Supplier Selection by the Pair of Nondiscretionary Factors-Imprecise Data Envelopment Analysis Models

Islamic Azad University, Karaj, Iran
Journal of the Operational Research Society (Impact Factor: 0.91). 10/2009; 60(11). DOI: 10.1057/jors.2008.154
Source: OAI

ABSTRACT Discretionary models for evaluating the efficiency of suppliers assume that all criteria are discretionary, that is, controlled by the management of each supplier and varied at its discretion. These models do not assume supplier selection in the conditions that some factors are nondiscretionary. The objective of this paper is to propose a new pair of nondiscretionary factors-imprecise data envelopment analysis (NF-IDEA) models for selecting the best suppliers in the presence of nondiscretionary factors and imprecise data. A numerical example demonstrates the application of the proposed method. Yes Yes

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    • "Comparison of the operational capabilities of 10 suppliers to an auto lighting system OEM in Taiwan Demonstrates the use of the fuzzy AHP method and fuzzy DEA for assisting organisations to make the supplier selection decision Saranga and Moser (2010) Comparison of 120 firms across the globe with > US $3 billion turnover Demonstrates the use of a two-stage value chain DEA method for purchasing and supply management performance evaluation Jalalvand, et al. (2011) Comparison of supply chain (SC) performance of seven SCs in the Iran broiler industry Demonstrates the use of DEA and PROMETHEE II, as tools to compare SCs at the process level, business stage level and whole SC level Liang, Li, Cook, and Zhu (2011) Comparison of the supply chain performance of 50 Chinese universities Demonstrates the use of DEA to model efficiency in twostage serial processes where feedback variables are present Note: The applications of DEA in the specific related sub-field of supplier selection/rating; for example, Saen (2009), which demonstrates non-discretionary factors–imprecise DEA models for supplier selection, are too numerous to include in this table. Recent examples can be found in "
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    Production Planning and Control 10/2014; 25(13-14). DOI:10.1080/09537287.2013.808838 · 0.99 Impact Factor
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    • "Finally, DEA is a performance assessment tool since it estimates relative efficiency of a set of decision making units (DMUs). DMUs are entities which consume multiple inputs to produce multiple outputs (Farzipoor Saen, 2009; Azadi and Farzipoor Saen, 2012). One of the significant uses of DEA is to set targets for inefficient DMUs. "
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    Transportation Research Part E Logistics and Transportation Review 10/2014; 70:324–338. DOI:10.1016/j.tre.2014.07.009 · 2.27 Impact Factor
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    • "To select the best suppliers in the presence of both cardinal and ordinal data, Farzipoor Saen (2007) proposed a method, which is based on Imprecise Data Envelopment Analysis (IDEA). Farzipoor Saen (2009a) proposed a new pair of nondiscretionary factors-imprecise data envelopment analysis (NF-IDEA) models for selecting the best suppliers in the presence of nondiscretionary factors and imprecise data. Again, Farzipoor Saen (2009b) proposed a model for ranking suppliers in the presence of weight restrictions, nondiscretionary factors, and cardinal and ordinal data. "
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