Abstract
A variety of matching functions have been devised for ride-sourcing markets, such as perfect matching functions, Cobb–Douglas-type matching functions, queuing models, and physical models. However, less is known about the applicability and performance of these matching functions; that is, under what conditions each function effectively characterises a real market. This chapter conducts a series of simulation-based sensitivity analyses to calibrate, validate, and compare the most common matching functions, and to ascertain under what conditions they are applicable. Thus, a simulator is established to generate 420 scenarios of a ride-sourcing market with various levels of supply and demand, and a few widely used matching functions are compared in terms of their key performance metrics—matching rate, passengers' average matching time, passengers' average pick-up time, and passengers' average total waiting time—under various market scenarios.
| Original language | English |
|---|---|
| Title of host publication | Supply and Demand Management in Ride-Sourcing Markets |
| Publisher | Elsevier |
| Pages | 55-85 |
| Number of pages | 31 |
| ISBN (Electronic) | 9780443189371 |
| ISBN (Print) | 9780443189388 |
| DOIs | |
| Publication status | Published - 1 Jan 2023 |
Bibliographical note
Publisher Copyright:© 2023 Elsevier Inc. All rights reserved.
Keywords
- Calibration
- Cobb–douglas-type matching function
- First-come-first-serve model
- Matching functions
- Queuing model
- Simulation
- Validation