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This paper aims to promote the higher quality development of high-tech enterprises in China. While science and technology have greatly promoted human civilization, resources have been excessively consumed and the environment has been sharply polluted. Therefore, it is particularly important for current enterprises to make use of scientific and technological innovation to maximize the benefits of mankind, minimize the loss of nature, and promote the sustainable development of our country.

By using DEA-Banker-Charnes-Cooper (BCC) model and DEA-Malmquist model, this paper comprehensively examines the innovation efficiency of high-tech enterprises from both static and dynamic perspectives, and conducts a provincial comparative study with the panel data of ten representative provinces from 2011 to 2020.

The research findings are as follows: the rapid number increase of high-tech enterprises in most provinces (cities) is accompanied by an ineffective input–output efficiency; the quality of high-tech enterprises needs to comprehensively examine both input–output efficiency and total factor productivity; and there is not a positive correlation between element investment and innovation performance.

Because the DEA model used in this paper assumes that the improvement direction of invalid units is to ensure that the input ratio of various production factors remains unchanged but sometimes the proportion of scientific and technological activities personnel and the total research and development investment is not constant. In the future, the nonradial DEA model can be considered for further research. Due to historical data statistics, more provinces, cities and longer panel data are difficult to obtain. The samples studied in this paper mainly refer to the provinces and cities that ranked first in the number of national high-tech enterprises in 2020. Limited by the number of samples, DEA analysis failed to select more input and output indicators. In the future, with the accumulation of statistical data, the existing efficiency analysis will be further optimized.

Aiming at the misunderstanding of emphasizing quantity and neglecting quality in the cultivation of high-tech enterprises, this paper comprehensively uses DEA-BCC model and DEA Malmquist index decomposition method to make a comprehensive comparative study on the development of high-tech enterprises in ten representative provinces (cities) from two aspects of static efficiency evaluation and dynamic efficiency evaluation.

The purpose of this study is to investigate the impact of the accounting system reform on corporate innovation behavior and the heterogeneity and underlying mechanisms of this impact. This paper further aims to study the impact of accounting system reform on corporate value.

This study takes China's A-share listed corporates as a sample and uses the exogenous policy shock of the implementation of the New Accounting Standards in 2007 to design the identification strategy of propensity score matching and difference-in-differences method. By comparing the differences between the innovation level of corporates in high-tech industries and non-high-tech industries before and after the implementation of the New Accounting Standards, the impact of the accounting system reform on corporates' innovative behavior can be identified.

Results show that compared with corporates in traditional industries, high-tech corporates obtained higher patent output after the implementation of the New Accounting Standards. This reform mainly affects corporate innovation by improving corporate risk-taking. In addition, this paper finds that the reform of the accounting system has increased the market value of high-tech corporates in the long run.

This study provides new empirical evidence for addressing the insufficient innovation incentives for market entities and enriches the existing literature on the economic effects of the change of accounting systems and the influencing factors of corporate innovative behavior from the accounting system perspective.

This paper aims to examine whether information technology (IT) managers’ virtual listening, as rated by their high-tech employees, affected turnover behaviour beyond a new constellation of variables, some of which have never been researched as antecedents of turnover behaviour, particularly during a pandemic or crisis. Namely, the main aim, among others, is to answer the research question: does IT employees’ perception of the quality of their supervisors’ virtual listening in the pandemic and crisis era, when employees and managers work remotely, will negatively affect turnover behaviour? If yes, in which constellation of antecedents the virtual listening effecting on turnover behaviour?

Logistic regression analysis was conducted to test the hypotheses via SPSS 26 and PROCESS (Model 6). The variance inflation factor was calculated to test multicollinearity. Interaction was tested using the Hayes and Preacher PROCESS macro model. The researchers also used the J-N technique test (Johnson–Neyman via process). The supplemental analysis used also PROCESS MACRO (IBM Corp., Armonk, NY, USA, 2023) Model 4 and Bootstrap test.

