Data factors are becoming the core driving force in the intelligent transformation of libraries.Based on a systematic review of the progress in data governance practices in libraries both domestically and internationa...Data factors are becoming the core driving force in the intelligent transformation of libraries.Based on a systematic review of the progress in data governance practices in libraries both domestically and internationally,this study delves into the mechanism by which data governance promotes data factorization and proposes implementation paths for data governance oriented toward data factorization.The aim is to facilitate the intelligent transformation and high-quality development of libraries.展开更多
Service-oriented manufacturing is an important trend in the development of the manufacturing industry.Accelerating the development of service-oriented manufacturing is of great significance for building a modern indus...Service-oriented manufacturing is an important trend in the development of the manufacturing industry.Accelerating the development of service-oriented manufacturing is of great significance for building a modern industrial system,making China a strong manufacturing country,and improving its global industrial competitiveness.With the development of digital technology,service-oriented manufacturing has become a data-intensive production and service process.Data are widely applied in typical scenarios such as research and development,production,delivery to users,and operation and maintenance.Through data insights,software definition,command and control,real-time data streaming and aggregation,it helps to optimize business decisions,achieve economies of scale,enhance flexibility,improve service responsiveness,and unleash value-creation capabilities.This can comprehensively improve the operational performance of service-oriented manufacturing.To further accelerate the development of service-oriented manufacturing,it is necessary to focus on shaping the advantages of manufacturing data factors,increasing the supply of manufacturing data,enhancing the innovation of data technologies and data security,accelerating the research and application of data technology standards,and promoting cross-border data flows.展开更多
This study draws on public data openness policies of local governments and micro-level data from A-share listed enterprises across 30 provinces in China from 2011 to 2022.Thus,the study examines the mechanisms through...This study draws on public data openness policies of local governments and micro-level data from A-share listed enterprises across 30 provinces in China from 2011 to 2022.Thus,the study examines the mechanisms through which public data openness affects the innovation quality of“specialized,refined,distinctive,and innovative”(SRDI)enterprises.Furthermore,it analyzes the mediating effects of artificial intelligence(AI)development and enterprise research and development(R&D)costs,as well as the moderating effects of government subsidies,information infrastructure,and industrial agglomeration.The results indicate that public data openness significantly enhances the innovation quality of SRDI enterprises.However,this impact varies across regions,industries,and types of enterprises:inland cities,areas with lower education levels,and regions with underdeveloped digital infrastructure exhibit stronger effects.Non-state-owned enterprises are more responsive to public data openness compared to state-owned ones,and non-manufacturing enterprises benefit more than manufacturing ones.Mediation analysis indicates that public data openness enhances innovation capability,primarily by increasing local AI development and reducing R&D costs.Moreover,government subsidies and information infrastructure strengthen this positive effect,while industrial agglomeration may suppress it.展开更多
As an advanced form of productivity driven by technological innovation,new quality productive forces provide fundamental impetus for rural industries to break through traditional development bottlenecks and achieve hi...As an advanced form of productivity driven by technological innovation,new quality productive forces provide fundamental impetus for rural industries to break through traditional development bottlenecks and achieve high-quality growth.Based on a three-dimensional analytical framework of“technology-factors-value,”this paper systematically elucidates the internal mechanisms by which new quality productive forces empower the high-quality development of rural industries.It delves into the practical challenges at the levels of technological adaptation,factor allocation,and value transformation,and proposes implementation paths including localized technological innovation,restructuring of the factor system,and improvement of institutional safeguards,aiming to provide references for the modernization of agriculture and rural areas.展开更多
Data factors have become one of the five essential production factors,but their role in economic growth has always been ambiguous.Starting from AI technologies,this paper establishes an endogenous growth model of data...Data factors have become one of the five essential production factors,but their role in economic growth has always been ambiguous.Starting from AI technologies,this paper establishes an endogenous growth model of data factors affecting economic growth,constructs the generation path and value path of data factors,and estimates the value of new data factors at the provincial level in China from 1999 to 2018 accordingly.Based on theoretical analyses and empirical tests,it clarifes that data factors have a“two-dimensional driving effect”on China's economic growth,that is,data factors can drive growth both directly through its own economic growth effect and indirectly by promoting technological progress.Furthermore,this paper makes three extended discussions,aiming to make a trial study on the impacts of local government big data transaction platforms on data factors and their growth effects,discuss whether it is possible to reduce the uncertainties of local economic policy based on the nature of data factors,and make a preliminary survey of the output elasticity of data factors between 1999 and 2018.展开更多
