Pricing with Limited Knowledge of Demand

How should a firm price a new product for which little is known about demand? We propose a pricing rule that can be used if the firm can estimate (even roughly) the maximum price it can charge and still expect to sell some units, and the firm need not know in advance the quantity it will sell. The rule is simple: Set price as though the demand curve were linear. We show that if the true demand curve is one of many commonly used demand functions, or even a more complex function, and if marginal cost is known and constant, the firm can expect its profit to be close to what it would earn if it knew the true demand curve. We derive analytical performance bounds for a variety of demand functions, calculate expected profit performance for randomly generated demand curves, and evaluate the welfare implications of our pricing rule

Monopoly Pricing in a Vertical Market with Demand Uncertainty

We study a vertical market with an upsteam supplier and multiple downstream retailers. Demand uncertainty falls to the supplier who acts first and sets a uniform wholesale price before the retailers observe the realized demand and engage in retail competition. Our focus is on the supplier's optimal pricing decision. We express the price elasticity of expected demand in terms of the mean residual demand (MRD) function of the demand distribution. This allows for a closed form characterization of the points of unitary elasticity that maximize the supplier's profits and the derivation of a mild unimodality condition for the supplier's objective function that generalizes the widely used increasing generalized failure rate (IGFR) condition. A direct implication is that optimal prices between different markets can be ordered if the markets can be stochastically ordered according to their MRD functions or equivalently to their elasticities. Based on this, we apply the theory of stochastic orders to study the response of the supplier's optimal price to various features of the demand distribution. Our findings challenge previously established economic insights about the effects of market size, demand transformations and demand variability on wholesale prices and indicate that the conclusions largely depend on the exact notion that will be employed. We then turn to measure market performance and derive a distribution free and tight bound on the probability of no trade between the supplier and the retailers. If trade takes place, our findings indicate that ovarall performance depends on the interplay between demand uncertainty and level of retail competition

On the Mean Residual Life of Cantor-Type Distributions: Properties and Economic Applications

In this paper, we consider the mean residual life (MRL) function of the Cantor distribution and study its properties. We show that the MRL function is continuous at all points, locally decreasing at all points outside the Cantor set and has a unique fixed point which we explicitly determine. These properties readily extend to the parametric family of p-singular, Cantor type distributions introduced by Mandelbrot (1983). The findings offer evidence that, contrary to common perceptions, Cantor-type distributions are tractable enough to be considered for practical applications. We provide such an example from the field of economics in which Cantor-type distributions can be used to model markets with recurrent bandwagon effects and show that earlier anticipated bandwagon effects lead to higher monopolistic prices. We conclude with a simple implementation of the algorithm by Chalice (1991) to plot Cantor-type distributions

A Generalization of the Increasing Generalized Failure Rate Unimodality Condition

In this paper, we study unimodality conditions for distributions that describe markets with stochastic demand. Such conditions naturally emerge in the analysis of game-theoretic models of market competition (Cournot games) and supply chain coordination (Stackelberg games). We express the price elasticity of expected demand in terms of the mean residual life (MRL) function of the demand distribution and characterize optimal prices or equivalently, points of unitary elasticity, as fixed points of the MRL function. This leads to economic interpretable conditions on the demand distribution under which such fixed points exist and are unique. We find that markets with increasing price elasticity of expected demand that eventually become elastic correspond to distributions with decreasing generalized mean residual life (DGMRL) and finite second moment. DGMRL distributions strictly generalize the widely used increasing generalized failure rate (IGFR) distributions. We further elaborate on the relationship of the two classes, link their limiting behavior at infinity and examine moment and closure properties of DGMRL distributions that are important in economic applications. The DGMRL unimodality condition is useful in the analysis of optimal decisions under uncertainty in settings that are not covered by the widely-used IGFR condition; thus, it can be of broader interest to the game-theory and operations research literature

Innovative Revenue Management Practices with Probabilistic Elements

Sale of products with a probabilistic nature, where customers do not know which product they will receive at the time of service, has become popular over the recent years. In the revenue management literature, there has been a growing interest in understanding these modern approaches using analytical techniques. On the other hand, customer-centric revenue management has been replacing the long-standing inventory-centric approach because of the availability of rich data sets by focusing on understanding and predicting customer behavior and then optimizing price and/or quantity related decisions. In this dissertation, we take a customer-centric approach and do not only provide analytical results, but also empirically investigate how customers make their decisions, which is crucial in order to implement appropriate strategies. We first focus on an innovative hotel revenue management practice called standby upgrades, i.e., a practice where the guest is only charged for the discounted upgrade if it is available at the time of arrival. In particular, Chapter 2 discusses how to optimally price standby upgrades and evaluates their benefits through an analytical model. Chapter 3 uses a major hotel chain’s booking and standby upgrades data to investigate the extent of strategic guest behavior through empirical analysis. Then, we focus on another innovative revenue management practice, but in the mega event industry, called team-specific ticket options. Chapter 4 studies fans’ decision-making process for the 2015 College Football season using a unique data set

UNDERSTANDING CREATIVE CANADA: CULTURAL POLICY, PUBLIC SENTIMENT, AND DIGITAL TAX REFORMS

In recent years, Canada legislated the most significant amendments to cultural policy in over a generation aimed at addressing a policy drift amid digital disruption. With wide criticism for these reforms, they are assumed have garnered negative reception in absence a digital tax; however, the legal intricacies of often inconsistent, and overlapping digital tax measures advocated for in Canada remain largely unexamined. Against this background, the OECD/G20 are anticipated to implement the most fundamental overhauling of the international tax system in over a century, with a focus on addressing the tax challenges arising from the digitalisation of the economy. Recognizing that for a solution to be delivered in the coming year, there will need to be a consensus reached by OECD/G20 member countries by July 2021, this study considers the contingency of effective reforms, and alternative measures under consideration by the Government of Canada. Evidence suggests that a solution to today’s digital tax challenges is perhaps a caveat for addressing the issues of Canada’s cultural policy that center upon its failure to keep pace with the digital creative economy. Observations consider the bearing equitable taxation has on the Canadian government’s general tax revenues necessary to fund direct spending programs. In order to link industry-specific government spending with industry-specific behaviour, underlying ties between new Canadian media and digital taxation are investigated, so as to examine opportunities for sustainable cultural policy and funding in the Canadian context

A Simple Rule for Pricing with Limited Knowledge of Demand

Copyright: © 2020 INFORMS How should a firm price a new product for which little is known about demand? We propose a simple and practical pricing rule for new products where demand information is limited. The rule is simple: Set price as though the demand curve were linear. Our pricing rule can be used if three conditions hold: the firm can estimate the maximum price it can charge and still expect to sell some units, the firm need not plan in advance the quantity it will sell, and marginal cost is known and constant. We show that if the true demand curve is one of many commonly used demand functions, or even a more complex (randomly generated) function, the firm can expect its profit to be close to what it would earn if it knew the true demand curve. We derive analytical performance bounds for a variety of demand functions, calculate expected profit performance for randomly generated demand curves, and evaluate the welfare implications of our pricing rule. We show that with limited demand information (maximum price and marginal cost), our simple pricing rule can be used for new products while often achieving a near-optimal performance. We also discuss the limitations of our method by identifying cases where our pricing rule does not perform well