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In the highly competitive environment of the high-tech industry, leadership roles are often filled with numerous challenges and stressors. Success in the workforce requires a combination of high emotional intelligence and a connection to workplace spirituality. This study aimed to compare demographic differences among high-tech leaders regarding emotional intelligence, workplace spirituality, and career success. It also sought to examine the relationships and effects of emotional intelligence and workplace spirituality on career success, as well as the moderating role of workplace spirituality in these relationships. A survey was conducted with 139 leaders from various high-tech companies in Taiwan. The results showed that male leaders demonstrated higher levels of self-awareness and self-motivation in emotional intelligence, while leaders with higher education levels exhibited greater self-awareness and empathy. Additionally, both emotional intelligence and workplace spirituality were significant predictors of career success. Notably, workplace spirituality moderated the relationship between emotional intelligence and career success. The implications of this study highlight the importance of enhancing emotional intelligence and workplace spirituality to foster leaders' career success and gain a competitive advantage in the high-tech industry. [ABSTRACT FROM AUTHOR]

Employee turnover is an unavoidable part of business development, costing important human resources and impeding long-term growth and strategy implementation. To maintain a steady workforce, businesses must prioritize understanding and addressing this issue. The objective of this study is to examine the impact of leadership style, career development, and work stress on turnover intention in the high-tech industry and to investigate the moderating role of psychological contracts in these relationships. The sample consists of 380 employees of the R&D departments in high-tech companies in Shenzhen, Guangdong province, China, mainly engaged in the electronic information, advanced manufacturing, and automation sectors. The data were gathered via an online questionnaire, and the Smart-PLS approach was used to analyze the data. The empirical findings indicate that transactional leadership, transformational leadership, and career development are significantly and negatively related to turnover intention, whereas work stress has a significant positive effect. The psychological contract moderates the relationship between career development and turnover intention; the higher the psychological contract, the stronger the relationship. In addition, the psychological contract moderates the relationship between work stress and turnover intention, whereby the higher the psychological contract, the weaker the relationship. However, no empirical evidence suggests that the psychological contract moderates the relationship between leadership styles and turnover intention. The R² value is 0.485, indicating moderate explanatory power, and with a GOF index of 0.492, the model also demonstrates a good fit with the data. This study offers considerable implications for both theoretical and practical applications.

This study aims to investigate the influence of remote work on team effectiveness in high-tech enterprises in Jordan, specifically focusing on knowledge management as a mediator. The study utilized a quantitative research design, with 254 participants actively participating in remote work settings across high-tech firms in Jordan. The sample was chosen based on the participants’ personal experiences with remote work arrangements, which provide valuable insights into the interplay between remote working conditions and team dynamics. The paper designed a structured questionnaire to elicit responses from employees about the variables under investigation. The survey data were analyzed using SmartPLS4 to validate the theoretical framework and research hypotheses. The results show a significant positive relationship between remote work and team effectiveness, as well as an improvement in knowledge management practices under telework conditions. Knowledge management practices refer to communicative activities regarding the systematic collection, organization, sharing, and application of knowledge resources. The importance of effective knowledge management practices is realized in remote settings, primarily through increased team efficiency and productivity. These results are statistically significant (p = 0.000), which stresses the importance of effective remote teamwork with regard to knowledge management.

To address the challenges posed by the living environment and promote sustainable development, the Chinese government implemented a new environmental protection law in 2015. Based on the provincial panel data of 30 provinces, autonomous regions, and municipalities in China from 2010 to 2019, the spatial Durbin model is used to investigate the impact of environmental regulation on the employment effect of high-tech industries, and the spatial effect decomposition is used to further clarify the specific impact of environmental regulation on the employment of high-tech industries. The research finds that: Firstly, at the present stage, environmental regulation in China remains at a relatively low level. The employment generation effect of environmental regulation on high-tech industries is insufficient to offset the employment loss effect. Strengthening environmental regulation in the short term is unfavorable for employment in high-tech industries. Secondly, adjacent regions adopt a strategy of competitive differential environmental regulation between governments. The local government relaxes environmental regulation to increase employment, while the neighboring government strengthens environmental regulation to promote industrial upgrading. This approach benefits local employment in high-tech industries in the short term but hinders the sustainable development of high-tech industries. Thirdly, environmental regulation exhibits significant negative spatial spillover effects. Strengthening local environmental regulation will suppress the growth of high-tech industry employment in neighboring areas, and the spatial spillover effect of environmental regulation is primarily influenced by geographic location. [ABSTRACT FROM AUTHOR]

Climate change is destructive to both economic activity and life subsistence. The rising CO2 emission is continuously degrading the environment and altering the characteristics of multiple hazards that can adversely affect human life. Transition to energy sources and industrial processes can maximize the benefits of low transitioning carbon emission technologies while promoting equality and inclusivity. In this pursuit, the response of CO2 emission is provoked by renewable energy consumption, FDI, natural resource, interaction term of FDI and NR, medium–high-tech industry, and economic growth on APEC countries for the period 1996–2020. To draw clear and conclusive information about outcome variables at different quantiles, study applied panel quantiles regression with an optimization method, such as Markov chain Monte Carlo. Natural resource consumption, high-tech industry, and economic growth have a positive, heterogeneous, and significant effect on environmental degradation in all quantiles. It is worth noting that HT deteriorates the environment in APEC countries, generally technological progress increases energy efficiency and reduces emissions. But it confirms the existence of a cost effect, which increases the use of conventional low-cost products over high-tech products. FDI has a positive and significant effect in all quantiles except the first quantile and confirms the presence of PHH. The interaction term (FDI*NRR) and REC effects are negative and significant in all quantiles. The negative effects of interaction term revealed that domestic industry is the cause of over-consumption and emission of NR. The use of clean and green energy consumption is crucial for sustainable development. Policymakers need to design mechanism that promotes steward policies for domestic industry to discourage the use of NR, enhance local–international partnerships in low emission and energy-efficient technologies, and promote the use of renewable energy. These policies will help to achieve certain SDG's goals such as (SDG-7: clean energy sources), (SDG-8: sustainable development goal); and (SDG-9: climate action). [ABSTRACT FROM AUTHOR]

