Artikel

More dynamic than you think: Hidden aspects of decision-making

Decision-making is a multifaceted, socially constructed, human activity that is often non-rational and non-linear. Although the decision-making literature has begun to recognize the effect of affect on decisions, examining for example the contribution of bodily sensations to affect, it continues to treat the various processes involved in coming to a decision as compartmentalized and static. In this paper, we use five theories to contribute to our understanding of decision-making, and demonstrate that it is much more fluid, multi-layered and non-linear than previously acknowledged. Drawing on a group experience of deciding, we investigate the intrapersonal, interpersonal, and collective states that are at play. These states are shown to be iterative: each being reinforced or dampened in a complex interaction of thought, affect, social space and somatic sensations in a dynamic flux, whilst individuals try to coalesce on a decision. This empirical investigation contributes to theory, method and practice by suggesting that Volatility, Uncertainty, Complexity and Ambiguity (VUCA) is a human condition. VUCA permeates and impacts decision-making in a multitude of ways, beyond researchers' previous understanding. The innovation generated through this paper resides in a set of propositions that will accelerate progress in the theory, method, and practice of decision-making.

Language
Englisch

Bibliographic citation
Journal: Administrative Sciences ; ISSN: 2076-3387 ; Volume: 7 ; Year: 2017 ; Issue: 3 ; Pages: 1-29 ; Basel: MDPI

Classification
Öffentliche Verwaltung
Subject
non-rational
decision-making
intuition
mindfulness
wisdom
organizational space
social improvising

Event
Geistige Schöpfung
(who)
Robinson, Jennifer
Sinclair, Marta
Tobias, Jutta
Choi, Ellen
Event
Veröffentlichung
(who)
MDPI
(where)
Basel
(when)
2017

DOI
doi:10.3390/admsci7030023
Handle
Last update
10.03.2025, 11:44 AM CET

Data provider

This object is provided by:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.

Object type

  • Artikel

Associated

  • Robinson, Jennifer
  • Sinclair, Marta
  • Tobias, Jutta
  • Choi, Ellen
  • MDPI

Time of origin

  • 2017

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