The impact of technological advances in all industry sectors is being felt and, thus, there is no doubt that digital transformation will have significantly affect Lithuanian manufacturing sector. In order to assess the extent to which Lithuanian processing industry companies are digitalized, an in-depth descriptive analysis of installed digital technologies in these companies was executed.  The goal of this analysis – to determine whether Lithuanian companies of processing industry has been sufficiently digitalized and are ready to completely adopt the principles of Industry 4.0 in the installation of digital solutions within all segments of the value-chain creation. The research on already-applied digital tools and technologies in those companies was made during the phase of analysis.  There was also an attempt to define the most digitalized processes of operation and the least or non-digitalized processes of operations in those companies. After the assessment of a current digitalization level in the company was made,  there was an attempt to clarify the strengths and problematic challenges as well as the underlying reasons for its challenges. After the above-mentioned data was collected, recommendations on which additional tools and means to apply in order to encourage the process of digitalization in the companies were formulated and passed on to the companies.

The object of this paper is related to the public innovation support in Euro-pean Economic Area and its effectiveness assessment. Main aim of the re-search presented in this paper is to propose new model for public innovation support effectiveness assessment, which could be relevant to the contempo-rary needs and would be based on new explored practice of public innova-tion support developments. The methods of comparative, regression, model-ling analysis, multi-criteria evaluation, analogy search, logical abstraction and impact evaluation have been applied for the research presented in this paper. Proposed original system of quantitative and qualitative indicators that characterize any public innovation support system (public innovation support index) enables creation and implementation of measures devoted to the public innovation support impact improvement at EU and national level.

The object of this research is public innovation support in the European Economic Area and its effectiveness assessment. The main aim is to propose a new model for public innovation support effectiveness assessment, adjusted to contemporary needs and based on practice of public innovation support development. Research Design & Methods: The methods of comparative, cluster, regression, modelling analysis, multi-criteria evaluation, analogy search, logical abstraction and impact evaluation have been applied for the research presented in this paper. Findings: The paper conceptualizes a new model for the assessment of public innovation support. It is based on theoretical argumentation and practical verification. Its structure is based on new solutions and quantitative assessment methods. Implications & Recommendations: The analysis of the proposed model applicability revealed important patterns for the public innovation support impact assessment. Findings suggest that the increase of public innovation support index is a necessary but insufficient condition for the growth of the countries innovation index. The impact of public innovation support occurs only in the long run, as the delay of the effect exists. Contribution & Value Added: The proposed system of quantitative and qualitative indicators that characterize any public innovation support system (public innovation support index) enables the creation and implementation of measures devoted to the public innovation support impact improvement at EU and national level. The practical application of the suggested model is significant for the effectiveness improvement of public innovation support at EU institutions.

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Abstract. Competition in the banking sector is different from the competition in the other sectors. Banks can compete only on the basis of banking products. Also, banks are dependent on each other -actions of every market participant may strongly affect the others. Problems of one bank may encourage distrust of the entire banking system. Analysis of Lithuanian banking sector has showed that country's banking sector can be divided into three groups -the biggest banks, smaller and medium-sized banks and foreign banks branches. The largest part of banking sector is concentrated in activity of the three banks. All these banks are owned by Scandinavian capital. Lithuanian banking sector is highly concentrated. In 2005-2012 years the average mean of three banks concentration index (CR3) in deposits, assets and loans markets was 68 percent. According to these high values of concentration rates, Lithuanian banking sector can be characterized as oligopoly.