Xu Xiaolin. / "August 2006." / Thesis (Ph.D.)--Chinese University of Hong Kong, 2006. / Includes bibliographical references (p. 149-156). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts in English and Chinese.

Demand uncertainty has been recognized as one factor that may cause price dispersion in perfectly competitive markets with costly and perishable capacity. With the persistence of the degree of price dispersion in increasingly competitive markets, demand uncertainty has become more important for us to understand the phenomenon of fare inequality. This dissertation consists of three related studies on this topic. In the first study, Prescott (1975) model is extends by incorporating the heterogeneity of customers' reservation values. The model shows that the equilibrium price dispersion also depends on the mix of customers and their reservation values. With customer segmentation based on reservation values, the equilibrium price dispersion is more efficient than what can be achieved without segmentation. In the airline industry context, the model implies that different prices can exist simultaneously in the market and carriers would provide more seats if they can segment their travelers. This sheds light on an alternative motivation for airlines to require Saturday night stay over other than the practice of price discrimination. In the second study, a price simulation in the airline industry is conducted. The stochastic demand for coach class, nonstop, air travel service on the observed routs is calculated. Then a market price schedule based on Prescott's model is simulated by using nonparametric method. The comparison between the simulated price distribution and the actual price distribution provides evidence that on average more than 60 percent of the fare inequality on the observed routes can be accounted for by cost variation due to demand uncertainty under the condition of perfect competition. At last, an empirical model is specified to explore the relationship between route demand uncertainty and carrier price dispersion in U.S. air travel markets. The results demonstrate that the effect of route demand uncertainty on carrier price dispersion varies with the market structure. In monopoly market, the route demand uncertainty has no effect on carrier price dispersion. While in duopoly and competitive markets, the increase of route demand uncertainty is associated with the decrease of the carrier price dispersion. Furthermore, the negative relationship is magnified when the market becomes more competitive.

Pricing decision is the minority of all important decisions which can apparently influence a firm's profit-making within extremely short time. In an era of meagre profit, firms cannot stand any more injury caused of mistake at pricing. However, lots of managers still make pricing decision according to their experience or the action of other competitors without any mechanism of price-determining based on their firms' resource condition. The subject of this research is to probe the abiding price-reducing strategy for fashion appearing firms. Fashion apparel is a kind of commodities with seasonality and popularity, and is an example of all perishable goods. For all sorts of characteristic such as the need for long lead time before production, short time span for sale , and the low salvage value after season...etc., it makes firms reduce price to close out inventories by the end of seasons to evade value loss. When it comes to price-reducing, the fashion apparel is quite different from other commodities. It is a kind of commodity which has speciality of phased and monotonicity on price reduction. Therefore, it lacks two kinds of elasticity which are price-adjusting at any time and adjusting the price range at will. For the characteristic of close interdependence between product and time, and the normal demand on price-reducing, fashion apparel firms need some decision tools which are more fast, correct, and practical than any other ones. With two main parameters which are 'the levels of unsold inventory' and ' the length of season remaining ' along with two parameters which are 'discount factor' and ' the salvage value after season ', this research constructs out an stochastic dynamic programming model to maximize the expect profit and offer an program for calculating the optimal price-reduced range and time. After the analysis of generality and sensitivity with this model, it is found that the characteristics of this model are in conformity with theoretical research and real phenomenon of market. Besides, it is suitable for various kinds of price elastic demand. Hence, this model can be proved to be able to extend to other similar industries with the same nature.

