Emerging opportunities for information systems researchers to expand their PLS-SEM analytical toolbox
Industrial Management & Data Systems
ISSN: 0263-5577
Article publication date: 22 May 2024
Issue publication date: 18 June 2024
Abstract
Purpose
Rigorous applications of analytical tools in information systems (IS) research are important for developing new knowledge and innovations in the field. Emerging tools provide building blocks for future inquiry, practice and innovation. This article summarizes the findings of an analysis of the adoption and reporting of partial least squares structural equation modeling (PLS-SEM) analytical tools by Industrial Management & Data Systems authors in the most recent five-year period.
Design/methodology/approach
Selected emerging advanced PLS-SEM analytical tools that have experienced limited adoption are highlighted to broaden awareness of their value to IS researchers.
Findings
PLS-SEM analytical tools that facilitate understanding increasingly complex theoretical models and deliver improved prediction assessment are now available. IS researchers should explore the opportunities to apply these new tools to more fully describe the contributions of their research.
Research limitations/implications
Findings demonstrate the increasing acceptance of PLS-SEM as a useful alternative research methodology within IS. PLS-SEM is a preferred structural equation modeling (SEM) method in many research settings and will become even more widely applied when IS researchers are aware of and apply the new analytical tools.
Practical implications
Emerging PLS-SEM methodological developments will help IS researchers examine new theoretical concepts and relationships and publish their work. Researchers are encouraged to engage in more complete analyses by applying the applicable emerging tools.
Originality/value
Applications of PLS-SEM for prediction, theory testing and confirmation have increased in recent years. Information system scholars should continue to exercise sound practice by applying these new analytical tools where applicable. Recommended guidelines following Hair et al. (2019; 2022) are included.
Keywords
Acknowledgements
We would like to thank Prof. Hing Kai Chan, the editor of this manuscript, and two anonymous reviewers for their constructive comments to improve the manuscript.
Citation
Cepeda, G., Roldán, J.L., Sabol, M., Hair, J. and Chong, A.Y.L. (2024), "Emerging opportunities for information systems researchers to expand their PLS-SEM analytical toolbox", Industrial Management & Data Systems, Vol. 124 No. 6, pp. 2230-2250. https://doi.org/10.1108/IMDS-08-2023-0580
Publisher
:Emerald Publishing Limited
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