MEASURING LOCAL CONTEXT: USING MACHINE LEARNING AND K-MEANS CLUSTERING OF CONSUMER SURVEY DATA TO APPROXIMATE LOCAL ATTITUDES

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Research Overview

This study investigates the local context influencing alternative energy projects at Higher Education Institutions (HEIs). It examines how state policies, local attitudes, and financial feasibility shape sustainability commitments.

Data Sources

Key Research Questions

K-Means Clustering Methodology

Findings & Implications

The results highlight geographical variations in sustainability attitudes, suggesting that universities are more likely to invest in sustainable energy when state policies, financial incentives, and local public support align.