How much is trust: The cost and benefit of ridesharing with friends. (September 2017)

• Record Type: Journal Article
• Authors: Wang, Yaoli; Winter, Stephan; Ronald, Nicole
• Is Part Of: Computers, environment and urban systems. Volume 65(2017)
• Page Start: 103
• Page End: 112
• Publication Date: 2017-09
• Subjects: Ridesharing -- Social network -- Agent-based simulation -- Collaborative travel -- Trust -- Complex travel behaviour; City planning -- Data processing -- Periodicals; Regional planning -- Data processing -- Periodicals; 303.4834
• DOI: 10.1016/j.compenvurbsys.2017.06.002
• Languages: English
• ISSNs: 0198-9715

Abstract

Abstract: Ridesharing with social contacts (i.e., 'friends') is substantially more accepted than with strangers. However, limiting ridesharing to friends while rejecting strangers also reduces ride choices and increases detour costs. This work studies, from a theoretical perspective, whether the additional detour costs of limiting shared rides to social network contacts would be prohibitive. It proposes a social network based ridesharing algorithm with heterogeneous detour tolerances for varied social contacts. The theoretical matching rates and detour costs are compared in a simulation for three levels of social connectivity: travelling with direct contacts only, with direct and indirect contacts, or with anyone. The simulation allows for a systematic and comprehensive testing of system behaviour when varying the parameters of social network structure, detour tolerance, and spatial distribution of friendship. Results show that for a clustered friendship – the expected spatial distribution of a social network growing with a ridesharing network – ridesharing with friends does not cause significantly higher costs. Furthermore, the algorithm prioritising friends can substantially increase the matching of friends. An empirical study justifies the findings. Highlights: Considering social network preferences in ridesharing to encourage motivation Providing a social network based ridesharing algorithm Systematic testing of the algorithm with agent-based simulation Explaining the system from a theoretical perspective of geography