Designing AI-based decision support systems for carbon stock estimation and planning: A design science research

Simple item page
dc.contributor.authorLi, Amelia S.
dc.contributor.authorPan, Shan L.
dc.contributor.authorTim, Yenni
dc.contributor.authorNguyen, Hoang D.
dc.date.accessioned2026-10-15T15:38:01Z
dc.date.available2026-10-15T15:38:01Z
dc.date.issued2026-06-04
dc.description.abstractMitigating climate change presents significant challenges, particularly in effective carbon stock estimation and planning. Decision-making based on quantified carbon stock is essential for enabling carbon sequestration efforts in natural ecosystems, yet traditional field measurements are labor-intensive, geographically constrained, and difficult to be adopted at scale. Motivated by this practical challenge, we undertook a design science research (DSR) project to develop AI-based decision support systems that enhance the efficiency, accessibility, and scalability for carbon stock estimation and planning. Guided by technology affordance theory, our iterative design, development, demonstration, and evaluation process has led to the conceptualization of four affordance-based design principles that build on and contribute to the growing design knowledge for environmental sustainability. This research advances our understanding of the critical problem and solution domains of carbon stock estimation and planning. It also facilitates the emerging discourse on balancing AI and human intelligence in designing systems for complex decision-making challenges for sustainability. This study provides an exemplar of DSR for supporting Sustainable Development Goal 13 by demonstrating how to design systems that facilitate carbon sequestration and societal transition toward environmental sustainability.en
dc.description.versionPublished Version
dc.format.extent13
dc.format.mimetypeapplication/pdfen
dc.identifier.articleid114704
dc.identifier.authororcidLi, Amelia S.
dc.identifier.authororcidPan, Shan L.
dc.identifier.authororcidTim, Yenni
dc.identifier.authororcidNguyen, Hoang D.§0000-0003-2541-3269
dc.identifier.citationLi, A S, Pan, S L, Tim, Y & Nguyen, H D 2026, 'Designing AI-based decision support systems for carbon stock estimation and planning: A design science research', Decision Support Systems, vol. 208, 114704, pp. 1-13. https://doi.org/10.1016/j.dss.2026.114704
dc.identifier.doi10.1016/j.dss.2026.114704
dc.identifier.endpage13
dc.identifier.issn0167-9236
dc.identifier.journaltitleDecision Support Systems
dc.identifier.otherORCID: /0000-0003-2541-3269/work/230190337
dc.identifier.startpage1
dc.identifier.urihttps://hdl.handle.net/10468/19447
dc.identifier.volume208
dc.language.isoen
dc.publisherElsevier B.V.
dc.relation.urihttps://www.scopus.com/pages/publications/105041293231
dc.rights© 2026, authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
dc.rights.accessrightsopen access
dc.rights.licensenameAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.statusPeer reviewed
dc.subjectAI-based DSS
dc.subjectClimate change
dc.subjectDesign science research
dc.subjectEnvironmental sustainability
dc.subjectSDG
dc.subject[ComputerScience]
dc.subject[Insight]
dc.titleDesigning AI-based decision support systems for carbon stock estimation and planning: A design science researchen
dc.typeArticle (peer-reviewed)
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
1-s2.0-S016792362600093X-main.pdf
Size:
4.59 MB
Format:
Adobe Portable Document Format
Description:
Published Version
Download
Collections
Insight Research Ireland Centre for Data Analytics
School of Computer Science and Information Technology