<p>This dissertation consists of three chapters relating to dynamic demand models of storable goods and their application to taxes that are imposed on soft drinks. Broadly speaking, the first chapter builds the estimation strategy for dynamic demand models of storable goods that allows for unobservable heterogeneous preferences in household's tastes. The second chapter uses the estimation strategy developed in the first chapter to study the policy implications of taxes that are imposed on sugary soft drinks. The last chapter explores and provides an explanation for the level of pass-through for soda taxes. </p><p>To be more specific, the first chapter develops techniques for incorporating systematic brand preferences in dynamic demand models of storable goods. Dynamic demand models are important for correctly measuring price elasticities of products that can be stockpiled. However, most of the literature excludes systematic preferences over consumers' brand tastes. This chapter resolves this issue by incorporating random coefficient Logit models into a dynamic demand framework and hence allows for realistic demand substitution patterns. It builds on Hendel and Nevo's 2006 Econometrica paper, where the authors introduce a model of dynamic demand that flexibly incorporates observable heterogeneity and estimates it via a three-step procedure that separates brand and volume choices. While a powerful tool, this method is tricky to execute. Therefore, this chapter also discusses the difficulties that may face implementers.</p><p>The second chapter predicts the effects of taxes on sugar sweetened soft drinks (sugar taxes) on both total consumption and the welfare of different types of consumers. It specifies and estimates a structural dynamic demand model of storable goods with rational and forward-looking households. It flexibly incorporates persistent heterogeneous consumer preferences and develops a computationally attractive method for estimating its parameters. Sugar taxes have been proposed at both the national and state-level, and passed in three states, as a means of slowing or reversing the growth in obesity and diabetes. To accurately analyze the effects of these policies, this chapter takes two specific aspects of soft drinks into account: storability and differentiation. It compares the results from this model to two benchmark studies: a static model with consumer heterogeneity and a dynamic model without households' persistent heterogeneous tastes. It finds that failing to account for dynamics (i.e. storability) results in overestimated reduction in consumption and failing to account for persistent heterogeneous preferences (i.e. differentiation) results in overestimated reduction in consumption and underestimated welfare loss. The model and method developed here are readily applicable to many studies involving storable goods, such as firms' optimal pricing behavior and anti-trust policies analyses.</p><p>The third and last chapter focuses on the incidence of soda taxes by studying the pass-through level of these taxes. It lays out a framework for thinking about the determinants of the pass-through level. More specifically, it builds theoretical models that examine the pass-through under more complex supply structures with multiple manufactures and retailers. In addition to providing some intuition behind theoretical predictions of the models, this chapter also presents empirical results found in the data along with their implications.</p> / Dissertation

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Coordinated lot sizing problems, which assume a joint setup is shared by a product family, are commonly encountered in supply chain contexts. Total system costs include a joint set-up charge each time period any item in the product family is replenished, an item set-up cost for each item replenished in each time period, and inventory holding costs. Silver (1979) and subsequent researchers note the occurrence of coordinated replenishment problems within manufacturing, procurement, and transportation contexts. Due to their mathematical complexity and importance in industry, coordinated lot-size problems are frequently studied in the operations management literature. In this research, we address both uncapacitated and capacitated variants of the problem. For each variant we propose new problem formulations, one or more construction heuristics, and a simulated annealing metaheuristic (SAM). We first propose new tight mathematical formulations for the uncapacitated problem and document their improved computational efficiency over earlier models. We then develop two forward-pass heuristics, a two-phase heuristic, and SAM to solve the uncapacitated version of the problem. The two-phase and SAM find solutions with an average optimality gap of 0.56% and 0.2% respectively. The corresponding average computational requirements are less than 0.05 and 0.18 CPU seconds. Next, we propose tight mathematical formulations for the capacitated problem and evaluate their performance against existing approaches. We then extend the two-phase heuristic to solve this more general capacitated version. We further embed the six-phase heuristic in a SAM framework, which improves heuristic performance at minimal additional computational expense. The metaheuristic finds solutions with an average optimality gap of 0.43% and within an average time of 0.25 CPU seconds. This represents an improvement over those reported in the literature. Overall the heuristics provide a general approach to the dynamic demand lot-size problem that is capable of being applied as a stand-alone solver, an algorithm embedded with supply chain planning software, or as an upper-bounding procedure within an optimization based algorithm. Finally, this research investigates the performance of alternative coordinated lotsizing procedures when implemented in a rolling schedule environment. We find the perturbation metaheuristic to be the most suitable heuristic for implementation in rolling schedules.

