Distribution structures and distribution centre (DC) locations are essential for logistics companies to optimise logistics costs and service levels. This paper reviews Supply Chain Management (SCM), Geography and Economic Geographic literature on distribution structure and DC locations decision-making. Two central decision-making elements are discussed: process steps and decision-making factors. Added value of our paper is 1) A literature review 2) Conclusions on the state of current scientific knowledge in three research streams 3) A research agenda. Reviewing literature shows decision-making factors are renowned, however, importance of factors in each process step is unknown. Results also show literature diverges on which process steps logistics companies take (descriptive) or should optimally take (prescriptive) in distribution structure and DC location decision-making. Thus, more research is needed. Developing a descriptive conceptual model and testing on several industry sectors will be valuable to understand differences on distribution structure and DC location decision-making.
As society has to adapt to changing energy sources and consumption, it is driving away from fossil energy. One particular area of interest is electrical driving and the increasing demand for (public) charging facilities. For municipalities, it is essential to adapt to this changing demand and provide more public charging facilities.In order to accommodate on roll-out strategies in metropolitan areas a data driven simulation model, SEVA1, has been developed The SEVA base model used in this paper is an Agent-Based model that incorporate past sessions to predict future charging behaviour. Most EV users are habitual users and tend to use a small subset of the available charge facilities, by that obtaining a pattern is within the range possibilities. Yet, for non-habitual users, for example, car sharing users, obtaining a pattern is much harder as the cars use a significantly higher amount of charge points.The focus of this research is to explore different model implementations to assess the potential of predicting free-floating cars from the non-habitual user population. Most important result is that we now can simulate effects of deployement of car sharing users in the system, and with that the effect on convenience for habitual users. Results show that the interaction between habitual and non habitual EV users affect the unsuccessful connection attempts based increased based on the size of the car-sharing fleet up to approximately 10 percent. From these results implications for policy makers could be drawn.
MULTIFILE
05/21/2019
Several studies show that logistics facilities have spread spatially from relatively concentrated clusters in the 1970s to geographically more decentralized patterns away from urban areas. The literature indicates that logistics costs are one of the major influences on changes in distribution structures, or locations and usage of logistics facilities. Quantitative modelling studies that aim to describe or predict these phenomena in relation to logistics costs are lacking, however. This is relevant to design more effective policies concerning spatial development, transport and infrastructure investments as well as for understanding environmental consequences of freight transport. The objective of this paper is to gain an understanding of the responsiveness of spatial logistics patterns to changes in these costs, using a quantitative model that links production and consumption points via distribution centers. The model is estimated to reproduce observed use of logistics facilities as well as related transport flows, for the case of the Netherlands. We apply the model to estimate the impacts of a number of scenarios on the spatial spreading of regional distribution activity, interregional vehicle movements and commodity flows. We estimate new cost elasticities, of the demand for trade and transport together, as well as specifically for the demand for the distribution facility services. The relatively low cost elasticity of transport services and high cost elasticity for the distribution services provide new insights for policy makers, relevant to understand the possible impacts of their policies on land use and freight flows.
