Valuation of inter-boundary inefficiencies accounting IoT based monitoring system in processed food supply chain

Janpriy Sharma, Mohit Tyagi () and Arvind Bhardwaj
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Janpriy Sharma: Dr. B R Ambedkar National Institute of Technology
Mohit Tyagi: National Institute of Technology
Arvind Bhardwaj: Dr. B R Ambedkar National Institute of Technology

International Journal of System Assurance Engineering and Management, 2024, vol. 15, issue 4, No 5, 1374-1396

Abstract: Abstract Nowadays, demand for processed food items is escalating towards the record consumption volume, which resulted in the surging of the Food Supply Chain (FSCs) network. But, the flow of the commodities through the various channels of the FSC is hampered by the various inefficiencies, which persist due to a lack of monitoring. This results in the widening of the gap between the supply and demand patterns allied with it. To tackle the same, and cater to the upwelling shares of the consumer demand, the dynamics of the Food Supply Chain Performance System (FSCPS) need to be tuned with the avenues of Industry 4.0 practices. Presented work clusters the various attributes of the inefficiencies, which hampers the processed FSCs dynamics and maintenance-related activities, elaborated by their sub-attributes based upon their events of occurrences. A model comprising the various attributes and sub-attributes of inefficiencies constrained outside the organizational boundaries of a firm’s FSC is rendered in this study. For effective handling of the mutual interdependencies persisting between the attributes, the methodology of the Graph Theory and Matrix Approach (GTMA) is exercised for the analysis of the developed model. Outcomes of the presented work felicitate the managers of industries, its allied corporates and numerous stakeholders of the FSC to ground a robust decisional framework, governing policies and managing the process permutations.

Keywords: Food supply chains; Inter-organization inefficiencies; Internet of things; System monitoring; Graph theory and matrix approach (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s13198-022-01840-w

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