Hostname: page-component-848d4c4894-x5gtn Total loading time: 0 Render date: 2024-05-31T11:02:57.931Z Has data issue: false hasContentIssue false
  • English
  • Français

The role of work psychologists in the development of antiwork sentiments

Published online by Cambridge University Press:  07 March 2024

Goran Kuljanin Open the ORCID record for Goran Kuljanin [Opens in a new window]  and
Grace Lemmon Open the ORCID record for Grace Lemmon [Opens in a new window]
Goran Kuljanin*
Affiliation:
Department of Management and Entrepreneurship, DePaul University, Chicago, IL, USA
Grace Lemmon
Affiliation:
Department of Management and Entrepreneurship, DePaul University, Chicago, IL, USA
*
Corresponding author: Goran Kuljanin; Email: g.kuljanin@depaul.edu
Get access Rights & Permissions [Opens in a new window]

Abstract

An abstract is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content.
Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
Type
Commentaries
Information
Industrial and Organizational Psychology , Volume 17 , Issue 1 , March 2024 , pp. 45 - 49
Copyright
© The Author(s), 2024. Published by Cambridge University Press on behalf of Society for Industrial and Organizational Psychology

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Alliger, G. M., & McEachern, P. J. (2024). Antiwork offers many opportunities for I-O psychologists. Industrial and Organizational Psychology, 17(1), 1–30.Google Scholar
Braun, M. T., Kuljanin, G., Grand, J. A., Kozlowski, S. W. J., & Chao, G. T. (2022). The power of process theories to better understand and detect consequences of organizational interventions. Industrial and Organizational Psychology, 15(1), 99–104. https://doi.org/10.1017/iop.2021.125.CrossRefGoogle Scholar
Butts, C. T., Lomi, A., Snijders, T. A. B., & Stadtfeld, C. (2023). Relational event models in network science. Network Science, 11 (2), 175–183. https://doi.org/10.1017/nws.2023.9.CrossRefGoogle Scholar
Kozlowski, S. W. J., Chao, G. T., Grand, J. A., Braun, M. T., & Kuljanin, G. (2016). Capturing the multilevel dynamics of emergence: Computational modeling, simulation, and virtual experimentation. Organizational Psychology Review, 6(1), 3–33. https://doi.org/10.1177/2041386614547955.CrossRefGoogle Scholar
Macy, M. W., & Willer, R. (2002). From factors to actors: Computational sociology and agent-based modeling. Annual Review of Sociology, 28(1), 143–166. https://doi.org/10.1146/annurev.soc.28.110601.141117.Google Scholar
Mohr, L. B. (1982). Explaining organizational behavior: The limits and possibilities of theory and research. Proquest Info & Learning.Google Scholar
Pentland, B. T. (1999). Building process theory with narrative: From description to explanation. Academy of Management Review, 24(4), 711–724.Google Scholar
Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55(1), 68–78.Google Scholar
Schneider, B. (1987). The people make the place. Personnel Psychology, 40(3), 437–453. https://doi.org/10.1111/j.1744-6570.1987.tb00609.x.Google Scholar
Thiel, C., Bonner, J. M., Bush, J., Welsh, D., & Garud, N. (2022). Monitoring employees makes them more likely to break rules. Harvard Business Review. https://hbr.org/2022/06/monitoring-employees-makes-them-more-likely-to-break-rules Google Scholar