Research background: The value of clusters in developing advanced technology products and services as well as promoting regional growth is acknowledged by many policymakers and researchers (Lee et al., 2012). Hence, clusters are identified as enablers of the circular economy and resource efficiency in this study. Companies aim to enhance competencies and create competitive advantages in global competition and this can be achieved through pulling from a common and accessible pool of resources, information and demand for innovation which means that companies can profit from belonging to a cluster. Purpose of the article: The main aim of the article is to overview the scientific literature that addresses the circular economy, identify clusters and their role in the circular economy and suggest how small and medium enterprises could engage in a circular economy through clusters' performance development. Methods: Bibliometric literature analysis enables identifying the latest trends in scientific articles regarding a circular economy and clusters. The analytical hierarchy process (AHP) allows for composing the scheme of the cluster’s competitive advantage within circular economy. Findings & Value added: The findings suggest that resource efficiency is considered to be one of the most important ambitions and clusters can work as enablers of a circular economy for small and medium enterprises (SMEs), gaining a competitive advantage at the same time. Clusters can encourage and provide conditions in which SMEs would turn to a circular economy. The scheme of Cluster's competitive advantage proposed by the author can help cluster's coordinators, policymakers and all the concerned parties to verify the importance of clusters' involvement in the circular economy.
It is notable that the interest in clusters and their role in sustainable regional development are increasing as scholars often review this topic. Valuable observations are made on how the clusters should be researched in order to improve their performance which would result in economic growth both on regional and national scale. Clusters' performance is complicated to evaluate as the measures of the aspects that must be calculated differ and the most appropriate solution to formalize these aspects should be found. Different multi-criteria evaluation methods are suggested by scholars for a quantitative evaluation of performance of a certain phenomenon. This study attempts to present the clusters' performance evaluation by applying the multi-criteria SAW method. Seven clusters from Lithuania and Latvia were examined to serve the purpose of this study. The multi-criteria analysis could be used as a method in further evaluation of clusters' performance for it is comprehensible, easy to apply, helpful in the data evaluation of different measures and it provides adequate results, which is very important in a quantitative analysis. The results suggest that processes are very important in clusters' performance evaluation for clusters which show good results with processes, stay in high positions, whereas clusters which are keeping behind with processes show worse results in their performance. The study still needs to be supplemented by more clusters to obtain specific information and to elaborate on more specific clusters' performance evaluation methods.
This study aims at verifying the validity of cluster efficiency measurement tool. In previous study benchmarking was employed (Tvaronavičienė et al., 2015) IntroductionAccording to Karaev et al (2007), clusters are recognizable as an important instrument for improving SMEs productivity, innovativeness and overall competitiveness through overcoming their size limitations. Although there are many various studies conducted in different countries but a common understanding of the cluster concept has not been generally accepted yet. One of the most prominent authorities in the field is M. Porter (1990), who claims that national clusters are formed by firms and industries linked through vertical (buyer/supplier) and/or horizontal (common customers, technology, etc.) relationships with the main players located in a single nation/state. Later this definition was supplemented by Porter (1998), who added institutions (formal organizations) such as universities. The ability for a country to form an industrial cluster can be related to its international competitive advantage. Reduced input costs of the manufacturers, development of common suppliers, training of professional labor and a technical knowledge spillover effect can be achieved through the formation of clustering (Hsu, 2014). The effectiveness of a cluster is supposed to be increased by facilitating the transmission of knowledge and the development of institutions, which can be achieved through geographical proximity. Another important feature that is stressed by Porter (1998) is encouraging of innovation through enhanced division of labor among companies with physical proximity among numerous competing producers.Questions related to performance of clusters are widely discussed in scientific literature: researchers discuss such aspects as measuring of innovations (Rezk at al. 2015), approaches and methods of cluster analysis (Tvaronavičienė at al. 2015a;2015b), technology transfer processes and driving forces (Tvaronavičienė, Černevičiūtė 2015;Ignatavičius et al.); composition and governance specifics (Branten, Purju 2015;Fuschi, Tvaronavičienė 2016;Bistrova et al. 2014;Lace et al. 2015; Mentelet al. 2016;Raudeliūnienė et al. 2016); participation of start-ups (Laužikas et al. 2015;Tvaronavičienė 2016). Hence, spectrum of questions related to clustering phenomena is wide; efficiency of functioning issues, as it was mentioned above, is still under discussion.This study aims at verifying the validity of cluster efficiency measurement tool. In previous study benchmarking was employed to compare the performance of participating clusters which would enable to improve their results by getting the information about their strengths and weaknesses over other clusters. You can find the "The Cluster Efficiency Study through Benchmarking" in journal Enterpreneurship and Sustainability Issues.The mentioned study was carried out in order to compare the most successful, in a certain extent, clusters in Lithuania. Benchmarking approach was employed as the most precise technique...
This study was carried out in order to compare the most successful, in a certain extent, clusters in Lithuania. Benchmarking approach was employed as the most precise technique of data analysis in given conditions. There were several methods employed in a study, such as an interview for the initial stage of data collection, questionnaire survey as well as multi-criteria analysis in later stages and benchmarking for the final stage of the study as to generalize the results. The research has shown that multi-criteria and benchmarking methods are helpful in determining cluster performance. There might be some inaccuracies regarding the results as there were several questions with information not available for the cluster managers. A great number of elements included in the questionnaire survey may have led to some discrepancy. Benchmarking can help companies in cluster to evaluate their performance in comparison to others and seek for better results. The most successful clusters in Lithuania were studied to be a role model. Benchmarking is a practice which can help clusters to measure their performance as there is no systematic evaluation of cluster excellence in Lithuania.
Th e purpose of this study is to review cluster research and the methodology used to achieve the target. Specifi cally, this research explores the methods that are used in research papers aiming at cluster study. Bibliometrical analysis is used depending on an original database, created by the authors, selected after close review. 33 research papers were taken into consideration, published from 1999 to 2014 in international scientifi c journals. Th e fi ndings indicate that case study is used in many articles refering to cluster research. Other methods, such as analysis, interview, survey, research, equation and others are used to support case study. By analyzing the specifi c methods used in cluster research it is aimed at giving clarity to further research on the concept of cluster. It is well known that rather few research papers were analysed from the methodological point of view. However, this research requires a further analysis with a wider scope of scientifi c literature and works related to clusters.
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