Please use this identifier to cite or link to this item: https://repository.iimb.ac.in/handle/2074/22202
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dc.contributor.authorYayavaram, Sai
dc.contributor.authorChanda, Sasanka Sekhar
dc.date.accessioned2024-02-20T05:54:54Z-
dc.date.available2024-02-20T05:54:54Z-
dc.date.issued2023
dc.identifier.issn1381-298X
dc.identifier.issn1572-9346
dc.identifier.urihttps://repository.iimb.ac.in/handle/2074/22202-
dc.description.abstractIt is well recognized that many organizations operate under situations of high complexity that arises from pervasive interdependencies between their decision elements. While prior work has discussed the benefits of low to moderate complexity, the literature on how to cope with high complexity is relatively sparse. In this study, we seek to demonstrate that Lindblom's decision-making principle of muddlingthrough is a very effective approach that organizations can use to cope with high complexity. Using a computational simulation (NK) model, we show that Lindblom's muddlingthrough approach obtains outcomes superior to those obtained from boundedly rational decision-making approaches when complexity is high. Moreover, our results also show that muddlingthrough is an appropriate vehicle for bringing in radical organizational change or far-reaching adaptation.
dc.publisherSpringer
dc.subjectBounded rationality
dc.subjectComplexity
dc.subjectComputational simulation
dc.subjectInterdependence
dc.subjectNK model
dc.subjectOrganizational change
dc.subjectMuddling through
dc.titleDecision making under high complexity: A computational model for the science of muddli
dc.typeJournal Article
dc.identifier.doi10.1007/s10588-021-09354-9
dc.pages300-335p.
dc.vol.noVol.29
dc.issue.noIss.2
dc.journal.nameComputational and Mathematical Organization Theory
Appears in Collections:2020-2029 C
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