Connected shared mobility for passengers and freight: Investigating the potential of crowdshipping in urban areas

Passengers and freight mobility in urban areas represents an increasingly relevant component of modern city life. On one side, it fosters economic growth, but, on the other, it also generates high social costs. Congestion and pollution are two problems policy-makers want to curb adopting appropriate measures. The pervasive use of information and communication technology will contribute to the fuller affirmation of the sharing economy paradigm. In this context, connected shared mobility can play a crucial role in relieving cities from transport-related negative externalities. This paper analyses the feasibility and behavioral levers that might facilitate the diffusion of crowdshipping in urban areas. Two are the main objectives the paper pursues. First: investigate under which conditions passengers would be willing to act as crowdshippers. Second: find out under which conditions people would be willing to receive their goods via a crowdshipping service. Crowdshipping can generate positive impacts such as the reduction of total and ad-hoc trips, by optimizing, through sharing, the use of resources and infrastructures. The study described in this paper represents a preliminary investigation, focusing on University students, to acquire the necessary knowledge base for developing a stated preference research endeavor. Preliminary results show that 87% of students would, in principle, be willing to act as crowdshippers (i.e. supply) with an adequate compensation, while 93% of them are willing to receive their goods through a crowdshipping system (i.e. demand) under certain conditions, especially characterized by delivery timing and punctuality.

 

Marcucci, E., Le Pira, M., Carrocci, C. S., Gatta, V., Pieralice, E. (2017), “Connected shared mobility for passengers and freight: Investigating the potential of crowdshipping in urban areas”, In 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS), 2017 (pp. 839-843). IEEE