Modeling the Spatial Dimensions of Warehouse Rent Determinants: A Case Study of Seoul Metropolitan Area, South Korea

Abstract

The spatial mismatch between warehouse locations and urban freight demand mainly driven by logistics sprawl can have negative environmental impacts, due to the increase in average trucking distances. This study investigated the spatial dimension of warehouse rent determinants identifying the regional specifics of supply and demand of warehouse facilities and services. Based on the case of the Seoul Metropolitan Area in South Korea, spatial autoregressive regression (SAR) and mixed geographically weighted regression (MGWR) models were developed to explain the spatial stationary and non-stationary relationship between warehouse rent and the explanatory variables, including the transactional characteristics of the rental contracts, physical characteristics of the buildings, location factors, and various warehousing services. The MGWR results identified the distance to the nearest highway interchange, repackaging service, and built-in ramps as globally fixed variables and contract floor space, total building floor space, building age, and land price as locally varying variables. The results of this study allowed us to provide meaningful insights into the sustainable development of urban logistics facilities through a better understanding of the interaction between logistics activities, transportation infrastructure, and land use.

Overseas Warehouse Deployment for Cross-Border E-Commerce in the Context of the Belt and Road Initiative

“…In this paper, we investigated the determination factors of overseas warehouses for cross-border e-commerce and proposed a comprehensive method combined with E-TOPSIS and centrality in complex networks to find the optimal overseas warehouse locations for Chinese export products along the B&R. Our main findings are as follows: (1) Consistent with the findings of many previous studies on logistics warehouse locations, results show that freight demand is the most important factor influencing cross-border e-commerce overseas warehouse locations [49,50], followed by economic development level (GDP and PPC). This is mainly because trade demand is the key cause of logistics, and the level of economic development or GDP and per capita consumption of a region determines the trade demand of the area; (2) The betweenness centrality and outdegree centrality in a global trade network and the logistics infrastructure are also important factors in cross-border e-commerce overseas warehouse locations, which just ranked fourth, fifth, and sixth, respectively.…”

‘Proximity logistics’: Characterizing the development of logistics facilities in dense, mixed-use urban areas around the world

“…To discuss the development of logistics facilities in dense and mixed-use urban areas, we introduce the term 'proximity logistics'. It is anecdotally observed in various cities including Amsterdam, the Netherlands (Ploos Van Amstel et al, 2021); London, United Kingdom (Steer & Cross River Partnership, 2020); Paris, France (Dablanc, 2018); Seoul, South Korea (Lim and Park, 2020); Shenzhen, China (Xiao et al, 2021); and various cities in the United States (Kang, 2020).…”

Spatiotemporal Distribution Characteristics and Driving Forces of PM2.5 in Three Urban Agglomerations of the Yangtze River Economic Belt

“…The bandwidth and local regression coefficients are commonly used for the impact analysis of driving force factors [ 60 , 65 ]. The most significant advantage of the MGWR model was that it not only allowed the spatial variation of each parameter estimate but also generated a separate optimal bandwidth for the conditional relationship between the response variable and each predictive variable, simulating the spatial variation process under different spatial scales.…”