中国物流业数字化绿色化协调发展的时空演化与多元路径——基于AIS理论框架

doi:10.12118/j.issn.1000-6060.2025.640

摘要/Abstract

摘要：

物流业数字化绿色化协调发展是推动行业高质量转型和实现“双碳”目标的重要途径。基于2013—2023年中国30个省（区）的数据，通过构建物流业数字化绿色化协调发展水平测度体系，利用纵横向拉开档次法、耦合协调度模型和空间自相关分析剖析其时空特征。并基于变革动能性（A）、制度环境动态（I）与空间组织结构（S）的理论框架视角，借助动态定性比较分析（QCA）方法，探究其多元路径。结果表明：（1）时序演变上，2013—2023年中国物流业数字化绿色化耦合协调度总体呈上升趋势，耦合协调水平由初级协调演变为中等协调，呈现东部领先、中西部加速、东北滞后的发展格局。（2）空间演变上，中国物流业数字化绿色化协调发展存在空间正相关性，且呈现波动下降演进趋势，区域空间特征由集聚逐渐走向均衡，表现为典型的高-高（低-低）空间集聚模式。（3）不存在单一因素构成高耦合协调的必要条件，多因素匹配联动，形成高水平协调的3种组态路径，分别为数字创新协同型、绿色集聚驱动型和多元协同创新型。研究结果为各省（区）因地制宜提升物流业数字化绿色化协调发展水平、实现物流业高质量发展提供了路径指引与实践依据。

关键词: 物流业数字化, 物流业绿色化, 协调发展, AIS框架, 动态QCA, 多元路径

Abstract:

Coordinating the development of digitalization and greening in the logistics industry can promote high-quality transformation in the sector while helping to achieve China’s “dual carbon” goals. Based on data from 30 provinces (autonomous regions) of China from 2013 to 2023, this study construct a system to measure coordinated development of digitalization and greening in logistics using the vertical and horizontal scatter degree method, coupling coordination model, and spatial Moran’s I to analyze its spatiotemporal characteristics. Furthermore, based on the theoretical frameworks of change dynamism, institutional environment dynamics, and spatial organizational structure, we use a dynamic qualitative comparative analysis to explore multiple development pathways. The results indicated that: (1) In terms of temporal evolution, the degree of coupling coordination in digitalization and greening transformation in China’s logistics industry generally increased from 2013 to 2023, evolving from a state of primary coordination to medium coordination, with a geographic distribution characterized by eastern leading, central and western accelerating, and northeastern lagging. (2) The coordinated development of digitalization and greening in China’s logistics industry exhibits a significant positive spatial correlation with a fluctuating downward trend. The regional spatial pattern has gradually evolved from agglomeration toward a relative balance characterized by typical “high-high” and “low-low” spatial clustering patterns. (3) No single factor represents a necessary condition for achieving high coupling coordination. Multiple factors are matched and linked to form three configuration paths to high-level coordination, namely collaborative digital innovation, green agglomeration, and multidimensional collaborative innovation. This study provide both theoretical guidance and a practical basis for various regions to improve the “dual coordination” needed to achieve high-quality development within China’s logistics industry in a way that reflects local conditions.

Key words: digitalization of the logistics industry, greening of the logistics industry, coordinated development, AIS framework, dynamic QCA, multiple paths

李旭辉, 年庆雨. 中国物流业数字化绿色化协调发展的时空演化与多元路径——基于AIS理论框架[J]. 干旱区地理, 2026, 49(10): 2171-2181.

LI Xuhui, NIAN Qingyu. Spatiotemporal evolution and multiple paths for the coordinated development of digitalization and greening in China’s logistics industry: Based on the AIS theoretical framework[J]. Arid Land Geography, 2026, 49(10): 2171-2181.

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准则层	一级指标	二级指标	单位	属性
物流业数字化	数字化基础	互联网宽带接入用户数	10⁴个	+
		移动电话普及率	部·(10²人)^-1	+
		光缆线路长度	km	+
		邮政营业网点	个	+
	产业数字化	每百家企业拥有网站数	个	+
		每百人使用计算机数	台	+
		人均电子商务交易额	元	+
		有电子商务交易活动的企业占比	%	+
	数字化创新	新产品开发项目数	项	+
		物流相关专利申请数	个	+
		物流业R&D经费支出	10⁴元	+
物流业绿色化	绿色发展水平	单位货运量碳排放量	10⁴ t CO₂·(10⁴t)^-1	-
		单位货物周转量碳排放量	10⁴ t CO₂·(10⁸t km)^-1	-
		单位运输车辆碳排放量	10⁴ t CO₂·辆^-1	-
		单位公路线路里程碳排放量	10⁴ t CO₂·km^-1	-
		单位物流业增加值碳排放	10⁴ t CO₂·(10⁸元)^-1	-
		单位物流业固定资产投资碳排放量	10⁴ t CO₂·(10⁸元)^-1	-
	绿色治理	环境污染治理投资占GDP的比重	%	+
		建成区绿化覆盖率	%	+
		一般工业固体废物综合利用率	%	+

类型	区间
失调衰退	[0.0, 0.2)
勉强协调	[0.2, 0.4)
初级协调	[0.4, 0.5)
中等协调	[0.5, 0.6)
良好协调	[0.6, 0.8)
优质协调	[0.8, 1.0)

年份	Moran’sI	Z值	P值	年份	Moran’sI	Z值	P值
2013	0.366	3.312	0.000	2019	0.331	3.007	0.001
2014	0.360	3.263	0.001	2020	0.312	2.860	0.002
2015	0.389	3.491	0.000	2021	0.336	3.051	0.001
2016	0.320	2.914	0.002	2022	0.341	3.078	0.001
2017	0.310	2.827	0.002	2023	0.351	3.156	0.001
2018	0.338	3.072	0.001

年份	高-高集聚	低-高集聚	低-低集聚	高-低集聚
2013	北京、天津、上海、江苏、浙江、安徽、福建、山东	河北、江西、河南、广西、海南	山西、内蒙古、辽宁、吉林、黑龙江、湖北、湖南、重庆、四川、贵州、云南、陕西、甘肃、青海、宁夏、新疆	广东
2023	河北、上海、江苏、浙江、安徽、福建、山东、河南、湖北、湖南	天津、江西、广西、海南	山西、内蒙古、辽宁、吉林、黑龙江、云南、陕西、甘肃、青海、宁夏、贵州、新疆	北京、广东、重庆、四川

条件变量	高耦合协调度
条件变量	组态S1	组态S2	组态S3	组态S4	组态S5	组态S6
技术创新能力	●	●	●	●		●
绿色科技水平	•	•	•	•	●	●
政府支持力度	⊗			•	⊗	•
市场化水平	•	•	•		•	⊗
数字经济	●	●	●	●	•	●
物流业集聚程度		⊗		⊗	●	●
交通网络密度			•	•	•	⊗
一致性	0.977	0.981	0.985	0.993	0.97	0.918
PRI	0.969	0.977	0.982	0.991	0.951	0.766
原始覆盖度	0.409	0.431	0.458	0.249	0.197	0.073
唯一覆盖度	0.032	0.057	0.041	0.041	0.023	0.012
组间一致性调整距离	0.038	0.038	0.045	0.053	0.105	0.139
组内一致性调整距离	0.132	0.086	0.046	0.052	0.115	0.104
总体一致性	0.974
总体PRI	0.967
总体覆盖度	0.700