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In this paper we investigate the dynamics of a duopoly game with ambiguity aversion regarding uncertainty in demand and constant expectations concerning competitor production. The focus is on an asymmetric Cournot game where players engage in robust optimization and have different beliefs about the possible realizations of the random parameters of the price function. The players’ ambiguity aversion introduces multiple equilibria and instability that otherwise would not be present. The investigation of the global dynamics of the game reveals the emergence, through border-collision bifurcations, of periodic and chaotic dynamics.

We develop a nonlinear duopoly model in which the heuristic expectation formation and learning behavior of two boundedly rational firms may engender complex dynamics. Most importantly, we assume that the firms employ different forecasting models to predict the behavior of their opponent. Moreover, the firms learn by leaning more strongly on forecasting models that yield more precise predictions. An eight-dimensional nonlinear map drives the dynamics of our approach. We analytically derive the conditions under which its unique steady state is locally stable and numerically study its out-of-equilibrium behavior. In doing so, we detect multiple scenarios with coexisting attractors at which the firms’ behavior yields distinctively different market outcomes.

This paper examines an endogenous timing game in product differentiated duopolies under price competition when emission tax is imposed on environmental externality. We show that a simultaneous-move (sequential-move) outcome can be an equilibrium outcome in a private duopoly under significant (insignificant) environmental externality, but this result can be reversed in a mixed duopoly. We also show that when environmental externalities are significant, public leadership yields greater welfare than private leadership, and that public leadership is more robust than private leadership as an equilibrium outcome. Finally, we find that privatization can result in a public leader becoming a private leader, but this worsens welfare.

Managers of emerging platforms must decide what level of platform performance to invest in at each product development cycle in markets that exhibit two-sided network externalities. High performance is a selling point for consumers, but in many cases it requires developers to make large investments to participate. Abstracting from an example drawn from the video game industry, we build a strategic model to investigate the trade-off between investing in high platform performance versus reducing investment in order to facilitate third party content development. We carry out a full analysis of three distinct settings: monopoly, price-setting duopoly, and price-taking duopoly. We provide insights on the optimum investment in platform performance and demonstrate how conventional wisdom about product development may be misleading in the presence of strong cross-network externalities. In particular, we show that, contrary to the conventional wisdom about \"winner-take-all\" markets, heavily investing in the core performance of a platform does not always yield a competitive edge. We characterize the conditions under which offering a platform with lower performance but greater availability of content can be a winning strategy.