The impact of coordination and information on transport procurement

Transport cost is second in importance after production cost in industry. It is the purpose of the present paper to study the impact of information sharing and contractual instruments between a supply chain and its transport suppliers. After reviewing the literature, we propose a model to measure the benefits in terms of transport cost and standard deviation of transport cost. We evaluate three scenarios over one period reiterated for a shipper carrier two-echelon model with a mix of long- term and short-term procurement strategies: perfect information, asymmetric information and private information at one level of the supply chain. We evaluate the transfer in rent between carrier and shipper according to the information known and give some insights on optimal contract parameters.Supply chain management, coordination, contracts, information sharing, game theory, mechanisms

Buy Now and Price Later: Supply Contracts with Time-Consistent Mean-Variance Financial Hedging

We consider a two-stage supply chain comprising one risk-neutral manufacturer (he) and one risk-averse retailer (she), where the manufacturer procures consumption commodities in spot market as major inputs for production and sells the final products to the retailer. The retailer then sells the final products to the market at a stochastic clearance price. We investigate a flexible price contract that allows the manufacturer to determine the product wholesale price, and the retailer to determine the order quantity, based on the future spot price of consumption commodities. Compared with the simple wholesale price contract, a win-win situation can be achieved under the flexible price contract when the manufacturer's postponed processing cost is lower than a threshold. However, under this flexible price contract the retailer may suffer from the commodity price volatility, even if she does not procure the commodities directly. We further investigate how the risk-averse retailer conducts mean-variance financial hedging by purchasing consumption commodity futures contracts. We formulate the problem using a dynamic programming model and derive a closed-form time-consistent financial hedging policy. Through numerical experiments, we show that the commodity price risk from the manufacturer to the retailer is effectively mitigated with the hedging, and the benefits of the flexible price contract are maintained

The Effect of Material Price and Product Demand Correlations on Combined Sourcing and Inventory Management

Both material sourcing and inventory management are important competitiveness factors, and it is a significant challenge to integrate the two areas. In sourcing, combined strategies using long-term contracts and the spot market received increasing attention recently, typically concentrating on the financial effects. However, there is limited research on the consequence of combined sourcing considering both purchasing and inventory effects from an operations point of view. In this paper, we analyze the effect of uncertainty on the combined sourcing decision under stochastic demand and random spot-market-price fluctuations and exploit the benefits of forward buying in periods with low spot-price realizations, but also of intended backordering in case of a high spot price. Since the decision on capacity reservation has to take into account the short-term utilization of each source which in turn depends on the available long-term contract capacity, decision making faces highly complex interactions between long-term and short-term decisions.From finance research, we find scarce evidence that the spot prices of commodities evolve independently over time. Rather, price correlation across time periods is found, and a popular way to describe these price dynamics is to model it as a mean reverting process. Thus, in this contribution we will respectively extend common i.i.d. price models from operations management studies and will additionally consider the effect of correlation between demand and price. In this paper, we provide a managerial analysis showing the effects of demand and spot market price correlations on the optimal procurement policy and provide managerial insights. We model the combined sourcing problem as a stochastic dynamic optimization problem and analyze the optimal procurement strategy by means of stochastic dynamic programming. The behavior of the optimal policy confirmed several previous assumptions, though some interesting and important managerial consequences arise due to demand and price correlations. Based on the policy analysis, a numerical study will reveal to which extent inobservance or misspecification of an existing level of correlation might result in performance losses in operational decision making. These observations play an important role under the trend of increasing volatility and dynamic changes on the spot market but also in the customer’s behavior

Selection of Wood Supply Contracts to Reduce Cost in the Presence of Risks in Procurement Planning

