Fair Target Setting for Intermediate Products in Two-Stage Systems with Data Envelopment Analysis

Qingxian An, Haoxun Chen, Beibei Xiong (), Jie Wu and Liang Liang
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Qingxian An: Central South University
Haoxun Chen: University of Technology of Troyes
Beibei Xiong: Hunan University
Jie Wu: University of Science and Technology of China
Liang Liang: University of Science and Technology of China

Chapter Chapter 7 in Data Science and Productivity Analytics, 2020, pp 201-226 from Springer

Abstract: Abstract In a two-stage system with two divisions connected in series, fairly setting the target outputs for the first stage or equivalently the target inputs for the second stage is critical, in order to ensure that the two stages have incentives to collaborate with each other to achieve the best performance of the whole system. Data envelopment analysis (DEA) as a non-parametric approach for efficiency evaluation of multi-input, multi-output systems has drawn a lot of attention. Recently, many two-stage DEA models were developed for studying the internal structures of two-stage systems. However, there was no work studying the fair setting of the target intermediate products (or intermediate measures) although unreasonable setting will result in unfairness to the two stages because setting higher (fewer) intermediate measures means that the first (second) stage must make more efforts to achieve the overall production plan. In this chapter, a new DEA model taking account of fairness in the setting of the intermediate products is proposed, where the fairness is interpreted based on the Nash bargaining game model, in which the two stages negotiate their target efficiencies in the two-stage system based on their individual efficiencies. This approach is illustrated by an empirical application to insurance companies.

Keywords: Data envelopment analysis; Efficiency analysis; Intermediate products; Fairness concern; Nash bargaining game (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/978-3-030-43384-0_7

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