Abstract: In recent ten years, because of the rapid progress of technology, the cycle of releasing products is shortened, especially in 3C market. Under a given market scale, this study particularly concerns about the optimal pricing policy where there are two kinds of products having different degrees of greenness from different manufacturers sold by one retailer. The objective is to maximize the retailer(s)’s profit. Based on the characteristic of the multiple periods along the life cycle of a product, in this study, based on Game Theory, a Dynamic Programming (DP) model is developed to analyze the competitive condition as well as the market behavior for two products. In particular, according to recycling principle of WEEE, the retailer(s) will refund the remaining products to the manufacturer with lower price at the last stage. Finally, the proposed pricing policy has been shown to be theoretically valid and thoroughly applicable.

Brief Biography of the Speaker:
Hsiao-Fan Wang is the Distinguished Chair Professor of National Tsing Hua University, Taiwan, Republic of China. She has been teaching at the Department of Industrial Engineering and Engineering Management at the same university, NTHU after she graduated from Cambridge University, UK in 1981 . She used to be the Vice Dean of the College of Engineering; the Head of the Department of IEEM, NTHU, President of Chinese Fuzzy Systems Association, Vice President of International Fuzzy Systems Association and Erskine Fellow of Canterbury University, NZ. Also, she has been awarded the Distinguished Research Award from National Science Council of Taiwan, ROC; Distinguished Contracted Research Fellow of NSC and Distinguished Teaching Award of Engineering College, NTHU. She used to be the editor-in-chief of the Journal of Chinese Industrial Engineering Association; also the Journal of Chinese Fuzzy Set and Theories and now is the area editor of several international journals. Her research interests are in Multicriteria Decision Making, Fuzzy Set Theory and Green Supply Chain Management.