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Title: Fast and frugal heuristics and naturalistic decision making: a review of their commonalities and differences
Authors: Shan, Yixing
Yang, Lili
Keywords: Heuristic
Research philosophy
Research synergy
Issue Date: 2017
Publisher: © Taylor & Francis
Citation: SHAN, Y. and YANG, L., 2017. Fast and frugal heuristics and naturalistic decision making: a review of their commonalities and differences. Thinking and Reasoning, 23 (1), pp. 10-32.
Abstract: © 2016 Taylor & Francis Both the fast and frugal heuristics (FFHs) and the naturalistic decision making (NDM) research programmes have identified important areas of inquiry previously neglected in the traditional study of human judgment and decision making, and have greatly contributed to the understanding of people's real-world decision making under environmental constraints. The two programmes share similar theoretical arguments regarding the rationality, optimality, and role of experience in decision making. Their commonalities have made them appealing to each other, and efforts have been made, by their leading academics, to promote synergy and integration. However, there has been little progress towards this during the last decade. This paper seeks to address this gap by seeking to better understand their commonalities and differences. To do so, literature relating to the two programmes is reviewed. The findings of the review indicated that an integration of the two could enhance FFHs' field research in applied settings, facilitate its investigation on boundary conditions of people's decision strategy selection, enable NDM to embrace emerging research opportunities in the age of big data, as well as permit each programme to enlighten the research topics and to validate the research findings of the other.
Description: This paper is in closed access.
Version: Published
DOI: 10.1080/13546783.2016.1152999
URI: https://dspace.lboro.ac.uk/2134/21483
Publisher Link: http://dx.doi.org/10.1080/13546783.2016.1152999
ISSN: 1354-6783
Appears in Collections:Closed Access (Business)

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