" => "In bargaining situations, buyers and sellers do not gauge offers solely at the light of their self-interested material gains, but also seem to take into account non-monetary considerations such as fairness or reciprocity. This paper attemps to quantify these non-monetary motives in a buyer-seller context. We fit a model to a simple negotiation game data to quantify the role of fairness considerations in negotiation behavior, and then use the model to obtain out-of-sample estimates of play in more complex, sequential negotiation games. The model embeds a social utility function, a probabilistic decision rule, and captures experience effects. The out-of-sample test data comes from 6 previously reported studies, encompassing 20 distinct parameterizations of the sequential negotiation game. The model is remarkably accurate with respect to directional findings and to out-of-sample estimates of average first offers, accounting for 95% of the variability in the data. Out-of-sample estimates of rejection behavior account for more than half the variability. The results suggest that the influence of non-monetary considerations on bargainer decision can be reliably quantified to predict negotiations outcomes."
]
"authors_fields" => array:2 [
"fr" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
31 => Essec\Faculty\Model\Contribution {#2323
#_index: "academ_contributions"
#_id: "6045"
#_source: array:18 [
"id" => "6045"
"slug" => "genetics-and-marketing-myths-unknowns-established-facts-and-future-possibilities"
"yearMonth" => "2016-06"
"year" => "2016"
"title" => "Genetics And Marketing: Myths, Unknowns, Established Facts, And Future Possibilities"
"description" => "CARRASCO, G. et DE BRUYN, A. (2016). Genetics And Marketing: Myths, Unknowns, Established Facts, And Future Possibilities. Dans: 2016 INFORMS Marketing Science Conference."
"authors" => array:2 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:1 [
"name" => "CARRASCO G."
]
]
"ouvrage" => "2016 INFORMS Marketing Science Conference"
"keywords" => []
"updatedAt" => "2021-07-13 14:31:09"
"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" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
32 => Essec\Faculty\Model\Contribution {#2324
#_index: "academ_contributions"
#_id: "6229"
#_source: array:18 [
"id" => "6229"
"slug" => "investigating-the-profitability-of-multilevel-marketing"
"yearMonth" => "2012-05"
"year" => "2012"
"title" => "Investigating the Profitability of Multilevel Marketing"
"description" => "MUKHERJEE, P. et DE BRUYN, A. (2012). Investigating the Profitability of Multilevel Marketing. Dans: 41st EMAC Annual Conference 2012."
"authors" => array:2 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:1 [
"name" => "MUKHERJEE P."
]
]
"ouvrage" => "41st EMAC Annual Conference 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" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
33 => Essec\Faculty\Model\Contribution {#2325
#_index: "academ_contributions"
#_id: "6230"
#_source: array:18 [
"id" => "6230"
"slug" => "investigating-the-profitability-of-multilevel-marketing"
"yearMonth" => "2012-06"
"year" => "2012"
"title" => "Investigating the Profitability of Multilevel Marketing"
"description" => "MUKHERJEE, P. et DE BRUYN, A. (2012). Investigating the Profitability of Multilevel Marketing. Dans: 2012 INFORMS Marketing Science Conference."
"authors" => array:2 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:1 [
"name" => "MUKHERJEE P."
]
]
"ouvrage" => "2012 INFORMS Marketing Science Conference"
"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" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
34 => Essec\Faculty\Model\Contribution {#2326
#_index: "academ_contributions"
#_id: "2075"
#_source: array:18 [
"id" => "2075"
"slug" => "modeling-voter-choice-to-predict-the-final-outcome-of-two-stage-elections"
"yearMonth" => "2006-01"
"year" => "2006"
"title" => "Modeling Voter Choice to Predict the Final Outcome of Two-stage Elections"
"description" => "KAMAKURA, W.A., MAZZON, J.A. et DE BRUYN, A. (2006). Modeling Voter Choice to Predict the Final Outcome of Two-stage Elections. <i>International Journal of Forecasting</i>."
"authors" => array:3 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:1 [
"name" => "KAMAKURA W. A."
]
2 => array:1 [
"name" => "MAZZON J.A."
]
]
"ouvrage" => ""
"keywords" => array:3 [
0 => "Elections à deux tours"
1 => "Modélisation des votes"
2 => "Prédictions des résultats électoraux"
]
"updatedAt" => "2020-12-17 17:55:06"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => null
"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" => "Les auteurs proposent une modélisation des votes dans le cadre du premier tour d’élections, pour prédire le résultat de final des élections au deuxième tour."
"en" => "The authors offer a modeling approach to first-round voting behavior, and predict, based on this model, the final outcome a the second stage of an election."
]
"authors_fields" => array:2 [
"fr" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
35 => Essec\Faculty\Model\Contribution {#2327
#_index: "academ_contributions"
#_id: "2117"
#_source: array:18 [
"id" => "2117"
"slug" => "offering-online-recommendations-with-minimum-customer-input-through-conjoint-based-decision-aids"
"yearMonth" => "2008-03"
"year" => "2008"
"title" => "Offering Online Recommendations with Minimum Customer Input through Conjoint-Based Decision Aids"
"description" => "DE BRUYN, A., LIECHTY, J.C., HUIZINGH, E.K.R.E. et LILIEN, G.L. (2008). Offering Online Recommendations with Minimum Customer Input through Conjoint-Based Decision Aids. <i>Marketing Science</i>, 27(3), pp. 443-460."
"authors" => array:4 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:1 [
"name" => "LIECHTY J.C."
]
2 => array:1 [
"name" => "HUIZINGH E.K.R.E."
]
3 => array:1 [
"name" => "LILIEN G.L."
]
]
"ouvrage" => ""
"keywords" => array:1 [
0 => "Analyse conjointe"
]
"updatedAt" => "2020-12-17 17:55:06"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "443-460"
"volume" => "27"
"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" => "Cet article explore différentes approches permettant d'utiliser l'analyse conjointe pour développer un système de recommendation en ligne nécessitant des efforts minima de la part des utilisateurs."
"en" => "This article explores different approaches to design an efficient and easy-to-use questionnaire-based recommender system, based on the results of a conjoint analysis."
]
"authors_fields" => array:2 [
"fr" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
36 => Essec\Faculty\Model\Contribution {#2328
#_index: "academ_contributions"
#_id: "2145"
#_source: array:18 [
"id" => "2145"
"slug" => "opening-a-donors-wallet-the-influence-of-appeal-scales-on-likelihood-and-magnitude-of-donation"
"yearMonth" => "2013-10"
"year" => "2013"
"title" => "Opening a Donor’s Wallet: The Influence of Appeal Scales on Likelihood and Magnitude of Donation"
"description" => "DE BRUYN, A. et PROKOPEC, S. (2013). Opening a Donor’s Wallet: The Influence of Appeal Scales on Likelihood and Magnitude of Donation. <i>Journal of Consumer Psychology</i>, 23(4), pp. 496-502."
