The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
One Road to Turnover: An Examination of Work Exhaustion in Technology Professionals1
Abstract
The concept of work exhaustion (or job burnout) from the management and psychology research literature is examined in the context of technology professionals. Data were collected from 270 IT professionals and managers in various industries across the United States. Through structural equation modeling, work exhaustion was shown to partially mediate the effects of workplace factors on turnover intention. In addition, the results of the study revealed that: (1) technology professionals experiencing higher levels of exhaustion reported higher intentions to leave the job and, (2) of the variables expected to influence exhaustion (work overload, role ambiguity and conflict, lack of autonomy and lack of rewards), work overload was the strongest contributor to exhaustion in the technology workers. Moreover, exhausted IT professionals identified insufficient staff and resources as a primary cause of work overload and exhaustion. Implications for practice and future research are discussed.
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
Development and validation of brief measures of positive and negative affect: The PANAS scales.
Watson, D., Clark, L. A., & Tellegen, A. (1988) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.54.6.1063 · Cited by 32,433
Self-Reports in Organizational Research: Problems and Prospects
Podsakoff, P. M., & Organ, D. W. (1986) · Journal of Management · doi:10.1177/014920638601200408 · Cited by 17,102
The measurement of experienced burnout
Maslach, C., & Jackson, S. E. (1981) · Journal of Organizational Behavior · doi:10.1002/job.4030020205 · Cited by 14,496
Weber, R. (1990) · doi:10.4135/9781412983488 · Cited by 7,750
A Beginner's Guide to Structural Equation Modeling: Fourth Edition
Schumacker, R. E., & Lomax, R. G. (2015) · doi:10.4324/9781315749105 · Cited by 6,604
Negative affectivity: the disposition to experience aversive emotional states
Watson, D., & Clark, L. A. (1984) · Psychological Bulletin · doi:10.1037/0033-2909.96.3.465 · Cited by 4,636
A meta-analytic examination of the correlates of the three dimensions of job burnout
Lee, R. T., & Ashforth, B. E. (1996) · Journal of Applied Psychology · doi:10.1037/0021-9010.81.2.123 · Cited by 3,262
Personality and susceptibility to positive and negative emotional states.
Larsen, R. J., & Ketelaar, T. (1991) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.61.1.132 · Cited by 1,062
‘Burnout’, absence and turnover amongst British nursing staff
Firth, H., & Britton, P. (1989) · Journal of Occupational Psychology · doi:10.1111/j.2044-8325.1989.tb00477.x · Cited by 249
Cited by
Ahuja, M. K., & Bennett, J. (2005) · MIS Quarterly · doi:10.2307/25148691 · Cited by 818
Lee, A. R., Son, S.-M., & Kim, K. K. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2015.08.011 · Cited by 814
Molino, M., Ingusci, E., Signore, F., Manuti, A., Giancaspro, M. L., Russo, V., Zito, M., & Cortese, C. G. (2020) · Sustainability · doi:10.3390/su12155911 · Cited by 532
Joseph, D., Ng, K.-Y., Koh, C., & Ang, S. (2007) · MIS Quarterly · doi:10.2307/25148807 · Cited by 468
Impact of artificial intelligence on employees working in industry 4.0 led organizations
Malik, N., Tripathi, S. N., Kar, A. K., & Gupta, S. (2022) · International Journal of Manpower · doi:10.1108/ijm-03-2021-0173 · Cited by 416
The digital workplace and its dark side: An integrative review