The findings show that perceptions of supervisors’ virtual listening quality as rated by their employees moderated the relationship between organisational deviance as a type of organisational misbehaviour (OMB) and turnover behaviour and had the strongest effect on turnover behaviour beyond other key predictors (organisational deviance as a type of misbehaviour, turnover intention, job satisfaction, embeddedness and alternatives in the labour market). Alternatives to current work moderated the association between the perception of managers’ virtual listening behaviour as rated by their employees and turnover behaviour. Specifically, when alternatives in the labour market were high or medium, the perceived quality of managers’ virtual listening reduced turnover behaviour. Finally, the perception of the IT employees supervisors’ virtual listening moderated the relationship between organisational deviance and turnover intention among high-tech employees.

Evaluating supervisor listening in the high-tech firm may have value in terms of its relationship to outcomes such as retaining employees, turnover intention and especially turnover behaviour. The effect on turnover behaviour and of that new constellation of antecedents on turnover behaviour when people work remotely was not researched yet and important for the post COVID-19 era. Additionally, in contrast to most studies of turnover, this study also focus on the positive aspects of turnover and especially turnover behaviour to organisations in general and especially to high-tech firm and not just the negative aspect as was researched until now. Another contribution is the finding that when employees perceived their managers’ virtual listening quality as high, the effect of deviance as a type of OMB on turnover behaviour was positive. Namely, the listening as a moderator and turnover assisted in making the organisation cleaner from inappropriate behaviour. Additionally, when alternatives in the labour market are high or medium, perceived quality of virtual listening of managers as rated by their employees can reduce turnover behaviour. This virtual listening–turnover relationship and the moderator of alternatives to current work had not previously been found in the turnover literature and this is also significant a contribution to the turnover and withdrawal literature.

The study evaluates the effects of GVC participation on firm productivity and profitability. Hence this study aims to find evidence whether there is a clear difference between the productivity and profitability effects of simple and complex backward and forward participations for Turkish firms.

The authors employ a firm level data from the Türkiye's both first and second top 500 industrial enterprises from 1993 to 2019. In addition, the authors calculate country-sector level both backward and forward GVC participation indices with their simple and complex sub-indices for each year from 1990 to 2015 from the Full Eora data of the Eora Global Supply Chain Database. The authors estimate the model with OLS and fixed effects. To understand the role of the 2008 global crisis, the authors also undertake estimations for the pre-crisis and post-crisis. The authors also divide the data by R&D intensity of sectors.

While backward GVC participation lowers both labor productivity and profitability growth, forward GVC participation promotes both. Moreover, simple and complex backward participation have similarly negative effects on productivity and profitability growth, simple and complex forward participation have the completely opposite effects though. The authors then provide substantial evidence for the differing effects of participation on productivity and profitability growth between pre-crisis and post-crisis periods. Interestingly, backward participation has a negative impact for both hi-tech and low-tech firms while forward participation boosts the productivity growth only for low-tech firms, probably due to the relatively more upstream position of low-tech firms.

To the best of the knowledge, no previous study has yet examined the profitability effects of GVC for firms. Second, in addition to overall backward and forward GVC participation rates, the authors also calculate and utilize simple and complex GVC measures in the estimations. Third, to reveal whether the global financial crisis leads to a shift in the productivity and profitability effects of GVCs, the authors separately run the regressions for the pre- and post-crisis periods. Fourth, the authors then investigate the argument that hi-tech sectors/firms could benefit more from joining GVCs compared to firms in low-tech technology sectors.

The purpose of this study paper is to identify and prioritize the factors affecting the knowledge flow in high-tech industries.

This research is applied in terms of purpose and descriptive-survey in terms of data collection method. This research has been done in a qualitative–quantitative method. In the qualitative part, due to the nature of the data in this study, expert interviews have been used. The sample studied in this research includes 35 managers and expert professors with experience in the field of knowledge management working in universities and high-tech industries who have been selected by the method of snowball. In the quantitative part, the questionnaire tool and DANP multivariate decision-making method have been used.

In this study, a multicriteria decision-making technique using a combination of DEMATEL and ANP (DANP) was used to identify and prioritize the factors affecting the knowledge flow in high-tech industries. In this study, the factors affecting the knowledge flow, including 8 main factors and 31 subfactors, were selected. Human resources, organizational structure, organizational culture, knowledge communication, knowledge management tools, knowledge characteristics, laws, policies and regulations and financial resources were effective in improving knowledge flow, respectively.

