The DOI matches its Crossref record; 106 of the 106 references it cites were found in a registry or an index.
Using partial least squares structural equation modeling in hospitality and tourism: Do researchers follow practical guidelines?
Abstract
Purpose: The purpose of this study is to review the use of partial least squares-structural equation modeling (PLS-SEM) in the field of hospitality and tourism and thereby to assess whether the PLS-SEM-based papers followed the recommended application guidelines and to investigate whether a comparison of journal types (hospitality vs tourism) and journal qualities (top-tier vs other leading) reveal significant differences in PLS-SEM use. Design/methodology/approach: A total of 206 PLS-SEM based papers published between 2000 and April 2017 in the 19 SSCI-indexed hospitality and tourism journals were critically analyzed using a wide range of guidelines for the following aspects of PLS-SEM: the rationale of using the method, the data characteristics, the model characteristics, the model assessment and reporting the technical issues. Findings: The results reveal that some aspects of PLS-SEM are correctly applied by researchers, but there are still some misapplications, especially regarding data characteristics, formative measurement model evaluation and structural model assessment. Furthermore, few significant differences were found on the use of PLS-SEM between the two fields (hospitality and tourism) and between the journal tiers (top-tier and other leading). Practical implications: To enhance the quality of research in hospitality and tourism, the present study provides recommendations for improving the future use of PLS-SEM. Originality/value: The present study fills a sizeable gap in hospitality and tourism literature and extends the previous assessments on the use of PLS-SEM by providing a wider perspective on the issue (i.e. includes both hospitality and tourism journals rather than the previous reviews that focus on either tourism or hospitality), using a larger sample size of 206 empirical studies, investigating the issue over a longer time period (from 2000 to April, 2017, including the in-press articles), extending the scope of criteria (guidelines) used in the review and comparing the PLS-SEM use between the two allied fields (hospitality and tourism) and between the journal tiers (top-tier and other leading).
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Cites
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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
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Structural 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
PLS-SEM’s most wanted guidance
Becker, J.-M., Cheah, J.-H., Gholamzade, R., Ringle, C. M., & Sarstedt, M. (2023) · International Journal of Contemporary Hospitality Management · doi:10.1108/ijchm-04-2022-0474 · Cited by 1,223
Ashfaq, M., Yun, J., Yu, S., & Loureiro, S. M. C. (2020) · Telematics and Informatics · doi:10.1016/j.tele.2020.101473 · Cited by 987
Metadata
- Authors
- Usakli, A., & Kucukergin, K. G.
- Venue
- International Journal of Contemporary Hospitality Management
- Publisher
- Emerald
- Published
- 2018-10-09
- Volume
- 30
- Issue
- 11
- Pages
- 3462-3512
- ISSN
- 0959-6119 (ISSN-L)
- OpenAlex
- W2896833234
- Cited by
- 323
- References
- 106
- FWCI
- 19.39
- Type
- journal article
- Language
- en
- Open access
- closed
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- Usakli, A., & Kucukergin, K. G. (2018). Using partial least squares structural equation modeling in hospitality and tourism: Do researchers follow practical guidelines? International Journal of Contemporary Hospitality Management. https://doi.org/10.1108/ijchm-11-2017-0753
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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.