In this dissertation, we study inventory and revenue management problems for perishable products with customer choice considerations. This dissertation is composed of six chapters. In Chapter 1, we provide an overview and the motivation of problems. Subsequently, in Chapter 2, we propose a joint inventory and pricing problem for a perishable product with two freshness levels. After a stochastic time, a fresh item turns into a non-fresh item, which will expire after another random duration. Under an (r, Q) ordering policy and a markdown pricing strategy for non-fresh items, we formulate a model that maximizes the long-run average profit rate. We then reduce the model to a mixed-integer bilinear program (MIBLP), which can be solved efficiently by state-of-the-art commercial solvers. We also investigate the value of using a markdown strategy by establishing bounds on it under limiting regimes of some parameters such as large market demand. Further, we consider an Economic Order Quantity (EOQ)-type heuristic and bound the optimality gap asymptotically. Our results reveal that although the clearance strategy is always beneficial for the retailer, it may hurt customers who are willing to buy fresh products. In Chapter 3, we extend this model to the dynamic setting with multiple freshness levels of perishable products. Due to the complexity of the problem, we study the structural properties of value function and characterize the structure of the optimal policies by using the concept of anti-multimodularity. The structural analysis enables us to devise three novel and efficient heuristic policies. We further extend the model by considering donation policy and replenishment system. Our results imply that freshness-dependent pricing and dynamic pricing are two substitute strategies, while freshness-dependent pricing and donation strategy are two complement strategies for matching supply with demand. Also, high variability in product quality under dynamic pricing benefits the firm, but it may result in significant losses with a static pricing strategy. In Chapter 4, we study a joint inventory-pricing model for perishable items with fixed shelf lives to examine the effectiveness of different markdown policies, including single-stage, multiple-stage, and dynamic markdown policies both theoretically and numerically. We show that the value of multiple-stage markdown policies over single-stage ones asymptotically vanishes as the shelf life, market demand, or customers’ maximum willingness-to-pay increase. In chapter 5, with a focus on blood products, we optimize blood supply chain structure along with the operations optimization. Specifically, we study collection, production, replenishment, issuing, inventory, wastage, and substitution decisions under three different blood supply chain channel structures, i.e., the decentralized, centralized, and coordinated. We propose a bi-level optimization program to model the decentralized system and use the Karush–Kuhn–Tucker (KKT) optimality conditions to solve that. Although centralized systems result in a higher performance than decentralized systems, it is challenging to implement them. Thus, we design a novel coordination mechanism to motivate hospitals to operate in a centralized system. We also extend the model to the case with demand uncertainty and compare different issuing and replenishment policies. Analysis of a realistic case-study indicates that integration can significantly improve the performance of the system. Finally, Chapter 6 concludes this dissertation and proposes future research directions. / Dissertation / Doctor of Philosophy (PhD)

We consider a continuous time dynamic pricing model where a seller needs to sell a single item over a finite time horizon. Customers arrive in accordance with a Poisson process. Upon arrival, a customer either purchases the item if the posted price is lower than his/her reservation price, or leaves empty-handed. After purchasing the item, some customers, however, will return the item to the seller at an exponential rate for a full refund. We assume that a returned item is in mint condition and the seller can resell it to future customers. The objective of the seller is to dynamically adjust the price in order to maximize the expected total revenue when the sale horizon ends. We formulate the dynamic pricing problem as a dynamic programming model and derive the structural properties of the optimal policy and the optimal value function. For cases in which the customer's reservation price is exponentially distributed, we derive the optimal policy in a closed form. For general reservation price distribution, we consider an approximation of the original model by discretizing both time and the allowable price set. We then present an algorithm for numerically computing the optimal policy in this discrete time model. Numerical examples show that if the discrete price set is carefully chosen, the expected total revenue is nearly the same as that when the allowable price set is continuous. / Master of Science

One of the implicit assumptions made in research related to inventory control is to keep products indefinitely in inventory to meet future demand. However, such an assumption is not true for a large wide of products characterized by a limited lifetime. The economic impact of managing such products led to substantial work in perishable inventory control literature. Investigations developed so far underline the complexity of modeling perishable inventory. Moreover, the dependency of the lifetime to temperature conditions in which products are handled adds more complexity since the lifetime of products stemming from the same order may vary from product to another. In this context, the ability of Time Temperature Integrators to capture the effects of temperature variations on products' lifetime, offers an opportunity to reduce spoilage and therefore ensure product's freshness and safety. The general aim of this thesis is to model perishable inventory systems. Particularly, three different problem areas are considered. The first one concerns perishable inventory with fixed lifetime, often referred as Fixed Life Perishability Problem, where an approximate (r;Q) inventory policy is developed. This model relaxes some assumptions made in previous related works. The second problem considered is a (T; S) perishable inventory system with random lifetime. Results of this model contribute to the development of a theoretical background for perishable inventory systems which are based on Markov renewal process approach. The third area incorporates the impact of temperature variations on products' lifetime throughout inventory systems that use TTIs technology. More general settings regarding the demand and the lifetime distributions are considered throughout simulation analysis. The economic relevance stemming from the deployment of this technology is therefore quantified.

