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I am a Person, But They Are a Condition: The Role of Language Choices on Consumer Behavior for Stigmatized Groups

Synopsis

Although millions of consumers deal with various stigmatized identities such as obesity, homelessness, and substance use disorders, little is known about 1) whether stigmatized identity language within the marketplace matches consumer preferences and 2) the psychological factors that impact the use of these language choices towards stigmatized groups. While there is some evidence that people dealing with stigmatized conditions prefer person-first language (e.g., person with obesity) instead of identity-first language (e.g., obese person), the use of person-first language is not universal by brands. This talk first addresses research that uses health ads and voice-over lab studies. We find that people dealing with weight issues are more interested in engaging with nutrition brands that use person-first language to describe their weight identity. However, data scraping weight and nutrition brand websites reveals that brands are more likely to use identity-first language to describe weight identities. This talk then explores what drives the use of identity vs. person-first language for stigmatized groups. Using textual analysis of 1326 nonprofit organizations and academic literature as well as follow-up lab experiments, we find that for conditions perceived to be more changeable, organizations and people are more likely to use identity-first language. The relationship between people’s use of identity-first language for conditions viewed as changeable is mediated by perceptions of onset or personal responsibility for stigmatized others. Our results suggest that if person-first language is helpful in empowering stigmatized groups, it will be necessary to point out the multi-faceted nature of the systems that support the stigmatized condition, such that individuals are not saddled with the type of responsibility that hides their personhood behind their condition.

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Consumer ratings have become a prevalent driver of choice. I develop a model of social learning in which ratings can inform consumers about both product quality and their idiosyncratic taste for them. Depending on consumers’ prior knowledge, I show that ratings relatively advantage lower quality and more polarizing products. The reason lies in the stronger positive consumer self-selection these products generate: to buy them despite their deficiencies, their buyers must have a strong taste for them. Relatedly, consumer ratings should not be used to infer product design: what is polarizing ex-ante needs not be so among its buyers. I test these predictions using Goodreads book ratings data, and find strong evidence for them. Moreover, social learning appears to serve mostly a matching purpose: tracking the behaviour of Goodreads users over time shows that they specialize as they gather experience on the platform: they rate books with a lower average and number of ratings, while focusing on fewer genres. Thus, they become less similar to their average peer. Taken together, the findings suggest that consumer ratings contribute to both the long tail and, relatedly, consumption segregation. For managers, this illustrates, counterintuitively, the reputational benefits of polarizing products, particularly early in a firm’s lifecycle, but only when paired with the ability to match with the right consumers.

Mengxia Zhang,

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Doctoral Student, USC Marshall School of Business

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