Artificial intelligence-based assessment of the companies’ innovativeness in the context of digital transformation


Project no.: S-MIP-23-54

Project description:

The comprehensive evaluation of a company’s innovativeness and its impact is steadily becoming one of the most important objectives for any country’s innovation and economic policy in the area of digital transformation. Unfortunately, the traditional methods, which are founded upon surveys or patent data, do not provide a comprehensive and up-to-date representation of a firm’s innovation levels. Scientific articles, regularly emphasize the deficiencies that the latter methods’ have, like small data coverage, a lack of detail in the survey data, sparse periodic reporting, and tremendous costs. At the same time, in the economic field, a new scientifically based standpoint is emerging which relies upon artificial intelligence and an automated data mining approach that measures a firm’s innovativeness according to information that is displayed on companies’ websites. Data mining algorithms are used to retrieve ratios from massive databases and to convert them into economic information with as small as possible data lag. This type of data usage gives a stark advantage compared to surveys or patent-based measurement. Therefore, the goal of this project is to assess the level of innovativeness of the country’s companies and the impact on the country’s economy by applying artificial intelligence algorithms and using big data mining methods.

Project funding:

Projects funded by the Research Council of Lithuania (RCL), Projects carried out by researchers’ teams

Project results:

This project will create a unique, based on artificial intelligence methodology of innovation indicators’ evaluation, which will produce companies’ innovation index, and will assemble the methodology concerning the company’s innovation impact on the economic subject at a micro, sectoral and regional levels. This research will create Lithuania’s innovation map, which will depict companies’ innovation changes with shorter time lags and solve the sparse periodic problem. Additionally, a comprehensive view of companies’ innovation levels will be provided, which in turn will allow government institutions to take action related to innovation policy fosterage, help target selected economic measures, etc. The results of this research will contribute to the development of interdisciplinarity in terms of the integration of economics, big data and artificial intelligence. In the context of the country’s economic research, these would be innovative solutions, implementing a new scientific approach to digital analysis and research in the economics.

Period of project implementation: 2023-04-01 - 2026-03-31

Project coordinator: Kaunas University of Technology

Vaida Pilinkienė

2023 - 2026

Academic Centre of Economics, Business and Management, School of Economics and Business