The Government’s Environment Policy Index Impact on Recycler Behavior in Electronic Products Closed-Loop Supply Chain

We establish the model of multilevel closed-loop supply chain (CLSC) which included raw material supplier, manufacturer, distributor, retailer, and third-party recycler based on system dynamics (SD). Considering factors which influence recycler behavior-environmental policy index and recovery delay, we apply SD software—Vensim—to simulate CLSC model and study recycler behavior’s influence on the entire CLSC through calculating the bullwhip effect of all levels members order rate. Research shows that (1) the larger the environmental policy index, the greater the recycle proportion and the better the effect of weakening retailer’s order rate in forward supply chain, which however, increasingly, strengthen the reverse supply chain bullwhip effect, (2) the shorter the recovery delay, the better the effect of weakening the forward supply chain bullwhip effect and the longer the recovery delay, which increasingly weakens the reverse supply chain bullwhip effect, and (3) the effect of environmental policy index on the bullwhip effect of all levels members order rate is more significant than recovery delay

Introduction to computational mass transfer: with applications to chemical engineering

This book offers an easy-to-understand introduction to the computational mass transfer (CMT) method. On the basis of the contents of the first edition, this new edition is characterized by the following additional materials. It describes the successful application of this method to the simulation of the mass transfer process in a fluidized bed, as well as recent investigations and computing methods for predictions for the multi-component mass transfer process. It also demonstrates the general issues concerning computational methods for simulating the mass transfer of the rising bubble process. This new edition has been reorganized by moving the preparatory materials for Computational Fluid Dynamics (CFD) and Computational Heat Transfer into appendices, additions of new chapters, and including three new appendices on, respectively, generalized representation of the two-equation model for the CMT, derivation of the equilibrium distribution function in the lattice-Boltzmann method, and derivation of the Navier-Stokes equation using the lattice-Boltzmann model. This book is a valuable resource for researchers and graduate students in the fields of computational methodologies for the numerical simulation of fluid dynamics, mass and/or heat transfer involved in separation processes (distillation, absorption, extraction, adsorption etc.), chemical/biochemical reactions, and other related processes.

Introduction to computational mass transfer: with applications to chemical engineering

This book presents a new computational methodology called Computational Mass Transfer (CMT). It offers an approach to rigorously simulating the mass, heat and momentum transfer under turbulent flow conditions with the help of two newly published models, namely the C’2—εC’ model and the Reynolds  mass flux model, especially with regard to predictions of concentration, temperature and velocity distributions in chemical and related processes. The book will also allow readers to understand the interfacial phenomena accompanying the mass transfer process and methods for modeling the interfacial effect, such as the influences of Marangoni convection and Rayleigh convection. The CMT methodology is demonstrated by means of its applications to typical separation and chemical reaction processes and equipment, including distillation, absorption, adsorption and chemical reactors. Professor Kuo-Tsong Yu is a Member of the Chinese Academy of Sciences. Dr. Xigang Yuan is a Professor at the School of Chemical Engineering and Technology, Tianjin University, China

Research on the Dynamics Game Model in a Green Supply Chain: Government Subsidy Strategies under the Retailer’s Selling Effort Level

Based on dynamic game theory and the principal-agent theory, this paper examined different government subsidy strategies in green supply chain management. Assuming that the retailer’s level of selling effort involved asymmetric information, this study analyzed the impact of different government subsidy strategies on the wholesale price, the product greenness level, retail price, the level of selling effort, the manufacturer’s profit, and the retailer’s profit. The results showed that (1) the government’s subsidy strategy can effectively not only improve the product greenness level but also increase the profits of an enterprise in a green supply chain, which helps the retailer to enhance their selling effort; (2) regardless of whether the retailer’s level of selling effort was high or low, as the government’s subsidy coefficient increased, the wholesale price continued to decrease, and the product greenness level and retailer’s selling effort level also increased

Analysis of the Impact of Different Forecasting Techniques on the Inventory Bullwhip Effect in Two Parallel Supply Chains with a Competition Effect

This paper studies the impact of different forecasting techniques on the inventory bullwhip effect in two parallel supply chains with the competition effect, which is in contrast to the situation of a single product in a serial supply chain. In particular, this paper constructs two parallel supply chains, each of which includes one manufacturer and one retailer. Moreover, the market demand is impacted by the self-price sensitivity coefficient, the cross-price sensitivity coefficient, the market share, and the demand shock. We then assumed that the retailer can forecast market demand by using different forecasting techniques (i.e., the moving average technique (MA), the exponential smoothing technique (ES), and the minimum mean square error technique (MMSE)). We constructed the quantity model of the bullwhip effect and the inventory bullwhip effect. Finally, we analyzed the impact of different forecasting techniques and market share on the inventory bullwhip effect. We analyzed the conditions under which the retailers should choose different types of forecasting techniques on the basis of the inventory bullwhip effect. The results show that the MMSE forecasting technique can reduce the lead-time demand forecast error to the largest extent, and the inventory bullwhip effect can obtain the lowest level using the MMSE method: retailer-1 can reduce the inventory bullwhip effect by using the MA technique, when the self-price sensitivity coefficient, the price autoregressive coefficient, and the probabilities associated with customers choosing retailer-1’s product are very low

Introduction to Computational Mass TransferWith Applications to Chemical Engineering /

XI, 337 p. 219 illus., 42 illus. in color.online