published_or_final_version / Business Administration / Master / Master of Business Administration

Keywords. Hub-to-hub network, bid-price control, certainty equivalent control, combinatorial optimization, structures, primal-dual, revenue management, airline network, monotone thresholds, supermodularity/submodularity, L♮ concavity, Lagrange dual. / The subject of this study is the revenue management problem in hub-to-hub airline networks. The network consists of two hubs and a connecting flight between them with spoke cities expanding outwards. The airline produces various itineraries within the network, and its flights compete with each other for limited flight capacities during a fixed booking period. Although stochastic dynamic network revenue management has been theoretically established, in reality its implementation is still heavily dependent on linear programming-based heuristics. Simpson (1989) and Williamson (1992) proposed bid price control, which is now widely adopted by major airlines. Bertsimas and de Boer (2003) proposed certainty equivalent control, which has been little studied by RM researchers. In this thesis, bid price control is first explained, and then the structural properties of the hub-to-hub network are investigated. Using the Lagrange dual-function and the primal-dual relationship, it is shown that the threshold values used in bid price control have some monotone properties in the network's capacity states. The certainty equivalent control is then applied to the hub-to-hub network. By linking the network revenue management problem with a maximum-weight circulation problem in network flow, the optimal value function is shown to be supermodular in certain capacity dimensions, and submodular in other dimensions. This leads to the monotonicity of CEC thresholds on some short-haul itineraries. The notion of L ♮ concavity developed by Murota and Shioura (2005) is applied to this work, and it is shown that even the CEC thresholds on some two-leg or three-leg long-haul itineraries are monotonically increasing or decreasing in certain legs' capacities. It is hoped that the new structural properties found in this thesis can lead to a reduction of the computational work in the implementation of both the bid price control and the certainty equivalent control in the hub-to-hub airline network. / He, Hongzhi. / Adviser: Zhang Shuzhong. / Source: Dissertation Abstracts International, Volume: 72-04, Section: B, page: . / Thesis (Ph.D.)--Chinese University of Hong Kong, 2010. / Includes bibliographical references (leaves 111-118). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. Ann Arbor, MI : ProQuest Information and Learning Company, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese.

The efficiency of revenue management relies on the effectiveness of the strategies it employs. In the competing market nowadays, time has become an important concern at both demand and supply sides. With time-sensitive customers and additional benefits from intertemporal demand shift, we find that the sellers could turn to a time-differentiation based strategy as an effective revenue management tool. Motivated by real-life business issues of Toyota China dealerships, in this thesis, we consider stylized inventory-control models with delivery upgrades, in which the seller allocates its on-hand inventory to price and delivery-time sensitive customers. The seller provides two delivery-time options with different prices. Customers choose the proper purchasing option according to their heterogeneous preferences. The seller has two decisions: inventory commitment and inventory replenishment. The former addresses, within an inventory cycle, how on-hand inventories are allocated between the two classes of customers. The latter addresses, between inventory cycles, how the inventory is replenished. Furthermore, the seller may employ early delivery, namely upgrade, to achieve a higher inventory flexibility. We develop the optimal inventory allocation and upgrade, and inventory replenishment policies, and demonstrate that the optimal control can be characterized by a switching curve. Based on the basic model setting, we extend our analysis to include cases of upgrade cost, stock-out substitution, and capacity constraint. We further discuss the joint pricing and inventory decision. We obtain the form of the optimal joint policy, and show that the two strategies may well complement each other in our setting. When each is applied separately, their performances are also compared. To shed more light on the practical side, finally, we use the Toyota dealership data to calibrate the required parameters, and demonstrate the potential of the optimal inventory allocation and upgrade control. / Liang, Xiaoying. / Advisers: Houmin Yan; Youhua Chen. / Source: Dissertation Abstracts International, Volume: 72-04, Section: B, page: . / Thesis (Ph.D.)--Chinese University of Hong Kong, 2010. / Includes bibliographical references (leaves 118-124). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. Ann Arbor, MI : ProQuest Information and Learning Company, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. Ann Arbor, MI : ProQuest Information and Learning Company, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese.

Some owners of small-farm wineries have moved to direct and alternative revenue management strategies to generate revenue and create brand awareness because of increased competition and regulatory changes. Research has revealed that owners of small-farm wineries remain financially reliant on direct-to-consumer sales through tasting rooms that represent an estimated 70% of their total revenue generated. This qualitative multiple case study was an exploration of how revenue management decisions of small-farm winery owners may contribute to long-term survival in a regulated industry. Dynamic capabilities concept was the conceptual framework for this study. The study population consisted of 3 small-farm winery owners in Connecticut who have operated a winery with Connecticut Grown designation for at least 10 years. Data were collected through semistructured interviews, organizational documents, observation notes, and review of each winery's website. Three themes emerged from data analysis: focus on brand and customer base, constraints consideration, and competitors' impact. The findings and recommendations from this study may further small-farm winery owners' understanding of revenue management strategies they can use to overcome constraint challenges and mitigate competitors' impact. As small-farm winery owners improve profitability and sustain long-term survival, subsequent positive social change, such as small business development and increased employment opportunities, may lead to economic prosperity for the local community and financial stability of community residents.

