Use of partial least squares structural equation modelling (PLS-SEM) in privacy and disclosure research on social network sites: A systematic review

Structural equation modelling (SEM) is a statistical technique used in the field of Information Systems amongst others. The technique has been paid attention thanks to its flexibility and predictive power. However, there is a paucity of guidelines in the application of the technique in the field of Behavioural Information Security. Hence, this paper aims to provide a comprehensive guide of using PLS-SEM in disclosure and privacy studies on Social Network Sites (SNSs). Data has been gathered using papers (n=21) published between 2006 and 2022 from scholarly databases such as Google Scholar, Association for Information Systems eLibrary (AISeL), IEEE Xplore and Science Direct. The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA 2020) was used to analyse and synthesize the status of the field. Our systematic review covers data characteristics, reasons for using PLS-SEM, the evaluation of measurement models, the evaluation of the structural model and reporting best practices. The review proposed guidelines for the use of PLS-SEM in the discipline of Behavioural Infor-mation Security with a focus on disclosure and privacy on SNSs studies and other fields as well.

Automated summary

This paper provides a comprehensive guide for using PLS-SEM in disclosure and privacy studies on Social Network Sites (SNSs) in the field of Behavioural Information Security. A systematic review of 21 papers published between 2006 and 2022 was conducted using PRISMA 2020. The review proposes guidelines for the use of PLS-SEM in the discipline of Behavioural Information Security with a focus on disclosure and privacy on SNSs studies and other fields as well.