Paper Type
Complete
Paper Number
PACIS2025-1909
Description
Academic patents hold significant commercial value. To promote their commercialization, many technology transfer platforms recommend relevant patents to companies. However, companies still need to find time to communicate with busy university scholars who invented these patents, which slows down the transfer process and hinders potential co-development opportunities. Previous research has focused on human-AI one-on-one interactions between students or scholars and digital scholars, which doesn't work well for the one-to-many interactions needed in academic patent transfer. To address this, we proposed a company-multi-digital scholar collaborative framework with a resource-based view communication template. This framework uses a Large Language Model-based agent system, and the communication template focuses on 11 resource-based view factors. Companies can work with multiple digital scholars through this template to improve collaboration. We conducted a field experiment to test and validate the effectiveness of the proposed framework.
Recommended Citation
Liu, Zhaobin; Xu, Qingyu; FAN, Xia; and Ma, Jian, "Company-Multi-Digital Scholar Collaborative Framework Driven by Resource-based View for Patent Co-Development" (2025). PACIS 2025 Proceedings. 5.
https://aisel.aisnet.org/pacis2025/hci/hci/5
Company-Multi-Digital Scholar Collaborative Framework Driven by Resource-based View for Patent Co-Development
Academic patents hold significant commercial value. To promote their commercialization, many technology transfer platforms recommend relevant patents to companies. However, companies still need to find time to communicate with busy university scholars who invented these patents, which slows down the transfer process and hinders potential co-development opportunities. Previous research has focused on human-AI one-on-one interactions between students or scholars and digital scholars, which doesn't work well for the one-to-many interactions needed in academic patent transfer. To address this, we proposed a company-multi-digital scholar collaborative framework with a resource-based view communication template. This framework uses a Large Language Model-based agent system, and the communication template focuses on 11 resource-based view factors. Companies can work with multiple digital scholars through this template to improve collaboration. We conducted a field experiment to test and validate the effectiveness of the proposed framework.
Comments
HCI