KAUNAS UNIVERSITY OF TECHNOLOGY LITHUANIAN ENERGY INSTITUTE RASA VIEDERYTĖ ECONOMIC EVALUATION OF LITHUANIAN MARITIME SECTOR CLUSTERING PRECONDITIONS

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2 KAUNAS UNIVERSITY OF TECHNOLOGY LITHUANIAN ENERGY INSTITUTE RASA VIEDERYTĖ ECONOMIC EVALUATION OF LITHUANIAN MARITIME SECTOR CLUSTERING PRECONDITIONS Summary of Doctoral Dissertation Social Sciences, Economics (04S) 2014, Kaunas

3 The Doctoral Dissertation was prepared in at Kaunas University of Technology, School of Economics and Business, Department of Economics. Scientific Supervisor: Prof. Dr. Vytautas JUŠČIUS (Klaipėda University, Social Sciences, Economics- 04S). Dissertation Defence Board of Economics Science Field: Prof. Dr. Vytautas SNIEŠKA (Kaunas University of Technology, Social sciences, Economics-04S)-chairman; Prof. Dr. Jonas MARTINAVIČIUS (Vilnius University, Social sciences, Economics-04S); Prof. Dr. Valentinas NAVICKAS (Kaunas University of Technology, Social sciences, Economics-04S); Prof. Dr. Violeta PUKELIENĖ (Vytautas Magnus University, Social sciences, Economics-04S); Prof. Dr. Gražina STARTIENĖ (Kaunas University of Technology, Social sciences, Economics-04S). The official defence of the Doctoral Dissertation will be held at 10 a.m., on 16 th of January, 2015 at the public meeting of the Board of Economics Science field in the Rectorate Hall of Kaunas University of Technology. Address: K. Donelaičio St , LT-44209, Kaunas, Lithuania. Phone ( ) , fax. ( ) , The summary of the Doctoral Dissertation was sent on the 16 th of December, The Doctoral Dissertation is available at the Library of Kaunas University of Technology (K. Donelaičio St. 73, Kaunas, Lithuania) and Lithuanian Energy Institute (Breslaujos St. 3, Kaunas, Lithuania).

4 KAUNO TECHNOLOGIJOS UNIVERSITETAS LIETUVOS ENERGETIKOS INSTITUTAS RASA VIEDERYTĖ LIETUVOS JŪRINIO SEKTORIAUS KLASTERIZACIJOS PRIELAIDŲ EKONOMINIS VERTINIMAS Daktaro disertacijos santrauka Socialiniai mokslai, ekonomika (04S) 2014, Kaunas

5 Disertacija rengta metais Kauno technologijos universiteto Ekonomikos ir verslo fakultete, Ekonomikos katedroje. Mokslinis vadovas Prof. dr. Vytautas JUŠČIUS (Klaipėdos universitetas, socialiniai mokslai, ekonomika-04s). Ekonomikos mokslo krypties taryba: Prof. dr. Vytautas SNIEŠKA (Kauno technologijos universitetas, socialiniai mokslai, ekonomika-04s)-pirmininkas; Prof. dr. Jonas MARTINAVIČIUS (Vilniaus universitetas, socialiniai mokslai, ekonomika-04s); Prof. dr. Valentinas NAVICKAS (Kauno technologijos universitetas, socialiniai mokslai, ekonomika-04s); Prof. dr. Violeta PUKELIENĖ (Vytauto Didžiojo universitetas, socialiniai mokslai, ekonomika-04s); Prof. dr. Gražina STARTIENĖ (Kauno technologijos universitetas, socialiniai mokslai, ekonomika-04s). Disertacija bus ginama viešame ekonomikos mokslo krypties tarybos posėdyje, kuris įvyks 2015 m. sausio 16 d. 10 val. Kauno technologijos universiteto Rektorato salėje. Adresas: K. Donelaičio g , LT-44209, Kaunas, Lietuva. Tel. (8 37) , faksas (8 37) , el.paštas Disertacijos santrauka išsiųsta 2014 m. gruodžio 16 d. Su disertacija galima susipažinti Kauno technologijos universiteto (K. Donelaičio g. 20, Kaunas) ir Lietuvos energetikos instituto (Breslaujos g. 3, Kaunas) bibliotekose.