This study is about an integrated procurement and transportation planning system for purchased components of a consumer-durables manufacturer. Due to transportation cost structures and demand characteristics our problem can be classified as a variant of the dynamic-demand joint replenishment problem. The problem is to determine the replenishment policy using the advantages of coordinated transportation of items that will minimize the sum of total inventory holding and tranportation costs over a finite planning horizon. A mathematical model is formulated for purchasing and transportation decisions for the purchased items using the advantage of joint transportation costs. A two-phased solution method is proposed in order to obtain a &ldquo / good solution&rdquo / for the problem. The proposed solution method is compared with the current practice for different problem instances using retrospective data and created data. As a result it is shown that proposed method decrease the total inventory and transportation cost of the system even though the first aggregate problem can not be solved to optimality.

This thesis is divided into two parts. Part I deals with demand management. For goods with no substitutes, under supply constraints, fairness considerations introduce negative externalities and lead to a market failure. One example of such a good with no substitutes is water. In case of a market failure, it is necessary to design coordination mechanisms called contracts which provide the right incentives for coordination. As “repetition can yield coordination”, the aim in this part is to design price based dynamic demand management contracts which, under supply constraints, mitigate the market failure. In these contracts, we consider complete information settings; and use the status quo proposition as a fairness criterion for designing them. The contracts are designed as almost noncooperative dynamic games, within the agency theory framework, where the agent (the consumer) is induced to consume at a specified consumption level based on the incentive mechanism offered by the principal (the producer). These contracts use the solution concept of sub-game perfect Nash equilibrium (SPNE) to compute the price (mal-incentive) that acts as a credible threat for deviation from the specified consumption level. In these contracts, unlike the dynamic contracts with asymmetric information, the penalty for deviation is proportional to the amount of deviation. First, we consider a two-period demand management contract for a single consumer satisfying the status quo proposition. Under the assumption that the gain to the consumer and the loss to the producer by deviation is small, the contract is shown to be economically efficient. It is shown that, in the finite horizon, a fair demand management contract cannot be efficient. The demand management contract is homeomorphic to finite horizon alternating bargaining model. In the finite horizon alternating bargaining model, there is a unique SPNE, in which the player who offers last is always at an advantageous position. In the two-period contract, the assumption considered attenuates the last mover advantage and leads to the efficiency. We have shown that one possible way to achieve efficiency, without the assumption, is to make the agents uncertain about the period of interaction. This possibility can be included in an infinite horizon contract. Hence, next, we design an infinite horizon contract for a single consumer. It is proved that this contract is economically efficient and provides revenue sufficiency. The sensitivity analysis of the contract shows that the discounting rate measures the aversion to conservation characteristics of the consumer. The analysis of the contract shows that a sufficiently time-patient consumer is not penalized for the deviation, as the consumer himself is aware of conservation requirements. This result is similar to the results for the present-biased preferences in behavioral economics. Lastly, the infinite horizon contract is extended to two consumers case which internalizes the externality a consumer causes to another. In the two consumer case, consumers are strategically noninteracting; and it is shown that the producer acts as a budget balancer. These contracts are also shown to be economically efficient. The demand management contracts achieve both the procedural and end-state fairness. Also, the infinite horizon contracts are homeomorphic to infinite horizon alternating bargaining model. The efficiency of infinite horizon contracts is due to their homeomorphism with the alternating bargaining process as they exhaust all possible mutual gains from exchange. In the two-period model, the bargaining process is constrained and hence all possible mutual gains are not eliminated, leading to the inefficiency. In part II of the thesis, we discuss the notions of exchangeability in the Shapley value. The Shapley value is a probabilistic value for the transferable utility (TU) cooperative games, in which each player subjectively assigns probabilities to the events which define their positions in the game. In this part, the objective have been to explore the aspect of subjective probability which leads to the uniqueness of the Shapley value. This aspect of subjective probability is known as exchangeability. We derive the Shapley value using de Finetti’s theorem. We also show that, in the Shapley value, each player’s prospects of joining a t-player game as the last member of the game is a moment sequence of the uniquely determined uniform distribution. We stress on finite exchangeability; and deduce that, with finite exchangeability, the Shapley value is the only value in which the probability assignment is a unique mixture of independent and identical distributions. It is concluded that, in both the finite and infinite exchangeable cases, the uniqueness of probability assignment in the Shapley value is due to exchangeability and the mixing with the uniform distribution.

