Assessing Urban Logistics Pooling Sustainability via a Hierarchic Dashboard from a Group Decision Perspective

Abstract Purpose Urban logistics pooling is seen as a serious alternative to imposed urban consolidation centers. However, such strategies are quite new in urban distribution and merit to be evaluated using adapted methods that take into account the group decision nature of resource pooling. This chapter aims to propose, via an experimental collaborative decision support method, to define a grid of indicators and a reference situation database to measure the sustainable performance of urban logistics pooling systems. Methodology The proposed methodology combines a systematic literature analysis of Key Performance Indicators and a group decision support method to choose a suitable set to define a dashboard. First, we identify the main sustainability indicators from an overview of the literature, and class them into the categories of the 4As Sustainable Transport vision (i.e., Awareness, Act and shift, Avoidance, and Anticipation). Then, a group of 20 experts is solicited for an iterative experimental group decision-making method to converge to the concordance of a set of indicators. Findings The method allowed us to define a hierarchic dashboard agreed by all experts with seven main indicators and nine secondary indicators. Moreover, the experts signaled the need of defining a unified basis of comparison to estimate initial situations. To do this, we proposed a database of urban routes from the French Surveys on Urban Goods Transport. Research limitations The proposed dashboard is an example, and to provide a more unified one, the experience has to be iterated using different groups of decision-makers. Practical implications This method has the advantage of proposing a dashboard agreed by all involved stakeholders. Therefore, this chapter shows the patterns to reproduce it since the method is able to be replicated in any context of group decision in urban logistics. Originality/value The originality of the chapter arises on the use of an experimental group decision method using a group with a majority of practitioners, and to validate it by consensus.