This chapter presents four contrasted and near-caricatured scenarios of retail location and distribution, and compares them on the bases of both road occupancy rates and greenhouse gas emissions. Two main families of scenarios are defined: retailing land-use scenarios, based on the location of the different retailing activities of a city; and end-consumer delivery organizational scenarios, based on the definition of new services to deliver end-consumers, at home or to reception points. Those scenarios are simulated using an integrated approach combining inter-establishment goods transport flows, shopping trips, and end-consumer deliveries. The assessment approach is able to show the relation between several aspects of retailing deployment (mainly store location, catchment area's supply, and urban retailing planning policies) and both upstream distribution of goods to retailers and downstream usage of private vehicles for shopping. Although scenarios are extreme and contrasted, they are able to identify the limits and forces of the different retailing strategies in urban zones.
TopIntroduction
City logistics aims to study the urban part of the logistic chain and more precisely freight movements (in their different form) in order to reduce costs, externalities and nuisances related to urban goods transport. Several methods and approaches are found in literature (Taniguchi et al., 2001; van Binsbergen & Visser, 2002; Anderson et al., 2005; Ambrosini et al., 2008; Craninc, 2008; Gonzalez-Feliu, 2008; Quak, 2008). However, most works focus on final deliveries to retailers, and not on the other part of the urban supply chain, that of end-consumer movements (Russo and Comi, 2006; Gonzalez-Feliu et al., 2010). Three main types of flows can be related to goods transport in urban areas (Ségalou et al., 2004): inter-establishments movements (IEM) are related to freight distribution between the different activities, i.e. the exchange of goods between establishments; end-consumer movements (ECM) can be defined as the trips where the purchased goods are transporter near the consumer’s location, and urban management movements (UMM) include all flows related to the logistics activities of the city and its infrastructures (waste management, building, road and network construction and maintenance, postal services, household and enterprise moving actions, etc.). The first group of urban freight movements has been one of the most studied subjects in city logistics research. The second group, commonly studied in other fields but often not modelled as a part of the global urban freight distribution chain, is however an important component in terms of traffic volumes. According to Gonzalez-Feliu et al. (2012a), shopping trips represent in France between 10% and 25% of the total person trips, depending on the day of the week, and almost half of the total rad occupancy issues (in km.PCUs, i.e. Private Car Units) of urban goods transport flows. In terms of pollution, the urban transport of goods, including end-consumer movements, produces about 25% of the total CO2 emissions for transport, 35% of the NOx emissions and 40 to 50% of the solid particles (Ségalou et al., 2004).
Moreover, shopping trip behaviour is directly related to retailing land-use policies and to new services to consumers, like e-commerce and proximity delivery distribution services. Furthermore, those actions have also a direct impact on deliveries to retailing activities, showing that the link between IEM and ECM is crucial in urban logistics. It is then important to estimate the impacts of such policies and actions on the overall urban goods transport system, i.e. that which combines IEM, ECM and UMM flows. However, UMM being indirectly related to the other two flows, can be studied in a second time.
The aim of this chapter is to propose and examine four extreme scenarios and estimate the impacts of the actions they represent on both road traffic flows (in terms of rad occupancy issues) and greenhouse gas emissions. First, the simulation methodology used to estimate the impacts of the scenarios on urban goods flows is presented. Second, the proposed scenarios are described. Third, the four scenarios are simulated and the results compared and discussed. Finally, as a conclusion, the main strengths and limits of the analysis are presented, as well as further developments.