Andersson, H., Holmgren, M., Sörqvist, P., Threadgold, E., Beaman, C. P.
ORCID: https://orcid.org/0000-0001-5124-242X, Ball, L. J. and Marsh, J. E.
(2024)
The negative footprint illusion is exacerbated by the numerosity of
environment-friendly additions: unveiling the underpinning mechanisms.
Journal of Cognitive Psychology, 36 (2).
pp. 295-307.
ISSN 2044-592X
doi: 10.1080/20445911.2024.2313568
Abstract/Summary
The addition of environmentally friendly items to a set of conventional items sometimes leads people to believe that the carbon footprint of the entire set decreases rather than increases. This negative footprint illusion is supposedly underpinned by an averaging bias: people base environmental impact estimates not on the total impact of items but on their average. However, direct evidence for this underpinning mechanism is sparse. In the current paper, we tested novel predictions of the averaging-bias account. We found that the illusion’s magnitude increased with the addition of a greater number of “green” items when the number of conventional items was held constant (Studies 1 and 2), thus providing further support for the averaging bias account. We also challenged the account by testing what happens when the number of items in the conventional and “green” categories vary while holding the ratio between the two categories constant (Study 3). At odds with the averaging account, the magnitude of the illusion increased as the category size increased, thus revealing a potential role of a category-size bias. The results raise questions regarding the potential interplay between these two types of bias in the negative footprint illusion.
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| Item Type | Article |
| URI | https://reading-clone.eprints-hosting.org/id/eprint/114293 |
| Identification Number/DOI | 10.1080/20445911.2024.2313568 |
| Refereed | Yes |
| Divisions | Life Sciences > School of Psychology and Clinical Language Sciences > Language and Cognition |
| Publisher | Taylor & Francis |
| Download/View statistics | View download statistics for this item |
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