Improving Productivity by Periodic Performance Evaluation: A Bayesian Stochastic Model

Emmanuel Fernández-Gaucherand, Sanjay Jain, Hau L. Lee, Ambar G. Rao and M. R. Rao
Additional contact information
Emmanuel Fernández-Gaucherand: Systems and Industrial Engineering Department, The University of Arizona, Tucson, Arizona 85721
Sanjay Jain: Department of Marketing, The University of Arizona, Tucson, Arizona 85721
Hau L. Lee: Department of Industrial Engineering and Engineering Management, Stanford University, Stanford, California 94305
Ambar G. Rao: Faculty of Management, University of Toronto, Toronto, Ontario, Canada M5S 3E6
M. R. Rao: Stern School of Business, New York University, New York, New York 10006

Management Science, 1995, vol. 41, issue 10, 1669-1678

Abstract: We model the situation where the productivity of members of a group, such as a salesforce, is periodically evaluated; those whose performance is sub-par are dismissed and replaced by new members. Individual productivity is modeled as a random variable, the distribution of which is a function of an unknown parameter. This parameter varies across the members of the group and is specified by a prior distribution. In this manner, the heterogeneity in the group is explicitly accounted for. We model the situation as a parameter adaptive Bayesian stochastic control problem, and use dynamic programming techniques and the appropriate optimality equations to obtain solutions. We prove the existence of an optimal policy in the general case. Further, for the case when the sales process can be characterized by a Beta-Binomial or a Gamma-Poisson distribution, we show that the optimal policy is of the threshold type at each evaluation period, depending only on the accumulated performance up to a given period. We present a computational procedure to solve for the optimal thresholds. Results of computational experiments show that an increase in the heterogeneity of the group can lead to more stringent levels of minimal acceptable performance.

Keywords: stochastic productivity; unknown distribution parameters; periodic evaluations; Bayesian stochastic control; structured optimal policy; dynamic programming (search for similar items in EconPapers)
Date: 1995
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://dx.doi.org/10.1287/mnsc.41.10.1669 (application/pdf)

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:inm:ormnsc:v:41:y:1995:i:10:p:1669-1678

Access Statistics for this article

More articles in Management Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().