In this thesis, we analyze the effect that price postponement has on the performance and coordination of a two-stage supply chain facing consumer returns. In an extended news-vendor setting with a single product, a single manufacturer and a single retailer who faces stochastic and price-dependend demand, we allow the retailer to postpone his decision on the retail price until after demand uncertainty is resolved. A certain percentage of sold products is returned, which results in reverse logistics costs and a full refund for both consumer and retailer. In this setting we conduct an extensive computational study to investigate the value of considering returns in the optimization approach if the decision on the retail price is postponed. Moreover we analyze the value of the additional information gained by price postponement both if returns are considered or ignored. We present the impact on the equilibrium values of profits and decision variables for both the centralized and decentralized system and consider different incentive schemes to find out whether coordination is possible.

"Uncertainty" is used broadly to refer to things that are unknown or incompletely understood. In operations management, basic sources of uncertainty may include decision uncertainty, model uncertainty, analytical uncertainty, data uncertainty, and so on. Although uncertainty is unavoidable in decision making, different mechanisms can be designed to mitigate the impact of uncertainty. One commonly used strategy is "decision postponement," wherein the decision maker purposefully delays some of the decisions to a time when uncertainty is reduced or resolved. This type of a recourse action provides the decision maker with increased ability to match supply with demand. In this dissertation, we study the value of decision postponement in the context of different settings, including capacity investment, revenue management, and supply chain coordination. These problems share one characteristic in common: decision postponement, and as such, are all modeled as two-stage stochastic programming problems. In the first stage, a set of decisions are made under uncertainty so as to maximize the expected profit or utility. Then in the second stage, all uncertainty is resolved and a deterministic optimization problem is solved to determine the postponed decisions, constrained by the first stage decisions. In capacity investment, we study the capacity, pricing, and production decisions of a monopolist producing substitutable products with flexible or dedicated resources. While the capacity decision needs to be made ex-ante, under demand uncertainty, pricing and production decisions can be postponed until after uncertainty is resolved. We show how key demand parameters (the nature of uncertainty, market size, market risk, and risk attitude) impact the optimal capacity decision under the linear demand function. In particular, we show that if the demand shock is multiplicative, then in terms of the "invest or not" decision, the firm will be immune to forecast errors in parameters of the underlying demand shock distribution. Furthermore, incorrectly modeling the demand shock as additive, when, in fact, it is multiplicative, may lead to overinvestment. On the other hand, while the concept of a growth in market size leads to similar conclusions under both additive and multiplicative demand shocks, how market risk affects the optimal capacity decision depends critically on the form of the demand shock. In addition, the decision-maker's attitude toward risk significantly affects the optimal capacity level, and its impact highly depends on the structure of the resource network. Our analysis provides insights and principles on the optimal capacity investment decision under various settings. In airline revenue management, a well-studied problem is the optimal allocation of seat inventory among different fare-classes, given a capacity for the flight and a demand distribution for each class. In practice, capacity on a flight does not have to be fixed; airlines can exercise some flexibility on the supply side by swapping aircraft of different capacities between flights as partial booking information is gathered. This provides the airline with the capability to more effectively match their supply and demand. In this dissertation, we study the seat inventory control problem considering the aircraft swapping option. Our analytical results demonstrate that booking limits considering the swapping option can be considerably different from those under fixed capacity. We also show that principles on the relationship between the optimal booking limits and demand characteristics (size and risk) developed for the fixed-capacity problem no longer hold when swapping is an option. We develop new principles and insights on how demand characteristics affect the optimal seat allocation under the swapping possibility. We also perform a numerical study, which indicates that the revenue impact of using the "true" optimal booking limits under the swapping possibility can be significant. In supply chain coordination, we consider the influenza vaccine supply chain, which, due to the biological complexity of the production process, has a unique characteristic in that production yield is highly uncertain. Given the market demand and price, a monopolist supplier must decide how much raw material to input into production in the first stage. However, since the yield is unknown and production is costly, it is not necessarily in the supplier's best interest to ensure that all market demand is met. The supplier's input quantity depends on the trade-off between the costs of overproduction and undersupply. This, in fact, is one of the reasons why the influenza vaccine manufacturers in the United States lack motivation to produce sufficient amounts of vaccine to meet all demand [Williams (2005), Chick et al. (2008)]. In operations management, it is a well-known result that decentralized supply chains, where each player is only interested in optimizing her own objective, often lead to poor overall performance for the supply chain. However, a higher efficiency is achievable through contracting on a set of transfer payments [Cachon (2004)]. A "coordinating" contract is referred to as one in which each player's objective is in accordance with the supply chain's objective. Given the fact that influenza vaccine plays an important role in health care industry, it is important to study how different contracts impact the influenza vaccine supply chain, where the uncertainty is on the supply side. We study a game in which the supplier and the retailer are engaged in certain type of contracts that specify how risk is shared between the players. We study both the pre-ordering and the post-ordering settings, which respectively refer to the cases where the retailer orders the vaccine before or after the vaccine production is completed. We show that pre-ordering wholesale price contracts dominate post-ordering wholesale price contracts in terms of the resulting supply chain efficiency, but neither of them are able to fully coordinate the supply chain. We also find that cost-sharing contracts are able to coordinate the supply chain, while payback and advance-ordering wholesale price contracts fail to do so. Finally, we prove that if the unsold vaccine can be salvaged with some positive value, then the supply chain can be easily coordinated with wholesale price contracts. In studying this type of stochastic programming problems, it is not only important to characterize the optimal solution, but also important to gain an understanding of how the optimal solution will be affected by environmental parameters. Since the most inaccurate part in stochastic programming often lies in the parameters of the distribution functions, it is both interesting and meaningful to investigate how the optimal solution varies with the intrinsic nature of the random variables. Consequently, we make use of stochastic order relationships to study the behavior of the optimal solutions when the underlying random variables become either "larger" or "more risky." / Ph. D.

