Measuring expressway accessibility of enterprise based on an improved NN-2SFCA method in rural area

Equitable expressway accessibility is critical for revitalizing rural industries, yet traditional accessibility metrics often fail to capture the unique logistical needs of enterprises in complex rural environments. The widely used Two-Step Floating Catchment Area (2SFCA) method is limited in rural applications due to its reliance on fixed catchment areas and population-based demand weighting, which misrepresent actual travel conditions and overlook industry-specific requirements. To address these gaps, we propose an improved Nearest-Neighbor 2SFCA (NN-2SFCA) method that incorporates three key innovations: (1) network-based travel time derived from web mapping API instead of Euclidean distance, (2) a data-driven dynamic nearest-neighbor search to adaptively determine service ranges, and (3) demand weighting based on enterprise registered capital to reflect industrial scale rather than population distribution. Applied in Yunnan Province, China, results reveal severe inequality: 73 % of expressway services concentrate in only 10 % of townships, showing a clear core-periphery pattern. Significant sectoral disparities exist, with tourism having the poorest accessibility. The study offers actionable insights for optimizing resource allocation under the Rural Revitalization Strategy and presents a transferable framework for accessibility research in similar contexts.