讲座题目：Should Tech Companies Offer More Alternatives for Innovative Products?
Technology companies frequently face the problem of how many alternatives to offer consumers for their innovative products. Unlike traditional products, the quality of innovative products is usually unfamiliar to consumers (we refer to the unknown element as opaque quality), which makes results in previous studies on product variety unsuitable. In this paper, we build a simple stylized model to answer this product breadth problem. Consumers, who are behaviorally inattentive, evaluate both the design and quality of the product and make purchase decisions, and the technology company decides how great the product variety should be. Our analytical model is accompanied by experimental evidence.
The contribution of our paper is threefold. First, the model fills a vacuum in the literature on product variety decisions by considering both horizontal and vertical differentiation, as well as behavioral inattention. We show a tradeoff between product fit and perceived quality, which serves as a novel incentive for firms to limit product variety. Second, the experiment helps with understanding how consumers choose innovative products from a consumer behavioral viewpoint. Third, we also provide practical guidelines and important implications for marketing managers. Notably, we show that when the opaque quality of a product is large, the company should offer a limited number of alternatives.
Haoyu Liu is a PhD candidate in Operations Management at HKUST Business School, where he received his MPhil degree in 2017. Prior to that, he obtained his bachelor’s degree in Statistics and Operations Research at HKBU. His research interests include innovative operations, socially responsible operations, and the interface of marketing and operations. He employs various techniques to facilitate his research, ranging from mathematical modeling to typical tools in empirical and experimental studies. He has several papers currently under review in top journals, such as Management Science, Manufacturing & Service Operations Management, and Production and Operations Management.
讲座题目：Effect of EPR coefficient policy on the production decision in precious metal accessory recycling
This study examines the effect of the Extended Producer Responsibility (EPR) coefficient policy on the production decision between a supplier and a manufacturer in a precious metal accessory recycling supply chain. EPR coefficient is a regulation proposed by the government and enterprises to balance economic profit and EPR behavior, and refers to the production proportion of recycled products in all serviceable products. Enterprises with a large EPR coefficient have good EPR practice. This study uses the newsvendor model and numerical simulation to study a supply chain system with remanufacturing and reproduction processes. Results show that the optimal recycling mode and the optimal EPR coefficient are always present in precious metal accessory operations. The increasing market demand for recycled products and the improving whole recycling parameters are both effective in enlarging the optimal EPR coefficient. However, the improvement of single or partial recycling parameters (except the market demand parameter) has no effect on the optimal EPR coefficient. The implementation mechanism and applicable conditions of the EPR coefficient policy are also explored. This study indicates that the EPR coefficient policy is an appropriate and effective approach to promote the EPR practice of the Chinese Government.
Dr.Shuiye Niu is woking as a Postdoctor in the Department of Industrial Engineering of Tsinghua University, and a part-time assistant researcher at the Tsinghua MEM Education Center. She gained her PhD from Nankai University and won the honorary title of Outstanding Doctoral Graduate. Her research expertise is the optimization of supply chain operation decisions and sustainable supply chain management. More than 7 academic papers have been published in domestic or international well-known academic journals, such as International Journal of Production Research, Sustainability, Journal of Systems Engineering, as well as 3 international conference papers retrieved by CPCI-S (ISTP) / EI. She has presided over one Chinese Post-doctoral Science Fund Project and two university-level research projects; as a main participant, she has participated in 9 research projects, including Major Project of National Social Science Foundation, National Natural Science Foundation of China. She is fortunate to be a recipient of the Tsinghua University Postdoctoral Support Program. Currently, she is a member of INFORMS and Human Factors and Ergonomics Society, and a reviewer for several international academic journals, such as Journal of Cleaner Production.
潘禹辰，中国科学院大学经济与管理学院管理科学与工程专业博士生，师从吴德胜教授（博士阶段导师）和杨善林院士（硕士阶段导师）。并在美国芝加哥大学布斯商学院访学1年，师从Operations Research主编John Birge教授。潘禹辰的研究方向为大数据挖据与分析、网络建模和用户行为分析，尤其是在推荐系统中的应用。研究成果以第一作者发表在多个权威期刊上。其中包括Journal of Management Information Systems（FT50、央财AAA）、Decision Support Systems（ABS 3、央财AAA）、Information Sciences（中科院1区、央财AAA）、IEEE Systems Journal（JCR1区、央财AA）和PLOS ONE（央财A）等。入选科协“高端科技创新智库青年项目”。同时也是以上期刊的审稿人。