A Two-Phased AI-Enabled Framework for Innovation with User-Generated Data from Consumer Review Sites

Presenter Information

• Kristijan Mirkovski, Deakin UniversityFollow
• Jingda Kang, University of MelbourneFollow
• Libo Liu, University of MelbourneFollow
• Marta Indulska, University of QueenslandFollow
• Hao Liu, Deakin UniversityFollow

Location

Hilton Waikoloa Village, Hawaii

Event Website

https://hicss.hawaii.edu/

Start Date

7-1-2025 12:00 AM

End Date

10-1-2025 12:00 AM

Description

User-generated data from consumer review sites holds immense potential for driving product innovation, yet actionable research in this area remains limited. This paper addresses this gap by proposing a two-phased AI-enabled framework for leveraging consumer reviews throughout the idea selection and generation processes. Our framework utilizes advanced AI approaches to automate idea selection and generation in open innovation settings. The proposed framework aims to extract product innovation ideas from raw online reviews, employing cutting-edge machine learning for natural language processing and generative pre-trained transformers for natural language generation. This paper offers a novel AI-enabled approach for organizations to drive open innovation and improve product development processes.

Recommended Citation

Mirkovski, Kristijan; Kang, Jingda; Liu, Libo; Indulska, Marta; and Liu, Hao, "A Two-Phased AI-Enabled Framework for Innovation with User-Generated Data from Consumer Review Sites" (2025). Hawaii International Conference on System Sciences 2025 (HICSS-58). 3.
https://aisel.aisnet.org/hicss-58/cl/responsible_innovation/3