I saw the this tweet on x dot com. Here is my take:

A ride-hailing marketplace must balance the needs of both sides: users and drivers, while earning enough revenue for the value provided.

Most drivers prefer pricing based on actual distance and want platforms to incorporate time-based factors, especially during peak hours with heavy traffic. This approach aligns closely with how traditional taxis operate.

The estimated fare combines a surge multiplier (based on historical data and real-time supply-demand data) with the standard base fare (government regulated). The final fare is calculated using total time and distance.

Drivers see the fare labeled as an estimate. They believe they should earn more if they provide additional service beyond the estimate. However, ride-hailing platforms already incorporate surge pricing.

Notably, traditional metered taxi rides often generate less income for drivers compared to ride-hailing apps. Uber implemented this pricing model likely in response to driver feedback, particularly in Western markets where hourly wages are higher and freelance drivers expect better time-based compensation.

Users, however, prioritize pricing predictability. They interpret the estimated price as fixed rather than approximate. They avoid surprises at trip completion – if they wanted price negotiations, they would opt for street-hailed transportation. The challenge extends beyond expectation setting to trust preservation. When users perceive pricing as arbitrary or deceptive (even if it isn’t), their sense of fairness diminishes. They assume the platform’s system already accounts for traffic conditions dynamically.

Drivers also value earnings predictability. They prefer upfront pricing to evaluate trip worthiness but welcome additional compensation for extra effort.

These marketplace dynamics affect internal company operations as well.

Different departments – Business, Operations, Driver Support, User Experience, Strategy, and Customer Support (managing refund decisions) – often have competing priorities.

The solution requires educating both sides and setting clear expectations through standard operating procedures.

Implementing transparent fare breakdowns in the app can reduce frustration, while proactive refund mechanisms help maintain trust.

However, this remains a complex challenge.

The core issue isn’t about pricing models but user psychology: once customers feel deceived and that perception spreads among users, explanations alone cannot restore trust.