A fundamental challenge in operations management is to dynamically match spatially diversified supply sources with random demand units. This dissertation tackles this challenge in two major areas: in supply chain management, a company procures from multiple, geographically differentiated suppliers to service stochastic demands based on dynamically evolving inventory conditions; in revenue management of ride-hailing systems, a platform uses operational and pricing levers to match strategic drivers with random, location and time-varying ride requests over geographically dispersed networks. The first part of this dissertation is devoted to finding the optimal procurement and inventory management strategies for a company facing two potential suppliers differentiated by their lead times, costs and capacities. We synthesize and generalize the existing literature by addressing a general model with the simultaneous presence of (a) orders subject to capacity limits, (b) fixed costs associated with inventory adjustments, and (c) possible salvage opportunities that enable bilateral adjustments of the inventory, both for finite and infinite horizon periodic review models. By identifying a novel, generalized convexity property, termed (C1K1, C2K2)-convexity, we are able to characterize the optimal single-source procurement strategy under the simultaneous treatment of all three complications above, which has remained an open challenge in stochastic inventory theory literature. To our knowledge, we recover almost all existing structural results as special cases of a unified analysis. We then generalize our results to dual-source settings and derive optimal policies under specific lead time restrictions. Based on these exact optimality results, we develop various heuristics and bounds to address settings with fully general lead times. The second part of this dissertation focuses on a ride-hailing platform's optimal control facing two major challenges: (a) significant demand imbalances across the network, and (b) stochastic demand shocks at hotspot locations. Towards the first major challenge, which is evidenced by our analysis of New York City taxi trip data, the dissertation shows how the platform's operational controls--including demand-side admission control and supply-side empty car repositioning--can improve system performance significantly. Counterintuitively, it is shown that the platform can improve the overall value through strategic rejection of demand in locations with ample supply capacity (driver queue). Responding to the second challenge, a demand shock of uncertain duration, we show how the platform can resort to surge pricing and dynamic spatial matching jointly, to enhance profits in an incentive compatible way for the drivers. Our results provide distinctive insights on the interplay among the relevant timescales of different phenomena, including rider patience, demand shock duration and drivers' traffic delay to the hotspot, and their impact on optimal platform operations.

In 2004, 6% of the Crowne Plaza Auckland Hotel's guests were Priority Club members. Two years later, this number has more than doubled to 13%. Are the Priority Club guests contributing to leverage the hotel's profitability? This research is aimed at answering the question if the continuous increase in the number of Priority Club guests staying at the Crowne Plaza Auckland Hotel is an opportunity for the property to effectively optimise its revenue generation performance. The study is essentially focused on assessing the ability of the loyalty programme to generate revenue to the hotel. The Priority Club Rewards is a demand-based, revenue-orientated marketing strategy which is predominantly aimed at 1) promoting and attracting its 30 million members worldwide to stay at the company's extensive portfolio of hotels as well as 2) to entice the club members to spend money on the hotels' services and facilities. In return for their loyalty, these customers are entitled to receive benefits that correspond to their membership level. From a revenue management perspective, the programme exists to strategically help hoteliers not only to achieve higher occupancy levels through repeat visits from the club members but to also leverage the hotel's revenue generating performance through encouraging its members to not only stay in suites and club rooms but also to use the property's services and facilities more regularly. In other words, the objective of the Priority Club Rewards is to help hoteliers attract customers to their properties and at the same time encourage them to spend money whilst onsite. It was found that the Priority Club programme is fulfilling its first core objective, which is to bring more customers to the Crowne Plaza Auckland property. Hence, this research is predominantly focused on assessing the rewards programme's ability to also assist the Auckland hotel to increase profitability. The objective of this project is to analyse whether or not the increasing growth in the number of club members staying at the property can also be interpreted as a growth in the hotel's revenue generation performance. Firstly, a thorough review of the literature was conducted in order to identify any previous academic work that specifically analysed the relationship between the areas of revenue management and loyalty marketing. However, no extensive previous research was found that effectively analysed how these two fields interact with each other, particularly in the hotel industry. Nevertheless, research from Internet articles and other web-based media resources was highly beneficial to the success of this research. There were two data collection processes employed in this research: a Priority Club Survey identified the needs and preferences of the club members when staying at the Auckland hotel and, secondly, a Spending Pattern Analysis was conducted based on the hotel guests' account statements. The results from these two research methods were then carefully analysed and interpreted in order to achieve an accurate set of resourceful conclusions and recommendations.

