A single buyer-single supplier bargaining problem with asymmetric information : theoretical approach and software implementation

This paper is focused on the coordination of order and production policy between buyers and suppliers in supply chains. When a buyer and a supplier of an item work independently, the buyer will place orders based on his economic order quantity (EOQ). However, the buyer s EOQ may not lead to an optimal policy for the supplier. It can be shown that a cooperative batching policy can reduce total cost significantly. Should the buyer have the more powerful position to enforce his EOQ on the supplier, then no incentive exists for him to deviate from his EOQ in order to choose a cooperative batching policy. To provide an incentive to order in quantities suitable to the supplier, the supplier could offer a side payment. One critical assumption made throughout in the literature dealing with incentive schemes to influence buyer s ordering policy is that the supplier has complete information regarding buyer s cost structure. However, this assumption is far from realistic. As a consequence, the buyer has no incentive to report truthfully on his cost structure. Moreover there is an incentive to overstate the total relevant cost in order to obtain as high a side payment as possible. This paper provides a bargaining model with asymmetric information about the buyer s cost structure assuming that the buyer has the bargaining power to enforce his EOQ on the supplier in case of a break-down in negotiations. An algorithm for the determination of an optimal set of contracts which are specifically designed for different cost structures of the buyer, assumed by the supplier, will be presented. This algorithm was implemented in a software application, that supports the supplier in determining the optimal set of contracts

Setup Cost Reduction and Supply Chain Coordination in Case of Asymmetric Information

Screening contracts are a common approach to solve supply chain coordination problems under asymmetric information. Previous research in this area shows that asymmetric information leads to supply chain coordination deficits. We extend the standard framework of lotsizing decisions under asymmetric information by allowing investments in setup cost reduction. We find that asymmetric information leads to an overinvestment in setup cost reduction. Yet, the overall effect on supply chain performance is ambiguous. We show that these results holds for a wide variety of investment functions.

Think Local-Act Local: Is It Time to Slow Down the Accelerated Move to Global Marketing?

In view of the accelerated move of great corporations towards global marketing, the strategic changes of such companies raise interesting questions. Is marketing globalization reaching its limits after years of implementation? Is it time for companies to rethink their strategies and move back, like Coca-Cola, to a multi-domestic marketing approach?Global Marketing, Multi-Domestic Marketing Approach, Brand Equity, Drawbacks of Marketing Globalization, Coca-Cola

Innovation in Marketing Channels

In more recent years, the context of globalization in which market channel structures and strategies are developing is bringing to a more complex concept of marketing channels, with disintermediation or reintermediation, multichanneling and new roles/specializations that are emerging as new issues.In this context, innovation in marketing channels becomes a complex, multiorganizational, multidisciplinary activity that requires collaboration and interactions across various entities within the supply chain network. In recent years, the innovation processes in marketing channels have occurred with high intensity and speed, especially following the changes spurred by technology that allowed the adoption of more efficient organizational solutions.Retail; Channel Structure; Innovation in Marketing Channels; Retail Technological Innovation; Global Markets

Supply Chain

Traditionally supply chain management has meant factories, assembly lines, warehouses, transportation vehicles, and time sheets. Modern supply chain management is a highly complex, multidimensional problem set with virtually endless number of variables for optimization. An Internet enabled supply chain may have just-in-time delivery, precise inventory visibility, and up-to-the-minute distribution-tracking capabilities. Technology advances have enabled supply chains to become strategic weapons that can help avoid disasters, lower costs, and make money. From internal enterprise processes to external business transactions with suppliers, transporters, channels and end-users marks the wide range of challenges researchers have to handle. The aim of this book is at revealing and illustrating this diversity in terms of scientific and theoretical fundamentals, prevailing concepts as well as current practical applications

Coordination of supply chain inventory systems with private information

This dissertation considers the problems of coordinating different supply chain inventory systems with private information under deterministic settings. These systems studied are characterized by the following properties: (a) each facility in the system has self decision-making authority, (b) cost parameters of each facility are regarded as private information that no other facilities in the system have access to, and (c) partial information is shared among the facilities. Because of the above properties, the existing approaches for systems with global information may not be applicable. Thus, new approaches for coordinating supply chain inventory systems with private information are needed. This dissertation first studies two two-echelon distribution inventory systems. Heuristics for finding the replenishment policy of each facility are developed under global information environment. In turn, the heuristics are modified to solve the problems with private information. An important characteristic of the heuristics developed for the private information environment is that they provide the same solutions as their global information counterpart. Then, more complex multi-echelon serial and assembly supply chain inventory systems with private information are studied. The solution approach decomposes the problem into separate subproblems such that the private information is divided as required. Global optimality is sought with an iterative procedure in which the subproblems negotiate the material flows between facilities. At the core of the solution procedure is a node-model that represents a facility and its corresponding private information. Using the node-model as a building block, other supply chains can be formed by linking the node-models according to the product and information flows. By computational experiments, the effect of the private information on the performance of the supply chain is tested by comparing the proposed approach against existing heuristics that utilize global information. Experimental results show that the proposed approach provides comparable results as those of the existing heuristics with global information

