The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Prediction-oriented modeling in business research by means of PLS path modeling: Introduction to a JBR special section
Open accessAbstract
Under the main theme “prediction-oriented modeling in business research by means of partial least squares path modeling” (PLS), the special issue presents 17 papers. Most contributions include content from presentations at the 2nd International Symposium on Partial Least Squares Path Modeling: The Conference for PLS Users, which took place at the Universidad de Sevilla (Spain) from June 16 to 19, 2015. This conference provided PLS users with a platform for the fruitful exchange of ideas on variance-based structural equation modeling . At the same time, the conference addressed the latest methodological advances and their use in research practice. Finally, the conference resumed and enriched the ongoing discussion on the strengths and weaknesses of PLS. Researchers often emphasize that predictive capabilities is a strength of the PLS method . Nevertheless, methodological advances and applications in this direction are rare. The scientific committee therefore selected high-quality papers that mainly advance PLS and prediction. The special issue editors believe that these special issues will become the starting point for a more intensive use of predictive modeling in the social sciences discipline and for additional advances that will exploit PLS' capabilities in this area.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
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
Self-citationAn 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
Self-citationUsing pls path modeling in new technology research: updated guidelines
Henseler, J., Hubona, G., & Ray, P. A. (2016) · Industrial Management & Data Systems · doi:10.1108/imds-09-2015-0382 · Cited by 7,173
Self-citationModern Methods for Business Research
(1998) · doi:10.4324/9781410604385 · Cited by 6,534
Building Better Causal Theories: A Fuzzy Set Approach to Typologies in Organization Research
Fiss, P. C. (2011) · Academy of Management Journal · doi:10.5465/amj.2011.60263120 · Cited by 5,930
Common Beliefs and Reality About PLS: Comments on Rönkkö and Evermann (2013)
Henseler, J., Dijkstra, T. K., Sarstedt, M., Ringle, C. M., Diamantopoulos, A., Straub, D. W., Ketchen, D. J., Hair, J. F., Hult, G. T. M., & Calantone, R. J. (2014) · Organizational Research Methods · doi:10.1177/1094428114526928 · Cited by 3,332
Self-citationConfigurational Comparative Methods: Qualitative Comparative Analysis (QCA) and Related Techniques
Rihoux, B., & Ragin, C. (2009) · SAGE Publications · doi:10.4135/9781452226569 · Cited by 3,089
Ringle, C. M., Sarstedt, M., & Straub, D. W. (2012) · MIS Quarterly · doi:10.2307/41410402 · Cited by 2,184
Self-citationPeng, D. X., & Lai, F. (2012) · Journal of Operations Management · doi:10.1016/j.jom.2012.06.002 · Cited by 1,532
Sarstedt, M., Henseler, J., & Ringle, C. M. (2011) · Advances in International Marketing · doi:10.1108/s1474-7979(2011)0000022012 · Cited by 1,326
Self-citation
Cited by
Predictive model assessment in PLS-SEM: guidelines for using PLSpredict
Shmueli, G., Sarstedt, M., Hair, J. F., Cheah, J.-H., Ting, H., Vaithilingam, S., & Ringle, C. M. (2019) · European Journal of Marketing · doi:10.1108/ejm-02-2019-0189 · Cited by 4,618
Self-citationPartial least squares structural equation modeling in HRM research
Ringle, C. M., Sarstedt, M., Mitchell, R., & Gudergan, S. P. (2020) · The International Journal of Human Resource Management · doi:10.1080/09585192.2017.1416655 · Cited by 1,943
Self-citationBenitez, J., Henseler, J., Castillo, A., & Schuberth, F. (2020) · Information & Management · doi:10.1016/j.im.2019.05.003 · Cited by 1,788
Self-citationStructural model robustness checks in PLS-SEM
Sarstedt, M., Ringle, C. M., Cheah, J.-H., Ting, H., Moisescu, O. I., & Radomir, L. (2020) · Tourism Economics · doi:10.1177/1354816618823921 · Cited by 1,271
Self-citationBootstrapping and PLS-SEM: A step-by-step guide to get more out of your bootstrap results
Streukens, S., & Leroi-Werelds, S. (2016) · European Management Journal · doi:10.1016/j.emj.2016.06.003 · Cited by 1,120
Metadata
- Authors
- Cepeda Carrión, G., Henseler, J., Ringle, C. M., & Roldán, J. L.
- Venue
- Journal of Business Research
- Publisher
- Elsevier BV
- Published
- 2016-10
- Volume
- 69
- Issue
- 10
- Pages
- 4545-4551
- ISSN
- 0148-2963 (ISSN-L)
- OpenAlex
- W2346157870
- Cited by
- 274
- References
- 11
- FWCI
- 29.56
- Type
- journal article
- Language
- en
- Open access
- hybrid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Prediction-oriented modeling in business research by means of PLS path modeling: Introduction to a JBR special section. https://app.cochat.ai/papers/10.1016/j.jbusres.2016.03.048
- The paper
- Cepeda Carrión, G., Henseler, J., Ringle, C. M., & Roldán, J. L. (2016). Prediction-oriented modeling in business research by means of PLS path modeling: Introduction to a JBR special section. Journal of Business Research. https://doi.org/10.1016/j.jbusres.2016.03.048
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
