Abstract
We study a game involving a firm and a newly hired employee whose capability is initially unknown to both parties. Both players observe the performance of the employee and update their common posterior beliefs about the employee’s capability. The learning process presents each party with an option: the firm can terminate an incapable employee, and a capable employee can leave the firm for greater financial remuneration elsewhere. To understand the impact of this noncooperative interaction, we examine the Markov perfect equilibrium termination strategies and payoffs that unfold. We find that in the region of sufficiently high learning rates, reducing the rate of learning can increase the equilibrium payoff for both parties. Slower learning prolongs the employment because more performance outcomes must be observed to fully assess the employee’s capability. In the region of sufficiently slow learning rates, reducing the rate of learning can benefit the firm if the employee is deemed capable but hurt the firm otherwise. Our result identifies a nonfinancial way for firms to improve retention of capable new employees.
Original language | English (US) |
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Pages (from-to) | 927-941 |
Number of pages | 15 |
Journal | IISE Transactions |
Volume | 49 |
Issue number | 10 |
DOIs | |
State | Published - Oct 3 2017 |
Keywords
- Bayesian sequential decision
- employee retention
- stochastic dynamic game
- timing game
ASJC Scopus subject areas
- Industrial and Manufacturing Engineering