자료요약
본 연구는 고객이 비대면 모바일 금융 상품을 챗봇에게 추천받는 상황에서 고객의 긍/부정적인 인식과 반응을 유발할 수 있는 챗봇의 특성과 그 효과가 무엇인지 알아보고자 하였다. 보다 구체적으로, AI를 활용한 금융 챗봇 추천 메시지의 의인화와 개인화 수준에 따라 고객이 인지하는 메시지의 사회적 실재감과 인지된 유용성, 프라이버시 염려가 어떠한지 살펴보고, 이것이 챗봇 추천 서비스 이용의도에 미치는 영향을 검증하였다. 이를 위해, 개인화 수준을 세 단계로 제시하고 개인화 수준이 높을수록 소비자에게 긍정적인 인식을 줄 것인가에 대해 최적자극수준 이론을 중심으로 고찰하였다. 특히, 이 과정에서 실제 금융 상품 서비스와 유사한 챗봇 플랫폼을 제작하여 실험에 활용하고 응답자에게 경험하게 함으로써 가설을 검증하였다. 그 결과 고객이 금융 챗봇 추천 메시지의 의인화 수준과 개인화 수준이 높아질수록 사회적 실재감이 증가하고 이용의도에 유의미한 영향을 주는 것으로 나타났으며 개인화 수준이 높아질수록 프라이버시 염려가 증가하는 것으로 확인되었다. 또한 개인화 수준이 높아질수록 고객이 인지하는 유용성은 점차 커지나 역설적으로 이용의도는 중간 지점 이후 오히려 떨어지는 역U자 형태를 확인할 수 있었다. 본 연구는 AI 금융 챗봇 추천 메시지의 의인화와 개인화 수준이 고객에게 어떠한 반응을 일으키는지 확인하였으며, 특히 개인화 마케팅의 개인정보 활용 수준에 따른 고객 반응을 최적자극수준 이론을 적용하여 규명하였다는 점에서 이론적 의의가 있다고 할 수 있다. 또한, 이를 바탕으로 금융 챗봇 추천 메시지가 효과적인 마케팅 전략에 활용되기 위한 방안을 제시함으로써 실무적 함의 또한 가진다.
The main purpose of this study was to examine the characteristics of chatbots and their effects that could induce positive/negative perceptions and reactions of customers when a non-face-to-face mobile financial product was recommended by a chatbot. More specifically, we examined the social presence, perceived usefulness, and privacy concerns of the messages perceived by the customer according to the level of anthropomorphism and personalization of the financial chatbot recommendation messages. In particular, in this process, the level of personalization was presented in three stages. This study focused on the theory of Optimal Stimulation Level Theory to see if the higher level of personalization gave consumers a positive perception. As a result, the higher the level of anthropomorphism and personalization in the financial chatbot recommendation message, the higher the social presence and intention to use. And also, the higher the level of personalization, the more privacy concerns. In addition, the higher the level of personalization, the greater the perceived usefulness of the customer, but paradoxically, the intention to use was rather reduced after a middle point. This study confirmed how the level of anthropomorphism and personalization of financial chatbot recommendation messages caused customer reactions. And in particular, it had a theoretical significance in identifying customer responses according to the level of personal information usage in personalized marketing. In addition, it was meaningful that the financial chatbot recommendation message was a practical proposal for the industry by suggesting a method to be used in an effective marketing strategy.
The main purpose of this study was to examine the characteristics of chatbots and their effects that could induce positive/negative perceptions and reactions of customers when a non-face-to-face mobile financial product was recommended by a chatbot. More specifically, we examined the social presence, perceived usefulness, and privacy concerns of the messages perceived by the customer according to the level of anthropomorphism and personalization of the financial chatbot recommendation messages. In particular, in this process, the level of personalization was presented in three stages. This study focused on the theory of Optimal Stimulation Level Theory to see if the higher level of personalization gave consumers a positive perception. As a result, the higher the level of anthropomorphism and personalization in the financial chatbot recommendation message, the higher the social presence and intention to use. And also, the higher the level of personalization, the more privacy concerns. In addition, the higher the level of personalization, the greater the perceived usefulness of the customer, but paradoxically, the intention to use was rather reduced after a middle point. This study confirmed how the level of anthropomorphism and personalization of financial chatbot recommendation messages caused customer reactions. And in particular, it had a theoretical significance in identifying customer responses according to the level of personal information usage in personalized marketing. In addition, it was meaningful that the financial chatbot recommendation message was a practical proposal for the industry by suggesting a method to be used in an effective marketing strategy.
목차
1. 연구 배경과 목적
2. 이론적 논의 및 연구 가설
3. 연구방법
4. 연구 결과
5. 결론 및 제언
참고문헌
Abstract
2. 이론적 논의 및 연구 가설
3. 연구방법
4. 연구 결과
5. 결론 및 제언
참고문헌
Abstract
#금융 챗봇
#인공지능
#추천 메시지
#의인화
#개인화
#Financial Chatbot
#AI
#Recommended Message
#Anthropomorphism
#Personalization