The implications of pay transparency in the presence of over‐ and underconfident agents

Xiaoshuai Fan, Qingye Wu, Ying‐Ju Chen and Christopher S. Tang

Production and Operations Management, 2023, vol. 32, issue 7, 2304-2321

Abstract: Many companies are under pressure to improve pay transparency; however, its impact on their agents and principals remains unclear. As a way to investigate the upside and downside of pay transparency, we conduct our study based on a scenario in which agents have “cognitive bias” (namely, over‐ or underconfident). We also capture the notion of “social comparisons” behavior (namely, behind‐averse and ahead‐seeking) that occurs under pay transparency. By exploring a one‐principal‐two‐agent model, we find that agents' optimal effort decisions are affected by the “intersection” between agents' social comparison behavior and cognitive bias. Specifically, relative to the opaque policy, we find that pay transparency can entice agents to improve their job performance (in general). Our analysis also provides a guideline for principals to implement transparent payment policies properly (including the optimal payment scheme and the recruitment strategy). Specifically, pay transparency could enable the principal to offer a lower merit‐based factor level but a higher base salary level than opaque policy to motivate agents. To obtain high retained earnings, it is profitable for the principal to hire an overconfident agent if the principal chooses to adopt the opaque policy, but hire a mildly underconfident agent if pay transparency is selected. Moreover, we extend the base model to incorporate working capability heterogeneity across agents. We find that the agent's effort incentive and his opponent's working capability move in the same direction when the two agents' working capabilities are comparable under the transparent policy. Finally, by incorporating the environment's relative favoritism into the base model, we observe that when the environment is highly uncertain, the underconfident agent is willing to leverage environment uncertainty but the overconfident agent is willing to exert more effort.

Date: 2023
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