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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.
2022
Kante, Mahamadou
A mapping of the factors related to self-disclosure on social network sites Journal Article
In: International Journal of Big Data Management, vol. 2, no. 1, pp. 60–69, 2022, ISSN: 2631-8679.
Links | BibTeX | Tags: Behavioural Information Security, BIS, disclosure, partial least squares structural equation modelling, privacy, SNSs, Social media
@article{Kante2022a,
title = {A mapping of the factors related to self-disclosure on social network sites},
author = {Mahamadou Kante},
doi = {10.1504/IJBDM.2020.10034496},
issn = {2631-8679},
year = {2022},
date = {2022-01-01},
urldate = {2022-01-01},
journal = {International Journal of Big Data Management},
volume = {2},
number = {1},
pages = {60–69},
publisher = {Inderscience Publishers},
keywords = {Behavioural Information Security, BIS, disclosure, partial least squares structural equation modelling, privacy, SNSs, Social media},
pubstate = {published},
tppubtype = {article}
}
Kante, Mahamadou; Adepo, Joel Christian; Babri, Michel
Towards a Model for Self-Disclosure on Social Network Sites Book Section
In: Building Resilient Healthcare Systems With ICTs, pp. 229–254, IGI-Global, 2022, ISBN: 0000000255448.
Abstract | Links | BibTeX | Tags: Behavioural Information Security, BIS, developing countries, disclosure, partial least squares structural equation modelling, PLS, PLSPredict, SNSs, Social media
@incollection{Kante2022,
title = {Towards a Model for Self-Disclosure on Social Network Sites},
author = {Mahamadou Kante and Joel Christian Adepo and Michel Babri},
url = {http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-8915-1.ch010},
doi = {10.4018/978-1-7998-8915-1.ch010},
isbn = {0000000255448},
year = {2022},
date = {2022-01-01},
urldate = {2022-01-01},
booktitle = {Building Resilient Healthcare Systems With ICTs},
pages = {229–254},
publisher = {IGI-Global},
chapter = {10},
abstract = {One of the current discussions is the resilience of health systems in developing countries. Online platforms users including health system users (patients, doctors) are worried about their privacy being violated. While the users of social media enjoy the opportunity to learn, connect, and share, their privacy on those platforms is at risk. A possible cause of this is the information privacy paradox, which describes a disconnect between users' stated concerns and actual behaviour. In the pilot phase of this study, the authors have used the partial least squares structural equation modelling technique for the analysis of the relationships postulated to explain self-disclosure in social network sites. The survey instrument's content validity and adapted model's constructs validity and reliability were confirmed, and the preliminary findings revealed that the derived model explains 32.9% of the user's self-disclosure intention on social network sites.},
keywords = {Behavioural Information Security, BIS, developing countries, disclosure, partial least squares structural equation modelling, PLS, PLSPredict, SNSs, Social media},
pubstate = {published},
tppubtype = {incollection}
}
One of the current discussions is the resilience of health systems in developing countries. Online platforms users including health system users (patients, doctors) are worried about their privacy being violated. While the users of social media enjoy the opportunity to learn, connect, and share, their privacy on those platforms is at risk. A possible cause of this is the information privacy paradox, which describes a disconnect between users' stated concerns and actual behaviour. In the pilot phase of this study, the authors have used the partial least squares structural equation modelling technique for the analysis of the relationships postulated to explain self-disclosure in social network sites. The survey instrument's content validity and adapted model's constructs validity and reliability were confirmed, and the preliminary findings revealed that the derived model explains 32.9% of the user's self-disclosure intention on social network sites.