6 INTRODUCTION Relevance of the Research. Independent initiatives of clustering of business entities are observed in Lithuania. Some of them are focused on development of long-term economic goals, other are on their initial stage. Lithuania is a maritime country located in a strategically important geographical place and having a multi-purpose infrastructural object - Klaipeda State Seaport that is the northernmost ice free port on the Eastern coast of the Baltic Sea. Over the last decade this Maritime sector has created and developed the infrastructure that promotes entrepreneurship (that is, logistics system and logistics centres, free economic zone), highly qualified specialists were educated, gained experience in cargo storage and transportation sphere, programmes of modern quality management are introduced. Business operators operating in Maritime sector individually initiate branch associations or other joint structures by such means reaching common and individual goals and implementation of economic interests and reaching synergy effect of economic activities. Clustering is recognized as the economy phenomenon of many advanced and rapidly developing countries, clusters operating in many countries promote economic growth, attract innovations, qualified personnel, investments into scientific researches and experimental development, clustering promotes new technologies. Clustering also brings together companies, public and research institutions which social and commercial relations determine their specialization, allow to benefit from the unique and specialized resources and thus, enhances the advantage both of the cluster s members and the whole country's advantage. The cluster as a form of activity does not only change economic structure and potential of a country or a region (district) or a particular city, but also, strengthens capabilities of human, technical, scientific, capital, innovation, partnership and other capabilities the individual members of a cluster. Increased productivity, increased levels of competitiveness and innovative product development and commercialization - these are the results which cluster members can achieve working together. Clustering helps to develop new ideas and businesses, accelerate knowledge and technology transfer and implementation, product development. Clustering helps to improve labour and product quality, technological content; it also helps to create favourable conditions for improvement of the productivity, innovation. It helps to reduce costs of small and medium-sized enterprises, particularly in research and development, and innovation sphere; helps to promote the development of exports, reduce risks and increase the probability of success in choosing new investments, improve the efficiency of research and development processes; helps companies and their representative organizational structures to join the global expertise and innovation networks and to exploit the offered opportunities by the development of higher added value, to increase innovation and competitiveness. 5

7 Clustering as the process and the need and importance of cluster structures have been started analysed already at the end of the nineteenth century. Localization of economic activity ideas can be found in the 19th-century German economist J. H. Thunen works. The focus is given to the value of land and how this affects the agricultural production moving away from the trading place (Šalčius, 1927). Aforesaid ideas are further analysed in the works of A. Marshall. He introduced the concept of industrial districts, highlighting the benefit of economic activities of businesses in small areas (Marshall, 1890). English economist A. Marshall, 1890, in his work Principles of Economics analysed the concentration of specialized industries centred in one area, and called this phenomenon as the industrial districts. He also stated that due to the cost of one unit, innovation activity and growth can have a positive impact on other parts of the system, and the industrial districts as entire unit have to perform better than the individual units. In the middle of the twentieth century, researchers of cluster structures (Isard, 1956; Becattini, 1979) expanded the concept of industrial districts, with emphasis on export-oriented industries in close liaison with other regional industries, cost reduction of production and delivery, the ability to innovate and become the dominant player in the global markets, the importance of the clustering process. W. Isard (1956) described the phenomenon of clustering using the export-oriented industries and their links with other industries in the region. According to him, such a close industrial ties and show the existence of a cluster. In the late 1970, the economist G. Becattini raised the idea of clustering by applying this to northern Italian industrial organization. According to him, the reason to concentrate geographically covers the economic aspects such as the cost reduction of production and delivery, as well as the opportunity to become the dominant player in the global markets, where the ability to innovate is a key competitive advantage. S. Cruz and A. Texeira (2007), M. Porter (1990) highlighted the enormous potential of industrial clusters. This was a major event in the development of the cluster concept because Porter's ideas of cluster successfully made their way to into the areas of science and politics by creating a breakthrough of cluster initiatives in many countries. At the beginning of the twenty-first century, the concept of clustering became synonymous with the knowledge economy. The main argument was that the knowledge-based economy process engines - the technological know-how, innovation and the dissemination of information - develops favourably when such development is localized (Martin and Sunley, 2001). M. Porter (1998), one of the most influential economists who analysed the importance of localisation to economy, stated that the country's leading export companies are not isolated success stories but belong to the most successful groups of competitors of related industries. He called these groups as clusters, i. e., industries related by horizontal and vertical links and networks. 6

8 The idea of clustering in Lithuania was firstly developed by J. Činčikaitė and G. Belazarienė (2001), Business Strategy Institute (Cluster.., 2002), Lithuania's.., 2003) and Č. Švetkauskas (2003). Their works formed the basis for further development of clustering phenomenon in Lithuania. These and later (Jucevičius, 2007, 2008, 2009) studies and research works usually analysed development opportunities of industry clusters (wood, textile, etc.), clusters of services (tourism, etc.). Recently, the scientific literature usually use M. Porter s (1998) formulated concept of the cluster geographic concentrations of interconnected companies, specialised suppliers, service providers, firms in related industries and associated institutions (for example universities, standards agencies and trade associations) which not only compete with each other but also cooperate with each other. Also, the networks that occur within a geographic location, in which the proximity of companies and institutions ensure certain forms of commonality and increases the frequency of interaction. S. A. Rosenfeld (1997) marked the importance of synergy between the organizations. T. Hertog and P. Roelandt (1999) and J. Simmie and J. Sennett (2001) suggested a cluster analysis, looking at them as to the value (cost) development chain. Although clustering aims and goals of policy have not been reached yet in the economies of the countries of the European Union, however in most countries strategic documents they are reasonably presented and moved to the industrial sector development strategies and their implementation plans. Traditionally, starting from a national or regional planning initiatives, top-down method applies to the regional authorities by initiating and developing plans of clusters formation, creation and development and by creating methodology for the cooperation of enterprises in the particular geographical region. However, this does not contribute to the practical cases of cluster development and creation and this does not promote cooperation of enterprises. In order to enhance the competitiveness of enterprises and strengthen the competitive position in the market, cluster formation is increasingly becoming one of the essential conditions for the development of business cooperation and development, in particular the joint initiation of joint projects and the strengthening of mutual trust between the companies. Cluster formation is a dynamic process identified by common attributes and criteria, consisting of successive stages and having different maturity phases. Scientific problem and its level of investigation. In order to objectively reveal the level of the investigation of the problem analysed in this dissertation, the Matrix method of Garrard (2007) was adopted for the analysis of bibliographic data. Application of this method helped to carry out search of relevant publications in thirteen internationally recognized databases of scientific journals and scientific journals: EBSCO, Emerald Insight, Springer Link, Sage Journals, Science Direct, Oxford Journals, Wiley Science, Taylor and Francis, 7

