This chapter proposes a decision support system, STG-Sim, that estimates the number of shopping trip chains as well as the related distances to assess the impacts of the retailing structure on the final part of goods transport chains: that of bringing purchased goods to the end-consumer's location. First, the methodological framework of the shopping trip chain estimation is proposed. It includes a generation model (for both motorized and pedestrian trips), a catchment area distribution model (to relate the shopping locations to the household's ones), and a distance estimation procedure. An application to the deployment of four retailing poles (two new ones and two extension ones) in Lyon, France, is also presented. Finally, practical implications and further developments are presented.
TopIntroduction
Urban logistics is often associated to retailers’ final deliveries, although those flows represent about 15% of the total urban goods flows in number of trips, and only 10% of the road occupancy issues (Gonzalez-Feliu, 2018). Motorized shopping trips, which represent about 25% of such flows in number of trips and about 40% of road occupancy issues, are less studied in urban logistics since they are often associated to personal transport (Gonzalez-Feliu, 2018). Moreover, pedestrian shopping trips are also little studied, even in personal transport, since their contribution to road congestion is not relevant. Therefore, shopping trip estimation remains a challenging subject; indeed those trips present specific characteristics that make classical models not able to easily identify.
Although less popular than delivery trip modelling, shopping trip modelling has led to a non-negligible number of paper, from which two main categories of models are seen: behavioral approaches, mainly based on discrete choice and tour construction models (Russo & Comi, 2010; Barone et al., 2014; Nuzzolo et al., 2014), and classical generation-distribution models, mainly based on gravity or entropy distribution models (Ségalou, 1999; Gonzalez-Feliu et al., 2010a,b, 2012b).
With new modes of retailing, sales and consumption, identifying and measuring shopping trips has been a crucial issue for some practitioners, like urban planners of commercial managers, among others. Moreover, the estimation of those trips needs to be made in a geo-spatial logic. However, and opposing to some freight delivery models which can propose individual generation and route construction models (i.e. related to each single establishment or economic activity), shopping trips are estimated on the basis of global surveys which do not allow a statistical representativeness for geo-located actions (i.e. at the individual level), but can be applied at a zonal level. In that context, a zonal-based model can be a good alternative to estimate shopping trips and the impacts of new retailing developments.
The aim of this chapter is to present the STG-Sim methodology, as well as to illustrate them via an example. First, the main categories of urban goods transport movements are presented, focusing on end consumer’s movements (ECM), and the main modelling frameworks to estimate them overviewed, to then position the needs of addressing shopping trip modelling in urban goods transport. Then, the methodology of STG-Sim is presented. We address the main issues in the definition of shopping trips, the main phases of the methodology (generation, distribution and distance estimation) as well as the calibration of the different models, for both motorized and pedestrian shopping trips. After that, an example of application on the urban area of Lyon is proposed. Finally, practical implications and further developments are presented.