Case Studies
Feb 21, 2022

Case Study of Stratification, Spatial Agglomeration, and Unequal Logistics Industry Development on Western Cities in China

Publication: Journal of Urban Planning and Development
Volume 148, Issue 2

Abstract

There are large heterogeneities in the logistics development of urban agglomerations in western China due to the low compactness and spatial stability of urban agglomerations. Using the statistical yearbook and logistics industry data of 135 cities in western China from 2003 to 2018, we analyzed the spatial distribution characteristics of logistics enterprises using kernel density and cold–hot spot analysis. Simultaneously, economic development level, industrial structure of circulation, and the logistics industry are identified as influencing factors of logistics industry evolution. The comparative and integration analysis of spatial autocorrelation models and geographically weighted regressing models are implemented on the influencing factors of logistics enterprises’ spatial-temporal evolution. Our study revealed that the number and density of logistics enterprises in western China have continually increased in the past 20 years, factors such as per capita gross domestic product, population quantity, population density, the proportion of the tertiary industry, and density of logistics enterprises are all key factors supporting the evolution of the logistics industry in western China. The logistics industry in the western provinces has had outstanding development in the past 20 years; however, there are still obvious regional inequalities due to factors such as infrastructure and policy.

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Data Availability Statement

Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.

References

Barrell, J., and J. Grant. 2013. “Detecting hot and cold spots in a seagrass landscape using local indicators of spatial association.” Landscape Ecol. 28 (10): 2005–2018. https://doi.org/10.1007/s10980-013-9937-2.
Brown, S., V. L. Versace, L. Laurenson, D. Ierodiaconou, J. Fawcett, and S. Salzman. 2012. “Assessment of spatiotemporal varying relationships between rainfall, land cover and surface water area using geographically weighted regression.” Environ. Model. Assess. 17 (3): 241–254. https://doi.org/10.1007/s10666-011-9289-8.
Chan, H. K., J. Dai, X. Wang, and E. Lacka. 2019. “Logistics and supply chain innovation in the context of the Belt and Road Initiative (BRI).” Transp. Res. Part E Logist. Transp. Rev. 132: 51–56. https://doi.org/10.1016/j.tre.2019.10.009.
Chen, S., D. Zhuang, and H. Zhang. 2020. “GIS-based spatial autocorrelation analysis of housing prices oriented towards a view of spatiotemporal homogeneity and nonstationarity: A case study of Guangzhou, China.” Complexity 2020: 1079024. https://doi.org/10.1155/2020/1079024.
Chung, W., and A. Kalnins. 2001. “Agglomeration effects and performance: A test of the Texas lodging industry.” Strateg. Manage. J. 22 (10): 969–988. https://doi.org/10.1002/smj.178.
Cudzilo, M., R. Voronina, D. Dujak, and A. Kolinski. 2018. “Analysing the efficiency of logistic actions in complex supply chains-conceptual and methodological assumptions of research.” Logforum 14 (2): 171–184. https://doi.org/10.17270/j.Log.2018.255.
Folta, T. B., A. C. Cooper, and Y. Baik. 2006. “Geographic cluster size and firm performance.” J. Bus. Venturing 21 (2): 217–242. https://doi.org/10.1016/j.jbusvent.2005.04.005.
Getis, A., and J. K. Ord. 1992. “The analysis of spatial association by use of distance statistics.” Geogr. Anal. 24 (3): 189–206. https://doi.org/10.1111/j.1538-4632.1992.tb00261.x.
Giuffrida, M., R. Mangiaracina, A. Perego, and A. Tumino. 2017. “Cross-border B2C e-commerce to Greater China and the role of logistics: A literature review.” Int. J. Phys. Distrib. Logist. Manage. 47 (9): 772–795. https://doi.org/10.1108/ijpdlm-08-2016-0241.
Hervas-Oliver, J. L., F. Sempere-Ripoll, R. R. Alvarado, and S. Estelles-Miguel. 2018. “Agglomerations and firm performance: Who benefits and how much?” Reg. Stud. 52 (3): 338–349. https://doi.org/10.1080/00343404.2017.1297895.
Hirschinger, M. 2016. “The future of logistics in emerging markets – Fuzzy clustering scenarios grounded in institutional and factor-market rivalry theory.” In Essays on supply chain management in emerging markets, edited by E. Hartmann, 9–42. Wiesbaden, Germany: Springer Fachmedien Wiesbaden.
Huang, Y., L. Li, and Y. T. Yu. 2018. “Do urban agglomerations outperform non-agglomerations? A new perspective on exploring the eco-efficiency of Yangtze River Economic Belt in China.” J. Cleaner Prod. 202: 1056–1067. https://doi.org/10.1016/j.jclepro.2018.08.202.
