The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Recent Advances in Causal Modeling Methods for Organizational and Management Research
Abstract
The purpose of this article is to review recent advanced applications of causal modeling methods in organizational and management research. Developments over the past 10 years involving research on measurement and structural components of causal models will be discussed. Specific topics to be addressed include reflective vs. formative measurement, multidimensional construct assessment, method variance, measurement invariance, latent growth modeling (LGM), moderated structural relationships, and analysis of latent variable means. For each of the areas mentioned above an overview of developments will be presented, and examples from organizational and management research will be provided.
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
Comparative fit indexes in structural models.
Bentler, P. M. (1990) · Psychological Bulletin · doi:10.1037/0033-2909.107.2.238 · Cited by 25,266
THE BIG FIVE PERSONALITY DIMENSIONS AND JOB PERFORMANCE: A META‐ANALYSIS
BARRICK, M. R., & MOUNT, M. K. (1991) · Personnel Psychology · doi:10.1111/j.1744-6570.1991.tb00688.x · Cited by 8,689
Conventional wisdom on measurement: A structural equation perspective.
Bollen, K., & Lennox, R. (1991) · Psychological Bulletin · doi:10.1037/0033-2909.110.2.305 · Cited by 3,618
Common 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
Multidimensional constructs in organizational behavior research: an integrative analytical framework
Edwards, J. R. (2001) · Organizational Research Methods · doi:10.1177/109442810142004 · Cited by 1,128
Self-citationTesting Interaction Effects in LISREL: Examination and Illustration of Available Procedures
Cortina, J. M., Chen, G., & Dunlap, W. P. (2001) · Organizational Research Methods · doi:10.1177/109442810144002 · Cited by 512
Cited by
Liang, H., Saraf, N., Hu, Q., & Xue, Y. (2007) · MIS Quarterly · doi:10.2307/25148781 · Cited by 3,921
Diamantopoulos, A., & Siguaw, J. A. (2006) · British Journal of Management · doi:10.1111/j.1467-8551.2006.00500.x · Cited by 3,410
MacKenzie, S. B., Podsakoff, P. M., & Podsakoff, N. P. (2011) · MIS Quarterly · doi:10.2307/23044045 · Cited by 3,165
An empirical comparison of the efficacy of covariance-based and variance-based SEM
Reinartz, W., Haenlein, M., & Henseler, J. (2009) · International Journal of Research in Marketing · doi:10.1016/j.ijresmar.2009.08.001 · Cited by 2,906
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
Structural Equation Modeling and Natural Systems
Grace, J. B. (2006) · doi:10.1017/cbo9780511617799 · Cited by 2,432
Richardson, H. A., Simmering, M. J., & Sturman, M. C. (2009) · Organizational Research Methods · doi:10.1177/1094428109332834 · Cited by 1,721
Slade, E. L., Dwivedi, Y. K., Piercy, N. C., & Williams, M. D. (2015) · Psychology & Marketing · doi:10.1002/mar.20823 · Cited by 922
Lai, C.-S., Chiu, C.-J., Yang, C.-F., & Pai, D.-C. (2010) · Journal of Business Ethics · doi:10.1007/s10551-010-0433-1 · Cited by 852
Zhang, K. Z. K., Zhao, S. J., Cheung, C. M. K., & Lee, M. K. O. (2014) · Decision Support Systems · doi:10.1016/j.dss.2014.08.005 · Cited by 781
Defining and Measuring Servant Leadership Behaviour in Organizations
Sendjaya, S., Sarros, J. C., & Santora, J. C. (2008) · Journal of Management Studies · doi:10.1111/j.1467-6486.2007.00761.x · Cited by 844
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
“Working out for likes”: An empirical study on social influence in exercise gamification
Hamari, J., & Koivisto, J. (2015) · Computers in Human Behavior · doi:10.1016/j.chb.2015.04.018 · Cited by 473
Technostress creators and job outcomes: theorising the moderating influence of personality traits
Srivastava, S. C., Chandra, S., & Shirish, A. (2015) · Information Systems Journal · doi:10.1111/isj.12067 · Cited by 456
(2009) · Cited by 355
Gielnik, M. M., Frese, M., Kahara-Kawuki, A., Wasswa Katono, I., Kyejjusa, S., Ngoma, M., Munene, J., Namatovu-Dawa, R., Nansubuga, F., Orobia, L., et al. (2015) · Academy of Management Learning & Education · doi:10.5465/amle.2012.0107 · Cited by 305
Shao, Z., & Yin, H. (2019) · Internet Research · doi:10.1108/intr-02-2018-0086 · Cited by 94
Members' site use continuance on Facebook: Examining the role of relational capital
Chen, R., Sharma, S. K., & Raghav Rao, H. (2016) · Decision Support Systems · doi:10.1016/j.dss.2016.07.001 · Cited by 63
Purchase Intentions in a Chatbot Environment: An Examination of the Effects of Customer Experience
Martínez Puertas, S., Illescas Manzano, M. D., Segovia López, C., & Ribeiro-Cardoso, P. (2024) · Oeconomia Copernicana · doi:10.24136/oc.2914 · Cited by 34
Users as knowledge co-producers in the information system development project
Hsu, J. S.-C., Lin, T.-C., Zheng, G.-T., & Hung, Y.-W. (2012) · International Journal of Project Management · doi:10.1016/j.ijproman.2011.05.008 · Cited by 34
Metadata
- Authors
- Williams, L.
- Venue
- Journal of Management
- Publisher
- SAGE Publications
- Published
- 2003-12
- Volume
- 29
- Issue
- 6
- Pages
- 903-936
- ISSN
- 0149-2063 (ISSN-L)
- OpenAlex
- W2120839367
- Cited by
- 490
- References
- 6
- FWCI
- 8.69
- Type
- journal article
- Language
- en
- Open access
- closed
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.
