Narrow Results

Following the basic work conducted by Lee et al. [(1997a), The bullwhip effect in supply chains. Sloan Management Review, 38(3), 93–102; (1997b), Information distribution in a supply chain: The bullwhip effect. Management Science, 43(4), 546–558] and using two first-order autoregressive AR(1) models, respectively, this paper provides three quantitative models of the bullwhip effect of the two-level supply chain distribution network consisting of a single manufacturer and two retailers. The paper assumes that two retailers adopt the order point method, uses three kinds of demand forecasting technology, i.e., moving average, exponential smoothing and minimum mean square error methods, respectively, provides three corresponding models for analyzing the impact of bullwhip effect of two-level supply chain distribution network. At the same time, this paper compares and analyzes the results of the three models through simulation.

Over the last decade, collaboration and secure information-sharing (SIS) have been studied in the context of supply chain management (SCM) to determine their influence on improving a business’s performance and profitability. Collaboration refers to the firms working together to accomplish a particular objective, whereas SIS is a vital technology which permits the firms and the enablers of a supply chain to be integrated. In this paper, these aspects and their impacts on SCM are reviewed. A conceptual model with a set of hypotheses for measuring the effects of collaboration and information-sharing on SCs, which demonstrate their effective roles in SCM, is proposed.

Choosing the proper forecasting model is the mainstay of handling with demand variability in supply chain. In this paper, a simple supply chain model simulation consist of a retailer, a wholesaler, a distributor and a factory is used to analyze the demand variability using simple exponential smoothing, fuzzy regression, grey GM(1,1) and fuzzy grey GM(1,1) forecasting models.

One of the pernicious master issues of supply chain is the bullwhip or whiplash effect; i.e. the variability of the demand information between stages of the supply chain and the increase of this variability as the information moves upstream through the chain. In this paper, the reaction of bullwhip effect to grey and fuzzy grey GM(11) forecasting models is analyzed by quantifying the bullwhip effect with variance estimation and Lyapunov exponent using a simple supply chain Matlab simulation (i.e. beer game model) and results derived from the simulation compared with the ones obtained from using selected crisp forecasting model.

The present chapter provides an introductory account of supply chain management area by discussing major channels, information flows, and the main drivers and building blocks of supply chains. The chapter also introduces the decision hierarchy, performance metrics, value of information sharing and bull-whip effect in supply chain management. Finally, the paper provides a set-covering supply chain network design approach to supply chain management and illustrates it with the help of a numerical example.

This paper studies the impact factors and solutions for improving management performance of supply chain inventory control system based on the principles of system dynamics and artificial simulation from the perspective of dynamic complexity. This paper also takes the impact of RFID on the supply chain management into consideration under the context of the Internet of things. We think that “System Structure”, “Control Policy” and “Control Parameters” are three kinds of important factors to affect the performance of supply chain inventory management; and presents the “structural solutions” of adjusting the ordering cycle to match lead time, the “strategic solutions” based on taking the order bill amounts and the goods in transit into account, and the “operational solutions” based on parameter control. Then this paper probes the ways of their influence on the management performance under the condition of centralized control and decentralized control. Results show that the effectiveness of these three solutions on management performance is increasing under the condition of centralized control and is decreasing under the condition of decentralized control in turn. The results further show that the system thinking is important and effective to deal with the dynamic complex systems.