This paper studies the problem of multi-period pricing for perishable products in a competitive (oligopolistic) market. We study non cooperative Nash equilibrium policies for sellers. At the beginning of the time horizon, the total inventories are given and additional production is not an available option. The analysis for periodic production-review models, where production decisions can be made at the end of each period at some production cost after incurring holding or backorder costs, does not extend to this model. Using results from game theory and variational inequalities we study the existence and uniqueness of equilibrium policies. We also study convergence results for an algorithm that computes the equilibrium policies. The model in this paper can be used in a number of application areas including the airline, service and retail industries. We illustrate our results through some numerical examples. / Singapore-MIT Alliance (SMA)

With the increasing effect of disasters and long term issues on human well-being and economy over the recent years, effective management of humanitarian supply chains has become more important. This thesis work focuses on three problems in humanitarian supply chains where uncertainty is inherent, namely (i) post-disaster debris clearance with uncertain debris amounts, (ii) allocation of a health/humanitarian commodity in a developing country setting with multiple demand types, and (iii) distribution of specialized nutritious foods by a large scale humanitarian organization. In each of the three parts, the problem is formally defined, and a novel optimal solution approach incorporating the inherent uncertainty in the environment and updates is proposed. In cases where optimal models cannot be solved within reasonable time, novel heuristics are developed. Through structural analysis and computational experiments based on real data, the proposed approaches are compared to those that ignore the uncertainty in the environment and/or updates of information as new data becomes available. Using computational experiments, the proposed approaches are compared to those that are applied in practice, and the aspects of the system where performance improvements are more significant are analyzed.

<p>We propose an approximation scheme for single-product periodic-review inventory systems with L-natural-convex structure. We lay out three well-studied inventory models, namely the lost-sales system, the perishable inventory system, and the joint inventory-pricing problem. We approximate the value functions for these models by the class of L-natural-convex quadratic functions, through the technique of linear programming approach to approximate dynamic programming. A series of heuristics are derived based on the quadratic approximation, and their performances are evaluated by comparison with existing heuristics. We present the numerical results and show that our heuristics outperform the benchmarks for majority of cases and scale well with long lead times. In this dissertation we also discuss the alternative strategies we have tried but with unsatisfactory result.</p> / Dissertation

L’une des hypothèses implicites faites dans la recherche liée à la gestion des stocks est de maintenir les produits indéfiniment pour satisfaire la demande future. Toutefois, cette hypothèse n’est pas vraie pour les produits caractérisés par une durée de vie limitée. L’impact économique de la gestion de tels produits a conduit à d’importants travaux de recherche. Les investigations développées jusqu’ici ont souligné la complexité de modéliser les stocks de produits périssables. En plus, la dépendance de la durée de la vie à la température à laquelle les produits sont maintenus crée un challenge majeur en termes de modélisation puisque la durée de vie des produits provenant d’une même commande peut varier d’un produit à un autre. La capacité des nouvelles technologies de contrôle de fraîcheur telles que les intégrateurs temps - température de capturer les effets des variations de la température sur la durée de vie offre une opportunité de réduire les pertes et donc d’assurer la fraîcheur des produits vendus. L’objectif général de cette thèse est de modéliser des politiques de gestion de stock des produits périssables. En premier lieu, nous nous intéressons `a la politique (r;Q) o`u les produits ont une durée de vie constante. Le modèle que nous proposons relaxe certaines hypothèses formulées dans les précédents travaux. La deuxième politique considérée est la politique (T; S) où les produits ont une durée de vie aléatoire. Enfin, nous étudions l’impact des nouvelles technologies de contrôle de fraîcheur des produits périssables sur la gestion des stocks. Nous nous intéressons à la pertinence économique découlant du déploiement des intégrateurs temps températures dans la gestion des stocks. / One of the implicit assumptions made in research related to inventory control is to keep products indefinitely in inventory to meet future demand. However, such an assumption is not true for a large wide of products characterized by a limited lifetime. The economic impact of managing such products led to substantial work in perishable inventory control literature. Investigations developed so far underline the complexity of modeling perishable inventory. Moreover, the dependency of the lifetime to temperature conditions in which products are handled adds more complexity since the lifetime of products stemming from the same order may vary from product to another. In this context, the ability of Time Temperature Integrators to capture the effects of temperature variations on products’ lifetime, offers an opportunity to reduce spoilage and therefore ensure product’s freshness and safety. The general aim of this thesis is to model perishable inventory systems. Particularly, three different problem areas are considered. The first one concerns perishable inventory with fixed lifetime, often referred as Fixed Life Perishability Problem, where an approximate (r;Q) inventory policy is developed. This model relaxes some assumptions made in previous related works. The second problem considered is a (T; S) perishable inventory system with random lifetime. Results of this model contribute to the development of a theoretical background for perishable inventory systems which are based on Markov renewal process approach. The third area incorporates the impact of temperature variations on products’ lifetime throughout inventory systems that use TTIs technology. More general settings regarding the demand and the lifetime distributions are considered throughout simulation analysis. The economic relevance stemming from the deployment of this technology is therefore quantified.