A Decision Support Model for Cost-Effective Choice of Temperature-Controlled Transport of Fresh Food

Lohithaksha M. Maiyar (), Ramakrishnan Ramanathan, Indira Roy and Usha Ramanathan
Additional contact information
Lohithaksha M. Maiyar: Department of Entrepreneurship and Management, Indian Institute of Technology Hyderabad, Kandi 502284, India
Ramakrishnan Ramanathan: Essex Business School, University of Essex–Southend Campus, Elmer Approach, Southend-on-Sea, Essex SS1 1LW, UK
Indira Roy: Department of Entrepreneurship and Management, Indian Institute of Technology Hyderabad, Kandi 502284, India
Usha Ramanathan: Nottingham Business School, Nottingham Trent University, Nottingham NG1 4FQ, UK

Sustainability, 2023, vol. 15, issue 8, 1-22

Abstract: The application of a plethora of wireless technologies to support real-time food quality monitoring during transportation has significantly improved the performance of fresh food delivery systems. However, deployment of these technologies increases the capital and operational costs of food delivery and, hence, not all food delivery operations need to employ them. This paper looks at the trade-off of the costs involved in utilizing these technologies with the nature of food delivered, the length of transportation, and the perceived costs of food wasted using a linear programming model. The problem is formulated over a bi-echelon network with the possibility of transporting the fresh produce through dry vans, vans with temperature control but without monitoring capability, and vans with temperature control and monitoring capability. Results indicate that under situations of infinite vehicle resource availability, the optimal choice of the van type is independent of the demand levels; however, the optimal choice changes for different travel distances and the value of penalty costs (of allowing food to go waste). For example, technologies that maintain and monitor the temperature of storage conditions will be useful for food items that quickly become waste, especially when transported over longer distances and when the penalty costs are higher.

Keywords: Internet of Things sensors; temperature control; temperature monitoring; decision support model; food waste; food supply chains (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/15/8/6821/pdf (application/pdf)
https://www.mdpi.com/2071-1050/15/8/6821/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:15:y:2023:i:8:p:6821-:d:1126522

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().