A decentralized model of information pricing in networks

We propose a recursive method of pricing an information good in a network of holders and demanders of this good. The prices are determined via a unique equilibrium outcome in a sequence of bilateral bargaining games that are played by connected agents. If the information is an homogenous, non-depreciating good without network effects we derive explicit formulae which elucidate the role of the link pattern among the players. Particularly, we find out that the equilibrium price is intimately related to the existence of cycles in the network: It is zero if a cycle covers the trading pair and it is proportional to the direct and indirect utility that the good generates otherwise.

Dynamic pricing model and algorithm for perishable products with fuzzy demand (ABS 2* Journal)

This paper studies the dynamic pricing problem of selling fixed stock of perishable items over a finite horizon, where the decision maker does not have the necessary historic data to estimate the distribution of uncertain demand, but has imprecise information about the quantity demand. We model this uncertainty using fuzzy variables. The dynamic pricing problem based on credibility theory is formulated using three fuzzy programming models, viz.: the fuzzy expected revenue maximization model, a-optimistic revenue maximization model, and credibility maximization model. Fuzzy simulations for functions with fuzzy parameters are given and embedded into a genetic algorithm to design a hybrid intelligent algorithm to solve these three models. Finally, a real-world example is presented to highlight the effectiveness of the developed model and algorithm.

Robust Dynamic Pricing Over Infinite Horizon in The Presence of Model Uncertainty( 2* Journal)

This paper studies a problem of dynamic pricing faced by a retailer with limited inventory, uncertain about the demand rate model, aiming to maximize expected discounted revenue over an infinite time horizon. The retailer doubts his demand model which is generated by historical data and views it as an approximation. Uncertainty in the demand rate model is represented by a notion of generalized relative entropy process, and the robust pricing problem is formulated as a two-player zero-sum stochastic differential game. The pricing policy is obtained through the Hamilton-Jacobi-Isaacs (HJI) equation. The existence and uniqueness of the solution of the HJI equation is shown and a verification theorem is proved to show that the solution of the HJI equation is indeed the value function of the pricing problem. The results are illustrated by an example with exponential nominal demand rate.

NON-GAUSSIAN STATISTICS OF OIL PRICING TIME-SERIES: A CASE STUDY

The stochastic nature of oil price fluctuations is investigated over a twelve-year period, borrowing feedback from an existing database (USA Energy Information Administration database, available online). We evaluate the scaling exponents of the fluctuations by employing different statistical analysis methods, namely rescaled range analysis (R/S), scale windowed variance analysis (SWV) and the generalized Hurst exponent (GH) method. Relying on the scaling exponents obtained, we apply a rescaling procedure to investigate the complex characteristics of the probability density functions (PDFs) dominating oil price fluctuations. It is found that PDFs exhibit scale invariance, and in fact collapse onto a single curve when increments are measured over microscales (typically less than 30 days). The time evolution of the distributions is well fitted by a Levy-type stable distribution. The relevance of a Levy distribution is made plausible by a simple model of nonlinear transfer. Our results also exhibit a degree of multifractality as the PDFs change and converge toward to a Gaussian distribution at the macroscales.

Dynamic pricing models for used products in remanufacturing with lost-sales and uncertain quality

In this paper, we investigate the remanufacturing problem of pricing single-class used products (cores) in the face of random price-dependent returns and random demand. Specifically, we propose a dynamic pricing policy for the cores and then model the problem as a continuous-time Markov decision process. Our models are designed to address three objectives: finite horizon total cost minimization, infinite horizon discounted cost, and average cost minimization. Besides proving optimal policy uniqueness and establishing monotonicity results for the infinite horizon problem, we also characterize the structures of the optimal policies, which can greatly simplify the computational procedure. Finally, we use computational examples to assess the impacts of specific parameters on optimal price and reveal the benefits of a dynamic pricing policy. © 2013 Elsevier B.V. All rights reserved.

Dynamic pricing for used products in remanufacturing with back orders(ABS 3* Journal, Accepted with Revision on 2nd December 2011).

In remanufacturing, the supply of used products and the demand for remanufactured products are usually mismatched because of the great uncertainties on both sides. In this paper, we propose a dynamic pricing policy to balance this uncertain supply and demand. Specifically, we study a remanufacturer’s problem of pricing a single class of cores with random price-dependent returns and random demand for the remanufactured products with backlogs. We model this pricing task as a continuous-time Markov decision process, which addresses both the finite and infinite horizon problems, and provide managerial insights by analyzing the structural properties of the optimal policy. We then use several computational examples to illustrate the impacts of particular system parameters on pricing policy.

