A review of halal supply chain research: Sustainability and operations research perspective

This paper presents a comprehensive literature review of halal supply chain optimization from the perspective of sustainability and the application of operation research (OR) methodology. There are three issues in the halal supply chain that could describe its close relationship with sustainability. The first is halal integrity to ensure the halal-ness of a product. The second is the limited adoption of halal supply chain, and the third issue is limited number of studies that discuss sustainability in halal supply chain. To the best of our knowledge, there are very few researches in halal supply chain, particularly which consider sustainability in halal supply chain and which apply operation research (OR) method. The literature review is done through a comprehensive review of publications from 2000 to 2022. The review papers are classified based on eight categories in the taxonomy developed in this study. This paper may contribute to giving comprehensive review and identifying research challenges in sustainable halal supply chain optimization with OR approach. Based on the review, halal supply chain studies have been showing an increasing trend starting from 2011. Most publications are from Malaysia, while Indonesia comes second even though Indonesia has the largest Moslem population in the world. Most of the studies focus on whole supply chain and strategic decision level. Limited research is found in operation level decision. Most of the study focus on the study of food and beverages. Only a few studies have considered sustainability issue in halal supply chain. The review found that there is a balance between the application of quantitative and qualitative approach in halal supply chain. However artificial intelligence (AI) approach has not yet been applied in the research area of halal supply chain. Based on those findings, it is necessary to conduct more studies in the area of halal supply chain and relate it with sustainability using OR/AI methodology.