In this thesis we analyze optimal demand management policies for stochastic systems. In the first system considered, a manufacturer decides how to manage demand from customers that differ in their priority level and willingness to pay. He has limited production capacity and predetermined prices throughout the horizon. We find an optimal production and inventory strategy that rations current and future limited capacity between customer classes through reserving inventory for the future and accepting orders now for future delivery. Next, we extend these results to the case when the customers have different tolerance to delayed fulfillment, namely, first-class customers never accept backlogging whereas second-class customers agree to wait one period for a discount. We find an optimal policy similar to the production and inventory strategy that is used for the first system based on threshold values. The third system considers a firm whose recent performance in meeting quoted leadtimes affects future demand arrivals. We assume that the probability of a customer placing an order depends on the quoted leadtime, and both customer arrivals and processing times are stochastic. When capacity of the firm is infinite, we find the optimal leadtime to quote, and when capacity is finite and leadtime is industry-dictated, we determine that the optimal demand acceptance policy does not necessarily have a nice structure. We comment on the structure of the optimal policy for a special case and develop several heuristics for the general case. The final system considered in this thesis is the Sports and Entertainment industry, where demand is managed for a season of several performances by selling season tickets initially and single events later in the selling horizon. We specifically study the optimal time to switch between these market segments dynamically as a function of the state of the system and show that the optimal switching time is a set of time thresholds that depend on the remaining inventory and time left in the horizon.

<p>We were assigned to do this master thesis by Husqvarna AB who at the time for this thesis just had implemented a new material and production planning system called Replenishment system. Husqvarna AB wanted us to examine the effects of their new planning system to see if it was profitable or not. Husqvarna AB had for a time considered their delivery and supplier service to bee their biggest problem and they wanted to solve this problem by improving the communication with all involved actors in the logistic chain, which they hoped would result in a better mix of products in their warehouses. The aim of this report was therefor to analyze eventual effects for Husqvarna AB when changing from a traditional material- and production planing system to a more information intensive one. The result of this report showed effects on decreasing administrational routines and improved flexibility and lead-times. An increased information exchange and thereby a closer market control also improves the chances of a correct mix in stock which improves the lead-time to customer as the"correct"parts is in stock. These improvements must offcurse be considered together with the increased number of transports and the cost of the implementation in the organization.</p>

We were assigned to do this master thesis by Husqvarna AB who at the time for this thesis just had implemented a new material and production planning system called Replenishment system. Husqvarna AB wanted us to examine the effects of their new planning system to see if it was profitable or not. Husqvarna AB had for a time considered their delivery and supplier service to bee their biggest problem and they wanted to solve this problem by improving the communication with all involved actors in the logistic chain, which they hoped would result in a better mix of products in their warehouses. The aim of this report was therefor to analyze eventual effects for Husqvarna AB when changing from a traditional material- and production planing system to a more information intensive one. The result of this report showed effects on decreasing administrational routines and improved flexibility and lead-times. An increased information exchange and thereby a closer market control also improves the chances of a correct mix in stock which improves the lead-time to customer as the"correct"parts is in stock. These improvements must offcurse be considered together with the increased number of transports and the cost of the implementation in the organization.

