Research

Efficient allocation of a divisible resource and its associated costs among consumers is a critical issue in many societal decision-making scenarios. This decision is especially difficult when consumers have heterogeneous incomes and private levels of resource utility. Common approaches in practice often overlook either utility heterogeneity or income disparity, leaving a significant gap between potential and actual outcomes. We develop and analyze a resource allocation method to bridge this gap. Our model incorporates consumer heterogeneity in both income levels and private utility from the resource. We formulate the problem of allocating he resource and its associated costs or savings as a mechanism design problem, aiming to maximize aggregate consumer welfare. We propose a mechanism that offers consumers income-dependent menus (IDM) of quantity and cost (or savings) options, and uncover structural properties of these menus. Our IDM approach significantly outperforms the considered alternatives in a numerical study calibrated using real-world data. In the realm of resource allocation where both income and resource utility levels are heterogeneous, significant welfare gains can be realized by judiciously leveraging the dual dimensions of heterogeneity. Implementing our IDM approach ensures that consumers receive and contribute to resources in a manner that reflects their financial capacities and utility levels, maximizing overall welfare.

Utility regulators are grappling to devise compensation schemes for customers who sell rooftop solar generation back to the grid. Regulators seek to induce an optimal level of rooftop solar adoption, trading off between its environmental benefits and the financial burden that it imposes, while simultaneously safeguarding the interests of utilities, solar system installers, and customers. This is a difficult balance to achieve, and numerous failed attempts have received considerable press coverage in the last three years. For example, tariff changes in Nevada induced SolarCity, the market leader in solar systems, to suspend operations in the state. Motivated by this, we formulate and analyze a social welfare maximization problem for the regulator, focusing on how the choice of tariff interacts with her competing objectives. We uncover the structural properties of a successful tariff, finding that the tariff structures used in most states are inadequate: to achieve welfare optimal outcomes, a tariff must be able to discriminate among customer usage tiers and between customers with and without rooftop solar. We also demonstrate that these flexibilities do not imply more degrees of freedom for the regulator.  Finally, we present a tariff structure with these two characteristics and show how it can be implemented as a simple buy-all, sell-all tariff while retaining its favorable properties. We illustrate our findings numerically using household-level data from Nevada and New Mexico.

Internet-based technology enables firms to disseminate real-time delay information to delay-sensitive customers. We study how such delay announcements impact service providers in a competitive environment with two service providers who compete for market share. We model the service providers' strategies based on an endogenous timing game, investigating strategies that emerge in equilibrium. We determine the service providers' market shares under the various game outcomes by analyzing continuous-time Markov chains, which capture customers' joining decisions, and by developing a novel computational technique to analyze the intractable asymmetric Join-the-Shortest Queue system, providing bounds on the market shares. We find that only the lower capacity service provider announces its real-time delay under intermediate system loads and highly imbalanced capacities. However, for most parameter settings, the mere presence of a competitor induces both providers to announce delays in equilibrium, leaving customers better off on average. We relate our findings to the single-provider delay announcement literature by discussing the impact of competition on service providers, delay announcement technology firms, and customers 

 We study delay information disclosure policies for on-demand platforms serving two user classes---customers and providers---who seek matches using the platform. The platform's objective is to maximize the match rate by choosing the level of information--- no information, binary information (indicating whether the wait is zero or non-zero), or occupancy information (indicating the expected delay based on the number of users currently in the system)---to disclose to each user class. Users of each class are strategic and decide whether to join or balk based on the delay information disclosed to them. 

We consider two user types in each user class: patient users who are willing to wait for a match and impatient users who are not. We use continuous-time Markov chains to model the system as two-sided queues and employ equilibrium analysis to characterize users' joining behavior and the platform's match rate under each information disclosure policy. We show that the two-sided system decouples and disclosure decisions can be analyzed as two one-sided systems only if some level of information (binary or occupancy) is disclosed to both user classes. We find that disclosing binary information dominates disclosing no information or occupancy information to a user class when its patient users are sufficiently patient, while disclosing occupancy information dominates disclosing binary information to a user class when there are enough patient users. Numerical experiments show that disclosing occupancy information to both user classes, while often suboptimal, is typically not suboptimal by much. Finally, we find that compared to the platform's optimal disclosure choice, a user class may prefer more or less granular information for themselves or the other class. Furthermore, this utility analysis does not lend itself to decoupling.

Our findings hold crucial implications for platform managers: carefully evaluating the chosen information sharing strategy is imperative, and guidelines from the one-sided literature are generally inadequate for making disclosure decisions.