Introduction. The competitiveness of industry in modern conditions is carried out through scientific and technological development. High-tech companies play a key role in solving the main tasks of increasing the competitiveness of Russian economy in accordance with global challenges and priorities of Russia’s scientific and technological development. Theoretical analysis. High-tech production, Industry 4.0 technologies and technological entrepreneurship in modern economy are the main actors in achieving technological sovereignty, the transition to economic growth and technological support for the sustainable development of Russian production systems. The article examines the role of technological entrepreneurship in the transition of industrial enterprises to Industry 4.0 technologies. Empirical analysis. An innovative development dynamics analysis in Russia and foreign countries is carried out, a startup studio is considered as a tool for the development of technological entrepreneurship, as well as the practice of its implementation in Russia and the USA. Results. Based on the results of the study, a number of proposals for the development of technological entrepreneurship in the small and medium-sized enterprise industry sector were formulated and justified.

In the highly competitive environment of the high-tech industry, leadership roles are often filled with numerous challenges and stressors. Success in the workforce requires a combination of high emotional intelligence and a connection to workplace spirituality. This study aimed to compare demographic differences among high-tech leaders regarding emotional intelligence, workplace spirituality, and career success. It also sought to examine the relationships and effects of emotional intelligence and workplace spirituality on career success, as well as the moderating role of workplace spirituality in these relationships. A survey was conducted with 139 leaders from various high-tech companies in Taiwan. The results showed that male leaders demonstrated higher levels of self-awareness and self-motivation in emotional intelligence, while leaders with higher education levels exhibited greater self-awareness and empathy. Additionally, both emotional intelligence and workplace spirituality were significant predictors of career success. Notably, workplace spirituality moderated the relationship between emotional intelligence and career success. The implications of this study highlight the importance of enhancing emotional intelligence and workplace spirituality to foster leaders’ career success and gain a competitive advantage in the high-tech industry.

Today's competitive advantage is built through sustainability. Regional competitiveness is undoubtedly one of the most important components for achieving sustainability of development at the local level. The analysis of key factors and their correlations, aimed at gauging regional competitiveness, yields valuable insights into the multifaceted elements that impact the growth and advancement of underprivileged regions. However, a crucial question remains: What precisely are the factors that form the foundation for assessing and measuring regional competitiveness? The literature review and analysis initially identified the ten most frequently mentioned factors for measuring regional competitiveness. The overarching aim of the research is the understanding of the ten main determining factors of regional competitiveness and the extraction of ten propositions based on those ten factors and exploring the relationship between various factors and regional competitiveness. This study's time frame was from August 2023 to January 2024. In this research, our aim was to undertake a traditional literature review, concentrating on the context of doing a more traditional and critical literature review rather than a systematic literature review. We assess and evaluate published research spanning the last five years (2018–2023); we have identified and emphasized ten central and widely published factors that span various domains, including (1) economy, (2) labor market, (3) poverty and social inclusion, (4) healthcare, (5) educational infrastructure, (6) environmental considerations, (7) transportation infrastructure, (8) science and technology, (9) high-tech industries, and (10) innovation. Our main findings on these ten reviewed factors indicate the following. (a) The economy factor should be expanded to include education, healthcare, and environmental sustainability parameters, while (b) there is a need to address youth employment differences in the labor market. (c) Collaborative, multidimensional approaches are important, together with improving health infrastructures and services, to improve poverty and social exclusion. (d) Investments on education and innovation are required to improve prosperity and competitiveness, as are more informed policies and collaborative actions for a greener, healthier, and more sustainable future, and finally, (f) well-planned investments in transportation, the essential link between R&D, innovation, and economic progress, as well as additional high-tech industry development and innovative actions should be taken for permanently sustainable and economic growth of the regions. Overall, the research highlights how economic, social, and environmental factors intertwine to shape successful societies, forming a fundamental understanding of regional competitiveness. The research underscores the interconnectedness of economic, social, and environmental factors in shaping prosperous societies, providing a foundational understanding of regional competitiveness. [ABSTRACT FROM AUTHOR]

This study investigates the pivotal role of technological innovation in enhancing the export competitiveness of high-tech products in China, analyzing its interplay with industrial upgrading. Theoretically, it contributes to the understanding of how technological innovation affects high-tech product markets, offering a novel product-centric perspective distinct from traditional industry-focused views. Set against China's shift toward a dual circulation development paradigm, the research utilizes a panel regression model to analyze data from 30 Chinese provinces, cities, and autonomous regions from 2011 to 2021. The findings underscore the significant positive impact of technological innovation on export competitiveness, with variances noted across Eastern, Central, and Western regions. The study reveals that technological innovation primarily influences the global competitiveness of high-tech products through industrial upgrading. Policy recommendations emphasize strengthening technological innovation, enhancing education and government support, leveraging regional strengths, and achieving a balance between internal innovation capabilities and market openness. The findings suggest these strategies are crucial for enhancing export performance in the global market for high-tech products. [ABSTRACT FROM AUTHOR]

In a world where technological advancements shape not only markets but also societies, understanding the nuances of the high-tech industry is crucial for any stakeholder. Whether it’s global giants or emerging ecosystems like Ukraine, the common features are innovation, competition, and the relentless pace of change. Both operate in an environment characterized by stiff competition, rapid innovation, and a complex regulatory landscape. However, their individual growth and marketing strategies differ under the influence of local trends, existing skills, and government policies. McKinsey’s Technology Trends Forecast up to 2023 is a reminder of the acute talent shortage affecting the sector around the world. This adds another layer of complexity, making human capital as valuable as technological innovation. Clearly, both in Ukraine and elsewhere, the ability to attract, retain and develop talent is becoming a crucial factor for success in this sector. The marketing strategies employed in this sector are as complex as the technologies they aim to promote. From the need for thought leadership and content marketing to the benefits of partnerships, each approach has its own set of opportunities and challenges. Companies must constantly update their methods to adapt to new technological trends, as well as take into account the different regulatory and cultural landscapes in which they operate. The high-tech industry will continue to remain a key player in shaping the future economically, socially, and ethically. Policymakers and industry stakeholders must work in tandem to navigate this complex web of opportunities and challenges, keeping local needs and global shifts in mind. The only constant in the high-tech industry is changes, and success belongs to those who know how to adapt, innovate, and grow.

