数字生态下数据向善的源起、要素、驱动与困境  

How Data for Good is Possible in the Digital Ecology:Origins,Elements,Drivers and Dilemmas

作　　者：储节旺[1] 李佳轩 Chu Jiewang;Li Jiaxuan(School of Management,Anhui University,Hefei 230601)

机构地区：[1]安徽大学管理学院,合肥230601

出　　处：《图书情报工作》2023年第10期3-14,共12页Library and Information Service

基　　金：安徽省哲学社会科学规划重大项目“安徽打造具有重要影响力的科技创新策源地研究”(项目编号:AHSKZD2021D02)研究成果之一。

摘　　要：[目的/意义]探析数据向善的本质内涵与边界,对其实现的驱动因素进行挖掘,以帮助我国数字生态实现常态化数据向善发展。[方法/过程]通过理论溯源探求数据向善的内在要素与范畴,界定其本质概念,之后使用ISM模型分析数据主体采取数据向善行为的驱动因素,最后剖析数据向善实现的困境与未来。[结果/结论]研究发现驱动数据主体采取数据向善的动因可以分为核心动因、间接动因与表层动因,选择合适的驱动因素是实现数据向善的关键。在未来如果想要在社会层面上普及数据向善,需要从行规、法律、市场环境等多个维度出发。[Purpose/Significance]To explore the essential connotation and boundary of data goodness and to explore the driving factors of its realization,to help China's digital ecology realize the normalization of data goodness development.[Method/Process]This paper explored the intrinsic elements and scope of data goodness through theoretical tracing and defined its essential concept,then analyzed the driving factors of data subjects'adoption of data goodness using the ISM model,and finally analyzed the dilemma and future of data goodness.[Result/Conclusion]The paper found that the motivations that drive data subjects to adopt data for good can be divided into core,indirect and surface motivations,and choosing the right driver is the key to achieving data for good.In the future,if we want to popularise data for good at a societal level,we need to start from a number of dimensions such as regulations,laws and market environment.

关 键 词：数据向善 数字生态 驱动因素 数据要素 

分 类 号：G931.2[文化科学]