9 ICPSR, electronic catalogue of Martynas Mažvydas National Library of Lithuania, electronic catalogue of Virtual Library of Lithuania, Научная Электронная Библиотека elibrary.ru, Каталог Электронных Ресурсов. The search in English was performed in accordance with eight relevant key word combinations based on the title of the dissertation. If less than 800 articles were found which correspond to the keywords combinations, then after detailed review, there was rejecting of the articles, which do not correspond to the scope and object of the dissertation. The search was conducted according to the title of the scientific article, keywords and summary. Publications of the chosen databases were selected and the results of the search were analysed in the period of 22 February 2014 and 30 May With regard to the data of bibliographic analysis, keyword combination Lithuanian Maritime sector, Clustering, Preconditions, Economic analysis matched one scientific paper prepared by the author of this paper, which was found in EBSCO database. There were four books found which match key word combination according to the keyword combination of Lithuanian Maritime sector, Clustering, Preconditions, Economic analysis, however, on the scientific level they are not 0widely analysed. According to combination of Maritime sector, Clustering, Preconditions, the introductory paragraphs of the scientific articles in many cases discuss the importance of the Maritime clustering or the formation stages of clusters but these articles lack the detailed analysis of clustering causes, conditions, preconditions, risks and barriers. Brenner (2004), Hui (2005), Lorenzen (2005), Hassink and Dong-Ho (2005), Nadaban and Berde (2009) and other authors analysed various stages of the life cycle of the formation of clustering and cluster. Clustering in many scientific publications is often analysed as recognition of certain individual structural elements or signs and connection with causal relationships and linkages while forming a statistical clustering model. It should be noted that there is no single economic approach to analyse the Maritime clustering process. Different authors and different scientific and political contexts differently identify clustering, the importance and stages of cluster development and cluster formation often do not correlate with each other; preconditions, reasons, demand and benefit motives are often treated as synonyms of these concepts; the analysis of preconditions of clustering sector usually is carried out by the evaluation of goals of clusters. This suggests that there is no connectivity and continuity in respect of results of previously published researches. The evaluation of proposed preconditions of clustering sector lacks complexity and completeness; lack of a clear methodology for evaluation of preconditions of concrete clustering sector; scientific works often mistakenly equate sector and cluster and its evaluation continues in accordance with one selected scientific research method or industry groups of different 8

10 countries are called clusters and their economic data are further compared. Economic evaluation of preconditions of Maritime sector clustering is a significant research object of this dissertation. One of the main areas of the dissertation research - Lithuanian Maritime sector clustering preconditions to increase Productivity, Innovations and Competitiveness, factors influencing these preconditions and the level of occurrence of the sector in the clustering process. In Lithuania, research on Clustering and Maritime sector is very fragmentary in comparison with other economic phenomena and scientific problems: J. Činčikaitė and G. Belazarienė (2001), J. Bruneckienė and K. Pukėnas (2008), J. Bruneckienė (2010) and others studied the impact of clusters on the competitiveness of region. Recently the scientific literature (Jucevičius, 2009; Stalgienė, 2010, Porter, 1998; Rosenfeld, 2002; Roelandt and Hertog, 1999; Simmie and Sennett, 2001; Kamarulzaman and Mariati, 2008, etc.) have extensively analysed the clustering processes taking place in the world, the measures to promote clustering; the literature also discusses the business benefits for the individual members of the group and for the state in which the cluster is based on the bottom-up approach. Cluster formation initiatives bottom-up still has not received the proper attention of scientists (Lorenzen, 2005). It is noted that studies which analyse clusters in Lithuania (Jucevicius, 2009; 2012; Jucevicius, Rybakov and Šajeva, 2007; Stalgienė, 2010, etc.) lack focus on the stages of formation of clusters of common features and their isolation criteria, maturity phase identification of clusters. Also it should be noted that the studies analysing clusters in Lithuania (Jucevicius, 2009; Jucevicius et al, 2007; 2012; Stalgienė, 2010 and others) do not pay enough attention to maritime sector of Lithuania which is strategically important and economically viable for Lithuania. However, there are not any scientific publications, which would analyse maritime sector clustering and would conduct economic evaluation of clustering or its preconditions. The main research area of this dissertation is economic evaluation of Maritime sector Clustering Preconditions for increase Productivity, Innovations and Competitiveness. M. Porter (2000a, 2000b, 2003), T. Andersson and G. Napier (2007), T. Andersson et al. (2004) analysed different competitiveness preconditions problems and proposed preconditions methodology. Althrough there is a lack of research where Maritime sector clustering would be analysed as evaluation object of Productivity, Innovations and Competitiveness. So far there is no such preconditions methodology enabling economically evaluate preconditions of the maritime sector clustering. This dissertation seeks to create such methodology and empirically adapt it and verify this model in Lithuanian Maritime sector. This dissertation deals not only with theoretical problems but also with empirical ones. The practical significance of the dissertation research is justified 9

