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2023
Kante, Mahamadou; Michel, Babri
In: Computers in Human Behavior Reports, vol. 10, pp. 100291, 2023, ISSN: 24519588.
Abstract | Links | BibTeX | Tags: Behavioural Information Security, BIS, disclosure, partial least squares structural equation modelling, PLS, PLSPredict, privacy, SEM
@article{Kante2023,
title = {Use of partial least squares structural equation modelling (PLS-SEM) in privacy and disclosure research on social network sites: A systematic review},
author = {Mahamadou Kante and Babri Michel},
url = {https://linkinghub.elsevier.com/retrieve/pii/S2451958823000246},
doi = {10.1016/j.chbr.2023.100291},
issn = {24519588},
year = {2023},
date = {2023-05-01},
urldate = {2023-05-01},
journal = {Computers in Human Behavior Reports},
volume = {10},
pages = {100291},
publisher = {Elsevier},
abstract = {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 Information Security with a focus on disclosure and privacy on SNSs studies and other fields as well.},
keywords = {Behavioural Information Security, BIS, disclosure, partial least squares structural equation modelling, PLS, PLSPredict, privacy, SEM},
pubstate = {published},
tppubtype = {article}
}
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 Information Security with a focus on disclosure and privacy on SNSs studies and other fields as well.