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| Application of Information Analysis Methods in Evidence-Based Decision Making under the Digital Intelligence Integration Environment: Elements, Frameworks, and Optimization Strategies |
| Xia Yikun, Ye Junling |
| Research Institute for Data Management & Innovation, Nanjing University, Suzhou 215163 |
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Abstract Information analysis methods have accelerated the transformation from traditional to intelligent paradigms in the context of digital intelligence integration. Evidence-based decision-making, a core component of digital-intelligence-driven systems, serves as a key domain in the application of information analysis methods. Grounded in the context of evidence-based decision making, in combination with systems theory thinking, this study adopted a systematic literature review approach to explore the elements, framework, and optimization of information analysis methods. It identified the characteristics and interrelationships among three core dimensions, namely, evidence sources, analysis methods, and decision-making scenarios, and constructed a five-dimensional application framework incorporating elements, patterns, functions, actors, and contexts. The results suggested that the effective application of information analysis methods was achieved through the coupling of three-dimensional elements in the “data-evidence-decision” chain, shaped by multi-party collaboration and complex contextual interweaving. Accordingly, this paper proposes strategies, including enhancing data governance capabilities, rationally applying artificial intelligence technology for empowerment, and facilitating the integrated use and cross-validation of diverse methods. This study aimed to reveal the structural features and evolutionary logic of the application of information analysis methods in evidence-based decision-making, enhance the understanding of their operational mechanisms and functions, and offer strategic recommendations for their effective use in the context of digital intelligence integration.
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Received: 15 May 2025
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