宁波市港口物流企业空间格局及区位选择

doi:10.13249/j.cnki.sgs.2018.05.006

Abstract

Abstract:

With the rapid development of the modern logistics industry dominated by the port logistics in China's coastal cities, researches on the characteristics of spatial distribution and laws of evolution of the port logistics companies inside cities are beginning to appear. However, the existing research has not further studied the factors affecting the location selection of the port logistics companies. In this article, based on the data of location information of Ningbo port logistics companies, the characteristics of spatial distribution and factors that affect the location selection of the port logistics companies are analyzed. The differences of the locational characteristics between the different types of port logistics companies are identified. It enriches the case studies of the locational analysis of the port logistics companies in the coastal cities. Taking Ningbo as an example, this article employed the Kernel Density Estimation, Getis-ord Gi analysis and Poisson regression models to analyze data, and the results showed that: 1) The port logistics companies in Ningbo show centripetal concentration, and the spatial distribution of enterprises presents a tendency to decrease from the central city, the periphery to the suburbs, and the distribution pattern of the circle is obvious. Central business district and port industrial area are the popular areas for port logistics enterprises to gather. 2) At present, port logistics enterprises have obvious agglomeration characteristics, but the overall agglomeration degree is decreasing. At the same time, there are two trends, which are centralization and diffusion of central business district and port industrial area. 3) It is found that there are obvious differences in location choice of different types of port logistics companies: a) The freight forwarder logistics companies are mainly distributed in the central business area; b) The logistics business companies of warehouse are mainly distributed in port; c) The transportation logistics companies often choose the layout along the main road, because they mainly undertake land container transportation, the locational selection has traffic dependency; d) Compared with the other three types, the distribution of integrated logistics companies has no obvious locational tendencies. 4) Regarding the factors affecting the spatial distribution of Ningbo port logistics companies, the research shows that the policy factors, the price of land, the differences between urban and rural areas, the distance from the port, the economic potential of the region and its industrial structure all affect the spatial distribution of port logistics enterprises in varying degrees. However, there is no correlation with traffic convenience, and the main reason is that the road network construction in Ningbo is relatively perfect. At the same time, the article put forward the corresponding measures from three different aspects: first, strengthening top-level design in logistics industry; second, exploiting the regional advantages to form a park that integrates port logistics and port industry advantages;third, optimizing the infrastructure such as the traffic network deeply.

Key words: port logistics enterprises, spatial pattern, location selection, Ningbo

CLC Number:

F129.9

Rui Wang, Tianying Jiang, Shuai Wang. Spatial Pattern and Location Selection of Port Logistics Enterprises in Ningbo[J].SCIENTIA GEOGRAPHICA SINICA, 2018, 38(5): 691-698.

