Strategies for sensing innovation opportunities in smart grids: In the perspective of interactive relationships between science, technology, and business

Abstract

In response to the many changes and uncertainties facing the future, sensing opportunities for innovation is an important agenda. Formulating strategies for sensing opportunities in innovation requires an ecosystem perspective that integrates the science, technology, and business (S-T-B) fields that shape the innovation ecosystem. This study was to identify potential in the innovation ecosystem focusing on a text mining technique and similarity-based analysis, which is the fundamental concept of Literature-Based Discovery, an approach to deriving hidden associations between two areas in bibliometric databases. The purpose of this study was sensing innovation opportunities through intelligent trends and interaction analysis in S-T-B fields in the value chain of smart grids, which is the research target area. Topic modeling, and cosine similarity measurements were carried out using scientific papers, patents, business publication data corresponding to the S-T-B ecosystem. Through multi-dimensional data sources corresponding to the S-T-B fields, the evolutionary path of the smart grid value chain and its potential as a strategic tool for future innovative challenges were identified. This study has practical and policy implications in that it identifies a niche in the innovation system and provides meaningful information that could contribute to the revitalization of participation in the private sector and consumers.