품질경영학회지 (Journal of Korean Society for Quality Management)

  • 제47권4호
  • /
  • Pages.755-765
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  • 2019
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  • 1229-1889(pISSN)
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  • 2287-9005(eISSN)
한국품질경영학회 (Korean Society for Quality Management)
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챗봇 사용 의도에 영향을 미치는 요인 탐색 - 금융 서비스에서의 챗봇

Exploring Factors Influencing Usage Intention of Chatbot - Chatbot in Financial Service

  • 이민규 (연세대학교 일반대학원 융합기술경영공학 협동과정) ;
  • 박희준 (연세대학교 산업공학과)
  • Lee, Min Kyu (Department of Convergence Technology Management Engineering, Yonsei University) ;
  • Park, Heejun (Department of Industrial Engineering, Yonsei University)
  • 투고 : 2019.10.30
  • 심사 : 2019.11.04
  • 발행 : 2019.12.31
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초록

Purpose: Chatbots are widely diffusing across various industries to substitute human manpower in the industry. However as researchers only develop technology that is applied to chatbot, the diffusion is slow in progress. The purpose of this study is to propose useful implications to accelerate diffusion of chatbots across industries by analyzing the perception of customers. To achieve the research purpose this study analyzes causal effect relationship between characteristics of chatbot character, service quality, individual difference, and intention to use chatbot. Methods: This study developed a survey that contains various questionnaires for each construct based on literature review. Data collected through survey was tested for convergent validity and discriminant validity and further analyzed the relationship using PLS-SEM method to verify hypotheses. Results: Trustworthiness of the chatbot character, ease of use, application design, responsiveness, customization, assurance, inertia, and previous experience have significant influence on forming user satisfaction, consumer trust, and intention to use. The others, likability, appropriateness, technology anxiety, and need for interaction were not significant in this research. Conclusion: Although the constructs of the research model was significant in previous literatures, some do not have significant effect on intention to use chatbots. Based on the results, chatbot managers will be able to develop chatbot systems which are more appealing to users and more academic researchers will focus on analyzing user perception and intention.

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