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As the core of “Rise of Central China” strategy, the regional innovation capacity of the Wuhan Metropolitan Area is the key to enhance the innovation ability of central China and even China. High-tech industries are the key driving force to improving regional innovation. Studying the relationship between high-tech clusters and regional innovation capacity helps optimize the spatial layout of regional high-tech industries, upgrade the industrial structure and enhance regional innovation capacity. Based on the panel data of nine cities in the Wuhan Metropolitan Area from 2010–2019, we measure the regional innovation capacity and the degree of high-tech cluster using the super-SBM and locational quotient. Furthermore, we explore the high-tech cluster’s influence on regional innovation capacity by constructing a non-linear panel threshold model and a spatial econometric model. The results showed: 1) The innovation capability of the Wuhan Metropolitan Area shows a “W” type fluctuation upward trend, and the degree of the high-tech cluster is below the quotient level of 1, showing a continuous “M” type trend; 2) There is a non-linear double-threshold effect between high-tech cluster and innovation capacity, and the overall effect of promotion, but there is a marginal decreasing, probably because of the crowding effect or over-competition of the high-tech cluster in some regions; 3) After considering the spatial effect, the impact of the high-tech cluster on the innovation capacity of both local and neighboring regions shows a “U” curve, but the spillover to the neighboring areas is relatively limited. Therefore, to give full play to the advantages of the high-tech cluster, it is necessary to take a long-term view when formulating relevant industrial policies while considering the differences in regional economic development levels and spatial spillover effects.

Clusters being considered as the proponents of innovation, there is a reasonable consensus among researchers and policy-makers that they are the sources of innovation. Therefore, of late, both researchers and policy-makers have increasingly focused on demystifying the factors driving innovation among the firms in a cluster, especially in a high-tech cluster. At the surface level, researchers have identified that the dynamism through interactions of a firm with other firms and associated institutions is one of the key drivers of innovation in a firm residing in a cluster. However, the factors that constitute degree of cluster interactions of firms that determine their innovation levels have not been explored adequately. Bengaluru being one of the highly ranked global hubs of technological innovation in Asia, houses densely interconnected network of high-tech manufacturing firms. It is in the context of Bengaluru cluster that this paper discerned the factors constituting degree of cluster linkages of firms that differentiated the innovation performance among the firms in a cluster. It was found that the ability of a firm to integrate global value chain both vertically and horizontally through extra-cluster linkages determines the innovation performance of a firm in a cluster. [ABSTRACT FROM AUTHOR]

It is generally understood that clusters are the promoters of innovation and therefore, the attention of researchers has been increasingly to discern the factors driving innovation among the firms in a cluster, especially in a high-tech cluster. In this study, we identify the variables capturing the nature of a firm that possibly impact the absorptive capacity of a firm and subsequently ascertain their impact on the degree of interactions between a firm, and other firms and associated institutions within and outside a cluster, respectively. Furthermore, we probe the influence of these interactions as a whole on firm-level innovation. The study was carried out in the context of Bengaluru, which houses the densely interconnected network of innovationintensive high-tech manufacturing firms forming a high-tech manufacturing cluster. Data were drawn from 101 high-tech manufacturing firms belonging to electronics, machine tools, electrical and pharmaceutical industries. Based on the cluster analysis and subsequent graphical analysis on each of the three profiled clusters, it was found that size and origin of a firm have significant impact on the degree of firm's interactions. In turn, higher dynamism of firms in terms of degree of interactions led to higher innovation performance. [ABSTRACT FROM AUTHOR]

The purpose of this study was to develop a methodology for evaluating neighborhood impacts using a Geographic Information System (GIS) and to apply the procedures to the companies of the High-Technology Industrial Cluster of São Carlos. To this end, an evaluation was made of the neighborhood impacts on the physical environment, urban components, quality of life, and urban infrastructure using impact matrices, and the impacts were assigned scores according to type, order, magnitude and duration. Fiftyone companies were examined based on data provided by the companies themselves and on field surveys. The impacts are represented spatially in proportional symbols maps, based on the spatial distribution of the companies in the urban area of the city of São Carlos and the areas of influence of each company. The application of the proposed methodology served to validate it and indicated that the neighborhood impacts caused by the companies of this study are related to each company’s type of activity, its size, and its occupation of the area.