11 by opportunities of application of economic evaluation methodology of Lithuanian Maritime sector clustering preconditions the formulated model can be the basis for making important decisions for Lithuanian Maritime sector on political, managerial and economic issues: to prepare and implement National strategy of Maritime sector clustering to promote Maritime sector organizations of business, academic and public areas to cooperate and to form agglomerated business structures - clusters in order to increase Productivity, Innovations and Competitiveness and stimulating development of the Maritime sector. For cluster-prone organizations, this model is an informative set of meaningful indicators to help make decisions on cluster formation, involvement in the clustering process or a new cluster formation as organizations which are not related by clustering relations cannot use the significant advantages of cluster, such as Productivity, Innovations and Competitiveness. The problem of the scientific research - how comprehensively evaluate preconditions of Lithuanian Maritime sector clustering. Object of the researc - Preconditions of Lithuanian Maritime sector clustering. The aim of the research - to create combined evaluation methodics and to conduct economic evaluation of Lithuanian Maritime sector clustering preconditions. The objectives of the research: 1. To identify and to systematize structural composition of economic activities of Lithuanian Maritime sector. 2. To examine origin, formation and development of demand of Maritime sector clustering and to distinguish Maritime sector clustering preconditions on the increase of Productivity, Innovations and Competitiveness. 3. To evaluate economic significance of Lithuanian Maritime sector to whole Lithuanian economy. 4. According to peculiarities of Maritime sector clustering economic evaluation, to identify research initiatives of Lithuanian Maritime sector clustering and to evaluate them. 5. To create combined economic evaluation methodology of Maritime sector clustering preconditions. 6. To examine the created methodology by economic assessment of the clustering assumptions in the context of Lithuanian Maritime sector. Methods of research: systemic and comparative analysis and synthesis of scientific literature, strategic documents and legislation; statistical analysis of secondary data; empirical research: econometric analysis, expert evaluation and questionnaire survey; mathematical and statistical methods, using of statistical data processing applications: SPSS Statistics (v21.0) and Microsoft Excel (2010). The analysis of scientific literature, legislation and strategic documents was based on systematic (holistic) approach. The first and the second parts of this 10

12 dissertation are dedicated for systematic, logical and comparative analysis of scientific literature, legislation, strategic documents and for synthesis of scientific results. Formulation of scientific conclusions was based on logical induction and deduction methods. The third part of this dissertation presents the analysis of secondary data, questionnaire survey analysis and research by using expert evaluation and data obtained by mathematical and statistical analysis (including data structuring, processing, organization and calculation of statistical indicators) and by using statistical data processing applications: SPSS Statistics (v21.0) and Microsoft Excel (2010). The structure of the Dissertation. Dissertation consists of three parts. The first part analyses the origin, formation, development and economic significance for Lithuanian economy of demand of Maritime sector clustering. The second part of the dissertation analyses the evaluation features of clustering preconditions and conducts the model formation of economic evaluation of Maritime sector clustering preconditions. The third part of the dissertation presents empirical decisions of economic evaluation of Maritime sector clustering preconditions. The structure of the dissertation is determined by the main aims of the dissertation and the objectives set to reach the main aims. The conclusions briefly summarize key findings of the dissertation. Research base and used information sources. While analysing preconditions of Maritime sector clustering, scientific works of Lithuanian and foreign authors were used. In addition, published research results, publicly available strategic Lithuanian and foreign documents and laws governing the Maritime sector and the clustering process were used in this analysis. For the identification of the latest preconditions of Maritime sector clustering, the latest specialised literature, statistical data of Lithuanian Department of Statistics and Eurostat statistics, studies and reports of international organisations (European Commission, 2002; 2003; 2008; Organisation for Economic Cooperation and Development, 2001; 2008; World bank, 2011; 2012; 2013) and specialized research groups (European Cluster Observatory, 2014, Policy Research Corporation, 2009; Ecorys SCS Group, 2009; 2012; Gallup Europe, 2006), specialized publications (Sölvell, Lindqvist and Ketels, 2003; 2006; 2013; Sölvell, 2008) and studies (Lithuania Cluster Concept , 2014; Preconditions and Recommendations for Development of clusters in Lithuania, 2002; Lithuanian Industry clusters Developmental program Study, 2003). Empirical quantitative results were obtained from an econometric evaluation of the collected data, calculating Regional Coefficient, Coefficient of Agglomeration, Rate of Production Specialization and the Geographic Concentration Indicators also Index of Clustering. These indicators were chosen because of their complexity and universality in terms of regional concentration, clustering level, the extent of specialization and the extent of agglomeration. The 11

