Differentiated Pricing of Shared Mobility Systems Considering Network Effects

Transportation Science - DOI: https://doi.org/10.1287/trsc.2022.1131

45 Pages Posted: 8 Feb 2021 Last revised: 4 Apr 2022

See all articles by Matthias Soppert

Matthias Soppert

Bundeswehr University Munich

Claudius Steinhardt

Bundeswehr University Munich

Christian Müller

University of Duisburg-Essen - Mercator School of Management

Jochen Gönsch

University of Duisburg-Essen - Mercator School of Management

Date Written: April 1, 2022

Abstract

Over the last decades, shared mobility systems have become an integral part of inner-city mobility. Modern systems allow one-way rentals, that is, customers can drop off the vehicle at a different location to where they began their trip. A prominent example is car sharing. Indeed, this work was motivated by the insight we gained in collaborating closely with Europe’s largest car sharing provider, Share Now. In car sharing, as well as in shared mobility systems in general, pricing optimization has turned out to be a promising means of increasing profit while challenged by limited vehicle supply and asymmetric demand across time and space. Thus, in practice, providers increasingly use minute pricing that is differentiated according to where a rental originates, that is, considering its location and the time of day. In research, however, such approaches have not been considered yet. In this paper, we therefore introduce the corresponding origin-based differentiated, profit-maximizing pricing problem for shared mobility systems. The problem is to determine spatially and temporally differentiated minute prices, taking network effects on the supply side and several practice relevant aspects into account. Based on a deterministic network flow model, we formulate the problem as a mixed-integer linear program and prove that it is NP-hard. For its solution, we propose a temporal decomposition approach based on approximate dynamic programming. The approach integrates a value function approximation to incorporate future profits and account for network effects. Extensive computational experiments demonstrate the benefits of capturing such effects in pricing generally, as well as showing our value function approximation’s ability to anticipate them precisely. Furthermore, in a case study based on Share Now data from Florence in Italy, we observe profit increases of around 9% compared with constant uniform minute prices, which are still the de facto industry standard.

Keywords: shared mobility systems, car sharing, differentiated pricing, origin-based pricing, supply-side spatio-temporal network effects, approximate dynamic programming, optimization

JEL Classification: C44, M19

Suggested Citation

Soppert, Matthias and Steinhardt, Claudius and Müller, Christian and Gönsch, Jochen, Differentiated Pricing of Shared Mobility Systems Considering Network Effects (April 1, 2022). Transportation Science - DOI: https://doi.org/10.1287/trsc.2022.1131, Available at SSRN: https://ssrn.com/abstract=3745001 or http://dx.doi.org/10.2139/ssrn.3745001

Matthias Soppert (Contact Author)

Bundeswehr University Munich ( email )

Werner-Heisenberg-Weg 39
Neubiberg, 85577
Germany

Claudius Steinhardt

Bundeswehr University Munich ( email )

Werner-Heisenberg-Weg 39
Neubiberg, 85577
Germany

HOME PAGE: http://www.unibw.de/quantitative-methoden

Christian Müller

University of Duisburg-Essen - Mercator School of Management ( email )

Lotharstraße 65
Duisburg, Nordrhein-Westfalen 47057
Germany

Jochen Gönsch

University of Duisburg-Essen - Mercator School of Management ( email )

Lotharstraße 65
Duisburg, Nordrhein-Westfalen 47057
Germany
+49 203 379 - 2777 (Phone)
+49 203 379 - 1760 (Fax)

HOME PAGE: http://udue.de/goensch

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