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ZENODO
Dataset . 2024
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2024
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2024
License: CC BY
Data sources: Datacite
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Honesty Pledges to reduce Unethical Behavior

Authors: Peer, Eyal; Mazar, Nina; Feldman, Yuval; Ariely, Dan;

Honesty Pledges to reduce Unethical Behavior

Abstract

Authorities and managers often rely on individuals and businesses' self-reports and employ various forms of honesty declarations to ensure that those individuals and businesses do not over-claim payments, benefits, or other resources. While previous work has found that honesty pledges have the potential to decrease dishonesty, effects have been mixed. We argue that understanding and predicting when honesty pledges are effective has been obstructed due to variations in experimental designs and operationalizations of honesty pledges in previous research. Specifically, we focus on the role of whether and how an ex-ante honesty pledge asks individuals to identify (by ID, name, initials) and how much involvement the pledge requires from the individual (low: just reading vs. high: re-typing the text of the pledge). In four pre-registered online studies (N > 5000), we systematically examine these two dimensions of a pledge to find that involvement is often more effective than identification. In addition, low involvement pledges, without any identification, are mostly ineffective. Finally, we find that the effect of a high (vs. low) involvement pledge is relatively more persistent across tasks. Yet, repeating a low involvement pledge across tasks increases its effectiveness and compensates for the lower persistency across tasks. Taken together, these results contribute both to theory by comparing some of the mechanisms possibly underlying honesty pledges as well as to practice by providing guidance to managers and policymakers on how to effectively design pledges to prevent or reduce dishonesty in self-reports.

Keywords

Honesty pledges, Honesty nudges, Unethical behavior

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average