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.

Sprache
Englisch

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

Klassifikation
Öffentliche Verwaltung
Thema
non-rational
decision-making
intuition
mindfulness
wisdom
organizational space
social improvising

Ereignis
Geistige Schöpfung
(wer)
Robinson, Jennifer
Sinclair, Marta
Tobias, Jutta
Choi, Ellen
Ereignis
Veröffentlichung
(wer)
MDPI
(wo)
Basel
(wann)
2017

DOI
doi:10.3390/admsci7030023
Handle
Letzte Aktualisierung
10.03.2025, 11:44 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Artikel

Beteiligte

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

Entstanden

  • 2017

Ähnliche Objekte (12)