A DEA-based incentives system for centrally managed multi-unit organisations

Abstract

In multi-unit organisations such as a bank and its branches or a national body delivering publicly funded health or education services through local operating units, the need arises to incentivize the units to operate efficiently. In such instances, it is generally accepted that units found to be inefficient can be encouraged to make efficiency savings. However, units which are found to be efficient need to be incentivized in a different manner. It has been suggested that efficient units could be incentivized by some reward compatible with the level to which their attainment exceeds that of the best of the rest, normally referred to as “super-efficiency”. A recent approach to this issue (Varmaz et. al. 2013) has used Data Envelopment Analysis (DEA) models to measure the super-efficiency of the whole system of operating units with and without the involvement of each unit in turn in order to provide incentives. We identify shortcomings in this approach and use it as a starting point to develop a new DEA-based system for incentivizing operating units to operate efficiently for the benefit of the aggregate system of units. Data from a small German retail bank is used to illustrate our method.

Publication DOI: https://doi.org/10.1016/j.ejor.2016.10.040
Divisions: College of Business and Social Sciences > Aston Business School > Operations & Information Management
Additional Information: © 2016, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/
Uncontrolled Keywords: Data Envelopment Analysis,DEA,centralised management,incentive regulation,banking,Modelling and Simulation,Management Science and Operations Research,Information Systems and Management
Publication ISSN: 1872-6860
Last Modified: 11 Mar 2024 08:15
Date Deposited: 02 Nov 2016 13:15
Full Text Link:
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2017-06-01
Published Online Date: 2016-10-27
Accepted Date: 2016-10-19
Submitted Date: 2015-12-28
Authors: Afsharian, Mohsen
Ahn, Heinz
Thanassoulis, Emmanuel (ORCID Profile 0000-0002-3769-5374)

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