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    Thick as Thieves? Dishonest Behavior and Egocentric Social Networks
    25 Feb 2015Working Paper Summaries

    Thick as Thieves? Dishonest Behavior and Egocentric Social Networks

    by Jooa Julia Lee, Dong-Kyun Im, Bidhan L. Parmar and Francesca Gino
    In a series of laboratory and online experiments, the authors examined the relational and psychological consequences of dishonest behavior. Findings suggest that individuals' perceived social relationships are key to regulating human morality. While earlier research has shown that a cohesive social network can temper one's moral behavior through shared norms, this new work demonstrates a flip-side: People often construct their own social network as a way to defend themselves from threatening information.
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    Author Abstract

    People experience a threat to their moral self-concept in the face of discrepancies between their moral values and their unethical behavior. We theorize that people's need to restore their view of themselves as moral activates thoughts of a high-density personal social network. Such thoughts also lead people to more likely engage in further unethical behavior. In five experiments, participants reflected on their past unethical behavior, and then completed a task designed to measure network density. Those who cheated more frequently in the past, recalled their negative moral identity, or decided to lie were more likely to activate a high-density network (Experiments 1-3). Using a mediation-by-moderation approach (Experiment 4), we confirm that this link between dishonesty and network density is explained by a threat to positive self-concept. Importantly, activating a dense network after engaging in dishonest behavior allows further dishonest behavior in a subsequent task (Experiment 5).

    Paper Information

    • Full Working Paper Text
    • Working Paper Publication Date: February 2015
    • HBS Working Paper Number: 15-064
    • Faculty Unit(s): Negotiation, Organizations & Markets
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    Francesca Gino
    Francesca Gino
    Tandon Family Professor of Business Administration
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