Three-dimensional dynamic coupling model of enterprise business intelligence mining : construction, verification and competition barrier construction mechanism

Abstract: Aiming at the dual challenges of lagging business opportunity identification and failure of systemic risk early warning in the superposition environment of information overload and policy uncertainty, this study integrates dynamic capability theory, policy tool classification framework and cognitive psychology, and pioneers the three-dimensional dynamic coupling model of ’ policy anchoring-depth insight-action rule ’ : 1.Policy anchoring layer quantifies capital flow and compliance cost ( function C _ risk = α · Fine _ max + β · CLV _ loss + γ · Repair _ cost, R² = 0.82 ) ; the deep insight layer integrates ELM and SNA to develop the ’ third-order penetration method ’ ( misjudgment rate ≤ 12 % ) ; 3.Action transformation layer design ’ policy grafting-demand translation-intelligence puzzle ’ three rules. Through cross-validation of multiple cases in medical, financial and manufacturing industries ( N = 3, cycle 3 months ), the model significantly improved the business opportunity response efficiency by 40.2 % ( SD = 3.5 %, p < 0.01 ) and the accuracy of risk warning to 85.7 %.The core theoretical contribution of this model lies in the vertical coupling mechanism of macro policy deconstruction, meso demand insight and micro decision chain mapping. Its practical value lies in providing an operable framework and methodological tool for enterprises to shift from passively responding to market changes to actively foreseeing strategic opportunities. In particular, the ’ third-order penetration method ’ and ’ business opportunity credibility score card ’, which were first created, effectively reduced the risk of intelligence misjudgment. Based on the data of pilot enterprises, the study further puts forward the optimal ratio of resources ( policy guidance 32.1 % ± 2.4 %, deep demand motivation analysis 41.3 % ± 3.1 %, chain burial point 18.5 % ± 1.7 %, intelligence weaving network 8.1 % ± 0.9 % ) and the establishment of cross-functional ’Intelligence War Room ’organizational guarantee mechanism to enable enterprises to build dynamic competition barriers. Future research can explore the integration of cutting-edge Generative AI technology to achieve automatic policy deconstruction and intelligence weaving, and expand the application verification of the model in cross-cultural situations.