Abstract
Ride-hailing platforms and their expansion across markets is transforming urban transport landscape. However, algorithmic pricing used by such platforms has raised questions about algorithmic opacity, fairness, data privacy, regulatory difficulties, and so on. This paper attempts to understand if different individuals observe similar or widely different pricing on two ride-hailing platforms (namely, Uber and Ola) in India. A model is proposed to potentially explain algorithmic pricing in ride-hailing, given the “black box” nature of pricing algorithms and lack of relevant publicly available data. Using data collected from 138 individuals who participated in a survey, I examine fares quoted to them by mobile applications (apps) and browsers of both platforms. It is found that despite controlling for several ride-related characteristics, there exists substantial variation in prices quoted by the ride-hailing platforms. While time of search, medium of search (app or browser), and frequency of using the app emerge as key determinants of pricing, certain individual-specific characteristics likely also influence it. Overall, the analysis reveals that price determination on ride-hailing platforms is not a neutral demand-supply matching exercise. Thereby, the need for regulation, data privacy, and algorithmic audits is stressed upon for ensuring fairness and transparency in the sector.
Presenters
Neha AryaPhD Scholar, Humanities and Social Sciences, Indian Institute of Technology, Delhi, India
Details
Presentation Type
Paper Presentation in a Themed Session
Theme
KEYWORDS
RIDE-HAILING, DIGITAL APPLICATIONS, ALGORITHMIC PRICING, AUTOMATED PRICING
