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Because of the rapid progress of global value chains (GVCs), it is worthwhile to study their impact on innovation. This study aims to explore the impact of GVC position of high-tech industries in the developing-country context of China on innovation performance; it also aims to explore the moderating effects of industrial agglomeration (specialization agglomeration and diversification agglomeration) on the relationship between GVC position and innovation performance.

The study is based on data gathered on Chinese high-tech industries in 30 provinces from the 2005–2015 period. The econometric analysis relies on merged data from the China Premium Database and the Trade in Value Added 2018 Database.

The regression results show that GVC position of China’s high-tech industries significantly affects their innovation performance, and both specialization agglomeration and diversification agglomeration significantly enhance the positive relationship between GVC position and innovation performance of China’s high-tech industries. After dividing the country into coastal and inland regions, new findings appear.

This study highlights the importance of GVC position and its effect on innovation performance of China’s high-tech industries. It contributes to the literature on the relationship between GVCs and innovation by elaborating on the moderating effects of industrial agglomeration on this relationship.

This paper aims to examine the different impacts of six variables on firm technological innovation performance in different high-tech industries in China. Through a comparative analysis of data about growth enterprises market board (GEM)-listed companies, this study attempts to get some conclusions, to help firms in different high-tech industries use resources more rationally and to improve technological innovation performance more effectively.

This paper constructs semi-parametric models based on the relevant data of GEM-listed companies during 2010 to 2015 for different high-tech industries. These models can ensure that the influencing factors of firm technological innovation performance are no longer restricted to a particular aspect but can provide a comprehensive comparative analysis of the effects of factors on firm technological innovation performance in different high-tech industries.

The empirical results show that R&D expenditures have a significant positive impact on firm technological innovation performance in most high-tech industries, but not in electronic and communication equipment manufacturing industry; R&D personnel investment and government subsidies have significant positive impacts on firm technological innovation performance in knowledge-oriented industries; technology diversity has a significant positive impact on firm technological innovation performance in technology-oriented industries; the proportion of exports shows an inverted U-shaped relationship with firm technological innovation performance in electronic and communication equipment manufacturing industry, while firm size shows an inverted U-shaped relationship with firm technological innovation performance in general equipment manufacturing industry; and the effect of semi-parametric model fit is superior to the general parameters model.

Drawing on the resource dependence perspective, this paper is the first to consider a comprehensive treatment of differential effects of internal resources (R&D personnel, R&D expenditure), external resources (government subsides) and firm characteristics (firm size, export ratio) on firm technological innovation performance in different high-tech industries in an emerging country, in particular in contrast to previous studies that have focused on a single industry or taken the type of industry as a control variable. In addition, most studies about the determinants of firm innovation performance are based on survey questionnaires, which may introduce large subjective errors. Setting the relationship between variables in advance may also introduce fit error when using a general-parameter model. Semi-parametric regression which is used in this paper is able to prevent this shortcoming effectively. When constructing a regression model, this can be exempted from the formal constraints, thus estimating data more accurately and ensuring superior fit.

This study aims to analyze the moderating effect of managerial discretion on the relationship between cross-border knowledge search and the high-tech firms’ innovation quality in a global health emergency and addresses the following issues: the influence mechanism of different types of cross-border knowledge search on the high-tech firms’ innovation quality in a global health emergency; and the moderating role of different dimensions of manager discretion on the above relationship.

Based on the firms’ strategy selection methods, the authors divided cross-border knowledge search into three aspects, namely, breadth, depth and balance, and analyzed the impact of cross-border knowledge search on the innovation quality of high-tech firms in a global health emergency, taking managerial discretion as the moderating variable, and divided it into position rights, pay rights and operation rights according to the key rights of firms’ strategic management. Furthermore, the authors constructed a theoretical model, and for an analysis sample, the authors collected data from Chinese high-tech firms from 2013 to 2021.

The empirical results show that there is an inverted U-shaped relationship between cross-border knowledge search breadth, depth and balance and the innovation quality of high-tech firms. The position rights, pay rights and operation rights of managerial discretion have partially significant moderating effects on the relationship between cross-border knowledge search breadth, depth and balance and the high-tech firms’ innovation quality.

Considerable literature has grown around the theme of the impact of knowledge search on the firms’ innovation quality. Nevertheless, only a few studies draw on the combination of global health emergency, cross-border knowledge search and the innovation quality; in particular, no literature has analyzed the relationship between the three from the managerial discretion perspective. Exploring the above relationships has great theoretical value for enriching and improving knowledge management and innovation management theories and provides a theoretical basis and practical support for high-tech firms to face challenges of a global health emergency and to break through the innovation dilemma.

The purpose of this paper is to determine how high-tech firms should choose between independent research and development and technology introduction as well as to ascertain the effects of the three elements of competitive dynamics on the evolution of innovative behavior-based decisions and competitive results.

