资源型地区工矿企业空间集聚与区域转型——以山西省为例

doi:10.31497/zrzyxb.20210411

摘要/Abstract

摘要：

工矿企业是资源型地区实现区域转型的关键要素,研究工矿企业空间集聚的格局特征及驱动机理对于揭示资源型地区转型的空间过程及空间效应具有重要意义。以山西省为例,基于煤矿企业点数据,综合采用多种GIS空间分析方法,分析1990—2017年经济转型阶段,山西省煤矿企业空间集聚的格局演变及区位指向变化。进一步构建负二项回归模型分析山西省煤矿企业空间集聚演变的影响因素,解释资源型地区转型发展的驱动机理。结果表明：（1）煤矿企业整体集聚变化相对稳定,但发展内涵发生显著变化,企业趋向大型化、现代化、可持续化发展。（2）煤矿企业空间集聚逐步与煤层埋深线的岩层走向相吻合,并且表现出低坡度指向性、临交通线指向性特征。（3）宏观尺度上,煤矿企业空间集聚呈现以点状集聚为主到点状集聚与沿煤层线带状扩散并存的演变趋势;微观尺度上,煤矿企业核密度降低区域与核密度增加区域具有地理邻近性特征,空间上表现为煤矿企业的远郊区化过程。（4）资源禀赋对煤矿企业区位选择的影响最显著,地形坡度、路径依赖、省道、企业所有制性质、固定资产投资、区域面积等对煤矿企业的区位选择也具有显著影响,但是作用方向和强度存在差异;城镇化水平、铁路、高速公路等对煤矿企业区位选择的影响不显著。回归结果表明资源型地区的转型发展受自然基底条件、产业发展基础、区域发展阶段等多重因素的影响。

关键词: 煤矿企业, 空间集聚, 区位指向, 区域转型, 山西省

Abstract:

Mining enterprises are the key elements for achieving regional transformation in resource-based regions. It is of great significance to study the spatial agglomeration characteristics and driving mechanisms of mining enterprises to reveal the spatial process and spatial effects of resource-based regional transformation. The paper takes Shanxi province as an example, and based on the point data of coal mining enterprises, adopts a variety of GIS spatial analysis methods to analyze the evolution of the spatial agglomeration pattern and location change of Shanxi's coal mining enterprises during economic transformation from 1990 to 2017. Furthermore, a negative binomial regression model is constructed to examine the influencing factors of the spatial agglomeration and evolution of coal mining enterprises in the province, and to explain the driving mechanism of the transformation and development of resource-based regions. The results show that: (1) The overall agglomeration changes of coal mining enterprises were relatively stable, but the development connotation has changed significantly, and the enterprises were trending toward large-scale, modern and sustainable development. (2) The spatial agglomeration of coal mining enterprises gradually tended to the direction of coal seam line, and showed the characteristics of low-slope directivity and directivity of adjacent traffic lines. (3) On the macro scale, the spatial concentration of coal mining enterprises presents a trend of dominance of clustering to coexistence of point clustering and band-shaped diffusion along the coal seam line. On the micro scale, the regions with reduced kernel density and regions with increased kernel density had geographical proximity characteristics, which spatially represented the suburbanization process of coal mining enterprises. (4) Resource endowment had the most significant impact on the location selection of coal mining enterprises. Terrain slope, path dependence, provincial roads, corporate ownership, fixed asset investment, and the area of region also had significant effects on location selection of coal mining enterprises. But there are differences in the direction and intensity; the level of urbanization, railways, highways and other elements have no significant impact on the location selection of coal mining enterprises, indicating that the quality of transformation in resource-based regions is constrained by factors such as natural base conditions, industrial development foundations, and regional development stages.

Key words: coal mining enterprises, spatial agglomeration, location orientation, regional transformation, Shanxi province

秦志琴, 倪云松, 姜晓丽, 王让虎. 资源型地区工矿企业空间集聚与区域转型——以山西省为例[J]. 自然资源学报, 2021, 36(4): 948-964.

QIN Zhi-qin, NI Yun-song, JIANG Xiao-li, WANG Rang-hu. Agglomeration and regional transformation of coal mining enterprises: A case study of Shanxi province[J]. JOURNAL OF NATURAL RESOURCES, 2021, 36(4): 948-964.

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矿井等级	特大型	大型		中型	小型
矿井等级	特大型	大型Ⅰ	大型Ⅱ	中型	小型Ⅰ	小型Ⅱ
设计生产能力	≥1000	500、600、700、 800、900	120、150、180、240、 300、400	45、60、90	15、21、30	≤ 9

年份	样本数/个	特大型		大型				中型		小型
		特大型		大型Ⅰ		大型Ⅱ		中型		小型Ⅰ		小型Ⅱ
		数量/个	占比/%	数量/个	占比/%	数量/个	占比/%	数量/个	占比/%	数量/个	占比/%	数量/个	占比/%
1990	1220	0	0	0	0	39	3.20	52	4.26	202	16.56	927	75.98
2010	1029	18	1.75	49	4.76	296	28.77	629	61.13	37	3.60	0	0
2017	1011	9	0.89	28	2.77	360	35.61	591	58.46	23	2.27	0	0

年份	样本数/个	平均最邻近距离/m	期望平均最邻近距离/m	最邻近指数（NNI）	Z检验值	显著性水平/%
1990	1221	3118.54	5977.93	0.52	-31.96	1
2010	1036	3415.19	6205.66	0.55	-27.66	1
2017	1011	3205.24	6207.78	0.51	-29.42	1

坡度 /(°)	样本数		特大型		大型				中型		小型
	样本数		特大型		大型Ⅰ		大型Ⅱ		中型		小型Ⅰ		小型Ⅱ
	数量/个	占比/ %	数量/个	占比/ %	数量/个	占比/ %	数量/个		占比/ %	数量/ 个	占比/ %	数量/个	占比/ %	数量/个	占比/ %
<5	1437	43.51	17	62.96	53	68.83	304	43.74	531	41.59	141	53.82	393	42.39
5~10	1028	31.86	5	18.52	18	23.38	227	32.66	413	32.47	79	30.15	286	30.85
10~15	462	14.32	3	11.11	5	6.49	94	13.53	217	17.06	22	8.40	121	13.05
15~25	333	10.32	2	7.41	1	1.30	70	10.07	113	8.88	20	7.63	127	13.70
总量	3260	100	27	100	77	100	695	100	1272	100	262	100	927	100

年份	样本数 /个	铁路		高速公路		国道		省道
年份	样本数 /个	数量/个	占比/%	数量/个	占比/%	数量/个	占比/%	数量/个	占比/%
1990	1220	425	34.83	3	0.25	586	48.03	952	78.03
2010	1034	548	53.00	477	46.13	433	41.88	839	81.14
2017	1011	545	53.91	493	48.76	451	44.61	811	80.21