Decision making under high complexity: a computational model for the science of muddling through

Sai Yayavaram () and Sasanka Sekhar Chanda ()
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Sai Yayavaram: Indian Institute of Management Bangalore
Sasanka Sekhar Chanda: C-101 Academic Block, Indian Institute of Management Indore

Computational and Mathematical Organization Theory, 2023, vol. 29, issue 2, No 2, 300-335

Abstract: Abstract It 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 muddling through 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 muddling through approach obtains outcomes superior to those obtained from boundedly rational decision-making approaches when complexity is high. Moreover, our results also show that muddling through is an appropriate vehicle for bringing in radical organizational change or far-reaching adaptation.

Keywords: Bounded rationality; Complexity; Computational simulation; Interdependence; NK model; Organizational change; Muddling through (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10588-021-09354-9

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