【主讲】吴靖，香港中文大学副教授
【时间】2024年9月10日（周二）14:00-15:30
2024年9月12日（周四）14:00-15:30
2024年9月19日（周四）14:00-15:30
【地点】李华楼B431
【报告1】Empirical Research in Operations and Supply Chain Management: Overview on Questions and Insight
【摘要1】
This talk delves into the emerging realm of empirical research within operations and supply chain management. I will discuss the synergies between analytical and empirical research, address the importance of good questions, and the criteria that define the significance of research. I will introduce a variety of empirical research topics, with a focus on supply chain management, including the bullwhip effect, risk propagation, network concentration, capital structure, deglobalization, as well as societal factors such as human organization and CSR/ESG.
【报告2】Unraveling Causality: Econometric Models in Empirical Operations Management
【摘要2】
I will delve into the empirical methodologies used to establish causality in operations management research. We will explore the nuances and evolution of the Difference-in-Differences (DiD) approach, Instrumental Variables (IV), and the Regression Discontinuity Design (RDD). Special attention will be given to their assumptions, strengths, and limitations. Then, I will discuss how those causal identification techniques are used in my papers. Common secondary firm-level datasets suitable for empirical operations management will also be covered in this talk.
【报告3】The Bullwhip Effect in Servitized Manufacturers: Textual Analysis Using Large Language Models (LLMs)
【摘要3】
This talk explores the impact of servitization on the bullwhip effect in manufacturing industries. It delves into the concept of servitization, where manufacturers integrate services into their traditionally product-oriented business models. The study leverages both "bag of words" text mining and Large Language Models (LLMs) to construct a novel measurement for servitization, which is then validated through various metrics. The presentation concludes with a discussion on the broader implications of LLMs in business research and their potential as tools for unstructured data mining.
