Georges Zaccour

Digital platforms expose customers to product fit uncertainty, which may inhibit online purchases. As a result, firms may encourage online orders through influence tools such as influencer posts and promotional reviews, which can raise product awareness and be skewed in favor of a purchase. Nevertheless, customers who have ordered under such an influence may eventually return the product if it proves to be a mismatch. In this article, we study the interplay between a firm’s influence decision and its pricing and return policies. We find that a firm is motivated to employ an influence tool if it can effectively promote awareness. Under this scenario, the firm should engage in a meticulous configuration of price, refunds, and level of influence when the net benefit of return is non-negative and the marginal influence cost is low. Otherwise, the firm may rely solely on tailoring influence levels or customizing refunds, but not both, to cope with the price and maximize the expected profit. This highlights the substitution role between influencing customers ex ante and providing refunds ex post . Overall, the use of an influence tool broadens the situations to allow product returns. It also polarizes pricing strategy in that the firm may apply either premium pricing with a tailored level of influence or reduced pricing without any additional influence. Interestingly, aggressive influence actions may be accompanied by less premium in price and more generous refunds. The results provide an overarching strategy and practical guidance for firms in navigating the use of influence, pricing, and return policy design.

Space infrastructure and data have become indispensable to humanity at all scales, which is largely due to the advent of the New Space era, characterized by the creation of large satellite constellations. Unfortunately, these remarkable developments exacerbate an already pressing issue: the growing accumulation of space debris. In this paper, we propose a dynamic game-theoretic model showing that this problem can be contained, if an international institution is created and empowered to levy taxes to finance active debris removal activities.

Dealing with climate change requires that all countries engage in costlyefforts to reduce their emissions. Reaching this objective has so far beenelusive because it is in the best interest of each country to let the othersdo the effort and benefit itself from a better environment. The presence ofnegative externalities and strategic behavior have made game theory anatural paradigm to design an international environmental agreement (IEA)that codifies what countries should do. Considering that countries aresovereign and no supranational entity can impose an agreement, a stream ofliterature adopted a noncooperative mode of play to the formation of anenvironmental coalition. On the other hand, as joint optimization of allcountries' payoff leads to the best outcome, cooperative games approach hasalso been proposed to share the cost of climate change. Both approaches havetheir pros and cons.In this paper, we propose a model of coalition formation that combines bothcooperative and noncooperative modes of play. Starting from any givencoalition, we implement a Markov process that shows sequentially whichcountries join or leave the coalition until reaching an absorbing state. Allpossible sequential scenarios are considered and an allocation to the playeris made taking into account individual rationality. An illustration withvulnerable and invulnerable countries to pollution is given.

In this article, we study a class of two-player deterministic finite-horizon difference games with coupled inequality constraints, where each player has two types of decision variables: one involving sequential interactions and the other simultaneous interactions. We refer to this class of games as quasi-hierarchical dynamic games and define a solution concept called the feedback Stackelberg–Nash (FSN) equilibrium. Under separability assumption on cost functions, we provide a recursive formulation of the FSN solution using dynamic programming. We show that the FSN solution can be derived from the parametric feedback Stackelberg solution of an associated unconstrained game involving only sequential interactions, with a specific choice of the parameters that satisfy certain implicit complementarity conditions. For the linear–quadratic case, we show that an FSN solution is obtained by reformulating these complementarity conditions as a single large-scale linear complementarity problem. Finally, we illustrate our results using a dynamic duopoly game with production constraints.