Incentive-compatible public transportation fares with random inspection

TL;DR

This paper analyzes how to set public transportation fares with random ticket inspections to maximize revenue and prevent fare evasion, using data from Washington DC metro.

Contribution

It derives pricing strategies that incentivize full ticket purchases and demonstrates their effectiveness with real-world data.

Findings

Random inspection can cause over 59% revenue loss without price adjustments.

Properly adjusted prices can reduce fare evasion-related losses to below 20%.

Adjusting prices for incentives does not require increasing current fares.

Abstract

We consider the problem of designing prices for public transport where payment enforcing is done through random inspection of passengers' tickets as opposed to physically blocking their access. Passengers are fully strategic such that they may choose different routes or buy partial tickets in their optimizing decision. We derive expressions for the prices that make every passenger choose to buy the full ticket. Using travel and pricing data from the Washington DC metro, we show that a switch to a random inspection method for ticketing while keeping current prices could lead to more than 59% of revenue loss due to fare evasion, while adjusting prices to take incentives into consideration would reduce that loss to less than 20%, without any increase in prices.