The DOI matches its Crossref record; 160 of the 160 references it cites were found in a registry or an index.
Construct Development and Validation in Three Practical Steps: Recommendations for Reviewers, Editors, and Authors
Abstract
We review contemporary best practice for developing and validating measures of constructs in the organizational sciences. The three basic steps in scale development are: (a) construct definition, (b) choosing operationalizations that match the construct definition, and (c) obtaining empirical evidence to confirm construct validity. While summarizing this 3-step process [i.e., Define-Operationalize-Confirm], we address many issues in establishing construct validity and provide a checklist for journal reviewers and authors when evaluating the validity of measures used in organizational research. Among other points, we pay special attention to construct conceptualization, acknowledging existing constructs, improving existing measures, multidimensional constructs, macro-level constructs, and the need for independent samples to confirm construct validity and measurement equivalence across subpopulations.
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Cites
Hu, L., & Bentler, P. M. (1999) · Structural Equation Modeling A Multidisciplinary Journal · doi:10.1080/10705519909540118 · Cited by 108,788
Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003) · Journal of Applied Psychology · doi:10.1037/0021-9010.88.5.879 · Cited by 82,194
Structural equation modeling in practice: A review and recommended two-step approach
Anderson, J. C., & Gerbing, D. W. (1988) · Psychological Bulletin · doi:10.1037/0033-2909.103.3.411 · Cited by 41,941
Convergent and discriminant validation by the multitrait-multimethod matrix.
Campbell, D. T., & Fiske, D. W. (1959) · Psychological Bulletin · doi:10.1037/h0046016 · Cited by 17,116
Confirmatory factor analysis for applied research
(2007) · Choice Reviews Online · doi:10.5860/choice.44-2769 · Cited by 15,614
(1991) · Cited by 15,554
Structural equation models with unobservable variables and measurement error: Algebra and statistics
Fornell, C., & Larcker, D. F. (1981) · Journal of Marketing Research · doi:10.1177/002224378101800313 · Cited by 13,287
(2002) · Cited by 13,211
Construct validity in psychological tests.
Cronbach, L. J., & Meehl, P. E. (1955) · Psychological Bulletin · doi:10.1037/h0040957 · Cited by 11,195 · cited 2×
“We take the position that the phenomenon underlying the construct is real, even if our de fi nition and understanding of it are fl awed (Cronbach & Meehl, 1955; Messick, 1981).”
BackgroundResearch in Organizational Behavior
Hammer, E. R., Cummings, L. L., & Staw, B. M. (1984) · The Academy of Management Review · doi:10.2307/258300 · Cited by 10,806
Cited by
Cheung, G. W., Cooper-Thomas, H. D., Lau, R. S., & Wang, L. C. (2024) · Asia Pacific Journal of Management · doi:10.1007/s10490-023-09871-y · Cited by 2,262
“For best-practice recommendations for scale development research, readers are referred to Cortina et al. (2020), Hinkin (1998), and Lambert and Newman (2022).”
Attitudes towards artificial intelligence at work: Scale development and validation
Park, J., Woo, S. E., & Kim, J. (2024) · Journal of Occupational and Organizational Psychology · doi:10.1111/joop.12502 · Cited by 150
Metadata
- Authors
- Lambert, L. S., & Newman, D. A.
- Venue
- Organizational Research Methods
- Publisher
- SAGE Publications
- Published
- 2022-08-15
- Volume
- 26
- Issue
- 4
- Pages
- 574-607
- ISSN
- 1094-4281 (ISSN-L)
- 1552-7425
- OpenAlex
- W4291824852
- Cited by
- 259
- References
- 160
- FWCI
- 23.99
- Type
- journal article
- Language
- en
- Open access
- closed
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