Studies in newsvendor decision-making have shown that human decisions systematically deviate from analytical solutions found in many utility models of the single period problem (SPP). Yet for the most part the impacts of this human decision bias in systems of newsvendor type products have not been investigated. We study bias in human decision-making to determine how different factors affect the performance of systems of newsvendor type products. We extended the state of the arts utility models of SPP to analyze the effects of individuals wealth on individual decision-making. Our theoretical and empirical results proved that individuals wealth significantly affected individual decision-making. Specifically, our analysis concluded that wealthier individual ordered more than poorer individual did when presented with the same investment opportunity. We created a human decision bias (HDB) model to include different newsvendor ordering policies that individuals could use to determine their order quantities. This model is set up to investigate individuals reliance on different ordering policies under different experimental conditions. We designed multi period newsvendor experiments to study effects of factors such as item profit margin, wealth, value of learning, and salvage value on decision-maker's order quantity. We found that wealth and profit margin factors significantly affected individual newsvendor decision-making. Learning, gender, and salvage value factor did not exhibit significant effects in our empirical studies. We designed multi period multi echelon newsvendor experiments to study effects of factors such as the relationship between newsvendors, item profit margin, and newsvendors' wealth on the performance of two-echelon newsvendors system. We found item profit margin, wealth, and relationship between supplier and retailer to significantly affect newsvendor decision-making. Finally, we present a case study of US fresh produce industry to illustrate the impacts of human decision bias on the performance of a supply chain system.

<p>This thesis studies the allocation of stock in a two-level inventory system with stochastic demand. The system consists of one central warehouse which supplies N non-identical retailers with one single product. Customer demand occurs solely at the retailers and follows independent Poisson processes. The purpose is to investigate the value of using a more advanced allocation policy than First Come-First Serve at the central warehouse. The focus is on evaluating how well the simple First Come-First Serve assumption works in a system where the warehouse has access to real-time point-of-sale data, and where shipments are time based and consolidated for all retailers. The considered allocation policy is a myopic policy where the solution to a minimization problem, formulated as a constrained newsvendor problem, determines how the warehouse allocates its stock to the retailers. The minimization problem is solved using (a heuristic method based on) Lagrangian relaxation, and simulation is used to evaluate the average inventory holding costs and backorder costs per time unit when using the considered policy. The simulation study shows that cost savings around 1-4 percent can be expected for most system configurations. However, there were cases where savings were as high as 5 percent, as well as cases where the policy performed worse than First Come-First Serve. The study also shows that the highest cost savings are found in systems with relatively low demand, few retailers, short transportation times and a short time interval between shipments.</p>

In this thesis we study problems in the context of inventory control and facility location. In chapter 2 we study the competition among risk averse newsvendors. We showed that the well-known result for the single-product monopoly firm, which states higher risk aversion causes the firm to reduce its order quantity, cease to hold under the competition. We concluded that the higher risk aversion does not necessarily cause both firms to reduce their order quantity. We showed that the impact of risk aversion on equilibrium quantities is a trade-off between two effects: (a) Own risk aversion increment which causes that the firm reduces its order quantity and (b) Effect of spillover demand from competitor which causes that the firm increases its order quantity. We also show which firm raises its order quantity as both firms become more risk averse depending on their attributes: profitability ratio (overstocking to understocking ratio), initial risk aversion level and demand characteristic (distribution and substitution). In Chapter 3, we study how the operational decisions of a firm's manager depend on her own incentives, the capital structure, and financial decisions in the context of the newsvendor framework. We showed that in contrast to common practices, tying the manager's compensation to stock price (equity value) may not be optimal for shareholders. We propose to tie the managers' compensation to the firm value or include a debt-like instrument in the compensation package to mitigate the risk taking behaviour of the managers. We also show how the board of directors can modify the compensation structure based on the state of the economy and publicly available information about company's demand. In Chapter 4, we study the effect of risk attitude of decision makers on well-known location problems with uncertain demand. In addition to providing mathematical formulations for those problems, we also discussed how we can solve these problems using linearization techniques. We also shed some light on the importance of considering the volatility and correlation structure. Furthermore, we apply a Bayesian updating method, a useful tool for updating the probability distribution to incorporate the consultants' view about uncertain factors in location problems.