"authors" => array:2 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:3 [
"name" => "PROKOPEC Sonja"
"bid" => "B00145716"
"slug" => "prokopec-sonja"
]
]
"ouvrage" => ""
"keywords" => []
"updatedAt" => "2021-02-02 16:16:18"
"publicationUrl" => "https://doi.org/10.1016/j.jcps.2013.03.004"
"publicationInfo" => array:3 [
"pages" => "496-502"
"volume" => "23"
"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" => "We examine the influence of appeal scales on the likelihood and magnitude of donation in a large field experiment. We argue and show that the leftmost anchor on the appeal scale most strongly influences the likelihood of donating; the lower the anchor, the higher the donation likelihood. Furthermore, our findings indicate that increasing the steepness of the amounts on the appeal scale increases the magnitude of donations. Both effects are stronger for infrequent than for frequent donors. Our results demonstrate that by using what a charity knows about past donor behavior, it can alter appeal scales to change donation behavior."
"en" => "We examine the influence of appeal scales on the likelihood and magnitude of donation in a large field experiment. We argue and show that the leftmost anchor on the appeal scale most strongly influences the likelihood of donating; the lower the anchor, the higher the donation likelihood. Furthermore, our findings indicate that increasing the steepness of the amounts on the appeal scale increases the magnitude of donations. Both effects are stronger for infrequent than for frequent donors. Our results demonstrate that by using what a charity knows about past donor behavior, it can alter appeal scales to change donation behavior."
]
"authors_fields" => array:2 [
"fr" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
37 => Essec\Faculty\Model\Contribution {#2329
#_index: "academ_contributions"
#_id: "6660"
#_source: array:18 [
"id" => "6660"
"slug" => "maximizing-vs-satisficing-understanding-managers-tradeoffs-between-exploration-and-exploitation"
"yearMonth" => "2012-06"
"year" => "2012"
"title" => "Maximizing vs. Satisficing: Understanding Managers' Tradeoffs Between Exploration and Exploitation"
"description" => "DE BRUYN, A. et FERECATU, A. (2012). Maximizing vs. Satisficing: Understanding Managers' Tradeoffs Between Exploration and Exploitation. Dans: 2012 INFORMS Marketing Science Conference."
"authors" => array:2 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:1 [
"name" => "FERECATU A."
]
]
"ouvrage" => "2012 INFORMS Marketing Science Conference"
"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" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
38 => Essec\Faculty\Model\Contribution {#2330
#_index: "academ_contributions"
#_id: "6924"
#_source: array:18 [
"id" => "6924"
"slug" => "predicting-customer-behavior-with-lstm-neural-networks"
"yearMonth" => "2019-06"
"year" => "2019"
"title" => "Predicting Customer Behavior with LSTM Neural Networks"
"description" => "DE BRUYN, A. et SARKAR, M. (2019). Predicting Customer Behavior with LSTM Neural Networks. Dans: 2019 INFORMS Marketing Science Conference."
"authors" => array:2 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:1 [
"name" => "SARKAR Mainak"
]
]
"ouvrage" => "2019 INFORMS Marketing Science Conference"
"keywords" => []
"updatedAt" => "2021-09-24 10:33:27"
"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" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
39 => Essec\Faculty\Model\Contribution {#2331
#_index: "academ_contributions"
#_id: "5197"
#_source: array:18 [
"id" => "5197"
"slug" => "understanding-managers-tradeoffs-between-exploration-and-exploitation"
"yearMonth" => "2016-06"
"year" => "2016"
"title" => "Understanding Managers’ Tradeoffs Between Exploration and Exploitation"
"description" => "FERECATU, A. et DE BRUYN, A. (2016). Understanding Managers’ Tradeoffs Between Exploration and Exploitation. Dans: <i>1st Behavioral Industrial Organization & Marketing Symposium</i>. University of Michigan."
"authors" => array:2 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:1 [
"name" => "FERECATU A."
]
]
"ouvrage" => "1st Behavioral Industrial Organization & Marketing Symposium"
"keywords" => []
"updatedAt" => "2021-07-13 14:31:06"
"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" => null
"en" => null
]
"authors_fields" => array:2 [
"fr" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
40 => Essec\Faculty\Model\Contribution {#2332
#_index: "academ_contributions"
#_id: "5400"
#_source: array:18 [
"id" => "5400"
"slug" => "an-empirical-investigation-of-word-of-mouth-spillovers-on-consumer-decision-process"
"yearMonth" => "2017-05"
"year" => "2017"
"title" => "An Empirical Investigation of Word-Of-Mouth Spillovers on Consumer Decision Process"
"description" => "DE BRUYN, A. (2017). An Empirical Investigation of Word-Of-Mouth Spillovers on Consumer Decision Process. Dans: 46th European Marketing Academy Conference (EMAC) 2017."
"authors" => array:1 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
]
"ouvrage" => "46th European Marketing Academy Conference (EMAC) 2017"
"keywords" => []
"updatedAt" => "2021-09-24 10:33:27"
"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" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
41 => Essec\Faculty\Model\Contribution {#2333
#_index: "academ_contributions"
#_id: "1312"
#_source: array:18 [
"id" => "1312"
"slug" => "hierarchical-bayesian-conjoint-models-incorporating-measurement-uncertainty"
"yearMonth" => "2008-01"
"year" => "2008"
"title" => "Hierarchical Bayesian Conjoint Models Incorporating Measurement Uncertainty"
"description" => "LIECHTY, J.C., FONG, D.K.H., HUIZINGH, E.K.R.E. et DE BRUYN, A. (2008). Hierarchical Bayesian Conjoint Models Incorporating Measurement Uncertainty. <i>Marketing Letters</i>, 19(3), pp. 141-155."
"authors" => array:4 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:1 [
"name" => "LIECHTY J.C."
]
2 => array:1 [
"name" => "FONG D.K.H."
]
3 => array:1 [
"name" => "HUIZINGH E.K.R.E."
]
]
"ouvrage" => ""
"keywords" => array:1 [
0 => "Incertitude"
]
"updatedAt" => "2020-12-17 17:55:06"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "141-155"
"volume" => "19"
"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" => "Comment améliorer la modélisation des préférences des consommateurs en prenant en compte des mesures d'incertitude des consommateurs à propos de leurs propres préférences."
"en" => "How measuring uncertainty about consumers' own preferences can improve the quantification of these preferences."
