Pricing theory is concerned with determining a realistic market-related price of an asset that is not yet marketed. There are several approaches to this issue, most of which use systems theory concepts, such as optimization, dynamic recursion, probability, stochastic process, and control. Pricing theory has therefore benefited greatly from systems theory. Systems theory can also benefit from pr...

We investigate intermediary asset pricing theories empirically and find strong support for intermediary book leverage as the relevant state variable. A parsimonious dynamic pricing model that uses detrended broker-dealer leverage as a price of risk variable, and innovations to broker-dealer leverage as pricing factor is shown to perform well in time series and cross sectional tests of a wide va...

Knowing each customer’s preferences enhances the ability to design and market the right offer in terms of content and price. The more a retailer interacts with its customers, the more it learns as it observes revealed preferences. Lower prices typically lead to more interactions and more learning but lower short-term profits. This paper brings the concept of learning functions to this dynamic p...

Plug-in Hybrid Electric Vehicles (PHEVs) are the vehicles that depend on energy from power grid. When such vehicles are deployed in large scale, there will be great demand for energy in peakhours. There will be different levels of usage based on time. Towards this end, optimizing the supplydemand and also pricing for PHEVs is very challenging problem to be addressed. Recently there was a soluti...

In this paper, we introduce the concept of dynamic pricing within the context of our previous Stackelberg network game model and view the ISP’s policy as an incentive policy, and the underlying game as a reverse Stackelberg game. We study this incentive-design problem under complete information as well as incomplete information. In both cases, we show that the game is not generally incentive co...

Future communication networks are envisioned to be based upon a new communication paradigm which is user centric, i.e., users have freedom to choose a service provider to maximize their utilities. Pricing schemes adopted by service providers will impact the decision of users in selecting networks. In this paper, we formulate the problem as a Markov Decision Process (MDP) framework and apply Q-l...

Traditionally, network operators have used simple flat-rate broadband data plans for both wired and wireless network access. But today, with the popularity of mobile devices and exponential growth of apps, videos, and clouds, service providers are gradually moving towards more sophisticated pricing schemes, including dynamic pricing. This decade will therefore likely witness a major change in w...

This paper describes the development and implementation of a dynamic congestion pricing scheme, augmented with a game-theoretic evolutionary learning model, into a realistic urban highway in Athens, Greece. The model recognizes several important behavioral features related to the response of users to the congestion pricing strategy. Such features include day-to-day as well as within-day adjustm...

This paper analyzes the dynamic traffic assignment problem on a two-alternative network with one alternative subject to a dynamic pricing that responds to real-time arrivals in a system optimal way. Analytical expressions for the assignment, revenue and total delay in each alternative are derived as a function of the pricing strategy. It is found that minimum total system delay can be achieved ...

this paper focuses on formulating capacity-price trade off problem in yield management for manufactur-ing industry by drawing motivation from the remarkable success of yield management (ym) implementation in airlines. in the current practice, there is no alternative and procedure for the manufacturer, as well as cus-tomers to take advantage of using the unfulfilled capacity in discounted offers...