This paper establishes the evaluation index system of digital transformation of manufacturing enterprises, and uses the combined weight model of critical entropy method to evaluate the digital transformation of 64 automobile manufacturing enterprises listed as of 2012 from 2018 to 2020.Then this paper puts forward four research hypotheses about the impact of digital transformation on enterprise performance,and verifies the research hypotheses by constructing an individual fixed effect model.The results show that the digital transformation of China's automobile manufacturing enterprises has developed well,and the digital index of more than 50% of enterprises has improved in three years.Digital transformation has a significant positive impact on enterprise performance.Digital transformation will improve enterprise performance by reducing enterprise operating cost rate.Digital transformation can reduce the management expense rate and sales expense rate of enterprises.

Based on the theoretical analysis of how the digital economy can alleviate urban poverty, the impact of the digital economy on relative urban poverty is empirically analyzed using panel data of 31 Chinese provinces.The study finds that:the digital economy can significantly alleviate urban poverty.After the robustness test and considering the endogenous,the conclusion is still valid.In contrast,the poverty reduction effect of digital economy in the western region is greater than that in the eastern region.There is a single threshold effect in reducing poverty in digital economy.When the threshold value is exceeded,the poverty reduction effect is significantly improved.The higher the poverty level,the more obvious the poverty reduction effect of digital economy.The poverty alleviation mechanism of digital economy is to increase employment and stimulate entrepreneurial enthusiasm.In order to give full play to the poverty reduction effect of digital economy,this paper puts forward countermeasures and suggestions from the aspects of promoting the construction of digital infrastructure,improving the digital level of public services and establishing a longterm poverty alleviation mechanism.

In the digital era, enterprise digital transformation has become an important driver of innovation in electronics manufacturing firms.Using Shanghai and Shenzhen A-share electronics manufacturing firms as research samples,we empirically examine the impact of enterprise digital transformation on enterprise innovation and the transmission mechanism.The results show that the higher the environmental uncertainty,the stronger the innovation-driving effect of enterprise digital transformation.Further research shows that the driving effect of enterprise digital transformation on innovation is more pronounced in non-state-owned firms compared to state-owned firms when executive literacy is high or the firm is in a recessionary stage.The level of regional marketization also has an asymmetric effect on the innovation-driving effect of corporate digital transformation.

Based on the relevant data of 31 provinces in China from 2011 to 2020, this paper selects indicators from five aspects, including internet penetration rate, employment situation of information industry and output situation of digital industry.Calculate the digital economy level of 31 provinces (autonomous regions and cities), then examines the relationship between the China's digital economy and the real economy through grey correlation degree,coupling coordination degree and spatial correlation network.The results show that the development pattern of China's digital economy is generally high in the east and low in the west,with obvious regional differences.Provinces with faster development of digital economy can better reflect the positive promotion effect of digital economy and have higher coupling coordination degree with real economy.Provinces with faster development of digital economy and higher coupling coordination degree with real economy have more significant spatial external spillover effect on surrounding areas.Finally, the government should accelerate the development of digital economy, give full play to the advantages of digital economy to promote the development of real economy, strengthen supervision and guidance, and avoid the emergence of digital economy from real to virtual phenomenon.

Based on the quasi-natural experiment formed by the integration of industrialization and informatization pilot program,this paper studies the impact of digital transformation on capital allocation efficiency with the listed manufacturing enterprises as the research object.We finds that: (1) The digital transformation of enterprises can significantly improve capital allocation efficiency, which is valid after robust tests. (2) Digital transformation can promote the efficiency of capital allocation by improving enterprise information transparency and reducing enterprise financing constraints. (3) Through heterogeneity analysis and test, compared with state-owned enterprises and regulatory enterprises,the effect of digital transformation to improve the efficiency of enterprise capital allocation is more obvious in non-state-owned enterprises and competitive enterprises.

Technological innovation is the endogenous driving force for the high-quality development of logistics.Understanding the spatial differences and evolutionary processes of technological innovation in my country's regional logistics industry is conducive to proposing targeted countermeasures to reduce regional differences in technological innovation levels,promote the coordinated development of the logistics industry,and enhance international competitiveness.This article uses crawler technology to obtain logistics industry patent data from the national key industry patent information service platform,uses Dagum Gini coefficient to analyze the spatial differences and sources of technological innovation in China's logistics industry;and finally the Gaussian kernel density function is used to reveal its dynamic evolution process.The study finds that:the spatial difference of technological innovation in China's logistics industry mainly comes from regional differences.The western region has the largest difference within the circle,and the difference between the eastern and western regions is the largest.China's logistics technology innovation level is on the rise as a whole,and each region presents a different dynamic evolution process.

