Research on the effects of command-and-control and market-oriented policy tools on China's energy conservation and emissions reduction innovation

The impact of environmental regulation on technology innovation is a hot spot in current research where a large number of empirical studies are based on Porter Hypothesis(PH). However, there are still controversies in academia about the establishment of "weak" and "narrow" versions of PH. Based on the panel data of application for patent of energy conservation and emission reduction(ECER) technology of Chinese city scale during 2008-2014, comprehensive energy price, pollutant emission, etc., mixed regression model and systematic generalized method of moments method were adopted, respectively,to study the impact of market-oriented and command-and-control policy tool on China's ECER technology innovation. The results show that the environmental regulation hindered the technological innovation in the immediate phase; however, it turned out to be positive in the first-lag phase. Hence, the establishment of "weak" PH is time-bounded. The command-and-control policy tool played a more positive role in promoting technological innovation in the first-lag phase than market-oriented policy tool. Therefore, "narrow" PH is not tenable. The reason is that the main participants of China's ECER technology innovation are state-owned companies and public institutions. Regionally speaking, the impact which command-and-control policy tool has on technological innovation at sight was nonsignificant in the eastern, the central, and the western regions of China whilst market-oriented policy tool had a negative effect. And market-oriented policy tool in the central region had strongest negative effect, which would diminish in the eastern region and become weakest in the western region. This was related to regional energy consumption level and the market economic vitality.

A quantitative study of disruptive technology policy texts:An example of China’s artificial intelligence policy

Purpose:The transformative impact of disruptive technologies on the restructuring of the times has attracted widespread global attention.This study aims to analyze the characteristics and shortcomings of China’s artificial intelligence(AI)disruptive technology policy,and to put forward suggestions for optimizing China’s AI disruptive technology policy.Design/methodology/approach:Develop a three-dimensional analytical framework for“policy tools-policy actors-policy themes”and apply policy tools,social network analysis,and LDA topic model to conduct a comprehensive analysis of the utilization of policy tools,cooperative relationships among policy actors,and the trends in policy theme settings within China’s innovative AI technology policy.Findings:We find that the collaborative relationship among the policy actors of AI disruptive technology in China is insufficiently close.Marginal subjects exhibit low participation in the cooperation network and overly rely on central subjects,forming a“center-periphery”network structure.Policy tool usage is predominantly focused on supply and environmental types,with a severe inadequacy in demand-side policy tool utilization.Policy themes are diverse,encompassing topics such as“Intelligent Services”“Talent Cultivation”“Information Security”and“Technological Innovation”,which will remain focal points.Under the themes of“Intelligent Services”and“Intelligent Governance”,policy tool usage is relatively balanced,with close collaboration among policy entities.However,the theme of“AI Theoretical System”lacks a comprehensive understanding of tool usage and necessitates enhanced cooperation with other policy entities.Research limitations:The data sources and experimental scope are subject to certain limitations,potentially introducing biases and imperfections into the research results,necessitating further validation and refinement.Practical implications:The study introduces a three-dimensional analysis framework for disruptive technology policy texts,which is significant for formulating and enhancing disruptive technology policies.Originality/value:This study utilizes text mining and content analysis techniques to quantitatively analyze disruptive technology policy texts.It systematically evaluates China’s AI policies quantitatively,focusing on policy tools,policy actors,policy themes.The study uncovers the characteristics and deficiencies of current AI policies,offering recommendations for formulating and enhancing disruptive technology policies.

Research on the Work-for-Relief Policy within the Scope of Comprehensive Rural Revitalization:Quantitative Analysis of Policy Texts Based on 71 Policy Documents

Work-for-relief plays a unique role in China’s journey toward modernization.From the perspectives of policy tools and interest analysis,this paper uses quantitative analysis of policy texts and integrates grounded theory to build a policy expression analysis model to discuss the current work-for-relief policy system.The study found that China’s use of the work-for-relief policy is unbalanced,and it is necessary to enhance the involvement of non-governmental sectors,as well as to fully consider the policy’s target groups and the social issues that need addressing.

Impact of scientific and technological innovation policies on innovation efficiency of high-technology industrial parks-A dual analysis with linear regression and QCA

Scientific and technological innovation policies play a critical role in the innovative development of high-technology industrial parks.However,it remains unclear how scientific and technological innovation policies impact the innovation efficiency of hightechnology industrial parks and what the impact pathways are.An in-depth investigation of this topic can give an insight into the inherent relation between the scientific and technological innovation policies and technological innovation.By conducting a theoretical analysis,this study empirically analyzed the impact of scientific and technological innovation policies on the innovation efficiency of high-technology industrial parks.The main research methods applied in this study were linear regression and qualitative comparative analysis(QCA).The results showed that the policy targets drove innovation efficiency in a relatively minor way.Among all policy tools,the demand-based policy tools had the most significant influence on innovation efficiency.The supply-based and environment-based policy tools had notable positive impacts during the lag periods of policies.The policy mix pathways for scientific and technological innovation policies that impact innovation efficiency come in four forms,namely,the targets-directed,demand-driven,supplydominated environment optimization,and environment-dominated comprehensive pathways.Therefore,this study put forward proposals on classifying and refining the scientific and technological innovation policies and optimizing the policy mix-driven models.

What Drives Cost Efficiency of Banks in China？

This study uses stochastic frontier analysis to examine the factors that influenced cost efficiency of banks in China from 2005 to 2013. The results indicate that policy variables, such as the reserve requirement ratio, the interest rate spread and open market operations by the People＇s Bank of China, are effective in improving the cost efficiency of banks, but shadow banking variables may reduce cost efficiency. Among the various bank types, city commercial banks appear to be the most efficient and foreign banks are the least efficient. The present study suggests that policy-makers can have a positive influence on bank cost efficiency by adjusting macro policy variables on different types of banks and by requiring more information on the shadow banking activities to improve monitoring.