By studying the research, it was found that the study area is limited, and the previous work has remained at the level of documentation and little practical use has been done. In previous research, the discussion of knowledge flow has not been very open, and doing incomplete work causes limited experiences and increases cost and time wastage, and parallel work may also occur. Therefore, to complete the knowledge management circle and fully achieve the research objectives, as well as to make available and transfer the experiences of people working in this field and also to save time and reduce costs, the contents and factors of previous models have been counted. It is designed for high-tech industries, a model for the flow of knowledge.

Based on the density dependence theory, this paper attempts to explore how two types of interdependence among firms located in the same national high-tech zones (NHTZs) – mutualism and competition – affect entrepreneurship in the NHTZs. The authors suggest that increasing firm density can help enhance legitimacy and form mutual networks. However, as the competition becomes fierce, the above positive relationship will weaken when the firm density exceeds a certain level. In addition, the authors are interested in whether the age of NHTZs would affect their sensitivity to legitimacy and competition and whether firm density affects entrepreneurship.

This article formulates two hypotheses from the theoretical deduction. The hypotheses are examined using the ordinary least squares (OLS) regression with a unique, unbalanced panel dataset of Chinese NHTZs spanning from 2014 to 2021. Considering potential endogeneity risk among the variables, the authors attempt to lag variables and ultimately find the results are still robust.

Drawing upon the density dependence theory, the empirical results show firm density is conducive to promoting entrepreneurship, while the positive relationship between community density and NHTZs' entrepreneurship gradually weakens as the firm density surpasses a certain level. The dynamics between mutualism and competition have different impacts on NHTZs' entrepreneurship. In addition, the results demonstrate that the linkage between firm interdependence and entrepreneurship is stronger for younger NHTZs. Firm density has an impact on entrepreneurship through legitimacy and excessive competition effects.

On the one hand, the research period of this paper is 2014–2021, as the China Torch Statistical Yearbook only started to publish operating revenues in 2014, so the data period of this paper is relatively short. More research can be done in the future when more data is disclosed. On the other hand, the qualitative analysis cannot be conducted because of the limited data and materials. In future research, the qualitative analysis of entrepreneurial activities in NHTZs, such as questionnaires or case studies, needs to be supplemented, which will be an interesting direction.

Most existing research has not distinguished the differences between NHTZs (Wang et al., 2019), especially the differences in legitimacy and access to resources caused by the age of NHTZs. This article considers the heterogeneity between NHTZs, which helps to provide theoretical and practical evidence for a transition economy like China to make trade-off decisions on balancing absorbing new entrants with promoting the efficient allocation of resources based on the density and age of NHTZs.

Drawing upon density dependency theory, this paper enriches the literature on agglomeration and entrepreneurship with a new perspective and extends the study to NHTZs.

First, this paper provides new evidence on how agglomeration affects entrepreneurship from an ecological perspective with the help of mutualism and competition interdependence. Most studies have explored the role of agglomeration in entrepreneurship, focussing on social networks, knowledge spillovers or resource endowments (Acs et al., 2013; Capozza et al., 2018; Yu, 2020). Drawing upon density dependency theory, this paper enriches the literature on agglomeration and entrepreneurship with a new perspective and extends the study to NHTZs. Second, the emphasis of science parks has been primarily on qualitative or case studies (Salvador et al., 2013; Guo and Verdini, 2015; Xie et al., 2018). We have diversified the quantitative research between agglomeration and entrepreneurship by using panel data from Chinese NHTZs from 2014 to 2021. Third, most existing research has not distinguished the differences between NHTZs (Wang et al., 2019), especially the differences in legitimacy and access to resources caused by the age of NHTZs. This article considers the heterogeneity between NHTZs, which helps to provide theoretical and practical evidence for a transition economy like China to make trade-off decisions on balancing absorbing new entrants with promoting the efficient allocation of resources based on the density and age of NHTZs. Finally, this paper meticulously investigates the profound influence and underlying mechanisms of firm density within NHTZs on entrepreneurship. It discerns two distinct mechanisms at play: the legitimacy effect and the impact of excessive competition resulting from firm density. This comprehensive analysis significantly contributes to our comprehension of the intricate interplay between firm density and entrepreneurship, shedding light on the dynamics of competition and mutual benefits.

