The DOI matches its Crossref record.
An Investigation of Liking of Computers, Help Received, and Job Outcomes for Computer Workers
Abstract
The number of workers having to use computers in their jobs continues to increase. However, not all employees enjoy computer work at the same levels, and for those who do not enjoy computer work, negative outcomes are likely to result. Further, it is important to examine how work-related support from either supervisors or coworkers will minimize/buffer the relationships between not liking computer work and the consequences of job satisfaction and technology overload. We examine these hypotheses in a sample of 225 workers, from a wide range of jobs, all of whom work more than 20 hours per week on their computers. Our results show that liking computer work is positively related to job satisfaction, and supervisor computer help moderates the relationships between liking computer work and the outcomes of job satisfaction and technology work overload. Practical implications, limitations, and suggestions for future research are offered.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Further, there are empirical studies that analyze the relationship between leadership and technostress (Çiçek and Kılınç 2021;Harris and Marett 2009).”
From Leadership and technostress: A systematic literature review (2025) · cites this paper as Harris and Marett 2009
In the citing paper
“Moreover, leadership has been shown to moderate the impact of individual factors like workaholism (Spagnoli et al. 2020) or the level of preference for computer work (Harris and Marett 2009) on technostress and technostress-related outcomes.”
From Leadership and technostress: A systematic literature review (2025) · cites this paper as Harris and Marett 2009
Citations
Cites
Still being checked.
Cited by
Sorted by citations
Leadership and technostress: A systematic literature review
Rademaker, T., Klingenberg, I., & Süß, S. (2025) · Management Review Quarterly · doi:10.1007/s11301-023-00385-x · Cited by 59
Harris, K. J., Lambert, A. D., & Harris, R. B. (2013) · Journal of Applied Social Psychology · doi:10.1111/jasp.12122 · Cited by 33
Self-citationAn investigation of the impact of abusive supervision on technology end-users
Harris, K. J., Marett, K., & Harris, R. B. (2013) · Computers in Human Behavior · doi:10.1016/j.chb.2013.06.008 · Cited by 14
Self-citationReimagining the role of technology in higher education: the new normal and learners’ likes
Greve, K., & Tan, A. (2021) · Compass Journal of Learning and Teaching · doi:10.21100/compass.v14i3.1231 · Cited by 7
Metadata
- Authors
- Harris, R. B., & Marett, K.
- Affiliations
- Indiana University Southeast (US)
- Mississippi State University (US)
- Venue
- Journal of Organizational and End User Computing
- Publisher
- IGI Global Scientific Publishing
- Published
- 2009-07-01
- Volume
- 21
- Issue
- 3
- Pages
- 60-79
- ISSN
- 1546-2234 (ISSN-L)
- 1546-5012
- OpenAlex
- W2006106542
- Cited by
- 4
- References
- 0
- Citations by year
- 2023: 1 · 2021: 1 · 2013: 2
- FWCI
- 0.00
- Type
- journal article
- Language
- ng
- Open access
- closed
- Locations
- Journal of Organizational and End User Computing (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Psychology › Social Psychology › Technostress in Professional Settings
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Job Satisfaction and Organizational Behavior
- Keywords
- job satisfaction, coworker support, computer workers, moderating effect, job outcomes
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