Automating materiality assessment with a data-driven document-based approach
Materiality assessment is a critical process for companies to understand the interest perceived by its stakeholders towards topics related to environmental, social, and governance issues. Materiality assessment helps companies define their growth and communicative strategies; recently, it has become...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-06-01
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| Series: | International Journal of Information Management Data Insights |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2667096824000995 |
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| _version_ | 1846101653758935040 |
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| author | Matteo Francia Enrico Gallinucci Matteo Golfarelli |
| author_facet | Matteo Francia Enrico Gallinucci Matteo Golfarelli |
| author_sort | Matteo Francia |
| collection | DOAJ |
| description | Materiality assessment is a critical process for companies to understand the interest perceived by its stakeholders towards topics related to environmental, social, and governance issues. Materiality assessment helps companies define their growth and communicative strategies; recently, it has become crucial within sustainability reporting, i.e., the practice of annually declaring the activities conducted to pursue economic growth in a sustainable way for society. In this paper, we propose a data-driven and automated approach to carry out materiality assessment. Stakeholders’ perception of important topics is obtained by analyzing relevant textual documents (e.g., company reports, press releases, social media posts), identifying mentions of potentially interesting topics, and converting them to scores that produce materiality rankings or matrices. An iterative methodology is proposed to incrementally carry out materiality assessment by progressively building the domain knowledge required to automate the process. Efficiency and effectiveness evaluations are carried out in a real-world scenario. |
| format | Article |
| id | doaj-art-b95d0af8bb4849f2ad7b106b65c4b657 |
| institution | Kabale University |
| issn | 2667-0968 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Information Management Data Insights |
| spelling | doaj-art-b95d0af8bb4849f2ad7b106b65c4b6572024-12-29T04:48:13ZengElsevierInternational Journal of Information Management Data Insights2667-09682025-06-0151100310Automating materiality assessment with a data-driven document-based approachMatteo Francia0Enrico Gallinucci1Matteo Golfarelli2DISI - University of Bologna, Via dell’Università, 50, 47522, Cesena (FC), ItalyCorresponding author.; DISI - University of Bologna, Via dell’Università, 50, 47522, Cesena (FC), ItalyDISI - University of Bologna, Via dell’Università, 50, 47522, Cesena (FC), ItalyMateriality assessment is a critical process for companies to understand the interest perceived by its stakeholders towards topics related to environmental, social, and governance issues. Materiality assessment helps companies define their growth and communicative strategies; recently, it has become crucial within sustainability reporting, i.e., the practice of annually declaring the activities conducted to pursue economic growth in a sustainable way for society. In this paper, we propose a data-driven and automated approach to carry out materiality assessment. Stakeholders’ perception of important topics is obtained by analyzing relevant textual documents (e.g., company reports, press releases, social media posts), identifying mentions of potentially interesting topics, and converting them to scores that produce materiality rankings or matrices. An iterative methodology is proposed to incrementally carry out materiality assessment by progressively building the domain knowledge required to automate the process. Efficiency and effectiveness evaluations are carried out in a real-world scenario.http://www.sciencedirect.com/science/article/pii/S2667096824000995Materiality assessmentDecision support systemInformation retrievalSustainability reporting |
| spellingShingle | Matteo Francia Enrico Gallinucci Matteo Golfarelli Automating materiality assessment with a data-driven document-based approach International Journal of Information Management Data Insights Materiality assessment Decision support system Information retrieval Sustainability reporting |
| title | Automating materiality assessment with a data-driven document-based approach |
| title_full | Automating materiality assessment with a data-driven document-based approach |
| title_fullStr | Automating materiality assessment with a data-driven document-based approach |
| title_full_unstemmed | Automating materiality assessment with a data-driven document-based approach |
| title_short | Automating materiality assessment with a data-driven document-based approach |
| title_sort | automating materiality assessment with a data driven document based approach |
| topic | Materiality assessment Decision support system Information retrieval Sustainability reporting |
| url | http://www.sciencedirect.com/science/article/pii/S2667096824000995 |
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