]
"authors_fields" => array:2 [
"fr" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
42 => Essec\Faculty\Model\Contribution {#2334
#_index: "academ_contributions"
#_id: "1323"
#_source: array:18 [
"id" => "1323"
"slug" => "how-incorporating-feedback-mechanisms-in-a-dss-affects-dss-evaluations"
"yearMonth" => "2009-12"
"year" => "2009"
"title" => "How Incorporating Feedback Mechanisms in a DSS Affects DSS Evaluations"
"description" => "KAYANDE, U., DE BRUYN, A., LILIEN, G.L., RANGASWAMY, A. et VAN BRUGGEN, G.H. (2009). How Incorporating Feedback Mechanisms in a DSS Affects DSS Evaluations. <i>Information Systems Research</i>, 20(4), pp. 527-546."
"authors" => array:5 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:1 [
"name" => "KAYANDE U."
]
2 => array:1 [
"name" => "LILIEN G.L."
]
3 => array:1 [
"name" => "RANGASWAMY A."
]
4 => array:1 [
"name" => "VAN BRUGGEN G.H."
]
]
"ouvrage" => ""
"keywords" => array:6 [
0 => "Apprentissage"
1 => "Decision Support Systems"
2 => "Evaluation"
3 => "Feedback"
4 => "Modèle mental"
5 => "Outils d'aide à la décision"
]
"updatedAt" => "2020-12-17 17:55:06"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => "527-546"
"volume" => "20"
"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" => "Cet article montre que pour qu'un outil d'aide à la décision (DSS) soit adopté et utilisé, il est impératif de réduire le "gap" qui existe entre la manière dont le manager voit le monde, et la manière dont le DSS le modélise. Ce "gap" ne peut être réduit que par un procédé d'apprentissage, qui nécessite deux types simultanés de "feedback loops": upside potential feedback et corrective feedback."
"en" => "This article shows that for a Decision-Support System to be adopted (and used), one needs to reduce the gap between the manager's mental model (how s/he sees the world) and the DSS model (how the DSS models it), through deep learning. This deep learning can only be achieved by a combination of upside potential feedback (what could be achieved) and corrective feedback (how to achieve it)."
]
"authors_fields" => array:2 [
"fr" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
43 => Essec\Faculty\Model\Contribution {#2335
#_index: "academ_contributions"
#_id: "5488"
#_source: array:18 [
"id" => "5488"
"slug" => "bayesian-database-profiling"
"yearMonth" => "2016-01"
"year" => "2016"
"title" => "Bayesian Database Profiling"
"description" => "OTTER, T. et DE BRUYN, A. (2016). Bayesian Database Profiling. Dans: 2016 Winter Marketing-Economics Summit."
"authors" => array:2 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:1 [
"name" => "OTTER Thomas"
]
]
"ouvrage" => "2016 Winter Marketing-Economics Summit"
"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" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
44 => Essec\Faculty\Model\Contribution {#2336
#_index: "academ_contributions"
#_id: "5490"
#_source: array:18 [
"id" => "5490"
"slug" => "bayesian-profiling-of-customers-using-census-bureau-data"
"yearMonth" => "2013-07"
"year" => "2013"
"title" => "Bayesian Profiling of Customers Using Census Bureau Data"
"description" => "DE BRUYN, A. et OTTER, T. (2013). Bayesian Profiling of Customers Using Census Bureau Data. Dans: 2013 INFORMS Marketing Science Conference."
"authors" => array:2 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:1 [
"name" => "OTTER Thomas"
]
]
"ouvrage" => "2013 INFORMS Marketing Science Conference"
"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" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
45 => Essec\Faculty\Model\Contribution {#2337
#_index: "academ_contributions"
#_id: "5689"
#_source: array:18 [
"id" => "5689"
"slug" => "customer-acquisition-strategies-in-direct-marketing-will-better-always-mean-higher-value"
"yearMonth" => "2009-01"
"year" => "2009"
"title" => "Customer Acquisition Strategies in Direct Marketing: Will Better Always Mean Higher Value?"
"description" => "DE BRUYN, A. (2009). Customer Acquisition Strategies in Direct Marketing: Will Better Always Mean Higher Value? Dans: 31st Annual Marketing Science Conference."
"authors" => array:1 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
]
"ouvrage" => "31st Annual Marketing Science Conference"
"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" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
46 => Essec\Faculty\Model\Contribution {#2338
#_index: "academ_contributions"
#_id: "5801"
#_source: array:18 [
"id" => "5801"
"slug" => "dont-speak-how-the-market-halo-effect-harms-the-leaders"
"yearMonth" => "2015-05"
"year" => "2015"
"title" => "Don't speak! How the Market Halo Effect Harms the Leaders"
"description" => "DE BRUYN, A. et COLICEV, A. (2015). Don't speak! How the Market Halo Effect Harms the Leaders. Dans: European Marketing Academy Conference 2015."
"authors" => array:2 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:1 [
"name" => "COLICEV A."
]
]
"ouvrage" => "European Marketing Academy Conference 2015"
"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" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
47 => Essec\Faculty\Model\Contribution {#2339
#_index: "academ_contributions"
#_id: "5892"
#_source: array:18 [
"id" => "5892"
"slug" => "estimating-the-heterogeneity-of-fairness-preferences-on-bargaining-behavior"
"yearMonth" => "2015-06"
"year" => "2015"
"title" => "Estimating the Heterogeneity of Fairness Preferences on Bargaining Behavior"
"description" => "DE BRUYN, A. et FERECATU, A. (2015). Estimating the Heterogeneity of Fairness Preferences on Bargaining Behavior. Dans: Informs Marketing Science 2015."
"authors" => array:2 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:1 [
"name" => "FERECATU A."
]
]
"ouvrage" => "Informs Marketing Science 2015"
"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" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
48 => Essec\Faculty\Model\Contribution {#2340
#_index: "academ_contributions"
#_id: "14199"
#_source: array:18 [
"id" => "14199"
"slug" => "marketing-analytics-educating-managers-vs-educating-technicians"
"yearMonth" => "2022-05"
"year" => "2022"
"title" => "Marketing analytics: educating managers vs. educating technicians"
"description" => "DE BRUYN, A. (2022). Marketing analytics: educating managers vs. educating technicians. Dans: 2022 European Marketing Academy (EMAC) Annual Conference. Budapest."
"authors" => array:1 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
]
"ouvrage" => "2022 European Marketing Academy (EMAC) Annual Conference"
"keywords" => []
"updatedAt" => "2023-07-21 01:00:38"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => ""
"volume" => ""
"number" => ""
]
"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" => ""
"en" => ""
]
"authors_fields" => array:2 [
"fr" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
49 => Essec\Faculty\Model\Contribution {#2341
#_index: "academ_contributions"
#_id: "14939"
#_source: array:18 [
"id" => "14939"
"slug" => "bots-bargaining-with-humans-building-ai-super-bargainers-with-algorithmic-anthropomorphization"
"yearMonth" => "2024-05"
"year" => "2024"
"title" => "Bots Bargaining with Humans: Building AI Super-Bargainers with Algorithmic Anthropomorphization"
"description" => "DE BRUYN, A. et CHAUDHURI, S. (2024). Bots Bargaining with Humans: Building AI Super-Bargainers with Algorithmic Anthropomorphization. Dans: 53rd European Marketing Academy (EMAC) Conference 2024. Bucharest."