Huang, Y. P. 2016. “Understanding China’s Belt & Road Initiative: Motivation, framework and assessment.” China Econ. Rev. 40: 314–321. https://doi.org/10.1016/j.chieco.2016.07.007.
Kabak, O., F. Ulengin, and S. O. Ekici. 2018. “Connecting logistics performance to export: A scenario-based approach.” Res. Transp. Econ. 70: 69–82. https://doi.org/10.1016/j.retrec.2018.05.007.
Kauhl, B., J. Schweikart, T. Krafft, A. Keste, and M. Moskwyn. 2016. “Do the risk factors for type 2 diabetes mellitus vary by location? A spatial analysis of health insurance claims in Northeastern Germany using kernel density estimation and geographically weighted regression.” Int. J. Health Geographics 15 (1): 38. https://doi.org/10.1186/s12942-016-0068-2.
Kinra, A., K. S. Hald, R. R. Mukkamala, and R. Vatrapu. 2020. “An unstructured big data approach for country logistics performance assessment in global supply chains.” Int. J. Oper. Prod. Manage. 40 (4): 439–458. https://doi.org/10.1108/ijopm-07-2019-0544.
Lagorio, A., R. Pinto, and R. Golini. 2016. “Research in urban logistics: A systematic literature review.” Int. J. Phys. Distrib. Logist. Manage. 46 (10): 908–931. https://doi.org/10.1108/ijpdlm-01-2016-0008.
Lan, S. L., M. L. Tseng, C. Yang, and D. Huisingh. 2020. “Trends in sustainable logistics in major cities in China.” Sci. Total Environ. 712: 136381. https://doi.org/10.1016/j.scitotenv.2019.136381.
Lean, H. H., W. Huang, and J. J. Hong. 2014. “Logistics and economic development: Experience from China.” Transp. Policy 32: 96–104. https://doi.org/10.1016/j.tranpol.2014.01.003.
Li, J., D.-D. Xiao, H. Lei, T. Zhang, and T. Tian. 2020a. “Using cuckoo search algorithm with Q-learning and genetic operation to solve the problem of logistics distribution center location.” Mathematics 8 (2): 149. https://doi.org/10.3390/math8020149.
Li, K. X., M. J. Jin, G. Q. Qi, W. M. Shi, and A. K. Y. Ng. 2018. “Logistics as a driving force for development under the Belt and Road Initiative - the Chinese model for developing countries.” Transp. Rev. 38 (4): 457–478. https://doi.org/10.1080/01441647.2017.1365276.
Li, Y. X., M. Abdel-Aty, J. H. Yuan, Z. Y. Cheng, and J. Lu. 2020b. “Analyzing traffic violation behavior at urban intersections: A spatiotemporal kernel density estimation approach using automated enforcement system data.” Accid. Anal. Prev. 141: 105509. https://doi.org/10.1016/j.aap.2020.105509.
Li, Z. W., and P. He. 2018. “Data-based optimal bandwidth for kernel density estimation of statistical samples.” Commun. Theor. Phys. 70 (6): 728–734. https://doi.org/10.1088/0253-6102/70/6/728.
Lin, D. W., Z. Z. Cui, V. Chongsuvivatwong, P. Palittapongarnpim, A. Chaiprasert, W. Ruangchai, J. Ou, and L. Huang. 2020. “The geno-spatio analysis of Mycobacterium tuberculosis complex in hot and cold spots of Guangxi, China.” BMC Infect. Dis. 20 (1): 462. https://doi.org/10.1186/s12879-020-05189-y.
Lin, X. Z. 2011. “Guangxi, China-ASEAN uniform information joint development of manufacturing and logistics industry.” Appl. Mech. Mater. 52–54: 2099–2104. https://doi.org/10.4028/www.scientific.net/AMM.52-54.2099.
Liu, B. L., S. J. Lee, J. H. Xiao, L. Wang, and Z. L. Jiao. 2013. Contemporary logistics in China: Transformation and revitalization. Berlin: Springer.
Liu, W., J. Zhang, S. Wei, and D. Wang. 2021. “Factors influencing organisational efficiency in a smart-logistics ecological chain under e-commerce platform leadership.” Int. J. Logist.-Res. Appl. 24 (4): 364–391. https://doi.org/10.1080/13675567.2020.1758643.
Long, R., H. Ouyang, and H. Guo. 2020. “Super-slack-based measuring data envelopment analysis on the spatial-temporal patterns of logistics ecological efficiency using global Malmquist Index model.” Environ. Technol. Innov. 18: 100770. https://doi.org/10.1016/j.eti.2020.100770.
Mahpula, A., D. G. Yang, A. Kurban, and F. Witlox. 2013. “An overview of 20 years of Chinese logistics research using a content-based analysis.” J. Transp. Geogr. 31: 30–34. https://doi.org/10.1016/j.jtrangeo.2013.04.011.
Mangiaracina, R., G. Marchet, S. Perotti, and A. Tumino. 2015. “A review of the environmental implications of B2C e-commerce: A logistics perspective.” Int. J. Phys. Distrib. Logist. Manage. 45 (6): 565–591. https://doi.org/10.1108/ijpdlm-06-2014-0133.
Mothilal, S., A. Gunasekaran, S. P. Nachiappan, and J. Jayaram. 2012. “Key success factors and their performance implications in the Indian third-party logistics (3PL) industry.” Int. J. Prod. Res. 50 (9): 2407–2422. https://doi.org/10.1080/00207543.2011.581004.
Onden, I., A. Z. Acar, and F. Eldemir. 2018. “Evaluation of the logistics center locations using a multi-criteria spatial approach.” Transport 33 (2): 322–334. https://doi.org/10.3846/16484142.2016.1186113.