This thesis explores the institutional choices available to Timor-Leste to manage their natural resource wealth wisely and avoid the resource curse. Timor-Leste is a poor country and its challenge is to use its large per capita resource wealth to alleviate poverty and enable sustainable development. This research examines the Petroleum Fund Law, and other mechanisms to manage petroleum revenue that the Government of Timor-Leste has established. These mechanisms appear to be resilient, but remain untested. Based on field interviews in Timor-Leste, the study offers insights into the opinions of East Timorese and foreign advisers about how Timor-Leste´s petroleum revenue should be managed, and how a poor country can raise the living standards of its people.¶A framework that identifies human and social capital as essential to the quality of institutions is developed in this research, which proposes that the pre-condition of institutions affects the management of natural resource revenue. As a result of history (not its natural resource wealth) Timor-Leste´s productive institutions are weak and destructive institutions, such as corruption, are strong. The preferences of the research participants, identified using semi-structured interviews and multi-criteria decision analysis, revealed that what petroleum revenue is spent on is the most important petroleum revenue management decision. Further, health and education were regarded the highest spending priorities. Petroleum revenue management decisions that may affect Timor-Leste´s economic, social and political independence were also important to participants.¶Timor-Leste´s sustainable development depends on continued assistance in the form of foreign advisers to address its lack of human capital. A commitment to transparency should counteract the lack of trust between government and civil society. Timor-Leste will also need to invest more in people, and recognise that the wise management of its petroleum revenue depends as much on good governance as the mechanisms designed to manage it. The people of Timor-Leste´s fierce determination to overcome the challenges they face, against all odds, may help Timor-Leste to avoid the resource curse.¶

With the success of Revenue Management (RM) techniques over the past three decades in various segments of the service industry, many manufacturing firms have started exploring innovative RM technologies to improve their profits. This dissertation studies RM for make-to-order (MTO) and make-to-stock (MTS) systems. We start with a problem faced by a MTO firm that has the ability to reject or accept the order and set prices and lead-times to influence demands. The firm is confronted with the problem to decide, which orders to accept or reject and trade-off the price, lead-time and potential for increased demand against capacity constraints, in order to maximize the total profits in a finite planning horizon with deterministic demands. We develop a mathematical model for this problem. Through numerical analysis, we present insights regarding the benefits of price customization and lead-time flexibilities in various demand scenarios. However, the demands of MTO firms are always hard to be predicted in most situations. We further study the above problem under the stochastic demands, with the objective to maximize the long-run average profit. We model the problem as a Semi-Markov Decision Problem (SMDP) and develop a reinforcement learning (RL) algorithm-Q-learning algorithm (QLA), in which a decision agent is assigned to the machine and improves the accuracy of its action-selection decisions via a “learning" process. Numerical experiment shows the superior performance of the QLA. Finally, we consider a problem in a MTS production system consists of a single machine in which the demands and the processing times for N types of products are random. The problem is to decide when, what, and how much to produce so that the long-run average profit. We develop a mathematical model and propose two RL algorithms for real-time decision-making. Specifically, one is a Q-learning algorithm for Semi-Markov decision process (QLS) and another is a Q-learning algorithm with a learning-improvement heuristic (QLIH) to further improve the performance of QLS. We compare the performance of QLS and QLIH with a benchmarking Brownian policy and the first-come-first-serve policy. The numerical results show that QLIH outperforms QLS and both benchmarking policies.

This paper analyzes macroeconomic factors and their effect on 2-year government bonds of 11 countries in the European Monetary Union. I specifically looked at how a simultaneous budget and trade surplus effect a country's bond yield spread relative to Germany's bond yield. My model showed that double surplus countries have a larger yield spread than countries that do not have a double surplus.

In the first part of this thesis, we study revenue management in resource exchange alliances. We first show that without an alliance the sellers will tend to price their products too high and sell too little, thereby foregoing potential profit, especially when capacity is large. This provides an economic motivation for interest in alliances, because the hope may be that some of the foregone profit may be captured under an alliance. We then consider a resource exchange alliance, including the effect of the alliance on competition among alliance members. We show that the foregone profit may indeed be captured under such an alliance. The problem of determining the optimal amounts of resources to exchange is formulated as a stochastic mathematical program with equilibrium constraints. We demonstrate how to determine whether there exists a unique equilibrium after resource exchange, how to compute the equilibrium, and how to compute the optimal resource exchange. In the second part of this thesis, we study the estimation of risk measures in risk management. In the financial industry, sell-side analysts periodically publish recommendations of underlying securities with target prices. However, this type of analysis does not provide risk measures associated with underlying companies. In this study, we discuss linear regression approaches to the estimation of law invariant conditional risk measures. Two estimation procedures are considered and compared; one is based on residual analysis of the standard least squares method and the other is in the spirit of the M-estimation approach used in robust statistics. In particular, Value-at-Risk and Average Value-at-Risk measures are discussed in detail. Large sample statistical inference of the estimators is derived. Furthermore, finite sample properties of the proposed estimators are investigated and compared with theoretical derivations in an extensive Monte Carlo study. Empirical results on the real data (different financial asset classes) are also provided to illustrate the performance of the estimators.