Context-Sensitive Mental Model Aggregation in a Second-Order Adaptive Network Model for Organisational Learning

Gülay Canbaloğlu; Jan Treur

doi:10.1007/978-3-030-93409-5_35

Context-Sensitive Mental Model Aggregation in a Second-Order Adaptive Network Model for Organisational Learning

Gülay Canbaloğlu^*, Jan Treur

^*Corresponding author for this work

Computer Science

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

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Abstract

Organisational learning processes often exploit developed individual mental models in order to obtain shared mental models for the organisation by some form of unification or aggregation. The focus in this paper is on this aggregation process, which may depend on a number of contextual factors. It is shown how a second-order adaptive network model for organisation learning can be used to model this process of aggregation of individual mental models in a context-dependent manner.

Original language	English
Title of host publication	Complex Networks and Their Applications X
Subtitle of host publication	Volume 1, Proceedings of the Tenth International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2021
Editors	Rosa Maria Benito, Chantal Cherifi, Hocine Cherifi, Esteban Moro, Luis M. Rocha, Marta Sales-Pardo
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	411-423
Number of pages	13
ISBN (Electronic)	9783030934095
ISBN (Print)	9783030934088, 9783030934118
DOIs	https://doi.org/10.1007/978-3-030-93409-5_35
Publication status	Published - 2022
Event	10th International Conference on Complex Networks and Their Applications, COMPLEX NETWORKS 2021 - Madrid, Spain Duration: 30 Nov 2021 → 2 Dec 2021

Publication series

Name	Studies in Computational Intelligence
Volume	1015
ISSN (Print)	1860-949X
ISSN (Electronic)	1860-9503

Conference

Conference	10th International Conference on Complex Networks and Their Applications, COMPLEX NETWORKS 2021
Country/Territory	Spain
City	Madrid
Period	30/11/21 → 2/12/21

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© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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10.1007/978-3-030-93409-5_35

Context-Sensitive Mental Model Aggregation in a Second-Order Adaptive Network Model for Organisational LearningFinal published version, 1.27 MBLicence: Article 25fa Dutch Copyright Act

https://www.researchgate.net/publication/354176039Licence: Unspecified

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Canbaloğlu, G., & Treur, J. (2022). Context-Sensitive Mental Model Aggregation in a Second-Order Adaptive Network Model for Organisational Learning. In R. M. Benito, C. Cherifi, H. Cherifi, E. Moro, L. M. Rocha, & M. Sales-Pardo (Eds.), Complex Networks and Their Applications X: Volume 1, Proceedings of the Tenth International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2021 (pp. 411-423). (Studies in Computational Intelligence; Vol. 1015). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-93409-5_35

Canbaloğlu, Gülay ; Treur, Jan. / Context-Sensitive Mental Model Aggregation in a Second-Order Adaptive Network Model for Organisational Learning. Complex Networks and Their Applications X: Volume 1, Proceedings of the Tenth International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2021. editor / Rosa Maria Benito ; Chantal Cherifi ; Hocine Cherifi ; Esteban Moro ; Luis M. Rocha ; Marta Sales-Pardo. Springer Science and Business Media Deutschland GmbH, 2022. pp. 411-423 (Studies in Computational Intelligence).

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title = "Context-Sensitive Mental Model Aggregation in a Second-Order Adaptive Network Model for Organisational Learning",

abstract = "Organisational learning processes often exploit developed individual mental models in order to obtain shared mental models for the organisation by some form of unification or aggregation. The focus in this paper is on this aggregation process, which may depend on a number of contextual factors. It is shown how a second-order adaptive network model for organisation learning can be used to model this process of aggregation of individual mental models in a context-dependent manner.",

author = "G{\"u}lay Canbaloğlu and Jan Treur",

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Canbaloğlu, G & Treur, J 2022, Context-Sensitive Mental Model Aggregation in a Second-Order Adaptive Network Model for Organisational Learning. in RM Benito, C Cherifi, H Cherifi, E Moro, LM Rocha & M Sales-Pardo (eds), Complex Networks and Their Applications X: Volume 1, Proceedings of the Tenth International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2021. Studies in Computational Intelligence, vol. 1015, Springer Science and Business Media Deutschland GmbH, pp. 411-423, 10th International Conference on Complex Networks and Their Applications, COMPLEX NETWORKS 2021, Madrid, Spain, 30/11/21. https://doi.org/10.1007/978-3-030-93409-5_35

Context-Sensitive Mental Model Aggregation in a Second-Order Adaptive Network Model for Organisational Learning. / Canbaloğlu, Gülay; Treur, Jan.
Complex Networks and Their Applications X: Volume 1, Proceedings of the Tenth International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2021. ed. / Rosa Maria Benito; Chantal Cherifi; Hocine Cherifi; Esteban Moro; Luis M. Rocha; Marta Sales-Pardo. Springer Science and Business Media Deutschland GmbH, 2022. p. 411-423 (Studies in Computational Intelligence; Vol. 1015).

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

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Canbaloğlu G, Treur J. Context-Sensitive Mental Model Aggregation in a Second-Order Adaptive Network Model for Organisational Learning. In Benito RM, Cherifi C, Cherifi H, Moro E, Rocha LM, Sales-Pardo M, editors, Complex Networks and Their Applications X: Volume 1, Proceedings of the Tenth International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2021. Springer Science and Business Media Deutschland GmbH. 2022. p. 411-423. (Studies in Computational Intelligence). Epub 2022 Jan 1. doi: 10.1007/978-3-030-93409-5_35

Context-Sensitive Mental Model Aggregation in a Second-Order Adaptive Network Model for Organisational Learning

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