In this dissertation, we study the interplay between a firm’s operations strategy, with regard to its capacity management, and its marketing decision of product differentiation. For this, we study a market comprising heterogeneous customers who differ in their preferences for time and price. Time sensitive customers are willing to pay a price premium for a shorter delivery time, while price sensitive customers are willing to accept a longer delivery time in return for a lower price. Firms exploit this heterogeneity in customers’ preferences, and offer a menu of products/services that differ only in their guaranteed delivery times and prices. From demand perspective, when customers are allowed to self-select according to their preferences, different products act as substitutes, affecting each other’s demand. Customized product for each segment, on the other hand, results in independent demand for each product. On the supply side, a firm may either share the same processing capacity to serve the two market segments, or may dicate capacity for each segment. Our objective is to understand the interaction between product substitution and the firm’s operations strategy (dedicated versus shared capacity), and how they shape the optimal product differentiation strategy. To address the above issue, we first study this problem for a single monopolist firm, which offers two versions of the same basic product: (i) regular product at a lower price but with a longer delivery time, and (ii) express product at a higher price but with a shorter delivery time. Demand for each product arrives according to a Poisson process with a rate that depends both on its price and delivery time. In addition, if the products are substitutable, each product’s demand is also influenced by the price and delivery time of the other product. Demands within each category are served on a first-come-first-serve basis. However, customers for express product are always given priority over the other category when they are served using shared resources. There is a standard delivery time for the regular product, and the firm’s objective is to appropriately price the two products and select the express delivery time so as to maximize its profit rate. The firm simultaneously needs to decide its installed processing capacity so as to meet its promised delivery times with a high degree of reliability. While the problem in a dedicated capacity setting is solved analytically, the same becomes very challenging in a shared capacity setting, especially in the absence of an analytical characterization of the delivery time distribution of regular customers in a priority queue. We develop a solution algorithm, using matrix geometric method in a cutting plane framework, to solve the problem numerically in a shared capacity setting. Our study shows that in a highly capacitated system, if the firm decides to move from a dedicated to a shared capacity setting, it will need to offer more differentiated products, whether the products are substitutable or not. In contrast, when customers are allowed to self-select, such that independent products become substitutable, a more homogeneous pricing scheme results. However, the effect of substitution on optimal delivery time differentiation depends on the firm’s capacity strategy and cost, as well as market characteristics. The optimal response to any change in capacity cost also depends on the firm’s operations strategy. In a dedicated capacity scenario, the optimal response to an increase in capacity cost is always to offer more homogeneous prices and delivery times. In a shared capacity setting, it is again optimal to quote more homogeneous delivery times, but increase or decrease the price differentiation depending on whether the status-quo capacity cost is high or low, respectively. We demonstrate that the above results are corroborated by real-life practices, and provide a number of managerial implications in terms of dealing with issues like volatile fuel prices. We further extend our study to a competitive setting with two firms, each of which may either share its processing capacities for the two products, or may dedicate capacity for each product. The demand faced by each firm for a given product now also depends on the price and delivery time quoted for the same product by the other firm. We observe that the qualitative results of a monopolistic setting also extend to a competitive setting. Specifically, in a highly capacitated system, the equilibrium prices and delivery times are such that they result in more differentiated products when both the firms use shared capacities as compared to the scenario when both the firms use dedicated capacities. When the competing firms are asymmetric, they exploit their distinctive characteristics to differentiate their products. Further, the effects of these asymmetries also depend on the capacity strategy used by the competing firms. Our numerical results suggest that the firm with expensive capacity always offers more homogeneous delivery times. However, its decision on how to differentiate its prices depends on the capacity setting of the two firms as well as the actual level of their capacity costs. On the other hand, the firm with a larger market base always offers more differentiated prices as well as delivery times, irrespective of the capacity setting of the competing firms.

