The DOI matches its Crossref record; 53 of the 53 references it cites were found in a registry or an index.
A central question in cross-cultural research: Do employees of different cultures interpret work-related measures in an equivalent manner?
Abstract
Within the present research, a covariance structure analytic procedure is applied to test the stability and transferability of organizational measures between groups in cross-cultural research. Findings support the need to establish the equivalency of constructs and measures prior to interpreting differences in means of self-report variables between culturally diverse groups. Indeed, for two measures, the cultural groups were using different conceptual frames of reference when responding to the items. For a third measure, the groups were calibrating the true scores differently. However, the source of the calibration difference was identified and subsequently accounted for in later analyses. Thus, differences between latent means for the culturally diverse groups were calculated and interpreted. The approach outlined in this paper is proffered as yielding valuable insights regarding the appropriateness of comparative cross-cultural studies.
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Cited by
Evaluating Goodness-of-Fit Indexes for Testing Measurement Invariance
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Power and sensitivity of alternative fit indices in tests of measurement invariance.
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Chen, F. F. (2008) · Journal of Personality and Social Psychology · doi:10.1037/a0013193 · Cited by 962
Metadata
- Authors
- Riordan, C.
- Venue
- Journal of Management
- Publisher
- SAGE Publications
- Published
- 1994
- Volume
- 20
- Issue
- 3
- Pages
- 643-671
- ISSN
- 0149-2063 (ISSN-L)
- OpenAlex
- W2104507550
- Cited by
- 373
- References
- 53
- FWCI
- 5.86
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
