Research On Interactive Cooperation And Innovation Of Enterprise Clusters

One of the most interesting and remarkable phenomenon currently at play in the global economy is the growing number and importance of the enterprise clusters. In a wide array of industries, clustering has enabled many firms to acquire competitive advantages that would have otherwise not been possible. In recent years, ongoing research on enterprise clusters has been conducted from the perspective that regards enterprise clusters as a main strategy for developing regional economies.In this thesis, an enterprise cluster is defined as a group of independent enterprises and organizations operating within a specific industrial field and which form networks based on geographic proximity and dynamic interconnections and interactions. Not surprisingly, given their effectiveness in promoting regional economic development, enterprise clusters have in recent years begun to attract more attention and become a research focus, especially in the fields of economics and management. Most academic work on clusters, however, has so far tended to be carried out by Western researchers who have primarily focused on understanding the experience of developed societies and extending those insights to the world beyond.Prior research on enterprise clusters has tended to focus at the macro-level. With the increasing interdependence of global economy, much attention has been given to the role of clustering as a whole in regional economic development and on economic performance. That said, there is a smaller literature that has looked at the interaction among enterprises and other actors in clusters. As such, the thesis expects to make both theoretical and practical contributions to clustering research at the micro-level, as well as to the development of regional economies.Many clusters are still on a low-level development path and faced considerable barriers. First, in many cases the core competitive advantages of clusters have not yet been sufficiently demonstrated. They are typically classified as operating in labour-intensive industries, employing relatively low levels of technical competency and producing a homogeneous array of products. Second, they exhibit low levels of cooperation. It is argued that clusters assist enterprises to get over obstacles they may not overcome by themselves, such as insufficiency of information, finance and motivation. Current industrial locations and agglomerations are not all the results of optimization, but the coincidence or accident of history. The thesis draws upon the recent research findings of various fields. Knowledge from regional economics, economic geography and institutional economics in particular is utilized. The thesis'objective is to locate the inner cooperative mechanism of clusters and then, analyse how this mechanism influences the pattern of clustering in different contexts. The aim is to find an applicable innovative model of clustering which realistically fits into the current world economic environment. The thesis has practical significance on the development of both current and potential clusters.The starting point of the thesis is the definition and features of clusters. Based on the evolvement of clusters, the thesis analyses barriers clusters confront and their reasons. Moreover, due to geographically proximity, enterprises in clusters tend to share specialised inputs and utilize the same suppliers and services, a situation which to decreases firms'search costs. Furthermore, enterprises within a cluster can share the training costs, and research and marketing facilities. Organizations within clusters can more easily establish and maintain solid relationships with financial institutions, allowing them to more readily draw upon financial resources and acquire loans. Drawing upon this recent research, this thesis analyse relational resources further, and particularly focuses on relationships between competition and cooperation within clusters. Its aim is to have a better understanding of clustering growth and innovation.Based on RBV, RV and Cooperative theories, according to the degree of closeness of all stakeholders, clustering networks can be divided into three layers: core layer, auxiliary layer and outer layer. The relationships among actors are composed of horizontal and vertical relationships. Clustering relations contain informal relations, as well as transaction relations based on the market. Previous research on clusters supported the aforementioned argument and holds that firms'resources can go beyond their boundaries and more relational returns can occur through ties. Recently, researchers have started to emphasize that enterprises and the relationships they form are the central actors of enterprise clusters. The key to the successful development of clusters is to encourage all the stakeholders to collaborate to make their industry more competitive. The innovative performance of a region or nation is largely determined by the degree to which its enterprises interact with other regional or national organizations and enterprises. Clustering can foster such innovation-enhancing interactions. Based on the above analysis, the thesis builds up the interactive and cooperative mechanism, which provides a new view on clustering research.Regional innovation systems has thus recently become of greater interest to researchers. Enterprise clusters lie at the heart of these regional innovative systems. Compared to national innovation systems, regional innovation systems are widely considered to be more beneficial to economic development. This is because most technical innovation happens regionally drawing upon local resources. Not only does geographical proximity make the sharing of tacit knowledge and infrastructure possible, but clustered companies are also more likely to establish connections with universities and other research institutions. This networking tends to make clustered companies more innovative than non-clustered enterprises. The benefits of clustering are clearly seen in its effects on innovation. Co-location can stimulate knowledge transfer, in particular tacit knowledge. The Innovation model building strategies consist of building cooperative and innovative networks, cultivating innovative entrepreneurs and human resources with strong technological capabilities, improving the degree of outward orientation, and establishing an open knowledge environment. According to the situation of current enterprise clusters, the thesis puts forward feasible policy recommendations in terms of interactive cooperation and innovation.The conclusions of the thesis are as following. First, the thesis argues that relations within clusters, in particular the relations between enterprises are critical for clustering development. The thesis discussed interactions between enterprises and stakeholders in the process of the development of clusters. It examines relationship coordination and interaction at different levels within clusters and from a range of different perspectives, including that of the government, universities, research institutes and industrial associations. Second, based on the importance of formal networks, as emphasized by researchers, the thesis argues that networks, especially informal networks, play an irreplaceable role in innovation. Networks should be regarded as relational resources, which, when combined with internal resources, have a positive influence on innovative performance and dynamic development. Enterprise clusters are not only effective tools for enhancing competitiveness, but also contribute toward the building of a new model of regional economic development. Only through a variety of interactive forms can innovative clusters maintain competitive advantage. Finally, on the aspect of theory, the thesis extends the RBV theory and emphasizes the importance of the combination of internal and external capabilities. From a resource-based view, the thesis argues that innovative performance emanates mainly from internal and relational resources arising through the interaction of different actors. The thesis also establishes a theoretical model of innovation within enterprise clusters.