Effect of machine learning on competitiveness of regions in Finland
Mossolainen, Artur (2021)
Pro gradu -tutkielma
School of Business and Management, Kauppatieteet
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The purpose of this research is to examine the effect of Machine Learning on competitiveness of 310 municipalities in Finland and find out the economic implications using data from 2010-2018. To achieve this, a formative index was created to measure competitiveness of municipalities. This index consisted of four dimensions, which were social equity, innovativeness, centralization, and reachability. To measure Machine Learning impact, a score was used for each municipality called the Suitability for Machine Learning. This measure scores every occupational task based on how well it can be automated with Machine Learning. The score is then calculated for every occupation based on the tasks it contains and applied on employment data of Finnish municipalities to get a final score for each municipality. The competitiveness index score and Suitability for Machine Learning score were then used in panel regression analysis to see their impact on Gross Domestic Product per capita, and yearly mean salary, which were used as the economic performance measures in this study. The study concludes that Machine Learning does have a positive impact on economy, but a negative impact on competitiveness, while competitiveness has a negative short-term impact on GDP and salary, and a positive long-term impact.