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Modeling causal factors of post-harvesting losses in vegetable and fruit supply chain: An Indian perspective

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  • Gardas, Bhaskar B.
  • Raut, Rakesh D.
  • Narkhede, Balkrishna

Abstract

The crops of vegetables and fruits help farmers in generating employment, and increasing their income. This sector also provides nutritional security to the people in the remote as well as urban areas. The objective of this paper is to identify and model the causal factors of the post-harvesting losses in the Indian context. Through exhaustive literature survey and expert opinions, fourteen critical factors were identified, and the interpretive structural modeling (ISM) approach was used to establish an interrelationship among the defined factors and to determine the key criteria having high driving power. The research work is carried out in two parts, in Part- I inputs were taken from the experts of academia, and in Part-II inputs from the field experts were considered. Results obtained from both the cases were compared and discussed. After analyzing the factors, in two parts it was found that three factors, namely lack of linkages between industry, Government, and institution (B8), lack of technology and advanced technique in food processing (B10), and lack of linkage between farmers and processing unit (B6), were found to be the most significant factors. The developed ISM model is intended to guide the supply chain members at various stages and levels to achieve sustainability in social, economic, & ecological dimensions and increase efficiency of the vegetable and fruit supply chain by eliminating the crucial factors causing post-harvesting losses.

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  • Gardas, Bhaskar B. & Raut, Rakesh D. & Narkhede, Balkrishna, 2017. "Modeling causal factors of post-harvesting losses in vegetable and fruit supply chain: An Indian perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 1355-1371.
  • Handle: RePEc:eee:rensus:v:80:y:2017:i:c:p:1355-1371
    DOI: 10.1016/j.rser.2017.05.259
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    2. Raut, Rakesh D. & Priyadarshinee, Pragati & Gardas, Bhaskar B. & Jha, Manoj Kumar, 2018. "Analyzing the factors influencing cloud computing adoption using three stage hybrid SEM-ANN-ISM (SEANIS) approach," Technological Forecasting and Social Change, Elsevier, vol. 134(C), pages 98-123.
    3. Abdelrahman Ali & Chunping Xia & Moustafa Ismaiel & N’Banan Ouattara & Irfan Mahmood & Dessalegn Anshiso, 2021. "Analysis of determinants to mitigate food losses and waste in the developing countries: empirical evidence from Egypt," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 26(6), pages 1-26, August.
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    5. Peyman Zandi & Mohammad Rahmani & Mojtaba Khanian & Amir Mosavi, 2020. "Agricultural Risk Management Using Fuzzy TOPSIS Analytical Hierarchy Process (AHP) and Failure Mode and Effects Analysis (FMEA)," Agriculture, MDPI, vol. 10(11), pages 1-27, October.
    6. Monika Verma & Christine Plaisier & Coen P. A. van Wagenberg & Thom Achterbosch, 2019. "A Systems Approach to Food Loss and Solutions: Understanding Practices, Causes, and Indicators," Sustainability, MDPI, vol. 11(3), pages 1-22, January.
    7. Gaurvendra Singh & Yash Daultani & Rajendra Sahu, 2022. "Investigating the barriers to growth in the Indian food processing sector," OPSEARCH, Springer;Operational Research Society of India, vol. 59(2), pages 441-459, June.
    8. Daniel Faibil & Martin Agyemang & Owusu Amponsah & Himanshu Gupta & Simonov Kusi-Sarpong, 2021. "Assessing drivers of post-harvest losses: tangible and intangible resources’ perspective," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(11), pages 15785-15829, November.
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