This paper selects the data of China's specialized,special and new“small giants”listed companies from 2011 to 2021,and starts from the key production factor and strategic asset of data assets,empirically examine...This paper selects the data of China's specialized,special and new“small giants”listed companies from 2011 to 2021,and starts from the key production factor and strategic asset of data assets,empirically examines the impact of data assetization on the supply chain resilience of SRDI SMEs,and examines the impact of data assetization on the supply chain resilience of SRDI SMEs using the role of the mechanism model.Through the mechanism model,the mediating effects of financing constraints and technological innovation are examined,and a path of action is drawn,which provides theoretical evidence and policy recommendations for promoting the digital transformation of SRDI SMEs and improving supply chain resilience.展开更多
As data is incorporated into production factors,the Accounting discipline should intensively study the new data asset.Starting from the analysis of the value attribute,right attribute,and relationship attribute of the...As data is incorporated into production factors,the Accounting discipline should intensively study the new data asset.Starting from the analysis of the value attribute,right attribute,and relationship attribute of the data,it is found that under certain conditions,the data has complete Accounting attributes and can be included in the assets.The Accounting discipline shall establish the research direction of Data Asset Accounting and focus on the research,including the recognition and measurement of data assets,the value evaluation of data assets,information disclosure,and Data Asset Accounting standards.Data assets are facing the major challenge of integrating into the Accounting discipline.We can carry out the Accounting professional reform and textbook construction facing the practice of data assets management from the aspects of theoretical construction,talent training,and industry research cooperation.展开更多
In order to realize the effective management of massive data resources brought by the comprehensive informatization of power system, it can better provide scientific basis for production decisions and better solve the...In order to realize the effective management of massive data resources brought by the comprehensive informatization of power system, it can better provide scientific basis for production decisions and better solve the data asset management problems of enterprises. First of all, this paper analyzes the present situation and demand of data resources, puts forward a data asset management system suitable for the power industry, discusses it deeply, and designs its function, data structure and technical structure. Provide efficient, safe, shared and comprehensive data services and data centers for electric power enterprises. On this basis, the data asset management system constructed can not only effectively guarantee the use of data resources, but also accelerate the digital transformation, cultivate digital economy and build digital ecology.展开更多
This paper explores the audit risks associated with the recognition of data assets on financial statements,focusing on the complexities arising from their replicability,unique valuation patterns,and contextual depende...This paper explores the audit risks associated with the recognition of data assets on financial statements,focusing on the complexities arising from their replicability,unique valuation patterns,and contextual dependencies.It identifies major misstatement risks at both the financial statement and assertion levels,including the potential for management to exaggerate data asset values,uncertainties in valuation methods,and deficiencies in data governance and internal controls.Additionally,auditors’lack of professional knowledge and inappropriate audit methods can lead to inspection risks.The paper emphasizes the urgent need for enhanced accounting standards for data assets,effective guidelines for their recognition and measurement,and robust internal controls.Furthermore,it advocates for the exploration of effective valuation methods and the incorporation of advanced technologies,such as big data and AI,into auditing practices.By improving auditor training and methodologies,organizations can better manage the inherent risks associated with data asset auditing.展开更多
With the advancement of technologies such as the Internet,cloud computing,and artificial intelligence,data has evolved into data assets,which hold significant economic value.Recently,China has introduced a series of a...With the advancement of technologies such as the Internet,cloud computing,and artificial intelligence,data has evolved into data assets,which hold significant economic value.Recently,China has introduced a series of accounting standards for valuing data assets on balance sheets.These standards define the conceptual scope and categories of data assets,establishing an institutional foundation for their recognition as capital contributions.As data assets are controllable,integral,and transferable,they qualify as non-monetary capital contributions under article 48 of the newly-revised Company Law of China.Within this context,this article aims to refine the analytical framework for data assets as capital contributions under the newly-revised Company Law,balancing the protection of individual privacy rights with the realization of data's economicvalue.展开更多
