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Anchoring without scale distortion

Published online by Cambridge University Press:  01 January 2023

Štěpán Bahník*
Affiliation:
Faculty of Business Administration, Prague University of Economics and Business, náměstí Winstona Churchilla 4, Prague, 130 67, Czech Republic
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Abstract

The scale distortion theory of anchoring argues that people are influenced by a previously considered numeric value, an anchor, because the anchor distorts the scale on which a subsequent judgment is made. The distortion of the scale due to the anchor is a momentary effect that would be overridden if the scale was distorted again, for example, by consideration of a different value on the same scale. In the present study, participants compared thirteen random anchors on the same scale to thirteen different objects. Subsequent numeric estimates of objects’ attributes were influenced by the corresponding anchors even though the anchors were divided from the estimates by twelve questions pertaining to different values on the same scale. The numeric value considered immediately before the estimate did not have a considerable effect on the judgment. While the anchoring effect was robust, it cannot be easily explained by scale distortion. Other possible theories of the anchoring effect are compatible with the results.

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Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
The authors license this article under the terms of the Creative Commons Attribution 3.0 License.
Copyright
Copyright © The Authors [2021] This is an Open Access article, distributed under the terms of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Figure 0

Figure 1: The size of the anchoring effect by item (A) and trial number (B). The points represent effect sizes — estimated differences between judgments for anchor values 1 and 1000 — and error bars represent 95% confidence intervals around them.

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