The Facet Satisfaction Scale: an Effective Affective Measure of Job Satisfaction Facets

Job satisfaction facets are theoretically and practically important variables. Most existing facet satisfaction scales, however, have two noteworthy limitations—they often do not clearly assess affective content, and they use non-parallel items. In the current paper, we examined the measurement qualities of the Facet Satisfaction Scale (FSS; [Beehr et al. (Journal of Applied Social Psychology 36:1523–1547, 2006)], a measure that may address the limitations of existing facet satisfaction measures.
Design/Methodology/Approach
We conducted four studies to examine the measurement qualities of the FSS: (a) Study 1 examined the FSS’s factor structure, (b) Study 2 examined its test-retest reliability and construct validity, (c) Study 3 further examined its construct validity, and (d) Study 4 examined the extent to which the FSS assesses the affective and cognitive components of job satisfaction.
Findings
We found that the FSS produced the hypothesized five-factor structure and that the FSS subscales each yielded high levels of internal consistency and test-retest reliability. We also found evidence of the construct validity of the FSS subscales, and we found that the FSS subscales are generally effective measures of the affective component of their respective job satisfaction facets.
Implications
As a result of the current findings, we recommend the FSS when researchers wish to measure the affective component of job satisfaction facets.
Originality/Value
Little previous research has examined the FSS’s measurement qualities. The current studies address this gap by providing evidence for the reliability and validity of the FSS. This is of value because the FSS addresses some limitations inherent to other facet satisfaction measures.
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Notes
We replicated the Study 1 findings using a combined dataset comprising the Study 1, 2, 3, and 4 datasets (N = 456). The fit of the single-factor model (χ 2 = 6675.69, df = 275, p < 0.01; RMSEA = 0.26; CFI = 0.32; TLI = 0.25; SRMR = 0.18), the fit of the hypothesized five-factor model (χ 2 = 1308.62, df = 265; RMSEA = 0.11; CFI = 0.89; TLI = 0.87; SRMR = 0.06), and the difference in fit between the two models (Δχ 2 = 5367.07, Δdf = 10, p < 0.01) we observed within the combined dataset were generally similar to those we observed within the Study 1 dataset.
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Author information
Authors and Affiliations
- Wright State University, 303C Fawcett Hall, 3640 Colonel Glenn Highway, Dayton, OH, 45435-0001, USA Nathan A. Bowling
- Governors State University, University Park, IL, USA Stephen H. Wagner
- Central Michigan University, Mount Pleasant, MI, USA Terry A. Beehr
- Nathan A. Bowling