Continuous innovation investment is the basis for enterprises to maintain competitive advantage.In the face of increasingly concentrated buyer forces,maintaining the sustainability of innovation is the key to deal with market fluctuations and achieve sustainable development.Based on the perspective of resource capability and knowledge management,using the panel data of A-share listed companies of New Energy Vehicle parts in Shanghai and Shenzhen from 2013 to 2020,this paper empirically tests the impact mechanism of the concentration of automobile enterprises in the upstream of the industry on the innovation sustainability of parts enterprises.The research shows that there is an inverted U-shaped relationship between buyers'market power and enterprise innovation sustainability.The research on path mechanisms shows that strategic difference plays an intermediary role in the inverted U-shaped relationship between buyer's market power and enterprise innovation sustainability.At the same time,the ability of digital transformation helps to smooth the inverted U-shaped impact of buyer's market power on the sustainability of enterprise innovation.Further research shows that compared with enterprises in growth and decline,the intermediary effect of the strategic difference of mature enterprises is the highest.

As the basic unit of regional development, the improvement of urban innovation ability can effectively promote regional high-quality development.This paper uses the gravity center model, spatial coupling analysis model, and geographical detector model to analyze the spatial and temporal evolution and driving factors of the innovation ability of prefecture-level cities in five northwestern provinces of China from 2011 to 2020.The results show that from 2011 to 2020,the urban innovation capability of the five northwestern provinces of China shows a fluctuating upward trend,with an average annual growth rate of 4.39%.The regional development status has been improved, but the internal synergy of the urban innovation system is insufficient, and the efficiency of resource allocation is not high.The center of gravity of urban innovation capability and innovation environment has a strong spatial overlap.The core driving force of the change of innovation capability center of gravity gradually transforms from innovation subject and innovation performance to innovation resources,and the driving factors of the spatial distribution of urban innovation ability are mainly concentrated in the level of innovation subject.

Based on the patent application data of 5G field in China from 1989 to 2020 as research samples, this paper discusses the influence of organizational resilience on enterprise technological innovation from the perspective of cooperative network,and the moderating effect of internal knowledge heterogeneity of enterprises on the relationship between them.The research results show that organizational resilience has an inverted U-shaped impact on corporate technological innovation;internal knowledge heterogeneity of enterprises weakens the inverted U-shaped relationship between organizational resilience and corporate technological innovation.

By dividing industrial green innovation process into development and achievement transformation two stages, the paper makes a research on the spatial correlation of financial cluster to industrial green innovation efficiency, and finds that: (1) financial cluster can positive influence industrial green development innovation efficiency, but it is mainly local effect, the influence of it to neighborhood is not obvious.(2) Industrial structure and regional infrastructure can positive influence industrial green development innovation efficiency,but the level of open-door to the outside world can negative influence industrial green innovation development efficiency.(3) The promotion of financial cluster to industrial green innovation achievement transformation efficiency has choke point, its local effect is not obvious, but the influence of it to neighborhood is negative. (4) The size of industrial enterprise can negative influence industrial green innovation achievement transformation efficiency, but industrial structure, infrastructure and the level of open-door to the outside world can positive influence industrial green innovation achievement transformation efficiency.

Artificial intelligence has developed rapidly since the 21st century, and its combination with the development of various fields promotes the rapid development of various fields.This paper introduces 20 indicators covering value, technology, momentum, sentiment, reversal and 8 machine learning algorithms to predict the returns of stocks in Shanghai and Shenzhen.From the perspective of the contribution of each index to the models,this paper finds that technical index and reversal index have the highest impact on the future stock return.Then,this paper sortes these stocks according to their predicted returns and forms a trading strategy.By comparing the results of various models,it is found that the trading strategy formed by predicting the return rate can obtain significant excess returns in the Chinese market, and the prediction effect of deep neural network is the best, followed by the regularized linear machine learning model.Through reasonable prediction methods, investors can avoid their own risks, meanwhile,it can provide certain reference significance for policy makers and better understand the irrational factors in Chinese market transactions.

Based on the background of the rapid development of industrial robots, the transformation and upgrading of manufacturing industry and the rising labor cost,this paper investigates the impact of the application of industrial robots on the average labor wage.Study finds that industrial robot application infiltration density an additional unit,average wage labor will increase 215 yuan, the average industrial robot is a significant wage premium effect, and the wage premium effect significant differences between different regions, in the eastern area, middle area and northeast area is reduced, in turn in the western region.On the contrary,the application of industrial robots will have a significant negative impact on the average wage of labor.In addition,the study finds that the use of industrial robots can generate a wage premium by promoting skill upgrading.The conclusion of this paper has certain policy reference significance for promoting the coordinated development of intelligent manufacturing and labor market.

From the perspective of enterprise behavior, this paper theoretically analyzes the impact of green credit on employment scale in traditional energy industry,its mechanism and regional heterogeneity.Using the provincial panel data from 2009 to 2019, by constructing fixed effect model, mediation effect model and threshold model, the results of analysis show that green credit has a positive effect on employment in traditional energy industry on national level,but with the increase of green credit scale,the positive effect weakens.The demand for clean energy plays a partial intermediary role in the process of policy effect.In addition, there is regional heterogeneity in the policy effect of green credit: in areas with a higher proportion of secondary industry,due to high dependence on traditional energy industry, green credit has a stronger positive employment effect; in western part of China,the positive employment effect of green credit is stronger because the scale of green credit is lower.