Marsh, E., Vallejos, E. P., & Spence, A. (2022) · Computers in Human Behavior · doi:10.1016/j.chb.2021.107118 · Cited by 348
Vatanasombut, B., Igbaria, M., Stylianou, A. C., & Rodgers, W. (2008) · Information & Management · doi:10.1016/j.im.2008.03.005 · Cited by 346
Understanding teleworkers’ technostress and its influence on job satisfaction
Suh, A., & Lee, J. (2017) · Internet Research · doi:10.1108/intr-06-2015-0181 · Cited by 347
Yu, L., Cao, X., Liu, Z., & Wang, J. (2018) · Information Technology & People · doi:10.1108/itp-10-2016-0237 · Cited by 297
Tams, S., Legoux, R., & Léger, P.-M. (2018) · Computers in Human Behavior · doi:10.1016/j.chb.2017.11.026 · Cited by 188
KLOPPER, H. C., COETZEE, S. K., PRETORIUS, R., & BESTER, P. (2012) · Journal of Nursing Management · doi:10.1111/j.1365-2834.2011.01350.x · Cited by 173
Person-Job Cognitive Style Fit for Software Developers: The Effect on Strain and Performance
CHILTON, M. A., HARDGRAVE, B. C., & ARMSTRONG, D. J. (2005) · Journal of Management Information Systems · doi:10.1080/07421222.2005.11045849 · Cited by 138
Mahmud, I., Ramayah, T., & Kurnia, S. (2017) · Information Systems · doi:10.1016/j.is.2017.05.005 · Cited by 131
Agogo, D., & Hess, T. J. (2018) · European Journal of Information Systems · doi:10.1080/0960085x.2018.1435230 · Cited by 121
Retention of IT professionals: Examining the influence of empowerment, social exchange, and trust
Ertürk, A., & Vurgun, L. (2015) · Journal of Business Research · doi:10.1016/j.jbusres.2014.05.010 · Cited by 107
Shah, S. H. A., Haider, A., Jindong, J., Mumtaz, A., & Rafiq, N. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.810378 · Cited by 86
Leung, L. (2011) · Human Technology: An Interdisciplinary Journal on Humans in ICT Environments · doi:10.17011/ht/urn.2011112211714 · Cited by 79
Tugtekin, U., Barut Tugtekin, E., Kurt, A. A., & Demir, K. (2020) · Social Media + Society · doi:10.1177/2056305120963760 · Cited by 78
An examination of work exhaustion in the mobile enterprise environment
Kim, H. J., Lee, C. C., Yun, H., & Im, K. S. (2015) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2015.07.009 · Cited by 45
Koriat, N., & Gelbard, R. (2014) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2014.04.009 · Cited by 44
(2008) · Journal of the Association for Information Systems · Cited by 36
Grummeck-Braamt, J.-V., Nastjuk, I., Najmaei, A., & Adam, M. (2021) · Proceedings of the Annual Hawaii International Conference on System Sciences · doi:10.24251/hicss.2021.796 · Cited by 25
Investigating the reversed causality of engagement and burnout in job demands-resources theory
De Beer, L. T., Pienaar, J., & Rothmann, S. (2013) · SA Journal of Industrial Psychology · doi:10.4102/sajip.v39i1.1055 · Cited by 14
Eustress and Distress in the Context of Telework
Van Slyke, C., Lee, J., Duong, B. Q., & Ellis, T. S. (2022) · Information Resources Management Journal · doi:10.4018/irmj.291526 · Cited by 12
Cheng, H.-L., Lin, T.-C., Tan, W.-K., & Chiu, C.-M. (2021) · Online Information Review · doi:10.1108/oir-06-2020-0214 · Cited by 11
Social Context of Turnover-Mixed Methods Study of Indian IT Professionals
Haran, V. V., & Niederman, F. (2022) · Journal of Global Information Management · doi:10.4018/jgim.299320 · Cited by 5
Metadata
- Authors
- Moore, J. E.
- Venue
- MIS Quarterly
- Publisher
- MIS Quarterly
- Published
- 2000-03-01
- Volume
- 24
- Issue
- 1
- Pages
- 141-168
- ISSN
- 0276-7783 (ISSN-L)
- 2162-9730
- OpenAlex
- W63814348
- Cited by
- 947
- References
- 9
- FWCI
- 21.53
- 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.