Title: Text-based Analysis of Firm and Product Competition: A Tale of Two Studies

Speaker: Cui Geng, Professor, Lingnan University (Hong Kong) and School of Business, Guangdong University of Foreign Studies; Chief Expert of Yunshan Studio for Business Administration Discipline Construction; National-level Talent; Adjunct Professor, School of Economics and Management, Shandong University. His research fields include digital economy, network marketing, big data analysis, machine learning and artificial intelligence applications, internationalization of Chinese enterprises, Chinese marketing, and economic integration between Hong Kong and the Chinese mainland. He is a leading scholar in Chinese consumer research, digital marketing, and the application of artificial intelligence in marketing. His research results have been published in multiple top international academic journals such as "Journal of Marketing", "Strategic Management Journal", "Management Science", "MIS Quarterly" and "Journal of International Business Studies". He serves as Executive Director of the Asia Pacific Division of the Academy of International Business and a reviewer and contributing editor for several academic journals.

Abstract: Traditional competition analysis usually relies on the Standard Industrial Classification (SIC) system to identify competitors and evaluate competition concentration, thereby providing references for industry and corporate strategies. However, this rough competition measurement and analysis ignores the relationships between enterprises in the value chain (such as partners and competitors, producers and suppliers) and fails to consider enterprise heterogeneity (such as intra-enterprise share, diversified and focused enterprises) and asymmetric competition. In recent years, the development of network analysis, machine learning, and Natural Language Processing (NLP) has led to text-based competition analysis, which has proven to be more accurate and insightful (Hoberg 2010, 2016). Using enterprise and product data from brand awards and product comparisons (such as reviews), we identify competitors at the enterprise and product levels, evaluate competition asymmetry and its impact on corporate strategies, and present two studies: Study 1 - "Following Stars? How Competitors’ Brand Awards Shape Rivals’ Product Strategies: Exploring the Impact of Brand Cognition on Product Strategy Choices"; Study 2 - "Deep Learning for Market Structure and Asymmetric Competition: Integrating Purchase Decisions and Attribute Cognition from Product Comparison Reviews".

Date & time: 21 July 2025, 10:00

Venue: B321, Zhixin Building, Central Campus, Shandong University