"authors" => array:2 [
0 => array:3 [
"name" => "De BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:1 [
"name" => "CHAUDHURI Sumon"
]
]
"ouvrage" => "53rd European Marketing Academy (EMAC) Conference 2024"
"keywords" => []
"updatedAt" => "2024-07-10 01:01:23"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => ""
"volume" => ""
"number" => ""
]
"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" => ""
"en" => ""
]
"authors_fields" => array:2 [
"fr" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
50 => Essec\Faculty\Model\Contribution {#2342
#_index: "academ_contributions"
#_id: "11968"
#_source: array:18 [
"id" => "11968"
"slug" => "artificial-intelligence-and-marketing-pitfalls-and-opportunities"
"yearMonth" => "2020-08"
"year" => "2020"
"title" => "Artificial Intelligence and Marketing: Pitfalls and Opportunities"
"description" => "DE BRUYN, A., VISWANATHAN, V., SHAN BE, Y., BROCK, J.K.U. et VON WANGENHEIM, F. (2020). Artificial Intelligence and Marketing: Pitfalls and Opportunities. <i>Journal of Interactive Marketing</i>, 51(August), pp. 91-105."
"authors" => array:5 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:1 [
"name" => "VISWANATHAN Vijay"
]
2 => array:1 [
"name" => "SHAN BE Yean"
]
3 => array:1 [
"name" => "BROCK Jürgen Kai-Uwe"
]
4 => array:1 [
"name" => "VON WANGENHEIM Florian"
]
]
"ouvrage" => ""
"keywords" => []
"updatedAt" => "2023-07-10 17:13:02"
"publicationUrl" => "https://doi.org/10.1016/j.intmar.2020.04.007"
"publicationInfo" => array:3 [
"pages" => "91-105"
"volume" => "51"
"number" => "August"
]
"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 article discusses the pitfalls and opportunities of AI in marketing through the lenses of knowledge creation and knowledge transfer. First, we discuss the notion of “higher-order learning” that distinguishes AI applications from traditional modeling approaches, and while focusing on recent advances in deep neural networks, we cover its underlying methodologies (multilayer perceptron, convolutional, and recurrent neural networks) and learning paradigms (supervised, unsupervised, and reinforcement learning). Second, we discuss the technological pitfalls and dangers marketing managers need to be aware of when implementing AI in their organizations, including the concepts of badly defined objective functions, unsafe or unrealistic learning environments, biased AI, explainable AI, and controllable AI. Third, AI will have a deep impact on predictive tasks that can be automated and require little explainability, we predict that AI will fall short of its promises in many marketing domains if we do not solve the challenges of tacit knowledge transfer between AI models and marketing organizations."
"en" => "This article discusses the pitfalls and opportunities of AI in marketing through the lenses of knowledge creation and knowledge transfer. First, we discuss the notion of “higher-order learning” that distinguishes AI applications from traditional modeling approaches, and while focusing on recent advances in deep neural networks, we cover its underlying methodologies (multilayer perceptron, convolutional, and recurrent neural networks) and learning paradigms (supervised, unsupervised, and reinforcement learning). Second, we discuss the technological pitfalls and dangers marketing managers need to be aware of when implementing AI in their organizations, including the concepts of badly defined objective functions, unsafe or unrealistic learning environments, biased AI, explainable AI, and controllable AI. Third, AI will have a deep impact on predictive tasks that can be automated and require little explainability, we predict that AI will fall short of its promises in many marketing domains if we do not solve the challenges of tacit knowledge transfer between AI models and marketing organizations."
]
"authors_fields" => array:2 [
"fr" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
51 => Essec\Faculty\Model\Contribution {#2343
#_index: "academ_contributions"
#_id: "11969"
#_source: array:18 [
"id" => "11969"
"slug" => "lstm-response-models-for-direct-marketing-analytics-replacing-feature-engineering-with-deep-learning"
"yearMonth" => "2021-02"
"year" => "2021"
"title" => "LSTM Response Models for Direct Marketing Analytics: Replacing Feature Engineering with Deep Learning"
"description" => "SARKAR, M. et DE BRUYN, A. (2021). LSTM Response Models for Direct Marketing Analytics: Replacing Feature Engineering with Deep Learning. <i>Journal of Interactive Marketing</i>, 53(February), pp. 80-95."
"authors" => array:2 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:1 [
"name" => "SARKAR Mainak"
]
]
"ouvrage" => ""
"keywords" => array:6 [
0 => "Long-short term memory neural network (LSTM)"
1 => "Recurrent neural network (RNN)"
2 => "Feature engineering"
3 => "Response model"
4 => "Panel data"
5 => "Direct marketing"
]
"updatedAt" => "2023-07-10 16:44:08"
"publicationUrl" => "https://doi.org/10.1016/j.intmar.2020.07.002"
"publicationInfo" => array:3 [
"pages" => "80-95"
"volume" => "53"
"number" => "February"
]
"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 predictive modeling, firms often deal with high-dimensional data that span multiple channels, websites, demographics, purchase types, and product categories. Traditional customer response models rely heavily on feature engineering, and their performance depends on the analyst's domain knowledge and expertise to craft relevant predictors. As the complexity of data increases, however, traditional models grow exponentially complicated. In this paper, we demonstrate that long-short term memory (LSTM) neural networks, which rely exclusively on raw data as input, can predict customer behaviors with great accuracy. In our first application, a model outperforms standard benchmarks. In a second, more realistic application, an LSTM model competes against 271 hand-crafted models that use a wide variety of features and modeling approaches. It beats 269 of them, most by a wide margin. LSTM neural networks are excellent candidates for modeling customer behavior using panel data in complex environments (e.g., direct marketing, brand choices, clickstream data, churn prediction)."
"en" => "In predictive modeling, firms often deal with high-dimensional data that span multiple channels, websites, demographics, purchase types, and product categories. Traditional customer response models rely heavily on feature engineering, and their performance depends on the analyst's domain knowledge and expertise to craft relevant predictors. As the complexity of data increases, however, traditional models grow exponentially complicated. In this paper, we demonstrate that long-short term memory (LSTM) neural networks, which rely exclusively on raw data as input, can predict customer behaviors with great accuracy. In our first application, a model outperforms standard benchmarks. In a second, more realistic application, an LSTM model competes against 271 hand-crafted models that use a wide variety of features and modeling approaches. It beats 269 of them, most by a wide margin. LSTM neural networks are excellent candidates for modeling customer behavior using panel data in complex environments (e.g., direct marketing, brand choices, clickstream data, churn prediction)."
