Although the influence of identity on consumer behavior has been documented in many streams of literature, the absence of a consistent definition of identity and of generally accepted principles regarding the drivers of identity-based behavior complicates comparisons across these literatures. To resolve that problem, we propose a simple but inclusive definition of identity. Identity can be defined as any category label with which a consumer selfassociates that is amenable to a clear picture of what a person in that category looks like, thinks, feels and does. Building from this definition, we propose the following five basic principles that can help researchers model the process of identity formation and expression:(1) Identity Salience: identity processing increases when the identity is an active component of the self; (2) Identity Association: the non-conscious association of stimuli with a positive and salient identity improves a person's response to the stimuli; (3) Identity Relevance: the deliberative evaluation of identity-linked stimuli depends on how diagnostic the identity is in the relevant domain; (4) Identity Verification: individuals monitor their own behaviors to manage and reinforce their identities; and (5) Identity Conflict: identity-linked behaviors help consumers manage the relative prominence of multiple identities. To illustrate the potential usefulness of these principles for guiding identity research, we discuss new avenues for identity research and explain how these principles could help guide investigations into these areas.

Artificial intelligence (AI) helps companies offer important benefits to consumers, such as health monitoring with wearable devices, advice with recommender systems, peace of mind with smart household products, and convenience with voice-activated virtual assistants. However, although AI can be seen as a neutral tool to be evaluated on efficiency and accuracy, this approach does not consider the social and individual challenges that can occur when AI is deployed. This research aims to bridge these two perspectives: on one side, the authors acknowledge the value that embedding AI technology into products and services can provide to consumers. On the other side, the authors build on and integrate sociological and psychological scholarship to examine some of the costs consumers experience in their interactions with AI. In doing so, the authors identify four types of consumer experiences with AI: (1) data capture, (2) classification, (3) delegation, and (4) social. This approach allows the authors to discuss policy and managerial avenues to address the ways in which consumers may fail to experience value in organizations’ investments into AI and to lay out an agenda for future research.

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This research contributes to the current understanding of language effects in advertising by uncovering a previously ignored mechanism shaping consumer response to an increasingly globalized marketplace. We propose a language-specific episodic trace theory of language emotionality to explain how language influences the perceived emotionality of marketing communications. Five experiments with bilingual consumers show (1) that textual information (e.g., marketing slogans) expressed in consumers' native language tends to be perceived as more emotional than messages expressed in their second language, (2) that this effect is not uniquely due to the activation of stereotypes associated to specific languages or to a lack of comprehension, and (3) that the effect depends on the frequency with which words have been experienced in native- versus second-language contexts. (c) 2008 by JOURNAL OF CONSUMER RESEARCH, Inc..

Although the influence of identity on consumer behavior has been documented in many streams of literature, the absence of a consistent definition of identity and of generally accepted principles regarding the drivers of identity-based behavior complicates comparisons across these literatures. To resolve that problem, we propose a simple but inclusive definition of identity. Identity can be defined as any category label with which a consumer selfassociates that is amenable to a clear picture of what a person in that category looks like, thinks, feels and does. Building from this definition, we propose the following five basic principles that can help researchers model the process of identity formation and expression:(1) Identity Salience: identity processing increases when the identity is an active component of the self; (2) Identity Association: the non-conscious association of stimuli with a positive and salient identity improves a person's response to the stimuli; (3) Identity Relevance: the deliberative evaluation of identity-linked stimuli depends on how diagnostic the identity is in the relevant domain; (4) Identity Verification: individuals monitor their own behaviors to manage and reinforce their identities; and (5) Identity Conflict: identity-linked behaviors help consumers manage the relative prominence of multiple identities. To illustrate the potential usefulness of these principles for guiding identity research, we discuss new avenues for identity research and explain how these principles could help guide investigations into these areas.