Michael C. Wang Publications

We consider a seller who offers services to a buyer with multi-unit demand. Prior to the realization of demand, the buyer receives a noisy signal of their future demand, and the seller can design contracts based on the reported value of this signal. Thus, the buyer can contract with the service provider for an unknown level of future consumption, such as in the market for cloud computing resources or software services. We characterize the optimal dynamic contract, extending the classic sequential screening framework to a nonlinear and multi-unit setting. The optimal mechanism gives discounts to buyers who report higher signals, but in exchange they must provide larger fixed payments. We then describe how the optimal mechanism can be implemented by two common forms of contracts observed in practice, the two-part tariff and the committed spend contract. Finally, we use extensions of our base model to shed light on policy-focused questions, such as analyzing how the optimal contract changes when the buyer faces commitment costs, or when there are liquid spot markets.

We analyze how market segmentation affects consumer welfare when a monopolist can engage in both second-degree price discrimination (through product differentiation) and third-degree price discrimination (through market segmentation). We characterize the consumer-optimal market segmentation and show that it has several striking properties: (1) the market segmentation displays monotonicity—higher-value customers always receive higher quality product than lower-value regardless of their segment and across any segment; and (2) when aggregate demand elasticity exceeds a threshold determined by marginal costs, no segmentation maximizes consumer surplus. Our results demonstrate that strategic market segmentation can benefit consumers even when it enables price discrimination, but these benefits depend critically on demand elasticities and cost structures. The findings have implications for regulatory policy regarding price discrimination and market segmentation practices.