Customer-Centric Dynamic Pricing for Free-Floating Shared Mobility Systems

31 Pages Posted: 20 Dec 2021

See all articles by Christian Müller

Christian Müller

University of Duisburg-Essen - Mercator School of Management

Jochen Gönsch

University of Duisburg-Essen - Mercator School of Management

Matthias Soppert

Bundeswehr University Munich

Claudius Steinhardt

Bundeswehr University Munich

Date Written: December 15, 2021

Abstract

Free-floating shared mobility systems offer customers the flexibility to pick up and drop off vehicles at any location within the business area and, thus, have become the most popular type of shared mobility system. However, this flexibility has the drawback that vehicles tend to accumulate at locations with low demand. To counter these imbalances, pricing has proven to be an effective and cost-efficient means. The fact that customers use mobile applications, combined with the fact that providers know the exact location of each vehicle in real-time, provides new opportunities for dynamic pricing.

In this context, we develop a pricing approach for the dynamic online problem of a provider who determines profit-maximizing prices whenever a customer opens the provider's mobile application to rent a vehicle. Our pricing approach has three distinguishing features: First, it is customer-centric, i.e., it considers the customer's location as well as disaggregated choice behavior to precisely capture the effect of price and walking distance to the available vehicles on the customer's propensity to choose a vehicle. Second, our pricing approach is origin-based, i.e., prices are differentiated by location and time of rental start, which reflects the real-world situation where the rental destination is usually unknown. Third, our approach is anticipative and uses a stochastic dynamic program to anticipate the effect of current decisions on future vehicle locations, rentals, and profits. As solution method, we propose a non-parametric value function approximation, which offers several advantages for the application, e.g., historical data can readily be used and main parameters can be pre-computed such that the online pricing problem becomes tractable. Extensive numerical studies, including a case study based on Share Now data, demonstrate that our approach increases profits by up to 13% compared to existing approaches from the literature and other benchmarks.

Keywords: Free-Floating Shared Mobility System, Customer-Centric Dynamic Pricing, Data-Driven Non-Parametric Value Function Approximation

Suggested Citation

Müller, Christian and Gönsch, Jochen and Soppert, Matthias and Steinhardt, Claudius, Customer-Centric Dynamic Pricing for Free-Floating Shared Mobility Systems (December 15, 2021). Available at SSRN: https://ssrn.com/abstract=3987196 or http://dx.doi.org/10.2139/ssrn.3987196

Christian Müller (Contact Author)

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

Matthias Soppert

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

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