Reputation, Competition, and Lies in Labor Market Recommendations
成果类型:
Article
署名作者:
Camara, Odilon; Jia, Nan; Raffiee, Joseph
署名单位:
University of Southern California; University of Southern California
刊物名称:
MANAGEMENT SCIENCE
ISSN/ISSBN:
0025-1909
DOI:
10.1287/mnsc.2022.4654
发表日期:
2023
页码:
7022-7043
关键词:
Human capital
hiring
strategic communication
referrals
game theory
摘要:
We examine strategic communication in labor market recommendations. Our formal model features two-sided asymmetric information: An adviser has private information about his own preference bias for a focal candidate and a signal of the quality of this candidate, whereas the hiring firm has private information about the quality of an alternative candidate. The adviser can choose whether to recommend his focal candidate to the firm. If he recommends and the firm hires the candidate, then the adviser pays a reputational cost (receives a reputation boost) if the firm later learns that the hire has low quality (high quality). Our main results describe how the equilibrium behavior of advisers (lying choices) and firms (hiring choices) depend on the intricate interplay between preference biases, reputation, lying costs, and the hiring firm's labor market strength (access to alternative candidates with higher quality). We show that the equilibrium features assortative matching: advisers with a higher (lower) reputation choose to lie less (more), and consequently, their candidates are more likely to be hired by firms with strong (weak) access to high-skilled outside candidates. Two equilibrium forces create a rich get richer effect. First, advisers choose to lie less to hiring firms with access to better top candidates, further benefiting those firms. Second, advisers with a higher (lower) reputation choose to lie less (more), which increases (decreases) their future reputation, creating a reputation trap. We discuss the implications of our model for hiring strategy, referral systems, and the ability to accrue and sustain human capital-based competitive advantages.