Since 2010, China's economic growth has stagnated due to an unbalanced regional industrial structure and lack of sufficient qualified technical personnel. A nonlinear autoregressive distributed lag (NARDL) model has been used in this study to examine the asymmetric effects of secondary vocational education and training (SVET) and higher vocational education and training (HVET) and their interaction with high-tech industries on economic growth over the period 1980-2020. The findings show that an increase in secondary vocational education and training (SVET) significantly boosts long-term economic growth, while a decrease in secondary vocational education and training (SVET) insignificantly reduces long-term China economic growth. Likewise, the upward change in higher vocational education and training (HVET) promotes and the downward fluctuation in higher vocational education and training (HVET) significantly reduces China's long-term economic growth. The moderating role of secondary vocational education in the impact of high-tech industries on China's economic growth is positive, but not significant. However, higher vocational education plays a significant positive moderating role in high technology industries impact on economic growth. Strategically, the study analysis suggests that economic transition prosperity can be achieved by encouraging higher vocational education and the equal development of high-tech industries in all regions. In addition, this study also proposes to cultivate high-quality talents related to high-tech development and modern industrial innovation and upgrading through higher vocational education, improve productivity, and promote the country's intensive development. [ABSTRACT FROM AUTHOR]

With the rapid advancement of global technology, high-tech industries have become key drivers for the economic growth of many nations and regions. This study delves into the spatiotemporal dynamics and determinants influencing China's high-tech sector from 2007 to 2021. The key findings include the following: (1) Nationally, the high-tech sector has been a cornerstone for China's GDP growth over the preceding 15 years. The expansion rate of the high-tech domain consistently outpaces the broader economy. In particular, since 2015, the percentage of high-tech industries' GDP has surged to approximately 42%. (2) At the provincial level, the spatial representation of the high-tech sector's GDP predominantly leans towards the east and the south, revealing pronounced spatial autocorrelation. Nevertheless, the demarcations between east and west and between north and south are progressively diminishing. (3) Regarding influential determinants, R&D internal expenditure, operating revenue, and industry agglomeration have been instrumental in spearheading innovation and bolstering growth within the high-tech realm. These insights are invaluable for comprehending the evolutional nuances of China's high-tech industry and devising pertinent policy measures. [ABSTRACT FROM AUTHOR]

China is implementing a structural tax reduction policy to upgrade the structure of household consumption and promote the development of high-tech industry. This article constructs a heterogeneous NK-DSGE (New Keynesian - Dynamic Stochastic General Equilibrium) model to study the effects of tax reduction policies on consumption upgrading and the development of high-tech industry. The tax categories involved in this model are divided into demand-side tax and supply-side tax. We build two indexes to measure the consumption structure and the development of high-tech industry. It is found that reducing high-tech enterprise income tax would upgrade the consumption structure and promote the development of high-tech industries in the short term. Reducing low-tech enterprise income tax would achieve similar effects in the medium and long term. Moreover, tax such as consumption tax, labour income tax and capital income tax reduction policies can upgrade the consumption structure and promote the development of high-tech industry in the long term. Finally, this article finds that when the elasticity of labour substitution is smaller, reducing high-tech enterprise income tax is more effective. [ABSTRACT FROM AUTHOR]

Employees' innovative performance determines an organization's long-term sustainability and competitive advantages, particularly in the technology sector. Drawing on social exchange and work conformity theory, we investigate how employees' informational and normative conformity relates to their innovative performance through the lens of instrumental and expressive ties. R&D managers and professional-level employees from Taiwan's 2000 largest high-tech firms participate in the survey. Hypotheses were tested using structural equation modeling with a valid sample of 399 responses from the participants. The findings reveal that, through the mediating roles of instrumental and expressive ties, employees' informational conforming behaviors promote their innovative performance. In contrast, normative conformity may reduce employees' innovative performance by weakening their social ties. Conformist behaviors have long been deemed as the inhibitor of creativity and innovation. Nevertheless, this study adopts a social exchange perspective and clarifies how conformity can both promote and hinder professional employees' innovative performance by affecting their social networking. The paper concludes with managerial implications, discussion, and recommendations for future research. [ABSTRACT FROM AUTHOR]

There is still a significant gap between most high-tech fields in China and developed countries, and the relationship between the economic resilience of innovation systems and the innovation capability of the high-tech industry has received attention. Using data from 30 provinces in China, this study adopts the fuzzy-set qualitative comparative analysis approach to analyze the relationship between economic resilience and high-tech industry innovation capability, and the findings are as follows: (1) Technological talents and economic development are necessary conditions for explaining the high innovation capability of high-tech industries. (2) The combination of economic resilience and different factors constitutes the equivalent configuration of two high innovation capabilities and four low innovation capabilities. (3) Under high-intensity technological competition between governments, the increased agglomeration of technological talents, and high-quality economic development, the strengthening of economic resilience is conducive to enhancing the innovation capability of high-tech industries. (4) Under low-intensity technological competition between governments, a well-developed technology market, and increased agglomeration of technological talents, the strengthening of economic resilience is adverse to enhancing the innovation capability of high-tech industries. The main contribution of this study is to clarify the configuration mechanism of economic resilience that acts on the innovation capability of the high-tech industry and reveal the complex interaction between economic resilience and multiple factors. [ABSTRACT FROM AUTHOR]

This study explores the synergetic development capability of China's high-tech industry innovation ecosystem and the diversification path necessary to improve it. Based on the four-spiral perspective, the system synergetic development index was constructed, and the composite system collaborative degree model was used to measure the synergetic development capability of the high-tech industry innovation ecosystem across 30 provinces and cities in China from 2012 to 2020. The influencing factor model of improving the system's synergetic development capability was constructed under the technology–organization–environment (TOE) framework, and a fuzzy set qualitative comparative analysis (fsQCA) method was used to explore the multiple paths available to improve the synergetic development ability of the system. The results show that the four-helix system's synergetic development capability is poor and needs to be improved. The "technology–organization–environment" conditions cannot be used alone as the necessary conditions for the improvement in the system's synergetic development capability but need to exert a joint, matching effect through the combination of different factors. In addition, market openness is crucial on the path toward the highly synergetic development of the system. The research results not only provide a theoretical basis for comprehensively improving the system's synergetic development capability but also provide a practical reference for the differentiation path being revealed. In short, this study has important theoretical and practical significance to promoting the synergetic development and benign evolution of the high-tech industry innovation ecosystem. [ABSTRACT FROM AUTHOR]

