在数字经济背景下,财务数据管理对企业管理效能和决策能力至关重要。然而,企业在数据标准、质量管理、安全保障等方面仍面临诸多挑战。本研究基于数据管理能力成熟度模型(DCMM),结合层次分析法(AHP)和模糊综合评价法(FCE),构建了财务数...在数字经济背景下,财务数据管理对企业管理效能和决策能力至关重要。然而,企业在数据标准、质量管理、安全保障等方面仍面临诸多挑战。本研究基于数据管理能力成熟度模型(DCMM),结合层次分析法(AHP)和模糊综合评价法(FCE),构建了财务数据管理成熟度评价体系。研究优化了DCMM模型的适配性,细化了能力域、能力项和子能力项,并确定了各指标在财务数据管理能力成熟度评估应用下的定义与权重。同时,研究建议通过问卷调查和数据分析,计算企业财务数据管理综合得分,以识别企业财务数据管理短板并提供优化建议。研究结果表明,该体系可有效评估企业财务数据治理水平,并为其优化数据管理策略提供科学支持。In the era of the digital economy, accounting data management plays a crucial role in enhancing corporate management efficiency and decision-making. However, enterprises still face significant challenges in data standards, quality management, and security assurance. This study develops an accounting data management maturity evaluation system based on the Data Management Capability Maturity Model (DCMM), integrating the Analytic Hierarchy Process (AHP) and Fuzzy Comprehensive Evaluation (FCE) methods. The research refines the DCMM framework by specifying capability domains, capability items, and sub-capability items, while defining and assigning weights to each indicator within the context of accounting data management maturity assessment. Additionally, the study proposes the use of questionnaire surveys and data analysis to calculate an overall accounting data management score, enabling enterprises to identify weaknesses and receive targeted optimization recommendations. The findings demonstrate that this system effectively evaluates corporate accounting data governance levels and provides scientific support for optimizing data management strategies.展开更多
文摘在数字经济背景下,财务数据管理对企业管理效能和决策能力至关重要。然而,企业在数据标准、质量管理、安全保障等方面仍面临诸多挑战。本研究基于数据管理能力成熟度模型(DCMM),结合层次分析法(AHP)和模糊综合评价法(FCE),构建了财务数据管理成熟度评价体系。研究优化了DCMM模型的适配性,细化了能力域、能力项和子能力项,并确定了各指标在财务数据管理能力成熟度评估应用下的定义与权重。同时,研究建议通过问卷调查和数据分析,计算企业财务数据管理综合得分,以识别企业财务数据管理短板并提供优化建议。研究结果表明,该体系可有效评估企业财务数据治理水平,并为其优化数据管理策略提供科学支持。In the era of the digital economy, accounting data management plays a crucial role in enhancing corporate management efficiency and decision-making. However, enterprises still face significant challenges in data standards, quality management, and security assurance. This study develops an accounting data management maturity evaluation system based on the Data Management Capability Maturity Model (DCMM), integrating the Analytic Hierarchy Process (AHP) and Fuzzy Comprehensive Evaluation (FCE) methods. The research refines the DCMM framework by specifying capability domains, capability items, and sub-capability items, while defining and assigning weights to each indicator within the context of accounting data management maturity assessment. Additionally, the study proposes the use of questionnaire surveys and data analysis to calculate an overall accounting data management score, enabling enterprises to identify weaknesses and receive targeted optimization recommendations. The findings demonstrate that this system effectively evaluates corporate accounting data governance levels and provides scientific support for optimizing data management strategies.
