Artykuł w czasopiśmie
Brak miniatury
Licencja

CC-BYCC-BY - Uznanie autorstwa

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

Autor
Żołnierski, Aleksander
Cetera, Wiesław
Gogołek, Włodzimierz
Jaruga, Dariusz
Data publikacji
2022
Abstrakt (EN)

Efective programming of research and development (R&D) support, adjusted to the actual potential of benefciaries, requires the use of modern analytical tools. An efcient 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 refning 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 cartechnology trend. The presented case study shows the efectiveness 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 ofered, but also benefcial for the quality of strategic resources management within the institution itself. The comparison of the predictions made by the described tools with the classifcations made by experts, the former are more accurate and precise. Moreover, the results of the analyses performed by the presented model are not infuenced by distorting factors—fads, trends, political pressures, or processes with an unidentifed, 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 efectively enables the management of more precise programmes supporting innovative activities used for the frst time in Poland. It is also one of the frst uses of these methods by public administration in the world. Our approach not only strengthens improved adjustment of the support ofered for R&D activity, but also makes it possible to apply and improve management methods in public institutions.

Słowa kluczowe EN
Big Data
Information refining
Information technologies management
Research and development management
Research and development support programming
Data management
Business statistics
Innovation
Dyscyplina PBN
nauki o bezpieczeństwie
Czasopismo
Journal of Big Data
Tom
9
Zeszyt
46
Strony od-do
1-21
Data udostępnienia w otwartym dostępie
2022-04-28
Licencja otwartego dostępu
Uznanie autorstwa