13 empirical qualitative results were obtained in the expert study where the experts in the first stage conducted the direct evaluation of the preconditions and risks of the Lithuanian Maritime sector clustering and granted weighted estimate. The second stage conducts expert research based on conversation-interview method. Empirical quantitative results were obtained by using questionnaire survey method. The questionnaire was distributed via web channel because it is universally available, the most convenient and the least cost requiring survey tool. The questionnaire was posted on Lithuanian website using specialized Internet access The research was conducted in the period of May - July The Novelty of the Dissertation Purified structure of Lithuanian Maritime sector. The paper provides systematic structure of Lithuanian maritime sector according to groups of industry groups distinguishing three main Lithuanian Maritime sector parts: the Traditional Maritime sector, Coastal and Marine tourism and Fisheries. In order to distinguish the main causal areas of industry groups of Lithuanian Maritime sector, there is additionally provided the structure of Lithuanian Maritime sector where industry groups are connected in accordance with their function and the interconnection is presented. The concepts of Sector, Maritime Sector, Clustering and Precondition are summarized and presented. After identification of uncertainty of the concepts of sector, maritime sector, clustering and preconditions, this paper presents the classification and in accordance with keywords summarized and formulated definitions of these concepts. Sector - this is part of the national economy, with a certain general economic characteristics, combining similar economic behavior codified in economic activities, groups of institutional units. Marine sector - a combination of economic activities (which includes the traditional sectors of marine, coastal and marine tourism and fisheries), a complex combining economic activity groups (shipbuilding, marine works, marine services, marine equipment and facilities maintenance, tourism and fisheries and aquaculture) and assigned / or related business, academic and public sector groups of institutional units. Clustering - this cluster formation process involving the relevant economic activities in groups running vertically and / or horizontally integrated companies and their tendency to concentrate on the general activities of the realization of the value added chain to economic benefits. Precondition - the initial reasoned argument based on assumptions given in evidence based on similar facts. The risks and preconditions of Lithuanian Maritime sector have been distinguished and systematized. This paper identifies and codifies the main Lithuanian Maritime sector clustering preconditions and risks according to their significant features, associated with increase of Productivity, Innovations and Competitiveness. The work systematizes features of preconditions specific to Maritime sector clustering. These features are combined into exploited formulas 12

14 of preconditions; the list made of preconditions is divided into 3 parts in accordance with the impact of preconditions on the increase of Productivity, Innovations and Competitiveness. The risks of Maritime sector clustering are indicated as barriers of increase of Productivity, Innovations and Competitiveness. Clustering risk equivalent is presented for each clustering precondition. By concluding the list of risks and formulas, the same methodical principals were followed as in systematization of preconditions: risks were relatively divided into three parts: increase barriers of Productivity, Innovations and Competitiveness. The economic indicators were set which are significant to evaluation of Maritime sector clustering preconditions. The author of the work created database of results of economic activities of Lithuanian Maritime sector enterprises and periodically added this database with the latest official data announced by Statistics Lithuania and currently the database has got these systematized indexes of economic activities of enterprises : Number of companies acting Lithuanian Maritime sector, Number of workers in these companies, Turnover, Added value (at factor costs), Gross operating profit, Gross investment in tangible assets, R&D investments. According to available data, indicators of Gross margin and Labour productivity are calculated. The average method is used in order to determine which economic activities in the Maritime sector exclude by the economic indicators. In order to identify the Lithuanian Maritime sector clustering key features: the specialization and concentration - used these quantitative indicators and indexes of assessment: the Regional Coefficient, Agglomeration Coeffiient, Production Specialization Index, Clustering Index and Geographic Concentration Indicators: Localization Index, Herfindahl Index, Herfindahl-Hirschman Index, Ellison-Glaeser Geographic Concentration Index. Conceptual combined economic evaluation model of Maritime sector clustering preconditions was designed. Designed conceptual combined economic evaluation model of Maritime sector clustering preconditions is a visual method (diagram) which presents causal relations between factors and stages, which are significant for the problem analysed. The methodology of combined economic evaluation of Maritime sector clustering preconditions is composed. Taking into account the specification of the subject, complexity of the analysed scientific problem and complication of the thesis object, the composed methodology of combined economic evaluation of Maritime sector clustering preconditions includes: Empirical quantitative analysis by choosing econometric estimation method and by calculating the Regional coefficient, Agglomeration Coefficient, Indexes of Production specialization and Geographical concentration, Index of Clustering; Empirical qualitative research - expert evaluation, which consists of two parts: the first part presents ranking of preconditions and obstacles and direct evaluation method, the 13

