Research On Aggregation Degree And Effects Of High-tech Industrial Clusters

With the acceleration of economic globalization and regionalization，agglomerationas an objective phenomenon has become an important issue of the academic research. Inthe late20th century，high-tech developed rapidly, brought in many success cases ofhigh-tech industry cluster, such as U.S. Silicon Valley. The successful model ofhigh-tech industry cluster caused high attention by international economic organizations,governments and local authorities, they all strongly advocated local industry clusterstrategy and promoted establishment of High Technology Development Zones. Basedon the qualitative research, people prefer to quantify the various factors for empiricalevaluation. Therefore, research on aggregation degree and effects of High-Techindustrial clusters has far-reaching theoretical significance and practical significance.Based on the review of domestic and foreign industrial cluster theory andevaluation research, paper describes the concept of high-tech industry cluster firstly, andthen proposes method for evaluating the cluster’s agglomeration degree andeffectiveness through building high-tech industry cluster measure system.For measuring aggregation degree of high-tech industrial clusters, paper choosesspatial aggregation of cluster, scale specialization, internal correlation and innovationholds as four first level indicators, and twelve factors as second level indicators, thenconstructs aggregation degree evaluation criteria and system. For further, achieves acomprehensive measure of the concentration degree of high-tech industry with theweight method.In order to have a comprehensive assessment of the high-tech industrial clustereffect, paper selectes ten aspects as evaluation index around factors of clustereffectiveness to identify and measure the cluster effect. The factors involving inhardware conditions, internal concentration degree, innovation capability andsocial-cultural environment.On the basis of the above studies, paper explores the development trend ofhigh-tech industrial clusters for further. In this part, the thesis introduces Boston matrixinto the trend recognition of industrial clusters for the first time. According to thedifferent combination of cluster’s aggregation degree and effectiveness discussed, the trends of high-tech industrial clusters can be divided into four kinds as a star cluster, theTaurus cluster, a question mark clusters and thin dog cluster. Followed a similar method,it can be deeply obtained four characteristics trends of development. These trendsclassification reflects the phase characteristics of industrial clusters, and provides a goodreference for scientific evaluation and appropriate development strategies. Then, papersums up five point promotion strategies to promote the development of high-techindustrial clusters.Finally, paper conducts an empirical analysis of high-tech industrial clusters inShandong Province. With time series data measurement, study founds that the high-techindustrial cluster in Shandong Province is still in the Taurus cluster. Its concentrationdegree is not high and the cluster effect is also not played fully. To achieve long-termeffective development, Shandong Province should continue to increase the clusterconstruction investment, improve the capability of independent innovation and so on.The main text is divided into eight chapters. Chapters III, IV and V are the focus ofthe paper, especially Chapter V which is also the key innovative part of the thesis.Innovative work mainly in the following areas: the building of aggregation degreemeasurement module and evaluation system for high-tech industrial clusters;description on elements and its patterns with industrial clusters effect; establishment ofhigh-tech industrial cluster effect evaluation system; provision of cluster matrix andtrends classification of high-tech industrial cluster development based on aggregationdegree and effectiveness.