Management researchers have traditionally perceived the need to balance between rigor and relevance, thus simultaneously advancing theory and offering managerial insights. The selection of proper research methods plays a fundamental role. Among them, structural equation modeling (a second-generation technique for multivariate analysis) has witnessed remarkable popularity in the last decades to assess relationships among constructs. There are two main approaches to structural equation modeling: the covariance-based approach (CB-SEM) and the variancebased approach (PLS-SEM). However, until recently, the PLS-SEM has been to a large extent ignored and many scholars have considered structural equation modeling as synonymous with CB-SEM. In the last decade, PLS-SEM has gained a huge interest from social sciences researchers from all over the world and many management journals (such as Journal of Business Research, European Journal of Management, and many others) have published special issues on this method. The renewed interest in PLS-SEM has been largely driven by the extensive work of management and marketing scholars such as Joseph F. Hair, Jr., Tomas M. Hult, Christian M. Ringle and Marko Sarstedt (Hair et al., 2017; Hair et al., 2018). Their well-known book about this method [“A primer on partial least squares structural equation modeling (PLS-SEM)”] has received more than 20,000 citations in Google Scholar since the publication of its first edition in 2014. Given that the use of this method could support the Italian management scholars to further increase their participation to the international debate on management issues, we recently co-edited the Italian version of this book (Hair et al., 2020). The purpose of this extended abstract is to provide a comprehensive review of the state of PLS-SEM research by the community of Italian management scholars.
Balancing theory and practice: a review of the state of PLS-SEM research by the community of Italian management scholars
Fabio Cassia
2021-01-01
Abstract
Management researchers have traditionally perceived the need to balance between rigor and relevance, thus simultaneously advancing theory and offering managerial insights. The selection of proper research methods plays a fundamental role. Among them, structural equation modeling (a second-generation technique for multivariate analysis) has witnessed remarkable popularity in the last decades to assess relationships among constructs. There are two main approaches to structural equation modeling: the covariance-based approach (CB-SEM) and the variancebased approach (PLS-SEM). However, until recently, the PLS-SEM has been to a large extent ignored and many scholars have considered structural equation modeling as synonymous with CB-SEM. In the last decade, PLS-SEM has gained a huge interest from social sciences researchers from all over the world and many management journals (such as Journal of Business Research, European Journal of Management, and many others) have published special issues on this method. The renewed interest in PLS-SEM has been largely driven by the extensive work of management and marketing scholars such as Joseph F. Hair, Jr., Tomas M. Hult, Christian M. Ringle and Marko Sarstedt (Hair et al., 2017; Hair et al., 2018). Their well-known book about this method [“A primer on partial least squares structural equation modeling (PLS-SEM)”] has received more than 20,000 citations in Google Scholar since the publication of its first edition in 2014. Given that the use of this method could support the Italian management scholars to further increase their participation to the international debate on management issues, we recently co-edited the Italian version of this book (Hair et al., 2020). The purpose of this extended abstract is to provide a comprehensive review of the state of PLS-SEM research by the community of Italian management scholars.File | Dimensione | Formato | |
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