东北大学建校100周年
工商管理学院系列学术报告第64场
报告题目：Data-Driven Research Methods
报告人：美国匹兹堡大学Katz商学院 Jennifer Shang 教授
主持人：hjc888黄金城 秦绪伟教授 卢震副教授
报告时间：2023年12月19日（周二）上午 9:30 --12:30
腾讯会议号：217-329-697
报告摘要：
“Data-Driven Research Methods” course is designed to broaden and enrich students' knowledge and understanding of statistical concepts. Multivariate statistical techniques can be used to analyze data in many fields such as Finance, Production and Operations, Accounting, Marketing, Personnel Management, etc. Through overviewing actual applications in various fields and in-class exercises involving real-world data, students can apply the techniques to topics such as consumer and market research, supply chain analytics, creditworthiness and risk assessment, stress test, and early warning signals outside pre-set limits, and make better business decisions. The course will teach students to better derive insights from data, ask questions to shape business vision and to drive value. They will also be able to improve business processes by using the right data insights as decision makers and incorporating these insights into management decisions. The main purpose of this course is to enhance students' data-driven analytical skills to the level necessary to deal with Data Mining and other essential material in the Business Analytics domain.
报告人简介：
Prof. Jennifer Shang is a professor of Business Administration and area director for Business Analytics and Operations at the Katz School of Business at the University of Pittsburgh and a renowned scholar in the field of operations management and decision-making science in the United States. Prof. Shang’s research focuses on healthcare analytics, operations management, and e-commerce. She applies data/business analytics approaches to enhance patient care outcomes and improve hospital’s operational efficiency. She also develops theoretical and heuristic approaches to improve the productivity and quality of business operations; employs multi-criteria decision-making techniques (e.g., AHP/ANP, DEA) to measure organization’s relative efficiency; and combines intangible human judgment with objective data to effectively rank options and predict outcomes. She has published more than 140 papers. Among them, 9 12 papers have been published in top academic journals such as Management Science, Journal of Marketing, Marketing Science, Information Systems Research, Production and Operations Management, Manufacturing & Service Operations Management, INFORMS Journal on Computing, Journal of Marketing Research, etc. and 30 of them in EJOR.
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