15 second part presents qualitative research based on conversation-interview method and empirical quantitative pilot study - questioning. The essence of the combined economic evaluation of preconditions of Maritime sector clustering is the systematic attitude towards the integrity and applicability of research methods in order to by the empirical research to get clear and objective data on Lithuanian Maritime sector clustering preconditions and on the basis of that, to make conclusions about the results the benefit or losses of Lithuanian Maritime sector clustering preconditions for country, region, sector, economic activities group, enterprise or related organisations. Complex economic evaluation model of Maritime sector clustering preconditionsis verified in the context of Lithuanian Maritime sector. According to created and described combined economic evaluation methodology of Maritime sector clustering preconditions, the created model was verified in Lithuanian Maritime sector context: conducted evaluation of Lithuanian Maritime sector impact on agricultural economy of the country, distinguished and described methods of the empirical quantitative research, using selected research instruments collected significant data, calculated identifying indexed and indicators of clustering characteristics, carried out estimate weight analysis and ranking of expert Maritime sector clustering preconditions and risks, formulated conclusions on analysis of collected data during the expert conversation-interview, carried out statistical analysis of collected data during empirical research - questionnaire and presented conclusions of data analysis of the pilot research. Limitations of the Research. There are possible inaccuracies in methodology of referring of companies for Lithuanian Maritime sector, uncertainty of the preconditions of clustering concept, subjectivity of expert evaluation and limited expert competence in a certain fields and unreliability of publicly available statistical research data. Continuity of Dissertation Research. In order to perform deeper analysis of empirical qualitative research of economic evaluation of preconditions of Lithuanian Maritime sector clustering in terms of content, it is appropriate to expand the carried Pilot study and by ensuring the representativeness of the study sample, to collect reliable data for the analysis of the research results. It is appropriate to continue periodically to complement the Data base of the main economic indexes of the companies ( units) of Maritime sector in Lithuania, updating the information in accordance with publicly available data of the Statistics Lithuania, it is appropriate to include values of Exports and Imports of the Lithuanian Maritime sector companies. It is planned in the future to create a Methodology for verification of economic evaluation results of formed clusters and it is planned to verify this methodology in the case analysis of Lithuanian clusters. It is appropriate to initiate and maintain Lithuanian Maritime cluster formation and take concrete steps to realize this idea. It is planned in the future 14

16 to conduct analysis of complexity, compatibility and optimization opportunities of Lithuanian Maritime sector clustering, to conduct evaluation of Science, Business and Public sector institutions operating in the Lithuanian Maritime sector It is appropriate to analyse not only Economic but also Social and Political impact on the Country s economy of the Lithuanian Maritime sector. It would be appropriate in the future while conducting research on preconditions of Lithuanian Maritime sector clustering, to evaluate an economic volume of Offshore business operating in the Maritime sector and to evaluate its impact not only on Lithuanian Maritime sector but also on Economic performance of all country. There are available fields of economic evaluation methodology of preconditions of certain complex Maritime sector clustering: 1. This methodology can be applied on the national (regional) level for the preconditions of operating Maritime sector clustering evaluation. It can be applied and for other countries research of preconditions of Maritime sectors clustering. Improved methodology would also works in other countries to evaluate clustering preconditions of Industry sectors but then certain characteristics of industry clustering should be identified, to formulate the clustering preconditions and risks statements to suit a particular industrial sector, to evaluate optimal number of selected preconditions and risks, to select appropriate methods for the analysis of clustering preconditions and risks, to evaluate the need to involve experts into the study and identify current experts and to consider need of concrete industry group in with regard to the establishment of the cluster organization. 2. This method can help to evaluate national (regional) potential and development opportunities of Maritime sector, to distinguish the main factors determining and limiting preconditions of the clustering. 3. This methodology can be applied in order to compare preconditions of Maritime sector clustering in the Baltic sea region countries. 4. The modified methodology could be a reference tool for business, science and public sector entities which evaluate the clustering of industry sectors. Scope of the dissertation. The dissertation consists of 298 pages (257 pages without attachments), 53 figures, 61 table, 17 annexes. 395 references used in Lithuanian, English, French, German and Russian languages. 15

17 CONTENT OF DISSERTATION INTRODUCTION 1. RESEARCH CHARACTERISTICS OF MARITIME SECTOR CLUSTERING PRECONDITIONS 1.1. Maritime sector clustering demand Emergence, Formation and Development Structure and Development Predictions of Maritime sector Peculiarities of Clustering Preconditions Formation Interorganizational Communication Advantages for the Maritime sector Organizations 1.2. Economic Significance of Maritime sector Clustering Economic Significance of Maritime sector Clustering for Lithuanian Economy Characteristics of the Maritime sector Policy based on Preconditions of Cluster Formation The Need for economic evaluation of Clustering Preconditions 2. ECONOMIC EVALUATION METHODOLOGY OF LITHUANIAN MARITIME SECTOR CLUSTERING PRECONDITIONS 2.1. Peculiarities of Economic Evaluation Clustering Preconditions Methods and Indexes of General Clustering evaluation Evaluation Problems and Limitations of Clustering Preconditions in the Maritime sector 2.2. Model formation of Economic evaluation of Maritime sector Clustering Preconditions Creation of Maritime sector Clustering Preconditions Combined economic evaluation Methodology Process and Structure of Lithuanian Maritime sector Clustering Preconditions Combined economic evaluation Model 3. EMPIRICAL SOLUTIONS OF MARITIME SECTOR CLUSTERING PRECONDITIONS ECONOMIC EVALUATION 3.1. Lithuanian Maritime sector Clustering initiatives and their Evaluation 3.2. Verification of Clustering Preconditions Combined economic evaluation Model in the context of Lithuanian Maritime sector Methodology of Clustering Preconditions Combined economic evaluation and the Main principles of Data analysis Evaluation of Clustering Preconditions by calculating Regional Coefficient, Agglomeration Coefficient, Production Specialization Index, Geographic Concentration Indexes and Clustering Index Results and their interpretation of Clustering Preconditions Expert Evaluation The results of Statistical research on Clustering Preconditions and their Interpretation Consideration of the Results of Combined economic Evaluation of Maritime sector Clustering Preconditions CONCLUSIONS REFERENCES LIST OF SCIENTIFIC PUBLICATIONS ON THE TOPIC OF DISSERTATION ANNEXES 16

