Retention of capable new employees under uncertainty: Impact of strategic interactions
H. Dharma Kwon and
Onesun Steve Yoo
IISE Transactions, 2017, vol. 49, issue 10, 927-941
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.
Date: 2017
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://hdl.handle.net/10.1080/24725854.2017.1325028 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:uiiexx:v:49:y:2017:i:10:p:927-941
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/uiie20
DOI: 10.1080/24725854.2017.1325028
Access Statistics for this article
IISE Transactions is currently edited by Jianjun Shi
More articles in IISE Transactions from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().