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

Authors :
Jie Wu
Beibei Xiong
Haoxun Chen
Liang Liang
Qingxian An
Central South University [Changsha]
Laboratoire d'Optimisation des Systèmes Industriels (LOSI)
Institut Charles Delaunay (ICD)
Université de Technologie de Troyes (UTT)-Centre National de la Recherche Scientifique (CNRS)-Université de Technologie de Troyes (UTT)-Centre National de la Recherche Scientifique (CNRS)
Hunan University [Changsha] (HNU)
University of Science and Technology of China [Hefei] (USTC)
Source :
Data Science and Productivity Analytics, Data Science and Productivity Analytics, pp.201-226, 2020, ⟨10.1007/978-3-030-43384-0_7⟩, International Series in Operations Research & Management Science ISBN: 9783030433833
Publication Year :
2020
Publisher :
HAL CCSD, 2020.

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.

Details

Language :
English
ISBN :
978-3-030-43383-3
ISBNs :
9783030433833
Database :
OpenAIRE
Journal :
Data Science and Productivity Analytics, Data Science and Productivity Analytics, pp.201-226, 2020, ⟨10.1007/978-3-030-43384-0_7⟩, International Series in Operations Research & Management Science ISBN: 9783030433833
Accession number :
edsair.doi.dedup.....b24ff72e1549bfc66f7a1fae5b52262b