High-tech Industries In China Research Articles

Intelligent analysis on the factors influencing the innovation and development performance of high-tech industry in China, based on two-stages model

Intelligent analysis on the factors influencing the innovation and development performance of high-tech industry in China, based on two-stages model

A proposed framework for accelerated innovation in data-driven environments

PurposeIn today’s rapidly changing business environment, the case for accelerated innovation processes has become increasingly compelling at both a theoretical and practical level. Thus, the purpose of this paper is to propose a conceptual framework for accelerated innovation in a data-driven market environment.Design/methodology/approachThis research is based on a two-step approach. First, a set of propositions concerning the best approaches to accelerated innovation are put forward. Then it offers qualitative evidence from five case studies involving world-leading firms, and explains how innovation can be accelerated in different kinds of data-driven environments.FindingsThe key sets of factors for accelerated innovation are: collateral structure; customer involvement; and ecosystem of innovation. The proposed framework enables firms to find ways to innovate – specifically, to make product innovation faster and less costly.Research limitations/implicationsThe findings from this research focus on high-tech industries in China. Using several specific innovation projects to represent accelerated innovation could raise the problem of the reliability and validity of the research findings. Additional research will probably be required to adapt the proposed framework to accommodate the cultural nuances of other countries and business environments.Practical implicationsThe study is intended as a framework for managers to apply their resources to conduct product innovation in a fast and effective way. It developed six propositions about how, specifically, data analytics and ICTs can contribute to accelerated innovation.Originality/valueThe research shows that firms could harvest external knowledge and import ideas across organisational boundaries. An accelerated innovation framework is characterised by a multidimensional process involving intelligence efforts, relentless data collection and flexible working relationships with team members.

Research on Innovation Knowledge Spillover Effect of China’s High-Tech Industry R&D-Base on Multidimensional Spatial Weight Matrices

Based on the panel data of R&D activities of the provincial high-tech industry in China from 1998 to 2014, this paper adopts the spatial weight matrix of different dimensions including geographical distance, technical distance, economic distance, proximity distance, and human capital distance, to construct a spatial econometric model to analyze the knowledge spillover effects of R&D activities through both local and transnational routes. The results show that in the case of spatial auto-correlation of the dependent variables, the results of the spatial panel model are more accurate and reliable than those obtained by the conventional panel model. The spatial coefficients of the spatial econometric model based on five different spatial weight matrices are all very significant, and there is a clear spatial correlation between the R&D activities of high-tech industries in different regions. Labor input and exports have a positive impact on innovation output, but the introduction of technology will hinder independent innovation in China’s high-tech industry, and the impact of capital investment to innovation output is uncertain, as it closely relates to the set of models. In addition, the space knowledge spillover effect through the local approach is larger than that produced by the transnational route.

Assessing the relative efficiency of Chinese high-tech industries: a dynamic network data envelopment analysis approach

The high-tech industry in China has largely developed in recent decades. To provide a basis for the sustainable development of high-tech industry, the government should evaluate its performance to find out its strengths and weaknesses that are critical for the future improvement of business operations. Dynamic network data envelopment analysis has received considerable attention from researchers evaluating the performance of a system during long-term production. However, studies on the issue of shared outputs caused by the lagged production effect of inputs are rare. In a real high-tech industry, the outputs during a production period are derived from the inputs in that production period and also from the inputs in the previous period. These intertemporal shared outputs in a system cannot be easily divided into different periods. Thus, a new dynamic two-stage data envelopment analysis approach is proposed to measure the efficiency of such system with a two-stage structure and shared outputs. We divide a high-tech activity system into two stages: technology research and development stage and technology digestion and absorption stage, where intertemporal shared outputs occur. Empirical results from our approach indicate that Chinese high-tech industries are weak in the technology digestion and absorption stage. Finally, suggestions are provided to improve the overall efficiency of Chinese high-tech industries.

Research on the Impact of International Technology Spillover and Absorptive Capacity on the Independent Innovation of High-tech Industries

International technology spillover effect has been regarded as an important path to realize independent innovation as for the host countries. And the study about whether absorptive capacities of high-tech industries in China improve the achievement of international technology spillover effect from a meso perspective is the weak link in current research. From the perspectives of overall high-tech industries and heterogeneous sub-sectors, this paper theoretically and empirically analyzes the effects of international technology spillover and absorptive capacity on independent innovation. It arrives at the results as follows:firstly, international technology spillover effect plays a sound promotion role in the overall independent innovation of high-tech industries; secondly, for the research results of heterogeneous sub-sectors of high-tech industries, the spillover effect of foreign RD absorptive capacities of some industries cannot promote the realization of international technology spillover effect and absorptive capacities of another industries have promoted the realization of international technology spillover effect. This paper has played a positive role in the development of overall high-tech industries and sub-sectors from introduction-imitation mode to introduction-absorption and re-innovation mode.

