摘要
人工智能与物流业高质量发展密切相关。基于新质生产力的理论内涵以及人工智能“技术—经济”的研究范式,构建“人工智能+物流”双系统耦合协调理论模型,以明确二者耦合协调的内在机理与演化逻辑。以中国2014—2023年31个地区的面板数据为研究对象,运用耦合协调度模型和Dagum基尼系数分解法探究人工智能与物流业耦合协调发展水平与区域发展差异,结果表明:样本期内耦合协调水平呈现上升趋势,区域间以及区域内呈现显著的差异化态势;技术、经济、人才等资源要素优化配置驱动了人工智能与物流业耦合协同呈现“萌芽—过渡—高质量发展”的三阶段跃迁。因此,地区间应发挥各自资源禀赋优势,走区域差异化发展道路;地区内应破解资源流动壁垒,打造“人工智能+物流”产业集群;对处于不同耦合协调阶段的地区要因地施策,协同推进物流业降本增效及智能物流跨越式发展。
Abstract
Artificial intelligence (AI) serves as a vital enabler for the high-quality development of the logistics industry. Drawing on the theoretical connotation of new quality productive forces and the techno-economic research paradigm of artificial intelligence, this paper constructs a theoretical model for the coupling and coordination of the dual systems of “AI + logistics”, and clarifies the internal mechanism and evolutionary logic underlying their coupling coordination. Taking the panel data of 31 provincial-level regions in China from 2014 to 2023 as research samples, this study adopts the coupling coordination degree model and Dagum Gini coefficient decomposition method to examine the level of coupled and coordinated development between artificial intelligence and the logistics industry as well as regional disparities. The empirical results reveal that the overall coupling coordination level maintained an upward trend throughout the sample period, with prominent divergences both across and within regions. Furthermore, the optimal allocation of resource factors including technology, economy and talent drives the three-stage evolution of the AI-logistics coupling synergy: initial budding stage, transitional stage and high-quality development stage. Accordingly, regions should leverage their respective resource endowments and pursue differentiated development paths. Within each region, barriers restricting resource mobility ought to be eliminated to foster industrial clusters integrating AI and logistics. Targeted policies should be formulated for regions at distinct coupling coordination stages to jointly advance cost reduction and efficiency improvement in logistics, as well as the leapfrog development of intelligent logistics.
关键词
人工智能 /
物流业 /
耦合协调 /
新质生产力 /
高质量发展
Key words
artificial intelligence /
logistics industry /
coupling and coordination /
new quality productive forces /
high-quality development
胡毅, 王舒婷, 唐朝丰.
新质生产力视角下人工智能与物流业耦合协调发展水平测度及演化分析[J]. 北京交通大学学报(社会科学版). 2026, 25(2): 68-79
HU Yi, WANG Shu-ting, TANG Chao-feng.
Measurement and Evolution Analysis of the Coupling Coordinated Development Between Artificial Intelligence and Logistics Industry from the Perspective of New Quality Productive Forces[J]. Journal of Beijing Jiaotong University(Social Sciences Edition). 2026, 25(2): 68-79
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
参考文献
1 汪旭晖,段怡杰.新质生产力驱动全社会物流成本降低的机制与路径[J].中国流通经济,2024,38(7):15-24.
2 马荣,王灏翔,焉祯.论新质生产力:深刻内涵、生成背景、践行路径[J].北京交通大学学报(社会科学版),2025,24(1):10-17.
3 程乐. “人工智能+物流”:技术张力与结构性优化[J]. 人民论坛, 2025, (2):35-40.
4 翟玲. 基于人工智能的物流系统优化[J]. 山西财经大学学报, 2024, 46(S2):77-79.
5 BELHADI A, MANI V, KAMBLE S S, et al. Artificial Intelligence-Driven Innovation for Enhancing Supply Chain Resilience and Performance under the Effect of Supply Chain Dynamism :An EmpiricalInvestigation[J]. Annals of Operations Research,2021,(1):1-26.
6 宋华,韩梦玮,沈凌云.人工智能在供应链韧性塑造中的作用——基于迈创全球售后供应链管理实践的案例研究[J].中国工业经济, 2024,(5):174-192.
7 刘帅.数字物流促进物流业碳排放效率提升的机制与效应[J]. 中国流通经济, 2024, 38(6):54-65.
