An Empirical Analysis of Regional Logistics Efficiency and Its Determinants in Sichuan Province: Evidence from DEA and Tobit Models

This study investigates the regional logistics efficiency of Sichuan Province, China, from 2011 to 2019, using a combination of the Data Envelopment Analysis-Banker, Charnes, and Cooper (DEA-BCC) model and the Tobit model.The primary objective is to assess the efficiency of the logistics industry and identify the key determinants influencing this efficiency within the context of high-quality development.A comprehensive inputoutput index system and a set of influencing factor variables were constructed to evaluate logistics performance across various regions of the province.The findings indicate that factors such as the level of economic development, urbanization, and geographical location significantly enhance regional logistics efficiency.In contrast, the level of informatization and the industrial structure exhibit clear inhibitory effects.Specifically, a higher degree of informatization does not necessarily correspond with improved logistics efficiency, potentially due to inefficiencies in technology adoption or uneven infrastructure development.Furthermore, the current industrial structure, with its reliance on traditional industries, may hinder the optimization of logistics systems.Based on these results, several policy recommendations are put forward, including the optimization of the industrial structure, better integration of information technologies in logistics processes, and the strategic utilization of Sichuan's geographical advantages.This research provides valuable insights for policymakers aiming to enhance logistics efficiency as part of the region's broader economic development strategy.