Digitální knihovnaUPCE
 

Representativeness heuristics: a literature review of its impacts on the quality of decision-making

ČlánekOtevřený přístuppeer-reviewedpublished
Náhled

Datum publikování

2018

Vedoucí práce

Oponent

Název časopisu

Název svazku

Vydavatel

Univerzita Pardubice

Abstrakt

The representativeness heuristic is one of the cognitive shortcuts that simplify human decision-making. The simplicity provided by the heuristic brings advantages but also risks arising from a lack of information, leading to cognitive errors and biases. The aim of this study is to identify and evaluate the impact of biases connected to the representativeness heuristic on the quality of economic decision-making. For that purpose, a systematic literature review was conducted, and seventeen empirical studies were analyzed. The review found that the effect of the biases is indeed significant in the real world, namely in the area of business. Most of the studies analyzed the representativeness heuristics in investment and did not prove any strictly negative impact of heuristic decision-making. In fact, under certain circumstances, representativeness heuristics can be recommended. In addition to investment, we covered studies focusing on management, auditing, insurance and consulting. Although these studies show the possible impact of the heuristic on the quality of decision making, it is impossible to form general conclusions due to the lack of research in these fields. Alongside investment, further research into the use of the representativeness heuristics in various settings is recommended as well as research into the possible ways to reduce or even eliminate the negative side effects and biases of the heuristics.

Rozsah stran

p. 29 - 38

ISSN

1211-555X (Print)
1804-8048 (Online)

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Projekt

Zdrojový dokument

Scientific papers of the University of Pardubice. Series D, Faculty of Economics and Administration. 43/2018

Vydavatelská verze

Přístup k e-verzi

open access

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Klíčová slova

representativeness heuristics, systematic review, bias, management, decision-making

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