Based on the social network analysis method, this paper analyzes the evolution characteristics of the global wind power equipment trade network topology and community structure from 2002 to 2020.The results show that: on the whole, the global wind power equipment trade network is closely linked and has the characteristics of small world.Individually,there is little difference in the centrality of each product trade network node.Among them,the trade status of China's wind power equipment industry is gradually improving and occupies a core position in each product trade network.Spatially,the wind power equipment trade network center has been continuously transferred to East Asia, forming a spatial pattern of three pillars of Europe, North America and East Asia.The evolution characteristics of each product trade network community plate show that the glass fiber trade network is relatively balanced,while the trade network of wind power equipment parts and wind turbines is obviously unbalanced.

Based on the quasi natural experiment of environmental information disclosure implemented in 2008, this paper establishes difference in difference(DID) and spatial difference in difference(SDID) models to study how environmental information disclosure affects regional economic low-carbon development.The study finds that environmental information disclosure significantly reduces carbon emissions and promoted regional economic low-carbon development.After parallel trend test,placebo test, replacement of explained variables and other tests, the conclusion is still stable.The mechanism test finds that industrial structure upgrading and technological innovation are the main channels for environmental information disclosure to promote regional economic low-carbon development.Heterogeneity analysis shows that the promotion effect of environmental information disclosure on low-carbon economy is different in geographical location, urban administrative level, energy consumption intensity and environmental supervision intensity.Further expansion analysis shows that the impact of environmental information disclosure on carbon emissions has a spatial spillover effect,which leads to the increase of carbon emissions in other regions while reducing carbon emissions in this region.The research conclusions have positive policy implications for how to reduce carbon emissions under the background of “carbon peak” and “carbon neutralization”.

After analyzing the influence mechanism of industrial agglomeration and financial agglomeration on green total factor productivity, based on the spatial panel data of 30 provinces (autonomous regions and cities) in China from 2011 to 2020, this paper empirically analyzes the relationship between industrial agglomeration,financial agglomeration and green total factor productivity and the spatial spillover effect by using the spatial durbin model.The results show that there is an inverted “U” curve relationship between industrial agglomeration and local green total factor productivity.Financial agglomeration can improve local green total factor productivity.At the same time,they also have a positive effect on the green total factor productivity of surrounding areas.In the case of changing the spatial weight matrix and sample observation time,the empirical results are still robust.Based on the above analysis, this paper deepens the research on industrial agglomeration, financial agglomeration and green total factor productivity,and provides policy reference for improving green total factor productivity.

The development of construction waste resource recovery industry needs the support of effective policy system.Quantitative evaluation of construction waste resource recovery policy can provide theoretical basis for policy formulation,adjustment and optimization.Based on the content analysis method and policy evaluation theory,this paper constructs policy effectiveness evaluation criteria and Policy Modeling Consistency index policy evaluation model based on 80 policies texts of construction waste recycling issued by China from 2001 to 2021,and further conducts empirical analysis on 6 policy texts.The results show that China's construction waste recycling law has a guiding effect on other levels of policies.The results show that China's construction waste recycling law has a guiding effect on other levels of policies.The average score of Policy Modeling Consistency index of 6 representative policy texts belongs to good level, and there is room for improvement.Policies focuses on safeguards rather than incentives,and the process of construction waste resource recycling industry in China mainly depends on enterprises,and the development of the industry is not enough.

In order to promote the recovery of enterprises from the impact of the COVID-19 pandemic, and improve the resilience of enterprises.This paper first summarizes the influencing factors of enterprise resilience, including individuals, enterprises, external environment, etc., and establishes a research framework for enterprise resilience.Secondly, combined with the characteristics of the epidemic and its prevention and control,a research model of enterprise recovery is established from the perspective of dynamics, and the composition and representation form of enterprise resilience are explained.Then, it discusses the momentum, impulse, kinetic energy, etc.of enterprise recovery, and explains the impact of resilience on the recovery state of enterprises from time and space, respectively.Finally, a process model for enterprise recovery under the background of the COVID-19 pandemic is established.The model shows that factors such as leader characteristics and capabilities, corporate resources, corporate scale, epidemic impact, and policy assistance determine the acceleration, speed, momentum, and kinetic energy of corporate recovery by affecting corporate resilience,which in turn determines the state of corporate recovery.

Knowledge is the decisive force for enterprise competitiveness.The ability of enterprises to rely on knowledge to win competition and win economic profits in a market environment can be called “enterprise knowledge competitiveness”.Enterprises form a three-level knowledge structure of “general knowledge-specific knowledge-proprietary knowledge” through repeated recycling reproduction process.Based on this,the theoretical model and evaluation system for enterprise knowledge competitiveness are established,and evaluates the knowledge competitiveness of 183 listed companies in the computer communication industry from 2012 to 2020 by adopting the “differential weighting method”.The study finds that: the overall level of enterprise knowledge competitiveness in the computer communications industry is low, and the phenomenon of “polarization” is more prominent; general knowledge, specific knowledge and proprietary knowledge have orders of magnitude difference in the enterprise competitiveness,and their contribution levels increase in order.