dc.creator | Cepeda-Carrión, Gabriel | es |
dc.creator | Henseler, Jörg | es |
dc.creator | Ringle, Christian M. | es |
dc.creator | Roldán Salgueiro, José Luis | es |
dc.date.accessioned | 2018-03-20T10:07:53Z | |
dc.date.available | 2018-03-20T10:07:53Z | |
dc.date.issued | 2016 | |
dc.identifier.citation | Cepeda-Carrión, G., Henseler, J., Ringle, C.M. y Roldán Salgueiro, J.L. (2016). Prediction-oriented modeling in business research by means of PLS path modeling: Introduction to a JBR special section. Journal of Business Research, 69 (10), 4545-4551. | |
dc.identifier.issn | 0148-2963 | es |
dc.identifier.uri | https://hdl.handle.net/11441/71116 | |
dc.description.abstract | Under the main theme
“
prediction-oriented modeling in business research by means of partial least squares path
modeling
”
(PLS), the special issue presents 17 papers. Most contributions include content from presentations at
the 2nd International Symposium on Partial Least Squares Path Modeling: The Conference for PLS Users, which
took place at the Universidad de Sevilla (Spain) from June 16 to 19, 2015. This conference provided PLS users
with a platform for the fruitful exchange of ideas on variance-based structural equation modeling. At the same
time, the conference addressed the latest methodological advances and their use in research practice. Finally,
the conference resumed and enriched the ongoing discussion on the strengths and weaknesses of PLS.
Researchers often emphasize that predictive capabilities is a strength of the PLS method. Nevertheless,
methodological advances and applications in this direction are rare. The scienti
fi
c committee therefore selected
high-quality papers that mainly advance PLS and prediction. The special issue editors believe that these special
issues will become the starting point for a more intensive use of predictive modeling in the social sciences
discipline and for additional advances that will exploit PLS' capabilities in this area | es |
dc.format | application/pdf | es |
dc.language.iso | eng | es |
dc.publisher | Elsevier | es |
dc.relation.ispartof | Journal of Business Research, 69 (10), 4545-4551. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Partial least squares | es |
dc.subject | Prediction-oriented modeling | es |
dc.subject | Business research | es |
dc.subject | Quantitative methods | es |
dc.title | Prediction-oriented modeling in business research by means of PLS path modeling: Introduction to a JBR special section | es |
dc.type | info:eu-repo/semantics/article | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/acceptedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Administración de Empresas y Comercialización e Investigación de Mercados (Marketing) | es |
dc.relation.publisherversion | https://doi.org/10.1016/j.jbusres.2016.03.048 | es |
dc.identifier.doi | 10.1016/j.jbusres.2016.03.048 | es |
idus.format.extent | 7 | es |
dc.journaltitle | Journal of Business Research | es |
dc.publication.volumen | 69 | es |
dc.publication.issue | 10 | es |
dc.publication.initialPage | 4545 | es |
dc.publication.endPage | 4551 | es |
dc.identifier.sisius | 20962202 | es |