Jesus Gonzalez-Feliu and Joëlle Morana
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…
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.
Details
Keywords
Joëlle Morana and Jesus Gonzalez-Feliu
The purpose of this paper is to propose a sustainable dashboard for evaluating the sustainable performance of urban delivery systems from the perspective of operational logistics…
Abstract
Purpose
The purpose of this paper is to propose a sustainable dashboard for evaluating the sustainable performance of urban delivery systems from the perspective of operational logistics managers, one of the categories of stakeholders given less consideration by public authorities in their quest for consensus.
Design/methodology/approach
First, a synthesis of the main works on the subject is proposed to provide a common grid of economic, environmental and social/societal indicators for sustainable supply chain management (SSCM), after which the method for defining the dashboard is presented. This method is derived from a collaborative decision-support approach and applied to a panel of operational logistics managers. Using a co-constructive method, a group of experts is consulted first separately, then by small groups and then a group restitution and consensus search process is made to find an agreed-upon set of indicators.
Findings
The results show a difference between the indicators chosen in the individual phase and those defined in small groups. They also show a gap between classical expert-obtained indicators (mainly made by one or a small group of non-operational experts) and the proposed dashboard, made by and for operational managers.
Originality/value
The originality of the paper is that it addresses two issues (urban logistics evaluation and consensus search) by using methods of natural and active pedagogy and shows by an experimental method the interests and opportunities of collaboration in defining sets of indicators for urban logistics evaluation.
Details
Keywords
Daphne Greiner and Jean-François Lemoine
Past research has emphasised the potential for conversational artificial intelligence (AI) to disrupt services. Conversely, the literature recognises customer expectations as…
Abstract
Purpose
Past research has emphasised the potential for conversational artificial intelligence (AI) to disrupt services. Conversely, the literature recognises customer expectations as fundamental to service quality and customer satisfaction. However, the understanding of users’ expectations for conversational AI services is currently limited. Building upon previous research that has underscored the importance of users’ expertise, this study aims to provide valuable insights into the expectations of users with varying levels of expertise.
Design/methodology/approach
Forty-five semi-structured interviews were conducted, on three populations: experts, quasi-experts and non-experts from various countries including Japan, France and the USA. This includes 10 experts and 11 quasi-experts, as in professionals in conversational AI and related domains. And 25 non-experts, as in individuals without professional or advanced academic training in AI.
Findings
Findings suggest that users’ expectations depend on their expertise, how much they value human contact and why they are using these services. For instance, the higher the expertise the less anthropomorphism was stated to matter compared to technical characteristics, which could be due to a disenchantment effect. Other results include expectations shared by all users such as a need for more ethics including public interest.
Originality/value
The study provides insights into a key yet relatively unexplored area: it defines three major expectations categories (anthropomorphic, technical and ethical) and the associated expectations of each user groups based on expertise. To the best of the authors’ knowledge, it also highlights expectations never detected before as such in the literature such as explainability.