Our work and the organization in which we work play significant roles in many of our lives. Yet, theoretically grounded understanding of when is it that the relationships with our work and that with our work environment make a great place to work is almost non-existent. So far the organizations that feature in the Fortune Best Companies to Work For, or the Forbes the Happiest Companies to Work For, or the Glassdoor Best Places to Work, etc., are considered as proxies for great places to work. However, the characterizations of the antecedents of these workplaces are fragmented, idiosyncratic, and confounding, as they cover a wide span of factors (e.g., pride, job satisfaction, flexibility, inspiring leadership, camaraderie, trust, work-life balance, etc.), and adopt a one-size fits all approach, without a theoretical underpinning, limiting their generalizability and usefulness.
In my dissertation, I addressed these shortcomings through the fit perspective and through the mechanism of meaning in and at work. I proposed the meaning-through-fit model of great places to work, underpinned by identity (Stryker & Berke, 2000), social identity (Ashforth & Mael, 1989), and social information processing theories (Salancik & Pfeffer, 1978). The model hypothesized that the employees’ perception of a great place to work is built and sustained by meaning in work (from the relationship with the work itself) based on the underlying person-work fit, and by meaning at work (from the relationship with the work environment) based on the underlying person-supervisor, the person-group, and the person-organization fits.
I tested the proposed model using a mixed methods approach, with the help of three Studies. In Study 1, I conducted 26 semi-structured interviews to assess the face validity of the model and to obtain inputs for the survey instrument and for the scenario descriptions to be used in Study 2. In Study 2, I tested the hypothesized model with the help of quantitative data gathered through a three-wave Main Survey with participants from MTurk (N=481), after two Pilot Surveys (N=95 and 247). I confirmed the results through Scenario Analysis with participants from MTurk (N=399). Out of the seven main variables in the proposed model, I developed scales to measure three variables (employees’ perception of a great place to work, meaning at work, and person-group fit), and refined the scales to measure four variables (person-work fit, person-supervisor fit, person-organization fit, and meaning in work). In Study 3, I conducted 45 structured interviews in order to gain a deeper understanding of the findings from Study 2.
The quantitative data gathered in Study 2 provided partial support to the proposed model, indicating that meaning in work partly mediated the relationship between person-work fit and employees’ perception of a great places to work, and meaning at work partly mediated the relationship between person-organization fit and employees’ perception of a great place to work. The data also indicated that meaning at work is the more significant predictor compared to meaning in work. Among the fits, person-organization fit mattered the most. Study 3 provided interesting insights and explanations about the findings from Study 2. The meaning-through-fit model of great places to work works around the problematic one-size fits all approach, acknowledges the differences among the employees in the understanding of and expectations from a great places to work, offers increased generalizability and a pathway to leaders to build great places to work from the employees’ perspective, and contributes theoretically and empirically to Positive Organizational Scholarship. / Graduate / 2019-08-26
Identifer | oai:union.ndltd.org:uvic.ca/oai:dspace.library.uvic.ca:1828/10080 |
Date | 18 September 2018 |
Creators | Kar, Anirban |
Contributors | Elangovan, A. R. |
Source Sets | University of Victoria |
Language | English, English |
Detected Language | English |
Type | Thesis |
Format | application/pdf |
Rights | Available to the World Wide Web |
Page generated in 0.0022 seconds