A metafrontier-based yardstick competition mechanism for incentivising units in centrally managed multi-group organisations

  • Mohsen AfsharianEmail author
S.I.: Data Envelopment Analysis: Four Decades On


In many empirical applications of data envelopment analysis models, a central body manages a set of similar decision making units (DMUs), which are organised into a few distinct groups. This grouping is often used in order to ensure that the DMUs have enough flexibility to effectively fulfill the demands of their local customers in line with the group assignments and according to the different environmental constraints. While the central management in such organisations faces information asymmetry concerning the operating costs of the units, it wishes to incentivise them through benchmarking to operate as efficiently as possible. This paper extends previous literature in this area to account for heterogeneity among operating units and the need for central management to cope with asymmetry of information in managing such organisations. Within this approach, inefficient units are required to improve performance in a manner which most closely reflects their own output profiles and cost structures within their groups. Operating units which are identified to be efficient are also incentivised by some reward consistent with the level of their impact on the efficiency of their groups. Data from KONE Corporation, which is internationally renowned as one of the leaders in the elevator and escalator industry, are used to illustrate the proposed method as well as to compare the results with those obtained by the existing “decentralised” and “centralised” systems of incentives in the literature.


Data envelopment analysis (DEA) Centrally managed multi-group organisations Metafrontier Incentive regulation The elevator and escalator industry 



This work was supported by the Deutsche Forschungsgemeinschaft (DFG) in the context of the research fund AH 90/5-2. The author is grateful for constructive comments made by the anonymous referees and guest editors, which greatly improved the paper. The author would also like to thank the representatives of KONE for the provision of the data set. The empirical application in this paper is only illustrative of the proposed approach and does not necessarily reflect the official policy of KONE.


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© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Business SciencesTechnische Universität BraunschweigBraunschweigGermany

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