| Abstract [eng] |
The final master's project, based on world international trade data, developed a competitiveness assessment model that would be appropriate for assessing the current situation of a sector or product in relation to other countries and making certain strategic decisions on export strategy issues. The analysis of the export competitiveness of the Lithuanian sector in the markets of the main trading partners of countries in the period of 2009—2018 was selected and the factors influencing the export competitiveness of the sector were assessed. For this purpose, the constant market share analysis (CMSA) method is used, which decomposes changes in market share into individual effects and allows us to determine the impact of each of these effects in the change in market share of the analyzed country sector. The Revealed Comparative Advantage Index (RCA) makes it possible to determine whether a sector has a comparative advantage in international trade and thus indirectly reflects the level of competitiveness. The Gravity method shows the causality of factors influencing exports between specific countries and goods or sectors, including economic indicators. To see certain trends in world trade, international trade data were sorted, aggregated, and systematized. After evaluating the results of CMSA and RCA, it is appropriate to identify the factors that in one way or another affect the volume of exports. With the help of neural networks, the influence of gross domestic product, population, and distance between countries on the change in the effect of competitiveness was assessed. The study can be useful for export strategy makers, researchers, and at the firm level can be adapted for analysis of opportunities in foreign markets. |
