Publication: Multilevel organisational learning in a project-based organisation: computational analysis based on a 3rd-order adaptive network model
dc.contributor.coauthor | Treur, Jan | |
dc.contributor.coauthor | Wiewiora, Anna | |
dc.contributor.department | Department of Computer Engineering | |
dc.contributor.kuauthor | Canbaloğlu, Gülay | |
dc.contributor.kuprofile | Undergraduate Student | |
dc.contributor.other | Department of Computer Engineering | |
dc.contributor.schoolcollegeinstitute | College of Engineering | |
dc.contributor.yokid | N/A | |
dc.date.accessioned | 2024-11-09T23:59:11Z | |
dc.date.issued | 2022 | |
dc.description.abstract | This paper describes how the recently developed self-modeling network modeling approach for multilevel organisational learning has been tested on applicability for a real-world case of a project-based organisation. The modeling approach was able to successfully address this complex case by designing a third-order adaptive network model. Doing this, as a form of further innovation three new features have been added to the modeling approach: Recombination of selected high-quality mental model parts, refinement of mental model parts, and distinction between context-sensitive detailed control and global control. © 2022 Elsevier B.V.. All rights reserved. | |
dc.description.indexedby | Scopus | |
dc.description.issue | C | |
dc.description.openaccess | YES | |
dc.description.publisherscope | International | |
dc.description.volume | 213 | |
dc.identifier.doi | 10.1016/j.procs.2022.11.040 | |
dc.identifier.issn | 1877-0509 | |
dc.identifier.link | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85146121992&doi=10.1016%2fj.procs.2022.11.040&partnerID=40&md5=836b28dea19badf449bbad2d39bce7da | |
dc.identifier.scopus | 2-s2.0-85146121992 | |
dc.identifier.uri | http://dx.doi.org/10.1016/j.procs.2022.11.040 | |
dc.identifier.uri | https://hdl.handle.net/20.500.14288/15580 | |
dc.keywords | Adaptive computational model | |
dc.keywords | Multilevel organisational learning | |
dc.keywords | Project-based organisation computational methods | |
dc.keywords | Knowledge management | |
dc.keywords | Learning systems | |
dc.keywords | Quality control | |
dc.keywords | Adaptive computational model | |
dc.keywords | Adaptive networks | |
dc.keywords | Computational modelling | |
dc.keywords | Mental model | |
dc.keywords | Modeling approach | |
dc.keywords | Multilevels | |
dc.keywords | Network models | |
dc.keywords | Organizational learning | |
dc.keywords | Project-based organizations | |
dc.keywords | Cognitive systems | |
dc.language | English | |
dc.publisher | Elsevier B.V. | |
dc.source | Procedia Computer Science | |
dc.subject | Construction industry | |
dc.subject | Project-based organizations | |
dc.subject | Office management | |
dc.title | Multilevel organisational learning in a project-based organisation: computational analysis based on a 3rd-order adaptive network model | |
dc.type | Conference proceeding | |
dspace.entity.type | Publication | |
local.contributor.authorid | N/A | |
local.contributor.kuauthor | Canbaloğlu, Gülay | |
relation.isOrgUnitOfPublication | 89352e43-bf09-4ef4-82f6-6f9d0174ebae | |
relation.isOrgUnitOfPublication.latestForDiscovery | 89352e43-bf09-4ef4-82f6-6f9d0174ebae |