Modelling the enablers of Industry 4.0 technology adoption in agricultural supply chains in emerging economies

Purpose The adoption of Industry 4.0 is critical for the post-pandemic recovery and growth of the agricultural sector, particularly in developing economies, where it can boost productivity, increase income, reduce poverty and create jobs. This study aims to identify, model and prioritize key enablers for Industry 4.0 adoption in Thailand’s agricultural sector. Design/methodology/approach The study identified and validated 10 key enablers through a comprehensive literature review and semi-structured interviews with key stakeholders. Interpretive structural modelling (ISM) was used to gain insights into the hierarchical structure and complex interrelationships among enablers. The cross-impact matrix multiplication applied to classification (MICMAC) analysis clustered the enablers into four groups (autonomous, dependent, linkage and driver) based on their ability to drive change and their dependency on other factors. Findings Government regulation and policies emerged as the enabler with the highest driver power influencing other enablers. A firm’s top management involvement/support, awareness and capacity-building programmes, stakeholder collaboration and partnerships were found to be de-pendent on other enablers. The ISM model and MICMAC analysis highlighted the enablers needing prioritization. Research limitations/implications This study focused on the Thai agricultural sector as the context for the findings. The identification and prioritization of enablers offer a foundation for future research and the exploration of similar enablers in different sectors or economies. Originality/value This is the first comprehensive investigation to identify and model the enablers of Industry 4.0 adoption in agricultural supply chains in emerging economies, indicating a significant contribution to the existing literature.