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Problem definition: We consider two business models for a two-sided economy under uncertainty: dealership and marketplace with fulfillment services. Although both business models can bridge the gap between demand and supply, it is not clear which model is better for the firm or for the consumers. Methodology/results: We show that, whereas the two models differ substantially in pricing power, inventory risk, fee structure, and fulfillment time, both models share several important features with the revenues earned by the firm from the two models converging when the markets are thick. We also show that, for thick markets, there is a one-to-one mapping between their corresponding optimal policies. Managerial implications: Our results provide guidelines for firms entering two-sided markets: when the market is thick, the two business models are similar; when the market is thin, they should carefully inspect a number of market conditions before making the choice. Funding: The research of G. Li is partially supported by the National Natural Science Foundation of China [Grants 72150002, 72394361] and the Guangdong Provincial Key Laboratory of Mathematical Foundations for Artificial Intelligence [Grant 2023B1212010001]. The research of N. Chen is partially supported by the Natural Sciences and Engineering Research Council of Canada Discovery [Grant RGPIN-2020-04038]. The research of G. Gallego is partially supported by Collaborative Research Funding Hong Kong [Grant C6032-21G]. The research of P. Gao is supported by the National Natural Science Foundation of China [Grants 72201234, 72192805], Collaborative Research Funding Hong Kong [Grant C6032-21G], and the Guangdong Provincial Key Laboratory of Mathematical Foundations for Artificial Intelligence [Grant 2023B1212010001]. Supplemental Material: The online supplement is available at https://doi.org/10.1287/msom.2022.0253. [ABSTRACT FROM AUTHOR]

In this paper, we study discounted stochastic games with an additive rewards and transitions (ARAT) structure. We assume that the transition probabilities are dominated by some probability measures on a countably generated measurable state space and are norm continuous in actions of the players. We prove the existence of Markov perfect equilibria in which the players can use randomization on two pure actions in each state. When the state space is countable, then we show that there exists a pure Markov perfect equilibrium. Assuming additionally that the transition probabilities have no conditional atoms, we establish some existence results on pure Markov perfect equilibria for ARAT games with uncountable state space using a version of Lyapunov's theorem for conditional expectation of correspondences due to Dynkin and Evstigneev. We also include a wide-ranging discussion on equilibria for discounted stochastic games with a general state space. [ABSTRACT FROM AUTHOR]

We consider a distributed computing setting wherein a central entity seeks power from computational providers by offering a certain reward in return. The computational providers are classified into long-term stakeholders that invest a constant amount of power over time and players that can strategize on their computational investment. In this paper, we model and analyze a stochastic game in such a distributed computing setting, wherein players arrive and depart over time. While our model is formulated with a focus on volunteer computing, it equally applies to certain other distributed computing applications such as mining in blockchain. We prove that, in Markov perfect equilibrium, only players with cost parameters in a relatively low range which collectively satisfy a certain constraint in a given state, invest. We infer that players need not have knowledge about the system state and other players' parameters, if the total power that is being received by the central entity is communicated to the players as part of the system's protocol. If players are homogeneous and the system consists of a reasonably large number of players, we observe that the total power received by the central entity is proportional to the offered reward and does not vary significantly despite the players' arrivals and departures, thus resulting in a robust and reliable system. We then study by way of simulations and mean field approximation, how the players' utilities are influenced by their arrival and departure rates as well as the system parameters such as the reward's amount and dispensing rate. We observe that the players' expected utilities are maximized when their arrival and departure rates are such that the average number of players present in the system is typically between 1 and 2, since this leads to the system being in the condition of least competition with high probability. Further, their expected utilities increase almost linearly with the offered reward and converge to a constant value with respect to its dispensing rate. We conclude by studying a Stackelberg game, where the central entity decides the amount of reward to offer, and the computational providers decide how much power to invest based on the offered reward. [ABSTRACT FROM AUTHOR]

Using a dynamic preferential trade agreement (PTA) formation model, we show that political biases in exporting and import‐competing sectors substantially impact the extent of PTA formation. While both exclusion and free riding incentives constrain the expansion to global free trade in a free trade agreement (FTA) game, only the former incentive arises in a customs union (CU) game. When we endogenize the choice between FTAs and CUs, the tension between the flexibility benefit of FTAs and the coordination benefit of CUs reveals that FTAs always serve as PTA building blocks while CUs may serve as PTA building or stumbling blocks. [ABSTRACT FROM AUTHOR]