Environmental pricing of externalities from different sources of electricity generation in Chile

The rapid increase in electricity demand in Chile means a choice must be made between major investments in renewable or non-renewable sources for additional production. Current projects to develop large dams for hydropower in Chilean Patagonia impose an environmental price by damaging the natural environment. On the other hand, the increased use of fossil fuels entails an environmental price in terms of air pollution and greenhouse gas emissions contributing to climate change. This paper studies the debate on future electricity supply in Chile by investigating the preferences of households for a variety of different sources of electricity generation such as fossil fuels, large hydropower in Chilean Patagonia and other renewable energy sources. Using Double Bounded Dichotomous Choice Contingent Valuation, a novel advanced disclosure method and internal consistency test are used to elicit the willingness to pay for less environmentally damaging sources. Policy results suggest a strong preference for renewable energy sources with higher environmental prices imposed by consumers on electricity generated from fossil fuels than from large dams in Chilean Patagonia. Policy results further suggest the possibility of introducing incentives for renewable energy developments that would be supported by consumers through green tariffs or environmental premiums. Methodological findings suggest that advanced disclosure learning overcomes the problem of internal inconsistency in SB-DB estimates.

Road traffic congestion and public information - An experimental investigation

This paper reports laboratory experiments designed to study the impact of public information about past departure rates on congestion levels and travel costs. Our design is based on a discrete version of Arnott et al.'s (1990) bottleneck model. In all treatments, congestion occurs and the observed travel costs are quite similar to the predicted ones. Subjects' capacity to coordinate is not affected by the availability of public information on past departure rates, by the number of drivers or by the relative cost of delay. This seemingly absence of treatment effects is confirmed by our finding that a parameter-free reinforcement learning model best characterises individual behaviour.

Short-Sale Constraints and the Pricing of Managerial Skills

We investigate the impact of the absence of short selling on the pricing of managerial skills in the mutual fund industry. In the presence of divergent opinions regarding managerial skills, fund managers can strategically use fees to attract only the most optimistic capital. The recognition of this fee strategy helps explain a set of stylized observations and puzzles in the mutual fund industry, including the underperformance of active funds, the existence of flow convexity, and the negative correlation between gross-of-fee α and fees.

Pharmacological characterization of a noninvasive, chronic, experimental dog model of nasal congestion

The present experiments were undertaken to pharmacologically characterize a noninvasive, chronic, experimental dog model of nasal congestion with the overall goal of developing an effective tool for studying the mechanism of action of nasal decongestant drugs.

Acoustic rhinometry in the dog:a novel large animal model for studies of nasal congestion

The aim of this project was to develop and pharmacologically characterize an experimental dog model of nasal congestion in which nasal patency is measured using acoustic rhinometry. Solubilized compound 48/80 (0.3-3.0%) was administered intranasally to thiopental anesthetized beagle dogs to elicit nasal congestion via localized mast cell degranulation. Compound 48/80-induced effects on parameters of nasal patency were studied in vehicle-treated animals, as well as in the same animals pretreated 2 hours earlier with oral d-pseudoephedrine or chlorpheniramine. Local mast cell degranulation caused a close-related decrease in nasal cavity volume and minimal cross-sectional area (Amin) together with a highly variable increase in nasal secretions. Maximal responses were seen at 90-120 minutes after 48/80 administration. Oral administration of the adrenergic agonist, d-pseudoephedrine (3.0 mg/kg), significantly antagonized all of the nasal effects of compound 48/80 (3.0%). In contrast, oral administration of the histamine H1 receptor antagonist chlorpheniramine (10 mg/kg) appeared to reduce the increased nasal secretions but was without effect on the compound 48/ 80-induced nasal congestion (i.e., volume and Amin). These results show the effectiveness of using acoustic rhinometry in this anesthetized dog model. The observations that compound 48/80-induced nasal congestion was prevented by d-pseudoephedrine pretreatment, but not by chlorpheniramine, suggest that this noninvasive model system may provide an effective tool with which to study the actions of decongestant drugs in preclinical investigations.