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This paper aims to identify the influence of innovation network and technological learning on innovation performance of high-tech cluster enterprises.

Using a questionnaire, data are collected from Dalian High-tech Industrial park in China. In addition, structural equation model is used to identify the influence of innovation network and technological learning on the innovation performance of high-tech cluster enterprise.

The findings of this study show that the centrality of network location and the strength of the network relationship have a direct positive effect on technology acquisition, technology digestion and technology exploit of high-tech cluster enterprises. Meanwhile, technology acquisition has a direct positive effect on technology digestion, technology digestion has a direct positive effect technology exploit, and technology exploit has a direct positive effect innovation performance of high-tech cluster enterprises.

To improve innovation performance, high-tech cluster enterprises should not only nurture and optimize innovation networks but also improve technological learning ability.

This paper empirically supports the significant influence of innovation network and technological learning on innovation performance. While the results provide guidance for researchers and practitioners, it also adds value to innovation-related research.

The purpose of this paper is to focus on selection of a location which can widely influence business strategy planning and operation profit.

In this paper, the relationship between location strategy and clustering is primarily shown by obtaining location decision criteria and the impact of high‐tech firms with the decision‐making trial and evaluation laboratory (DEMATEL) method. Then, analytic network process (ANP) method is used to explain the value and benefits from cluster location.

The authors study decision‐making for location selection of high‐tech firms in Hsinchu Science Park. The example is based on two dimensions including network effect and transaction cost. Network effect plays a more significant role than transaction cost for this example location selection of high‐tech firms in Hsinchu Science Park. The Science Park is surrounded by entrepreneurial spirit, a significant talent pool, and support infrastructure.

This paper explores how high‐tech managers make their decisions on location strategy in Science Park.

The authors found that cost and benefit factors of network effect dominate the major decision‐making in selection of location and has direct impact on strategic intent. They also have shown that the DEMATEL and ANP approaches are valuable for evaluating this situation.

Over recent decades, talent agglomeration has emerged as a critical topic for scholars, businesses and government officers. Innovative ability is a core competition for high-tech talents. In China, low innovation is the bottleneck, as the high-tech industry usually cannot provide sufficient support for the continuous needs of innovative talents. To enhance the continuous support of talents, it is important to obtain the mechanisms of talent evaluation and flow in high-tech industry. Exploring the incentive factors influencing the scientific and technological personnel, adjust the layout of talents and promote the rational agglomeration. It’s significant to realize the regional economic development.

This study proposes an assessment model using the multi-criteria decision-making method of analytical hierarchy process (AHP) to determine the weights of incentive factors and a nonlinear programing model, from micro, meso and macro perspectives of individual, organizational and social incentives by adopting Maslow’s hierarchy of needs theory, Kurt Lewin’s field theory and Lee’s push-pull theory. After the literature review and interviews with 14 experts, this study produced a research framework and a pairwise comparison questionnaire. In addition, the relative quantitative weights of 3 main categories and 15 indicators are identified and ranked based on the AHP method.

The results demonstrate that the most important dimension is the individual, and the top three highest weighted factors are job satisfaction, sense of working accomplishment and interpersonal relationships. The discussion in this study showed that the proposed model is rational and acceptable to motivate high-tech innovation talent (HTIT) agglomeration for high-tech enterprises, universities, government and start-ups.

The pairwise comparison using the AHP method is limited to expert opinions, which are considered comparatively subjective. The number of incentive factors should be increased, as some indicators may have been omitted from the AHP model.

According to the results, some suggestions can be recommended to corporate executives, HR managers and government officers to attract and retain high-tech talents and further to improve industrial clusters and economic development.

This paper derives a relative ranking of importance based on the opinions of experienced HR specialists, high-tech talent, scholars and government official, and assesses the consistency of results. The ordering represents the importance of indicators and sub-indicators of two levels from respondents’ perspectives in an industry cluster background. The study, focusing on the high-tech industry in China (which is a developing country), offers a unique view, as earlier studies mainly collect data from developed countries.