O’Sullivan, D. 2003. “Geographically weighted regression: The analysis of spatially varying relationships, by A. S. Fotheringham, C. Brunsdon, and M. Charlton.” Geogr. Anal. 35 (3): 272–275. https://doi.org/10.1111/j.1538-4632.2003.tb01114.x.
Özmen, M., and E. K. Aydoğan. 2020. “Robust multi-criteria decision making methodology for real life logistics center location problem.” Artif. Intell. Rev. 53 (1): 725–751. https://doi.org/10.1007/s10462-019-09763-y.
Peeters, A., M. Zude, J. Kathner, M. Unlu, R. Kanber, A. Hetzroni, R. Gebbers, and A. Ben-Gal. 2015. “Getis-Ord’s hot- and cold-spot statistics as a basis for multivariate spatial clustering of orchard tree data.” Comput. Electron. Agric. 111: 140–150. https://doi.org/10.1016/j.compag.2014.12.011.
Pratt, B., and H. J. Chang. 2012. “Effects of land cover, topography, and built structure on seasonal water quality at multiple spatial scales.” J. Hazard. Mater. 209–210: 48–58. https://doi.org/10.1016/j.jhazmat.2011.12.068.
Qi, G., W. Shi, K.-C. Lin, K. F. Yuen, and Y. Xiao. 2020. “Spatial spillover effects of logistics infrastructure on regional development: Evidence from China.” Transp. Res. Part A Policy Pract. 135: 96–114. https://doi.org/10.1016/j.tra.2020.02.022.
State Administration for Industry and Commerce of China. 2014. “China National Enterprise Credit Information Publicity System. n.d.” Details of logistics enterprises nationwide.” Accessed March 1, 2019. http://www.gsxt.gov.cn/index.html/.
Shiu, A., R. Li, and C. K. Woo. 2016. “Economic growth and infrastructure investments in energy and transportation: A causality interpretation of China’s western development strategy.” Energy J. 37: 211–222. https://doi.org/10.5547/01956574.37.SI1.ashi.
Shrestha, A., and W. Luo. 2017. “Analysis of groundwater nitrate contamination in the Central Valley: Comparison of the geodetector method, principal component analysis and geographically weighted regression.” ISPRS Int. J. Geo-Inf. 6 (10): 297. https://doi.org/10.3390/ijgi6100297.
Summers, T. 2016. “China’s ‘new silk roads’: Sub-national regions and networks of global political economy.” Third World Q. 37 (9): 1628–1643. https://doi.org/10.1080/01436597.2016.1153415.
Thai, V. V. 2013. “Logistics service quality: Conceptual model and empirical evidence.” Int. J. Logist. Res. Appl. 16 (2): 114–131. https://doi.org/10.1080/13675567.2013.804907.
van der Zee, E., D. Bertocchi, and D. Vanneste. 2020. “Distribution of tourists within urban heritage destinations: A hot spot/cold spot analysis of TripAdvisor data as support for destination management.” Curr. Issues Tourism 23 (2): 175–196. https://doi.org/10.1080/13683500.2018.1491955.
Viana, M. S., and J. P. Moreno Delgado. 2019. “City logistics in historic centers: Multi-criteria evaluation in GIS for city of Salvador (Bahia - Brazil).” Case Stud. Transp. Policy 7 (4): 772–789. https://doi.org/10.1016/j.cstp.2019.08.004.
Wu, D. 2020. “Spatially and temporally varying relationships between ecological footprint and influencing factors in China’s provinces using geographically weighted regression (GWR).” J. Cleaner Prod. 261: 121089. https://doi.org/10.1016/j.jclepro.2020.121089.
Yu, H., Y. Deng, and S. Xu. 2018. “Evolutionary pattern and effect of administrative division adjustment during urbanization of China: Empirical analysis on multiple scales.” Chin. Geogr. Sci. 28 (5): 758–772. https://doi.org/10.1007/s11769-018-0990-2.
Zhang, J., and X.-P. Liu. 2017. “Evaluation of integrated logistics service based on SERVQUAL model.” In Proc., 2017 International Conference on Computer Systems, Electronics and Control, 1–9. New York: IEEE.
Zhao, M., and X. Liu. 2018. “Development of decision support tool for optimizing urban emergency rescue facility locations to improve humanitarian logistics management.” Saf. Sci. 102: 110–117. https://doi.org/10.1016/j.ssci.2017.10.007.
Zhen, L. I., Y. Yongchun, and Q. Linhuang. 2008. “Difference among the growth of GDP and urbanization of provinces and cities in West China since the reform and opening-up.” China Popul.·Resour. Environ. 18 (5): 19–26. https://doi.org/10.1016/S1872-583X(09)60017-6.
Zhu, M. H., and L. G. Shao. 2020. “An analysis on the economic cooperation and the industrial synergy of the main river region: From the perspective of the Yangtze river economic zone.” J. Ambient Intell. Hum. Comput. 11 (3): 1055–1064. https://doi.org/10.1007/s12652-018-1011-0.
Zou, X., S. Somenahalli, and D. Scrafton. 2020. “Evaluation and analysis of urban logistics competitiveness and spatial evolution.” Int. J. Logist. Res. Appl. 23 (5): 493–507. https://doi.org/10.1080/13675567.2019.1703916.

