Mathematics in the Supply Chain

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Price Flexibility in Channels of Distribution: Evidence from Scanner Data

In this study, we empirically examine the extent of price rigidity using a unique store-level time series data set - consisting of (i) actual retail transaction prices, (ii) actual wholesale transaction prices which represent both the retailers' costs and the prices received by manufacturers, and (iii) a measure of manufacturers' costs - for twelve goods in two widely used consumer product categories. We simultaneously examine the extent of price rigidity for each of the twelve products at both, final goods and intermediate goods levels. We study two notions of price rigidity employed in the existing literature: (i) the frequency of price changes, and (ii) the response of prices to exogenous cost changes. We find that retail prices exhibit remarkable flexibility in terms of both notions of price rigidity. i.e., they change frequently and they seem to respond quickly and fully to cost changes. Furthermore, we find that retail prices respond not just to their direct costs, but also to the upstream manufacturers' costs, which further reinforces the extent of the retail price flexibility. At the intermediate goods level of the market, in contrast, we find relatively more evidence of rigidity in the response of manufacturers prices to cost changes. This despite the fact that wholesale prices change frequently and therefore exhibit flexibility according to the first notion of price rigidity.Price Flexibility, Price Rigidity, Final Goods Market, Intermediate Goods Market, Stages of Processing, Structural VAR, Scanner Data, Transaction Price Data, Frequency of Price Changes, Price Response to Exogeneous Cost Changes, Retail Price, Wholesale Price, New Keynesian Macroeconomics, How Markets Clear, Time Series Analysis, Orange Juice, Orange Juice Frozen Concentrate, Futures Market

Dynamic Modeling and Analysis for Supply Chain

The objective of this study is to use system dynamics methodology to model the supply chain system and then present the optimal control to optimize the performance of supply chain by minimize the quadratic cost function while tracking and keeping the inventory close to target level. Under the system dynamics point of view, the supply chain was modeled as the continuous differential equation with lead time delay modeled as the first order delay model. In contrast to the frequency domain analysis of the classical control approach, the proposed control utilizes the time-domain state space representation with a set of input, output and state variables to build the dynamic system. On the other hand, by using the system dynamics it allows us to apply different control laws and analyze the dynamic behavior of system so that the decision policies can be found to improve the performance of supply chain. In this paper we employ the linear quadratic optimal control for such kind of supply chain dynamic system, the aim of controller is to find the control input as the order quantity to minimize the cost function and keep high customer satisfaction by tracking the target inventory level. Finally, the numerical simulation results are carried out in Matlab/Simulink environment and the performance of optimal controller will be compared with some classical control policies such as proportional and order-up-to level control policy. It is shown that our approach can obtain some good performances.Chapter 1. Introduction 1 1.1 Background 1 1.2 Motivation of this research 3 1.3 Research objectives 5 Chapter 2. Supply chain management and performance measurements 7 2.1 Supply chain management 7 2.2 Structure of supply chain management 10 2.3 Performance measurement of supply chain management 13 2.4 Process in supply chain management 15 Chapter 3. Dynamic modeling of supply chain 21 3.1 Production model 21 3.2 Transportation model 27 3.3 Distribution model 29 3.4 State-space of supply chain model 30 3.5 Costs function of supply chain 31 Chapter 4. Controller design 33 4.1 State-space model 33 4.2 Linear Quadratic Regular control design 33 4.3 Optimal tracking controller 35 Chapter 5. Simulation results 37 5.1 Demand and control parameters 37 5.2 Simulation results and analysis 38 Chapter 6. Conclusion 44 References 4

Ocean container transport : an underestimated and critical link in global supply chain performance

With supply chains distributed across global markets, ocean container transport now is a critical element of any such supply chain. We identify key characteristics of ocean container transport from a supply chain perspective. We find that unlike continental (road) transport, service offerings tend to be consolidated in few service providers, and a strong focus exists on maximization of capital intensive resources. Based on the characteristics of the ocean container transport supply chain, we list a number of highly relevant and challenging research areas and associated questions

Modeling inventory and responsiveness costs in a supply chain

Evaluation of supply chain performance is often complicated by the various interrelationships that exist within the network of suppliers. Currently many supply chain metrics cannot be analytically determined. Instead, metrics are derived from monitoring historical data, which is commonly referred to as Supply Chain Analytics. With these analytics it is possible to answer questions such as: What is the inventory cost distribution across the chain? What is the actual inventory turnover ratio? What is the cost of demand changes to individual suppliers? However, this approach requires a significant amount of historical data which must be continuously extracted from the associated Enterprise Resources Planning (ERP) system. In this dissertation models are developed for evaluating two Supply Chain metrics, as an alternative to the use of Supply Chain Analytics. First, inventory costs are estimated by supplier in a deterministic (Q , R, δ )2 supply chain. In this arrangement each part has two sequential reorder (R) inventory locations: (i) on the output side of the seller and (ii) on the input side of the buyer. In most cases the inventory policies are not synchronized and as a result the inventory behavior is not easily characterized and tends to exhibit long cycles. This is primarily due to the difference in production rates ( δ), production batch sizes, and the selection of supply order quantities (Q) for logistics convenience. The (Q , R, δ )2 model that is developed is an extension of the joint economic lot size (JELS) model first proposed by Banerjee (1986). JELS is derived as a compromise between the seller\u27s and the buyer\u27s economic lot sizes and therefore attempts to synchronize the supply policy. The (Q , R, δ )2 model is an approximation since it approximates the average inventory behavior across a range of supply cycles. Several supply relationships are considered by capturing the inventory behavior for each supplier in that relationship. For several case studies the joint inventory cost for a supply pair tends to be a stepped convex function. Second, a measure is derived for responsiveness of a supply chain as a function of the expected annual cost of making inventory and production capacity adjustments to account for a series of significant demand change events. Modern supply chains are expected to use changes in production capacity (as opposed to inventory) to react to significant demand changes. Significant demand changes are defined as shifts in market conditions that cannot be buffered by finished product inventory alone and require adjustments in the supply policy. These changes could involve a ± 25% change in the uniform demand level. The research question is what these costs are and how they are being shared within the network of suppliers. The developed measure is applicable in a multi-product supply chain and considers both demand correlations and resource commonality. Finally, the behavior of the two developed metrics is studied as a function of key supply chain parameters (e.g., reorder levels, batch sizes, and demand rate changes). A deterministic simulation model and program was developed for this purpose