The DOI matches its Crossref record; 103 of the 103 references it cites were found in a registry or an index.
Why PLS-SEM is suitable for complex modelling? An empirical illustration in big data analytics quality
Open accessAbstract
The emergence of multivariate analysis techniques transforms empirical validation of theoretical concepts in social science and business research. In this context, structural equation modelling (SEM) has emerged as a powerful tool to estimate conceptual models linking two or more latent constructs. This paper shows the suitability of the partial least squares (PLS) approach to SEM (PLS-SEM) in estimating a complex model drawing on the philosophy of verisimilitude and the methodology of soft modelling assumptions. The results confirm the utility of PLS-SEM as a promising tool to estimate a complex, hierarchical model in the domain of big data analytics quality.
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Cites
Evaluating structural equation models with unobservable variables and measurement error
Fornell, C., & Larcker, D. F. (1981) · Journal of Marketing Research · doi:10.1177/002224378101800104 · Cited by 109,190
Baron, R. M., & Kenny, D. A. (1986) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.51.6.1173 · Cited by 91,532
An Introduction to the Bootstrap
Efron, B., & Tibshirani, R. J. (1994) · doi:10.1201/9780429246593 · Cited by 40,500
A new criterion for assessing discriminant validity in variance-based structural equation modeling
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-014-0403-8 · Cited by 38,459
Pls-Sem: indeed a silver bullet
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011) · Journal of Marketing Theory and Practice · doi:10.2753/mtp1069-6679190202 · Cited by 21,631
An Introduction to the Bootstrap
Efron, B., & Tibshirani, R. J. (1993) · doi:10.1007/978-1-4899-4541-9 · Cited by 21,230
(2014) · DigitalCommons - Kennesaw State University (Kennesaw State University) · Cited by 12,785
(1993) · Journal of the American Dietetic Association · doi:10.1016/0002-8223(93)92196-5 · Cited by 11,976
The use of partial least squares path modeling in international marketing
Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009) · Advances in International Marketing · doi:10.1108/s1474-7979(2009)0000020014 · Cited by 10,926
An assessment of the use of partial least squares structural equation modeling in marketing research
Hair, J. F., Sarstedt, M., Ringle, C. M., & Mena, J. A. (2012) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-011-0261-6 · Cited by 8,088
Research works printed but not linked: 27
- 10.1002/asi.v62.1 · doi:10.1002/asi.v62.1
- Barclay Donald, 1995, Technology Studies, 2, 285
- Barton D., 2012, Harvard Business Review, 90, 78
- 10.1080/09537287.2011.642486 · doi:10.1080/09537287.2011.642486
- Chin Wynne W., 1998, Management Information Systems Quarterly
- 10.1145/217278 · doi:10.1145/217278
- Davenport Thomas H., 2012, MIT Sloan Management Review, 54, 43
- 10.1007/978-3-540-32827-8 · DOI · Paper page
- 10.1007/978-3-540-32827-8 · DOI · Paper page
- 10.1002/asmb.v24:5 · DOI
- 10.2307/3151312 · DOI · Paper page
- 10.2307/3151566 · doi:10.2307/3151566 · Paper page
- 10.1007/978-3-540-32827-8 · DOI · Paper page
- 10.1086/jcr.2003.30.issue-2 · doi:10.1086/jcr.2003.30.issue-2
- Kiron David, 2014, MIT Sloan Management Review, 55, 1
- Lavalle S., 2011, MIT Sloan Management Review, 52, 21
- McAfee A., 2012, Harvard Business Review, 90, 60
- McAfee Andrew, 2012, Harvard Business Review, 90, 60
- Pyke Steve, 2011, Philosophers
- Ransbotham Sam, 2016, MIT Sloan Management Review, 57, 1
- Ray Gautam, 2005, MIS Quarterly, 625
- Ringle Christian, 2012, MIS Quarterly (MISQ), 36, iii, 10.2307/41410402 · DOI · Paper page
- 10.1108/aim · doi:10.1108/aim
- 10.2307/3151679 · DOI
- Stafford T. F., 2011, Management Information Systems Quarterly, 35, xv, 10.2307/23044043 · doi:10.2307/23044043
- Wold Herman, 1975, Perspectives in Probability and Statistics, in Honor of MS Bartlett, 117
- 10.1007/978-1-4613-8171-6 · doi:10.1007/978-1-4613-8171-6
Cited by
When to Use and How to Report the Results of PLS-SEM
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019) · European Business Review · doi:10.1108/ebr-11-2018-0203 · Cited by 27,541
Partial least squares structural equation modeling
Sarstedt, M., Ringle, C. M., & Hair, J. F. (2017) · Handbook of Market Research · doi:10.1007/978-3-319-05542-8_15-1 · Cited by 3,285
Partial Least Squares Structural Equation Modeling
Sarstedt, M., Ringle, C. M., & Hair, J. F. (2022) · Handbook of Market Research · doi:10.1007/978-3-319-57413-4_15 · Cited by 1,483
Dubey, R., Gunasekaran, A., Childe, S. J., Fosso Wamba, S., Roubaud, D., & Foropon, C. (2021) · International Journal of Production Research · doi:10.1080/00207543.2019.1582820 · Cited by 958
Partial Least Squares Structural Equation Modeling
Sarstedt, M., Ringle, C. M., & Hair, J. F. (2021) · Handbook of Market Research · doi:10.1007/978-3-319-05542-8_15-2 · Cited by 876
Metadata
- Authors
- Akter, S., Fosso Wamba, S., & Dewan, S.
- Venue
- Production Planning & Control
- Publisher
- Informa UK Limited
- Published
- 2017-07-11
- Volume
- 28
- Issue
- 11-12
- Pages
- 1011-1021
- ISSN
- 0953-7287 (ISSN-L)
- 1366-5871
- OpenAlex
- W2735855334
- Cited by
- 478
- References
- 103
- FWCI
- 13.06
- Type
- journal article
- Language
- en
- Open access
- green
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