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Common Methods Bias: Does Common Methods Variance Really Bias Results?
Abstract
Methods variance and its effects are at the center of a debate in organizational science. Most of the debate, however, is focused on the prevalence of common methods variance and ignores common methods bias, or the divergence between observed and true relationships among constructs. This article assesses the level of common methods bias in all multitrait-multimethod correlation matrices published over a 12-year period in a set of six social science journals using a combination of structural equation modeling and meta-analysis. The results indicate that only 46% of the variation in measures is attributable to the constructs, that 32% of the observed variation in measures is attributable to common methods variance, and that common methods variance results in a 26% bias in the observed relationships among constructs. This level of bias is cause for concern but does not invalidate many research findings.
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“To help mitigate concerns about effects of transient sources of common method bias, we employed a lagged longitudinal design (Study 2; Doty and Glick, 1998;Podsakoff et al., 2003;Spector, 2006).”
From Work hard or play hard: the effect of leisure crafting on opportunity recognition and venture performance (2023) · cites this paper as Doty and Glick, 1998
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“Although this may be considered unlikely due to the differentials amongst the patterns of correlations and factor loadings ( Campbell & Fiske, 1959 ; Doty & Glick, 1998 ), this issue may be overcome in future studies by incorporating multiple ratings by customers, supervisors and management of firms to measure custome…”
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“Bias could be present if (1) a single factor emerges from an exploratory factor analysis, or (2) one factor accounts for the majority of the covariance among the variables (Podsakoff, MacKenzie, Jeong-Yeon, & Podsakoff, 2003; Doty & Glick, 1998).”
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“This method variance and its effects are the focal points of debate in organisational behavioural research (Doty and Glick, 1998; Lindell and Whitney, 2001; Malhotra et al., 2006).”
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“Although there is general consensus that common source bias exists, research indicates it has been overused to criticize studies employing self-reported data (Crampton and Wagner 1994; Doty and Glick 1998; Spector 1987; Spector and Brannick 1995; Spector 2006; Conway and Lance 2010).”
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“Another concern about self-report data is common method variance (CMV) being introduced as an artifact of the data collection technique (Crampton & Wagner, 1994; Doty & Glick, 1998).”
Method
Metadata
- Authors
- Doty, D. H., & Glick, W. H.
- Affiliations
- Syracuse University (US)
- Arizona State University (US)
- ORCID
- Doty, D. Harold
- Venue
- Organizational Research Methods
- Publisher
- SAGE Publications
- Published
- 1998-10
- Volume
- 1
- Issue
- 4
- Pages
- 374-406
- ISSN
- 1094-4281 (ISSN-L)
- 1552-7425
- OpenAlex
- W2168082050
- Cited by
- 1,380
- References
- 84
- Citations by year
- 2026: 37 · 2025: 39 · 2024: 51 · 2023: 52 · 2022: 51 · 2021: 64 · 2020: 62 · 2019: 58 · 2018: 55 · 2017: 67 · 2016: 63 · 2015: 64 · 2014: 95 · 2013: 89 · 2012: 92
- FWCI
- 9.20
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Organizational Research Methods (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Social Sciences › Business, Management and Accounting › Strategy and Management › Business Strategies and Management Research
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Keywords
- measurement bias, construct relationships, measurement error, organizational analysis
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