Journal of service management · 2023 · 146 citations · 69 references
Social SciencesPsychologySocial PsychologyCustomer Relationship ManagementInterpersonal RelationshipsRelationship MarketingCustomer EngagementRelationship DevelopmentRelationship FormationRelationship MaintenanceSocial InteractionUser Engagement AnalysisChatbot Customer ExperienceChatbot InteractionChatbot SystemsChatbotsConceptual Model DevelopmentOnline Relationship DevelopmentService User EngagementSurvey Data Processing
Purpose The purpose of this study is to explore customer-artificial intelligence (AI) service technology engagement and relationship development drivers, as well as potential negative consequences in the context of social chatbots. Design/methodology/approach A sequential mixed-method approach combined exploratory qualitative and confirmatory quantitative analyses. A conceptual model developed from Study 1 qualitative content analysis of in-depth interviews with active users of the AI social chatbot Replika was tested in Study 2 by analyzing survey data obtained from current Replika users. Findings Loneliness, trust and chatbot personification drive consumer engagement with social chatbots, which fosters relationship development and has the potential to cause chatbot psychological dependence. Attachment to a social chatbot intensifies the positive role of engagement in relationship development with the chatbot. Originality/value This study was the first to combine qualitative and quantitative approaches to explore drivers, boundary conditions and consequences of relationship and dependence formation with social chatbots. The authors proposed and empirically tested a novel theoretical model that revealed an engagement-based mechanism of relationship and dependence formation with social chatbots.
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When to use and how to report the results of PLS-SEM
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