This paper explores the challenges and opportunities related to the activation of data assets in the maritime industry.This study sheds light on the evolving landscape of data asset monetization in the maritime sector...This paper explores the challenges and opportunities related to the activation of data assets in the maritime industry.This study sheds light on the evolving landscape of data asset monetization in the maritime sector.The successful activation of these data assets has the potential to generate substantial economic benefits.By addressing ownership,pricing,and security concerns,maritime enterprises can unlock the true potential of their data assets and contribute to the growth and development of the industry.Maritime enterprises possess extensive and long-standing data assets,which have the potential for substantial value extraction.The first part highlights the global trend of data asset monetization and provides an overview of data accumulation by leading maritime companies.It also underscores the unique characteristics of maritime data,including relatively straightforward ownership and ease of utilization.The second part delves into the practical experiences and pros and cons of data asset monetization in various regions.The third part examines the main risks associated with data asset monetization in maritime enterprises.These risks include issues related to ownership and profit distribution after data rights are established,the possibility of data idling leading to a bubble effect,and escalating concerns about data security.In the fourth part,the paper offers specific regulatory pathways and recommendations to address these challenges.This includes resolving ownership attribution issues,implementing market-oriented pricing strategies with legal safeguards,and embracing technological measures for robust data security,such as distinguishing between information and raw data and ensuring the anonymization of original data.展开更多
In the digital economy,data assets have come to be regarded as the new oil,underscoring their critical role in modern business models and decision-making processes.In response,the Chinese government has prioritized th...In the digital economy,data assets have come to be regarded as the new oil,underscoring their critical role in modern business models and decision-making processes.In response,the Chinese government has prioritized the formalization and management of data assets,introducing policies aimed at enhancing their value.Given the unique nature of data assets,characterized by the potential for both depreciation and appreciation,precise methods for assessing value changes and realizing the appreciation of data assets are urgently needed.Effective data governance techniques,including data cleaning,acquisition,and integration,are essential for maximizing the economic potential of data assets.Against this backdrop,this survey explores two key issues from a data governance perspective:the enhancement of data asset value and the quantification of its changes.It is structured around two primary dimensions:first,by examining data assets'inherent properties and quality indicators,and second,by utilizing an“on-demand evaluation”approach that assesses value of data assets in response to the performance of downstream machine learning models.By advancing understanding of these issues,this study seeks to optimize strategies for maximizing the economic impact of data assets through refined data governance practices.展开更多
基金National Undergraduate Training Program for Innovation and Entrepreneurship(D202410120257422558)。
文摘This paper selects the data of China's specialized,special and new“small giants”listed companies from 2011 to 2021,and starts from the key production factor and strategic asset of data assets,empirically examines the impact of data assetization on the supply chain resilience of SRDI SMEs,and examines the impact of data assetization on the supply chain resilience of SRDI SMEs using the role of the mechanism model.Through the mechanism model,the mediating effects of financing constraints and technological innovation are examined,and a path of action is drawn,which provides theoretical evidence and policy recommendations for promoting the digital transformation of SRDI SMEs and improving supply chain resilience.
文摘As data is incorporated into production factors,the Accounting discipline should intensively study the new data asset.Starting from the analysis of the value attribute,right attribute,and relationship attribute of the data,it is found that under certain conditions,the data has complete Accounting attributes and can be included in the assets.The Accounting discipline shall establish the research direction of Data Asset Accounting and focus on the research,including the recognition and measurement of data assets,the value evaluation of data assets,information disclosure,and Data Asset Accounting standards.Data assets are facing the major challenge of integrating into the Accounting discipline.We can carry out the Accounting professional reform and textbook construction facing the practice of data assets management from the aspects of theoretical construction,talent training,and industry research cooperation.
文摘In order to realize the effective management of massive data resources brought by the comprehensive informatization of power system, it can better provide scientific basis for production decisions and better solve the data asset management problems of enterprises. First of all, this paper analyzes the present situation and demand of data resources, puts forward a data asset management system suitable for the power industry, discusses it deeply, and designs its function, data structure and technical structure. Provide efficient, safe, shared and comprehensive data services and data centers for electric power enterprises. On this basis, the data asset management system constructed can not only effectively guarantee the use of data resources, but also accelerate the digital transformation, cultivate digital economy and build digital ecology.
