摘要
数字经济时代,如何释放数据价值已经成为实业界和学术界关注的焦点和热点.数据价值化以数据资源化、数据资产化、数据商品化和数据资本化为核心阶段,从动态演化的新视角揭示了数据创造价值的过程.目前相关研究比较分散,缺乏系统梳理,尚未形成对数据价值化的完整认知.基于此,本文系统回顾和梳理数据价值化相关研究,首先系统梳理2011至2022年发表的250篇英文文献和117篇中文文献,科学呈现和对比中西方有关数据价值化的细分研究主题;其次整合已有研究明晰数据价值化的概念内涵和特征;接着基于价值链理论构建数据价值化的整合研究框架,明确数据资源化、数据资产化、数据商品化和数据资本化四个阶段的关键数据行为,以及四个阶段的前置因素和结果产出;最后提出未来值得研究的五大议题.本研究明确了数据价值化的知识脉络和研究边界,有助于推动数据价值化的进一步研究.
Abstract
Data has become a strategic resource and an important productive force in the era of the digital economy.How to release the value of data has become the focus and hotspot of attention in the industry and academia.Data valued process takes data resourcing,data assetizing,data commercializing,and data capitalizing as the core stage,revealing the process of data value creation from a new perspective of dynamic evolution.In general,the number of related studies covers a wide range of areas,but the research vein and focus are not particularly clear,and there is a lack of high-quality literature review in the data valued process research.Therefore,by systematically summarizing 250 English and 117 Chinese literatures on data valued process published in mainstream journals from 2011 to 2022,this paper aims to clarify the research themes,connotations,and characteristics of data valued process,discuss value realization process,and construct an integrated research framework for data valued process.The conclusions of this paper are as follows:First,the focus of data valued process research in China and the West is not exactly the same.English literatures have evolved from the management of data to the application of data in specific scenarios,Chinese literatures have evolved from data value mining to data market circulation,Second,this paper clarifies the connotation of data valued process and finds that the process relies on other traditional elements,is based on a broader ecology,generates economies of scale,has flexibility,and supports new business models.Third,the research framework for the integration of data valued process follows the logic of"antecedent factor-realization process-effect output".Key data behaviors at each stage enable data to flow through the data value chain and create data value,and this process is affected by antecedent factors such as technology,organization,and environment,which can generate data value,economic value,and social value.The future directions of this paper are that:To discuss key data behaviors such as data governance,data value assessment,and data trading;to search for suitable paths for data commercialization and data capitalization for Chinese firms;to deepen the research by combining digital contexts such as digital innovation and digital entrepreneurship;to conduct a scenario-based research on data valued process;to dig out the potential risks or negative impacts in data valued process.The contributions of this paper are that:First,it systematically reviews the existing research,and clarifies the themes of data valued process.Second,it analyzes the connotation of data valued process to identify the research scope and boundary of it.Third,it constructs an integrated research framework to promote the construction of the theoretical system of data valued process.Fourth,it proposes the research topics that need to be deeply explored in the future.
NETL
NSTL
维普
万方数据