]
"authors_fields" => array:2 [
"fr" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
52 => Essec\Faculty\Model\Contribution {#2344
#_index: "academ_contributions"
#_id: "12422"
#_source: array:18 [
"id" => "12422"
"slug" => "understanding-managers-trade-offs-between-exploration-and-exploitation"
"yearMonth" => "2022-01"
"year" => "2022"
"title" => "Understanding Managers' Trade-offs between Exploration and Exploitation"
"description" => "FERECATU, A. et DE BRUYN, A. (2022). Understanding Managers' Trade-offs between Exploration and Exploitation. <i>Marketing Science</i>, 41(1), pp. 139-165."
"authors" => array:2 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:1 [
"name" => "FERECATU Alina"
]
]
"ouvrage" => ""
"keywords" => array:6 [
0 => "Managerial decision-making"
1 => "Behavioral economics"
2 => "Exploration/exploitation trade-offs"
3 => "Multi-armed bandits"
4 => "Belief-updating"
5 => "Satisficing"
]
"updatedAt" => "2024-10-31 13:51:19"
"publicationUrl" => "https://pubsonline.informs.org/doi/10.1287/mksc.2021.1304"
"publicationInfo" => array:3 [
"pages" => "139-165"
"volume" => "41"
"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" => "Managers frequently explore new strategies, and exploit familiar ones, when making decisions on new product development, pricing, or advertising. Exploring for too long, or exploiting too soon, will generate inferior financial returns. Our research describes decision-makers' exploration/exploitation trade-offs and their link to psychometric traits. We conduct an incentive-aligned study in which subjects play a multi-armed bandit experiment and evaluate how subjects balance exploration and exploitation, linked to psychometric traits. To formally describe exploration/exploitation trade-offs, we develop a behavioral model that captures latent dynamics in learning behavior. Subjects transition between three unobserved states: exploration, exploitation, and inertia, updating their beliefs about expected payoffs. Our analysis suggests that decision-makers over-explore low-performing options, forgoing over 30\% of potential revenue. They heavily rely on recent experiences. Risk-averse decision-makers spend more time exploring. Maximizers are more sensitive to payoffs than satisficers. Our research builds the groundwork needed to devise remedial actions aimed at assisting managers find an optimal balance between exploration and exploitation. One way to achieve this goal is by carefully designing the learning environment. In two additional studies, we analyze the evolution of exploration/exploitation trade-offs across different learning environments. Offering decision-makers repeated opportunities to learn and increasing the planning horizon appears beneficial."
"en" => "Managers frequently explore new strategies, and exploit familiar ones, when making decisions on new product development, pricing, or advertising. Exploring for too long, or exploiting too soon, will generate inferior financial returns. Our research describes decision-makers' exploration/exploitation trade-offs and their link to psychometric traits. We conduct an incentive-aligned study in which subjects play a multi-armed bandit experiment and evaluate how subjects balance exploration and exploitation, linked to psychometric traits. To formally describe exploration/exploitation trade-offs, we develop a behavioral model that captures latent dynamics in learning behavior. Subjects transition between three unobserved states: exploration, exploitation, and inertia, updating their beliefs about expected payoffs. Our analysis suggests that decision-makers over-explore low-performing options, forgoing over 30\% of potential revenue. They heavily rely on recent experiences. Risk-averse decision-makers spend more time exploring. Maximizers are more sensitive to payoffs than satisficers. Our research builds the groundwork needed to devise remedial actions aimed at assisting managers find an optimal balance between exploration and exploitation. One way to achieve this goal is by carefully designing the learning environment. In two additional studies, we analyze the evolution of exploration/exploitation trade-offs across different learning environments. Offering decision-makers repeated opportunities to learn and increasing the planning horizon appears beneficial."
]
"authors_fields" => array:2 [
"fr" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
53 => Essec\Faculty\Model\Contribution {#2345
#_index: "academ_contributions"
#_id: "12668"
#_source: array:18 [
"id" => "12668"
"slug" => "bayesian-consumer-profiling-how-to-estimate-consumer-characteristics-from-aggregate-data"
"yearMonth" => "2022-08"
"year" => "2022"
"title" => "Bayesian Consumer Profiling: How to Estimate Consumer Characteristics from Aggregate Data"
"description" => "DE BRUYN, A. et OTTER, T. (2022). Bayesian Consumer Profiling: How to Estimate Consumer Characteristics from Aggregate Data. <i>Journal of Marketing Research</i>, 59(4), pp. 755-774."
"authors" => array:2 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:1 [
"name" => "OTTER Thomas"
]
]
"ouvrage" => ""
"keywords" => array:6 [
0 => "Consumer profiling"
1 => "Data augmentation"
2 => "Data brokerage"
3 => "Bayesian profiling"
4 => "Sociodemographic profiling"
5 => "Geolocation"
]
"updatedAt" => "2023-01-26 14:54:44"
"publicationUrl" => "https://journals.sagepub.com/doi/abs/10.1177/00222437211059088"
"publicationInfo" => array:3 [
"pages" => "755-774"
"volume" => "59"
"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" => "Firms use aggregate data from data brokers (e.g., Acxiom, Experian) and external data sources (e.g., Census) to infer the likely characteristics of consumers in a target list and thus better predict consumers’ profiles and needs unobtrusively. We demonstrate that the simple count method most commonly used in this effort relies implicitly on an assumption of conditional independence that fails to hold in many settings of managerial interest. We develop a Bayesian profiling method introducing different conditional independence assumptions. We also show how to introduce additional observed covariates into this model. We use simulations to show that in managerially relevant settings, the Bayesian method will outperform the simple count method, often by an order of magnitude. We then compare different conditional independence assumptions in two case studies. The first example estimates customers’ age based on their first names; prediction errors decrease substantially. In the second example, we infer the income, occupation, and education of online visitors of a marketing analytic software company based exclusively on their IP addresses. The face validity of the predictions improves dramatically and reveals an interesting (and more complex) endogenous list-selection mechanism than the one suggested by the simple count method."
"en" => "Firms use aggregate data from data brokers (e.g., Acxiom, Experian) and external data sources (e.g., Census) to infer the likely characteristics of consumers in a target list and thus better predict consumers’ profiles and needs unobtrusively. We demonstrate that the simple count method most commonly used in this effort relies implicitly on an assumption of conditional independence that fails to hold in many settings of managerial interest. We develop a Bayesian profiling method introducing different conditional independence assumptions. We also show how to introduce additional observed covariates into this model. We use simulations to show that in managerially relevant settings, the Bayesian method will outperform the simple count method, often by an order of magnitude. We then compare different conditional independence assumptions in two case studies. The first example estimates customers’ age based on their first names; prediction errors decrease substantially. In the second example, we infer the income, occupation, and education of online visitors of a marketing analytic software company based exclusively on their IP addresses. The face validity of the predictions improves dramatically and reveals an interesting (and more complex) endogenous list-selection mechanism than the one suggested by the simple count method."
