Journal of Modern Business Administration

Objective New retail leverages the advantages of data to fully explore its rich commercial value and maximize business benefits through the utilization of data assets. The quality of data is crucial in extracting useful and valuable information. To promote the evaluation and standardized management of data quality systems, it is necessary to establish a corresponding evaluation index system for data quality in new retail. Method Based on the concepts of new retail and data quality, this paper conducts a review of domestic and foreign literature and references existing data quality evaluation systems. Ultimately, it identifies four dimensions of data quality evaluation, including intrinsic data quality, user applicability, data governance level, and data technology level, along with 18 secondary data quality evaluation indicators. The fuzzy interpretive structural model is used to determine the direct and indirect relationships between the evaluation indicator factors. These relationships are then used as inputs for the network structure of the analytic hierarchy process to construct the evaluation index system. Conclusion In the evaluation system for data quality in new retail, data accuracy is identified as the key factor determining data quality. Additionally, user applicability is an important dimension in overall data quality assessment. Therefore, in the mature stage of data business development, efforts should be focused on enhancing user applicability.

New retail data; Quality evaluation; Fuzzy interpretive structural model; Analytic hierarchy process