Les activités d'achat dans l'industrie des pâtes et papiers représentent une part importante du coût global de la chaîne d'approvisionnement. Les décideurs prévoient l'approvisionnement en bois requis jusqu'à un an à l'avance afin de garantir le volume d'approvisionnement pour le processus de production en continu dans leur usine. Des contrats réguliers, flexibles et d'options avec des fournisseurs de différents groupes sont disponibles. Les fournisseurs sont regroupés en fonction de caractéristiques communes, telles que la propriété des terres forestières. Cependant, lors de l'exécution du plan, des risques affectent les opérations d'approvisionnement. Si les risques ne sont pas intégrés dans le processus de planification des achats, l'atténuation de leur impact sera generalement coûteuse et compliquée. Des contrats ad hoc coûteux supplémentaires pourraient être nécessaires pour compenser le manque de livraisons. Pour aborder ce problème dans cette thèse, dans un premier projet, un modèle mathématique déterministe des opérations d'approvisionnement est développé. L'objectif du modèle est de proposer un plan d'approvisionnement annuel pour minimiser le coût total des opérations relatives. Les opérations sont soumises à des contraintes telles qu’une proportion minimale de l'offre par chaque groupe de fournisseurs, des niveaux cibles des stocks, de la satisfaction de la demande, la capacité par la cour à bois et la capacité du procédé de mise en copeaux. Les décisions sont liées à la sélection des contrats d'approvisionnement, à l'ouverture de cour à bois et aux flux du bois. Dans un deuxième projet, une évaluation du plan d'approvisionnement à partir du modèle déterministe du premier projet est effectuée en utilisant une approche de simulation Monte Carlo. Trois stratégies contractuelles différentes sont comparées : fixes, flexibles et une combinaison des deux types des contrats. L'approche de simulation de ce projet évalue la performance du plan par la valeur attendue et la variabilité du coût total, lorsque le plan est exécuté pendant l'horizon de planification. Dans un troisième projet, une approche de programmation stochastique en deux étapes est utilisée pour fournir un plan d'approvisionnement fiable. L'objectif du modèle est de minimiser le coût prévu du plan d'approvisionnement en présence de différents scénarios générés en fonction des risques. Les décisions lors de la première étape sont la sélection des contrats dans la première période et l'ouverture des cours à bois. Les décisions de la deuxième étape concernent la sélection des contrats commençant après la première période, les flux, l'inventaire et la production du procédé de la mise en copeaux. iii L'étude de cas utilisée dans cette thèse est inspirée par Domtar, une entreprise des pâtes et papiers située au Québec, Canada. Les résultats des trois projets de cette thèse aident les décideurs à réduire les contraintes humaines liées à la planification complexe des achats. Les modèles mathématiques développés fournissent une base pour l'évaluation de la stratégie d'approvisionnement sélectionnée. Cette tâche est presque impossible avec les approches actuelles de l'entreprise, car les évaluations nécessitent la formulation de risques d'approvisionnement. L'approche de programmation stochastique montre de meilleurs résultats financiers par rapport à la planification déterministe, avec une faible variabilité dans l'atténuation de l'impact des risques.Procurement activities in the pulp and paper industry account for an important part of the overall supply chain cost. Procurement decision-makers plan for the required wood supply up to one year in advance to guarantee the supply volume for the continuous production process at their mill. Regular, flexible and option contracts with suppliers in different groups are available. Suppliers are grouped based on common characteristics such as forestland ownership. However, during the execution of the plan, sourcing risks affect procurement operations. If risks are not integrated into the procurement planning process, mitigating their impact is likely to be expensive and complicated. Additional expensive ad hoc contracts might be required to compensate for the lack of deliveries. To tackle this problem, the first project of this thesis demonstrates the development of a deterministic mathematical model of procurement operations. The objective of the model is to propose an annual procurement plan to minimize the total cost of procurement operations. The operations are subject to constraints such as the minimum share of supply for each group of suppliers, inventory target levels, demand, woodyard capacity, and chipping process capacity. The decisions are related to the selection of sourcing contracts, woodyards opening, and wood supply flow. In the second project, an evaluation of the procurement plan from the deterministic model from project one is performed by using a Monte Carlo simulation approach. Three different strategies are compared as fixed, flexible, and a mix of both contracts. The simulation approach in this project evaluates the performance of the plan by the expected value and variability of the total cost when the plan is executed during the planning horizon. In the third project, a two-stage stochastic programming approach is used to provide a reliable procurement plan. The objective of the model is to minimize the expected cost of the procurement plan in the presence of different scenarios generated based on sourcing risks. First-stage decisions are the selection of contracts in the first period and the opening of woodyards. Second-stage decisions concern the selection of contracts starting after the first period, flow, inventory, and chipping process production. The case study used in this thesis was inspired by Domtar, which is a pulp and paper company located in Quebec, Canada. The results of three projects in this doctoral dissertation support decision-makers to reduce the human limitation in performing complicated procurement planning. The developed mathematical models provide a basis to evaluate the selected procurement strategy. This task is nearly impossible with current approaches in the company, as the evaluations require the formulation of v sourcing risks. The stochastic programming approach shows better financial results comparing to deterministic planning, with low variability in mitigating the impact of risks

