Second-order PLS structural equation modeling in scientific research
DOI:
https://doi.org/10.23925/2446-9513.2023v10id59733Keywords:
SEM-PLS of Higher Order, Second order, Systematic Review, Integrative Review, Social Network Analysis, Quantitative methodAbstract
This study looked at how structural equation modeling using partial least squares of higher order has been used in various fields of science. We used the integrative type of systematic review method for this. We used the Coordination for the Improvement of Higher Education Personnel database. We searched this database for articles with eight different descriptors published between 2010 and 2020. In total, we used 173 articles as the basis for our analysis in our study. We used coding and graph analysis through social network analysis to analyze the data. The main findings show that social science is the most commonly used area for this method, and that most studies do not detail how they conducted the higher-order structural equation through partial least squares modeling. The study also shows which metrics are commonly used and which could be used more effectively for greater reliability.
References
ALDIERI, L.; KOTSEMIR, M.; VINCI, C. P. The impact of research collaboration on academic performance: An empirical analysis for some European countries. Socio-Economic Planning Sciences, v. 62, p. 13–30, 2018.
ALI, F.; RASOOLIMANESH, S. M.; SARSTEDT, M.; RINGLE, C. M.; RYU, K. An assessment of the use of partial least squares structural equation modeling (PLS-SEM) in hospitality research. International Journal of Contemporary Hospitality Management, v. 30, n. 1, p. 514–538, 2018.
BASTIAN, M.; HEYMANN, S.; JACOMY, M. Gephi: An Open Source Software for Exploring and Manipulating Networks. Icwsm, p. 361–362, 2009.
BOOTH, A.; SUTTON, A.; PAPAIOANNOU, D. Systematic Approaches to a Successful Literature Review. 2. ed. London: SAGE, 2016. v. 34
BOTELHO, L. L. R.; CUNHA, C. C. DE A.; MACEDO, M. O MÉTODO DA REVISÃO INTEGRATIVA NOS ESTUDOS ORGANIZACIONAIS. GESTÃO E SOCIEDADE, v. 5, p. 121–136, 2011.
BRANDES, U. A faster algorithm for betweenness centrality. Journal of mathematical sociology, v. v. 25, n. n. 2, p. 163–177, 2001.
CROCETTA, C.; ANTONUCCI, L.; CATALDO, R.; GALASSO, R.; GRASSIA, M. G.; LAURO, C. N.; MARINO, M. Higher-Order PLS-PM Approach for Different Types of Constructs. Social Indicators Research, v. 154, n. 2, p. 725–754, 2021.
DÖRNER, D.; FUNKE, J. Complex problem solving: What it is and what it is not. Frontiers in Psychology, v. 8, n. JUL, p. 1–11, 2017.
HAIR, J. F.; HOWARD, M. C.; NITZL, C. Assessing measurement model quality in PLS-SEM using confirmatory composite analysis. Journal of Business Research, v. 109, n. August 2019, p. 101–110, 2020.
HAIR, J. F.; RINGLE, C. M.; SARSTEDT, M. PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, v. 19, n. 2, p. 139–152, 2011.
HAIR, J. F.; RISHER, J. J.; SARSTEDT, M.; RINGLE, C. M. When to use and how to report the results of PLS-SEM. European Business Review, v. 31, n. 1, p. 2–24, 2019.
HAIR, J. F.; SARSTEDT, M.; PIEPER, T. M.; RINGLE, C. M. The Use of Partial Least Squares Structural Equation Modeling in Strategic Management Research: A Review of Past Practices and Recommendations for Future Applications. Long Range Planning, v. 45, n. 5–6, p. 320–340, 2012.
HAIR, J. F.; SARSTEDT, M.; RINGLE, C. M. Rethinking some of the rethinking of partial least squares. European Journal of Marketing, v. 53, n. 4, p. 566–584, 2019.
HAIR, J.; HOLLINGSWORTH, C. L.; RANDOLPH, A. B.; CHONG, A. Y. L. An updated and expanded assessment of PLS-SEM in information systems research. Industrial Management and Data Systems, v. 117, n. 3, p. 442–458, 2017.
