A Consensus-based Approach for Team Allocations: the Case of Logistics in Campania Region

Clara Bassano, Maria Vincenza Ciasullo, Matteo Gaeta, Luigi Rarità


This work proposes a competence-based approach, enriched by consensus, for deciding on team compositions, in particular, time- and quality-dependent contexts, where teams have to perform some assigned activities. This problem is very relevant for the dynamics of logistic networks whose nodes are warehouses, distribution centers, and small family businesses that deal with work orders that have to be satisfied. The approach consists of models that focus on workers’ competences by using the Knowledge, Skills, and Attitudes model for workers’ knowledge representation, and competence models to describe the activities to be performed. Some consensus strategies among workers are then used to obtain the correct choice of teams to assign to the various work orders. According to the concept of value co-creation, this paper proposes an original and hybrid approach, based on competences and enriched by consensus, in order to obtain and select the most “suitable” teams for the activities to be performed. This approach is tested, carefully and in depth, on the real case of a small family business inside a sophisticated logistics area, consisting of a fleet of trucks that, by transporting goods from one point to another, underpins the logistics chain inside the Campania region (Italy). These areas of logistics consider small family businesses, which manage the maintenance and repair or trucks, as highly critical nodes of the system. We show that our approach produces results similar to the decisions made by the leader of such a small family business.


Logistics; competence; consensus; experience

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DOI: 10.7250/csimq.2016-6.02


1. Monitoring Viability and Sustainability in Healthcare Organizations
Marialuisa Saviano, Clara Bassano, Paolo Piciocchi, Primiano Di Nauta, Mattia Lettieri
Sustainability  vol: 10  issue: 10  first page: 3548  year: 2018  
doi: 10.3390/su10103548


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