Identification of security risk factors for small reservoirs is the basis for implementation of early warning systems.The manner of identification of the factors for small reservoirs is of practical significance when ...Identification of security risk factors for small reservoirs is the basis for implementation of early warning systems.The manner of identification of the factors for small reservoirs is of practical significance when data are incomplete.The existing grey relational models have some disadvantages in measuring the correlation between categorical data sequences.To this end,this paper introduces a new grey relational model to analyze heterogeneous data.In this study,a set of security risk factors for small reservoirs was first constructed based on theoretical analysis,and heterogeneous data of these factors were recorded as sequences.The sequences were regarded as random variables,and the information entropy and conditional entropy between sequences were measured to analyze the relational degree between risk factors.Then,a new grey relational analysis model for heterogeneous data was constructed,and a comprehensive security risk factor identification method was developed.A case study of small reservoirs in Guangxi Zhuang Autonomous Region in China shows that the model constructed in this study is applicable to security risk factor identification for small reservoirs with heterogeneous and sparse data.展开更多
Activity data and emission factors are critical for estimating greenhouse gas emissions and devising effective climate change mitigation strategies. This study developed the activity data and emission factor in the Fo...Activity data and emission factors are critical for estimating greenhouse gas emissions and devising effective climate change mitigation strategies. This study developed the activity data and emission factor in the Forestry and Other Land Use Change (FOLU) subsector in Malawi. The results indicate that “forestland to cropland,” and “wetland to cropland,” were the major land use changes from the year 2000 to the year 2022. The forestland steadily declined at a rate of 13,591 ha (0.5%) per annum. Similarly, grassland declined at the rate of 1651 ha (0.5%) per annum. On the other hand, cropland, wetland, and settlements steadily increased at the rate of 8228 ha (0.14%);5257 ha (0.17%);and 1941 ha (8.1%) per annum, respectively. Furthermore, the results indicate that the “grassland to forestland” changes were higher than the “forestland to grassland” changes, suggesting that forest regrowth was occurring. On the emission factor, the results interestingly indicate that there was a significant increase in carbon sequestration in the FOLU subsector from the year 2011 to 2022. Carbon sequestration increased annually by 13.66 ± 0.17 tCO2 e/ha/yr (4.6%), with an uncertainty of 2.44%. Therefore, it can be concluded that there is potential for a Carbon market in Malawi.展开更多
摘要Data factors are becoming the core driving force in the intelligent transformation of libraries.Based on a systematic review of the progress in data governance practices in libraries both domestically and internationally,this study delves into the mechanism by which data governance promotes data factorization and proposes implementation paths for data governance oriented toward data factorization.The aim is to facilitate the intelligent transformation and high-quality development of libraries.
基金supported by the key project of the National Social Science Fund of China,“Research on the Mechanisms for Enhancing the Modernization Level of Industrial and Supply Chains Driven by the Digital Economy”(No.22AZD124)the innovative engineering project of the Chinese Academy of Social Sciences,“Research on the Global Competitiveness of Advanced Manufacturing and the Construction of a Manufacturing Powerhouse in China”(No.2022GJS02)the Dengfeng strategic advantage discipline project in Industrial Economics at the Chinese Academy of Social Sciences.
摘要Service-oriented manufacturing is an important trend in the development of the manufacturing industry.Accelerating the development of service-oriented manufacturing is of great significance for building a modern industrial system,making China a strong manufacturing country,and improving its global industrial competitiveness.With the development of digital technology,service-oriented manufacturing has become a data-intensive production and service process.Data are widely applied in typical scenarios such as research and development,production,delivery to users,and operation and maintenance.Through data insights,software definition,command and control,real-time data streaming and aggregation,it helps to optimize business decisions,achieve economies of scale,enhance flexibility,improve service responsiveness,and unleash value-creation capabilities.This can comprehensively improve the operational performance of service-oriented manufacturing.To further accelerate the development of service-oriented manufacturing,it is necessary to focus on shaping the advantages of manufacturing data factors,increasing the supply of manufacturing data,enhancing the innovation of data technologies and data security,accelerating the research and application of data technology standards,and promoting cross-border data flows.
