An Adaptive Self-Modeling Network Model for Multilevel Organisational Learning

Gülay Canbaloğlu, Jan Treur, Peter Roelofsma

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

Organisational learning is often considered to concern mental models as a vehicle for individual, team, and organizational learning. By learning individual mental models, a basis for formation of shared team mental models is created, and based on the different shared team mental models, a shared organisation mental model can be obtained. This pathway is indicated by feed-forward learning. In addition, feedback learning follows the opposite pathway: shared team mental models can be learned from a shared organisation mental model and individual mental models can be learned from shared team mental models. These pathways and their interactions provide complex dynamic and adaptive mechanisms that together constitute organizational learning. These mechanisms have been used as a basis for an adaptive computational network model for organisational learning. The model is illustrated by a not too complex but realistic case study.
Original languageEnglish
Title of host publication Proceedings of the 7th International Congress on Information and Communication Technology, ICICT'22
PublisherSpringer Nature Switzerland AG
Publication statusAccepted/In press - 20 Oct 2021

Publication series

NameLecture Notes in Networks and Systems
PublisherSpringer Nature

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