This paper describes the construction of an evolutionary game model and a multi-agent-based model of innovative behavior-based decisions by heterogeneous high-tech firms. The models are used to analyze the evolution path and evolutionarily stable strategy of innovative behavior-based decisions. In addition, multi-agent-based simulation is used to gain insight into the effects of competitive dynamics on the dynamic evolution of innovative behavior-based decisions.

This paper reveals four evolutionary equilibrium states of the innovation behavior-based decisions of high-tech firms. Based on the findings, these overall evolutionary trends are not affected by the timing of competitive market entry or the intensity of competition. In addition, simulated evidence is added that the timing of competitive market entry is an important factor affecting market-leading innovative strategies and dynamic competition results, and competition intensity is closely related to the evolutionary speed of innovation behavior-based decisions.

The key contribution of this paper is its new view of innovative behavior-based decisions from a competitive dynamics perspective. The new competitive dynamics-based framework for innovative behavior-based decisions of high-tech firms proposed in the paper can resolve the problem of obtaining a sustainable competitive advantage for high-tech firms in a competitive dynamics context.

For the studies whose purposes are to evaluate the relationship between industrial characteristics and innovation activities of the enterprises, there are some limitations in the measures of industrial characteristics and using traditional statistical techniques. The purpose of this paper is to investigate the relationship between industrial characteristics and innovation capabilities within Chinese high-tech industries using grey system theory. The research results show that grey system theory is suitable to investigate the relationship between industrial characteristics and innovation capabilities within Chinese high-tech industries.

This paper proposes the measures of industrial characteristics and innovation capabilities of high-tech enterprises. First, based on the data on Chinese large and medium-sized high-tech enterprises for the period of 2011-2013, this paper applies grey relational analysis to identify the relatively most important indexes on affecting innovation capabilities of Chinese high-tech enterprises. Second, based on the results from grey relational analysis, this study draws a ranking of the five Chinese high-tech industries in terms of innovation capabilities by grey decision making. Finally, based on the results from grey decision making, this study applies GM (0, N) model to investigate the relationship between industrial characteristics and innovation capabilities within Chinese high-tech industries.

The results of this study show that in the evaluation indexes system of innovation capabilities of high-tech enterprises, personnel in R & D institutions, R & D personnel, internal expenditure on R & D, expenditure on new product development, expenditure on technology imports, expenditure on technology renovation, and expenditure on technology assimilation and absorption are relatively most important elements affecting innovation capabilities of Chinese high-tech enterprises. In addition, the two top ranking on innovation capabilities are manufacture of electronic equipment and communication equipment, and manufacture of medicines. At last, the findings indicate that in the measures of industrial characteristics, the three top ranking on affecting innovation capabilities of Chinese high-tech enterprises are R & D intensity, technology absorption intensity of indigenous high-tech enterprises and foreign-invested enterprises size. The opening level is in the middle position. Technology intensity, market concentration, and state-owned enterprises size are the three bottom ranking on affecting innovation capabilities of Chinese high-tech enterprises.

This study has some limitations. First, this study is limited to Chinese high-tech industries. The findings may not be applicable to other countries’ high-tech industries. Further studies with other countries’ high-tech industries could be extended and examined how industrial characteristics affect innovation capabilities of the firms in these industries. Second, the measures of industrial characteristics proposed in this study are somewhat theoretically weak. In the future, the authors will further improve the current analysis, and develop the measures of industrial characteristics. Finally, with the advent of the more data with the consistent statistical coverage released by China’s National Bureau of Statistics during the more continuous years, other methods, such as panel data regression model in econometrics could be used to evaluate the relationship between industrial characteristics and innovation capabilities within Chinese high-tech industries. By then, the scholars can compare the results from grey system theory and those from panel data regression model in econometrics.

Appropriate industrial environment is favorable for Chinese high-tech enterprises to feed their innovation capabilities. Scientific evaluation on the relationship between industrial characteristics and innovation capabilities within Chinese high-tech industries is of great significance for Chinese high-tech enterprises in exerting technological catch-up and promoting their competitive advantage. The purposed measures of industrial characteristics and innovation capabilities of high-tech enterprises in this paper, and combined methodology based on grey system theory could be applied to evaluate the relationship between industrial characteristics and innovation capabilities of Chinese high-tech enterprises.

This paper proposes the measures of industrial characteristics and innovation capabilities of high-tech enterprises, and uses grey system theory to evaluate the relationship between industrial characteristics and innovation capabilities within Chinese high-tech industries.

The study aimed to analyze the influence of network embeddedness on the innovation performance of high-tech enterprises in Guangdong Province.

A conceptual model of the influence of network embeddedness on the innovation performance of high-tech enterprises in Guangdong province is established, which takes the business model as the mediating variable and political association as the moderating variable. Multivariate statistical analysis and the MacKinnon confidence interval method were used to analyze 418 questionnaires.