This paper aims to evaluate whether the integration of smart specialization strategies (S3) into clusters significantly impacts their efficiency for countries that still do not implement this policy. This study tests three effects: whether the kind of policies envisaged through an S3 strategy impacts cluster’s efficiency; whether this impact changes with the technological intensity of the clusters; to determine which S3 is more suitable for sub-clusters at different levels of technological intensity.

The Mexican economy is taken as case of study because it has a proper classification of its industries intro Porter’s cluster’s definition but still does not adopt the S3 policy. Through data envelopment analysis (DEA), this study evaluates the cluster’s efficiency increment when variables representing the S3 elements are included.

The results show that strategies following the S3 had a significant impact in all clusters, but when clusters were classified by technological intensity, the impact on efficiency is higher in clusters in the medium low-tech group.

According to the results in the DEA, it can be concluded that these S3 strategies have the potential to increase the clusters’ productivity significantly. These results make convenient the adoption of the S3 policy by countries that already count with a properly cluster definition.

These findings contribute to the lack of studies that analyze the join implementation of S3 on clusters.

The purpose of this paper is to ascertain the factors that influence the decision of a firm in a cluster to patent its inventions.

This study adopts a stratified random sampling technique to choose 101 sample firms from the identified population of firms in a cluster. Further, it uses the primary data collection method to collect data from sample firms through semi-structured questionnaires and in-depth interviews with the top level management of the sample firms. Furthermore, it carries out binary logistic regression analysis to primarily examine the influence of capability and willingness factors of a firm on the propensity of a firm to patent its inventions.

The paper corroborates from the results of the binary logit model that invention capacity has a significant positive impact on a firm’s propensity to obtain patents. In addition, the absorptive capacity of a firm above a certain threshold is likely to have a significant positive influence on the decision of a firm to patent its inventions. On the one hand, between the two motivator factors conventional motivators and strategy related motivators, conventional motivator factor has a significant positive influence on a firm’s propensity to obtain patents. On the other hand, both the de-motivator factors (time, market and cost constraints and procedural issues) have a significant negative influence on a firm’s propensity to patent its inventions.

This paper makes a key contribution to the existing literature by empirically validating the influence of capability of a firm in terms of its invention and absorptive capacities, and willingness of a firm constituting motivator and de-motivator factors, on the decision of a firm to obtain patents, in the context of a firm in a high-tech manufacturing cluster in a developing economy.

The purpose of this study is to discuss how ethnicity and gender influence high-tech entrepreneurship in the Cambridge cluster emphasizing homophily and how and why bridging and bonding ties are created in moving individuals from the periphery to cross the threshold into acceptance.

The authors present findings on the micro-dynamics of ethnicity and gender in high-tech entrepreneurship underpinned by homophily. The authors discuss how ethnicity and gender influence who enters and stays in high-tech entrepreneurship university spinouts. Through an entrepreneurial narrative qualitative approach, the authors explore how and why bridging and bonding ties may be created and the challenges for those at the periphery to cross the threshold into acceptance. The study adopts an entrepreneurial narrative qualitative approach using interviews with individuals associated with the Cambridge cluster.

The authors add to the entrepreneurship literature by responding to the call for multiplexity within homophily, and the research indicates that homophily strongly influences who enters and who leaves the cluster based on bridging and bonding ties. The findings address the need for more focused understanding of entrepreneurial clusters and how mechanisms can be developed to create an environment to nurture both bridging and bonding ties. It is possible for an entrepreneurial cluster to be perceived as attractive and thriving while being homophilous. Ethnic individuals and women continue to struggle to gain acceptance in the Cambridge cluster.

Interviews were conducted by one person – an ethnic minority female – for continuity of all interviews. Yet as many of the participants were not minorities, it is possible that an interviewer who was not an ethnic minority may have elicited different narratives.

