The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.
Job satisfaction in Britain: individual and job related factors
Open accessAbstract
Recently there has been a resurgence of interest in the analysis of job satisfaction variables. Job satisfaction is correlated with labour market behaviour such as productivity, quits and absenteeism. In this paper four different measures of job satisfaction are related to a variety of personal and job characteristics. The data used are from the 28 240 British employees in the Workplace Employee Relations Survey, 1997. This data set is larger and more recent than in any previous studies. Four measures of job satisfaction that have not previously been used are considered: satisfaction with influence over job; satisfaction with amount of pay; satisfaction with sense of achievement; and satisfaction with respect from supervisors. The paper contributes to the literature by analysing job satisfaction with respect to industrial composition and occupations. One of the striking findings is that those in the education and health sectors are less satisfied with their pay but more satisfied with their sense of achievement. Further, it is found that employees who received job training were more satisfied than those who had no training opportunities. Unlike previous studies, it is found that married individuals have lower job satisfaction levels than the unmarried. Other results confirm those in the literature, such as women being more satisfied than men, and a U-shaped relationship between satisfaction and age.
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Citations
Cites
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Job satisfaction and gender: Why are women so happy at work?
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Is job satisfaction U‐shaped in age?
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Metadata
- Authors
- Gazioglu, S., & Tansel, A.
- Venue
- Applied Economics
- Publisher
- Informa UK Limited
- Published
- 2006-06-10
- Volume
- 38
- Issue
- 10
- Pages
- 1163-1171
- ISSN
- 0003-6846 (ISSN-L)
- 1466-4283
- OpenAlex
- W2171223267
- Cited by
- 432
- References
- 27
- FWCI
- 16.01
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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