Assessing sustainability of supply chains by double frontier network DEA: A big data approach

被引：124

作者：

Badiezadeh, Taliva ^{[1
]}

Saen, Reza Farzipoor ^{[2
]}

Samavati, Tahmoures ^{[2
]}

机构：

[1] Islamic Azad Univ, Young Researchers & Elites Club, Karaj Branch, Alborz, Iran

[2] Islamic Azad Univ, Dept Ind Management, Fac Management & Accounting, Karaj Branch, POB 31485-313, Karaj, Iran

来源：

COMPUTERS & OPERATIONS RESEARCH | 2018年 / 98卷

关键词：

Sustainable supply chain management (SSCM); Big Data; Network data envelopment analysis (NDEA); Data envelopment analysis (DEA); Double frontier; Undesirable outputs; DATA ENVELOPMENT ANALYSIS; ADDITIVE EFFICIENCY DECOMPOSITION; PREDICTIVE ANALYTICS; ANALYSIS MODEL; DATA SCIENCE; MANAGEMENT; PERFORMANCE; PRODUCTIVITY; INDUSTRY; OUTPUTS;

D O I：

10.1016/j.cor.2017.06.003

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Nowadays, performance evaluation of sustainable supply chain management (SSCM) is a very important topic for researchers and practitioners. Data envelopment analysis (DEA) is an appropriate method for assessing performance of SSCM in presence of Big Data. Network DEA (NDEA) can calculate efficiency of multi-stage processes. In this paper, an NDEA model for calculating optimistic and pessimistic efficiency is developed. Our proposed model can incorporate undesirable outputs. Also, our model can rank supply chains in terms of efficiency scores. A case study demonstrates efficacy of our proposed model. (C) 2017 Elsevier Ltd. All rights reserved.

引用

页码：284 / 290

页数：7

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