The Retention Effect of Withholding Performance Information

2007 ◽  
Vol 82 (2) ◽  
pp. 389-425 ◽  
Author(s):  
Korok Ray

It is a common practice for firms to conduct performance evaluations of their employees and yet to withhold this information from those employees. This paper argues that firms strategically withhold performance information to retain workers. In particular, if the worker enjoys high outside options and is tempted to quit, then the firm chooses not to reveal his performance information in order to keep him on the job. The firm's equilibrium strategy is to fire if performance is sufficiently low, reveal information if performance is sufficiently high, and withhold information otherwise. The pooling equilibrium is robust under a wide variety of settings, such as general cost functions, ability-contingent outside options, nonlinear contracts, nonverifiable output, and multiple stages of production.

2020 ◽  
Vol 68 (4) ◽  
pp. 1218-1230
Author(s):  
Zhenghua Long ◽  
Nahum Shimkin ◽  
Hailun Zhang ◽  
Jiheng Zhang

In “Dynamic Scheduling of Multiclass Many-Server Queues with Abandonment: The Generalized cμ/h Rule,” Long, Shimkin, Zhang, and Zhang propose three scheduling policies to cope with any general cost functions and general patience-time distributions. Their first contribution is to introduce the target-allocation policy, which assigns higher priority to customer classes with larger deviation from the desired allocation of the service capacity and prove its optimality for any general queue-length cost functions and patience-time distributions. The Gcμ/h rule, which extends the well-known Gcμ rule by taking abandonment into account, is shown to be optimal for the case of convex queue-length costs and nonincreasing hazard rates of patience. For the case of concave queue-length costs but nondecreasing hazard rates of patience, it is optimal to apply a fixed-priority policy, and a knapsack-like problem is developed to determine the optimal priority order efficiently.


Author(s):  
Gregory A Porumbescu ◽  
Suzanne J Piotrowski ◽  
Vincent Mabillard

Abstract Social accountability reforms emphasize expanding performance information disclosure and incorporating citizen feedback into performance evaluations of public organizations. However, social accountability scholarship has largely ignored possible discriminatory implications of performance information use despite calls for more social equity research. We look to bridge these two literatures, arguing that increasing exposure to performance information can actually activate racial bias in citizen feedback. Using two samples of White MTurk participants residing in the United States, we test this argument in a Negative Performance Information Study (n = 800) and a Positive Performance Information Study (n = 800). In the Negative Performance Information Study, we find increased exposure to negative performance information triggers more negative performance evaluations of public organizations led by Black public managers, but not White public managers, and strengthens preferences to fire Black public managers, but not White public managers. In the Positive Performance Information Study, we find increased exposure to positive performance information has no impact on performance evaluations of Black, nor White public managers but strengthens preferences to reappoint White, but not Black public managers. These findings suggest increasing exposure to performance information triggers racial bias in performance evaluations and preferences for holding public managers accountable.


Algorithmica ◽  
2013 ◽  
Vol 69 (3) ◽  
pp. 582-604 ◽  
Author(s):  
Hiroshi Fujiwara ◽  
Tobias Jacobs

2014 ◽  
Vol 43 (1) ◽  
pp. 126-143 ◽  
Author(s):  
Sungjin Im ◽  
Benjamin Moseley ◽  
Kirk Pruhs

Annals of PDE ◽  
2021 ◽  
Vol 7 (2) ◽  
Author(s):  
Felix Otto ◽  
Maxime Prod’homme ◽  
Tobias Ried

AbstractWe extend the variational approach to regularity for optimal transport maps initiated by Goldman and the first author to the case of general cost functions. Our main result is an $$\epsilon $$ ϵ -regularity result for optimal transport maps between Hölder continuous densities slightly more quantitative than the result by De Philippis–Figalli. One of the new contributions is the use of almost-minimality: if the cost is quantitatively close to the Euclidean cost function, a minimizer for the optimal transport problem with general cost is an almost-minimizer for the one with quadratic cost. This further highlights the connection between our variational approach and De Giorgi’s strategy for $$\epsilon $$ ϵ -regularity of minimal surfaces.


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