A NEW REVERSE LOGISTICS APPROACH TO REDUCE WASTE IN THE RETAIL STORE

Abstract

Purpose: Take back policy is nothing new for other manufacturing industries. But for fruit retail, it is difficult to implement returning the fruit to any previous processes due to perishability. The purpose of this thesis is to explore the retail strategies in reverse supply chains and to develop a decision support system for prioritization of these strategies for effective reverse logistics implementation in the fruits and vegetables industry. Design/methodology/approach: Based on a literature review, different reverse logistics criteria and approaches for fruits and vegetables have been selected, and fuzzy AHP TOPSIS methodology is used to prioritize fruit-specific reverse logistics processes. Research Application: Sorting the fruits and vegetables according to the anomaly, abnormal shape, partially rotten, or strain on fruit skin is useful for the retailers to separate and initiate preliminary reverse logistics activity. The manager can take prior disposal or promotion strategies for those fruits and vegetables. It will cause a reduction in ultimate food waste. For that reason, a Fuzzy-AHP TOPSIS method has been established in this thesis which will provide the reverse process decision based on the fruit condition at any point of the retail journey of that fruit. Originality/value: According to the literature review, there are very few studies on the reverse logistics of the fruits and vegetables supply chain. However, promotion implication and disposition decision based on prioritization is not the first-time exploration for fruit retail to increase reverse logistics awareness. The thesis shows a unique way to use a prioritization technique to make decisions about what to do with suboptimal fruit in a store's display case. It helps the store owner keep track of the prices of fruits at all times and find problem fruits early, which would otherwise be thrown away. Case Plan: A case of a fruits and vegetables retail shop in Qatar is discussed for the illustration and validation of the methodology. Findings: Fruits and vegetable diagnosis and inspection is a crucial part of quality control and health safety. From harvesting to retailing, stakeholders encounter tons of food losses due to the lack of monitoring of the fruit condition in retail, the problem gets worse because it is being handled by many people, including retailers and customers. We propose a transparent fiberglass-made vertical fruit showcase, which provides 80 percent more visibility, takes lesser shop space, and prevents human contact. It is convenient for the retailer and customer to use and the controlled fruit environment is easy to integrate with IoT which will help to generate consensus data for fruit management decisions in machine learning. The final comparative assessment between the conventional selling method and the proposed method shows a significant decrease in waste generation in the reverse logistics processing method. Conclusion: The thesis is concluded with future directions of machine learning integration to increase the robustness of the proposed method. The managerial takeaways and the limitations of the thesis are also identified. Keywords: AHP, TOPSIS, Fruits and vegetable waste, Retail, Qatar

Date of Award	2023
Original language	American English
Awarding Institution	HBKU College of Science and Engineering