29th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems, Sep. 11, 2025
29th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES 2025)
This study proposes a framework for measuring the commercialization of individual technologies using corporate disclosures. Based on the observation that corporate disclosure documents consistently provide information on both business operations and R&D activities, we define two indices, the Business Use Index and the Attention Index, derived from the number of companies that mention specific technologies in the description of business and R&D activities sections of Japanese securities reports. Using a ten-year dataset, we extract technology terms and compute these indices across time. We then apply time-series clustering to identify typical commercialization patterns. The results reveal diverse trajectories corresponding to technological evolution stages, ranging from growth, as seen in cloud computing, to decline in hydrogen stations, and maturity and renewed attention in solar cells. This method provides a scalable and interpretable approach to identify the business status of technologies using publicly available corporate data.
technology commercialization; corporate disclosures; time-series clustering; natural language processing;
@inproceedings{Kes2025-sato,
title={{Measuring Technology Commercialization Using Corporate Disclosures and Observing Temporal Patterns}},
author={Misa Sato and Masanori Hirano and Kentaro Imajo and Mitsuo Yoshida},
booktitle={29th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems},
year={2025}
}