With the rapid development of high-tech industries, the research perspective of industrial innovation has gradually evolved from the innovation system to innovation ecosystem. Whether the innovation ecosystem of China's high-tech industry can achieve the benign evolution and development of the system under the new global pattern has become a real issue. Based on the perspective of the four-helix innovation model, in this study we construct an index system of the industrial innovation ecosystem development and designs a framework system of the industrial innovation ecosystem development capability, including the coordinated development capability, evolutionary development capability, and sustainable development capability at three levels. We construct measurement models of different capability dimensions and multi-dimensionally analyses of the regional development differences and change trends of each capability dimension of the system. The results show that the coordinated development capability of China's high-tech industrial innovation ecosystem is poor, which inhibits the comprehensive capability of the system's development to a certain extent. Although the evolutionary and sustainable development capabilities fluctuate greatly and have significant regional differences, they are measured at a better level and thereby contribute to the development of the system. [ABSTRACT FROM AUTHOR]

Because of escalating technological conflicts, the US-China technology war, and hegemonic competition since the late 2010s, “technonationalism,” has become a critical topic in the international political economy, and this study contributes to the ongoing discussion proposing two mediating variables, the global value chain (GVC) and the US-China competition in the 2010s. First, we propose a shift in the technonationalist paradigm, from focusing on a single-state approach with an industrial policy oriented toward development to a multistate focus approach with a geoeconomic strategy oriented toward security. It also highlights the integration of business interests into the national strategic agenda as a critical criterion. Second, the study examines investment in Japan by Elpida Memory, Kioxia, and Taiwan Semiconductor Manufacturing Company. Based on Japan as a case study, the findings show a shift to technonationalism, as the government responds to changes in international political conditions, rather than to domestic demands for supporting a specific segment of the semiconductor industry.

Promoting technology transfer is an important strategic measure for China to promote industrial innovation. However, there is little research exploring the influence of technology transfer on the green innovation efficiency (GIE) of China's high-tech industry (HTI). From the perspective of process, green innovation in HTI is a continuous three-stage system including research and development (R&D), commercialization, and diffusion. Therefore, we measure the GIE of China's HTI by using a three-stage network data envelopment analysis (NDEA) model considering environmental pollution and establish a series of regression models to investigate the role of the two main ways of technology transfer, domestic technology acquisition (DTA) and foreign technology introduction (FTI), in improving the GIE of HTI. The results show that the average GIE of China's HTI is 0.7727 from 2011 to 2020. Except for Jiangsu, Guangdong, Qinghai, and Xinjiang, green innovation in HTI in other provinces in China is inefficient. DTA has significantly promoted GIE in HTI. FTI has a positive impact on the GIE of HTI but is not statistically significant. The robustness test confirmed these results. This study is helpful to understand the differences between the effects of DTA and FTI on the GIE of China's HTI, to provide a basis for adjusting technology transfer policies.

Knowledge always constitutes the primary productive force for the social and economic development of the country, and consequently innovation has become a new development theme in most countries worldwide. Characterized by high profitability and high growth, Chinese high-tech industries show a rapid growth trend in size and effectiveness, which have been the supporting force and cornerstone for the national economy to promote the upgrading of products and industrial structures. In this study, a combination of Criteria Importance through Intercriteria Correlation (CRITIC) and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method was proposed to evaluate the innovation capacity of high-tech industries. A total of 25 three-level evaluation indicators were established to construct a high-tech industry innovation capacity indication system. The CRITIC method was used to calculate the weight of each indicator, and the TOPSIS method was used to make comprehensive decisions on the high-tech industries of 31 provinces in China. Results show that the development trends of high-tech industries vary greatly in the 31 provinces of China. The top five indicators are the rate-of renovation and reformation projects completed and put into use; the amount of investment in renovation and reformation; the rate of projects completed and put into use; the gross value of production and operation output at current prices; and the expenditure of large and medium-sized high-tech enterprises on technology reformation. These indicators are the critical factors affecting the ranking of high-tech industries at the provincial level. Guangdong ranks first, followed by Jiangsu and Zhejiang, sequentially. The differences in economic and geographical factors initially result in the regional distribution imbalance of high-tech industries, typically “the eastern preceding over the middle, and the middle preceding over the western.” Conclusions provide significantly valuable references in expanding the indication system for a comprehensive evaluation of the independent innovation capacity of high-tech enterprises, which also show valuable references in suggesting measures for the government and enterprises to improve the independent innovation capacity of high-tech enterprises. [ABSTRACT FROM AUTHOR]

Environmental regulation has become a significant way to achieve sustainable development. Taking the panel data of China's high-tech industries from 2007–2016 in 30 provinces and cities as a sample, regression models are established to study the impact of three different types of environmental regulations on international competitiveness and the moderating effect of R&D (research & development) investment. The results show that the impact of environmental regulations on the international competitiveness of high-tech industries is related to the type of environmental regulation. There is a significant negative correlation between economic environmental regulation (EER) and the international competitiveness of high-tech industries, and R&D investment has a significant inhibitory effect on the relationship between the two. For both commanding environmental regulation (CER) and participatory environmental regulation (PER), R&D investment plays a significant moderating role in environmental regulation and the international competitiveness of high-tech industries. The impact of all three environmental regulations on R&D investment was positive but not significant. Finally, based on these research conclusions, a few countermeasures and suggestions are discussed for the formulation of China's environmental regulation policies and the development of high-tech industries. [ABSTRACT FROM AUTHOR]