摘要This study draws on public data openness policies of local governments and micro-level data from A-share listed enterprises across 30 provinces in China from 2011 to 2022.Thus,the study examines the mechanisms through which public data openness affects the innovation quality of“specialized,refined,distinctive,and innovative”(SRDI)enterprises.Furthermore,it analyzes the mediating effects of artificial intelligence(AI)development and enterprise research and development(R&D)costs,as well as the moderating effects of government subsidies,information infrastructure,and industrial agglomeration.The results indicate that public data openness significantly enhances the innovation quality of SRDI enterprises.However,this impact varies across regions,industries,and types of enterprises:inland cities,areas with lower education levels,and regions with underdeveloped digital infrastructure exhibit stronger effects.Non-state-owned enterprises are more responsive to public data openness compared to state-owned ones,and non-manufacturing enterprises benefit more than manufacturing ones.Mediation analysis indicates that public data openness enhances innovation capability,primarily by increasing local AI development and reducing R&D costs.Moreover,government subsidies and information infrastructure strengthen this positive effect,while industrial agglomeration may suppress it.
摘要As an advanced form of productivity driven by technological innovation,new quality productive forces provide fundamental impetus for rural industries to break through traditional development bottlenecks and achieve high-quality growth.Based on a three-dimensional analytical framework of“technology-factors-value,”this paper systematically elucidates the internal mechanisms by which new quality productive forces empower the high-quality development of rural industries.It delves into the practical challenges at the levels of technological adaptation,factor allocation,and value transformation,and proposes implementation paths including localized technological innovation,restructuring of the factor system,and improvement of institutional safeguards,aiming to provide references for the modernization of agriculture and rural areas.
基金“Research on System Regulation on High-quality Supply of Data Factors under the Framework of‘Market+Government+Community’Collaborative Governance”,a National Social Science Fund Project for 2022.(22BJL033).
摘要Data factors have become one of the five essential production factors,but their role in economic growth has always been ambiguous.Starting from AI technologies,this paper establishes an endogenous growth model of data factors affecting economic growth,constructs the generation path and value path of data factors,and estimates the value of new data factors at the provincial level in China from 1999 to 2018 accordingly.Based on theoretical analyses and empirical tests,it clarifes that data factors have a“two-dimensional driving effect”on China's economic growth,that is,data factors can drive growth both directly through its own economic growth effect and indirectly by promoting technological progress.Furthermore,this paper makes three extended discussions,aiming to make a trial study on the impacts of local government big data transaction platforms on data factors and their growth effects,discuss whether it is possible to reduce the uncertainties of local economic policy based on the nature of data factors,and make a preliminary survey of the output elasticity of data factors between 1999 and 2018.
基金supported by the National Nature Science Foundation of China(Grant No.71401052)the National Social Science Foundation of China(Grant No.17BGL156)the Key Project of the National Social Science Foundation of China(Grant No.14AZD024)
摘要Identification of security risk factors for small reservoirs is the basis for implementation of early warning systems.The manner of identification of the factors for small reservoirs is of practical significance when data are incomplete.The existing grey relational models have some disadvantages in measuring the correlation between categorical data sequences.To this end,this paper introduces a new grey relational model to analyze heterogeneous data.In this study,a set of security risk factors for small reservoirs was first constructed based on theoretical analysis,and heterogeneous data of these factors were recorded as sequences.The sequences were regarded as random variables,and the information entropy and conditional entropy between sequences were measured to analyze the relational degree between risk factors.Then,a new grey relational analysis model for heterogeneous data was constructed,and a comprehensive security risk factor identification method was developed.A case study of small reservoirs in Guangxi Zhuang Autonomous Region in China shows that the model constructed in this study is applicable to security risk factor identification for small reservoirs with heterogeneous and sparse data.
摘要Activity data and emission factors are critical for estimating greenhouse gas emissions and devising effective climate change mitigation strategies. This study developed the activity data and emission factor in the Forestry and Other Land Use Change (FOLU) subsector in Malawi. The results indicate that “forestland to cropland,” and “wetland to cropland,” were the major land use changes from the year 2000 to the year 2022. The forestland steadily declined at a rate of 13,591 ha (0.5%) per annum. Similarly, grassland declined at the rate of 1651 ha (0.5%) per annum. On the other hand, cropland, wetland, and settlements steadily increased at the rate of 8228 ha (0.14%);5257 ha (0.17%);and 1941 ha (8.1%) per annum, respectively. Furthermore, the results indicate that the “grassland to forestland” changes were higher than the “forestland to grassland” changes, suggesting that forest regrowth was occurring. On the emission factor, the results interestingly indicate that there was a significant increase in carbon sequestration in the FOLU subsector from the year 2011 to 2022. Carbon sequestration increased annually by 13.66 ± 0.17 tCO2 e/ha/yr (4.6%), with an uncertainty of 2.44%. Therefore, it can be concluded that there is potential for a Carbon market in Malawi.