Optimizing multi-attribute pricing plans with time- and location-dependent rates for different carsharing user profiles

• Type: Article in International Scientific Journal
• Date: 2024

Authors

Golalikhani, M (Author) Other; Beatriz Brito Oliveira (Author) FEUP; Correia, GHD (Author) Other; José Fernando Oliveira (Author) FEUP; Maria Antónia Carravilla (Author) FEUP

Journal

Title: Transportation Research Part E: Logistics and Transportation Review

Vol. 192

ISSN: 1366-5545

Publisher: Elsevier

Indexing

ISI Web of Knowledge - 0 Citations

Scopus - 0 Citations

Other information

Authenticus ID: P-016-ZXX

DOI: 10.1016/j.tre.2024.103760

Abstract (EN): One of the main challenges of one-way carsharing systems is to maximize profit by attracting potential customers and utilizing the fleet efficiently. Pricing plans are mid or long-term decisions that affect customers' decision to join a carsharing system and may also be used to influence their travel behavior to increase fleet utilization e.g., favoring rentals on off-peak hours. These plans contain different attributes, such as registration fee, travel distance fee, and rental time fee, to attract various customer segments, considering their travel habits. This paper aims to bridge a gap between business practice and state of the art, moving from unique single-tariff plan assumptions to a realistic market offer of multi-attribute plans. To fill this gap, we develop a mixed-integer linear programming model and a solving method to optimize the value of plans' attributes that maximize carsharing operators' profit. Customer preferences are incorporated into the model through a discrete choice model, and the Brooklyn taxi trip dataset is used to identify specific customer segments, validate the model's results, and deliver relevant managerial insights. The results show that developing customized plans with time- and location-dependent rates allows the operators to increase profit compared to fixed-rate plans. Sensitivity analysis reveals how key parameters impact customer choices, pricing plans, and overall profit.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 22