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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

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  • Chia-Nan Wang

    (Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung 80778, Taiwan
    Department of Industrial Engineering and Management, Fortune Institute of Technology, Kaohsiung 81160, Taiwan)

  • Van Thanh Nguyen

    (Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung 80778, Taiwan
    Department of Industrial Systems Engineering, CanTho University of Technology, Can Tho 900000, Vietnam)

  • Hoang Tuyet Nhi Thai

    (Department of Industrial Systems Engineering, CanTho University of Technology, Can Tho 900000, Vietnam)

  • Ngoc Nguyen Tran

    (Department of Industrial Systems Engineering, CanTho University of Technology, Can Tho 900000, Vietnam)

  • Thi Lan Anh Tran

    (Department of Industrial Systems Engineering, CanTho University of Technology, Can Tho 900000, Vietnam)

Abstract

Today, business organizations are facing increasing pressure from a variety of sources to operate using sustainable processes. Thus, most companies need to focus on their supply chains to enhance sustainability to meet customer demands and comply with environmental legislation. To achieve these goals, companies must focus on criteria that include CO 2 (carbon footprint) and toxic emissions, energy use and efficiency, wastage generations, and worker health and safety. As in other industries, the food processing industry requires large inputs of resources, which results in several negative environmental effects; thus, decision-makers have to evaluate qualitative and quantitative factors. This work identifies the best supplier for edible oil production in the small and medium enterprise (SME) food processing industry in Vietnam. This study also processes a hybrid multicriteria decision-making (MCDM) model using a fuzzy analytical hierarchy process (FAHP) and green data envelopment analysis (GDEA) model to identify the weight of all criteria of a supplier’s selection process based on opinions from company procurement experts. Subsequently, GDEA is applied to rank all potential supplier lists. The primary objective of this work is to present a novel approach which integrates FAHP and DEA for supplier selection and also consider the green issue in edible oil production in uncertain environments. The aim of this research is also to provide a useful guideline for supplier selection based on qualitative and quantitative factors to improve the efficiency of supplier selection in the food industry and other industries. The results reveal that Decision-Making Unit 1 (DMU 1), DMU 3, DMU 7, and DMU 9 are identified as extremely efficient for five DEA models, which are the optimal suppliers for edible oil production. The contributions of this research include a proposed MCDM model using a hybrid FAHP and GDEA model for supplier selection in the SME food processing industry under a fuzzy environment conditions in Vietnam. This research also is part of an evolution of a new hybrid model that is flexible and practical for decision-makers. In addition, the research also provides a useful guideline in supplier selection in the food processing industry and a guideline for supplier selection in other industries.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jmathe:v:6:y:2018:i:12:p:302-:d:187907
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    References listed on IDEAS

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    2. Morteza Yazdani & Dragan Pamucar & Prasenjit Chatterjee & Ali Ebadi Torkayesh, 2022. "“A multi-tier sustainable food supplier selection model under uncertainty”," Operations Management Research, Springer, vol. 15(1), pages 116-145, June.
    3. Mishra, Arunodaya Raj & Mardani, Abbas & Rani, Pratibha & Kamyab, Hesam & Alrasheedi, Melfi, 2021. "A new intuitionistic fuzzy combinative distance-based assessment framework to assess low-carbon sustainable suppliers in the maritime sector," Energy, Elsevier, vol. 237(C).
    4. Fengsheng Chien & Chia-Nan Wang & Ka Yin Chau & Van Thanh Nguyen & Viet Tinh Nguyen, 2021. "Sustainability in the Business Sector: A Fuzzy Multicriteria Decision-Making Model for Financial Leasing Company Selection of the Vietnamese SMEs," SAGE Open, , vol. 11(3), pages 21582440211, July.
    5. Katerina Fotova Čiković & Ivana Martinčević & Joško Lozić, 2022. "Application of Data Envelopment Analysis (DEA) in the Selection of Sustainable Suppliers: A Review and Bibliometric Analysis," Sustainability, MDPI, vol. 14(11), pages 1-30, May.
    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. Özlem Arslan & Necip Karakurt & Ecem Cem & Selcuk Cebi, 2023. "Risk Analysis in the Food Cold Chain Using Decomposed Fuzzy Set-Based FMEA Approach," Sustainability, MDPI, vol. 15(17), pages 1-20, September.
    8. Monica Aureliana Petcu & Liliana Ionescu-Feleaga & Bogdan-Ștefan Ionescu & Dumitru-Florin Moise, 2023. "A Decade for the Mathematics : Bibliometric Analysis of Mathematical Modeling in Economics, Ecology, and Environment," Mathematics, MDPI, vol. 11(2), pages 1-30, January.

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