This study aims to investigate the influence and impact mechanism of capital tax incentives on firm innovation.

This study employs the difference-in-differences (DID) method, in conjunction with the exogenous impact of accelerated depreciation (AD) pilot policy. This study selects Chinese listed companies from 2010 to 2017 as the research sample.

Firstly, AD exerts a substantial positive effect on the quantity and quality of the innovation output of firms, and the positive impact results primarily from heightened investment in fixed assets, particularly, machinery and equipment. Secondly, the influence of the policy is pronounced in non-state-owned enterprises, mature enterprises, less capital-intensive enterprises and non-high-tech industries, which all exhibit strong innovation incentives. Lastly, the tax incentive policy significantly stimulates firm innovation in the short term, but its long-term impact on innovation incentives lacks statistical significance.

This study highlights the significance of capital tax incentives in facilitating the innovation process in firms.

Robots are widely used in industrial manufacturing and service industries around the world. However, most of the previous studies on industrial robots use data at the national or industry level in the context of developed countries. This study examines the impact of imported industrial robots on firm innovation at the firm level in China.

Drawing on a large dataset of more than three million records in China, including non-publicly traded small and medium firms, the authors adopt a difference-in-differences method to investigate the impact and channels of industrial robots on firm innovation.

The authors find that the application of industrial robots increases firm innovation. Two possible channels are identified through which robots promote innovation: alleviation of financial constraints and the improvement of human capital. Further analysis shows that the effect of robots on innovation is more pronounced for firms that are highly dependent on external financing, belong to high-tech industries, import high-end robots, have insufficient supply of skilled labor and private firms (non-SOEs). The authors also find that industrial robots increase the firms' innovation quality and the marginal contribution of innovation to firms' total factor productivity.

This study provides big data evidence of the unintended positive consequences of industrial robots on firm innovation. The results are helpful to clarify the controversy of industrial robots. It also has important implications for government industrial policy making, firm innovation and human resource management.

This paper aims to investigate the influence of the regional business environment on local firm innovation, considering various dimensions such as administrative, financial and legal environments.

Multiple regression analysis is employed to analyze archival data for firms listed on Chinese stock markets.

We find that the optimizations of the administrative and financial environments positively affect firm innovation, whereas the legal environment does not exert a similar impact. Our analysis also reveals that the business environment’s optimization significantly influences innovation in firms that are small, non-state-owned and operating in high-tech industries. Furthermore, the business environment acts as a moderating variable in the relationship between firm innovation and firm value.

This study contributes to a more comprehensive understanding of institutional-level determinants of firm innovation, highlighting the nuances of the legal environment and the importance of context-specific analysis, especially in emerging markets like China.

Developing countries can significantly enhance firm innovation by improving the business environment, including the optimization of administrative and financial systems, reducing transaction costs and ensuring capital supply. Tailored legal frameworks and alternative institutional strategies may also be explored.

This study explicitly emphasizes the governmental role in promoting firm innovation, shedding light on policy formulation and strategic alignment with local administrative policies.

To the best of our knowledge, this paper is the first to explore the relationship between the business environment and firm innovation using World Bank indicators in an emerging market context, providing novel insights into the unique dynamics of legal, financial and administrative sub-environments.

The focus is on determining the long-term relationship in explaining how technological capabilities interact with trade and global value chain (GVC) participation to aid in the upgradation process using a panel auto-regressive distributed lag (ARDL) model. The results suggest that export of both low-skill and medium-skill technology-intensive manufactures and patents by residents positively and significantly impact GVC participation.

This paper examines the dynamic linkages between GVC participation and technological capability of major Asian countries in a comparative (1995–2018) perspective.

This implies that certain sectors enable greater integration into GVCs in the long-run, supported by critical learning variables. Further, with the help of the panel causality test, a bi-directional flow between GVC participation and export of high-technology manufactures and import of labour-intensive technology manufactures is witnessed. Even a one-way flow from research and development (R&D) intensity to GVC participation is seen.

The technological capabilities are found to be characterising the initial structure of local enterprises in trade and GVCs, as well as the extent to which emerging-market firms may harness knowledge flows and migrate into high-tech industries.