@article{Guo2026, 
author = {Tingting Guo and Leiju Qiu and Lianchong Zhang},
title = {Research on Data Management Capability Assessment},
year = {2026},
journal = {International Journal of Crowd Science},
volume = {10},
number = {3},
pages = {166-177},
keywords = {data management, capability maturity model, quantitative assessment, commercial remote sensing satellite},
url = {https://www.sciopen.com/article/10.26599/IJCS.2026.9100003},
doi = {10.26599/IJCS.2026.9100003},
abstract = {In the digital economy, data are crucial for enterprise value creation, yet many organizations still lack systematic assessment tools for data management capability. This paper presents a comprehensive review and develops a multidimensional framework encompassing five core dimensions: data strategy and governance, data resources and quality, technology and platform support, data application and value realization, and security and risk management. We further analyze three complementary assessment methodologies—maturity grading, quantitative assessment, and qualitative assessment. Recognizing that existing models primarily address data for internal operations, we introduce a product-oriented data management capability assessment model. To demonstrate its applicability, we conduct a case study on 11 commercial remote sensing satellite companies, constructing a tailored three-level indicator system and employing entropy-weighted TOPSIS for evaluation. Results reveal clear enterprise stratification, with data sustainable development capability and data market capability emerging as the primary differentiators. This paper contributes a theoretically grounded and operationally feasible assessment framework, offering both academic insights and practical guidance for enterprises seeking to enhance their data management capabilities and accelerate digital transformation.}
}