The study adds to the entrepreneurship literature by focusing on multiplexity within homophily in examining the dynamics of homophily in the context of the Cambridge cluster and the significance of nurturing bridging and bonding ties. The research comments on implications for practice among three interlinked but autonomous groups: first, the individual entrepreneurs; second, the networks she/he belongs to; third, the university as both fertile ground for entrepreneurship and an educational institution where entrepreneurship education is engaged in for encouraging and supporting spinouts.

The aim of this paper is to highlight the importance of industrialization and its role in realizing technological innovation leading towards economic development. China has made a 15‐year plan to develop an innovation driven economy, for which it requires a strong and a structured industrial base. An overview of China's industrial strategy has been provided, followed by the challenges and the possible measures needed to be taken in order to achieve its long‐term goals.

Phenomenology, exploratory research and inductive approach for analysing management of technological innovation, industrial clusters and economic development, and, China's innovation plan.

China has emerged as the fastest developing economy and is currently in the transition stage from factor driven to investment driven. In order to stabilize and move towards the investment driven and then to the innovation‐driven stage, China requires a strong industrial base. In order to do so, China needs to cope with the challenges of: a weak system of intellectual property management: lack of skilled and technical labour and adequate financial resources: slow pace in competence and competitiveness upgrading: a weak educational system: industrial pollution; and, lack of basic research.

The paper serves as a guide to students and researchers by presenting a summary of global trends regarding technological innovation, industrial clusters, and China's industrial policies to develop an innovation driven economy.

The purpose of this paper is to categorize industrial clusters, and then compare three industrial clusters of three countries from the perspectives of hard environment, soft environment, factors from supply and demand sides, and the network mechanism.

Data were collected through interview with cluster coordinators. Qualitative case studies were conducted.

The center of excellence behaves well in nearly all aspects, while the spatially narrowly distributed specific center of innovation mainly exploits benefits from its concentrated sector. For the Chinese comprehensive technology incubator, relatively limited geographical space and broad sectorial distribution endow it with unclear strengths, implying the inadequacy of interconnectedness and industry relatedness mentioned by Porter.

Data were collected mainly from cluster coordinators, implying further data collecting and more comprehensive analysis.

It only makes sense to compare industrial clusters that are comparable with each other. Elements must be matched to facilitate the network interactions, and hence the innovation performance of clusters.

This paper contributes to the theoretical basis through it analyzing and clarifying the scales to measure industrial clusters, and answers the question: what is the situation of industrial clusters behaving in several aspects including hard environment, soft environment, supply, demand, network interactions and innovation performance?

This paper aims to examine a cluster-based strategy implemented in the German federal state of North Rhine-Westphalia under the 2007-2013 “Regional Competitiveness and Employment” programme. Departing from traditional discretionary approaches, a substantial share of the funds was now allocated on a competitive basis. The authors analyse the resulting distribution of funds across stakeholders and sub-regions and try to assess the pros and cons of this process, which constitutes a novel delivery system for cluster policies.

Following a literature review, the paper applies two sets of regression models to explain the distribution of funds under the new policy delivery system. Interviews with stakeholders provide evidence on the efficacy and efficiency of the competitive funding process.

The changes introduced in the 2007-2013 funding period benefit universities and research organisations, as well as intermediary organisations, whereas the private sector and especially small firms capture a rather small piece of the pie. Contrary to the “innovation paradox” hypothesis, structurally weak sub-regions did not lose out in state-wide funding contests. The presence of universities with an overall high volume of third-party funding is the key variable explaining the spatial distribution of funds. This interview evidence identifies the duration of the selection process and its administrative complexity as main weaknesses, which the authors attribute to bureaucratic rationality on different levels.

This is the first analysis of a competitive funding scheme at the sub-national level, using the German federal state of North Rhine-Westphalia as a case study. It sheds light on the mechanisms of funding allocation in the 2007-2013 funding period of the European Union’s cohesion policy, which was reoriented towards supporting regional competitiveness and employment in response to the Lisbon Agenda. While competitive funding is still seen as mobilising regional stakeholders and improving the quality of projects and the selection process, these findings highlight administrative complexity as a main deficiency, which has partly been addressed in the 2014-2020 funding period.