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.