Under the rapidly developing economy in China, accurate forecasting holds vital significance for policymaking and operational planning within the high-tech industry. However, the influencing factors affecting the output, accompanied by the time-delay effect, could be nonlinear, and uncertain. Thereby, this paper proposes a new nonlinear grey multivariable model with time-varying lag parameters. To be specific, the newly designed time delay function and power exponent are introduced, which can significantly enhance the adaptability and flexibility of the proposed method. The Grey Wolf Optimization algorithm is utilized to calculate the dynamic time lag parameters and power exponent to improve the prediction reliability. Furthermore, this new approach is applied to predict the high-tech industry's output in China, Shanghai Municipality, and the Eastern Region, with due consideration given to the time-delay effect between input factors and outputs. To assess its efficacy, some leading models are selected for comparison to the proposed model. Furthermore, the utilization of Monte-Carlo simulation, the Probability Density Analysis, and the simulations are used to demonstrate the robustness and stability of this new method. The findings show that the proposed model is a feasible and applicable approach for prediction, exhibiting outstanding accuracy. [ABSTRACT FROM AUTHOR]

There is still a significant gap between most high-tech fields in China and developed countries, and the relationship between the economic resilience of innovation systems and the innovation capability of the high-tech industry has received attention. Using data from 30 provinces in China, this study adopts the fuzzy-set qualitative comparative analysis approach to analyze the relationship between economic resilience and high-tech industry innovation capability, and the findings are as follows: (1) Technological talents and economic development are necessary conditions for explaining the high innovation capability of high-tech industries. (2) The combination of economic resilience and different factors constitutes the equivalent configuration of two high innovation capabilities and four low innovation capabilities. (3) Under high-intensity technological competition between governments, the increased agglomeration of technological talents, and high-quality economic development, the strengthening of economic resilience is conducive to enhancing the innovation capability of high-tech industries. (4) Under low-intensity technological competition between governments, a well-developed technology market, and increased agglomeration of technological talents, the strengthening of economic resilience is adverse to enhancing the innovation capability of high-tech industries. The main contribution of this study is to clarify the configuration mechanism of economic resilience that acts on the innovation capability of the high-tech industry and reveal the complex interaction between economic resilience and multiple factors.

The article is devoted to the analysis of the current state of the industrial sector of the Republic of North Ossetia-Alania and the need for its modernization in a new format. The necessity of modern industrial production is substantiated and a new paradigm (the «Star» project) is proposed for the reconstruction and development of a modern industrial base of the regional economy based on micro-nanoelectronic, photonic and fiber-optic science-intensive innovative technologies of the fifth and sixth technological modes. The leading principles of the new paradigm are: the system-innovative approach, the system-communication approach, the cluster approach, the principle of the «triple helix», the continuity of the scientific and innovation cycle, the outstripping development of regional science and personnel training systems.

The current technological potential energy agglomeration situation and the driving mechanism for high-tech (HT) industry development can be clarified based on the front view of innovative behaviour. Thus, it can be defined using three dimensions: comprehensive innovation environment, innovation initiative and attraction of innovation factors. This study theoretically investigates the internal mechanism and spatial effect of technological potential energy agglomeration driving the development of the HT industry and establishes an empirical analysis using a general nested space model (GNS). China's regional technological potential energy agglomeration level increases over time, and a 'conduction' development pattern spreading from the northeast to the southwest is observed. The diversified agglomeration of technological potential energy can significantly transform the low- and medium-tech (LMT) industry to the HT industry at the 1% level, with a driving force of 0.5994. The driving force of the specialised agglomeration is 0.2538, less than the diversified agglomeration. The specialised agglomeration of technological potential energy hinders the development of HT industries in neighbouring areas, as core technologies are excusive with limited innovation resources. Therefore, all provinces should promote HT industries by cultivating platforms for technological potential energy agglomeration, encouraging technological innovation, strengthening foreign trade and promoting institutional innovation. [ABSTRACT FROM AUTHOR]

With the rapid development of high-tech industries, the research perspective of industrial innovation has gradually evolved from the innovation system to innovation ecosystem. Whether the innovation ecosystem of China’s high-tech industry can achieve the benign evolution and development of the system under the new global pattern has become a real issue. Based on the perspective of the four-helix innovation model, in this study we construct an index system of the industrial innovation ecosystem development and designs a framework system of the industrial innovation ecosystem development capability, including the coordinated development capability, evolutionary development capability, and sustainable development capability at three levels. We construct measurement models of different capability dimensions and multi-dimensionally analyses of the regional development differences and change trends of each capability dimension of the system. The results show that the coordinated development capability of China’s high-tech industrial innovation ecosystem is poor, which inhibits the comprehensive capability of the system’s development to a certain extent. Although the evolutionary and sustainable development capabilities fluctuate greatly and have significant regional differences, they are measured at a better level and thereby contribute to the development of the system.

High-tech industrial agglomeration plays a significant role in regional sustainable development. Local governments have issued many industrial policies to accelerate the development of high-tech industries in China. Evaluating high-tech industry policies from the perspective of regional industrial synergy can prevent problems in policy implementation and promote the industrial synergy in a region. For this purpose, taking China's Beijing-Tianjin-Hebei (BTH) region as a case, we evaluate seven policies governing the high-tech industry in this region by using the approach which integrates the policy modeling consistency index (PMC-Index) model and text mining. We propose an evaluation system with consideration of regional industrial synergy, which is based on the PMC-Index model. The results show that the lowest PMC-Index value of the seven policies is 5.30, the highest is 8.17, and the average is 6.67. Among the policies, four are of excellent or perfect grade and relatively comprehensive; three are of acceptable grade and relatively insufficient. The overall designs of the high-tech industrial policies are reasonable but there is still much room for improvement. According to the average scores of the main indicators, the policies function relatively poorly in terms of policy release agency, policy timeliness, policy type and policy receptor. The optimizations for the shortcomings of each policy are also suggested. This study may not only provide some enlightenment to policymakers, but also provide a supplement for the policy evaluation field. [ABSTRACT FROM AUTHOR]