Dynamic network data envelopment analysis based upon technology changes

ABSTRACTThe existing dynamic models assume the technology is unchanged in which the same factor should have the same multiplier, no matter which process it is associated with. The internal network structures embedded in a multi-period system are ignored in the literature. The current paper considers that the technology is changed in the dynamic system The same factor may have different multipliers in different periods, except for the variables of intermediate measures connecting two stages in one period and flows connecting two consecutive periods. An additive aggregation dynamic network data envelopment analysis is developed to measure the multi-period systems with a two-stage process embedded in each period. The system efficiency, overall efficiency and stage efficiencies of each period can be derived, and the relationship between the system efficiency and period efficiencies can be identified. The newly developed dynamic network model is nonlinear, and can be transformed to a semi-definite programming problem. A case of high-tech industry in China is illustrated to the approach.

Study on the R&D performance of high-tech industry in China - based on data envelopment analysis

Having number of scientific research institutions, number of scientific researchers, and new product R&D expenses as the input indices of R&D performance and new product sales revenue, number of patent application, and number of valid patents as the output indices, Data Envelopment Analysis (DEA) is applied in this study to calculate the input and output based technical efficiency of five categories of industries in high-tech industry in China. Besides, the projection analysis is combined for the empirical research. The results reveal that, under the same scientific research output rate, the inputs of pharmaceutical manufacturing industry are comparatively higher than those of the other four industries that it requires further optimization. Finally, targeting suggestions are proposed according to the research conclusion.

Are High-Performance Human Resource Practices In Organizations Creative or Noncreative?

Researchers have found that high-performance human resource practices (HPHRP) are positively related to good firm performance and sustainable competitive advantage; however, there is not substantial evidence about their effect on individual creativity. We examined the relationship between HPHRP and individual creativity with a sample of 466 employees of high-tech industries in China. Findings showed that HPHRP had an inverse U-shaped relationship with individual creativity, which was positively moderated by proactive personality. When the employee had a very proactive personality, the positive relationship between human resource practices that were not high performance and individual creativity, and the negative relationship between HPHRP and individual creativity escalated. Evidence also supported a mediation effect of intrinsic motivation on the interaction effect of HPHRP, proactive personality, and individual creativity.

Efficiency evaluation of the regional high-tech industry in China: A new framework based on meta-frontier dynamic DEA analysis

This paper proposes a new framework based on the combination of the dynamic DEA, meta-frontier analysis theory, and truncated regression model, and then focuses on the efficiency evaluation of regional high-tech industries in China. For all of the overall technical efficiency, technical efficiency, and scale efficiency scores, the east area is always in the lead, with the central and west areas obviously lagging behind. The eastern area has the highest technology level, whereas the west and central areas fall behind in turn. However, the meta-technology ratio of the west area has rapidly increased and presents a trend of catching up with the east. The variables of GRP per capital, total exports and imports, highway mileage per capita, and ratio of tertiary industry to GRP have positive relationships with technical efficiency, and the time trend exhibits a negative coefficient.

Organizational Structure, Cross-functional Integration and Performance of New Product Development Team

In the era of global competition, how to improve the performance of new product development team is an important scientific issue. In this study, with the organizational structure of the enterprise as the explanatory variable, the cross-functional integration of the team as the intermediary variable, a cross level conceptual model is constructed to analyze the performance of new product development team, and the survey data of manufacturing industry and high-tech industry in China are analyzed by using multilevel linear model. The research results show that the characteristics of organizational structure has impact of cross levels on performance of new product development team, cross-functional integration of the team has a partial mediating effect between the mechanical organization and the performance of the new product development team and a complete mediating effect between the organic organization and the performance of the new product development team.

