<![CDATA[This paper investigates how integrating business analytics and geospatial data can enhance the assessment of climate adaptation and energy transition policies in the United States. The study aims to develop and test an analytical framework that quantitatively evaluates policy effectiveness, resilience, and equity across spatial and temporal scales. Using predictive modeling, spatial clustering, and multi-criteria optimization, the framework combines policy, climate, and energy datasets to identify trends, vulnerabilities, and opportunities for sustainable transformation. Three U.S. case studies urban heat adaptation in Phoenix, renewable energy deployment in Texas, and disaster resilience planning in coastal Louisiana demonstrate the framework’s application. The analysis reveals that regions leveraging data-driven strategies achieve up to 18% higher efficiency in renewable integration and greater adaptive capacity in extreme heat management. These findings highlight the framework’s ability to translate complex geospatial and analytical insights into actionable policy guidance. By uniquely integrating business analytics with geospatial intelligence, this research offers a novel, evidence-based approach to evaluating climate and energy transition policies, contributing to both methodological innovation and practical policymaking for a low-carbon, climate-resilient future.]]>
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