Engaging consumers through artificially intelligent technologies: Systematic review, conceptual model, and further researchVisa övriga samt affilieringar
2024 (Engelska)Ingår i: Psychology & Marketing, ISSN 0742-6046, E-ISSN 1520-6793, Vol. 41, nr 4, s. 880-898Artikel, forskningsöversikt (Refereegranskat) Published
Abstract [en]
While consumer engagement (CE) in the context of artificially intelligent (AI-based) technologies (e.g., chatbots, smart products, voice assistants, or autonomous cars) is gaining traction, the themes characterizing this emerging, interdisciplinary corpus of work remain indeterminate, exposing an important literature-based gap. Addressing this gap, we conduct a systematic review of 89 studies using the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) approach to synthesize the AI-based CE literature. Our review yields three major themes of AI-based CE, including (i) Increasingly accurate service provision through AI-based CE; (ii) Capacity of AI-based CE to (co)create consumer-perceived value, and (iii) AI-based CE's reduced consumer effort in their task execution. We also develop a conceptual model that proposes the AI-based CE antecedents of personal, technological, interactional, social, and situational factors, and the AI-based CE consequences of consumer-based, firm-based, and human-AI collaboration outcomes. We conclude by offering pertinent implications for theory development (e.g., by offering future research questions derived from the proposed themes of AI-based CE) and practice (e.g., by reducing consumer-perceived costs of their brand/firm interactions).
Ort, förlag, år, upplaga, sidor
John Wiley & Sons, 2024. Vol. 41, nr 4, s. 880-898
Nyckelord [en]
artificial intelligence, consumer engagement, PRISMA, systematic review
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Företagsekonomi
Identifikatorer
URN: urn:nbn:se:umu:diva-219529DOI: 10.1002/mar.21957ISI: 001136719500001Scopus ID: 2-s2.0-85181493334OAI: oai:DiVA.org:umu-219529DiVA, id: diva2:1829513
2024-01-192024-01-192024-06-11Bibliografiskt granskad