The impact of firm-level innovativeness on socioeconomic indicators: an AI-driven approach
Alina Stundžienė et al.
Abstract
This study examined the impact of firm-level innovativeness on socioeconomic indicators at regional and sectoral levels, using Artificial Intelligence (AI) techniques to analyze unstructured data from the websites of 32,559 companies. Using this data, an Innovation Index was constructed. The results indicated a generally low-to-moderate level of innovativeness among Lithuanian firms, with an average Innovation Index of 35 out of 100. Notably, 38.6% of firms scored 0, showing no detectable signs of innovation. Innovativeness was found to be highest in Vilnius and Kaunas, and in sectors such as electricity, information and communication, and public administration. An econometric analysis revealed that a 1-point increase in the Innovation Index was associated with a 0.02% rise in gross average earnings, a 0.27% increase in gross value added, a 0.17% increase in FDI per capita, and a 0.05% increase in GDP per capita. Higher innovativeness levels were also linked to lower unemployment and migration rates. The findings underscore the importance of innovation for regional development and labor market outcomes, and that an AI-driven approach can offer a reliable and scalable alternative to traditional methods, providing more timely and objective assessments. The approach is adaptable across countries, thus offering valuable insights for policymakers and researchers.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.