文章摘要
刘枬,周雨,郝雪镜.基于ISM-MICMAC的数据资产价值影响因素研究[J].情报工程,2024,10(3):063-076
基于ISM-MICMAC的数据资产价值影响因素研究
Research on Influencing Factors of Data Asset Value Based on ISMMICMAC
  
DOI:10.3772/j.issn.2095-915X.2024.03.005
中文关键词: 数据资产价值;影响因素;解释结构模型;MICMAC分析
英文关键词: Data Asset Value; Identification of Influencing Factors; ISM; MICMAC
基金项目:教育部人文社会科学基金项目“大数据资产的定价机理、方法和规范研究”(20XJAZH007)。
作者单位
刘枬 重庆交通大学经济与管理学院 重庆 400074 
周雨 重庆交通大学经济与管理学院 重庆 400074 
郝雪镜 重庆市信息通讯咨询设计有限公司 重庆 400041 
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中文摘要:
      [目的/意义]通过深入剖析数据资产价值的研究现状,指出目前对数据资产价值的定义和理解还比较模糊和笼统。[方法/过程]为了更好地理解和评估数据资产的价值,采用文献调研、专家调查和问卷调查等方法,提取出57个影响数据资产价值的因素,并通过因子分析得出13个主要因素,通过建立解释结构模型,分析因素之间的层级关系和作用机理。同时,还使用MICMAC方法对因素进行驱动力-依赖性分析,实现因素的进一步分层和分类。最后,针对研究得出的主要影响因素,从表层、具体层和关键层三个层面提出了与国家、企业、用户等主体相关的具体对策建议,以促进数据资产价值的实现和提高。[局限]问卷调查以及专家评估打分存在一定的主观性。同时,数据资产价值影响因素指标也具有一定的可拓展性。[结果/结论]研究结果表明:信息提取要素投入价值因素、数据采集要素投入价值因素以及数据组织管理价值因素为关键层因素,属于独立因素群,具有较高的驱动力和低依赖性,对其他因素发挥支撑和推动作用。
英文摘要:
      [Objective/Significance] This paper introduces the research status of data asset value and points out that the definition and understanding of data asset value are still vague and general. [Methods/Processes] In order to better understand and evaluate the value of data assets, 57 factors affecting the value of data assets were extracted by literature research, expert survey and questionnaire survey, and 13 major factors were obtained through factor analysis. The hierarchical relationship and mechanism of action among factors were analyzed by establishing an explanatory structure model. At the same time, MICMAC method is also used for driving force-dependency analysis of factors to achieve further stratification and classification of factors. Finally, based on the main influencing factors obtained from the research, this paper puts forward specific countermeasures and suggestions related to the country, enterprises, users and other subjects from the surface level, concrete level and key level, so as to promote the realization and improvement of the value of data assets. [Limitations] Questionnaire survey and expert evaluation have some subjectivity. At the same time, the index of influencing factors of data asset value also has certain extensibility. [Results/Conclusions] The results show that the input value factor of information extraction, the input value factor of data acquisition and the value factor of data organization and management are the key factors, belonging to the independent factor group, with high driving force and low dependence, and playing a supporting and promoting role for other factors.
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