题  目：Newsvendor Models for Innovative Products with One-Shot Decision Theory（基于一次性决策理论的创新产品报童模型）

演讲人：郭沛俊，日本横滨国立大学教授

主持人：林贵华，太阳成集团tyc33455cc教授

时  间：2017年5月4日（周四）下午15:00-16:00

地  点：太阳成集团tyc33455cc校本部东区太阳成集团tyc33455cc420室

主办单位：太阳成集团tyc33455cc、太阳成集团tyc33455cc青年教师联谊会

演讲人简介：

本硕博均毕业于大连理工大学，并于2000年在大阪府立大学获得其第二个博士学位，现为日本横滨国立大学经营学部决策科学系教授。郭教授的研究领域为运营管理，主要包括在不确定因素和不确定模型下的决策分析。他在国际上首次提出了"一次性决策理论"(One-Shot Decision Theory)，该理论对不确定因素下做决策有非常重要的意义。郭教授已在国际重要期刊发表数十篇学术论文，现为IEEE Transactions on SMC、Information Sciences、Fuzzy Economic Review等杂志编委。

演讲内容简介：

This presentation includes two parts. In Part I, we clarify the fundamental differences between the one-shot decision theory and other decision theories under uncertainty to highlight that one-shot decision theory is a scenario-based decision theory instead of a lottery-based one; point out the instinct problems in other decision theories to show that the one-shot decision theory is necessary to solve one-shot decision problems; manifest the relation between the one-shot decision theory and the other probabilistic decision methods. In Part II, we consider newsvendor models for innovative products whose life cycles are expected to be smaller than the procurement lead times. Determining optimal order quantities of such products is a typical one-shot decision problem for a retailer. Hence, newsvendor models based on the one-shot decision theory (OSDT) are proposed. In the proposed models, for each order quantity, the retailer chooses one demand amongst all possible demands while considering the satisfaction level caused by the occurrence of the demand and the relative likelihood of the demand occurring. The selected demand is called the focus point of the order quantity. The optimal order quantity corresponds to the maximum satisfaction level of its focus point. Four types of retailers who choose four different types of focus points, i.e. active, passive, apprehensive and daring retailers are taken into account and the analytic results are given. The proposed models are scenario-based decision models which provide a fundamental alternative to analyze newsvendor problems of innovative products.

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