Dynamic Pricing Strategy For Perishable Products In Competitive Markets With Consumer Behavior

As a powerful tool in revenue management, dynamic pricing is a business strategy that adjusts the product price in real time in order to maximize profit. In recent years, dynamic pricing strategies and their further development get widely applied in airlines, car rental and hotel rooms.The traditional research on dynamic pricing focus on monopolistic models and assumes the firm enjoys monopoly power. A monopolistic model is that the distribution of the demand depends solely on the price set by the monopolist. This assumption is problematic nowadays because customer can easily extract the real-time price of the product in the internet. At the same time, with the development of information technology, more and more consumers'buying behavior becomes diversify. The customer behaviour in competitive markets is an unavoidable issue in the applications of dynamic pricing. The optimized pricing decision without considering this issue will not perform well. Based on this motivation, the effect of competition on customer behaviour is substantial and should be taken into account when determining the optimal price to charge for goods or services. How to take competition and customers'behavior into the decision-making model, in order to improve the profit of firms, is very necessary for theoretical research and practical applications.Based on review of current researches of dynamic pricing in revenue management, this thesis studies thoroughly the dynamic pricing strategy for revenue management in competitive markets with consumer behavior. We study the topic through introducing cancellation demand, strategic consumers and heterogeneity of consumer preferences in competitive markets using dynamic optimization theory and game theory, from the aspects of whether the consumer preferences are heterogeneity.Fitst, chapter 3 presents the dynamic pricing strategies that maximize revenue when selling an inventory of identical items by a fixed time with internet where there is a competing seller. We study the dynamic pricing decisions of the firm without cancellation demand, and further extend the pricing strategies which influenced by the cancellation demand. The results of game show that the cancellation demand does not affect the properties of the expected revenue, and both firms will charge of the lowest price at the beginning and last time of selling season.Chapter 4 analyzes a dynamic pricing model for two retailers selling to a finite population of strategic consumers and introduces a new type of competition between the retailers, to be referred to as zigzag competition. We present the model in the situations that the inventory is sufficient to satisfy all consumers, and prove the existence of a unique subgame-perfect equilibrium pricing policy. We also provide equilibrium optimality conditions for both consumer and seller based on reducing the dimension of the state space. Then we prove monotonicity results on equilibrium price, choice probability and customers'utility for special cases. We further extend the model to the situations where the retailers cannot satisfy the entire market demand, and discuss the computing method of the model.Heterogeneity of customer preferences is often an important factor in management practices. Chapter 5 relaxs the assumptions that all of the customers are identical and divid the consumer into two types: time-dependent and price-dependent.We introduce and analyze a multi-period dynamic pricing model under duopoly competition and show the existence of Nash equilibrium. We also show the uniqueness of Nash equilibrium in the the situations where there are two firms. We further obtain that if there are multiple equilibria, each firm prefers to play its highest equilibrium price.Chapter 6 introduces a dynamic model which integrates pricing and capacity allocation for two retailers selling to a finite population of consumers, and divid the consumer into two types: contract group and walk-in group. Upon receiving the booking request, the firm has to decide whether to offer service to the contract group and what fees to charge the walk-in group. Solutions and corresponding properties are discussed. We also discuss the relationship of the optimal price strategy and obtain the optimal allocation of inventory which is achieved by the total number of remaining units. Finally, we demonstrate that the dynamic allocation of capacity can improve the revenue of firm in competitive markets when facing the heterogeneous consumers.