A review of Data Development Analysis (DEA) applications in supply chain management research

The objective of this paper is to review the application of Data Envelopment Analysis (DEA) in Supply Chain Management (SCM) research including different perspectives and research topics. In this review, academic databases used were ScienceDirect, Scopus and Google Scholar. The latter database was included to identify unpublished studies, conference proceedings and other types of unpublished studies. Practical review criteria are used for the inclusion or exclusion of the pertinent literature. In total 55 publications were found and analyzed in this paper. We found that even though both DEA and SCM were established as a field of study for a long time but there are only a few that applied the DEA to SCM. Most of studies applying DEA in SCM did not consider the whole supply chain, only some parts of the chain were analyzed. Based on the findings of the review, potential research agendas were developed.

[1]  Ali Emrouznejad,et al.  Fuzzy data envelopment analysis: A discrete approach , 2012, Expert Syst. Appl..

[2]  M. Skibniewski,et al.  Supply chain optimization tool for purchasing decisions in B2B construction marketplaces , 2007 .

[3]  Adel Hatami-Marbini,et al.  Allocating fixed resources and setting targets using a common-weights DEA approach , 2013, Comput. Ind. Eng..

[4]  Anthony D. Ross,et al.  An integrated benchmarking approach to distribution center performance using DEA modeling , 2002 .

[5]  Guo Xiao-yan.  Performance Evaluation of Airport Construction Energy-saving based on DEA Network Design and Performance Analysis , 2011 .

[6]  Chien-Ming Chen,et al.  Production , Manufacturing and Logistics A network-DEA model with new efficiency measures to incorporate the dynamic effect in production networks , 2008 .

[7]  Yuan-Duen Lee,et al.  Applying integrated DEA/AHP to evaluate the economic performance of local governments in China , 2011, Eur. J. Oper. Res..

[8]  Jie Wu,et al.  Environmental efficiency evaluation based on data envelopment analysis: A review , 2012 .

[9]  David Hummels.  Transportation Costs and International Trade in the Second Era of Globalization , 2007 .

[10]  David L. Olson,et al.  Supply chain risk, simulation, and vendor selection , 2008 .

[11]  Hamid Noori,et al.  A new methodology for evaluating sustainable product design performance with two-stage network data envelopment analysis , 2012, Eur. J. Oper. Res..

[12]  Valter Afonso Vieira,et al.  Relationship marketing in supply chain: an empirical analysis in the Brazilian service sector , 2011 .

[13]  Haritha Saranga,et al.  Performance evaluation of purchasing and supply management using value chain DEA approach , 2010, Eur. J. Oper. Res..

[14]  Debra Hofman,et al.  The supply chain top 25 : raising the bar , 2012 .

[15]  Joe Zhu,et al.  Equivalence in two-stage DEA approaches , 2009, Eur. J. Oper. Res..

[16]  Tetsuo Iida,et al.  Production , Manufacturing and Logistics Coordination of cooperative cost-reduction efforts in a supply chain partnership , 2012 .

[17]  Lawrence M. Seiford,et al.  Data envelopment analysis (DEA) - Thirty years on , 2009, Eur. J. Oper. Res..

[18]  David J. Barnes,et al.  A literature review of decision-making models and approaches for partner selection in agile supply chains , 2011 .

[19]  F. Chan,et al.  An empirical investigation of factors affecting e-collaboration diffusion in SMEs , 2012 .

[20]  Shiv Prasad Yadav,et al.  A concept of fuzzy input mix-efficiency in fuzzy DEA and its application in banking sector , 2013, Expert Syst. Appl..

[21]  Liang Liang,et al.  Two-stage BCC Model for Cooperative Efficiency Evaluation Using a Geometric Mean Method , 2008 .

[22]  R. F. Rea,et al.  Network DEA , 1999 .

[23]  M. D. Webber,et al.  Supply-chain management: logistics catches up with strategy , 1982 .

[24]  Ali Emrouznejad,et al.  Fuzzy assessment of performance of a decision making units using DEA: A non-radial approach , 2010, Expert Syst. Appl..

[25]  Loo Hay Lee,et al.  A study on the selection of benchmarking paths in DEA , 2011, Expert Syst. Appl..

