Optimizing Food Traceability Technologies in Manufacturing Industries: A Multi-Criteria Decision Analysis Using TOPSIS

Abstract

As food safety concerns continue to escalate, robust food traceability systems have become a critical necessity in the food manufacturing industry. A comprehensive analysis of novel technologies and traceability techniques has been presented in this study. These technologies and approaches include Radio Frequency Identification (RFID), barcode technology, blockchain, Internet of Things (IoT), DNA barcoding and enterprise resource planning (ERP). The research aims to determine which of these novel technologies offers the ideal solution for effective food traceability technology by using the TOPSIS approach. The analysis encompasses a comprehensive examination of the primary factors such as cost, accuracy, compatibility, reliability, scalability, data security & privacy, and user-friendliness affecting technology selection, accompanied by weighted allocations for each aspect. Emphasising the critical role of Food Traceability Systems (FTS) in averting recent outbreaks, the study also integrates insights from expert opinion interviews along with comprehensive surveys, involving eleven experts with diverse professional backgrounds and experience levels ranging from 1 to 18 years, including roles such as quality control, factory and production management. Findings from this study underscore the importance of balancing technological efficiency with industry-specific practicalities. While barcode technology remains dominant, achieving a performance score of 0.699, IoT closely followed barcode technology with a performance score of 0.523, while blockchain DNA Barcoding, ERP, and RFID 0.448, 0.386, 0.368, and 0.306 followed respectively, each presenting unique trade-offs requiring strategic managerial consideration. This research provides valuable insights for food manufacturers seeking to optimize their traceability strategies and ensure compliance with evolving food safety regulations however future advancements in AI and machine learning-driven traceability systems may shift industry preferences.