文摘This paper explores the audit risks associated with the recognition of data assets on financial statements,focusing on the complexities arising from their replicability,unique valuation patterns,and contextual dependencies.It identifies major misstatement risks at both the financial statement and assertion levels,including the potential for management to exaggerate data asset values,uncertainties in valuation methods,and deficiencies in data governance and internal controls.Additionally,auditors’lack of professional knowledge and inappropriate audit methods can lead to inspection risks.The paper emphasizes the urgent need for enhanced accounting standards for data assets,effective guidelines for their recognition and measurement,and robust internal controls.Furthermore,it advocates for the exploration of effective valuation methods and the incorporation of advanced technologies,such as big data and AI,into auditing practices.By improving auditor training and methodologies,organizations can better manage the inherent risks associated with data asset auditing.
基金supported by the National Social Science Foundation ofChina(GrantNo.21BFX079).
文摘With the advancement of technologies such as the Internet,cloud computing,and artificial intelligence,data has evolved into data assets,which hold significant economic value.Recently,China has introduced a series of accounting standards for valuing data assets on balance sheets.These standards define the conceptual scope and categories of data assets,establishing an institutional foundation for their recognition as capital contributions.As data assets are controllable,integral,and transferable,they qualify as non-monetary capital contributions under article 48 of the newly-revised Company Law of China.Within this context,this article aims to refine the analytical framework for data assets as capital contributions under the newly-revised Company Law,balancing the protection of individual privacy rights with the realization of data's economicvalue.
基金National Social Science Fund of China,21BFX077,Xiaolan Yu。
文摘This paper explores the challenges and opportunities related to the activation of data assets in the maritime industry.This study sheds light on the evolving landscape of data asset monetization in the maritime sector.The successful activation of these data assets has the potential to generate substantial economic benefits.By addressing ownership,pricing,and security concerns,maritime enterprises can unlock the true potential of their data assets and contribute to the growth and development of the industry.Maritime enterprises possess extensive and long-standing data assets,which have the potential for substantial value extraction.The first part highlights the global trend of data asset monetization and provides an overview of data accumulation by leading maritime companies.It also underscores the unique characteristics of maritime data,including relatively straightforward ownership and ease of utilization.The second part delves into the practical experiences and pros and cons of data asset monetization in various regions.The third part examines the main risks associated with data asset monetization in maritime enterprises.These risks include issues related to ownership and profit distribution after data rights are established,the possibility of data idling leading to a bubble effect,and escalating concerns about data security.In the fourth part,the paper offers specific regulatory pathways and recommendations to address these challenges.This includes resolving ownership attribution issues,implementing market-oriented pricing strategies with legal safeguards,and embracing technological measures for robust data security,such as distinguishing between information and raw data and ensuring the anonymization of original data.
基金supported by the National Natural Science Foundation of China(Nos.62202126 and 62232005)the Natural Science Foundation Project of Heilongjiang Province of China(No.YQ2024F005).
文摘In the digital economy,data assets have come to be regarded as the new oil,underscoring their critical role in modern business models and decision-making processes.In response,the Chinese government has prioritized the formalization and management of data assets,introducing policies aimed at enhancing their value.Given the unique nature of data assets,characterized by the potential for both depreciation and appreciation,precise methods for assessing value changes and realizing the appreciation of data assets are urgently needed.Effective data governance techniques,including data cleaning,acquisition,and integration,are essential for maximizing the economic potential of data assets.Against this backdrop,this survey explores two key issues from a data governance perspective:the enhancement of data asset value and the quantification of its changes.It is structured around two primary dimensions:first,by examining data assets'inherent properties and quality indicators,and second,by utilizing an“on-demand evaluation”approach that assesses value of data assets in response to the performance of downstream machine learning models.By advancing understanding of these issues,this study seeks to optimize strategies for maximizing the economic impact of data assets through refined data governance practices.
