The DOI matches its Crossref record; 218 of the 218 references it cites were found in a registry or an index.
When Conscientious Employees Meet Intelligent Machines: An Integrative Approach Inspired by Complementarity Theory and Role Theory
Abstract
Over the past century, conscientiousness has become seen as the preeminent trait for predicting performance. This consensus is due in part to these employees’ ability to work with traditional 20th-century technology. Such pairings balance the systematic nature of conscientious employees with the technology’s need for user input and direction to perform tasks—resulting in a complementary match. However, the 21st century has seen the incorporation of intelligent machines (e.g., artificial intelligence, robots, and algorithms) into employees’ jobs. Unlike traditional technology, these new machines are equipped with the capability to make decisions autonomously. Thus, their nature overlaps with the orderliness subdimension of conscientious employees—resulting in a non-complementary mismatch. This calls into question whether the consensus about conscientious employees’ effectiveness with 20th-century technology applies to 21st-century jobs. Integrating complementarity and role theory, we refine this consensus. Across three studies using distinct samples (an experience sampling study, a field experiment, and an online experiment from working adults in Malaysia, Taiwan, and the United States), each focused on a different type of intelligent machine, we show not only that using intelligent machines has benefits and consequences, but, importantly, that conscientious (i.e., orderly) employees are less likely to benefit from working with them.
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“This will likely pose a threat to the editor’s experience of self-efficacy because AI occupies the proactive role of generating a creative product and the editor occupies the reactive role of aiding with improving its work24,25.”
From Establishing the importance of co-creation and self-efficacy in creative collaboration with artificial intelligence (2024) · cites this paper as [25]
Citations
Cites
Multiple regression: testing and interpreting interactions
(1992) · Choice Reviews Online · doi:10.5860/choice.29-3352 · Cited by 36,647
(1993) · Journal of the American Dietetic Association · doi:10.1016/0002-8223(93)91697-o · Cited by 18,452
Job Demands, Job Decision Latitude, and Mental Strain: Implications for Job Redesign
Karasek, R. A. (1979) · Administrative Science Quarterly · doi:10.2307/2392498 · Cited by 12,597
Research in Organizational Behavior
Hammer, E. R., Cummings, L. L., & Staw, B. M. (1984) · Academy of Management Review · doi:10.2307/258300 · Cited by 11,176
Barredo Arrieta, A., Díaz-Rodríguez, N., Del Ser, J., Bennetot, A., Tabik, S., Barbado, A., Garcia, S., Gil-Lopez, S., Molina, D., Benjamins, R., et al. (2020) · Information Fusion · doi:10.1016/j.inffus.2019.12.012 · Cited by 10,423
Machine learning: Trends, perspectives, and prospects
Jordan, M. I., & Mitchell, T. M. (2015) · Science · doi:10.1126/science.aaa8415 · Cited by 9,955
Organizational Information Requirements, Media Richness and Structural Design
Daft, R. L., & Lengel, R. H. (1986) · Management Science · doi:10.1287/mnsc.32.5.554 · Cited by 9,868
Cohen, J. (1992) · Psychological Bulletin · doi:10.1037//0033-2909.112.1.155 · Cited by 8,771
Personality Structure: Emergence Of The 5-Factor Model
Digman, J. M. (1990) · Annual Review of Psychology · doi:10.1146/annurev.ps.41.020190.002221 · Cited by 6,731
An alternative "description of personality": The Big-Five factor structure.
Goldberg, L. R. (1990) · Journal of Personality and Social Psychology · doi:10.1037//0022-3514.59.6.1216 · Cited by 6,652
Research works printed but not linked: 16
- Agrawal A., 2017, MIT Sloan Management Review, 58, 28
- Bauer J. C., 2000, Journal of Modern Business, 3, 41
- Brislin R. W., 1980, Handbook of cross-cultural psychology, vol. 2: Methodology:, 389
- Brynjolfsson E., 2018, American Economic Association Papers and Proceedings, 108, 43
- Cohen J., 1992, Psychological Bulletin, 112, 155, 10.1037/0033-2909.112.1.155 · DOI · Paper page
- Davenport T. H., 2019, Artificial intelligence: The insights you need from Harvard Business Review.
- Davenport T. H., 2016, Only humans need apply: Winners and losers in the age of smart machines.
- De Cremer D., 2020, Leadership by algorithm: Who leads and who follows in the AI era.
- Diekmann J., 2015, Employee recruitment, selection, and assessment: Contemporary issues for theory and practice, 117
- 10.5465/3069307 · DOI · Paper page
- Goldberg L. R., 1990, Journal of Personality and Social Psychology, 59, 1216, 10.1037/0022-3514.59.6.1216 · DOI · Paper page
- Langer E. J., 1976, Journal of Personality and Social Psychology, 34, 191, 10.1037/0022-3514.34.2.191 · DOI
- Lee M. K., 2015, CHI ’15: Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, 1603
- Muthén L., 2015, Mplus user’s guide.
- Parsons T., 1951, The social system.
- Wilson H. J., 2018, Harvard Business Review, 96, 114
Cited by
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Yam, K. C., Tang, P. M., Jackson, J. C., Su, R., & Gray, K. J. (2022) · Journal of Applied Psychology · doi:10.1037/apl0001045 · Cited by 368
Can AI really help? The double-edged sword effect of AI assistant on employees’ innovation behavior
Yin, M., Jiang, S., & Niu, X. (2023) · Computers in Human Behavior · doi:10.1016/j.chb.2023.107987 · Cited by 314
He, C., Teng, R., & Song, J. (2023) · International Journal of Contemporary Hospitality Management · doi:10.1108/ijchm-07-2022-0848 · Cited by 250
Recognizing and utilizing novel research opportunities with artificial intelligence
von Krogh, G., Roberson, Q., & Gruber, M. (2023) · Academy of Management Journal · doi:10.5465/amj.2023.4002 · Cited by 164
Managing with Artificial Intelligence: An Integrative Framework
Hillebrand, L., Raisch, S., & Schad, J. (2025) · Academy of Management Annals · doi:10.5465/annals.2022.0072 · Cited by 209
Metadata
- Authors
- Man Tang, P., Koopman, J., McClean, S. T., Zhang, J. H., Li, C. H., De Cremer, D., Lu, Y., & Ng, C. T. S.
- Affiliations
- University of Georgia
- Texas A&M University (US)
- University of Oklahoma (US)
- Washington University in St. Louis (US)
- National University of Singapore
- National University of Singapore (SG)
- National Sun Yat-sen University (TW)
- Venue
- Academy of Management Journal
- Publisher
- Academy of Management
- Published
- 2022-06
- Volume
- 65
- Issue
- 3
- Pages
- 1019-1054
- ISSN
- 0001-4273 (ISSN-L)
- 1948-0989
- OpenAlex
- W3211155880
- Semantic Scholar
- d804dd90e7632bee1eaad8d0c8d696d620ec5731
- Cited by
- 370
- References
- 215
- Citations by year
- 2026: 162 · 2025: 117 · 2024: 54 · 2023: 27 · 2022: 9
- FWCI
- 22.07
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Academy of Management Journal (publishedVersion)
- ePrints Soton (University of Southampton) (submittedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Job Satisfaction and Organizational Behavior
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › AI and HR Technologies
- Social Sciences › Human Factors and Ergonomics › Human-Automation Interaction and Safety
- Keywords
- conscientiousness, intelligent machines, artificial intelligence, robots, algorithms, complementarity principle, role theory, orderliness, employee performance, autonomous decision-making, human-machine interaction
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