山东交通学院学报

为评价京津冀区域的智慧物流效率，基于京津冀区域2013—2022年智慧物流的投入指标、产出指标和影响因素数据，采用数据包络分析(data envelopment analysis, DEA)模型测算京津冀区域智慧物流的技术效率、纯技术效率和规模效率，通过截断回归模型(Tobin′s probit model, Tobit模型)分析经济发展水平、行业因素、能源利用率、数字化销售收入和互联网发展水平等影响因素对京津冀区域智慧物流效率的影响程度。结果表明：2013—2022年北京市智慧物流技术效率呈阶段性跃升，2013—2015年不断增大，2016年后持续保持有效(仅2021年无效);2013—2022年天津市智慧物流技术效率仅2015、2019年无效，河北省仅2015、2016、2020年无效；北京市、天津市智慧物流技术效率无效的主要原因是纯技术效率低，河北省是规模效率低；经济发展水平、行业因素与数字化销售收入显著正向影响智慧物流效率，能源利用率和移动互联网发展水平未达显著水平。建议京津冀区域进一步优化产业结构并强化经济发展动能，推动智慧物流不断发展。

To measure smart logistics efficiency in the Beijing-Tianjin-Hebei Region, panel data on input indicators, output indicators, and influencing factors from 2013 to 2022 are utilized. The data envelopment analysis(DEA) model is applied to calculates technical efficiency, pure technical efficiency, and scale efficiency of regional smart logistics. The Tobit model is used to analyzes the impact intensity of economic development level, industrial factors, energy utilization rate, digital sales revenue, and internet development level on smart logistics efficiency. Recommendations for enhancing efficiency are proposed. Results indicate: during the period 2013 to 2022, Beijing′s smart logistics technical efficiency shows stage-wise leaps, continuously increasing from 2013 to 2015 and remaining efficient after 2016 except 2021; Tianjin achieves efficiency in 8 a, with inefficiency only in 2015 and 2019; Hebei achieves efficiency in 7 a, with inefficiency in 2015, 2016, and 2020; low pure technical efficiency primarily causes inefficiency in Beijing while low scale efficiency dominates in Hebei; economic development level, industrial factors, and digital sales revenue exhibit significant positive effects on smart logistics efficiency, whereas energy utilization rate and internet development level show insignificant impacts. Recommendations include optimizing industrial structure, strengthening economic drivers, and advancing smart logistics development.