We extend the dual sourcing model based on the newsvendor framework by considering the environmental impact of transport. In our context, dual sourcing means that a company, e.g. a retailer, uses an offshore and an onshore supplier. We include environmental regulations for transport in the model. Firstly, emission taxes for the transport from the offshore source are considered. It can be shown that with increasing emissions taxes the company sources less from offshore. This improves the environmental performance but the economic performance (expected profit) is severely harmed. Secondly, we propose that an emission trading scheme is valid for transport activities. In this case, the optimal policy turns out to be a two-sided control-limit policy. If the emission limit (expressed in product units) is set to the minimal offshore order quantity the environmental impact of transport can be reduced while the economic performance is nearly not affected. Thus, from managerial perspective emission trading is preferred to an emission tax on transport. Also from the perspective of policy-making emission trading is reasonable as it helps to limit the negative environmental impact of transport but does not strongly reduce the competitiveness of individual companies.

Cooperation among humanitarian organizations has attracted increasing attention to enhance effectiveness and efficiency of relief supply chains. Our research focuses on horizontal cooperation in inventory management which is currently implemented in the United Nations Humanitarian Response Depot (UNHRD) network. The present work follows a two-step research approach, which involves collection of empirical data and quantitative modeling to examine and overcome the coordination challenges of the network. Our interviews with members of the network identified several managerial issues for sustainable cooperative inventory management that the UNHRD network pursues. Using a newsvendor model in the context of non-cooperative game theory, our research has explored member humanitarian organizations' incentive of joining the network, a coordination mechanism which achieves system optimality, and impacts of members' decisions about stock rationing. Our results indicate that behaviors of member HOs do not necessarily align with the UNHRD's expectation. Our results suggest that for system optimality, a system coordinator should carefully assess the circumstances, including demand coefficient and stock rationing. Our research also proposes a policy priority for the first-best system optimal inventory management.

The thesis deals with market models with random inputs represented by the newsvendor problem for which the randomness is given through a random number of customers. Presented work is divided into three chapters. In the first chapter we present the elementar newsvendor problem as stochastic programming problem with a fixed recourse. In the second chapter we present the multiplayer game theory adapted to the newsvendors problem. Moreover, in the second chapter we extend the problem by the second newsvendor on the market and in the third chapter we generalize the problem for n newsvendors on the market. We deal with the situations that arise in the chapters two and three from the game theory point of view and we study characteristics of a Nash equilibrium. Presented theory is demonstrated on illustrative examples in the ends of the two last chapters. 1

Inventory control is important to ensuring sufficient quantities of items are available tomeet demands of customers. The Newsvendor problem is a model used in Operations Research to determine optimal inventory levels for fulfilling future demands. Our study extends the newsvendor problem to a food truck problem. We used simulation to show that the food truck does not reduce to a newsvendor problem if demand depends on exogenous factors such temperature, time etc. We formulate the food truck problem as a multi-product multi-period linear program and found the dual for a single item. We use Discrete Event Simulation to solve the stochastic version of the dual and found the optimal order to maximize the food vendors profit.

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The Bertrand Duopoly model for demand in economics is a well-used model. Although this model has important insights towards pricing strategy, it does not accurately depict true market behaviors. In this paper, we will examine the advantages and disadvantages of the current model and its assumptions.We then take a whole new approach towards modeling this phenomena, using Poisson processes to model the demand of goods. We will discuss why this is a better approach and explain how we can extend this to better understand pricing strategies and market dynamics. We then apply our findings to the newsvendor problem, a commonly used problem in inventory management. Using non-homogeneous Poisson processes we explain how to find an optimal pricing strategy and an optimal inventory level for the newsvendor problem.In this paper we explain how to extend the newsvendor problem to a newsvendor duopoly problem. Again we show how to find the optimal pricing strategies and inventory levels for multiple goods in a market. Having found the optimal pricing strategy and inventory level, we then examine the market dynamics in more details. We explore monopolistic and duopolistic markets where the goods range from complements to substitutes and homogeneous to differentiated goods. We discuss how to model the progression of the inventory probabilities and then explain how to price inventory options.