18 REVIEW ON DISSERTATION CONTENT 1. RESEARCH CHARACTERISTICS OF MARITIME SECTOR CLUSTERING PRECONDITIONS This part analyses the emergence of demand of Maritime sector clustering, formation and development and the significance of Lithuanian maritime sector clustering for Country's economy is evaluated Maritime sector clustering demand Emergence, Formation and Development This part analyses structure and development predictions of Lithuanian Maritime sector, analyses peculiarities of formation of preconditions of clustering, distinguishes inter organizational communication advantages for the Maritime sector organizations Structure and Development Predictions of Maritime sector The concept of Maritime sector is not used by the Statistics Lithuania in the official accounts of the economic activities, this concept is not included into the statistical annual reports of the banks operating in the Republic of Lithuania. Therefore, the Maritime sector concept used in strategic documents of the Republic of Lithuania and legal acts is conditional and strictly regulated. Scientific literature and strategic documents (Lithuanian Dictionary, 2013, Statistics Lithuania, 2011; A value chain..., 2011; ESaTDOR, 2013; Government Resolution No. 786, 2008; the Regional Business..., 2012) the concept of the Maritime Sector interpret in different ways, depending on the author of Strategy document or belonging of an author of the scientific literature to a particular type of organization. According to the extracted significant features of the concept of the Maritime sector, the description of concepts of the sector and Maritime sector to be followed in this paper: Sector - a part of the national economy, which has certain common economic characteristics and combining groups of institutional units of similar economic behaviour, systematized into economic activities. Maritime sector - it is a combination of economic activities (which includes traditional maritime sector, coastal and marine tourism and fisheries) that complexly combines for groups of economic activities (shipbuilding, marine works, marine services, marine equipment and facilities maintenance, tourism, fisheries and aquaculture) assigned and/ or related business, science and public sector groups of institutional units. Figure 1 shows that Lithuanian Maritime sector is divided into three structural parts and this sector is defined in accordance with the EU studies which use economic activities and features used to describe them. 17

19 Maritime sector Fisheries Traditional maritime sector Coastal and marine tourism G Shipping Offshore supply Marine equipment Marine works Marine services Shipbuilding L A C H Inland navigation H Recreational boating G Seaports H F H G C C D H B M N C Exploitation of marine aggregates C Navy and coastal safeguard O G N I R Fig. 1. Structure of Maritime Sector Sections: A - Agriculture, forestry and fishing; B - Mining and quarrying; C - Manufacturing; D - Electricity, gas, steam and air conditioning supply; F - Construction; G - Wholesale and retail trade; repair of motor vehicles and motorcycles; G - Wholesale and retail trade; repair of motor vehicles and motorcycles; I - Accommodation and food service activities; L - Real estate activities; M - Professional, scientific and technical activities; N - Administrative and support service activities; O - Public administration and defence; compulsory social security; R - Arts, entertainment and recreation. Total - 13 sections. Figure 2 provides the systematized structure of the main economic activities of the Maritime sector. Renewable energy sources and electricity production Oil and natural gas production and processing Fossil fuels and quarrying Marine cable and pipeline construction Dikes, ports and canals forming Peat and salt extraction Marine Supply Cargo handling Marine works and offshore supply Machinery and equipment manufacturing and repair Machinery and equipment manufacturing Wiring and installation materials Marine equipment and machineries exploitation Shipping Marine services Technical consulting, engineering and design Motor vehicles and equipment rental Sea port activities Navy and coastal safeguard Marine and coastal shipping Inland waterways Recreational shipping Accommodation Catering Travel, sports and cultural activities Sporting goods for sale and rent Real estate for sale and for rent Coastal and marine tourism Related fields of activities Fisheries and aquaculture Shipbuilding Marine and freshwater fishing Marine and freshwater aquaculture Fish and fish products, wholesale and retail trade Raw Material Processing and preserving forage production Research institutions and research centers Higher education institutions The public sector (national, regional and local) institutions The line and professional associations, consortia Financial organizations Non-profit organizations International Maritime Sector's activities abroad Ships and floating structures Recreational sports and shipbuilding Different types of ship repair and maintenance Fig. 2. The structure of Lithuanian Maritime sector 18