<div>As the manufacturing and healthcare systems becomes more complex, efficiently managing these systems requires cooperation and coordination between different parties. This dissertation examines the coordination issues in a supply chain problem and diagnostic decision making in the healthcare system. Below, we provide a brief description of the problem and results achieved. </div><div> </div><div>With supply chain becoming increasingly extended, the uncertainty in the upstream production process can greatly affect the material flow that aims toward meeting the uncertain demand at the downstream. In Chapter 2, we analyze a two-location system in which the upstream production facility experiences random capacities and the downstream store faces random demands. Instead of decomposing the profit function widely used to treat multi-echelon systems, our approach builds on the notions of stochastic functions, in particular, the stochastic linearity in midpoint and the directional concavity in midpoint, which establishes the concavity and submodularity of the profit functions. In general, it is optimal to follow a two-level state-dependent threshold policy such that an order is issued at a location if and only if the inventory position of that location is below the corresponding threshold. When the salvage values of the ending inventories are linear, the profit function becomes decomposable in the inventory positions at different locations and the optimal threshold policy reduces to the echelon base-stock policy. The effect of production and demand uncertainty on inventory levels depends critically on whether the production capacity is limited or ample in relation to the demand. Only when the capacity is about the demand, the upstream facility holds positive inventory; otherwise, all units produced are immediately shipped to the downstream. We further extend our analysis to situations with general stochastic production functions and with multiple locations.</div><div> </div><div> </div><div>In Chapter 3, we examine the two-stage supply chain problem (described in Chapter 2) under the decentralized control. We consider two scenarios. In the first scenario, the retail store does not have any supply information including the inventory level at the manufacturing facility. We show that the upstream and downstream can be dynamically coordinated with proper transfer payment defined on local inventories and their own value function in the dynamic recursion. In the second scenario, the demand distribution is unknown to the manufacturing facility as well as the retail store does not know the supply information. We characterize the optimal transfer contracts under which coordination can be achieved, and propose an iterative algorithm to compute the optimal transfer contracts in the decentralized setting. The total profit of the decentralized system under our algorithm is guaranteed to converge to the centralized optimal channel profit for any demand and supply distribution functions. </div><div> </div><div>In Chapter 4, we provide a case study for the framework developed in [1]. The authors study the evaluation and integration of new medical research considering the operational impacts. As a case study, we first describe their two-station queueing control model using the MDP framework. We then present the structural properties of the MDP model. Since multiple classes of patients are considered in the MDP model, it becomes challenging to solve when the the number of patient classes increases. We describe an efficient heuristic algorithm developed by [1] to overcome the curse of dimensionality. We also test the numerical performance of their heuristic algorithm, and find that the largest optimality gap is less than 1.50% among all the experiments. </div><div> </div>

<p>This dissertation studies coordination mechanism design for sustainable supply networks in a globalized environment, with the goal of achieving long-term profitability, environmental friendliness and social responsibility. We examine three different types of supply networks in detail.</p><p>The first network consists of one supplier and multiple retailers. The main issue is how to efficiently share a scarce resource, such as capacities for green technology, among all members with private information under dynamically changing environment. We design a shared surplus supply agreement among the members which can lead to both efficient private investments and efficient capacity allocation under unpredictable and unverifiable market conditions.</p><p>The second network is a serial supply chain. The source node provides critical raw material (like coffee cherries) for the entire chain and is typically located in an underdeveloped economy, the end node is a retailer serving consumer at a developed economy (like Starbucks Co.). We construct a dynamic supply agreement that takes into account the changing market and production conditions to ensure fair compensations so that the partners have the right incentives to work together to develop sustainable quality supply.</p><p>The third network is a stylized global production network of a multinational company consisting of a home plant and a foreign branch. The branch serves the foreign market but receives a key component from the home plant. The distinctive feature is that both facilities belong to the same company, governed by the headquarters, yet they each also have their own autonomies. We analyze the role of the headquarters in designing coordination mechanism to improve efficiency. We show the headquarters can delegate the coordination effort to the home plant, as long as it keeps veto power.</p> / Dissertation