In this dissertation, we study the interplay between a firm’s operations strategy, with regard to its capacity management, and its marketing decision of product differentiation. For this, we study a market comprising heterogeneous customers who differ in their preferences for time and price. Time sensitive customers are willing to pay a price premium for a shorter delivery time, while price sensitive customers are willing to accept a longer delivery time in return for a lower price. Firms exploit this heterogeneity in customers’ preferences, and offer a menu of products/services that differ only in their guaranteed delivery times and prices. From demand perspective, when customers are allowed to self-select according to their preferences, different products act as substitutes, affecting each other’s demand. Customized product for each segment, on the other hand, results in independent demand for each product. On the supply side, a firm may either share the same processing capacity to serve the two market segments, or may dicate capacity for each segment. Our objective is to understand the interaction between product substitution and the firm’s operations strategy (dedicated versus shared capacity), and how they shape the optimal product differentiation strategy. To address the above issue, we first study this problem for a single monopolist firm, which offers two versions of the same basic product: (i) regular product at a lower price but with a longer delivery time, and (ii) express product at a higher price but with a shorter delivery time. Demand for each product arrives according to a Poisson process with a rate that depends both on its price and delivery time. In addition, if the products are substitutable, each product’s demand is also influenced by the price and delivery time of the other product. Demands within each category are served on a first-come-first-serve basis. However, customers for express product are always given priority over the other category when they are served using shared resources. There is a standard delivery time for the regular product, and the firm’s objective is to appropriately price the two products and select the express delivery time so as to maximize its profit rate. The firm simultaneously needs to decide its installed processing capacity so as to meet its promised delivery times with a high degree of reliability. While the problem in a dedicated capacity setting is solved analytically, the same becomes very challenging in a shared capacity setting, especially in the absence of an analytical characterization of the delivery time distribution of regular customers in a priority queue. We develop a solution algorithm, using matrix geometric method in a cutting plane framework, to solve the problem numerically in a shared capacity setting. Our study shows that in a highly capacitated system, if the firm decides to move from a dedicated to a shared capacity setting, it will need to offer more differentiated products, whether the products are substitutable or not. In contrast, when customers are allowed to self-select, such that independent products become substitutable, a more homogeneous pricing scheme results. However, the effect of substitution on optimal delivery time differentiation depends on the firm’s capacity strategy and cost, as well as market characteristics. The optimal response to any change in capacity cost also depends on the firm’s operations strategy. In a dedicated capacity scenario, the optimal response to an increase in capacity cost is always to offer more homogeneous prices and delivery times. In a shared capacity setting, it is again optimal to quote more homogeneous delivery times, but increase or decrease the price differentiation depending on whether the status-quo capacity cost is high or low, respectively. We demonstrate that the above results are corroborated by real-life practices, and provide a number of managerial implications in terms of dealing with issues like volatile fuel prices. We further extend our study to a competitive setting with two firms, each of which may either share its processing capacities for the two products, or may dedicate capacity for each product. The demand faced by each firm for a given product now also depends on the price and delivery time quoted for the same product by the other firm. We observe that the qualitative results of a monopolistic setting also extend to a competitive setting. Specifically, in a highly capacitated system, the equilibrium prices and delivery times are such that they result in more differentiated products when both the firms use shared capacities as compared to the scenario when both the firms use dedicated capacities. When the competing firms are asymmetric, they exploit their distinctive characteristics to differentiate their products. Further, the effects of these asymmetries also depend on the capacity strategy used by the competing firms. Our numerical results suggest that the firm with expensive capacity always offers more homogeneous delivery times. However, its decision on how to differentiate its prices depends on the capacity setting of the two firms as well as the actual level of their capacity costs. On the other hand, the firm with a larger market base always offers more differentiated prices as well as delivery times, irrespective of the capacity setting of the competing firms.

In this thesis, we analyze the impact of the decentralization of price and leadtime decisions made by the marketing and production departments, respectively, in a make-to-order firm. We first study a monopoly environment, and find that in the decentralized setting, the total demand generated is larger, leadtimes are longer, quoted prices are lower, and the firm profits are lower as compared to the centralized setting. We show that coordination can be achieved using a transfer price contract with bonus payments, where both departments receive a fraction of the total revenues generated as a bonus payment. In the second study, we extend this work to a duopoly environment, where two firms compete on the basis of their price and leadtime quotes in a common market. We find that under intense price competition, firms may suffer from a decentralized structure, particularly under high flexibility induced by high capacity, where revenue based sales incentives motivate sales/marketing for more aggressive price cuts resulting in eroding margins. We take the parameters of the demand models in the first two studies as constant, while estimating those parameters based on historical data is a very important problem in practice. In the last study of this thesis, we address the challenges encountered in estimating the price sensitivity of customers shifting focus to the passenger travel industry. We explore how to obtain better price elasticity estimates through an empirical study with an emphasis on the endogeneity problem, which arises as a result of the simultaneous determination of supply and demand. We show that if one does not account for endogeneity, price elasticities may induce an upward-sloping demand curve suggesting that high price produces high demand, or may be biased downward to the extent that elastic demand curves are incorrectly classified as inelastic. We show the improvement in price elasticities through an instrumental variable approach.