Dynamic Price Discrimination and Quality Provision Based on Purchase History

This paper develops a general two-period model of product line pricing with customer recognition. Specifically, we consider a monopolist who can sell vertically differentiated products over two periods to heterogeneous consumers. Each consumer demands one unit of the product in each period. In the second period, the monopolist can condition the price-quality offers on the observed purchasing behavior in the first period. In this setup, the monopolist can price discriminate consumers not only by quality, but also by purchase history. Several interesting results are derived. First, we fully characterize the monopolist's optimal pricing strategy when there are two types of consumers, and a simple condition is given to determine whether the monopolist will price discriminate by quality in the first period. We compare it to the case when there is no customer recognition or the firm is able to commit to its future actions. When the type space is a continuum, we show that there is no fully separating equilibrium, and some properties of the optimal contracts (price-quality pairs) are characterized within the class of partitional PBE.Price discrimination; Supermodularity; Submodularity; Behavior-Based Pricing; Ratchet Effect; Bunching

Competition versus Collusion: The Impact of Consumer Inertia

We consider a model of dynamic price competition to analyze the impact of consumer inertia on the ability of firms to sustain high prices. Three main consequences are identified, all of which contrast with predictions of the standard model of collusion: (i) maintaining high prices does not require punishment strategies when firms are sufficiently myopic, (ii) if buyers are sufficiently inert, then high prices can be sustained for all discount factors, and (iii) the ability to maintain high prices may depend non-monotonically on the level of the discount factor when the industry exhibits network externalities and demand is sufficiently viscous. These results provide a number of interesting insights with regard to competitive and collusive pricing behavior. In particular, we illustrate how direct communication between firms may facilitate collusion.microeconomics ;

Monopoly Pricing of Experience Goods

We develop a dynamic model of experience goods pricing with independent private valuations. We show that the optimal paths of sales and prices can be described in terms of a simple dichotomy. In a mass market, prices are declining over time. In a niche market, the optimal prices are initially low followed by higher prices that extract surplus from the buyers with a high willingness to pay. We consider extensions of the model to integrate elements of social rather than private learning and turnover among buyers.Monopoly, dynamic pricing, learning, experience goods, continuous time, Markov perfect equilibrium

Experimentation in Two-Sided Markets

We study optimal experimentation by a monopolistic platform in a two-sided market framework. The platform provider faces uncertainty about the strength of the externality each side is exerting on the other. It maximizes the expected present value of its profit stream in a continuous-time infinite-horizon framework by setting participation fees or quantities on both sides. We show that a price-setting platform provider sets a fee lower than the myopically optimal level on at least one side of the market, and on both sides if the two externalities are of approximately equal strenght. If the externality that one side exerts is sufficiently weaker than the externality it experiences, the optimal fee on this side exceeds the myopically optimal level. We obtain analogous results for expected prives when the platform provider chooses quantities. While the optimal policy does not admin closed-form representations in general, we identify special cases in which the undiscounted limit of the model can be solved in closed form

전략적 고객 행동을 고려한 심층 강화학습 기반 항공사 동적 가격 결정 연구

학위논문(석사) -- 서울대학교대학원 : 공과대학 산업공학과, 2023. 2. 문일경.This thesis considers an airline dynamic pricing problem in the presence of patient customers. Nowadays, customers behave strategically to pay lower than their willingness to pay because they know airlines are implementing dynamic pricing strategies. To capture the non-myopic characteristic, we propose a Markov decision process (MDP) including a history of offered prices as a state variable. In contrast to previous studies, distributions of customers' properties are assumed to be unknown in advance. Deep reinforcement learning (DRL) algorithms are utilized to solve it, and the results of numerical experiments are presented to show that their performance can be improved with the proposed formulation. Comparisons between algorithms are also made to determine which can construct appropriate pricing structures for the patient and non-stationary demand. The structures of pricing policies generated from the bootstrapped deep Q-network algorithm imply that airlines should offer high and low prices alternately from the beginning of the sales period rather than increasing prices as time goes on. We also ascertain that more frequent consecutive high-priced periods can increase airlines' revenue in environments with higher customer patience levels.본 연구에서는 전략적 소비자가 존재하는 시장에서 항공사 동적 가격 결정 문제를 다루었다. 최근 소비자들은 항공사에서 동적 가격 정책을 시행하는 것을 인지하고 있기 때문에, 그들의 지불 용의보다 낮은 가격을 지불하기 위해 전략적으로 행동한다. 이러한 소비자 특성을 고려하여, 본 연구에서는 과거에 제시된 가격 기록을 상태 변수로 포함하는 마르코프 의사결정 과정 모델을 제안하였다. 이 때 고객 특성에 대한 확률 분포들은 사전에 알려져 있지 않다고 가정하였다. 문제 해결을 위해 심층 강화학습 방법론이 활용되었으며, 알고리즘 별 비교를 통해 전략적이고 동적인 수요 하에서 가장 적절한 가격 구조를 도출하는 알고리즘을 제시하였다. 또한 해당 가격 구조를 분석하여 전략적 수요로부터 추가적인 수익을 발생시키기 위한 경영적 통찰력을 제공하고자 하였다.Chapter 1 Introduction 1 Chapter 2 Problem description 9 2.1 Dynamics of patient customers 9 2.2 Markov decision process 11 2.3 Airline dynamic pricing 11 Chapter 3 Solution methods 15 3.1 Deep Q-network 17 3.2 Bootstrapped DQN 18 3.3 Optimistic learning for decreasing cyclic policies 21 Chapter 4 Numerical experiments 23 4.1 Comparison between MDP formulations in the presence of patient customers 24 4.2 Comparison between pricing algorithms for non-stationary demand and insufficient inventory 27 4.3 Structure of pricing policies from the BDQN algorithm 33 4.4 Non-stationary test for the distributions of reservation prices 34 Chapter 5 Conclusions 38 Bibliography 41 국문초록 47석

Incomplete cost pass-through under deep habits

A number of empirical studies document that marginal cost shocks are not fully passed through to prices at the firm level and that prices are substantially less volatile than costs. We show that in the relative-deep-habits model of Ravn, Schmitt-Grohe, and Uribe (2006), firm-specific marginal cost shocks are not fully passed through to product prices. That is, in response to a firm-specific increase in marginal costs, prices rise, but by less than marginal costs leading to a decline in the firm-specific markup of prices over marginal costs. Pass-through is predicted to be even lower when shocks to marginal costs are anticipated by firms. In our model, unanticipated firm-specific cost shocks lead to incomplete pass-through (or a decline in markups) of about 20 percent and anticipated cost shocks are associated with incomplete pass-through of about 50 percent. The model predicts that cost pass-through is increasing in the persistence of marginal cost shocks and U-shaped in the strength of habits. The relative-deep-habits model implies that conditional on marginal cost disturbances, prices are less volatile than marginal costs