題目：Feedback Stackelberg games for dynamic supply chains with cost learning
主講人：Sethi Suresh Pal. 教授（美國德克薩斯大學達拉斯分校）
時間：2015年9月21日10點
地點：主樓418
主講人簡介：
Suresh P. Sethi任教于德克薩斯大學達拉斯分校，現為加拿大皇家科學院院士，Charles & Nancy Davidson運作管理的杰出教授，智能供應網絡中心主任(the Center for Intelligent Supply Networks)。Sethi教授在運作管理、營銷、工業工程、最優控制等領域做出了杰出貢獻，最為人熟知是Sethi advertising model、DNSS Points以及有關最優控制的教科書，如Optimal Control Theory: Applications to Management Science and Economics。
Sethi教授在國際主流期刊上發表學術論文264篇，其中Management Science 11篇, Operations Research 17篇, Production and Operations Management 16篇, Manufacturing & Service Operations Management 5篇。
Sethi教授現為Production and Operations Management協會主席，同時擔任Production and Operations Management期刊（UT Dallas 24種頂級期刊之一）的Department Editor，SIAM Journal on Control and Optimization的責任編輯，Automatica的副主編。現擔任Management Science、Operations Research(OR)、IIE Transactions(IIE) 、Manufacturing & Service Operations Management等多種權威期刊的審稿專家。
內容簡介：
We study a two-period supply chain in which a manufacturer produces a product, learns to reduce cost , and sells it through a retailer with a price-dependent demand. The manufacturer's second-period production cost declines linearly in the first-period production with a random learning rate. The manufacturer may or may not have the option to carry inventory. We model the problem as a dynamic Stackelberg game and obtain an explicit feedback Stackelberg equilibrium. The explicit solution allows us to examine the impact of mean learning rate and learning rate variability on the manufacturer's production and pricing decisions, as well as on the retailer's procurement and pricing decisions. We demonstrate that as the mean learning rate or the learning rate variability increases, the traditional double marginalization problem becomes more severe, leading to greater efficiency loss in the channel. We provide revenue sharing contracts that can coordinate the dynamic supply chain. In particular, when the manufacturer may hold inventory, we identify two major drivers for inventory carryover: market growth and learning rate variability. Lastly, we demonstrate the robustness of our results by examining a model in which learning takes place continuously.
（承辦：技術經濟與管理系、科研與學術交流中心）
