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A winner-take-all evaluation in data envelopment analysis

  • S.I.: DEA in Data Analytics
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Abstract

Numerous corporations are composed of several branches working in parallel regions, and the branches in regional markets are involved in the winner-take-all competition. This paper extends data envelopment analysis (DEA) method to the performance evaluation for those corporations. Firstly, a DEA model is proposed to calculate actual efficiencies of regional branches, where the market demands are considered as nontechnical constraints. Secondly, a winner-take-all evaluation is introduced to assess the overall performance of corporations. In the evaluation, analytic hierarchy process is used to obtain weights indicating regions’ relative importance, and values are assigned to regions according to their weights. Then branches in each region divide the assigned value based on a function reflecting the winner-take-all principle, i.e., a few winners get absolute majority of the value. The total values corporations obtain are employed to compare their overall performances. Our method not only presents the competitiveness and the development potential of corporations, but also helps managers to make more reasonable productivity allocations and effectively avoid the overcapacity. A numerical example is designed to illustrate our method.

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Acknowledgements

The research is supported by the National Natural Science Foundation of China (Nos. 71631006, 71601173), the National Soft Science Research Program (No. 2013GXS1D006), the China Postdoctoral Science Foundation (Nos. 2015M580556, 2016T90588), Philosophy and Social Science Project of Anhui Province (No. AHSKY2014D28), and the Fundamental Research Funds for the Central Universities.

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  1. School of Management, University of Science and Technology of China, 96 Jinzhai Road, Hefei, 230026, Anhui, People’s Republic of China

    Feng Yang, Lijing Jiang & Sheng Ang

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  1. Feng Yang
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  2. Lijing Jiang
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  3. Sheng Ang
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Correspondence to Sheng Ang.

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Yang, F., Jiang, L. & Ang, S. A winner-take-all evaluation in data envelopment analysis. Ann Oper Res 278, 141–158 (2019). https://doi.org/10.1007/s10479-018-2833-z

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