A new theory has emerged, raising questions about whether ride-hailing apps charge iPhone users more than Android users for the same rides. Recent tests conducted by The Times of India (TOI) have sparked speculation, with findings showing consistently higher prices for iOS users in Chennai. The tests compared cab fares for identical routes checked simultaneously on iPhone and Android devices.
After seeing this tried same pick up and drop locations in ola and uber separately using iphone and android
Wat is this ya @Olacabs @Uber_India
Why two different charges in different devices for same pick up and drop loactions🫠🫠🫠 https://t.co/L9MdVoE1uR pic.twitter.com/XSXPFMtOPM— Arivazhagan (@ariv22) December 26, 2024
Although the price differences were most noticeable for shorter, single rides, the results are not definitive proof of discrimination. Factors like varying demand and fluctuating algorithms make it difficult to draw firm conclusions. Nonetheless, the findings have reignited concerns about the opaque pricing strategies used by ride-hailing platforms.
In response, Uber has denied any practice of personalizing fares based on the type of phone a user owns. They attributed the discrepancies to dynamic pricing, which is influenced by factors such as real-time demand, estimated travel time, and distance. However, Ola, another popular ride-hailing service, did not respond to TOI’s inquiries.
Experts, however, have raised doubts about these explanations. C. Ambigapathy, managing director of Chennai-based ride-hailing platform Fastrack, suggested that it is technically possible for companies to adjust fares based on the user’s hardware. He believes ride-hailing companies could easily manipulate fares while citing dynamic pricing algorithms as a cover.
P. Ravikumar, a former senior director at the Centre for Development of Advanced Computing, explained that advanced machine learning technologies such as Google Cloud AI and Azure ML enable ride-hailing platforms to incorporate a range of variables—including device type and usage patterns—into their pricing models. He suggested that if consistent factors like estimated travel time and distance were accounted for, users should not face discrepancies based on their device.
One expert involved in framing India’s aggregator policy noted that surge pricing is not only tied to the type of device a user owns. Instead, platforms adjust fares based on a user’s behavior and patterns, with frequent users or those who check fares multiple times often facing higher prices.
Despite these claims, the allegations have yet to be independently verified. However, experts are calling for greater transparency from ride-hailing platforms to ensure fair pricing practices for all users, regardless of the device they use.
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