The results show that both relational embeddedness and structural embeddedness have significant positive effects on the innovation performance of high-tech enterprises in Guangdong Province. The business model has a partial mediating effect between relationship embeddedness, structure embeddedness, and innovation performance of high-tech enterprises in Guangdong Province, respectively. Political relevance has a significant negative moderating effect on the relationship between the relationship embeddedness and innovation performance of high-tech enterprises in Guangdong Province, but the moderating effect on structural embeddedness and innovation performance of high-tech enterprises in Guangdong province has not been verified.

The study of this paper also has some shortcomings: very few data research samples exist; the external factors affecting the performance of high-tech enterprises in Guangdong Province need to be further refined. The research scale needs further improvement.

In this paper, embedding theory, transaction cost theory, resource dependence theory, rent-seeking theory, new institution theory and uncertainty management theory were integrated by system attempt to reveal the mediating and moderating roles of business model and political relevance, respectively, between network embeddedness behavior and entrepreneurial innovation performance of high-tech enterprises. The research conclusions expand the relevant research in the field of entrepreneurial innovation. At the same time, the research results provide theoretical support and reference for the innovative growth of high-tech enterprises and government behavior decision-making in Guangdong province.

Network embeddedness will have a profound impact on the entrepreneurial innovation performance of high-tech enterprises. Existing research has overlooked discussing this issue from the perspective of internal and external influencing factors within the enterprise. Therefore, this study addresses this issue by (1) introducing the business model as the mediating variable from an internal perspective of the enterprise, (2) introducing political association as the moderating variable from an external perspective of the enterprise and (3) 418 original questionnaires of high-tech enterprises in Guangdong Province were used to test the effect of the study variables.

Innovation strategy is critical for firms to achieve success in the market. However, relatively little is known about what factors promote the development of innovation strategy in high-tech new ventures. The purpose of this paper is to address this gap by developing and examining the theoretical model that links effectuation to innovation strategy through opportunity shaping in high-tech new ventures.

The proposed theoretical model is developed by integrating the effectuation theory, innovation strategy literature and opportunity literature. Empirical data were collected from 212 entrepreneurs and top executives in Chinese high-tech new ventures through a survey. Baron and Kenny’s (1986) mediation and moderation model assessment procedures are used to analyze the data.

The empirical results indicate that effectuation has a positive effect on innovation strategy and opportunity shaping. Opportunity shaping has a positive effect on innovation strategy, and its effect is positively moderated by competitive intensity. The author also finds that opportunity shaping plays a fully mediating role in the relationship between effectuation and innovation strategy.

These findings enrich innovation strategy research and advance the effectuation theory by providing empirical evidence of the impact of effectuation on innovation strategy in high-tech new ventures. The findings also contribute to a growing stream of research on opportunity and integrating opportunity shaping into a more complete framework of innovation. Moreover, this research provides deeper insight into the missing links between effectuation and innovation strategy in high-tech new ventures by uncovering the mediating role of opportunity shaping.

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.

High-tech enterprises, as the national innovation powerhouses, have garnered considerable interest, particularly regarding their technological innovation capabilities. Nevertheless, prevalent research tends to spotlight the impact of individual factors on innovative behavior, with only a fraction adopting a comprehensive viewpoint, scrutinizing the causal amalgamations of precursor conditions influencing the overall innovation proficiency of high-tech enterprises.

This paper employs a hybrid approach integrating necessary condition analysis (NCA) and fuzzy-set qualitative comparative analysis (fsQCA) to examine the combinatorial effects of antecedent factors on high-tech enterprises' innovation output. Our analysis draws upon data from 46 listed Chinese high-tech enterprises. To promote technological innovation within high-tech enterprises, we introduce a novel perspective that emphasizes technological innovation networks, grounded in a network agents-structure-environment framework. These antecedents are government subsidy, tax benefits, customer concentration, purchase concentration rate, market-oriented index and innovation environment.

The findings delineate four configurational pathways leading to high innovative output and three pathways resulting in low production.

This study thereby enriches the body of knowledge around technological innovation and provides actionable policy recommendations.

This paper compares four external technology acquisition channels' (foreign technology transfer, exporting, inter-industry R&D spillover and domestic technology transfer) contributions to Chinese high-tech enterprises' innovation in the moderating role of absorptive capacity (AC).

Using technological catch-up theory and China Statistics Yearbook on High Technology Industry, this research investigates 16 Chinese high-tech industries from 2004 to 2015 via negative binomial regression.

The results show that indigenous knowledge transfer improves foreign-funded enterprises' (FFEs) innovation, while transnational knowledge transfer is the main channel for state-owned enterprises' (SOEs) technology acquisition. AC strengthens the positive relationship between transnational knowledge transfer and innovation in SOEs and improves FFEs' innovation and exported tacit knowledge absorption.

This study contributes to the literature on external technology acquisition (ETA) and innovation by examining the different mechanism of ETA instead of isolated strategy considering the AC and ownership structure of Chinese high-tech enterprises, which enrich the technological catch-up theory.