Say No to Price Discrimination: Decentralized and Automated Incentives for Price Auditing in Ride-Hailing Services

Abstract

As the most successful application of the sharing economy, ride-hailing service is popular worldwide and serves millions of users per day worldwide. Ride-hailing service providers (SPs) usually collect users' personal data to improve their services via big data technologies. However, SPs may also use the collected user data to apply personalized prices to different users, which raises price fairness concerns. In this paper, we propose a smart price auditing system named Spas. Spas allows a user to purchase Fair Price Insurance in the form of Price Auditing Contract, then the price of ride-hailing service (RHS) order will be audited automatically once completed. According to the auditing result, the contract punishes misbehaving SPs and also compensates affected users automatically. By replacing an untrustworthy centralized auditor with carefully designed smart contracts, we construct a decentralized price auditing system which is trustworthy and transparent. We demonstrate a theoretical model for practical payment flows based on real RHS user data and we implement Spas in Hyperledger Fabric to show that decentralizing and automating price auditing for RHS with financial incentives is technically feasible.