A Fuzzy DEMATEL-ANP-TOPSIS Model for Cross-Border E-Commerce Driven Agricultural Value Chain Upgrading in Henan

Abstract

Globalisation and digital transformation are fundamentally changing agricultural supply chains, with the digital economy emerging as a catalyst for more connected, intelligent, and sustainable agricultural systems. Within this evolving landscape, cross-border e-commerce (CBEC) has become a strategic mechanism for enhancing agricultural value chains by improving efficiency, increasing value creation, and strengthening international market integration. As one of China's principal agricultural regions and a major grain-producing province, Henan is experiencing an important transition from conventional agricultural practices to a digitally enabled agricultural economy. Achieving this transformation requires strategic decision-making under multiple, often conflicting, criteria while operating within constraints associated with limited resources and a complex policy environment. Consequently, selecting the most suitable agricultural value chain upgrading strategy represents a challenging multi-criteria decision-making (MCDM) problem. To address this challenge, the present study develops an integrated hybrid decision-support framework grounded in decision science. The proposed framework combines fuzzy Decision-Making Trial and Evaluation Laboratory (Fuzzy DEMATEL), fuzzy Analytic Network Process (Fuzzy ANP), and fuzzy Technique for Order Preference by Similarity to Ideal Solution (Fuzzy TOPSIS). By integrating these complementary approaches, the framework effectively captures uncertainty in expert judgements while simultaneously accounting for the interdependent relationships among evaluation criteria. An evaluation index system was established through a comprehensive review of the literature together with the Delphi method, resulting in five principal dimensions: digital infrastructure, cross-border logistics and cold chain, quality control and traceability, policy support and financial empowerment, and human capital and innovation. These dimensions were operationalised using fifteen critical evaluation criteria. The empirical findings identify cross-border logistics and cold chain efficiency, together with digital infrastructure capability, as the principal causal drivers facilitating agricultural value chain upgrading. Among the four strategic alternatives evaluated, optimisation of the cross-border cold chain logistics network and airport transport channels achieved the highest closeness coefficient (0.714), indicating that it represents the most effective implementation strategy under current conditions. The stability and reliability of the proposed framework were further confirmed through sensitivity analysis and comparative evaluation using fuzzy MARCOS and fuzzy COPRAS methods, both of which produced consistent ranking outcomes. Overall, this research extends the application of MCDM techniques within digitally driven agricultural supply chains while offering practical guidance for policymakers seeking to formulate targeted digital agriculture strategies and promote sustainable rural revitalisation in Henan Province as well as other developing agricultural economies.