High-tech industry stands out as progressive, inovative field of industry which continuously makes investments towards R&D development. High-tech industry also has distinguishing features such as rapid use of new science findings and constant investments to new equipment, which tends to quickly depreciate and is replaced. Also, high-tech industry companies typicaly cooperate with international organisations, research centers and universities. It is not unusual for high-tech industry companies to have a lot of patents and licences. It is difficult to implement business improvement models, which tend to increase competitive advantage by reducing production cost, increasing production speed and reducing delivery time in continiously evolving high-tech industry companies. In this paper the posibility to implement business improvement models in high-tech industry is analyzed. Additionaly, employee motivation and initiative, as factors of business model implementation success is analyzed. Finally, based on the research of scientific literature and empirical data of two high-tech industry companies a model for high-tech industry performance improvement is proposed, which also introduces tools to improve employee motivation and initiative. Article in Lithuanian. Pažangiųjų technologijų pramonės veiklos tobulinimas Santrauka Pažangiųjų technologijų pramonė išsiskiria kaip nuolat progresuojanti, inovatyvi, dideles investicijas į mokslinius tyrimus ir plėtrą investuojanti pramonės šaka. Pažangiųjų technologijų pramonei taip pat būdingas greitas mokslinių naujovių ir inovacijų įsisavinimas, dažnos ir didelės investicijos į techninę įrangą, kuri yra dažnai atnaujinama ir greitai nuvertėja, yra pakeičiama nauja. Taip pat ši pramonės sritis išsiskiria nuolatiniu bendradarbiavimu su tarptautinėmis organizacijomis ir mokslinių tyrimu centrais, universitetais, gali pasižymėti ir dideliu patentų, licencijų skaičiumi. Tokiame nuolatinės kaitos klimate sunkiau įdiegti srauto valdymo priemones, kuriomis organizacijos gali įgyti konkurencinį pranašumą dėl mažesnių gamybos kaštų, greitesnės gamybos ir galimybės produktą klientui pristatyti greičiau. Šiame tyrime nagrinėjamos galimybės pažangiųjų technologijų pramonės sektoriuje įdiegti veiklos efektyvumą didinančias priemones remiantis Lean, Six Sigma ir apribojimų teorija. Taip pat nagrinėjama darbuotojų motyvacijos ir iniciatyvumo įtaka šių priemonių įdiegimo sėkmei. Remiantis mokslinės literatūros apžvalga ir atliktų dviejų pažangiųjų technologijų įmonių ir bendros grupės kiekybinių tyrimų rezultatais sukuriamas pažangiųjų technologijų pramonės efektyvumo didinimo modelis, atsižvelgiant į darbuotojų motyvaciją ir iniciatyvumą, pateikiamos išvados ir pasiūlymai. Reikšminiai žodžiai: darbuotojų motyvacija, pažangiųjų technologijų pramonė, gamybos optimizavimas, Lean, Six Sigma, apribojimų teorija, inovacijos, efektyvumo didinimas, atsakinga organizacija.

The high-tech industry belongs to the core strategic national development category and is essential in promoting social future economic growth and scientific and technological progress. This paper constructs a theoretical framework for high-tech industry land misallocation based on the four-level institutional analysis method. The study selects Zhejiang Province of China as the research area. It uses the literature research method and multiple regression analysis methods to analyze the root causes and influence mechanism of land misallocation for the high-tech industry. The research shows that the land-use support policies for the high-tech industry can effectively alleviate the misallocation of land factors. In contrast, the government’s improper financial support measures and tax incentives increase the degree of land misallocation in the high-tech industry. The higher the R&D expenditure-to-income ratio and profitability, the lesser the land misallocation in the high-tech industry. Government behavior and enterprise behavior impact land misallocation in the high-tech industry, but government behavior has a major impact. Therefore, the government, enterprises, and the market should adopt an integrated strategy to reduce excessive government intervention in land resource allocation, allowing the market to play a decisive role in resource allocation, and stimulate the vitality of enterprise R&D and innovation. This study helps to reveal the deep motivation of land misallocation for high-tech industry and provides practical guidance for optimizing the high-tech industrial land allocation and promoting high-quality industrial development.

Rare earth elements (REEs) are essential for promoting clean energy technologies and making high-performance materials because of their unique physical and chemical properties. In order to respond to climate change, the Chinese government has promised to achieve carbon neutrality before 2060. Under such a circumstance, the demand for REEs will increase significantly. However, several challenges exist in current REEs supply chain management in China. This policy brief discusses these challenges from a life cycle perspective, covering REEs mining, smelting, manufacturing, waste management, and recycling. Policy recommendations on future REEs supply chain management are then proposed, including adequate mining quota, a strategic REEs list, innovative high-tech applications, and circular economy.

Accurate analysis of technological innovation mechanism in different regions is the key to promoting China’s technological innovation, economic transformation and upgrading. This paper collected statistical data of high-tech enterprises in 27 provinces in China from 2009 to 2016, established a novel PSO-GRNN model, and applied sensitivity analysis to explore the influencing factors and regional differences of enterprise technological innovation in Eastern, Central and Western China. The empirical results showed that the influencing factors were innovation investment, market environment, government support and foreign technology spillover sorting by impact size. Innovation investment was the decisive factor of technological innovation, but innovation resources mainly concentrated on Eastern China, severely insufficient in Central and Western China. Market environment was favorable to Eastern and Central China, but unfavorable to Western China, which restricted greatly the development of Western China. The principalagent problem of state-owned enterprise and the crowding out effect of government research and development funds jointly led to the negative influence of government support on technological innovation. Foreign technology spillover had significant positive effects on technological innovation in Western China. This paper clarifies some disputes about influencing factors of technological innovation and provides a new research perspective for related issues. First published online 27 May 2021

The paper uses the panel smooth conversion fractional-order system model to divide the mechanism of financial development in high-tech industries into two systems. At the same time, the article uses a continuous state to connect these two extreme situations to investigate the nonlinear characteristics of linear feedback control that inhibit the impact of financial development on high-tech industries. Studies have shown that financial development under a low system has a significant role in promoting high-tech industries. On the other hand, financial development under the high-level system has a restraining effect on high-tech industries. There are dual-threshold characteristics between the scale of financial development and the development of high-tech industries. Firstly, the scale of financial development should be controlled within [0.553, 0.840]. Secondly, there is a single threshold between the level of financial development and the development of high-tech industries, and the level of financial development should be controlled within 0.756.

