Observations on Inclusive Development of Rural E-Commerce in China: Traffic Resource Allocation Based on the DEMATEL-ISM Model

Amid the integration of the digital and platform economies, rural e-commerce traffic resource integration involves complex multi-factor interactions and hidden causal pathways, making key mechanism identification challenging. To overcome the limitations of conventional DEMATEL–ISM studies, which often rely on manually defined factors and lack integration between factor discovery and structural analysis, this study proposes an integrated LLM–DEMATEL–ISM workflow. Rather than a simple application of LLMs, the proposed framework combines LLM-assisted factor identification, structured validation, expert evaluation, and DEMATEL–ISM modeling into a unified analytical process. LLMs support multi-source factor discovery, while expert validation ensures conceptual reliability; DEMATEL and ISM further quantify causal relationships and reveal hierarchical transmission structures. The results identify market entity scale, organizational coordination capability, and digital traffic mechanisms as key hub factors. The main methodological contribution lies in establishing a reproducible human–machine–structure collaborative framework that bridges data-driven factor discovery and expert-validated structural modeling, providing a new analytical paradigm for complex-systems research in the digital economy.