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Investigating Enablers to Improve Transparency in Sustainable Food Supply Chain Using F-BWM

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Intelligent and Fuzzy Techniques: Smart and Innovative Solutions (INFUS 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1197))

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Abstract

Food Supply Chains (FSC) are complex and dynamic in behavior and prone to increasing risks of unsustainability. Consumers increasingly demand food quality, safety, and sustainability, which are fast becoming issues of great importance in FSC. Lack of real-time information sharing and connectivity among stakeholders make these issues tougher to mitigate. Supply chain transparency (SCT) is thus an essential attribute to manage these supply chain complexities and enhance the sustainability of FSC. The paper identifies and analyses key enablers for SCT in FSC. Several technical, as well as sustainability-related enablers, contribute to the implementation of SCT. The identified enablers are analyzed using Fuzzy-best worst methodology (F-BWM), which determine the most critical factors using the decision maker’s opinion. Extending BWM with fuzzy logic incorporates the vagueness of human-behaviour into decision making approach. The results of this research provides decision makers with the priority of enablers to the decision maker. Enhancing these enablers in will help improve the transparency for better management of FSC. The article expands upon the practical as well as theoretical implications of SCT on sustainability in FSC. It addresses the requirement of including sustainability in the decision-making process. The results demonstrate the effectiveness of the F-BWM for the decision making process. The study is conducted by considering downstream supply chain activities in Indian context. It is one of the first studies that analyzes SCT enablers using F-BWM method in Indian context. The study contributes towards improving the environmental, economical, and social sustainability of FSC.

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Author information

Authors and Affiliations

  1. Department of Mechanical and Industrial Engineering, Indian Institute of Technology, Roorkee, 247667, Uttrakhand (UK), India

    Anish Kumar & Pradeep Kumar

  2. Knowledge Management and Business Decision Making, Plymouth Business School, University of Plymouth, Plymouth, PL48AA, UK

    Sachin Kumar Mangla

  3. Department of Industrial Engineering, Turkish-German University, 34820, Istanbul, Turkey

    Yasanur Kayikci

Authors
  1. Anish Kumar
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  2. Sachin Kumar Mangla
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  3. Pradeep Kumar
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  4. Yasanur Kayikci
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Corresponding author

Correspondence to Yasanur Kayikci .

Editor information

Editors and Affiliations

  1. Department of Industrial Engineering, Istanbul Technical University, Istanbul, Turkey

    Cengiz Kahraman

  2. Department of Industrial Engineering, Istanbul Technical University, Istanbul, Turkey

    Sezi Cevik Onar

  3. Department of Industrial Engineering, Istanbul Technical University, Ä°stanbul, Turkey

    Basar Oztaysi

  4. Department of Industrial Engineering, Istanbul Technical University, Istanbul, Turkey

    Irem Ucal Sari

  5. Industrial Engineering Department, Yildiz Technical University, Istanbul, Turkey

    Selcuk Cebi

  6. Industrial Engineering Department, Galatasaray University, Istanbul, Turkey

    A. Cagri Tolga

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Kumar, A., Mangla, S.K., Kumar, P., Kayikci, Y. (2021). Investigating Enablers to Improve Transparency in Sustainable Food Supply Chain Using F-BWM. In: Kahraman, C., Cevik Onar, S., Oztaysi, B., Sari, I., Cebi, S., Tolga, A. (eds) Intelligent and Fuzzy Techniques: Smart and Innovative Solutions. INFUS 2020. Advances in Intelligent Systems and Computing, vol 1197. Springer, Cham. https://doi.org/10.1007/978-3-030-51156-2_65

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