Analytical reasoning reduces internet fraud susceptibility
Analytical reasoning reduces internet fraud susceptibility
Fake websites extract an enormous financial and psychological toll on consumers across the globe, with some estimates reaching billions of dollars each year. Yet, there is a paucity of empirical data on why some consumers respond to fake websites while others remain immune. In nine studies (6 in the main text, 3 in Supplemental Materials) we tested the hypothesis that analytical reasoning promotes the ability to discriminate real from fake versions of popular consumer websites. We found evidence in support of this hypothesis in individual difference studies using both convenience (Supplemental Studies 1–2) and representative samples (Study 1) with expertise as a boundary condition of this effect (Study 2). We also found evidence for this hypothesis experimentally by inducing time pressure (Study 3) and priming participants to engage System 2 (analytic) versus System 1 (intuitive) processes (Study 4). This latter experimental effect was bounded by expertise (Study 5). Finally, we showed that the link between analytical reasoning and discriminability is mechanistically driven by memory recall (Study 6). Collectively, these studies provide convergent evidence that analytical reasoning may protect individuals from Internet fraud by helping them detect fraudulent websites.
Analytical reasoning, Cognitive reflection, Internet fraud, Internet security
Kelley, Nicholas J.
445e767b-ad9f-44f2-b2c6-d981482bb90b
Hurley-Wallace, Anna L.
7942e783-3a78-4fd2-8794-ac62ccf96d84
Warner, Katherine L.
81b18e4c-5b0f-48b5-adce-82a6d94dd284
Hanoch, Yaniv
3cf08e80-8bda-4d3b-af1c-46c858aa9f39
1 May 2023
Kelley, Nicholas J.
445e767b-ad9f-44f2-b2c6-d981482bb90b
Hurley-Wallace, Anna L.
7942e783-3a78-4fd2-8794-ac62ccf96d84
Warner, Katherine L.
81b18e4c-5b0f-48b5-adce-82a6d94dd284
Hanoch, Yaniv
3cf08e80-8bda-4d3b-af1c-46c858aa9f39
Kelley, Nicholas J., Hurley-Wallace, Anna L., Warner, Katherine L. and Hanoch, Yaniv
(2023)
Analytical reasoning reduces internet fraud susceptibility.
Computers in Human Behavior, 142, [107648].
(doi:10.1016/j.chb.2022.107648).
Abstract
Fake websites extract an enormous financial and psychological toll on consumers across the globe, with some estimates reaching billions of dollars each year. Yet, there is a paucity of empirical data on why some consumers respond to fake websites while others remain immune. In nine studies (6 in the main text, 3 in Supplemental Materials) we tested the hypothesis that analytical reasoning promotes the ability to discriminate real from fake versions of popular consumer websites. We found evidence in support of this hypothesis in individual difference studies using both convenience (Supplemental Studies 1–2) and representative samples (Study 1) with expertise as a boundary condition of this effect (Study 2). We also found evidence for this hypothesis experimentally by inducing time pressure (Study 3) and priming participants to engage System 2 (analytic) versus System 1 (intuitive) processes (Study 4). This latter experimental effect was bounded by expertise (Study 5). Finally, we showed that the link between analytical reasoning and discriminability is mechanistically driven by memory recall (Study 6). Collectively, these studies provide convergent evidence that analytical reasoning may protect individuals from Internet fraud by helping them detect fraudulent websites.
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Accepted/In Press date: 31 December 2022
e-pub ahead of print date: 12 January 2023
Published date: 1 May 2023
Additional Information:
Funding Information:
This research was supported by grants from the University of Southampton Web Science Institute ( https://www.southampton.ac.uk/wsi ) Research Collaboration Stimulus Fund to Nicholas J. Kelley (RCSF-2020-Kelley) and Yaniv Hanoch (RCSF-2019-Hanoch).
Publisher Copyright:
© 2023 The Authors
Keywords:
Analytical reasoning, Cognitive reflection, Internet fraud, Internet security
Identifiers
Local EPrints ID: 475614
URI: http://eprints.soton.ac.uk/id/eprint/475614
ISSN: 0747-5632
PURE UUID: 3d4704dd-d72a-4252-96ef-ccaf983e0b3a
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Date deposited: 22 Mar 2023 17:42
Last modified: 30 Nov 2024 03:02
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Author:
Anna L. Hurley-Wallace
Author:
Katherine L. Warner
Author:
Yaniv Hanoch
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