Università degli studi di Modena e Reggio Emilia

Since the global request for freight transportation is increasing as a consequence of the increasing requirements of the modern economy, logistics processes need to be optimized through the application of innovative technologies, to ensure a high level of quality, flexibility, and effectiveness in logistics operations. The adoption of innovative technologies allows the creation and development of new products and services, able to optimize the existing logistics processes and create value. In particular, one of the most promising technology for logistics applications is the 5G communication network that allows, together with companion technologies such as the Internet of Things, Artificial Intelligence, and the Cloud, the collection, integration, and sharing of a large amount of data from different sources. However, to ensure the market adoption of innovative products and services, the different actors and stakeholders of the logistics chain must be involved from the early stages of the development. This allows them to keep into account their actual needs in the development process of the business models and for the future exploitation of the solutions. This paper analyzes the process of development of collaborative business models in the context of 5G-LOGINNOV, a project aimed at the development of 5G-based solutions to optimize the logistics operations in ports and retro-ports.

This paper proposes a methodology to assess the impact of shared light electric vehicles in urban areas. The proposed approach consists of the comparison between the emissions and costs of travels carried out by traditional cars fueled by gasoline and those performed by shared light electric vehicles in six European cities (Bari, Berlin, Genoa, Malaga, Rome and Trikala) located in four different European countries (Italy, Germany, Spain and Greece). Based on the number of kilometers traveled and a set of conversion factors, the environmental impact and the cost of fuel/electricity are assessed for the two transport modes. Furthermore, the paper proposes a methodology to create a geographical scaled up scenario that allows to evaluate emissions and costs in case of an increased use of shared electric vehicles. The data analyzed revealed that the travel time of L-category electric vehicles might be longer compared to cars. Furthermore, by replacing car trips with L-category electric vehicles, CO 2 emissions could decrease of more than 70% in one year, thus reducing about 6, 082 kg of CO 2 emissions.