Personalized Communication as a Platform for Service Inclusion? Initial Insights Into Interpersonal and AI-Based Personalization for Stigmatized Consumers
Although calls for inclusiveness in services are becoming more vigorous, empirical research on how to design and implement service inclusion for stigmatized consumers remains scant. This paper draws on key questions of personalization (i.e., who personalizes what for whom?) to tailor the (a) source...
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Published in | Journal of service research : JSR Vol. 27; no. 1; pp. 28 - 48 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
Los Angeles, CA
SAGE Publications
01.02.2024
SAGE PUBLICATIONS, INC |
Subjects | |
Online Access | Get full text |
ISSN | 1094-6705 1552-7379 |
DOI | 10.1177/10946705231188676 |
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Summary: | Although calls for inclusiveness in services are becoming more vigorous, empirical research on how to design and implement service inclusion for stigmatized consumers remains scant. This paper draws on key questions of personalization (i.e., who personalizes what for whom?) to tailor the (a) source and (b) content of marketing messages in order to better include stigmatized consumers. The authors examine this idea in three experiments in healthcare/well-being settings. In terms of message source, the results show that, in interpersonal interactions, service companies can employ the principle of homophily to better engage stigmatized consumers (Study 1). In contrast, homophily-inspired personalized messages to stigmatized consumers can backfire in the context of consumer-artificial intelligence (AI)-interactions (human-to-avatar interactions; Study 2). Moreover, in terms of message content, Study 3 explores how, and under which conditions, companies can leverage thinking AI versus feeling AI for improved service inclusiveness. Finally, the studies point to anticipated consumer well-being as a crucial mediator driving effective service inclusiveness among stigmatized consumers. The results not only contribute to an emerging theory of service inclusiveness, but also provide service scholars and managers with initial empirical results on the role of AI in inclusive services. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
ISSN: | 1094-6705 1552-7379 |
DOI: | 10.1177/10946705231188676 |