]
"authors_fields" => array:2 [
"fr" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
54 => Essec\Faculty\Model\Contribution {#2346
#_index: "academ_contributions"
#_id: "12731"
#_source: array:18 [
"id" => "12731"
"slug" => "did-clickbait-crack-the-code-on-virality"
"yearMonth" => "2022-05"
"year" => "2022"
"title" => "Did Clickbait Crack the Code on Virality?"
"description" => "MUKHERJEE, P., DUTTA, S. et DE BRUYN, A. (2022). Did Clickbait Crack the Code on Virality? <i>Journal of the Academy of Marketing Science</i>, 50, pp. 482-502."
"authors" => array:3 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:1 [
"name" => "MUKHERJEE Prithwiraj"
]
2 => array:1 [
"name" => "DUTTA Souvik"
]
]
"ouvrage" => ""
"keywords" => array:7 [
0 => "Social media"
1 => "Clickbait"
2 => "Persuasion Knowledge Model"
3 => "Source derogation -Sharing"
4 => "Topic modeling"
5 => "Sentiment analysis"
6 => "Propensity score matching."
]
"updatedAt" => "2024-10-31 13:51:19"
"publicationUrl" => "https://doi.org/10.1007/s11747-021-00830-x"
"publicationInfo" => array:3 [
"pages" => "482-502"
"volume" => "50"
"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" => "Although clickbait is a ubiquitous tactic in digital media, we challenge the popular belief that clickbait systematically leads to enhanced sharing of online content on social media. Using the Persuasion Knowledge Model, we predict that clickbait tactics may be perceived by some readers as a manipulative attempt, leading to source derogation where the publisher may be perceived as less competent and trustworthy. This, in turn, may reduce some readers’ intention to share content. Using a controlled experiment, we confirm that high-emotional headlines are shared more and show evidence that clickbait often leads to inferences of manipulative intent and source derogation. We then use a well-known secondary data set containing 19,386 articles from 27 leading online publishers. We supplement it with Twitter share data, sentiment analysis, topic modeling, and additional control variables. We confirm that, on average, clickbait articles elicit far fewer shares than non-clickbait articles. Our results are stable, with large effect sizes even after controlling for endogenous selection."
"en" => "Although clickbait is a ubiquitous tactic in digital media, we challenge the popular belief that clickbait systematically leads to enhanced sharing of online content on social media. Using the Persuasion Knowledge Model, we predict that clickbait tactics may be perceived by some readers as a manipulative attempt, leading to source derogation where the publisher may be perceived as less competent and trustworthy. This, in turn, may reduce some readers’ intention to share content. Using a controlled experiment, we confirm that high-emotional headlines are shared more and show evidence that clickbait often leads to inferences of manipulative intent and source derogation. We then use a well-known secondary data set containing 19,386 articles from 27 leading online publishers. We supplement it with Twitter share data, sentiment analysis, topic modeling, and additional control variables. We confirm that, on average, clickbait articles elicit far fewer shares than non-clickbait articles. Our results are stable, with large effect sizes even after controlling for endogenous selection."
]
"authors_fields" => array:2 [
"fr" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
55 => Essec\Faculty\Model\Contribution {#2347
#_index: "academ_contributions"
#_id: "13970"
#_source: array:18 [
"id" => "13970"
"slug" => "horizontal-referrals-in-b2b-markets"
"yearMonth" => "2024-02"
"year" => "2024"
"title" => "Horizontal Referrals in B2B Markets"
"description" => "HADA, M., DE BRUYN, A. et LILIEN, G.L. (2024). Horizontal Referrals in B2B Markets. <i>Journal of Marketing Research</i>, 61(1), pp. 143-164."
"authors" => array:3 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:1 [
"name" => "HADA Mahima"
]
2 => array:1 [
"name" => "LILIEN Gary L."
]
]
"ouvrage" => ""
"keywords" => array:4 [
0 => "B2B Markets"
1 => "Referrals"
2 => "Customer-Supplier Relationship"
3 => "Conjoint Experiment"
]
"updatedAt" => "2024-10-31 13:51:19"
"publicationUrl" => "https://journals.sagepub.com/doi/epdf/10.1177/00222437231175415"
"publicationInfo" => array:3 [
"pages" => "143-164"
"volume" => "61"
"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" => """
Horizontal referrals –when suppliers recommend other suppliers– are a common phenomenon in complex B2B markets. For the referring supplier, giving the best-possible horizontal referral may strengthen the relationship with its customer, yet it may also threaten the referring supplier’s future revenues and cross-selling opportunities. Instead, the supplier could make an obligatory referral, one that fulfills the obligations of recommending another supplier while keeping referring supplier’s own interests paramount. We rely on role theory and its antecedents (mutual trust and referring supplier’s dependence) to determine when a referring supplier adopts the role of a friend (vs. a businessperson) and gives the best-possible referral (vs. an obligatory\n
referral). Study 1, an experiment, supports our theoretical model. Study 2, a conjoint study, links the observable antecedents of the referring supplier-customer relationship to their choice of horizontal referrals. Study 3, another experiment, looks at the consequences of the horizontal referral on the referring supplier-customer relationship and shows that providing an obligatory referral can hurt the customer’s intent to continue their relationship with their supplier. This effect is mediated by the customer’s perceived alignment of interest with their supplier. For B2B marketing research and practice, we report that the supplier’s dependence is critical to predicting the quality of horizontal referrals, even though an exploratory survey showed that customers overlook that dimension and focus on mutual trust when seeking referrals.
"""
"en" => """
Horizontal referrals –when suppliers recommend other suppliers– are a common phenomenon in complex B2B markets. For the referring supplier, giving the best-possible horizontal referral may strengthen the relationship with its customer, yet it may also threaten the referring supplier’s future revenues and cross-selling opportunities. Instead, the supplier could make an obligatory referral, one that fulfills the obligations of recommending another supplier while keeping referring supplier’s own interests paramount. We rely on role theory and its antecedents (mutual trust and referring supplier’s dependence) to determine when a referring supplier adopts the role of a friend (vs. a businessperson) and gives the best-possible referral (vs. an obligatory\n
referral). Study 1, an experiment, supports our theoretical model. Study 2, a conjoint study, links the observable antecedents of the referring supplier-customer relationship to their choice of horizontal referrals. Study 3, another experiment, looks at the consequences of the horizontal referral on the referring supplier-customer relationship and shows that providing an obligatory referral can hurt the customer’s intent to continue their relationship with their supplier. This effect is mediated by the customer’s perceived alignment of interest with their supplier. For B2B marketing research and practice, we report that the supplier’s dependence is critical to predicting the quality of horizontal referrals, even though an exploratory survey showed that customers overlook that dimension and focus on mutual trust when seeking referrals.
