Speaker Profile
Dr. GAO Weihe is a Chaired Professor and the Associate Dean of the College of Business at Shanghai University of Finance and Economics. He has published over 80 papers in prominent domestic and international journals and media outlets, including Journal of Marketing, Decision Support Systems, Industrial Marketing Management, Asia Pacific Journal of Management, as well as leading Chinese journals such as Management World, Journalism and Communication Research, Chinese Journal of Management Science, and Nankai Business Review.
He has led or completed over 20 national, provincial, and ministerial-level research projects. These include a Key Special Project of National Natural Science Foundation of China (NSFC); five NSFC General and Young Scientist Projects; an NSFC Project for International Cooperation with Overseas, China Hong Kong, China Macao, and China Taiwan; a Key Project of National Social Science Fund of China (NSSFC); a Humanities and Social Sciences Project of Ministry of Education; and a Shanghai Social Science Project.
Professor Gao is the recipient of numerous prestigious awards for his scholarly and societal impact. At the national level, he has been honored twice with the Ministry of Education's Award for Outstanding Scientific Research (Humanities & Social Sciences) and received a rare "Excellent" final evaluation from the National Natural Science Foundation of China (NSFC) for a key project. His municipal-level accolades include the Shanghai Award for Excellence in Philosophy and Social Sciences (twice), the Shanghai Award for Excellence in Policy Consultation (twice), a Special Award from the Shanghai Municipal Government's Development Research Center, and the Outstanding Paper Award for Academic Achievements in Chinese Think Tanks
Abstract
Generative AI technology has expanded the capabilities of marketing in generating insights, matching, and communication, but it also brings new challenges. The focus of generative tools on standardized tasks and localized processes creates issues of both efficiency and mismatch in corporate marketing practices. Furthermore, overly personalized outputs can erode consumer trust in the company and its products, while the uncontrollable nature of the generated content exacerbates control difficulties within the corporate marketing system. A substantial paradigm shift from analytical marketing to generative AI marketing can only be achieved by systematically addressing these challenges.
Therefore, this research proposes a generative AI marketing framework centered on tools, content, and systems.
Tools: It addresses the efficiency and mismatch problems by organizing generative content, derived from three distinct generation categories, into a systematic framework of tools.
Content: It resolves the trust deficit caused by content inconsistencies across different stages through a closed-loop matching of foundational, interactive, and organizationally produced, disseminated, or received content.
System: It constructs a comprehensive generative marketing system by integrating end products, decision-making processes, and marketing strategies.
Date/Time: November 7, 2025, 15:30 p.m.
Venue: Room 0204, 0 Teaching Building, Jiuliu Campus
