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This research aims to comprehensively analyse the Agri-food supply chain, by identifying the barriers, and considering effective pathways towards a green supply chain. To the best of our knowledge, in the research area of supply chain, the majority of the research is oriented towards the evaluation of barriers and pathways or drivers to the implementation of green supply chain management in the manufacturing industry. The field of Agri-food is among the sectors of concern due to the quantum and basic necessity of the industry.

The contribution of this paper is to develop and evaluate a general framework of the most relevant barriers and possible pathways towards the green Agri-food supply chain, with the help of a hybrid approach combining both the ANP and ELECTRE I methods, via a case study of the fish canning industry.

Furthermore, the study findings will help both academicians and practitioners in developing and evaluating green supply chain frameworks in this area of study.

The results of this study show that the cost of greening the supply in terms of implementing sustainability standard, or advanced technology are the most relevant barriers, and that the social and operational pathways family is among the best effectives pathways.

Green supply chain (GSC) modelling is still evolving, yet according to the literature, there is no standard and comprehensive approach for modelling GSCs. This chapter attempts to examine this remarkable gap in research by proposing a standard approach for industrial supply chain (SC) modelling, which allows integrating all relevant environmental constraints. This new approach is inspired from other methodologies proposed earlier regardless of their area of study and implemented via a case study in fish canning industry. The steps of the proposed approach are based on Artificial Intelligence (AI), which has become a mainstream trend nowadays. The proposed approach may help managers and researchers and could provide a guideline for GSC modelling.