20 In order to distinguish the main causal areas of industry groups of Lithuanian Maritime sector, there is additionally provided the structure of Lithuanian Maritime sector where industry groups are connected in accordance with their function and the interconnection is presented Peculiarities of Clustering Preconditions Formation The interest to agglomerate and geographically spread economic activities was observed at the beginning of the Nineteenth century. The first scientific works related to the studies of demand of economic concentration were published by Ricardo (1817), von Thunen (1826), Launhardt (1882) and Weber (1909) in published journals. Specialized industrial location research are analysed in detail and presented in the works of Marshall (1890). The author noted that clustering of activities in the geographic areas of focus will have a significant impact on the performance of the companies (Hofe and Chen, 2006). These cluster formation conditions can be distinguished. The first - the Geographical proximity of the cluster elements (Doeringer and Terkla 1995; Prevezer and Swann, 1996), which allows agglomerating (in regards of volume and aim) with internal specialization and division of labour force. The second condition is related to Social networks (Roelandts and den Hertog, 1999; Rosenfeld, 2005) which includes global electronic communications network intended to transfer technological knowledge and organize training in groups (Asheim, 1999). The third criterion is related to the Institutional common values and culture of expectations, business climate (trust of informal relationship, cooperation). This allows the creation of new businesses and the formation of the cluster itself (Maskell, 2001; Rosenfeld, 2005). In this research, it is considered that the clustering - is the cluster formation process involving combined companies which operate vertically and / or horizontally in the groups of related economic activities and their tendency to concentrate on the realization of the general activities in Value-added chain by seeking the economic benefits. The Clustering Process in five Steps: Common opportunities / problem identification, the Recognition of need or opportunities for collaboration, Cooperation development or the joint project initiation, Clustering by implementing a number of joint projects and Cooperation formalization. Assumptions, causes or hypotheses are sometimes identified as preconditions. In the case of Maritime sector clustering it is often treated as benefits or economic benefit is evaluated. This paper considers the precondition as the initial reasoned argument based on predictions with regard to reasoned evidence of similar facts. While analysing motives of selecting preconditions of clustering for the increase of Productivity, Innovations and Competitiveness, this paper analyses the relations of Productivity, Innovations and Competitiveness. 19

21 According to the analysis of scientific literature, strategic documents and the analysis of studies, Maritime sector clustering preconditions systematically are combined into three groups (seven conditions for each group), respectively: to increase Productivity, to increase Innovations and to increase Competitiveness and presented in Table 1. Table 1. The description of preconditions of clustering for the increase Productivity, Innovations and Competitiveness. Description of Clustering Precondition I group of preconditions - for the increase Productivity (P) a) By disposing of the general business infrastructure, there is a possibility to reduce operating costs, to increase indexes of productivity and efficiency, to ensure optimal the manufacturing process loads. b) The ability to specialize and focus on the main activity by transferring secondary and additional activities to the sector members who specialize in these activities. c) Due to the migration of qualified specialists within the sector, business entities there are created conditions to use and optimally use internal capacities of human resources. d) By disposing of the general distribution channels, the opportunities are created for sector members to create the overall supply chain or use them. e) Co-operating companies in their respective fields are typical examples of synergy effect. f) Clustering helps to achieve economies of production scale and scope. g) Companies working together are in common marketing, distribution strategy and reduction of logistics costs. II group of preconditions - for the increase Innovations (I) a) Favourable conditions are created for transmission - take over of good practice, to search solutions for solving common problems. b) There emerges an opportunity to reduce various business risks, other costs related to investments, by diversifying these costs between members of business systems. c) During the sector clustering processes, the socialization is promoted and community-based culture is developed between companies. d) In cooperation there is formed favourable conditions for promotion of policy of innovation and the development of innovation. e) In cooperation there is on going promotion of research and experimental development (R&D) and there is an opportunity of commercialization of higher education products (prototype) developed. f) Clustering promotes innovative business creation and development, spin-off business occurring. g) In collaboration, representatives of the clustering can reach higher level of innovation by cooperation in the fields of research and technological development. III group of preconditions - for the increase Competitiveness (K) a) Cooperation gives an opportunity easier, cheaper and quicker to get specialised information about markets, technologies and resources. b) There are created conditions for the best prices to buy and sell high quality products and services. c) Co-operating companies are in a strong bargaining power while searching for new clients and suppliers, dealing with the supply or sales questions, raising and discussing issues relevant to business system at national level, by providing designed applications for financial support or for other favourable business conditions. d) The advantages of geographical concentration of enterprises and access to the shared infrastructure facilities emerge (Port of Klaipėda, infrastructure of rail, roads and ferries). e) The joint forces help easier to enter to new local and international markets, to compete, maintain and strengthen positions in markets, develop channels of distribution of the production/ services, to look for potential users, customers, suppliers. f) Because of the unique intensity of knowledge exchange between members of the business system, innovative ideas are stimulated, new products, services or/ and management systems are created and launched. g) Cooperation between companies increase foreign direct investment opportunities. Table 2 presents systematic Risk groups of clustering barriers to increase Productivity, barriers to increase Innovations and barriers to increase Competitiveness as well as their significant characteristics. 20