This paper considers the intertemporal pricing problem for a monopolist marketing a new product. The key feature differentiating this paper from the extant management science literature on intertemporal pricing is the assumption that consumers are intertemporal utility maximizers. A subgame perfect Nash equilibrium pricing policy is characterized and shown to involve intertemporal price discrimination. We compare this policy to the optimal policy for a monopolist facing myopic consumers and find that for any given state, prices are always lower with rational consumers than with myopic consumers. For plausible parameter values the assumption of consumer rationality can be shown to lead to large differences in optimal prices. Moreover, if a monopolist facing rational consumers implements the optimal myopic consumer pricing policy, profits can be significantly less than if the monopolist follows the equilibrium pricing policy for rational consumers.marketing: pricing, games: noncooperative, dynamic programming
We consider a queuing system consisting of a finite number of identical exponential servers. Each server has its own queue, and upon arrival each customer must be assigned to some server's queue. Under the assumption that no jockeying between queues is permitted, it is shown that the intuitively satisfying rule of assigning each arrival to the shortest line maximizes, with respect to stochastic order, the discounted number of customers to complete their service in any time t.
We consider a queuing system consisting of a finite number of identical exponential servers. Each server has its own queue, and upon arrival each customer must be assigned to some server's queue. Under the assumption that no jockeying between queues is permitted, it is shown that the intuitively satisfying rule of assigning each arrival to the shortest line maximizes, with respect to stochastic order, the discounted number of customers to complete their service in any time t.
A highly successful spreadsheet-based management science course for MBA students at Indiana University deals mainly with simulation and mathematical optimization with spreadsheet solvers and includes many applications of management science that are extremely relevant to these students. They seem to prefer the spreadsheet approach over the traditional management science approach.
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