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Go to Journal of Urban Planning and Development
Journal of Urban Planning and Development
Volume 148Issue 2June 2022

History

Received: Dec 2, 2020
Accepted: Nov 4, 2021
Published online: Feb 21, 2022
Published in print: Jun 1, 2022
Discussion open until: Jul 21, 2022

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Yiwei Zhang [email protected]
Postgraduate, School of Information Management, Jiangsu Key Laboratory of Data Engineering and Knowledge Service, Nanjing Univ., Nanjing 210023, China. Email: [email protected]
Postgraduate, School of Information Management, Jiangsu Key Laboratory of Data Engineering and Knowledge Service, Nanjing Univ., Nanjing 210023, China. Email: [email protected]
Postgraduate, School of Information Management, Jiangsu Key Laboratory of Data Engineering and Knowledge Service, Nanjing Univ., Nanjing 210023, China. Email: [email protected]
Professor, School of Information Management, Jiangsu Key Laboratory of Data Engineering and Knowledge Service, Nanjing Univ., Nanjing 210023, China. Email: [email protected]
Sanhong Deng [email protected]
Professor, School of Information Management, Jiangsu Key Laboratory of Data Engineering and Knowledge Service, Nanjing Univ., Nanjing 210023, China (corresponding author). Email: [email protected]

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