The article discusses the importance of identifying technological convergence in emerging cybersecurity technologies to foster innovation. It critiques past studies for their binary assessment methods and introduces a new approach utilizing attribution scores to analyze technological relationships. By employing bibliometric indicators along with text mining, the study develops proximity indices for various encryption technologies. A case study reveals a notable convergence between blockchain and public-key cryptography, providing actionable insights for investors and researchers interested in these fields.
In an era characterized by a technological revolution, understanding the dynamics of technological evolution, convergence, and emergence has become crucial for advancing science and fostering economic innovation.
Our approach utilizes attribution scores to enhance the relationships between research papers, combining keywords, citation rates, and collaboration status with specific technological concepts.
The proposed method integrates text mining and bibliometric analyses to formulate and predict technological proximity indices for encryption technologies using the 'OpenAlex' catalog.
Our case study findings highlight a significant convergence between blockchain and public-key cryptography, evident in the increasing proximity indices.
Collection
[
|
...
]