Dynamic Pricing and Service Quality in Ride-Sharing: A Statistical Analysis

Authors

  • Daniel Sanin-Villa Universidad EAFIT
  • Cristian Mateo Hernandez Instituto Tecnologico Metropolitano (ITM), Colombia
  • Vanessa Botero-Gomez Instituto Tecnologico Metropolitano (ITM), Colombia

DOI:

https://doi.org/10.19139/soic-2310-5070-2325

Keywords:

dynamic pricing, regression analysis, ride-sharing, cost optimization, customer satisfaction

Abstract

This study presents a comprehensive statistical analysis of factors influencing dynamic pricing and service quality in ride-sharing. Leveraging historical data, we employ regression models, including simple and multiple linear regressions, as well as logistic regression, to examine the relationships between trip duration, passenger count, driver availability, and customer loyalty on ride costs and service ratings. Results reveal that trip duration significantly predicts ride costs, while customer loyalty and location are key determinants of service quality. These findings provide actionable insights for enhancing dynamic pricing strategies and service quality optimization in ride-sharing, supporting data-driven decision-making in a competitive market.

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Published

2025-02-11

How to Cite

Sanin-Villa, D., Hernandez, C. M., & Botero-Gomez, V. (2025). Dynamic Pricing and Service Quality in Ride-Sharing: A Statistical Analysis. Statistics, Optimization & Information Computing, 13(4), 1732–1751. https://doi.org/10.19139/soic-2310-5070-2325

Issue

Vol. 13 No. 4 (2025)

Section

Research Articles

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