"""
]
"authors_fields" => array:2 [
"fr" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
56 => Essec\Faculty\Model\Contribution {#2348
#_index: "academ_contributions"
#_id: "14248"
#_source: array:18 [
"id" => "14248"
"slug" => "the-spillover-effects-of-positive-and-negative-buzz-on-brand-attitudes"
"yearMonth" => "2023-11"
"year" => "2023"
"title" => "The spillover effects of positive and negative buzz on brand attitudes"
"description" => "COLICEV, A. et DE BRUYN, A. (2023). The spillover effects of positive and negative buzz on brand attitudes. <i>European Journal of Marketing</i>, 57(9), pp. 2382-2406."
"authors" => array:2 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:1 [
"name" => "COLICEV Anatoli"
]
]
"ouvrage" => ""
"keywords" => array:6 [
0 => "Spillover effects"
1 => "Brand attitudes"
2 => "Brand strength"
3 => "Brand similarity"
4 => "Brand buzz"
5 => "Brand news"
]
"updatedAt" => "2024-10-31 13:51:19"
"publicationUrl" => "https://www.emerald.com/insight/content/doi/10.1108/EJM-01-2022-0044/full/html"
"publicationInfo" => array:3 [
"pages" => "2382-2406"
"volume" => "57"
"number" => "9"
]
"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 aims to investigate the effects of buzz about the focal brand on competing brands’ attitudes.\n
The authors find that spillover effects are widespread across product categories and affect competing brands through (negative) halo effect and (unfavorable) preference substitution. The authors do not find evidence of positive spillover effects for non-focal brands.\n
The authors provide generalizable evidence that positive and negative buzz spills over competing brands’ attitudes for hundreds of brands across the largest sectors of the US economy. Interestingly, positive and negative buzz have asymmetric effects on consumer attitudes. These effects vary by consumer attitude metric and are moderated by brand news intensity, strength and similarity.\n
First, marketing managers should monitor the buzz of competing brands. Second, if managers are concerned with impressions, they should intervene when there is a negative buzz about competitors (halo effect). Third, managers should stimulate positive buzz to negatively affect their competitors’ purchases. Fourth, managing a smaller brand has advantages regarding impressions and recommendations, while news intensity can shield from negative spillover effects for impressions. Finally, brand similarity amplifies the spillover effects across the board.
"""
"en" => """
This paper aims to investigate the effects of buzz about the focal brand on competing brands’ attitudes.\n
The authors find that spillover effects are widespread across product categories and affect competing brands through (negative) halo effect and (unfavorable) preference substitution. The authors do not find evidence of positive spillover effects for non-focal brands.\n
The authors provide generalizable evidence that positive and negative buzz spills over competing brands’ attitudes for hundreds of brands across the largest sectors of the US economy. Interestingly, positive and negative buzz have asymmetric effects on consumer attitudes. These effects vary by consumer attitude metric and are moderated by brand news intensity, strength and similarity.\n
First, marketing managers should monitor the buzz of competing brands. Second, if managers are concerned with impressions, they should intervene when there is a negative buzz about competitors (halo effect). Third, managers should stimulate positive buzz to negatively affect their competitors’ purchases. Fourth, managing a smaller brand has advantages regarding impressions and recommendations, while news intensity can shield from negative spillover effects for impressions. Finally, brand similarity amplifies the spillover effects across the board.
"""
]
"authors_fields" => array:2 [
"fr" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
57 => Essec\Faculty\Model\Contribution {#2349
#_index: "academ_contributions"
#_id: "14608"
#_source: array:18 [
"id" => "14608"
"slug" => "fundraising-analytics-a-roadmap-for-the-data-driven-fundraiser"
"yearMonth" => "2023-11"
"year" => "2023"
"title" => "Fundraising Analytics: A Roadmap for the Data-Driven Fundraiser"
"description" => "DE BRUYN, A. (2023). <i>Fundraising Analytics: A Roadmap for the Data-Driven Fundraiser</i>. 1st ed. Kindle."
"authors" => array:1 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
]
"ouvrage" => ""
"keywords" => array:3 [
0 => "Fundraising"
1 => "Marketing analytics"
2 => "Direct marketing"
]
"updatedAt" => "2024-05-28 10:26:16"
"publicationUrl" => "https://www.amazon.com/dp/B0CND9T3XD"
"publicationInfo" => array:3 [
"pages" => ""
"volume" => ""
"number" => ""
]
"type" => array:2 [
"fr" => "Livres"
"en" => "Books"
]
"support_type" => array:2 [
"fr" => "Editeur"
"en" => "Publisher"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => """
Customer data is becoming the new currency. It enables and fosters efficient customer relationship management, customer intimacy, and marketing performance. Yet, in a world where every news article boasts about the promises of artificial intelligence, advanced marketing analytics, and real-time optimization, fundraisers often find themselves years behind the curve.\n
This book takes a no-nonsense approach to fundraising analytics. It lays out the essential toolbox a fundraiser should understand and master to move forward: fundamental concepts, segmentation, predictive scoring techniques, and customer lifetime value, as well as a few miscellaneous topics.\n
The motto “let the data talk” is misguided. Data does not talk—data answers. And the first step to a more efficient, data-driven fundraising strategy is to understand which questions to ask and which matter the most. This book has been written to help you along your journey.
"""
"en" => """
Customer data is becoming the new currency. It enables and fosters efficient customer relationship management, customer intimacy, and marketing performance. Yet, in a world where every news article boasts about the promises of artificial intelligence, advanced marketing analytics, and real-time optimization, fundraisers often find themselves years behind the curve.\n
This book takes a no-nonsense approach to fundraising analytics. It lays out the essential toolbox a fundraiser should understand and master to move forward: fundamental concepts, segmentation, predictive scoring techniques, and customer lifetime value, as well as a few miscellaneous topics.\n
The motto “let the data talk” is misguided. Data does not talk—data answers. And the first step to a more efficient, data-driven fundraising strategy is to understand which questions to ask and which matter the most. This book has been written to help you along your journey.
"""
]
"authors_fields" => array:2 [
"fr" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
58 => Essec\Faculty\Model\Contribution {#2350
#_index: "academ_contributions"
#_id: "14636"
#_source: array:18 [
"id" => "14636"
"slug" => "silently-killing-your-panelists-one-email-at-a-time-the-true-cost-of-email-solicitations"
"yearMonth" => "2024-01"
"year" => "2024"
"title" => "Silently killing your panelists one email at a time: The true cost of email solicitations"
"description" => "FERECATU, A., DE BRUYN, A. et MUKHERJEE, P. (2024). Silently killing your panelists one email at a time: The true cost of email solicitations. <i>Journal of the Academy of Marketing Science</i>, In press."
