Potential for the use of large unstructured data resources by public innovation support institutions

Autor: Wiesław Cetera, Włodzimierz Gogołek, Aleksander Żołnierski, Dariusz Jaruga
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Journal of Big Data, Vol 9, Iss 1, Pp 1-21 (2022)
Druh dokumentu: article
ISSN: 2196-1115
DOI: 10.1186/s40537-022-00610-6
Popis: Abstract Effective programming of research and development (R&D) support, adjusted to the actual potential of beneficiaries, requires the use of modern analytical tools. An efficient R&D support system requires up-to-date data on technological trends, ongoing (and planning) research, market needs and developing innovation. The most popular programming methods were based on the analysis of data with a 4 to 5-year time delay until recently. Having described the method of refining information from unstructured data, we explore how to make it possible not only to solve the issue of up-to-date data but to identify of the latest trends in R&D activities. The analytical tools we describe were already fully functional in 2018 and are constantly being improved. The article presents the potential of one tool that can be applied in public support institutions. Methods of identifying and diagnosing technology trends are presented within the case study of the electric car technology trend. The presented case study shows the effectiveness of the method we developed for identifying and diagnosing areas requiring support from public funds. Public institutions, including public institutions supporting R&D and innovation processes, can apply tools that allow an increase in the quality of public support programmes offered, but also beneficial for the quality of strategic resources management within the institution itself. The comparison of the predictions made by the described tools with the classifications made by experts, the former are more accurate and precise. Moreover, the results of the analyses performed by the presented model are not influenced by distorting factors—fads, trends, political pressures, or processes with an unidentified, non-substantive background. It should be emphasized that the accuracy of the whole model is 0.84. The described tools and methods are already directly applicable in many areas related to the support of R&D activity worldwide. The article presents a solution that effectively enables the management of more precise programmes supporting innovative activities used for the first time in Poland. It is also one of the first uses of these methods by public administration in the world. Our approach not only strengthens improved adjustment of the support offered for R&D activity, but also makes it possible to apply and improve management methods in public institutions.
Databáze: Directory of Open Access Journals
Externí odkaz: