Essec\Faculty\Model\Contribution {#2233 ▼
#_index: "academ_contributions"
#_id: "2103"
#_source: array:26 [
"id" => "2103"
"slug" => "2103-non-symmetrical-composite-based-path-modeling"
"yearMonth" => "2017-11"
"year" => "2017"
"title" => "Non-Symmetrical Composite-Based Path Modeling"
"description" => "DOLCE, P., ESPOSITO VINZI, V. et LAURO, N.C. (2017). Non-Symmetrical Composite-Based Path Modeling. <i>Advances in Data Analysis and Classification</i>, 12(4), pp. 759-784. 
DOLCE, P., ESPOSITO VINZI, V. et LAURO, N.C. (2017). Non-Symmetrical Composite-Based Path Modeling. "
"authors" => array:3 [
0 => array:3 [
"name" => "ESPOSITO VINZI Vincenzo"
"bid" => "B00067049"
"slug" => "esposito-vinzi-vincenzo"
]
1 => array:1 [
"name" => "DOLCE P."
]
2 => array:1 [
"name" => "LAURO N.-C."
]
]
"ouvrage" => ""
"keywords" => array:3 [
0 => "PLS path modeling"
1 => "Non-symmetrical analysis"
2 => "Predictive composite-based methods"
]
"updatedAt" => "2021-09-24 10:33:27"
"publicationUrl" => "https://link.springer.com/article/10.1007/s11634-017-0302-1"
"publicationInfo" => array:3 [
"pages" => "759-784"
"volume" => "12"
"number" => "4"
]
"type" => array:2 [
"fr" => "Articles"
"en" => "Journal articles"
]
"support_type" => array:2 [
"fr" => "Revue scientifique"
"en" => "Scientific journal"
]
"countries" => array:2 [
"fr" => null
"en" => null
]
"abstract" => array:2 [
"fr" => """
Partial least squares path modeling presents some inconsistencies in terms of coherence with the predictive directions specified in the inner model (i.e. the path\n Partial least squares path modeling presents some inconsistencies in terms of coherence with the pre
directions), because the directions of the links in the inner model are not taken into account in the iterative algorithm. In fact, the procedure amplifies interdependence among blocks and fails to distinguish between dependent and explanatory blocks. The method proposed in this paper takes into account and respects the specified path directions, with the aim of improving the predictive ability of the model and to maintain the hypothesized theoretical inner model. To highlight its properties, the proposed method is compared to the classical PLS path modeling in terms of explained variability, predictive relevance and interpretation using artificial data through a real data application. A further development of the method allows to treat multi-dimensional blocks in composite-based path modeling. directions), because the directions of the links in the inner model are not taken into account in th
"""
"en" => "Partial least squares path modeling presents some inconsistencies in terms of coherence with the predictive directions specified in the inner model (i.e. the path directions), because the directions of the links in the inner model are not taken into account in the iterative algorithm. In fact, the procedure amplifies interdependence among blocks and fails to distinguish between dependent and explanatory blocks. The method proposed in this paper takes into account and respects the specified path directions, with the aim of improving the predictive ability of the model and to maintain the hypothesized theoretical inner model. To highlight its properties, the proposed method is compared to the classical PLS path modeling in terms of explained variability, predictive relevance and interpretation using artificial data through a real data application. A further development of the method allows to treat multi-dimensional blocks in composite-based path modeling. Partial least squares path modeling presents some inconsistencies in terms of coherence with the pre "
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2025-04-01T07:21:44.000Z"
"docTitle" => "Non-Symmetrical Composite-Based Path Modeling"
"docSurtitle" => "Articles"
"authorNames" => "<a href="/cv/esposito-vinzi-vincenzo">ESPOSITO VINZI Vincenzo</a>, DOLCE P., LAURO N.-C."
"docDescription" => "<span class="document-property-authors">ESPOSITO VINZI Vincenzo, DOLCE P., LAURO N.-C.</span><br><span class="document-property-authors_fields">Systèmes d'Information, Data Analytics et Opérations</span> | <span class="document-property-year">2017</span> <span class="document-property-authors">ESPOSITO VINZI Vincenzo, DOLCE P., LAURO N.-C.</span><br><sp "
"keywordList" => "<a href="#">PLS path modeling</a>, <a href="#">Non-symmetrical analysis</a>, <a href="#">Predictive composite-based methods</a> <a href="#">PLS path modeling</a>, <a href="#">Non-symmetrical analysis</a>, <a href="#">Predictive "
"docPreview" => "<b>Non-Symmetrical Composite-Based Path Modeling</b><br><span>2017-11 | Articles </span>"
"docType" => "research"
"publicationLink" => "<a href="https://link.springer.com/article/10.1007/s11634-017-0302-1" target="_blank">Non-Symmetrical Composite-Based Path Modeling</a> <a href="https://link.springer.com/article/10.1007/s11634-017-0302-1" target="_blank">Non-Symmetrica "
]
+lang: "fr"
+"_type": "_doc"
+"_score": 9.334091
+"parent": null
}
