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On leading and making data-driven decisions, or not
Dalarna University, School of Technology and Business Studies, Microdata Analysis.ORCID iD: 0000-0003-2317-9157
2019 (English)In: Developing Informed Intuition for Decision Making / [ed] Jay Liebowitz, Taylor & Francis Group, 2019, p. 161-173Chapter in book (Refereed)
Abstract [en]

In this chapter, I consider the cognitive biases arising in judgment under uncertainty that jeopardize good decision-making aligned with normative decision theories. This problem raises objections towards intuitive and fast decision-making. It would be appealing if training could be devised for reducing the biases, and I argue that such training is feasible. I relate best-practice in such training and advocate a number of topics to be included in such training for good, intuitive decision-making skills.

Place, publisher, year, edition, pages
Taylor & Francis Group, 2019. p. 161-173
Series
Data Analytics Applications
National Category
Other Computer and Information Science
Research subject
Complex Systems – Microdata Analysis, General Microdata Analysis - others
Identifiers
URN: urn:nbn:se:du-30686DOI: 10.1201/9780429298097ISBN: 9780367258573 (print)ISBN: 9780429298097 (electronic)OAI: oai:DiVA.org:du-30686DiVA, id: diva2:1350966
Available from: 2019-09-12 Created: 2019-09-12 Last updated: 2019-09-17Bibliographically approved

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Carling, Kenneth

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CiteExportLink to record
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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
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  • nn-NO
  • nn-NB
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  • Other locale
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Output format
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  • asciidoc
  • rtf