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Building supply chain coordination frameworks is a popular practice in the private sector in many developed countries. Despite this fact, in developing countries such as Uganda, the public health sector has hardly adopted this practice. Although the existing frameworks offer a good platform for measuring and improving the understanding of concepts underlying coordination dimensions at the micro-environment, they have limited capacity to analyse coordination interactions within the health sector, especially in developing countries like Uganda. Using the business management environment framework, this study explored the critical supply chain coordination dimensions, logistics activities dimensions and the management environment (market and macro) dimensions affecting the availability of Artemisinin-based Combination Therapies for malaria (ACTs). The overall main research goal of this thesis was to develop a supply chain coordination framework for malaria treatment therapies (ACTs) in general hospitals in Uganda. To understand the coordination dimensions of ACTs, the study adopted an exploratory sequential mixed research design, which involved a mixture of qualitative and quantitative approaches. For the qualitative phase, four focus group discussions were held. From the results, an instrument was developed and later validated using the quantitative approach. Specifically, Exploratory Factor Analysis (EFA) with a maximum likelihood extraction method followed by Confirmatory Factor Analysis (CFA) were used to analyse quantitative data. Considering the volume of the dimensions, Analytical Process Hierarchy (AHP) was carried out to rank the dimensions in order of priority. Analysis of the factor correlation matrix shows no common variance among the components; therefore, the principal components were distinct from one another and there was no discriminant validity. The CFA results showed that the standardised parameter estimates of the initial measurement models were all significant (p<.05). CFA and APH outputs were somehow different simply because each technique has its own purpose and principles. It was indicated that the correlation between critical supply chain coordination dimensions and level of ACTs availability is moderately higher, followed by logistics, macro and market environments. By better understanding the supply coordination dimensions effects on ACTs in Uganda, the research provides important direction to African governments and international donor agencies in their efforts to make malaria treatment therapies available, especially to the rural poor and avert death. The findings serve as a platform to argue for revisiting coordination dimensions in view of conditions that include a resurgent market and macro-environment in developing countries. The insight raises implications for extending coordination frameworks that are geographically focused, and specific to ACTs. It may influence policy direction in this regard and thus contribute to the body of knowledge. / Business Management / D. Phil. (Management Studies)

Lean production and Lean philosophy have been developed, studied and implemented over the world since it was know from Toyota Production System. International manufacturers/OEMs have more or less developed their own Lean production systems. Over the years, arising challenges from new technology and internationalization have force the OEMs to understand and evaluate the design of supply chain to support their lean production system, and to manage the SC and compete as a whole against other supply chains. When apply Lean principles to the level of Supply Chain, coordination is an essential element to success. Today, researches have been done on joint efforts on decision making among supply chain actors, and applying Lean tools such as VSM on an extended level, namely a supply chain. Whereas the methods to improve SC coordination when implementing Lean through SC remain undeveloped. By interviewing Lean supply chain experts, experienced personnel in Supply Chain Management, and Lean experts from various organizations, a methodology to identify and visualize the improvement areas in supply chain coordination was designed. The methodology was then tested in a European OEM’s supply chain. Value Stream Mapping, as the base, was adapted to support identification and visualization of improvement areas in supply chain coordination. Several misalignments in the SC coordination were found in the current state, then visualized in current state map and approved by various SC actors. The methodology was then improved according to the process of testing. The purpose of this thesis is to develop a methodology to identify and visualize the improvement areas in (manufacturing) supply chain coordination within a Lean perspective.

現今，許多公司與他們的供應商夥伴建立跨組織資訊系統交換資訊、給予對方更快速的回應，以在快速變遷的環境之下維持競爭力。此篇研究進行文獻探討之後，分別從流程觀點還有動態能力觀點這兩個研究理論的基礎之下建立了研究架構，來衡量跨組織資訊系統的績效。我們的研究架構提出，一間公司有兩個重要的動態能力，分別是供應鏈的整合能力還有協調能力，在資訊科技的投資上還有公司績效之間扮演相當重要的角色。 / 我們在台灣的PC產業中發行問卷來衡量此研究架構，利用線性回歸來驗證假設。實驗結果支持了論文中的兩個假設：(1)跨組織資訊系統正向影響動態能力，(2)供應鏈的整合能力在跨組織資訊系統投資還有公司績效中間扮演重要的中介角色。 / Nowadays, firms usually develop inter-organizational systems (IOS) with their suppliers to exchange information and give each other faster responses to sustain their competency under a fast-changing environment. This study reviewed past literature and developed a research framework to evaluate IOS performance based upon two theoretical perspectives: process view and dynamic capabilities. This framework proposed that firms’ dynamic capabilities-- supply chain integration capability and supply chain coordination capability might be an important mediator between IOS investment and firm performance. / A general survey is conducted in Taiwan PC industry to validate the research model. A linear regression is used to testify the hypotheses. The results support our two hypotheses: (1) IOS investment is positively related to the dynamic capabilities, which also have obvious impact on firm performance; (2) supply chain integration is an important mediator between IOS investments and firm performance, and on the other hand, firm performance is partially mediated by supply chain coordination.