Exploring the contextual factors behind various phases in logistics sprawl: The case of Seoul Metropolitan Area, South Korea

Kang, Sanggyun

doi:10.1016/j.jtrangeo.2022.103476

Cited by 11 publications

(2 citation statements)

References 34 publications

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“…For the former, most scholars focus on the study of geographical distribution, spatial pattern and network structure of specific logistics spaces such as airports [27], ports [28], logistics parks [29], and logistics centers or bases [30], and the gradual agglomeration of logistics spaces to the suburbs has become a consensus in the academic community. For the latter, Kang [31], Dablanc [32] and Rivera-Blasco [33] analyzed the stage characteristics and driving factors of logistics expansion in the Seoul metropolitan area of South Korea, in Los Angeles, California, in Seattle, Washington and in Madrid, Spain. Opasanon [34] conducted an exploratory study on the urban and spatial impacts of logistics facility relocation by hierarchical analysis.…”

Section: Logistics Facility and Spatial Planningmentioning

confidence: 99%

Evolution Model and Driving Mechanism of Urban Logistics Land: Evidence from the Yangtze River Delta

Cao,

Zhu,

Zhu

et al. 2024

Land

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Logistics land is the spatial carrier for the development of logistics enterprises. Its evolution mode and driving mechanism determine the level of high-quality development of the logistics industry, and serve as an important basis for urban planning and territorial spatial planning. This study introduced a Boston consulting group (BCG) matrix and geographically weighted regression (GWR) spatial econometric models to carry out empirical research on the Yangtze River Delta (YRD), in an effort to provide scientific information for evidence-based decision-making by governments and enterprises. The scale and ratio of logistics land (LLS and LLR) in the YRD showed significant spatial heterogeneity and autocorrelation, cities with large logistics land use converging from clusters to belts from 2000 to 2020, and agglomerations with high logistics land ratio (LLR) migrating from inland to coastal areas. Diversified models of logistics land evolution also emerged, such as high scale–high speed cities, low scale–low speed cities, high scale–low speed cities, and low scale–high speed cities. In addition, the driving mechanism of LLS and LLR was very complex, with a great difference in the intensity, nature and spatial effects of the influence of different factors. The inspiration from empirical case studies is urgent to revise the planning norms and clarify the LLS and LLR control standards for logistics land use. Meanwhile, the synergistic development target of the logistics industry in the new era is changing from the manufacturing industry to the commerce and trade industry; the establishment of planning zoning and the designing of differentiated management policies significantly improve the planning applicability.

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Section: Logistics Facility and Spatial Planningmentioning

confidence: 99%

Evolution Model and Driving Mechanism of Urban Logistics Land: Evidence from the Yangtze River Delta

Cao,

Zhu,

Zhu

et al. 2024

Land

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“…The logistics facilities have been moving outward away from inner urban areas to suburban areas due to the land policy and higher rents, which have received many attentions from both policy makers and academics. Particularly, logistics sprawl has resulted in the increased distance travelled by freight vehicles [5], then the increased quantity of transportation externalities (e.g. vehicle exhaust emission, greenhouse gas emissions, increasing fuel consumption and congestion, etc.).…”

Section: Introductionmentioning

confidence: 99%

Using evolutionary game theory to study the layout of urban distribution centers with considering consumers' green preference

li,

Wei,

Wang

et al. 2023

Preprint

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The geographical layout of urban distribution centers (DCs) affects not only the efficiency of distribution activities, but also the amount of negative externalities arising from delivery vehicles. Recently, the phenomenon of logistic sprawl has significantly reduced the social welfare as more negative externalities are produced. Government should play key role in optimizing the layout of urban DCs through incentive policy. For the first time, we apply the evolutionary game theory in controlling the layout of urban DCs with considering consumers’ green preference. We have developed a basic evolutionary game model based on static tax and subsidy to investigate the interactive mechanism between distribution enterprises (DEs) and government. Then we analyze the evolutionary behavior of DEs and government in three dynamic mechanisms: dynamic tax and static subsidy, dynamic subsidy and static tax, and dynamic tax and dynamic subsidy. Finally, a case study of optimizing the layout of DCs of Beijing is conducted. The simulation results show that the static tax and static subsidy mechanism cannot reach an evolutionary stable point, the three dynamic mechanisms can get the evolutionary stable state (ESS) effectively, in which the dynamic subsidy and static taxation is most effective for reaching the highest level of stable proportion state. In addition, we perform a sensitivity analysis to evaluate the influence of consumers' green preference on the evolutionary path of green DEs. This study can provide theoretical support for the government to formulate scientific incentive policies to guide the rational layout of urban DCs.

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Spatial patterns and investments in warehouses

Dablanc,

Heitz

2024

Advances in Transport Policy and Planning

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Exploring the contextual factors behind various phases in logistics sprawl: The case of Seoul Metropolitan Area, South Korea

Cited by 11 publications

References 34 publications

Evolution Model and Driving Mechanism of Urban Logistics Land: Evidence from the Yangtze River Delta

Evolution Model and Driving Mechanism of Urban Logistics Land: Evidence from the Yangtze River Delta

Using evolutionary game theory to study the layout of urban distribution centers with considering consumers' green preference

Spatial patterns and investments in warehouses

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