Figures/Tables 5

Table 1

Fig.1

Fig.2

Fig.3

Table 2

References 13

[14]	梁双波, 曹有挥, 吴威. 上海大都市区港口物流企业的空间格局演化[J]. 地理研究, 2013, 32(8):1448-1456.
	[Liang Shuangbo, Cao Youhui, Wu Wei.Spatial pattern evolution of port logistics enterprises in Shanghai metropolitan area. Geographical Research, 2013, 32(8):1448-1456.]
[15]	周蕾, 杨山, 王曙光. 城市内部不同所有制制造业区位时空演变研究——以无锡为例[J]. 人文地理, 2016,31(4):102-111.
	[Zhou Lei, Yang Shan, Wang Shuguang.The temporal and spatial changes of manufacturing location of different ownership in the context of economic transition: a case of Wuxi. Human Geography, 2016,31(4):102-111.]
[16]	宁波市统计局, 国家统计局宁波调查队. 宁波统计年鉴2017[M]. 北京: 中国统计出版社, 2017.
	[Ningbo Municipal Bureau Statistics, NBS Survey Office in Ningbo. Ningbo Statistical Yearbook(2017). Beijing: China Statistics Press, 2017.]
[1]	Hesse M, Rodrigue J P.The transport geography of logistics and freight distribution[J]. Journal of Transport Geography, 2004, 12: 171-184. doi: 10.1016/j.jtrangeo.2003.12.004
[2]	Aljohani K, Thompson R G.Impacts of logistics sprawl on the urban environment and logistics: taxonomy and review of literature[J]. Journal of Transport Geography, 2016, 57: 255-263. doi: 10.1016/j.jtrangeo.2016.08.009
[3]	Sakai T, Kawamura K, Hyodo T.Spatial reorganization of urban logistics system and its impacts: case of Tokyo[J]. Journal of Transport Geography, 2017, 60:110-118. doi: 10.1016/j.jtrangeo.2017.03.001
[4]	阿布都伟力·买合普拉, 杨德刚. 物流地理学研究进展与展望[J]. 地理科学进展, 2012, 31(2):231-238. doi: 10.11820/dlkxjz.2012.02.012
	[Abuduweili Maihepula, Yang Degang.Research Progress of Logistics Geography in China. Progress in Geography, 2012, 31(2):231-238.] doi: 10.11820/dlkxjz.2012.02.012
[5]	韩增林, 王成金, 尤飞. 中国物流业发展与布局的特点及对策探讨[J]. 地理科学进展, 2002, 21(1):81-89. doi: 10.11820/dlkxjz.2002.01.010
	[Han Zenglin, Wang Chengjin, You Fei.The characters of the development and distribution about Chinese Logistics and the discussion of the developing measures. Progress in Geography, 2002, 21(1):81-89.] doi: 10.11820/dlkxjz.2002.01.010
[6]	王成金. 中国物流企业的空间组织网络[J]. 地理学报, 2008, 63(2):135-146. doi: 10.3321/j.issn:0375-5444.2008.02.003
	[Wang Chengjin.Spatial organizational network of logistics company in China. Acta Geographica Sinica, 2008, 63(2):135-146.] doi: 10.3321/j.issn:0375-5444.2008.02.003
[7]	刘承良, 管明明. 低碳约束下中国物流业效率的空间演化及影响因素[J]. 地理科学, 37(12): 1805-1814.
	[Liu Chengliang, Guan Mingming. Spatial Evolution of Chinese Logistics Industry Efficiency Under Low Carbon Constraints and It’s Influencing Factors. Scientia Geographica Sinica, 37(12): 1805-1814.]
[8]	曹卫东. 城市物流企业区位分布的空间格局及其演化——以苏州为例[J]. 地理研究,2011, 30(11): 1997-2007. doi: 10.11821/yj2011110006
	[Cao Weidong.Spatial pattern and location evolution of urban logistics enterprises: taking Suzhou as an example. Geographical Research, 2011, 30(11):1997-2007.] doi: 10.11821/yj2011110006
[9]	蒋天颖, 伍婵提, 陈改改. 浙江省A级物流企业时空格局特征研究[J]. 地理科学, 2017, 37(11):1720-1727.
	[Jiang Tianying, Wu Chanti, Chen Gaigai.Spatio-temporal pattern of Zhejiang A-class logistics enterprise. Scientia Geographica Sinica, 2017, 37(11): 1720-1727.]
[10]	蒋天颖, 史亚男. 宁波市物流企业空间格局演化及影响因素[J]. 经济地理,2015, 35(10): 130-138.
	[Jiang Tianying, Shi Yanan.The spatial pattern evolution and influencing factors of logistics enterprises in Ningbo. Economic Geography, 2015, 35(10): 130-138.]
[11]	千庆兰, 陈颖彪, 李雁, 等. 广州市物流企业空间布局特征及其影响因素[J]. 地理研究, 2011, 30(7): 1254-1261. doi: 10.11821/yj2011070011
	[Qian Qinglan, Chen Yingbiao, Li Yan et al. Spatial distribution of logistics enterprises in Guangzhou and its influencing factors. Geographical Research, 2011, 30(7):1254-1261.] doi: 10.11821/yj2011070011
[12]	陈再齐, 闫小培, 曹小曙. 广州市港口服务业空间特征及其形成机制研究[J]. 地理科学, 2010, 30(1):30-38.
	[Chen Zaiqi, Yan Xiaopei, Cao Xiaoshu.The spatial characters and associated mechanism of port service industries in Guangzhou. Scientia Geographica Sinica, 2010, 30(1):30-38.]
[13]	曹卫东. 港航企业区位特征及其空间关联——以上海港口后勤区为例[J]. 地理研究, 2012, 31(6):1079-1088. doi: 10.11821/yj2012060011
	[Cao Weidong.Study on location features and spatial correlation of port enterprises: taking Shanghai Port Backup Area as an example. Geographical Research, 2012, 31(6):1079-1088.] doi: 10.11821/yj2012060011

		2000年	2005年	2010年	2016年
中心区	数量（个）	24	196	609	1181
中心区	占比（%）	30.00	47.23	53.70	55.32
外围区	数量（个）	54	213	496	825
外围区	占比（%）	67.50	51.33	43.74	38.64
郊区	数量（个）	2	6	29	129
郊区	占比（%）	2.50	1.45	2.56	6.04

变量	模型1	模型2
p_olicy	0.2401^**	0.2248^**
l_andprice	-0.6432^***	–
r_egion	–	-0.4091^**
p_ort	0.1664^**	0.1974^**
lnp_ergdp	0.8904^***	0.9634^***
i_ndu	0.4301^**	0.4360^**
d_ensity	0.1791	0.1813
常数项	7.2023^**	8.0619^**
Pseudo R²	0.5738	0.5361