This dissertation is concerned with decision making in retail operations management. Specifically, we focus on pricing, variety, and inventory decisions, which are at the interface of the marketing and operations functions of a retail firm. We consider two problems that relate to two major types of retail goods. First, we study joint pricing, variety, and inventory decisions for a set of substitutable" items that serve the same need for the consumer (commonly referred to as a "retailer's product line"). Second, we present a novel model of a selling strategy for "complementary" items that we refer to as ``convenience tying," and focus on analyzing the effect of this selling strategy on pricing and profitability. We also study inventory decisions under convenience tying and exogenous pricing. For a product line of substitutable items, the retailer's objective is to jointly determine the set of variants to include in her product line ("assortment"), together with their prices and inventory levels, so as to maximize her expected profit. We model the consumer choice process using a multinomial logit choice model and consider a newsvendor type inventory setting. We derive the structure of the optimal assortment for a special case where the non-ascending order of items in mean consumer valuation and the non-descending order of items in unit cost agree. For this special case, we find that an optimal assortment has a limited number of items with the largest values of the mean consumer valuation (equivalently, the items with the smallest values of the unit cost). For the general case, we propose a dominance rule that significantly reduces the number of different subsets to be considered when searching for an optimal assortment. We also present bounds on the optimal prices that can be obtained by solving single variable equations. Finally, we combine several observations from our analytical and numerical study to develop an efficient heuristic procedure, which is shown to perform well on many numerical tests. With the objective of gaining further insights into the structure of the retailer's optimal decisions, we study a special case of the product line problem with "similar items" having equal unit costs and identical reservation price distributions. We also assume that all items in a product line are sold at the same price. We focus on two situations: (i) the assortment size is exogenously fixed, while the retailer jointly determines the pricing and inventory levels of items in her product line; and (ii) the pricing is exogenously set, while the retailer jointly determines the assortment size and inventory levels. We also briefly discuss the joint pricing/variety/inventory problem where the pricing, assortment size, and inventory levels are all decision variables. In the first setting, we characterize the structure of the retailer's optimal pricing and inventory decisions. We then study the effect of limited inventory on the optimal pricing by comparing our results (in the ``risky case" with limited inventory) with the ``riskless case," which assumes infinite inventory levels. In addition, we gain insights on how the optimal price changes with product line variety as well as demand and cost parameters, and show that the behavior of the optimal price in the risky case can be quite different from that in the riskless case. In the second setting, we characterize the retailer's optimal assortment size considering the trade-off between sales revenue and inventory costs. Our stylized model allows us to obtain strong structural and monotonicity results. In particular, we find that the expected profit at optimal inventory levels is unimodal in the assortment size, which implies that the optimal assortment size is finite. By comparison to the riskless case, we find that this finite variety level is due to inventory costs. Finally, for the joint pricing/variety/inventory problem, we find that even when the retailer has control over the price, finite inventories still restrict the variety level. We also propose several bounds that can be useful in solving the joint problem. We then study a convenience tying strategy for two complementary items that we denote by "primary" and "secondary." The retailer sells the primary item in an appropriate department of her store. In addition, to stimulate demand, the secondary item is offered in two locations: its appropriate department and the primary item's department where it is displayed in very close proximity to the primary item. We analyze the profitability of this selling practice by comparing it to the traditional independent components strategy, where the two items are sold independently (each in its own department). We focus on understanding the effect of convenience tying on pricing. We also briefly discuss inventory considerations. First, assuming infinite inventory levels, we show that convenience tying decreases the price of the primary item and adjusts the price of the secondary item up or down depending on its popularity in the primary item's department. We also derive several structural and monotonicity properties of the optimal prices, and provide sufficient conditions for the profitability of convenience tying. Then, under exogenous pricing, we find that convenience tying is profitable only if it generates enough demand to cover the increase in inventory costs due to decentralizing the sales of the secondary item. / Ph. D.