Start Date
10-12-2017 12:00 AM
Description
Carsharing offers an ecologically friendly alternative to private car ownership, helping to alleviate urban mobility problems and pave a path toward a sustainable future for transportation. However, several obstacles in carsharing service management must be overcome in order to take full advantage of its potential as a mainstream mode of transportation. Among others, substantial barriers to involvement include the challenges regarding vehicle supply and demand management. Following a design science research approach, we develop a concept of area-based pricing strategy, presenting an innovative approach to spatial vehicle supply and demand management. We further support this new methodology by developing a decision support system framework for pricing area construction followed by a practical application. The results reveal that pricing areas reduce the need for vehicle relocations while facilitating better vehicle availability.
Recommended Citation
Brendel, Alfred Benedikt; Brennecke, Julian Tim; Zapadka, Patryk; and Kolbe, Lutz Maria, "A Decision Support System for Computation of Carsharing Pricing Areas and its Influence on Vehicle Distribution" (2017). ICIS 2017 Proceedings. 2.
https://aisel.aisnet.org/icis2017/ServiceScience/Presentations/2
A Decision Support System for Computation of Carsharing Pricing Areas and its Influence on Vehicle Distribution
Carsharing offers an ecologically friendly alternative to private car ownership, helping to alleviate urban mobility problems and pave a path toward a sustainable future for transportation. However, several obstacles in carsharing service management must be overcome in order to take full advantage of its potential as a mainstream mode of transportation. Among others, substantial barriers to involvement include the challenges regarding vehicle supply and demand management. Following a design science research approach, we develop a concept of area-based pricing strategy, presenting an innovative approach to spatial vehicle supply and demand management. We further support this new methodology by developing a decision support system framework for pricing area construction followed by a practical application. The results reveal that pricing areas reduce the need for vehicle relocations while facilitating better vehicle availability.