Spatial Pattern and Location Selection of Port Logistics Enterprises in Ningbo

RichHTML

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 5

References 13

Related Articles 15

Metrics

Comments

Recommended 10

[1]	Renfeng Ma,Xiaojing Zhou,Qian Li. Regional Types of the Characteristic Towns and Its Adaptive Path in the Yangtze River Delta Region [J]. SCIENTIA GEOGRAPHICA SINICA, 2019, 39(6): 912-919.
[2]	Shaobo Wang, Xiaolong Luo, Jianke Guo, Peigang Zhang, Zongni Gu. Dynamic Evolution of Tourism Spatial Structure Under the Improvement of the High Speed Rail Network in Northeast China [J]. SCIENTIA GEOGRAPHICA SINICA, 2019, 39(4): 568-577.
[3]	Shanzhu Cai, Lin Lu. China’s State-level Economic and Technological Development Zones and the Industrial Spatial Pattern Evolution: Empirical Research Based on Panel Data of Prefecture Level Cities [J]. SCIENTIA GEOGRAPHICA SINICA, 2019, 39(3): 415-423.
[4]	Shenglei Fu,Bojie Fu. Concept Clarification of Eco-geography and Analysis of Related Classical Studies [J]. SCIENTIA GEOGRAPHICA SINICA, 2019, 39(1): 70-79.
[5]	Li Yang, Chun Fu. Spatio-temporal Simulation of Gannan Ecological Barrier Under Different Scenarios [J]. SCIENTIA GEOGRAPHICA SINICA, 2018, 38(3): 457-463.
[6]	Gang Li, Lan Yang, Jianxiong He, Qian Liu, Xiliang Chen, Shuyan Xue. The Spatial Pattern and Organization Relation of the Pickup Points Based On POI Data in Xi’an: Focus on Cainiao Stations [J]. SCIENTIA GEOGRAPHICA SINICA, 2018, 38(12): 2024-2030.
[7]	Lei Che, Yongping Bai, Liang Zhou, Fan Wang, Xuepeng Ji, Fuwei Qiao. Spatial Pattern and Spillover Effects of Green Development Efficiency in China [J]. SCIENTIA GEOGRAPHICA SINICA, 2018, 38(11): 1788-1798.
[8]	Jinkai Yu, Jianqiu Ma. Spatial Pattern Evolution of Economic Links in Shandong Peninsula Urban Agglomeration [J]. SCIENTIA GEOGRAPHICA SINICA, 2018, 38(11): 1875-1882.
[9]	Canfei He, Xiangdong Zhu, Yinghui Kong, Wei Li. Agglomeration Economy, Incentive Policy and the Spatial Pattern of Chinese Computer Manufacturing Industry: A Case Study Based on Export Data [J]. SCIENTIA GEOGRAPHICA SINICA, 2018, 38(10): 1579-1588.
[10]	Ge Song, Panpan Wang. Spatial Pattern of Land Use Along the Terrain Gradient of County in Songnen High Plain: A Case Study of Bayan County [J]. SCIENTIA GEOGRAPHICA SINICA, 2017, 37(8): 1218-1225.
[11]	Deyou Meng, Ling Wei, Xinsheng Fan, Chao Gao. “Star-type” High-speed Railway Network and Its Impacts on the Accessibility and Urban Spatial Pattern in Henan, China [J]. SCIENTIA GEOGRAPHICA SINICA, 2017, 37(6): 850-858.
[12]	Bin Yu, Yan Lu, Juxin Zeng, Yuanyuan Zhu. Progress and Prospect on Rural Living Space [J]. SCIENTIA GEOGRAPHICA SINICA, 2017, 37(3): 375-385.
[13]	Yanjun Liu, Junfeng Tian, Zhanhui Fu, Degang Liu. The Evolution of the Relationship Between the Degree of Element Agglomeration and the Level of the Ecological Environment in the Harbin-Dalian Giant Urban Belt [J]. SCIENTIA GEOGRAPHICA SINICA, 2017, 37(2): 172-180.
[14]	Yongming Wang, Meixia Wang, Dianting Wu, Lin Zhao, Jianjun Ding. Spatial Patterns and Determinants of Rural Poverty: A Case of Guizhou Province, China [J]. SCIENTIA GEOGRAPHICA SINICA, 2017, 37(2): 217-227.
[15]	Qingke Yang, Xuejun Duan, Pingxing Li, Lei Wang. The Spatial Pattern and Coordination Analysis Between Degree of Land Development and Use Benefit in Jiangsu [J]. SCIENTIA GEOGRAPHICA SINICA, 2017, 37(11): 1696-1704.