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Performance Measurement with Fuzzy Data Envelopment Analysis pp 271–285Cite as

Supplier Performance Evaluation Using a Hybrid Fuzzy Data Envelopment Analysis Approach

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Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 309))

Abstract

Supplier performance evaluation plays a prime role in supplier quality development and controlling the cost of quality in supply chains. In this book chapter, we present a multistep approach based on fuzzy data envelopment analysis (DEA) approach for supplier quality evaluation. The criteria for supplier performance evaluation are obtained using Delphi technique. The hierarchy for the criteria and preferential relations between them are developed using the principles of analytic hierarchy process (AHP). Supplier performance evaluation is performed using fuzzy data envelopment analysis. Cross-efficiencies for performance evaluation minimize distance from the Ideal DMUs and maximize distance from the anti-ideal DMUs. A numerical illustration is provided.

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Author information

Authors and Affiliations

  1. CIISE—EV 7.640, Concordia University, Montreal, Canada

    Anjali Awasthi

  2. CIISE—EV 10.154, Concordia University, Montreal, Canada

    Khoshrow Noshad

  3. Decision Sciences, JMSB, Concordia University, Montreal, Canada

    Satyaveer Singh Chauhan

Authors
  1. Anjali Awasthi
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  2. Khoshrow Noshad
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  3. Satyaveer Singh Chauhan
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Corresponding author

Correspondence to Anjali Awasthi .

Editor information

Editors and Affiliations

  1. Operations and Information Management Group, Aston Business School, Aston University, Birmingham, United Kingdom

    Ali Emrouznejad

  2. Business Systems and Analytics Department, La Salle University, Philadelphia, Pennsylvania, USA

    Madjid Tavana

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© 2014 Springer-Verlag Berlin Heidelberg

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Awasthi, A., Noshad, K., Chauhan, S.S. (2014). Supplier Performance Evaluation Using a Hybrid Fuzzy Data Envelopment Analysis Approach. In: Emrouznejad, A., Tavana, M. (eds) Performance Measurement with Fuzzy Data Envelopment Analysis. Studies in Fuzziness and Soft Computing, vol 309. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41372-8_14

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  • DOI: https://doi.org/10.1007/978-3-642-41372-8_14

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-41371-1

  • Online ISBN: 978-3-642-41372-8

  • eBook Packages: EngineeringEngineering (R0)

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