Identifying barriers to big data analytics adoption in circular agri-food supply chains: a case study in Turkey

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Abstract
Big data analytics (BDA), along with the resource efficiency and sustainability perspectives of a circular economy, supports the transition to circular agri-food supply chains (AFSCs), contributing to a country’s achievement of the United Nations’ Sustainable Development Goals. However, there is still limited research demonstrating the importance and awareness of BDA implementation in circular AFSCs in developing countries. As a result of the barriers to BDA adoption in these regions, circular AFSCs in developing countries are still in their infancies. This study sought to identify the barriers to BDA adoption in circular AFSCs in Turkey using a Delphi-based Pythagorean fuzzy analytic hierarchy process. The proposed method removes the potential for bias and produces consensus among managers of companies in various AFSCs in Turkey. The findings of this study show that the most impactful barriers to BDA are technical, economic and social, followed by environmental and organisational. The most crucial sub-barriers to BDA adoption are “lack of trust, privacy and security”, “lack of financial resources” and “lack of skilled human resources”. This research can guide industry managers and policymakers in the development of strategies for overcoming barriers to BDA adoption in circular AFSCs in developing nations.

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