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Fuzzy AHP, DEA, and Managerial Analysis for Supplier Selection and Development; From the Perspective of Open Innovation

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  • Maimouna Diouf

    (School of Business, Pusan National University, Busan 46241, Korea)

  • Choonjong Kwak

    (School of Business, Pusan National University, Busan 46241, Korea
    Director, Pusan National University Press, Pusan National University, Busan 46241, Korea)

Abstract

Supplier management is critical for supply chain management (SCM). The aim of supplier selection is to find an order of preference among potential suppliers. However, the ranking results for supplier selection may not be important, particularly when the performances are conflicting or have minor differences. Different criteria may have different impacts on the ranking results, and different decision makers may place different priorities on multiple criteria. Relatively worse suppliers may still have to be used for many practical reasons. One alternative is supplier development, but it has been focused on categorizing individual suppliers for possible action plans. A new framework is proposed in this research to address supplier selection and supplier development at the same time in the publishing and printing industries. First, the fuzzy analytical hierarchy process (fuzzy AHP) and data envelopment analysis (DEA) are sequentially performed to rank and select the best supplier(s) of a publishing company. In addition to ranking suppliers, a managerial analysis is proposed to assess the impact of important criteria on supplier selection in more detail. Finally, the results of the DEA are provided for direct supplier development without supplier categorization. This research shows that the proposed framework effectively addresses supplier development as well as supplier selection in the publishing and printing industries.

Suggested Citation

  • Maimouna Diouf & Choonjong Kwak, 2018. "Fuzzy AHP, DEA, and Managerial Analysis for Supplier Selection and Development; From the Perspective of Open Innovation," Sustainability, MDPI, vol. 10(10), pages 1-17, October.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:10:p:3779-:d:176829
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    References listed on IDEAS

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    Cited by:

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    2. Mangirdas Morkunas & Elzė Rudienė & Lukas Giriūnas & Laura Daučiūnienė, 2020. "Assessment of Factors Causing Bias in Marketing- Related Publications," Publications, MDPI, vol. 8(4), pages 1-16, October.
    3. Lizhong Tong & Zhongmin Pu & Jizheng Ma, 2019. "Maintenance Supplier Evaluation and Selection for Safe and Sustainable Production in the Chemical Industry: A Case Study," Sustainability, MDPI, vol. 11(6), pages 1-15, March.
    4. Patricija Bajec & Danijela Tuljak-Suban & Eva Zalokar, 2021. "A Distance-Based AHP-DEA Super-Efficiency Approach for Selecting an Electric Bike Sharing System Provider: One Step Closer to Sustainability and a Win–Win Effect for All Target Groups," Sustainability, MDPI, vol. 13(2), pages 1-24, January.
    5. Min-Sung Kim & Eul-Bum Lee & In-Hye Jung & Douglas Alleman, 2018. "Risk Assessment and Mitigation Model for Overseas Steel-Plant Project Investment with Analytic Hierarchy Process—Fuzzy Inference System," Sustainability, MDPI, vol. 10(12), pages 1-17, December.
    6. Pankaj Dutta & Bharath Jaikumar & Manpreet Singh Arora, 2022. "Applications of data envelopment analysis in supplier selection between 2000 and 2020: a literature review," Annals of Operations Research, Springer, vol. 315(2), pages 1399-1454, August.
    7. Chia-Nan Wang & Van Thanh Nguyen & Hoang Tuyet Nhi Thai & Ngoc Nguyen Tran & Thi Lan Anh Tran, 2018. "Sustainable Supplier Selection Process in Edible Oil Production by a Hybrid Fuzzy Analytical Hierarchy Process and Green Data Envelopment Analysis for the SMEs Food Processing Industry," Mathematics, MDPI, vol. 6(12), pages 1-16, December.
    8. Mei Tang & Jie Wang & Jianping Lu & Guiwu Wei & Cun Wei & Yu Wei, 2019. "Dual Hesitant Pythagorean Fuzzy Heronian Mean Operators in Multiple Attribute Decision Making," Mathematics, MDPI, vol. 7(4), pages 1-27, April.

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