Despite the principal role of high-tech clusters in local planning practice and research, their location and sectoral typology at the granular level have been rarely studied. This study explores the location of U.S. high-tech clusters at a micro-scale by employing firm-level data sets and spatial statistics and examines their sectoral typology using market concentration indices in 52 large U.S regions. The majority (80 %) of the 627 tech clusters we identify have multiple dominant tech industries or are specialized in professional services. Furthermore, while clusters form the major regional hubs for the high-tech economy, they are home to a very small share (7 %, on average) of regional population. U.S. regions also have widely diverse spatial patterns of high-tech clusters; although some regions have scattered clusters, the New York and Northern California high-tech booming regions have clusters concentrated in central business districts (CBDs). Last, U.S. high-tech clusters and the overall high-tech economy are strongly shaped by the location and performance of professional services, i.e., consulting, legal, computer, engineering, and architectural services. • Our international contribution is a novel approach and innovative methodology on quantifying the finest scale location of high-tech clusters. • Most of the 627 identified tech clusters have multiple dominant tech industries or are specialized in professional services. • High-tech clusters are the major regional hubs for the high-tech economy, while home to only 7 percent (on average) of regional population. • U.S. high-tech clusters mostly depend on professional services, i.e., consulting, legal, computer, engineering, and architectural services. • Central business districts (CBDs) and major airport are home to cluster attention to the formation of "Aerotropolis" in the knowledge economy. [ABSTRACT FROM AUTHOR]

The Oulu region in Northern Finland has witnessed a remarkable growth of ICT industries since the 1980s. A town near the Arctic Circle with only 140,000 people (2012) created a high-tech business that employed at its best nearly 16,000 people in the region at the millennium. This article investigates the historical background of this phenomenon, which is not so much an imitation of Silicon Valley, but rather a result of special Finnish and northern characteristics. The most important contributing factors were the University of Oulu, governmental support and the success of the Nokia Corporation. Oulu's strength was the early clustering of the focal actors. Oulu established the first Technology Park in the Nordic countries in 1982. The northern mental environment, Oulu's traditions and many exceptionally active persons also contributed to the phenomenon. The case of Oulu is presented in a larger international context with the help of studies on regional high-tech clusters and the development of the information society. Present and future challenges are also addressed. [ABSTRACT FROM AUTHOR]

This paper provides an account of the emergence and development of a Venture Capital Industry in Israel, and the role it played in the recent successful growth of Israel's high tech cluster. The paper focuses on Israel's Venture Capital Industry, its emergence and operation during the 90s, in which period the number of VC Funds increased from 2 to over 100. The context is the transformation of Israel's high tech industry from the Defense-dominated Electronics industry of the 70s/80s to the 'Silicon Valley' model of the 90s characterized by large numbers of SU companies. During this period the share of high tech in manufacturing industry; and ICT's share in the Business Sector increased considerably attaining one of the highest levels worldwide. Given the importance of Venture Capital an analysis of the waves of new SU companies should be done jointly with an analysis of the emergence and development of Venture Capital (and vice-versa). The approach adopted is Evolutionary & Systemic rather than a focus on 'the operation' of a mature Venture Capital industry, which has been more frequent in the VC literature.We focus on the Dynamics of Venture Capital particularly of the emergence and of subsequent development of the industry. We link these with core Evolutionary concepts such as variation, selection and reproduction (Nelson 1995). The paper discusses the co-evolutionary and dynamic process involving the business sector, technology policies, venture-capitalists, individuals & Startup companies, and foreign linkages. We attempt to show that VC emergence is part & parcel of the reconfiguration of a pre-existing Electronics Industry one involving large amounts of SU and new and powerful links with global capital markets. The main conclusions and policy lessons of the paper are that specific technology policies targeted to the Venture Capital sector can be effective only to the extent that favorable background conditions exist or are created. The main groups of factors, events or sub-processes influencing the emergence process which started in 1993, and subsequent development, are: (1) favorable background conditions; (2) features of the immediate pre-emergence period (1989-92); (3) Targeted Policies which directly triggered VC Emergence (1993-98); (4) Strong VC-SU co-evolution; (5) Global Capital Market Links. [ABSTRACT FROM AUTHOR]