In this paper, we propose a user centric based general framework for revenue maximization in highly competitive wireless networks. By applying dynamic pricing, each service provider operates an optimal policy that aims at maximizing its revenue. The problem is formulated using the Markov Decision Process (MDP) framework and Qlearning is applied to determine an optimal policy which maximizes the...

Firms often have imperfect information about demand for their products. We develop an integrated econometric and theoretical framework to model firm demand assessment and subsequent pricing decisions with limited information. We introduce a panel data discrete choice model whose realistic assumptions about consumer behavior deliver partially identified preferences and thus generates ambiguity i...

This paper attempts to determine the certainty equivalent of an uncertain future cash flow or value through the option pricing method, and builds models of certainty equivalent and certainty equivalent coefficient. Based on the model of certainty equivalent coefficient, this paper further derives models of risk premium and risk-adjusted discount rate. The latter is a new capital asset pricing m...

We address the simultaneous determination of pricing and capacity investment strategies in a multi-period setting under demand uncertainty. In our model a monopolistic firm makes three decisions: capacity investment (or disinvestment), production (inventory), and price, all of which can be specified dynamically as a function of the state of the system. We analyze the optimal joint strategy and ...

This paper proposes an agent based mobile negotiation framework for personalized pricing of last minutes theatre tickets whose values are dependent on the time remaining to the performance and the locations of potential customers. In particular, case based reasoning and fuzzy cognitive map techniques are adopted in the negotiation framework to identify the best initial offer zone and adopt mult...

Analytical solutions to the derivatives pricing problem are known for only a small subset of derivatives and are usually based on strict assumptions. Practitioners will therefore frequently resort to numerical approximation techniques. In this paper, I will formulate a simple Markov decision process for which the optimal value function will, in a non-arbitrage world, be equivalent to a given de...

The IEM Movie Box Office Market forecasting and trading exercise is an important new form of Internet-based experiential learning. In this experience, students proceed beyond problem analysis to decision making in a situation in which their actions have real-dollar implications. From the exercise, students develop important marketing, finance, and technology skills. Instructors benefit from hav...

This paper considers the pricing decision faced by a seller of bundles composed of a service and an associated product offered to customers on a subscription basis using a two-part tariff scheme. An optimal pricing policy that maximizes the profit of a firm is obtained using a dynamic programming approach and it is found that, in the long run, there is an optimal number of customers associated ...

The article presents the results of the study of nonlinear market prices dynamic, simulated using game theory model, maps and theory of bifurcation. Market pricing is presented as a two-dimensional map. Qualitative analyses of the firms’ pricing system properties using the fixed points, analysis of the trajectories near these fixed points were fulfilled Simulation of the market prices dynamic s...

We consider a general class of network revenue management problems, where mean demand at each point in time is determined by a vector of prices, and the objective is to dynamically adjust these prices so as to maximize expected revenues over a finite sales horizon. A salient feature of our problem is that the decision maker can only observe realized demand over time but does not know the underl...