PLS-SEM: Looking Back and Moving Forward

By Marko Sarstedt, Christian M. Ringle, Joseph F. Hair. 2014

394 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/8c44107d9e72085551e49ab514286e29ff31ce07

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Citations in the corpus

Predicting the acceptance and use of information and communication technology by older adults: An empirical examination of the revised UTAUT2 (2017, methodology): “PLS is an appropriate technique because the study has a predictive research goal and a relatively complex model (Roldán and Sánchez-Franco 2012; Sarstedt, Ringle & Hair, 2014).”
Place-Oriented or People-Oriented Concepts for Destination Loyalty: Destination Image and Place Attachment versus Perceived Distances and Emotional Solidarity (2021, background): “Since the study aims to identify the predictive power of a network of concepts rather than confirming well-accepted theoretical structures (Sarstedt, Ringle, and Hair 2014), PLS-SEM was deemed appropriate.”
On the Emancipation of PLS-SEM: A Commentary on Rigdon (2012) (2014, methodology): “In addition, Long Range Planning, one of the leading journals in the strategic management field, has devoted three special issues to the method (Hair et al., 2012b, 2013; Robins 2012, 2014; Sarstedt et al., 2014), providing a clear indication of the importance of PLS-SEM for research and practice.”
Partial least squares path modeling: Time for some serious second thoughts (2016, methodology): “One empirical study on several limitations of PLS (i.e., R€onkk€o and Evermann, 2013) was referred to as “nothing short of a polemic” (Sarstedt et al., 2014, p. 134; see also Henseler et al., 2014).”
Crowded and popular: The two sides of the coin affecting theme-park experience, satisfaction, and loyalty (2020, neutral): “Given the emerging stage of crowding literature accompanied by the scant number of any existing models measuring crowding relationships especially at theme parks, this study strived to empirically determine the predictive power of a network of concepts, rather than confirming well-established theore”
Consumer adoption of the Uber mobile application: Insights from diffusion of innovation theory and technology acceptance model (2018, methodology): “PLS-PM is considered to be the most appropriate analytical technique for analyzing the data, as the focus of this study is to understand the predictive relationships among the constructs, rather than theory conformation or testing (Chin & Newsted, 1999; Sarstedt, Ringle, & Hair, 2014).”