Effects of dominance on operation policies in a two-stage supply chain in which market demands follow the Bass diffusion model

2018 ◽  
Vol 52 (4-5) ◽  
pp. 1261-1275
Author(s):  
Phan Nguyen Ky Phuc ◽  
Vincent F. Yu ◽  
Shuo-Yan Chou ◽  
Yu-Chung Tsao
Keyword(s):  
Supply Chain ◽  
Diffusion Model ◽  
Bass Model ◽  
Market Demand ◽  
Two Stage ◽  
Essential Information ◽  
Optimal Policies ◽  
Bass Diffusion ◽  
Bass Diffusion Model ◽  
Production Plans

The Bass model offers several successful applications in forecasting the diffusion process of new products. Due to its potential and flexibilities, the application of this model is not only limited now to forecasting, but also extends to other fields such as analyzing a supply chain’s responses, optimizing production plans, and so forth. This study investigates inventory and production policies in a two-stage supply chain with one manufacturer and one retailer, in which the market demand process follows the Bass diffusion model. The model assumes the market parameters and essential information are available and ready for access. This study then applies dynamic programming and heuristic algorithm to find the optimal policies for each stage under different scenarios.

scholarly journals Cooperative Green Technology Innovation of an E-Commerce Sales Channel in a Two-Stage Supply Chain

2021 ◽  
Vol 13 (13) ◽  
pp. 7499
Author(s):  
Zongyu Mu ◽  
Yuangang Zheng ◽  
Hao Sun
Keyword(s):  
Supply Chain ◽  
Technology Innovation ◽  
Spillover Effect ◽  
Product Market ◽  
Free Riding ◽  
Green Technology ◽  
Market Demand ◽  
Two Stage ◽  
Sales Channel ◽  
Innovation Activities

The potential broad market of green consumption has encouraged an increasing number of enterprises to carry out green technology innovation activities. This paper examines a two-stage supply chain of e-commerce sales channels under different cooperative models. We find that consumers’ green preferences are the main factor that affects green product market demand. The manufacturer and the retailer can raise the levels of green technology innovation and extend green promotional services to expand product market demand in online and offline channels. However, consumers’ e-commerce preferences and online free-riding behaviors affect the manufacturer’s sales channel choice. The retailer can improve the level of green promotional services to hold offline channel market demand, while promotional behaviors have a positive/negative spillover effect on online market demand if the level of free riding falls above/below consumers’ e-commerce preferences. The higher the cooperative level is, the later the manufacturer will open the online channel and close the offline channel to ensure a high level of green promotional service from the cooperative retailer. The results show that the stronger the level of cooperation among all members is, the better the economic, ecological, and social benefits will be. Therefore, we design a revenue-cost sharing contract that can effectively motivate green technology innovation and green promotional services and afford all members win-win profits.

scholarly journals Combining Diffusion and Grey Models Based on Evolutionary Optimization Algorithms to Forecast Motherboard Shipments

2012 ◽  
Vol 2012 ◽  
pp. 1-10
Author(s):  
Fu-Kwun Wang ◽  
Yu-Yao Hsiao ◽  
Ku-Kuang Chang
Keyword(s):  
Diffusion Model ◽  
Optimization Algorithms ◽  
Evolutionary Optimization ◽  
Grey Model ◽  
Percentage Error ◽  
Combined Model ◽  
Data Points ◽  
Evolutionary Optimization Algorithms ◽  
Bass Diffusion ◽  
Bass Diffusion Model

It is important for executives to predict the future trends. Otherwise, their companies cannot make profitable decisions and investments. The Bass diffusion model can describe the empirical adoption curve for new products and technological innovations. The Grey model provides short-term forecasts using four data points. This study develops a combined model based on the rolling Grey model (RGM) and the Bass diffusion model to forecast motherboard shipments. In addition, we investigate evolutionary optimization algorithms to determine the optimal parameters. Our results indicate that the combined model using a hybrid algorithm outperforms other methods for the fitting and forecasting processes in terms of mean absolute percentage error.

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