Assessing the welfare impacts of Shared Mobility and Mobility as a Service (MaaS)
By Henrik Becker, Miloš Balać, Francesco Ciari, Kay W. Axhausen. Transportation Research Part A: Policy and Practice, 2018
221 citations recorded by the source corpus.
Abstract Mobility as a Service (MaaS) is an attempt to overcome market segmentation by offering transport services tailored to the individual traveler's needs. An alternative to prior investment into single mobility tools, it may allow less biased mode choice decisions. Such a setting favors shared modes, where fixed costs can be apportioned among a large number of users. In turn, car-sharing, bike-sharing or ride-hailing may themselves become efficient alternatives to public transport. Although early field studies confirm the expected changes away from private car use and towards public or shared modes, impacts are yet to be studied for larger transport systems. This research conducts a first joint simulation of car-sharing, bike-sharing and ride-hailing for a city-scale transport system using MATSim. Results show that in Zurich, through less biased mode choice decisions alone, transport-related energy consumption can be reduced by 25%. In addition, introduction of car-sharing and bike-sharing schemes may increase transport system energy efficiency by up to 7%, whereas the impact of ride-hailing appears less positive. Efficiency gains may be higher if shared modes were used as a substitute for public transport in lower-density areas. In summary, a MaaS scheme with shared mobility may allow to slightly increase system efficiency (travel times & cost), while substantially reducing energy consumption.
Subfields: Automotive Engineering, Transportation
View Paper: https://www.semanticscholar.org/paper/46fc11dfe90e1f481f67936b8b365435b0668a3d
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In Automotive Engineering
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Citations in the corpus
- Mode choice, substitution patterns and environmental impacts of shared and personal micro-mobility (2021, methodology): “The MATSim Zurich scenario has been used extensively in 251 transport planning research (e.g., Balac et al., 2019; Becker et al., 2020; Hörl et al., 2021; 252 Manser et al., 2020) and provides reliable attribute values for the non-chosen alternatives.”