Journal article
Discovery of Technological Innovation Systems: Implications for Predicting Future Innovation
Journal of management information systems, Vol.41(1), pp.39-72
01/02/2024
DOI: 10.1080/07421222.2023.2301172
Abstract
In contrast with the accelerating trend of boundary-spanning (horizontal) technological innovation, the current Cooperative Patent Classification (CPC) scheme applies a hierarchical (vertical) structure to innovation output in terms of patents. For this reason, we argue that the CPC can be complemented with dynamic technological innovation system (TIS) discovery through machine learning that accounts for horizontal relationships across seemingly disparate technologies. Using a design science approach, we propose a framework to discover boundary-spanning TISs by leveraging the textual information from millions of patents. We validate our framework in terms of the ability of discovered relationships to predict future innovation quantity and quality in different technology classes. Our novel TIS-based innovation metrics that leverage patenting activity in related technology classes are significantly associated with future innovation intensity in focal technologies. We conduct experiments with machine learning models to further tease out the predictive utility of our TIS discovery framework.
Details
- Title: Subtitle
- Discovery of Technological Innovation Systems: Implications for Predicting Future Innovation
- Creators
- Junho Yoon - University of Iowa, Business AnalyticsGautam Pant - Univ Illinois, Gies Coll Business, Dept Business Adm, Champaign, IL USAShagun Pant - Univ Illinois, Gies Coll Business, Dept Business Adm, Champaign, IL USA
- Resource Type
- Journal article
- Publication Details
- Journal of management information systems, Vol.41(1), pp.39-72
- DOI
- 10.1080/07421222.2023.2301172
- ISSN
- 0742-1222
- eISSN
- 1557-928X
- Publisher
- Taylor & Francis
- Number of pages
- 34
- Language
- English
- Date published
- 01/02/2024
- Academic Unit
- Business Analytics
- Record Identifier
- 9984938143202771
Metrics
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