"authors" => array:3 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:1 [
"name" => "Ferecatu Alina"
]
2 => array:1 [
"name" => "Mukherjee Prithwiraj"
]
]
"ouvrage" => ""
"keywords" => array:2 [
0 => "marketing"
1 => "solicitation"
]
"updatedAt" => "2024-01-17 16:00:11"
"publicationUrl" => "https://link.springer.com/article/10.1007/s11747-023-00992-w"
"publicationInfo" => array:3 [
"pages" => ""
"volume" => "In press"
"number" => ""
]
"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" => "Marketing firms routinely interact with their panelists via email. While sending an invitation to respond to a survey may seem virtually costless, over-solicitation could lead to panelists unsubscribing or ignoring future emails. Since online panels are a crucial resource for a marketing research firm, such attrition is a major issue. We account for the unobserved cost of solicitations in a joint model of response and attrition propensities. Using a data set of more than 150,000 email solicitations sent over three years, we demonstrate that additional solicitations not only temporarily decrease the likelihood of future participation but also increase the attrition rate, likely due to wearout. The model where solicitations “kill” panelists outperforms out of sample a benchmark model that assumes dropout is caused by the passage of time instead. Since the impact of solicitations is both transient (on the response model) and permanent (on the dropout process), managers should wait for the temporary impact to dissipate before risking to “kill” their panelists with another solicitation. We illustrate the economic importance of this finding using a differential evolution method that optimizes the firm’s solicitation strategy under different scenarios and show a 30.7% improvement. In the long term, a greedy strategy (targeting the best-responding panelists) performs worse than a random policy."
"en" => "Marketing firms routinely interact with their panelists via email. While sending an invitation to respond to a survey may seem virtually costless, over-solicitation could lead to panelists unsubscribing or ignoring future emails. Since online panels are a crucial resource for a marketing research firm, such attrition is a major issue. We account for the unobserved cost of solicitations in a joint model of response and attrition propensities. Using a data set of more than 150,000 email solicitations sent over three years, we demonstrate that additional solicitations not only temporarily decrease the likelihood of future participation but also increase the attrition rate, likely due to wearout. The model where solicitations “kill” panelists outperforms out of sample a benchmark model that assumes dropout is caused by the passage of time instead. Since the impact of solicitations is both transient (on the response model) and permanent (on the dropout process), managers should wait for the temporary impact to dissipate before risking to “kill” their panelists with another solicitation. We illustrate the economic importance of this finding using a differential evolution method that optimizes the firm’s solicitation strategy under different scenarios and show a 30.7% improvement. In the long term, a greedy strategy (targeting the best-responding panelists) performs worse than a random policy."
]
"authors_fields" => array:2 [
"fr" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
59 => Essec\Faculty\Model\Contribution {#2351
#_index: "academ_contributions"
#_id: "14934"
#_source: array:18 [
"id" => "14934"
"slug" => "a-unifying-and-parsimonious-model-of-anchoring-and-context-dependent-preferences"
"yearMonth" => "2024-05"
"year" => "2024"
"title" => "A Unifying and Parsimonious Model of Anchoring and Context-Dependent Preferences"
"description" => "DE BRUYN, A., MUKHERJEE, P. et ÖNCÜLER, A. (2024). A Unifying and Parsimonious Model of Anchoring and Context-Dependent Preferences. Dans: 2024 Risk, Insurance and Savings Laboratory (RISLab) Workshop in Honour of Peter P. Wakker. Rabat."
"authors" => array:3 [
0 => array:3 [
"name" => "DE BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:3 [
"name" => "ÖNCÜLER Ayse"
"bid" => "B00183494"
"slug" => "onculer-ayse"
]
2 => array:1 [
"name" => "MUKHERJEE Prithwiraj"
]
]
"ouvrage" => "2024 Risk, Insurance and Savings Laboratory (RISLab) Workshop in Honour of Peter P. Wakker"
"keywords" => []
"updatedAt" => "2024-07-10 01:01:23"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => ""
"volume" => ""
"number" => ""
]
"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" => ""
"en" => ""
]
"authors_fields" => array:2 [
"fr" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
60 => Essec\Faculty\Model\Contribution {#2352
#_index: "academ_contributions"
#_id: "14938"
#_source: array:18 [
"id" => "14938"
"slug" => "riding-the-social-media-wave-how-brand-topic-salience-impacts-engagement-with-direct-marketing-communication"
"yearMonth" => "2024-05"
"year" => "2024"
"title" => "Riding the Social Media Wave: How Brand Topic Salience Impacts Engagement with Direct Marketing Communication"
"description" => "DE BRUYN, A., ARORA, M., CHAUDHURI, S. et MAZODIER, M. (2024). Riding the Social Media Wave: How Brand Topic Salience Impacts Engagement with Direct Marketing Communication. Dans: 53rd European Marketing Academy (EMAC) Conference 2024. Bucharest."
"authors" => array:4 [
0 => array:3 [
"name" => "de BRUYN Arnaud"
"bid" => "B00024825"
"slug" => "de-bruyn-arnaud"
]
1 => array:3 [
"name" => "MAZODIER Marc"
"bid" => "B00791034"
"slug" => "mazodier-marc"
]
2 => array:1 [
"name" => "ARORA Madhav"
]
3 => array:1 [
"name" => "CHAUDHURI Sumon"
]
]
"ouvrage" => "53rd European Marketing Academy (EMAC) Conference 2024"
"keywords" => []
"updatedAt" => "2024-07-10 01:01:23"
"publicationUrl" => null
"publicationInfo" => array:3 [
"pages" => ""
"volume" => ""
"number" => ""
]
"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" => ""
"en" => ""
]
"authors_fields" => array:2 [
"fr" => "Marketing"
"en" => "Marketing"
]
"indexedAt" => "2024-11-21T06:21:44.000Z"
]
+lang: "en"
+"_type": "_doc"
+"_score": 5.54257
+"parent": null
}
]
"avatar" => "https://faculty.essec.edu/wp-content/uploads/avatars/B00024825.jpg"
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1 => "<a href="https://scholar.google.com/citations?user=4rVAgWUAAAAJ" target="_blank">Google scholar</a>"
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"docTitle" => "Arnaud de BRUYN"
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"docPreview" => "<img src="https://faculty.essec.edu/wp-content/uploads/avatars/B00024825.jpg"><span><span>Arnaud de BRUYN</span><span>B00024825</span></span>"
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