In the modern conditions of economic development, the development of the industrial complex is being transformed with emphasis on digital technologies and high-tech production. The article considers new principles of the implementation of the state’s economic policy taking into account the challenges of the fourth industrial revolution, as well as the results of the analysis of the main indicators of industrial development, both in the world and in Russia in particular, including the assessment of the current state of innovation and technological activity of the industrial sector of the Russian economy. At the same time the authors pay special attention to the analysis of modern trends in the development of industry in countries with both a high level of high-tech production and a low level. The paper analyses the prospects of Russian industry development to justify the need for technological breakthrough strategies and technological modernization of industrial enterprises.

Since 2010, China's economic growth has stagnated due to an unbalanced regional industrial structure and lack of sufficient qualified technical personnel. A nonlinear autoregressive distributed lag (NARDL) model has been used in this study to examine the asymmetric effects of secondary vocational education and training (SVET) and higher vocational education and training (HVET) and their interaction with high-tech industries on economic growth over the period 1980–2020. The findings show that an increase in secondary vocational education and training (SVET) significantly boosts long-term economic growth, while a decrease in secondary vocational education and training (SVET) insignificantly reduces long-term China economic growth. Likewise, the upward change in higher vocational education and training (HVET) promotes and the downward fluctuation in higher vocational education and training (HVET) significantly reduces China's long-term economic growth. The moderating role of secondary vocational education in the impact of high-tech industries on China's economic growth is positive, but not significant. However, higher vocational education plays a significant positive moderating role in high technology industries impact on economic growth. Strategically, the study analysis suggests that economic transition prosperity can be achieved by encouraging higher vocational education and the equal development of high-tech industries in all regions. In addition, this study also proposes to cultivate high-quality talents related to high-tech development and modern industrial innovation and upgrading through higher vocational education, improve productivity, and promote the country's intensive development. [ABSTRACT FROM AUTHOR]

The innovation capability of high-tech industry reflects international competitiveness of a country. In order to scientifically evaluate the innovation capability, this paper proffers the comprehensive evaluation of the particle swarm synthesis optimization based on deviation maximization, principal component analysis and TOPSIS method. The evaluation index system of the innovation capability of high-tech industry is constructed; the paper conducts the empirical research through the particle swarm synthesis algorithm combined with provincial yearbook data on 30 provinces in China, and obtains the technological innovation capability results and rankings of each province's high-tech industry. The empirical results also show that the overall innovation capability of China's high-tech industry shows the growth trend, indicating that the implementation of an innovation-driven development strategy and other related policies have achieved suitable results. At the same time, the level of development in the eastern part of China is always higher than that of the central region and the western region. The paper further analyses reasons of differences in the development level of different regions. The particle swarm synthesis optimization has strong applicability in a comprehensive evaluation. This paper provides an effective reference for evaluating the innovation ability of the high-tech industry.

Since 2010, China's economic growth has stagnated due to an unbalanced regional industrial structure and lack of sufficient qualified technical personnel. A nonlinear autoregressive distributed lag (NARDL) model has been used in this study to examine the asymmetric effects of secondary vocational education and training (SVET) and higher vocational education and training (HVET) and their interaction with high-tech industries on economic growth over the period 1980–2020. The findings show that an increase in secondary vocational education and training (SVET) significantly boosts long-term economic growth, while a decrease in secondary vocational education and training (SVET) insignificantly reduces long-term China economic growth. Likewise, the upward change in higher vocational education and training (HVET) promotes and the downward fluctuation in higher vocational education and training (HVET) significantly reduces China's long-term economic growth. The moderating role of secondary vocational education in the impact of high-tech industries on China's economic growth is positive, but not significant. However, higher vocational education plays a significant positive moderating role in high technology industries impact on economic growth. Strategically, the study analysis suggests that economic transition prosperity can be achieved by encouraging higher vocational education and the equal development of high-tech industries in all regions. In addition, this study also proposes to cultivate high-quality talents related to high-tech development and modern industrial innovation and upgrading through higher vocational education, improve productivity, and promote the country's intensive development.

The high-tech industry plays a crucial role in reducing carbon emission and achieving green economic development. This research uses Meta-Frontier data envelopment analysis to measure the innovation efficiency level of the high-tech industry in China’s provinces from 1999 to 2018, compares the difference in this industry’s innovation efficiency under the regional Frontier and common Frontier, and inspects the convergence condition of its innovation efficiency in the three major areas of eastern, central, and western China. The results show under the regional Frontier that the difference in innovation efficiency of the western region’s high-tech industry is the biggest, while the difference in the central region is the smallest, and under the national common Frontier the innovation efficiency level of the eastern region’s high-tech industry is the highest, while that of the western region is the lowest. The regional pattern of innovation efficiency in the high-tech industry is consistent with the development trend of the regional economy. Moreover, by using the ratio of the technology gap ratio, we find that the eastern region has the potential optimal technology in China, whereas the central and western regions have large room for improvement. Lastly, the stochastic convergence test shows that the innovation efficiency of the central region’s high-tech industry presents a convergence trend, but the same trend does not occur in the western and eastern regions as well as for the whole country.

