ORCID

0009-0001-9085-9497

Keywords

workplace happiness, turnover intent, employee well-being, socio-technical model, workplace distress, structural equation modeling

Subject Categories

Business Administration, Management, and Operations | Management Information Systems | Organizational Behavior and Theory

Abstract

Technology workers are central to the innovation and performance of modern organizations and retaining them is a persistent challenge for modern organizations. One important aspect of retention in many contexts is Workplace Happiness, which has been argued to improve worker performance and reduce turnover; however, there is little empirical evidence of the effectiveness of these interventions for technology workers. This dissertation develops a model in which two affective states, Workplace Happiness and Workplace Distress, mediate the relationships between six socio-technical work conditions and two behavioral outcomes: Turnover Intent and Work Execution (i.e., self-rated work performance and quality). A systematic literature review and a systems-dynamics analysis identified the conditions and feedback structures most relevant to the technology workplace, and thematic coding of open-ended responses identified the process and tool changes workers most sought. The model was tested with survey responses from 607 United States technology workers recruited through Prolific. A split-sample design used separate exploratory and confirmatory subsamples, and the structural equation model was estimated with full-information maximum likelihood and bootstrapped mediation tests. A three-item happiness measure was developed and evaluated against the longer PERMA-Profiler and Shortened Happiness at Work instruments,  supporting its use in the structural test. The results showed that Workplace Happiness is distinct from Workplace Distress. Happiness mediated work conditions' effects on Turnover Intent, while Distress mediated their effects on Work Execution. Leadership Support and System Feedback best predicted Happiness, and Toil, the firefighting and technical-debt work that crowds out meaningful work, best predicted Distress. The structure also showed no detectable moderation across fourteen workforce characteristics, indicating broad generalizability across subgroups. The model is grounded in the academic literature and documents technology workers' perspectives and experiences with interventions meant to improve happiness at work, providing a basis for developing and prioritizing initiatives within technology organizations.

Completion Date

2026

Semester

Summer

Committee Chair

Heather Keathley

Degree

Doctor of Philosophy (Ph.D.)

College

College of Engineering and Computer Science

Department

Industrial Engineering and Management Systems

Format

PDF

Document Type

Dissertation

Language

English

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