
This paper investigates why audiences devalue organizations that behave inauthentically. One explanation is that inauthenticity leads to lower perceptions of product quality. This stems from the audience’s doubt of an inauthentic actor’s capability and commitment to produce high-quality goods. Another explanation is that audiences discount the symbolic value—or what the object represents—of products from inauthentic organizations. I empirically test each of these mechanisms in the craft beer industry. First, I exploit exogenous variation in consumers’ knowledge of craft brewers’ inauthentic identity (whether they are owned by a corporate brewer) to empirically demonstrate an inauthenticity discount. Next, I decompose audience evaluations to show that knowledge of a producer’s inauthenticity does not have a statistically significant impact on evaluators’ sensory experience of the product—its taste, smell, appearance, or mouthfeel—but that it does affect audience evaluations of the product’s symbolic value. This paper was accepted by Olav Sorenson, organizations.
bepress|Social and Behavioral Sciences, SocArXiv|Social and Behavioral Sciences, Social and Behavioral Sciences
bepress|Social and Behavioral Sciences, SocArXiv|Social and Behavioral Sciences, Social and Behavioral Sciences
| 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). | 112 | |
| 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. | Top 1% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
