西南边境城镇产业演化的时空特征与优化路径研究

doi:10.3969/j.issn.1004-9479.2025.06.20230089

摘要/Abstract

摘要：

边境城镇是区域协调发展的短板地区，推动其产业发展对优化开放格局和促进边境地区的安全稳定与繁荣具有重要意义。以云南、广西边境城镇为例，综合运用GIS空间分析等方法，探讨边境城镇产业时空演变特征及规律，并采用灰色关联和TOPSIS双重分析模型优化其产业发展路径。研究发现：①整体来说，西南边境城镇以进出口贸易为主导产业，辅之以零售业和旅游业；且产值呈现不均衡状态，昆明和南宁较高，其余城镇较低。②在时间上，西南边境城镇第三产业相对于第一产业和第二产业增长幅度较大，且差距明显；在空间上，全局空间集聚程度较低为弱集聚空间格局，局部上呈现较低的正相关性。③在发展路径上，西南边境城镇产业应优先发展进出口贸易、旅游业、零售业以及工业。同时，应以边境贸易为主导产业，以旅游业和零售业为强化产业，以工业和林业为突破产业，以农牧渔产业为特色产业。依据西南边境两省产业选择结果，根据边境城镇实际情况提出主导产业发展建议，并制定因地制宜的措施，为边境城镇振兴提供参考和借鉴。

关键词: 产业评估, 时空演进, 路径选择, 边境城镇, 西南边境

Abstract:

Promoting the industrial development is of great significance to optimize the opening pattern and promote the security, stability and prosperity of border areas. Taking the border towns in southwest Yunnan and Guangxi as examples, we explore the spatial and temporal evolution characteristics and laws of border towns' industries, and industrial optimization paths by using the models of gray correlation and TOPSIS. It is found that: ① Import and export trade are the leading industry of Southwest border towns， supplemented by retail and tourism； and the output value shows an uneven spatial pattern， with Kunming and Nanning higher and the rest lower. ② The tertiary industries in southwest border towns grows faster than the primary and secondary industries， and the gap is obvious； and the local positive correlation is low. ③ The industries in southwest border towns should give priority to the development of import and export trade, tourism, retail trade and industry, with border trade as the dependent industry, tourism and retail trade as the strengthening industry, industry and forestry as the breakthrough industries, and agriculture, animal husbandry and fishery industry as the special industry. Based on the results of industrial selection in the two southwestern border provinces, the leading industrial development suggestions and localized measures are proposed according to the actual situation of border towns to provide reference and guidance for the revitalization of border towns.

Key words: industrial assessment, spatial and temporal evolution, path selection, border towns, southwest border

王可心, 葛旭瑞, 华红莲, 李灿松, 王涛, 钱镜帆. 西南边境城镇产业演化的时空特征与优化路径研究[J]. 世界地理研究, 2025, 34(6): 135-148.

Kexin WANG, Xurui GE, Honglian HUA, Cansong LI, Tao WANG, Jingfan QIAN. Study on the spatio-temporal evolution characteristics and optimization path of industries in southwest border towns[J]. World Regional Studies, 2025, 34(6): 135-148.

图/表 10

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系统层	权重	指标层	权重
第一产业	0.323	农业	0.120
		林业	0.060
		渔业	0.049
		牧业	0.094
第二产业	0.079	工业	0.029
第二产业	0.079	建筑业	0.050
第三产业	0.598	住宿业和餐饮业	0.103
		零售业	0.329
		进出口贸易	0.097
		旅游业	0.069

系统层	权重	指标层	权重
第一产业	0.323	农业	0.120
		林业	0.060
		渔业	0.049
		牧业	0.094
第二产业	0.079	工业	0.029
第二产业	0.079	建筑业	0.050
第三产业	0.598	住宿业和餐饮业	0.103
		零售业	0.329
		进出口贸易	0.097
		旅游业	0.069

指数值	2010年	2015年	2020年
Moran's I指数	0.520 4	0.085 0	0.105 6
预期指数	－0.034 5	－0.034 5	－0.034 5
方差	0.013 4	0.011 9	0.011 6
Z得分	4.785 5	1.094 3	1.300 0
P值	0.000 0	0.273 8	0.193 7

指数值	2010年	2015年	2020年
Moran's I指数	0.520 4	0.085 0	0.105 6
预期指数	－0.034 5	－0.034 5	－0.034 5
方差	0.013 4	0.011 9	0.011 6
Z得分	4.785 5	1.094 3	1.300 0
P值	0.000 0	0.273 8	0.193 7

云南省			广西壮族自治区
评价项	关联度	排名	评价项	关联度	排名
进出口贸易	0.792	1	进出口贸易	0.809	1
零售业	0.692	2	工业	0.657	2
工业	0.681	3	零售业	0.657	3
旅游业	0.677	4	旅游业	0.637	4
林业	0.654	5	建筑业	0.632	5
农业	0.651	6	农业	0.626	6
建筑业	0.650	7	林业	0.625	7
牧业	0.647	8	牧业	0.618	8
住宿业和餐饮业	0.638	9	渔业	0.612	9
渔业	0.634	10	住宿业和餐饮业	0.611	10