The Effects of Government Expenditures Product and Innovation on Industrial Growth: Evidence from China’s High Technology Industry

The paper seeks to investigate the question of how expenditure for product and technology innovation may affect industrial production using panel data for China’s high technology industry, 2004-2014. We use panel data for 14 high-tech industry in China for the period 2004-2014. We conducted panel framework analyses, leading to using a pooled mean group estimator to test the long-run relationship between the variables in question. The result of the empirical test showed that expenditures for product innovation has a positive effect on industrial growth, indicating that an increase of 1% in product innovation expenditures leads to an increase of 0.88% in the growth of China’s hi-tech industry. In addition, real GDP per capita positively affects industrial growth, such that an increase of 1% in real GDP per capita induces an increase of 0.34% in industrial growth. The study, however, shows that expenditures for technology innovation have a negative effect on industrial growth. We propose policy implications based on these results.

The dynamic DEA assessment of the intertemporal efficiency and optimal quantity of patent for China’s high-tech industry

This study uses the dynamic data envelopment analysis (DEA) model to evaluate intertemporal efficiency for high-tech industries in China. The significant difference from previous studies is the assumption for patents, which are defined to be a carry-over intermediate linking different terms. The model further provides an indicator of adjustment ratio for patents, based on the assessment of optimal quantity of patents. Output and input inefficiency indicators are also developed in the model to explore the sources of operational inefficiency. The empirical results conclude that intertemporal efficiency trends upward over time; the quantity of patents is assessed to be in shortage during the early terms, but excessive in recent terms; and that deficits in financial output is a significant factor in creating inefficiency.

Do government grants promote innovation efficiency in China's high-tech industries?

Despite extensive discussion about the important role of government in enterprise development, the function of government grants in the innovation activities of high-technology (high-tech) industries is still unclear. In this paper, the stochastic frontier model and a unique panel data set of 17 high-tech industries in China spanning the 2001–2011 period are applied to explore how government grants affect the innovation performance of these industries. Results indicate that the innovation efficiency of high-tech industries rapidly improved in the past decade. However, it is found that government grants exert a negative influence on innovation efficiency of high-tech industries. However, the impact of private R&D funding is significant and positive. Furthermore, when the high-tech industries are grouped into five sub-industries, the results show that government grants had different effects on the innovation in each sub-industry.

Social capital, portfolio management capability and exploratory innovation: evidence from China

PurposeSocial capital is critical for firms to conduct business activities; however, whether it is always beneficial for exploratory innovation and the specific and contingent effects of each dimension remain unknown. This paper aims to examine the role of three dimensions of social capital in determining exploratory innovation and investigate how firms’ portfolio management capabilities shape these links.Design/methodology/approachSurvey data from 276 firms in high-tech industries in China are used to test the hypotheses.FindingsThe authors find that cognitive social capital negatively affects exploratory innovation, whereas relational and structural social capital both demonstrate inverted U-shaped relationships with exploratory innovation. In addition, portfolio management capability positively moderates the relationships between the three dimensions of social capital and exploratory innovation.Practical implicationsGiven the advantages and disadvantages, managers should be prudent in the establishment of social capital; moreover, firms should develop and improve their portfolio management capabilities to effectively manage their relationships in the pursuit of exploratory innovation.Originality/valueThis research contributes to the social capital theory and innovation literature in two ways. First, it provides a multi-dimensional examination of the effects of social capital on exploratory innovation and the empirical evidence of the negative side of social capital. Second, it extends the extant literature by introducing a more holistic perspective and proposing that portfolio management capability helps firms to overcome the negative effects and strengthen the positive effects of social capital on exploratory innovation.

A comparative study of land efficiency of electronics firms located within and outside development zones in Shanghai

The establishment of development zones is a vital strategy for attracting foreign direct investments and developing high-tech industries in China. Due to the absence of firm-level land use data, it is unclear whether firms located within development zones consume land more efficiently than their counterparts outside development zones. To fill this gap, this study compares land use efficiency of electronics firms located within and outside development zones in Shanghai. Results indicate that electronics firms within the development zones are significantly more efficient in land uses compared to those outside development zones. This study further shows that the nature of development zones and firms' attributes both condition land use efficiency of firms. This study highlights that the higher land efficiencies of firms in development zones are linked to governmental supports, technological externalities and international linkages.

