An Interval Valued Type 2 Intuitionistic Fuzzy Approach to Analyze the Barriers of Adopting Internet of Things in the Agriculture Supply Chain: Implications for Sustainable Development Goals

A supply chain connects organizations and individuals to produce and deliver an item to the last purchaser, including different information, resources, and activities. The agriculture supply chain is arguably the most intricate compared to other supply chains. Smart agriculture powered by IoT has the potential to significantly transform the agricultural sector by enhancing monitoring and management, reducing risks, raising production, and strengthening resilience to climate change. This research aims to examine operational and supply chain barriers to Internet of Things (IoT) adoption in the agriculture industry of an emerging economy. The barriers were identified based on a literature review and expert opinions. Then, the Interval Valued Type 2 Intuitionistic Fuzzy- decision-making trial and evaluation laboratory (DEMATEL) method is utilized to explore the causal and effect relations among the critical barriers of the agriculture supply chain. This study identifies 17 barriers under 4 significant categories of the agriculture supply chain. The results indicate that, “Unaffordability and uncertainty of technological advancement”, “Inadequacy of strong financial backing”, “Lack of standardization and regulations” and “Lack of guarantee on reliability, availability, and robustness” have the most significant impact on the whole process in the context of agriculture supply chain. The outcomes offer reasonable guidelines for partners and government strategy makers to improve the public supply chain in developing countries. The study discovers the indispensable and causal links, which have been undervalued so far, among agriculture supply chain barriers in an emerging economy context. In order to create a strong, sustainable agri-food supply chain, the practitioners can use the framework as a guide when planning their investments.