Industrial space demand and freight transportation activity: exploring the connection

Lindsey, Christopher; Mahmassani, Hani S.; Mullarkey, Matt; Nash, Terry; Rothberg, Steven

doi:10.1016/j.jtrangeo.2014.04.009

Cited by 25 publications

(10 citation statements)

References 14 publications

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“…However, some scholars studied the spatial and temporal distribution characteristics of urban agglomeration logistics [18,19]. Lindsey et al [20] studied the relationships among freight transport, economic market drivers, and industrial space demand. Kumar et al [21] investigated spatial patterns of transportation and logistics cluster in the US regions, applying spatial cluster and econometric analyses.…”

Section: Urban Agglomeration Logisticsmentioning

confidence: 99%

Multimodal Green Logistics Network Design of Urban Agglomeration with Stochastic Demand

Jiang

Zhang

et al. 2019

Journal of Advanced Transportation

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This study investigates a multimodal green logistics network design problem of urban agglomeration with stochastic demand, in which different logistics authorities among the different cities jointly optimize the logistics node configurations and uniform carbon taxes over logistics transport modes to maximize the total social welfare of urban agglomeration and consider logistics users’ choice behaviors. The users’ choice behaviors are captured by a logit-based stochastic equilibrium model. To describe the game behaviors of logistics authorities in urban agglomeration, the problem is formulated as two nonlinear bilevel programming models, namely, independent and centralized decision models. Next, a quantum-behaved particle swarm optimization (QPSO) embedded with a Method of Successive Averages (MSA) is presented to solve the proposed models. Simulation results show that to achieve the overall optimization layout of the green logistics network in urban agglomeration the logistics authorities should adopt centralized decisions, construct a multimode logistics network, and make a reasonable carbon tax.

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Section: Urban Agglomeration Logisticsmentioning

confidence: 99%

Multimodal Green Logistics Network Design of Urban Agglomeration with Stochastic Demand

Jiang

Zhang

et al. 2019

Journal of Advanced Transportation

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“…It is important to know the location of the warehouses by urban planners to define public policies applied to urban freight transport, to the city livability and the economic development (Healey, 2006). The cost of transportation and the operational efficiency of their activities are fundamental for the companies, and the location has a direct impact on them (Lindsay et al, 2014). Therefore, they try to locate their facilities strategically close to their main consumer market (Bowen, 2008).…”

Section: Wsb Journal Of Business and Financementioning

confidence: 99%

How to explain the location of logistics warehouses from the urban quality-of-life index and the local supply index?

Oliveira

Araújo

Oliveira

2019

WSB Journal of Business and Finance

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Warehouses are a fundamental element for the supply chain and, consequentially, provide resources for people to perform their daily tasks. Their location determines the type of goods movements that will be performed in the city area. Knowing their location is essential to define public policies applied to urban freight transport, city livability and economic development. In the search to make a better diagnosis of its area, the Belo Horizonte City Hall developed the urban quality-of-life index (UQLI) and the local supply index (LSI). This article used linear regression to identify the correlation amongst the UQLI, the LSI and the location of the logistics warehouses in urban areas. The best model obtained from the econometric analysis is the one that correlates warehouses with supermarkets, bookstores and stationery, residential area, quality of the house, bank and gas station. The results obtained were confirmed with spatial analysis. This result allows concluding that the warehouses are influenced by the favourable zoning, low land cost, proximity of regional and main streets of the city and high population and retailer density.

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“…calibrated, land use types do not capture actual resulting levels of activity -uses can become dormant. Often, employment data is used as a coarse activity metric (Holguín-Veras et al, 2012), though the relationship between employment and freight generation does not hold true between different land use divisions (Holguín-Veras et al, 2011, Lindsey et al, 2014, Joubert and Axhausen, 2011.…”

Section: Land Use Input Definitionsmentioning

confidence: 99%

“…Demand is highly heterogeneous, and may respond depending on freight transportation options. Economic conditions and fiscal shocks can provoke structural shifts in logistics patterns, which modelers must consider when attempting to formulate forward predictions (Lindsey et al, 2014).…”

Section: Demand Conditionsmentioning

confidence: 99%

Conceptualizing freight generation for transport and land use planning: A review and synthesis of the literature

et al. 2019

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Freight generation and movement patterns are not well understood by planners and policy-makers tasked with making complex strategic land use and transport planning decisions. In the absence of detailed planning evidence, they may rely on scant or anecdotal data, extrapolated and presented through complex quantitative models. Unfortunately, predictive model outputs can fail to accurately match observed outcomes, and such models cannot predict complex long-term phenomena which may transformatively disrupt freight production and movement patterns. Through a review of the literature, we apply Porter's Diamond Model of Competitive Advantage (Porter 1990) to develop a novel conceptual framework for freight generation. We illustrate how emerging themes and new evidence of relevant economic, environmental, social, and governmental factors can be meaningfully structured within this conceptual framework. By compiling recent evidence of spatio-temporal complexity from the literature, we highlight the utility of such a framework in assisting planners and decision-makers to incorporate a wider set of freight generation factors-particularly demand factors, land use relocation effects, shifting firm strategies, and emerging transport technologies-in the practices of understanding, modeling, planning, and managing urban freight. Application of the framework should assist in ensuring that significant factors and phenomena are not ignored in critical planning decisions, encourage the input of a more diverse set of planning expertise at the policy-making table, and throw renewed emphasis on potential qualitative and mixed-methods freight case study research.

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Industrial space demand and freight transportation activity: exploring the connection

Cited by 25 publications

References 14 publications

Multimodal Green Logistics Network Design of Urban Agglomeration with Stochastic Demand

Multimodal Green Logistics Network Design of Urban Agglomeration with Stochastic Demand

How to explain the location of logistics warehouses from the urban quality-of-life index and the local supply index?

Conceptualizing freight generation for transport and land use planning: A review and synthesis of the literature

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