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Price, wage and fixed commission in on-demand matching

On-demand platforms, such as the ride-hailing service Uber, often use crowdsourced supply to satisfy customer demand. In this paper, we study a two-sided on-demand matching platform's problem of determining wage (for crowdsourced suppliers) and price (for customers) in various market conditions. We investigate the performance of the fixed-commission structure, under which the wage is a fixed fraction of the price, regardless of the market conditions. We show that under mild conditions, the fixed-commission structure achieves at least 75% of the optimal revenue for the platform.
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McMaster University - School of Computational Science and Engineering