Data envelopment analysis (DEA) is a widely used non‐parametric method in efficiency measurement with multiinputs and multioutputs. Malmquist productivity measures the efficiency change in different periods and decomposes the general efficiency change into technical efficiency change and frontier shift. In this paper, we choose a driving industry in social development, the high‐tech industry, as an example to illustrate a new method, virtual frontier DEA model, in the aspect of improvement of the traditional DEA model. Additionally, we decompose the Malmquist productivity index with virtual frontier DEA model to find out the driving force of high‐tech efficiency change. [ABSTRACT FROM AUTHOR]

High-tech industry stands out as progressive, inovative field of industry which continuously makes investments towards R&D development. High-tech industry also has distinguishing features such as rapid use of new science findings and constant investments to new equipment, which tends to quickly depreciate and is replaced. Also, high-tech industry companies typicaly cooperate with international organisations, research centers and universities. It is not unusual for high-tech industry companies to have a lot of patents and licences. It is difficult to implement business improvement models, which tend to increase competitive advantage by reducing production cost, increasing production speed and reducing delivery time in continiously evolving high-tech industry companies. In this paper the posibility to implement business improvement models in high-tech industry is analyzed. Additionaly, employee motivation and initiative, as factors of business model implementation success is analyzed. Finally, based on the research of scientific literature and empirical data of two high-tech industry companies a model for high-tech industry performance improvement is proposed, which also introduces tools to improve employee motivation and initiative. [ABSTRACT FROM AUTHOR]

Technical service platform exerts a strong effect on supporting the innovation of the high-tech industry as a critical constituent of the modern service industry, and it can effectively enhance the development potential of technological innovation, but the degree of separation from technical service chain to high-tech industry chain is currently high. To explore how to improve the utilization efficiency of scientific and technological resources and facilitate the sustainable development of the high-tech industry by relying on technical service platform,a high-tech service platform was constructed by using Lotka-Volterra (L-V) model on the basis of ecosystem theory, the evolution path and stability conditions of high-tech service platform were analyzed followed by numerical simulation by Matlab computing. Results show that the development of hightech service platform follows the evolution path of "bilateral platform → core platform → platform ecosystem"; population evolution pattern in high-tech service platform ecosystem is decided by interdependence coefficient between populations; populations inside high-tech service platform ecosystem generate natural selection and synergistic effect and realize ecological balance among populations through evolution. Evolution of high-tech service platform system in this study provides a new theoretical framework for effective fusion and collaboration of science and technology service and industry, which is significant for elevating scientific and technological innovation level and improving technical service system construction.

Combined with the WRSR and improved CRITIC objective assignment method, this paper measures and grades the institutional innovation levels of high-tech industries in various provinces (cities and districts) in China, compares them horizontally and vertically, and interprets the temporal and spatial difference. Advanced members are located in the eastern coastal area, and the backward members are mainly composed of the western and northeast areas (cities, districts), while the rest are at a moderate level. Vertically, the levels in most provinces (cities, districts) have maintained a stable situation, and the overall level is low. Furthermore, the research puts forward some countermeasures from three aspects of government intervention, market development and the property right system, to effectively improve the institutional innovation level of high-tech industries in China.

This paper measures and analyzes the institutional influence on the development of China's high-tech industry from 1995 to 2016. The following discoveries are shown. The institutional environment on which China's high-tech industry depends has shown an increasing trend in recent years, but its momentum is obviously weaker than that in the early stage. The calculation results are the same and comprehensive whether the institutional variable is substituted directly into the production function as the explanatory variable or if it is put into the capital stock, labor force and Total factor productivity regression equations. The institutional influences on the input-output of the high-tech industry are very clear and positive, and its influence on the TFP is the greatest. Therefore, the continuous improvement of the institutional environment of high-tech industries is conducive to promoting the high-quality development of the industry.

This article analyzes the different effects of industrial aggregation, industry-university collaboration, foreign direct investment and government support on innovation performance and the synergistic effect between them, thereby to identify the determinants of innovation output of Chinese high-tech industry in the period 2009-2018. The results indicate that industrial agglomeration and industry-university collaboration both have a significant positive impact on the patent output of high-tech industries, but the synergistic effect between industrial agglomeration and industry-university collaboration is significantly negative. Meanwhile, both of foreign direct investment and government support could negatively affect the innovation output, while their synergistic effect is positive.

In recent years, China’s high-tech industry has made remarkable technological progress, but it has also brought serious environmental pollution, which has aroused great concern about its environmental efficiency. Although foreign technology transfer is considered as important ways for technological progress of the high-tech industry, the existing research on what role foreign technology transfer plays in improving the environmental efficiency of the high-tech industry is still lacking. Based on China’s interprovincial panel data from 2008 to 2017, we evaluated the environmental efficiency of the high-tech industry using the super-efficiency slacks-based measure (SBM) model with undesirable outputs. We then used the Tobit model to analyze the impact of technology introduction (TI) and foreign direct investment (FDI)—two major types of foreign technology transfer—on the environmental efficiency of the high-tech industry. The results of the super-efficiency SBM model show that the average environmental efficiency of China’s high-tech industry is only 0.4375. Except for Guangdong, Shanghai, and Beijing, most of the provinces in China have low environmental efficiency. The provinces with high environmental efficiency are in the eastern region, whereas the provinces with low environmental efficiency are concentrated in the central and western regions. Tobit regression results confirm the difference in the role of technology import and foreign direct investment in the improvement of environmental efficiency in China’s high-tech industry. Technology introduction has a significant positive impact on environmental efficiency. FDI also promotes environmental efficiency, but it is not statistically significant. These findings were confirmed by a series of robust tests. This study not only deepens our understanding of the environmental efficiency of China’s high-tech industry but also expands the theoretical research on the relationship between technology transfer and environmental efficiency.

As the world's largest manufacturing country, the rapid growth of China's manufacturing industry has historically relied on factor input. To achieve high-quality development of the manufacturing industry, China must accelerate the transformation from extensive factor input to innovation. The purpose of this study is to further explore the impact mechanisms of technological development policy on the high-quality development of the manufacturing industry. It selected data from 30 provinces and cities in China spanning from 2011 to 2021 for the study. Initially, it established a benchmark regression model to verify the positive impact of technological development policies on the high-quality development of the manufacturing industry. Subsequently, a mediation effect model was used to analyze the role of high-tech industry development in mediating this impact, and a moderation effect model was applied to study the moderating effect of the level of infrastructure informatization. Additionally, taking the industrial structure as a threshold variable, a panel threshold effect model was employed to explore the impact of technological development policy on the high-quality development of the manufacturing industry. It was found that enhancing the level of high-tech industries further facilitates the high-quality development of the manufacturing industry through technological development policy. The level of infrastructure informatization positively moderates the impact of technological development policy on the high-quality development of the manufacturing industry. Moreover, the industrial structure exhibits a threshold effect in this impact., Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Yamin Wang reports financial support was provided by Hunan Provincial Department of Education. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors. Published by Elsevier Ltd.)