The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Estimating Trait, Method, and Error Variance: Generalizing across 70 Construct Validation Studies
Open accessAbstract
The authors examine the construct validation results of 70 published data sets. The analysis shows that, on average, traits account for less than 50% of the variance in construct measures. These findings raise questions about the application of statistical techniques that assume minimal measurement error or do not properly model systematic measurement error.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
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
Construct Validity: A Review of Basic Issues and Marketing Practices
Peter, J. P. (1981) · Journal of Marketing Research · doi:10.2307/3150948 · Cited by 1,189
Cited by
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
Sources of method bias in social science research and recommendations on how to control it
Podsakoff, P. M., MacKenzie, S. B., & Podsakoff, N. P. (2012) · Annual Review of Psychology · doi:10.1146/annurev-psych-120710-100452 · Cited by 15,744
Podsakoff, P. M., MacKenzie, S. B., Paine, J. B., & Bachrach, D. G. (2000) · Journal of Management · doi:10.1177/014920630002600307 · Cited by 5,897
Common methods variance detection in business research
Fuller, C. M., Simmering, M. J., Atinc, G., Atinc, Y., & Babin, B. J. (2016) · Journal of Business Research · doi:10.1016/j.jbusres.2015.12.008 · Cited by 3,519
Common Method Bias in Marketing: Causes, Mechanisms, and Procedural Remedies
MacKenzie, S. B., & Podsakoff, P. M. (2012) · Journal of Retailing · doi:10.1016/j.jretai.2012.08.001 · Cited by 3,051
Common method bias in regression models with linear, quadratic, and interaction effects.
Siemsen, E., Roth, A., & Oliveira, P. (2010) · Organizational Research Methods · doi:10.1177/1094428109351241 · Cited by 2,706
Common method bias: It’ s bad, it’ s complex, it’ s widespread, and it’ s not easy to fix
Podsakoff, P. M., Podsakoff, N. P., Williams, L. J., Huang, C., & Yang, J. (2024) · Annual Review of Organizational Psychology and Organizational Behavior · doi:10.1146/annurev-orgpsych-110721-040030 · Cited by 1,899
The use of lisrel in validating marketing constructs
Steenkamp, J.-B. E. M., & van Trijp, H. C. M. (1991) · International Journal of Research in Marketing · doi:10.1016/0167-8116(91)90027-5 · Cited by 1,848
Richardson, H. A., Simmering, M. J., & Sturman, M. C. (2009) · Organizational Research Methods · doi:10.1177/1094428109332834 · Cited by 1,721
Lack of method variance in self-reported affect and perceptions at work: reality or artifact?
Williams, L. J., Cote, J. A., & Buckley, M. R. (1989) · Journal of Applied Psychology · doi:10.1037/0021-9010.74.3.462 · Cited by 1,616
Self-citationCommon methods bias: does common methods variance really bias results?
Doty, D. H., & Glick, W. H. (1998) · Organizational Research Methods · doi:10.1177/109442819814002 · Cited by 1,380
Cross-Sectional versus longitudinal survey research: concepts, findings, and guidelines
Rindfleisch, A., Malter, A. J., Ganesan, S., & Moorman, C. (2008) · Journal of Marketing Research · doi:10.1509/jmkr.45.3.261 · Cited by 1,305
Grewal, R., Cote, J. A., & Baumgartner, H. (2004) · Marketing Science · doi:10.1287/mksc.1040.0070 · Cited by 1,228
Self-citationFIT, EQUIFINALITY, AND ORGANIZATIONAL EFFECTIVENESS: A TEST OF TWO CONFIGURATIONAL THEORIES.