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[pt] Os sistemas metroviários desempenham um importante papel no transporte de passageiros nos grandes centros urbanos por sua alta capacidade de transporte, seu baixo índice poluente e por serem relativamente livres de congestionamentos. O headway - intervalo entre os trens – é uma importante variável no planejamento do serviço pois influencia na capacidade oferecida e no custo de operação. Este trabalho desenvolve um modelo de simulação de eventos discretos aplicado na análise da estrutura, capacidade e funcionamento da Linha 4 do sistema metroviário do Rio de Janeiro, sendo realizados experimentos com diferentes tempos de headway de forma a medir e avaliar o desempenho do sistema no atendimento à demanda prevista. Desenvolve-se um modelo de programação linear inteira mista (MIP) com o objetivo de encontrar valores ótimos de headway para a sua operação. Os modelos consideram as restrições de capacidade dos trens, tempos de deslocamento e a demanda dinâmica dos passageiros em cada estação. São utilizados dados do Estudo de Demanda para a Linha 4 (FGV, 2011) com a previsão de demanda para o período de pico da manhã do ano de 2016. O trabalho permite concluir que o dimensionamento da capacidade da Linha 4 do metrô atende com eficiência a demanda projetada para o ano de 2016 e que os modelos de simulação e otimização desenvolvidos podem ser adaptados e utilizados no apoio ao planejamento e operação de outros sistemas metroviários. / [en] Subway systems play an important role in passenger transportation in large urban centers due to their high transport capacity, low pollutant content and for being relatively free of traffic congestion. The headway - intervals between trains – is an important variable in service planning because it influences the capacity offered and cost of operation. This work develops a discrete event simulation model applied in the analysis of the structure, capacity and operation of Line 4 of the Rio de Janeiro subway system. Experiments with different headway times are performed in order to measure and evaluate the system performance in meeting the forecasted demand. A mixed integer linear programming model (MIP) is developed in order to find optimal headway values for its operation. The models consider the train capacity constraints, travel times contrainsts and the dynamic passenger demand at each station. Data from the Demand Study for Line 4 (FGV, 2011) are used with the demand forecast for the morning peak period of 2016. The work allows to conclude that the dimensioning of the capacity of the subway Line 4 efficiently meets the projected demand for the year 2016 and that the simulation and optimization models developed can be adapted and used to support the planning and operation of other metro systems.

To handle uncertainties and variabilities in production demands, many manufacturing companies have adopted different strategies, such as varying quoted lead time, rejecting orders, increasing stock or inventory levels, and implementing volume flexibility. Make-to-stock (MTS) systems are designed to offer zero lead time by providing an inventory buffer for the organizations, but they are costly and involve risks such as obsolescence and wasted expenditures. The main concern of make-to-order (MTO) systems is eliminating inventories and reducing the non-value-added processes and wastes; however, these systems are based on the assumption that the manufacturing environments and customers' demand are deterministic. Research shows that in MTO systems variability and uncertainty in the demand levels causes instability in the production flow, resulting in congestion in the production flow, long lead times, and low throughput. Neither strategy is wholly satisfactory. A new alternative approach, multi-channel manufacturing (MCM) systems are designed to manage uncertainties and variabilities in demands by first focusing on customers' response time. The products are divided into different product families, each with its own manufacturing stream or sub-factory. MCM also allocates the production capacity needed in each sub-factory to produce each product family. In this research, the performance of an MCM system is studied by implementing MCM in a real case scenario from textile industry modeled via discrete event simulation. MTS and MTO systems are implemented for the same case scenario and the results are studied and compared. The variables of interest for this research are the throughput of products, the level of on-time deliveries, and the inventory level. The results conducted from the simulation experiments favor the simulated MCM system for all mentioned criteria. Further research activities, such as applying MCM to different manufacturing contexts, is highly recommended.