Digital Twin-Enabled Decision Support for Flexible Dormitory Governance in Higher Education
- DOI
- 10.2991/978-2-38476-593-5_50How to use a DOI?
- Keywords
- digital twin; dormitory governance; higher education management; decision support; service optimization
- Abstract
This paper presents a digital twin-enabled decision support framework for flexible dormitory governance in higher education. The framework links student-state perception, room-resource visibility, rule-based screening, preference evaluation, and counselor review in one auditable governance loop. A pilot in Dormitory Building 9 at Panzhihua University uses de-identified data from 576 students in a 10-floor, 542-room building with a capacity of 2168 students. Compared with the manual process, the framework cuts room-allocation time from 210 to 12Â min and room-reassignment time from 135 to 6Â min, raises mean satisfaction from 3.0 to 4.0, reduces counselor workload from 120 to 25Â h per semester, and lowers vacancy rate from 8.5% to 2.1%. The findings indicate that digital twin technology can support interpretable dormitory governance under institutional constraints.
- Copyright
- © 2026 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Lu Yang AU - Yang Gao PY - 2026 DA - 2026/06/30 TI - Digital Twin-Enabled Decision Support for Flexible Dormitory Governance in Higher Education BT - Proceedings of the 2026 5th International Conference on Humanities, Wisdom Education and Service Management (HWESM 2026) PB - Atlantis Press SP - 461 EP - 469 SN - 2352-5398 UR - https://doi.org/10.2991/978-2-38476-593-5_50 DO - 10.2991/978-2-38476-593-5_50 ID - Yang2026 ER -