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Advances in manufacturing and information technologies have made it possible for firms to satisfy consumers’ increasing demand for unique products. Although, the mass customization of products is prevalent in almost all industries today, firms’ optimal mass customization strategy is still not that clear. The initial attempt to mass customization of a number of firms failed, because it proved to be unprofitable, while others have successfully established mass customization as a product strategy. The optimal degree of mass customization solves two decision problems: first, firms’ trade-off between the coverage of consumers’ preferences to charge a premium price and cost-efficient production; second, consumers’ trade-off between tailoring a product to their needs and interaction costs. In an attempt to facilitate managerial decision making, this thesis studies a firm’s mass customization decision in a game-theoretical model that combines the decision problems faced by each player in the interaction. Based on this model of company-customer interaction, novel insights into the optimal mass customization strategy of firms depending on their market and competitive environment are gained.
The combined impact of changing global demand and supply dynamics, extensive trading and speculation as well as global recessionary fears, has led to an environment of unprecedented volatility in worldwide commodity markets. As a result, effective risk management has become an increasingly important topic on the agenda of top management in a broad range of industries. While practical evidence shows that successful firms integrate both operational decision making and financial hedging in a firm-wide, coordinated risk management strategy, this entails managerial challenges. On the one hand, quantifying a firm’s exposure to raw material cost risk necessitates a sound understanding of the stochastic commodity market dynamics. On the other hand, once the exposure to different sources of risk is understood, executives face an intricate optimization problem over their operational and financial decision variables with the ultimate goal to reduce profit variability, while maintaining attractive business opportunities.
In this thesis, the topic of operational and financial risk management is investigated from three different perspectives.
In Chapter 2, a four-factor maximal affine stochastic volatility model of commodity prices is developed, which is consistent with many stylized characteristics of storable commodity markets as well as the historical term structure of commodity futures and option prices. Based on this model, we provide new insights with respect to the structural dynamics of commodity markets and the pricing and hedging of commodity derivatives. As the stochastic model used to describe the uncertain evolution of commodity prices can have important implications also in the valuation and risk management of real assets, a realistic commodity price model is a prerequisite for the integrated risk management models outlined in the subsequent chapters of this dissertation.
Given the previously developed intuition for commodity market dynamics, we model the integrated operational and financial risk management problem of a stylized, single-product industrial firm in Chapter 3. The firm faces risk in the price of commodity inputs and price sensitive, stochastic demand. Within this setting, the firm seeks to maximize inter-temporal utility under downside risk aversion over a multi-period time horizon by dynamically choosing physical procurement volumes, unit selling prices, and a futures hedge. We provide a flexible, simulation-based optimization algorithm, which allows us to solve the firm’s decision problem under realistic, multi-factor commodity price dynamics involving uncertainty in the interest rate and convenience yield as well as stochastic volatility. Based on this model, we characterize the firm’s optimal operating policy and investigate a range of topics including: (a) the value of managerial flexibility and the economic cost of restrictive supply contracts; (b) the importance of accounting for the stochastic nature of costs, interest rates, convenience yields, and volatility in risk management; (c) parameter and estimation risk; (d) the impact of risk aversion and hedging on the distribution of cash flows; and (e) the sensitivity of expected performance to key input parameters.
As opposed to the case of a single-product firm, integrated procurement risk management in a large, multi-divisional organization does not only require the above mentioned cross-functional coordination between, for example, the purchasing, sales, and finance department but also involves a cross-divisional coordination of actions in order to effectively target the firm-wide net risk exposure. To capture the specific aspects of integrated risk management in this type of setting, we extend the above model to a two-product firm in Chapter 4. Within this model, each of the two divisions are subject to cost and demand risk, which can be respectively correlated. Moreover, we allow for dynamic cross-selling to capture the potential complementarity/substitutability of items. The firm has access to futures, call, and put options associated with each of the commodity input markets for financial hedging. Under an intertemporal mean-variance utility function, we are able to provide analytic solutions to the firm’s dynamic procurement, pricing, and financial hedging problem. Based on a complementary numerical study, we analyze the impact of risk correlations and unilateral changes in the market environment of one division on the entire firm. Moreover, we discuss the impact of hedging and risk aversion on optimal policy and assess the effectiveness of different operational and financial hedging strategies for risk reduction.
In many situations, firms have an incentive to charge different prices to different consumers. A price discrimination strategy aims at exploiting differences in consumers' willingness to pay in order to increase the firm's profit. At the same time, consumers often evaluate a purchase transaction with respect to the perceived (un)fairness regarding the terms of the transaction, prices or qualities provided. If consumers are inequity averse to the extent that they care about whether other customers pay a lower relative price per quality, a quality based price discrimination may turn out less profitable than if consumers act selfishly.
The dissertation project analyzes the impact of consumer social preferences on the implementation of different pricing strategies in monopolistic and duopolistic markets. It accounts for asymmetrically distributed information about product quality and emphasizes the optimal signaling strategies in a monopoly. Additionally, quality-based price discrimination is identified as the optimal strategy to eliminate potential competition under perfect information. In the context of third-degree price discrimination, the effect of inequity aversion on quality choices is analyzed.