[26]  Majid Azadi,et al.  A novel network data envelopment analysis model for evaluating green supply chain management , 2014 .

[27]  Adel Hatami-Marbini,et al.  An ideal-seeking fuzzy data envelopment analysis framework , 2010, Appl. Soft Comput..

[28]  Joe Zhu,et al.  DEA models for supply chain efficiency evaluation , 2006, Ann. Oper. Res..

[29]  Rashed Khanjani Shiraz,et al.  Fuzzy rough DEA model: A possibility and expected value approaches , 2014, Expert Syst. Appl..

[30]  Mohsen Rostamy-Malkhalifeh,et al.  Evaluating performance supply chain by a new non-radial network DEA model with fuzzy data , 2012 .

[31]  Martin Christopher,et al.  Logistics and supply chain management : creating value-adding networks , 2005 .

[32]  Zach G. Zacharia,et al.  DEFINING SUPPLY CHAIN MANAGEMENT , 2001 .

[33]  Selim Zaim,et al.  Measuring the efficiency of customer satisfaction and loyalty for mobile phone brands with DEA , 2012, Expert Syst. Appl..

[34]  J. Shang.  Multicriteria facility layout problem: An integrated approach , 1993 .

[35]  Anders Segerstedt,et al.  Measuring supply chain cost , 2013 .

[36]  Gülçin Büyüközkan,et al.  Analyzing the Solutions of DEA Through Information Visualization and Data Mining Techniques: SmartDEA Framework , 2011, Expert Syst. Appl..

[37]  Joe Zhu,et al.  Measuring performance of two-stage network structures by DEA: A review and future perspective , 2010 .

[38]  Kuan Yew Wong,et al.  Monte Carlo Data Envelopment Analysis with Genetic Algorithm for Knowledge Management performance measurement , 2012, Expert Syst. Appl..

[39]  Joe Zhu,et al.  Deriving the DEA frontier for two-stage processes , 2010, Eur. J. Oper. Res..

[40]  Ali Azadeh,et al.  Location optimization of solar plants by an integrated hierarchical DEA PCA approach , 2008 .

[41]  Soroosh Nalchigar,et al.  Information technology project evaluation: An integrated data envelopment analysis and balanced scorecard approach , 2010, Expert Syst. Appl..

[42]  L. Seiford,et al.  Profitability and Marketability of the Top 55 U.S. Commercial Banks , 1999 .

[43]  A. Gunasekaran,et al.  A framework for supply chain performance measurement , 2004 .

[44]  Pietro Romano,et al.  Supply chain management: an analytical framework for critical literature review , 2000 .

[45]  Yuh-Jen Chen,et al.  Structured methodology for supplier selection and evaluation in a supply chain , 2011, Inf. Sci..

[46]  Abraham Charnes,et al.  Measuring the efficiency of decision making units , 1978 .

[47]  Jian Cai,et al.  Improving supply chain performance management: A systematic approach to analyzing iterative KPI accomplishment , 2009, Decis. Support Syst..

[48]  Adel Hatami-Marbini,et al.  A taxonomy and review of the fuzzy data envelopment analysis literature: Two decades in the making , 2011, Eur. J. Oper. Res..

[49]  Wei Yang,et al.  Resource allocation models' construction for the reduction of undesirable outputs based on DEA methods , 2013, Math. Comput. Model..

[50]  David Jacoby.  Guide to Supply Chain Management , 2009 .

[51]  Bin Li,et al.  Rough data envelopment analysis and its application to supply chain performance evaluation , 2009 .

[52]  Sebastián Lozano,et al.  Multiobjective target setting in data envelopment analysis using AHP , 2009, Comput. Oper. Res..

[53]  Pablo Arocena,et al.  Cost and quality gains from diversification and vertical integration in the electricity industry: A DEA approach , 2008 .

[54]  Jukka Korpela,et al.  Warehouse operator selection by combining AHP and DEA methodologies , 2007 .

[55]  Greg N. Gregoriou,et al.  Quantitative Models for Performance Evaluation and Benchmarking: Data Envelopment Analysis with Spreadsheets , 2008, The Journal of Wealth Management.