Business Intelligence and Sustainability Features in Education: A Systematic Literature Review

Educational sustainability has emerged as a critical framework for achieving the Sustainable Development Goals, yet the systematic measurement and management of sustainability features in schools remain underexplored, particularly regarding the application of advanced data-driven technologies. This study addresses the research question: How is Business Intelligence being utilized in measuring and managing sustainability features within educational contexts? A systematic literature review was conducted across Web of Science and Scopus databases, employing rigorous inclusion and exclusion criteria. From an initial identification of 4317 records, 36 articles published between 2021 and 2025 were selected for comprehensive analysis. Bibliometric analysis revealed an annual growth rate of 60.69%, indicating rapid emergence of this research domain. Qualitative content analysis identified four principal dimensions structuring the intersection between sustainability and data-driven technologies in education: environmental (energy efficiency, waste management), social (academic performance, educational equity), economic (cost–benefit analysis, return on investment), and governance and management based on Business Intelligence and information technologies. The findings confirm the convergence of Business Intelligence and educational sustainability as a promising field, while revealing a critical absence of empirical investigations validating these concepts within Brazilian contexts, particularly in technical secondary schools. This gap establishes both the foundation and scientific justification for advancing research in this domain.

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Publication Details

Journal
Sustainability
Published
2026-02-13
DOI
https://doi.org/10.3390/su18041954
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.00

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Business Intelligence and Sustainability Features in Education: A Systematic Literature Review

F. A. C. de Melo, Charlis Alberto Cabral de Moraes Júnior, Pablo Aurélio Lacerda de Almeida Pinto
Sustainability
Big Data and Business Intelligence
article

Business Intelligence and Sustainability Features in Education: A Systematic Literature Review

F. A. C. de Melo, Charlis Alberto Cabral de Moraes Júnior, Pablo Aurélio Lacerda de Almeida Pinto
article en

Abstract

Educational sustainability has emerged as a critical framework for achieving the Sustainable Development Goals, yet the systematic measurement and management of sustainability features in schools remain underexplored, particularly regarding the application of advanced data-driven technologies. This study addresses the research question: How is Business Intelligence being utilized in measuring and managing sustainability features within educational contexts? A systematic literature review was conducted across Web of Science and Scopus databases, employing rigorous inclusion and exclusion criteria. From an initial identification of 4317 records, 36 articles published between 2021 and 2025 were selected for comprehensive analysis. Bibliometric analysis revealed an annual growth rate of 60.69%, indicating rapid emergence of this research domain. Qualitative content analysis identified four principal dimensions structuring the intersection between sustainability and data-driven technologies in education: environmental (energy efficiency, waste management), social (academic performance, educational equity), economic (cost–benefit analysis, return on investment), and governance and management based on Business Intelligence and information technologies. The findings confirm the convergence of Business Intelligence and educational sustainability as a promising field, while revealing a critical absence of empirical investigations validating these concepts within Brazilian contexts, particularly in technical secondary schools. This gap establishes both the foundation and scientific justification for advancing research in this domain.

SustainabilityVol. 18(4)
Universidade Federal de Pernambuco (BR), Universidade de Pernambuco (BR)
Universidade de Pernambuco
Openalex Percentile: Top 63%
Big Data and Business Intelligence
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