题　目：Collaboration and Knowledge Sharing in Teams: A Graph-based Deep Learning Approach

嘉　宾：Qianyin Xia (夏乾尹), Ph.D. Candidate, 佐治亚州立大学

主持人：张铄 副教授 上海交通大学安泰经济与管理学院

时　间：2025年11月26日（周三）10:00-11:30

地　点：上海交通大学 徐汇校区 安泰经济与管理学院A407

内容简介:

Collaboration and knowledge sharing are foundational to modern organizations, particularly in environments where teamwork drives performance. However, jointly considering and separately quantifying the individual value of direct collaboration and indirect knowledge sharing across multiple teams remains empirically and methodologically challenging. This paper introduces a Two-Stage Hypergraph Neural Network (TSHyGNN) framework to model agent behavior in multi-agent, multi-team settings. By leveraging hypergraph structures and modeling team membership with hyperedges, this framework captures the complexity of real-world team structures beyond traditional dyadic models. It enables the modeling of both within-team collaboration and cross-team knowledge transfer, offering marketing a novel perspective by explicitly integrating knowledge sharing into the context of complex team collaboration.

演讲人简介：

Qianyin Xia, a Ph.D. candidate in Quantitative Marketing at the Robinson College of Business, Georgia State University.

As an empirical marketing modeler, his work lies at the intersection of econometric modeling and deep learning, with a particular emphasis on network-based marketing phenomena. Moving beyond traditional unit-level analysis, he examines how the performance and behavior of market units are shaped by the relational structures among interconnected marketing entities, such as consumers, firms, and platforms. This network-centric perspective enables him to uncover patterns of influence, strategic interactions, and spillover effects across the marketing ecosystem. 

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