The UTC Graduate School is pleased to announce that Wesley Gibbs will present Master’s research titled, THE ROLE OF FAIRNESS, TRANSPARENCY, AND FEEDBACK IN DRIVING MOTIVATION AND PERFORMANCE AMONG EMPLOYEES IN INCENTIVE-BASED ROLES on 03/02/2026 at 12:30 in McCallie, room 394. Everyone is invited to attend.
Psychology
Chair: Christopher Cunningham
Co-Chair:
Abstract:
Organizations are under increasing pressure to design reward systems that are not only competitive but also perceived as fair and transparent by employees. This issue is particularly salient in today’s workforce, where pay transparency legislation and widespread information sharing have heightened employee expectations for openness and equity. Early-career employees, who are forming long-term perceptions of organizational fairness, may be especially sensitive to these dynamics. Guided by Equity Theory and organizational justice frameworks, the present study is aimed at investigating how pay fairness, reward transparency, and feedback quality interact to shape motivation and job performance, including discretionary effort. A survey of early-career professionals in incentive-driven roles will be conducted, using validated measures of distributive justice, reward transparency, feedback environment, work motivation, and in-role performance. Which poses (RQ1) The relationships between pay fairness, reward transparency, feedback quality, and motivation differ between early-career employees and more experienced employees? Furthermore, the proposed conceptual model illustrates three hypothesized effects: (H1) Perceived pay fairness is positively associated with motivation for job performance among incentive-based employees; (H2) Perceived reward transparency is positively associated with motivation for job performance; and (H3) Feedback quality moderates the relationship between reward transparency and motivation for job performance such that the positive association is stronger at high levels of feedback quality and nonsignificant at low levels of feedback quality. Data will be analyzed through hierarchical regression and moderation techniques, with mediation being explored appropriately. The findings are expected to advance compensation and motivation research by integrating structural features of reward systems with individual motivational outcomes. The findings will also be used to offer practical implications for organizations seeking to retain and engage talent through fair, transparent, and feedback-rich systems.