DOTY, D. H., GLICK, W. H., & HUBER, G. P. (1993) · Academy of Management Journal · doi:10.5465/256810 · Cited by 1,198
Hulland, J., Baumgartner, H., & Smith, K. M. (2018) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-017-0532-y · Cited by 1,067
A meta-analysis of the convergent validity of self-control measures
Duckworth, A. L., & Kern, M. L. (2011) · Journal of Research in Personality · doi:10.1016/j.jrp.2011.02.004 · Cited by 1,031
MacKenzie, S. B., Podsakoff, P. M., & Fetter, R. (1991) · Organizational Behavior and Human Decision Processes · doi:10.1016/0749-5978(91)90037-t · Cited by 807
Simmering, M. J., Fuller, C. M., Richardson, H. A., Ocal, Y., & Atinc, G. M. (2015) · Organizational Research Methods · doi:10.1177/1094428114560023 · Cited by 734
Assessing Common Method Bias: Problems with the ULMC Technique1
Chin, W. W., Thatcher, J. B., & Wright, R. T. (2012) · MIS Quarterly · doi:10.2307/41703491 · Cited by 505
Sharma, R., Yetton, P., & Crawford, J. (2009) · MIS Quarterly · doi:10.2307/20650305 · Cited by 496
Analysis of role conflict and role ambiguity in a structural equations framework.
Netemeyer, R. G., Johnston, M. W., & Burton, S. (1990) · Journal of Applied Psychology · doi:10.1037/0021-9010.75.2.148 · Cited by 492
The Safety of Objects: Materialism, Existential Insecurity, and Brand Connection
Rindfleisch, A., Burroughs, J. E., & Wong, N. (2009) · Journal of Consumer Research · doi:10.1086/595718 · Cited by 441
How (Not) to Solve the Problem: An Evaluation of Scholarly Responses to Common Source Bias
Favero, N., & Bullock, J. B. (2015) · Journal of Public Administration Research and Theory · doi:10.1093/jopart/muu020 · Cited by 372
(2009) · Cited by 355
Kim, D. (2006) · Journal of the Academy of Marketing Science · doi:10.1177/0092070305281619 · Cited by 342
Marketing research using single-item indicators in structural equation models
Petrescu, M. (2013) · Journal of Marketing Analytics · doi:10.1057/jma.2013.7 · Cited by 279
What Drives Key Informant Accuracy?
Homburg, C., Klarmann, M., Reimann, M., & Schilke, O. (2012) · Journal of Marketing Research · doi:10.1509/jmr.09.0174 · Cited by 276
Hall, J., & Wagner, M. (2012) · Business Strategy and the Environment · doi:10.1002/bse.728 · Cited by 227
Examining the Impact of Servant Leadership on Sales Force Performance
Jaramillo, F., Grisaffe, D. B., Chonko, L. B., & Roberts, J. A. (2009) · Journal of Personal Selling & Sales Management · doi:10.2753/pss0885-3134290304 · Cited by 219
Measurement Errors in the Behavioral Sciences: The Case of Personality/Attitude Research
Buckley, M. R., Cote, J. A., & Comstock, S. M. (1990) · Educational and Psychological Measurement · doi:10.1177/0013164490503001 · Cited by 147
Self-citationRodríguez, N. G., Pérez, M. J. S., & Gutiérrez, J. A. T. (2008) · Journal of Business Research · doi:10.1016/j.jbusres.2007.06.011 · Cited by 145
National Culture and Social Desirability Bias in Measuring Public Service Motivation
Kim, S. H., & Kim, S. (2016) · Administration & Society · doi:10.1177/0095399713498749 · Cited by 124
Multitrait–multimethod matrices in consumer research: Critique and new developments
Bagozzi, R. P., & Yi, Y. (1993) · Journal of Consumer Psychology · doi:10.1016/s1057-7408(08)80022-8 · Cited by 61
Chen, J., & Kouhsari, M. (2025) · Computers & Education · doi:10.1016/j.compedu.2024.105232 · Cited by 13
Metadata
- Authors
- Cote, J. A., & Buckley, M. R.
- Venue
- Journal of Marketing Research
- Publisher
- SAGE Publications
- Published
- 1987-08
- Volume
- 24
- Issue
- 3
- Pages
- 315-318
- ISSN
- 0022-2437 (ISSN-L)
- 1547-7193
- OpenAlex
- W2060635400
- Cited by
- 748
- References
- 2
- FWCI
- 3.56
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
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.
