关键词: 物流产业, 管理效率, 产业环境生态, 三阶段DEA模型, 组态分析

Abstract: Cost reduction and efficiency enhancement are pivotal forces driving the transformation and upgrading of the logistics industry. Governments should foster an internal and external environment conducive to industry development, aiming to reduce operational costs and improve performance outcomes. However, a critical question is how to optimize the industrial ecosystem to promote efficiency. This paper focuses on China’s logistics industry and examines potential improvement opportunities from the theoretical perspectives of input-output and configuration analysis. Using a research framework based on industrial environment configuration, coupled with a three-stage Data Envelopment Analysis (DEA)/Stochastic Frontier Analysis (SFA) model and Fuzzy-set Qualitative Comparative Analysis (fsQCA) method, we quantify the impact of regional heterogeneity and random shocks on logistics efficiency. Subsequently, we analyze the relationship between environmental driving factors and logistics industry efficiency from a configuration perspective. The findings are as follows. (1) Government support as a direct driving factor, and consumer capacity and economic development as indirect driving factors, significantly reduce the redundancy in industry production value. (2) No single driving factor is necessary for achieving high efficiency; rather, high efficiency in the logistics industry results from the combined effect of multiple driving factors, with three specific industrial ecosystems conducive to improved efficiency outcomes identified. This mixed-method framework demonstrates strong complementarity, providing decision-making references from the perspectives of resource utilization and system integration to promote the efficient development of the logistics industry.

Key words: logistics industry, management efficiency, industrial ecosystem, three-stage DEA model, configuration analysis