Paper Type
Complete
Abstract
To combat environmental impact and commit to sustainably focused institutions, this paper aims to analyze data across the higher education sector. The fundamental research goal asks: How can and should Higher Education institutions advance their sustainability efforts, and what areas are most influential? To evaluate the most impactful initiatives, the authors encode and analyze data from 342 higher education institutions within the Sustainability Tracking Assessment and Rating System (STARS). Using visualizations and predictive modeling, the paper assesses international and domestic sustainability performance across five categories: Academics, Engagement, Planning & Administration, Operations, and Innovation & Leadership. The author's investigation highlights the lack of pursuit across the domestic region in Academics while revealing a strong global correlation between Engagement and Academics. This research provides the first aggregated analysis of sustainability efforts in higher education between both domestic and international regions, producing a fresh perspective into the domestic pitfalls of successfully advancing sustainability.
Paper Number
2062
Recommended Citation
Guhl Erdie, Isabella; Tripathi, Abhishek; Contant, Shamiere; and Bodine, Daniel, "Mapping the STARS: Using Machine Learning to Advance Higher Education Sustainability Efforts in the United States" (2025). AMCIS 2025 Proceedings. 4.
https://aisel.aisnet.org/amcis2025/data_science/sig_dsa/4
Mapping the STARS: Using Machine Learning to Advance Higher Education Sustainability Efforts in the United States
To combat environmental impact and commit to sustainably focused institutions, this paper aims to analyze data across the higher education sector. The fundamental research goal asks: How can and should Higher Education institutions advance their sustainability efforts, and what areas are most influential? To evaluate the most impactful initiatives, the authors encode and analyze data from 342 higher education institutions within the Sustainability Tracking Assessment and Rating System (STARS). Using visualizations and predictive modeling, the paper assesses international and domestic sustainability performance across five categories: Academics, Engagement, Planning & Administration, Operations, and Innovation & Leadership. The author's investigation highlights the lack of pursuit across the domestic region in Academics while revealing a strong global correlation between Engagement and Academics. This research provides the first aggregated analysis of sustainability efforts in higher education between both domestic and international regions, producing a fresh perspective into the domestic pitfalls of successfully advancing sustainability.
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