Government grants, private R&D funding and innovation efficiency in transition economy

Although the development of the high-tech industry is part of the national agenda of many countries, particularly transition economies, few studies have analysed innovation efficiency in countries with environments unfavourable to high-tech industry development. This study explores the relationships of government grants, private R&D funding and innovation efficiencies of the high-tech industry in China. We use a stochastic frontier analysis model to study the roles of government and market mechanisms in high-tech industry innovation from 1995 to 2008. Findings show that government grants do not crowd out private funding, but stimulate private R&D expenditure. Private R&D funding has positively influenced innovation in the Chinese high-tech industry, and efficiency potentials are widely under-exploited. Additionally, government grants are observed to negatively impact innovation by large firms in the Chinese high-tech industry. Furthermore, we reveal that human capital can promote the innovation performance of high-tech firms, excepting those of medium scale. The findings provide insightful perspectives on China's high-tech industry.

The Empirical Study on R&D Efficiency of High-Tech Industry in China

The Empirical Study on R&D Efficiency of High-Tech Industry in China

Framework of High-Technology Industry Innovation of China: Intellectual Property Protection and Industrial Knowledge Base

Based on panel data from 2000 to 2012, quantitative analysis was conducted on the relationship between intellectual property protection and China’s high-technology industry innovation. Results indicate that the intensity of intellectual property protection in China increases year by year and has a positive effect on the industrial knowledge base of the high-tech industry in China. The industrial knowledge base of each sub-industry in the high-tech industry of China has positive effects on owning inventive patents (OIP) and sales revenue of new products (SRNP). However, but stringent intellectual property protection has a certain inhibitory effect on OIP and SRNP for the manufacture of medicines, manufacture of medical equipment and measuring instruments, and manufacture of electronic and communication equipment. Moreover, stringent intellectual property protection has negative effects on OIP of all five sub-industries of the high-tech industry in China.

A GM(1,N)-based economic cybernetics model for the high-tech industries in China

Purpose – The purpose of this paper is to propose an economic cybernetics model based on the grey differential equation GM(1,N) for China's high-tech industries and provide the necessary support to assist high-tech industries management departments with their policy making. Design/methodology/approach – Based on the principle of grey differential equation GM(1,N), the grey differential equations of five high-tech industries in China are established using the net fixed assets, labor quantity and patent application quantity as cybernetics variables. After the discretization and first-order subtraction reduction to the simultaneous equation of the five grey models, a linear cybernetics model is resulted in. The structure parameters in the cybernetics system show explicit economic significance and can be identified through least square principle. At last, the actual data in 2004-2010 are introduced to empirically analyze the high-tech industrial system in China. Findings – The cybernetics system for China's high-tech industries are stable, observable, and controllable. On the whole, China's high-tech industries show higher output coefficients of the patent application quantity than those of net fixed assets and labor quantity. This suggests that China's industry development mainly depends on technological innovation rather than capital or labor inputs. It is expected that the total output value of China's high-tech industries will grow at an average annual rate of 15 percent in 2011-2015, with contributions of pharmaceuticals, aircraft and spacecraft, electronic and telecommunication equipments, computers and office equipments, medical equipments and meters by 21, 16, 13, 10, and 28 percent, respectively. In addition, pharmaceuticals, as well as medical equipments and meters, present upward proportions in the gross of Chinese high-tech industries significantly. Electronic and telecommunication equipments, plus computers and office equipments exhibit an obvious decreasing proportion. The proportion of the output value of aircraft and spacecraft is basically stable. Practical implications – Empirical analysis results are helpful for related management departments to formulate reasonable industrial policies to keep the sustained and stable development of the high-tech industries in China. Originality/value – Based on the grey differential equation GM(1,N), this research puts forward an economic cybernetics model for the high-tech industries in China. This model is applicable to the economic system with small sample data set.

An Optimized Grey Dynamic Model for Forecasting the Output of High-Tech Industry in China

The grey dynamic model by convolution integral with the first-order derivative of the 1-AGO data andnseries related, abbreviated as GDMC(1,n), performs well in modelling and forecasting of a grey system. To improve the modelling accuracy of GDMC(1,n),ninterpolation coefficients (taken as unknown parameters) are introduced into the background values of thenvariables. The parameters optimization is formulated as a combinatorial optimization problem and is solved collectively using the particle swarm optimization algorithm. The optimized result has been verified by a case study of the economic output of high-tech industry in China. Comparisons of the obtained modelling results from the optimized GDMC(1,n)model with the traditional one demonstrate that the optimal algorithm is a good alternative for parameters optimization of the GDMC(1,n)model. The modelling results can assist the government in developing future policies regarding high-tech industry management.