Service Bundle Sizing and Pricing for Mobility Services: Incorporating Elastic Demand and Fleet Operations

The last decade has witnessed the introduction and rapid growth of emerging mobility services. They are expected to further grow in the near future through the aid of developing information and vehicle technologies. With this rapid growth in services and as travelers begin to perceive mobility as a service, offering diverse types of services, such as discounted bundled pricing, may better meet the demand of travelers and, in return, secure demand for providers. In this paper, we formulate a service bundle sizing and pricing problem for mobility services. We account for the well-known travel demand property that reduced cost of travel induces more travel. We also account for trip-based service cost, which comes from complex fleet operations. In the proposed formulation, demand and fleet operations are derived as a function of the decision variables Bundle Sizing and Pricing. This model uses a traveler target mileage probability density function (DTTM-PDF) as an input and derives service bundle choice probability (and therefore, demand) as well as operational metrics. We specify DTTM-PDF and demand increase functions that can describe the data appropriately and also output a convex optimization formulation. A case study of New York City is presented.

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Publication Details

Journal
Service Science
Published
2025-12-01
DOI
https://doi.org/10.1287/serv.2024.0127
Primary Topic
Transportation and Mobility Innovations
Type
article
Field-Weighted Citation Impact
0.00
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article

Service Bundle Sizing and Pricing for Mobility Services: Incorporating Elastic Demand and Fleet Operations

Qingyang Xiao, Jee Eun Kang
Service Science
Transportation and Mobility Innovations
article

Service Bundle Sizing and Pricing for Mobility Services: Incorporating Elastic Demand and Fleet Operations

Qingyang Xiao, Jee Eun Kang
article en

Abstract

The last decade has witnessed the introduction and rapid growth of emerging mobility services. They are expected to further grow in the near future through the aid of developing information and vehicle technologies. With this rapid growth in services and as travelers begin to perceive mobility as a service, offering diverse types of services, such as discounted bundled pricing, may better meet the demand of travelers and, in return, secure demand for providers. In this paper, we formulate a service bundle sizing and pricing problem for mobility services. We account for the well-known travel demand property that reduced cost of travel induces more travel. We also account for trip-based service cost, which comes from complex fleet operations. In the proposed formulation, demand and fleet operations are derived as a function of the decision variables Bundle Sizing and Pricing. This model uses a traveler target mileage probability density function (DTTM-PDF) as an input and derives service bundle choice probability (and therefore, demand) as well as operational metrics. We specify DTTM-PDF and demand increase functions that can describe the data appropriately and also output a convex optimization formulation. A case study of New York City is presented.

Service ScienceVol. 17(4)
Johns Hopkins University Applied Physics Laboratory (US), University at Buffalo, State University of New York (US)
Openalex Percentile: Top 59%
Transportation and Mobility Innovations
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