Service Bundle Sizing and Pricing for Mobility Services: Incorporating Elastic Demand and Fleet Operations
Qingyang Xiao & Jee Eun Kang
What the paper says
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.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.