HE, J.-H. Variational iteration method–a kind of non-linear analytical technique: some examples. International journal of non-linear mechanics, v. 34, n. 4, p. 699–708, 1999.
HENSELER, J.; RINGLE, C. M.; SARSTEDT, M. A new criterion for assessing discriminant validity in variance-based structural equation modeling. J. of the Acad. Mark. Sci., p. 115–135, 2015.
HULST, R. C. VAN DER. Introduction to Social Network Analysis (SNA) as an investigative tool. Trends in Organized Crime, v. 12, n. 2, p. 101–121, 2009.
KANE, S. N.; MISHRA, A.; DUTTA, A. K. Preface: International Conference on Recent Trends in Physics (ICRTP 2016). Journal of Physics: Conference Series, v. 755, n. 1, 2016.
KATZ, J. S.; MARTIN, B. R. What is research collaboration? Research Policy, v. 26, n. 1, p. 1–18, 1997.
KAUFMANN, L.; GAECKLER, J. A structured review of partial least squares in supply chain management research. Journal of Purchasing and Supply Management, v. 21, n. 4, p. 259–272, 2015.
MIKULIĆ, J.; RYAN, C. Reflective versus formative confusion in SEM based tourism research: A critical comment. Tourism Management, v. 68, n. March 2017, p. 465–469, 2018.
PARANYUSHKIN, D. Identifying the pathways for meaning circulation using text network analysis. Berlim: Nodus Labs, 2011.
PARANYUSHKIN, D. InfraNodus: Generating insight using text network analysis. The Web Conference 2019 - Proceedings of the World Wide Web Conference, WWW 2019, p. 3584–3589, 2019.
RANI, P.; BHATIA, M. P. S.; TAYAL, D. K. An Astute SNA with OWA Operator to Compare the Social Networks. International Journal of Information Technology and Computer Science, v. 10, n. 3, p. 71–80, 2018.
SARSTEDT, M.; HAIR, J. F.; CHEAH, J.; BECKER, J.; RINGLE, C. M. How to specify, estimate, and validate higher-order constructs in PLS-SEM. Australasian Marketing Journal (AMJ, v. 27, p. 197–211, 2019.
SIQUEIRA, T. G. D. S. Possibilidades de pesquisa no Portal de Periódicos CAPES, 2020.
STREUKENS, S.; LEROI-WERELDS, S. Bootstrapping and PLS-SEM: A step-by-step guide to get more out of your bootstrap results. European Management Journal, v. 34, n. 6, p. 618–632, 2016.
SUONIEMI, S.; TERHO, H.; OLKKONEN, R. The Measurement of Endogenous Higher-Order Formative Composite Variables in PLS-SEM: An Empirical Application from CRM System Development. International Journal of Computer, Electrical, Automation, Control and Information Engineering, v. 6, n. 12, p. 1648–1652, 2012.
UL HADIA, N.; ABDULLAH, N.; SENTOSA, I. An Easy Approach to Exploratory Factor Analysis: Marketing Perspective. Journal of Educational and Social Research, v. 6, n. 1, p. 215–223, 2016.
WICKHAM, M.; DUNN, A.; SWEENEY, S. Analysis of the leading tourism journals 1999-2008. Annals of Tourism Research, v. 39, n. 3, p. 1714–1718, 2012.
WILLIAMS, E.; BREWE, E.; ZWOLAK, J.; DOU, R. Understanding centrality: Investigating student outcomes within a classroom social network. Proceedings of the Physics Education Research Conference., p. 375–378, 2015.
WOLD, H. Model Construction and Evaluation When Theoretical Knowledge Is Scarce. Evaluation of Econometric Models, p. 47–74, 1980.
Published
How to Cite
Issue
Section
License
Copyright (c) 2023 Abimael Ouro, Eucymara Santos, Esdras Santos, Ikaro Barreto, Maria Olave
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
