A stochastic cross-efficiency data envelopment analysis approach for supplier selection under uncertainty

This paper addresses one of the key objectives of the supply chain strategic design phase, that is, the optimal selection of suppliers. A methodology for supplier selection under uncertainty is proposed, integrating the cross-efficiency data envelopment analysis (DEA) and Monte Carlo approach. The combination of these two techniques allows overcoming the deterministic feature of the classical cross-efficiency DEA approach. Moreover, we define an indicator of the robustness of the determined supplier ranking. The technique is able to manage the supplier selection problem considering nondeterministic input and output data. It allows the evaluation of suppliers under uncertainty, a particularly significant circumstance for the assessment of potential suppliers. The novel approach helps buyers in choosing the right partners under uncertainty and ranking suppliers upon a multiple sourcing strategy, even when considering complex evaluations with a high number of suppliers and many input and output criteria.

[1]  Mariagrazia Dotoli,et al.  Using Cross-Efficiency Fuzzy Data Envelopment Analysis for Healthcare Facilities Performance Evaluation under Uncertainty , 2013, 2013 IEEE International Conference on Systems, Man, and Cybernetics.

[2]  M. Braglia,et al.  Vendor Selection Using Principal Component Analysis , 2000 .

[3]  J. Florens,et al.  Nonparametric frontier estimation: a robust approach , 2002 .

[4]  Loo Hay Lee,et al.  Supply chain performance measurement system: a Monte Carlo DEA-based approach , 2008 .

[5]  Xin Yu,et al.  A case based reasoning approach on supplier selection in petroleum enterprises , 2011, Expert Syst. Appl..

[6]  Jianren Wang,et al.  Canonical correlation discriminant analysis in the selection of suppliers , 2010, 2010 International Conference on Artificial Intelligence and Education (ICAIE).

[7]  Seyed Hassan Ghodsypour,et al.  A decision support system for supplier selection using an integrated analytic hierarchy process and linear programming , 1998 .

[8]  Ezgi Aktar Demirtaş,et al.  An integrated multiobjective decision making process for supplier selection and order allocation , 2008 .

[9]  William W. Cooper,et al.  Chapter 13 Satisficing DEA models under chance constraints , 1996, Ann. Oper. Res..

[10]  Rodney H. Green,et al.  Cross-Evaluation in DEA - Improving Discrimiation Among DMUs , 1995 .

[11]  R. Handfield,et al.  Supplier integration into new product development: coordinating product, process and supply chain design , 2005 .

[12]  J. Buda.  Mathematical-logic formulation in metal cutting theory , 1973 .

[13]  Mark D. Treleven,et al.  A risk/benefit analysis of sourcing strategies: Single vs. multiple sourcing , 1988 .

[14]  Vito Albino,et al.  A neural network application to subcontractor rating in construction firms , 1998 .

[15]  Reza Farzipoor Saen,et al.  Suppliers selection in the presence of both cardinal and ordinal data , 2007, Eur. J. Oper. Res..

[16]  F. Roodhooft,et al.  Effectively selecting suppliers using total cost of ownership , 1999 .

[17]  Zilla Sinuany-Stern,et al.  Review of ranking methods in the data envelopment analysis context , 2002, Eur. J. Oper. Res..

[18]  Joe Zhu,et al.  Imprecise data envelopment analysis (IDEA): A review and improvement with an application , 2003, Eur. J. Oper. Res..

[19]  P. Andersen,et al.  A procedure for ranking efficient units in data envelopment analysis , 1993 .

[20]  Walter Ukovich,et al.  A hierarchical optimization technique for the strategic design of distribution networks , 2013, Comput. Ind. Eng..

[21]  I. Ozkarahan,et al.  Supplier evaluation and management system for strategic sourcing based on a new multicriteria sorting procedure , 2007 .

[22]  Reza Farzipoor Saen,et al.  Supplier selection by the new AR-IDEA model , 2008 .

[23]  A. Ravindran,et al.  A multiobjective chance constrained programming model for supplier selection under uncertainty , 2011 .

[24]  C. Swift.  Preferences for single sourcing and supplier selection criteria , 1995 .

[25]  Suresh Kumar Jakhar,et al.  An integrated model of supply chain performance evaluation and decision-making using structural equation modelling and fuzzy AHP , 2014 .

[26]  R. J. Kuo,et al.  Integration of artificial neural network and MADA methods for green supplier selection , 2010 .

[27]  Z. H. Che,et al.  A hybrid approach for supplier cluster analysis , 2010, Comput. Math. Appl..

[28]  Tadeusz Sawik,et al.  Single vs. multiple objective supplier selection in a make to order environment , 2010 .

[29]  John Ramsay,et al.  Sourcing/Contracting Strategy Selection , 1990 .

[30]  Madeleine E. Pullman,et al.  AN ANALYSIS OF THE SUPPLIER SELECTION PROCESS , 1998 .

[31]  M. Dotoli,et al.  Balancing the additional costs of purchasing and the vendor set dimension to reduce public procurement costs , 2012 .

[32]  Ali Emrouznejad,et al.  Evaluation of research in efficiency and productivity: A survey and analysis of the first 30 years , 2008 .

[33]  Harald Tauchmann.  orderalpha: Nonparametric order-α efficiency analysis for Stata , 2011 .

[34]  Srinivas Talluri,et al.  A note on "A methodology for supply base optimization" , 2005, IEEE Transactions on Engineering Management.

[35]  Xiaowei Xu,et al.  Multi-criteria decision making approaches for supplier evaluation and selection: A literature review , 2010, Eur. J. Oper. Res..

[36]  Chiang Kao,et al.  Stochastic data envelopment analysis in measuring the efficiency of Taiwan commercial banks , 2009, Eur. J. Oper. Res..

[37]  Fabio Sciancalepore,et al.  Using a DEA-cross efficiency approach in public procurement tenders , 2012, Eur. J. Oper. Res..

[38]  P. W. Wilson,et al.  ASYMPTOTICS AND CONSISTENT BOOTSTRAPS FOR DEA ESTIMATORS IN NONPARAMETRIC FRONTIER MODELS , 2008, Econometric Theory.

[39]  R. Ramanathan.  Supplier selection problem: integrating DEA with the approaches of total cost of ownership and AHP , 2007 .

[40]  Mariagrazia Dotoli,et al.  A decision support system framework for purchasing management in supply chains , 2009 .

[41]  Shanling Li,et al.  Selection of contract suppliers under price and demand uncertainty in a dynamic market , 2009, Eur. J. Oper. Res..

[42]  R. G. Dyson,et al.  Data envelopment analysis, operational research and uncertainty , 2010, J. Oper. Res. Soc..

[43]  Ramayya Krishnan,et al.  A hybrid approach to supplier selection for the maintenance of a competitive supply chain , 2008, Expert Syst. Appl..

[44]  Juliang Zhang,et al.  Supplier selection and purchase problem with fixed cost and constrained order quantities under stochastic demand , 2011 .

[45]  C. Weber,et al.  Determination of paths to vendor market efficiency using parallel coordinates representation: A negotiation tool for buyers , 1996 .

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

[47]  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..

[48]  Riccardo Dulmin,et al.  Supplier selection using a multi-criteria decision aid method , 2003 .

[49]  Manoj Kumar Tiwari,et al.  Green supply chain performance measurement using fuzzy ANP-based balanced scorecard: a collaborative decision-making approach , 2014 .

[50]  Lei Li,et al.  Incorporating uncertainty into a supplier selection problem , 2011 .