Paper Type
Complete
Abstract
The widespread adoption of AI-driven chatbots has revolutionized customer service interactions, yet challenges persist in customer adoption, trust, and satisfaction. This study conducts a systematic literature review of top information systems journals and a leading conference (ICIS) to identify the effects of chatbot interactions in customer service and propose future research directions. By analyzing 42 articles, we identify seven effects categorized into immediate (e.g., perception and service evaluation), mid-term (e.g., adoption and behavior change), and long-term outcomes (e.g., loyalty and word-of-mouth). We synthesize prior research findings related to each theme and explain key factors, such as chatbot design and user characteristics, that contribute to these effects. Our findings reveal that despite growing research, significant gaps remain in understanding customer-chatbot interactions. We highlight underexamined areas and outline avenues for future research. This study contributes to both theory and practice by advancing knowledge on chatbot effectiveness and providing guidance for future investigations.
Paper Number
1613
Recommended Citation
Javadi, Shirin and Kordzadeh, Nima, "From First Impressions to Loyalty: Understanding User Effects of Customer Service Chatbots" (2025). AMCIS 2025 Proceedings. 10.
https://aisel.aisnet.org/amcis2025/sig_osra/sig_osra/10
From First Impressions to Loyalty: Understanding User Effects of Customer Service Chatbots
The widespread adoption of AI-driven chatbots has revolutionized customer service interactions, yet challenges persist in customer adoption, trust, and satisfaction. This study conducts a systematic literature review of top information systems journals and a leading conference (ICIS) to identify the effects of chatbot interactions in customer service and propose future research directions. By analyzing 42 articles, we identify seven effects categorized into immediate (e.g., perception and service evaluation), mid-term (e.g., adoption and behavior change), and long-term outcomes (e.g., loyalty and word-of-mouth). We synthesize prior research findings related to each theme and explain key factors, such as chatbot design and user characteristics, that contribute to these effects. Our findings reveal that despite growing research, significant gaps remain in understanding customer-chatbot interactions. We highlight underexamined areas and outline avenues for future research. This study contributes to both theory and practice by advancing knowledge on chatbot effectiveness and providing guidance for future investigations.
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