Research on the definition and conceptual understanding of meaningful work is fragmented. The purpose of this study is to better understand characteristics of people who experience meaningful work. Variables will be selected based on conceptual importance and empirical significance from a range of theoretical perspectives on meaningful work. The following constructs were studied through cluster analysis: (a) meaningful work, (b) authenticity at work, (c) career confidence, (d) work centrality, (e) religiousness, (f) meaning in life, (g) coworker satisfaction, (h) calling, (i) work engagement, (j) career commitment, and (k) work values. A sample of 437 adults who endorsed finding their work meaningful were recruited through Amazon’s Mechanical Turk (MTurk) online data collection service. A two-step process by Gore (2000) was followed for the data analysis. First, hierarchical cluster analysis using the “NbClust” package in R statistical software (Charrad, Ghazzali, Boiteau, & Niknafs, 2015) was used to determine the best number of clusters. Subsequently, k-means cluster analyses were used to assign individual cases to specific clusters.
| Identifer | oai:union.ndltd.org:siu.edu/oai:opensiuc.lib.siu.edu:dissertations-2690 |
| Date | 01 May 2019 |
| Creators | Miller, Aaron David |
| Publisher | OpenSIUC |
| Source Sets | Southern Illinois University Carbondale |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Dissertations |
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