Ranking intervals for two-stage production systems

Li, Yongjun, Shi, Xiao, Emrouznejad, Ali and Liang, Liang (2019). Ranking intervals for two-stage production systems. Journal of the Operational Research Society ,

Abstract

Traditional Data Envelopment Analysis (DEA) models find the most desirable weights for each Decision Making Unit (DMU) in order to estimate the highest efficiency score as possible. Usually, decision-makers are using these efficiency scores for ranking the DMUs. The main drawback in this process is that the ranking based on weights obtained from the standard DEA models ignore other feasible weights, this is due to the fact that DEA may have multiple solutions for each DMU. To overcome this problem, Salo and Punkka (2011) deemed each DMU as a “Black box” and developed a mix-integer model to obtain the ranking intervals for each DMU over sets of all its feasible weights. In many real-world applications, there are DMUs that have a two-stage production system. In this paper, we extend the Salo and Punkka (2011)’s model to more common and practical applications considering the two-stage production structure. The proposed approach calculates each DMU’s ranking interval for the overall system as well as for each subsystem/sub-stage. An application for non-life insurance companies is given to illustrate the applicability of the proposed approach. A real application in Chinese commercial banks shows how this approach can be used by policy makers.

Publication DOI: https://doi.org/10.1080/01605682.2018.1535267
Divisions: Aston Business School > Operations & information management
Aston Business School
Aston Business School > Operations & information management research group
Additional Information: This is an Accepted Manuscript of an article published by Taylor & Francis Group in Journal of the Operational Research Society on 4 Mar 2019, available online at: http://www.tandfonline.com/10.1080/01605682.2018.1535267
Uncontrolled Keywords: Ranking intervals,data envelopment analysis,two-stage production systems,Management Information Systems,Strategy and Management,Management Science and Operations Research,Marketing
Full Text Link:
Related URLs: https://www.tan ... 82.2018.1535267 (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
Accepted Date: 2018-10-01
Published Online Date: 2019-03-04
Authors: Li, Yongjun
Shi, Xiao
Emrouznejad, Ali ( 0000-0001-8094-4244)
Liang, Liang

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