Study on enhancing consumers’ purchase intention in E-commerce agricultural products

Purpose The purpose of this paper is to utilize the ISM–MICMAC–AHP integrated method to determine the factors influencing consumers’ purchase intention towards e-commerce agricultural products and develop a model, as well as to explore strategies to enhance consumers’ purchase intention. Design/methodology/approach The study conducts an exhaustive literature review and gathered expert opinions to identify 20 influencing factors across five dimensions, constructing a comprehensive factor system. The Interpretative Structural Modelling (ISM) method is used determine the hierarchical structure and interrelationships among these factors. Subsequently, Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) analysis is done to assess the influence and dependence relationships among the factors in the system. Finally, Analytic Hierarchy Process method is proposed to distribute assessment indicators weights. Findings The system of factors influencing consumers’ intention to purchase agricultural products through e-commerce is constructed as a six-level hierarchical interpretive structural model. The quality and safety of agricultural products, consumer review, taste and mouth-feel of agricultural products and e-commerce platform reputation are the main factors that affect consumers’ intention to purchase e-commerce agricultural products. Consumers’ degree of education, age and level of income exhibit the highest driving force, while e-commerce platform reputation demonstrates the highest level of dependence. Originality/value This paper represents the first attempt to employ an ISM-MICMAC-AHP integrated method to study consumers’ purchase intention for e-commerce agricultural products. The findings offer actionable insights for e-commerce platforms and policymakers, highlighting critical factors like product quality and platform reputation, which can inform strategies to enhance consumer trust and drive sustainable growth in agricultural e-commerce. This research supports evidence-based decision-making, promoting more effective management practices and policy development in the sector

Agriculture · Analytic hierarchy process · Business · E-commerce · Operations research · Originality · Process (computing) · Product (mathematics) · Qualitative research · Quality (philosophy) · Reputation · Computer Science · Digital Marketing and Social Media · E-commerce and Technology Innovations · Engineering · Marketing · Technology Adoption and User Behaviour

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