The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Formative versus reflective measurement models: Two applications of formative measurement
Open accessAbstract
This paper presents a framework that helps researchers to design and validate both formative and reflective measurement models. The framework draws from the existing literature and includes both theoretical and empirical considerations. Two important examples, one from international business and one from marketing, illustrate the use of the framework. Both examples concern constructs that are fundamental to theory-building in these disciplines, and constructs that most scholars measure reflectively. In contrast, applying the framework suggests that a formative measurement model may be more appropriate. These results reinforce the need for all researchers to justify, both theoretically and empirically, their choice of measurement model. Use of an incorrect measurement model undermines the content validity of constructs, misrepresents the structural relationships between them, and ultimately lowers the usefulness of management theories for business researchers and practitioners. The main contribution of this paper is to question the unthinking assumption of reflective measurement seen in much of the business literature.
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Cites
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Cronbach, L. J. (1951) · Psychometrika · doi:10.1007/bf02310555 · Cited by 43,931
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Anderson, J. C., & Gerbing, D. W. (1988) · Psychological Bulletin · doi:10.1037/0033-2909.103.3.411 · Cited by 41,941
A Paradigm for Developing Better Measures of Marketing Constructs
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Cited by
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
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
The Measurement of Entrepreneurial Orientation
Covin, J. G., & Wales, W. J. (2012) · Entrepreneurship Theory and Practice · doi:10.1111/j.1540-6520.2010.00432.x · Cited by 1,110
Deconstructing the construct: a network perspective on psychological phenomena
Schmittmann, V. D., Cramer, A. O. J., Waldorp, L. J., Epskamp, S., Kievit, R. A., & Borsboom, D. (2013) · New Ideas in Psychology · doi:10.1016/j.newideapsych.2011.02.007 · Cited by 740
Kuleto, V., Ilić, M., Dumangiu, M., Ranković, M., Martins, O. M. D., Păun, D., & Mihoreanu, L. (2021) · Sustainability · doi:10.3390/su131810424 · Cited by 561
Metadata
- Authors
- Coltman, T., Devinney, T. M., Midgley, D. F., & Venaik, S.
- Venue
- Journal of Business Research
- Publisher
- Elsevier BV
- Published
- 2008-12
- Volume
- 61
- Issue
- 12
- Pages
- 1250-1262
- ISSN
- 0148-2963 (ISSN-L)
- OpenAlex
- W2088530342
- Cited by
- 1,332
- References
- 7
- FWCI
- 48.69
- Type
- journal article
- Language
- en
- Open access
- green
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- Coltman, T., Devinney, T. M., Midgley, D. F., & Venaik, S. (2008). Formative versus reflective measurement models: Two applications of formative measurement. Journal of Business Research. https://doi.org/10.1016/j.jbusres.2008.01.013
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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.