8 刘伟华,王思宇,周志成.工业4.0技术对物流业制造业融合的影响路径研究——基于国家发展改革委征集典型案例集的研究[J].系统工程理论与实践, 2025,45(7):2245-2263.
9 徐孝民, 刘孟凯, 黄胜忠. 基于复杂适应系统理论的智慧物流创新系统及其创新行为模式[J]. 大连理工大学学报(社会科学版), 2024, 45(4):16-28.
10 ROMANOVA O A, BUKHVALOV N Y. Shared values in the formation of a modern techno-economic paradigm[J]. Economic and social changes: facts, trends, forecast, 2016,(3): 173-190.
11 宋宪萍, 曹宇驰. 人机交互何以影响人工智能技术—经济—社会范式的重构[J].西安交通大学学报(社会科学版), 2025, 45(3):161-171
12 CRUZ-JESUS F, PINHEIRO A, OLIVEIRA T. Understanding CRM adoption stages: empirical analysis building on the TOE framework[J]. Computers in Industry, 2019, 109: 1-13.
13 唐露源,徐源.中国生成式人工智能产业高效率发展路径研究——基于TOE框架的组态分析[J].科学学研究,2026,44(3):471-481.
14 BURSTR?M T, LAHTI T, PARIDA V, et al. Industrial ecosystems: A systematic review, framework and research agenda[J]. Technological Forecasting and Social Change, 2024, 208: 1-13.
15 WOSCHANK M, RAUCH E, ZSIFKOVITS H. A review of further directions for artificial intelligence, machine learning, and deep learning in smart logistics[J]. Sustainability, 2020, 12(9): 3760.
16 李树文,罗瑾琏,张志菲.AI能力如何助推企业实现价值共创——基于企业与客户间互动的探索性案例研究[J].中国工业经济,2023,(5):174-192.
17 CHEN W, MEN Y, FUSTER N, et al. Artificial intelligence in logistics optimization with sustainable criteria: A review[J]. Sustainability, 2024, 16(21): 9145.
18 胡毅,王舒婷,左腾达.数字经济赋能农村流通体系高质量发展组态路径研究[J].统计与信息论坛,2026,41(4):116-126.
19 蔡冬青,席中镪.制度型开放赋能新质生产力——来自跨境电商综试区的经验证据[J].现代财经(天津财经大学学报), 2025,45(4):3-21.
20 周跃军,刘先江.新质生产力劳动三要素的系统重塑和优化组合[J].湖南社会科学,2025,(1):40-49.
21 缪琦.现代物流高质量发展的现实基础、制约因素与发展建议[J].宏观经济研究,2024,(12):112-120.
22 吴群,朱嘉懿.数字化水平对电商业与物流业协同发展的影响机制研究[J].安徽大学学报(哲社版), 2024, 48(5):176-188.
23 刘彩霞.新质生产力赋能绿色物流的内在价值、现实挑战与实践构想[J].当代经济管理,2024, 46(11):42-49.
24 谷城,张树山,刘赵宁.物流业智慧化对企业绩效的影响与机制——基于供应链韧性视角[J].中国流通经济, 2024,38(7):87-100.
25 KAMARIOTOU M, KITSIOS F, MADAS M. E-business strategy for logistics companies: achieving success through information systems planning[J]. Logistics, 2021, 5(4): 73.
26 李然,孙涛,曹冬艳.平台经济视角下新物流新业态运营模式研究[J].当代经济管理,2023, 45(6):25-34.
27 郝智娟, 文琦, 施琳娜,等. 黄河流域城市群社会经济与生态环境耦合协调空间网络分析[J]. 经济地理, 2023, 43(12):181-191.
28 舒辉,胡毅.基于复合系统耦合的农业物流生态圈协同发展研究[J].统计与信息论坛,2020,35(12):62-71.
29 苏振东,宫硕,李卓平.新质生产力:创新力与生产力的耦合协调分析[J].当代经济科学,2025,47(3):96-114.
基金
江西省社会科学“十四五”(2025)基金青年项目“新质生产力视域下数字经济赋能江西省农村物流体系改革路径研究”(25GL65D);广东省基础与应用基础研究基金联合基金“基于高维SVAR模型的‘动态’波动溢出效应方法建模:理论及应用”(2023A1515110604)。