Copper and the negative price of storage

Commodities are often stored during periods in which storage returns a negative price. Further, during periods of"backwardation,"the expected revenue from holding inventories will be negative. Since the 1930s, the negative price of storage has been attributed to an offsetting"convenience yield."It has been argued that inventories are a necessary adjunct to business and that increasing inventories from some minimal level reduces overall costs. This theory has always been criticized by proponents of cost-of-carry models, who argue that a negative price for storage creates arbitrage opportunities. Proponents of the cost-of-carry model have asserted that storage will occur only with positive returns. They offer a set of price-arbitrage conditions that associate negative returns with stockouts. Still, stockouts are rare in commodity markets, and storage appears to take place during periods of"backwardation"in apparent violation of the price-arbitrage conditions. For copper, inventories have always been available to the market regardless of the price of storage. The author argues that although inventories may provide a cost-reducing convenience yield, inventories also have value because of uncertainty. Just as the price of a call option contains a premium based on price variability, so the shadow price of inventories contains a dispersion premium associated with the unplanned component of inventories. The author derives a generalized price-arbitrage condition in which either a convenience and/or a dispersion premium may justify inventory holding even during an expected price fall. He uses monthly observations of U.S. producer inventories to estimate the parameters of the price-arbitrage condition. The estimates and simulations he presents are ambiguous with regard to the existence of a convenience yield but strongly support the notion of a dispersion premium for copper. And although the average value of such a premium is low, the value of the premium increases rapidly during periods when inventories are scarce.Environmental Economics&Policies,Common Carriers Industry,Markets and Market Access,Access to Markets,Economic Theory&Research

Combining Spot and Futures Markets: A Hybrid Market Approach to Dynamic Spectrum Access

Dynamic spectrum access is a new paradigm of secondary spectrum utilization and sharing. It allows unlicensed secondary users (SUs) to exploit opportunistically the under-utilized licensed spectrum. Market mechanism is a widely-used promising means to regulate the consuming behaviours of users and, hence, achieves the efficient allocation and consumption of limited resources. In this paper, we propose and study a hybrid secondary spectrum market consisting of both the futures market and the spot market, in which SUs (buyers) purchase under-utilized licensed spectrum from a spectrum regulator, either through predefined contracts via the futures market, or through spot transactions via the spot market. We focus on the optimal spectrum allocation among SUs in an exogenous hybrid market that maximizes the secondary spectrum utilization efficiency. The problem is challenging due to the stochasticity and asymmetry of network information. To solve this problem, we first derive an off-line optimal allocation policy that maximizes the ex-ante expected spectrum utilization efficiency based on the stochastic distribution of network information. We then propose an on-line VickreyCClarkeCGroves (VCG) auction that determines the real-time allocation and pricing of every spectrum based on the realized network information and the pre-derived off-line policy. We further show that with the spatial frequency reuse, the proposed VCG auction is NP-hard; hence, it is not suitable for on-line implementation, especially in a large-scale market. To this end, we propose a heuristics approach based on an on-line VCG-like mechanism with polynomial-time complexity, and further characterize the corresponding performance loss bound analytically. We finally provide extensive numerical results to evaluate the performance of the proposed solutions.Comment: This manuscript is the complete technical report for the journal version published in INFORMS Operations Researc