Optimizing replenishment order quantities in uncoordinated supply chains

Many modern supply chains can be described as a series of uncoordinated suppliers. That is each supplier establishes their individual inventory and production policies on both the input and output sides. In these supply links there is minimal coordination between suppliers, and typically only prices and delivery guarantees are contracted. As a consequence, the inventory behavior and associated costs do not exhibit standard patterns. This makes it difficult to model and optimize these chains using classical inventory models. The common approach, therefore, for evaluating uncoordinated supply chains is to use Supply Chain Analytics software. These retrieve operational data from Enterprise Resource Planning (ERP) systems and then characterize the historical inventory performance behavior. Nearier (2008) developed a joint production inventory model for estimating inventory costs in uncoordinated chains as an alternative to supply chain analytics. They proposed a (Q, R, δ)2 relationship between each pair of sequential suppliers, where Q is the order quantity, R is the reorder level, and δ is the production or consumption rate. In this arrangement each part has two inventory locations: (i) on the output side of the seller, and (ii) on the input side of the buyer. hi this dissertation, the (Q, R, δ)2 model was extended. Three specific research tasks were accomplished in this regard. First, the inventory estimation accuracy of the original (Q, R, δ)2 model was improved. This was accomplished by deriving a more reliable estimate of the residual inventory at the end of each supply cycle. Further, a more accurate model of the inventory behavior in supply cycles where the seller has no production was developed. A discrete inventory simulation was used to demonstrate a significant improvement in the estimation accuracy, from a 10-30 % error range to within 5% error on average. Second, a prescriptive model for deriving the optimal Q when reducing inventory costs in a (Q, R, δ)2supply relationship was developed. From simulation studies, it was found that due to differences in production batch sizes, production rates, and replenishment order quantities, the inventory cost function exhibits a non-differentiable step-wise convex behavior. Further, the steps are observed to occur at integer ratios of Q and the buyer\u27s production batch. This behavior makes it difficult to analytically derive the optimal Q, which could occur at one of the step points or any intermediate point. A golden section based search heuristic for efficiently deriving the optimal Q was developed. Third, the robustness of Q to demand shifts was studied. A demand shift occurs wherever the mean demand jumps to a higher or lower level, similar to a moving average forecast. The demand shift range beyond, which there is significant deterioration in inventory costs and a change in the supply policy Q is justified, was determined Two supply policies were studied: (i) fixed delivery batch and (ii) fixed production period. For each stochastic demand shift behavior, a delivery batch size or production period that minimizes the total cost of both suppliers is selected

Quantitative analysis of multi-periodic supply chain contracts with options via stochastic programming

We propose a stochastic programming approach for quantitative analysis of supply contracts, involving flexibility, between a buyer and a supplier, in a supply chain framework. Specifically, we consider the case of multi-periodic contracts in the face of correlated demands. To design such contracts, one has to estimate the savings or costs induced for both parties, as well as the optimal orders and commitments. We show how to model the stochastic process of the demand and the decision problem for both parties using the algebraic modeling language AMPL. The resulting linear programs are solved with a commercial linear programming solver; we compute the economic performance of these contracts, giving evidence that this methodology allows to gain insight into realistic problems.stochastic programming; supply contract; linear programming; modeling software; decision tree

Cooperation in Supply Chain Networks: Motives, Outcomes, and Barriers

This paper analyzes the phenomenon of cooperation in modern supply chains in the light of Game Theory. We first provide a discussion on the meaning of cooperation in supply chains, its motives, outcomes and barriers. We then highlighted the applicability of Cooperative Game Theory as methodology for analyzing cooperation in supply chains. Second, we review recent studies that analyze the cooperation in supply chains by means of cooperative game theory. A special emphasis will be given inventory centralizations games. Finally, gaps in the literature are identified to clarify and to suggest future research opportunities