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의인화된 챗봇의 자기노출과 감정표현이 사용자 경험에 미치는 영향 - 금융서비스에서의 대화 오류 상황을 중심으로
Effect of Anthropomorphic Chatbot's Self-disclosure and Emotional Expression on User Experience - Focused on Conversational Error in Financial Service 원문보기

Journal of the convergence on culture technology : JCCT = 문화기술의 융합, v.8 no.4, 2022년, pp.445 - 455  

김환주 (연세대학교 정보대학원 UX트랙) ,  김지연 (연세대학교 정보대학원 UX트랙) ,  최준호 (연세대학교 정보대학원 UX트랙)

초록
AI-Helper 아이콘AI-Helper

금융 서비스에서 적극적으로 활용되고 있는 챗봇은 대화 오류와 기계적인 답변으로 사용자 경험을 저해하고 있다. 이 연구는 의인화된 챗봇의 자기노출과 감정표현이 금융 서비스에서 대화 오류 시 사용자 경험에 미치는 효과를 살펴보았다. 일상적인 금융 서비스 문의 상황에서 자기노출 유형(긍정적 vs. 부정적)과 감정표현 수준(높은 수준의 자신감 vs. 낮은 수준의 자신감)별로 시나리오를 구성해 온라인 실험을 진행하였고, 신뢰, 곤혹도, 서비스 회복만족, 지속 사용의도를 측정하였다. 실험 결과, 의인화된 챗봇의 자기노출과 감정표현에서 신뢰, 곤혹도, 서비스 회복만족, 지속 사용의도에 대해 각각 주효과가 나타났고 신뢰와 곤혹도에서 상호작용 효과가 나타났다. 결론적으로 의인화된 챗봇이 긍정적 자기노출과 자신감 있는 감정표현을 할 때 상대적으로 신뢰가 높아지고 곤혹도가 낮아지는 것을 확인하였다.

Abstract AI-Helper 아이콘AI-Helper

Financial service chatbots are hindering user experience with conversational errors and machine-like responses. This study aims to examine the effect of self-disclosure and emotional expression of an anthropomorphic chatbot on user experience before conversation errors occur in financial services. I...

주제어

표/그림 (7)

참고문헌 (35)

  1. Macrobill Embrain Trendmonitor, Chatbot service usage and attitude research, Research report, pp. 1-26, November 2020. 

  2. S. Lee, J. Lee, and D. Chung, "A Study on the Factors Affecting the Acceptance Intention of Chatbot Service in the Financial Industry," Korea Technology Innovation Society(KOTIS), Vol. 24, No. 5, pp. 845-869, 2021. DOI : 10.35978/jktis.2021.10.24.5.845 

  3. S. Lee and J. Yun, "A Convergence Study on Chatbot Persona and User Experience of Financial Service - Focused on Loan Service," The Korea Society of Science & Art (KSAF), Vol. 37, No. 4, pp. 257-267, 2019. DOI : 10.17548/ksaf.2019.09.30.257 

  4. Z. Ashktorab, M. Jain, Q. Vera Liao, and J. D. Weisz, "Resilient chatbots: Repair strategy preferences for conversational breakdowns," In Procedings of the 2019 CHI conference on human factors in computing systems, Paper 254, pp. 1-12, May 2019. DOI : 10.1145/3290605.3300484 

  5. A. Khurana, P. Alamzadeh, and P. K. Chilana, "ChatrEx: Designing explainable chatbot interfaces for enhancing usefulness, transparency, and trust," In 2021 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC), IEEE, pp. 1-11. October 2021. DOI : 10.1109/VL/HCC51201.2021.9576440. 

  6. D. Benner, E. Elshan, S. Schobel, and A. Janson, "What do you mean? A Review on Recovery Strategies to Overcome Conversational Breakdowns of Conversational Agents," In 42nd International Conference on Information Systems (ICIS), Austin. USA. 2021. 

  7. N. Mozafari, W. H. Weiger, and M. Hammerschmidt, "Resolving the chatbot disclosure dilemma: leveraging selective self-presentation to mitigate the negative effect of chatbot disclosure," In Proce dings of the 54th Hawaii International Conference on System Sciences, pp. 2916-2923, January, 2021. 

  8. N. Mozafari, W. H. Weiger, and M. Hammerschmidt, "Trust me, I'm a bot-repercussions of chatbot disclosure in different service frontline settings," Journal of Service Management. Vol. 33, No. 2, 2021. DOI : https://doi.org/10.1108/JOSM-10-2020-0380 

  9. G. Mark Grimes, R. M. Schuetzler, and J. S. Giboney, "Mental Models and Expectation Violations in Conversational AI Interactions," Decision Support Systems, Vol. 144, 113515, 2021. DOI : 10.1016/j.dss.2021.113515 

  10. S. Duncan Jr, "Nonverbal communication," Psychological Bulletin, Vol. 72 No. 2, pp. 118-137, 1969. DOI : 10.1037/h0027795 

  11. J. P. Laurenceau, L. F. Barrett, and P. R. Pietromonaco, "Intimacy as an interpersonal process: The importance of self-disclosure, partner disclosure, and perceived partner responsiveness in interpersonal exchanges," Journal of personality and social psychology, Vol. 74, No. 5, pp.1238-1251, 1998. DOI : 10.1037//0022-3514.74.5.1238. 

  12. L. R. Wheeles, and J. Grotz, "Conceptualization and measurement of reported self-disclosure," Human communication research, Vol. 2, No. 4, pp.338-346, 1976. DOI: 10.1111/j.1468-2958.1976.tb00494.x 

  13. J. A. Doster, and S. J. Brooks, "Interviewer disclosure modeling, information revealed, and interviewee verbal behavior," Journal of Consulting and Clinical Psychology, Vol. 42, No. 3, pp. 420-426, 1974. DOI : 10.1037/h0036618 

  14. K. W. Phillips, N. P. Rothbard, and T. L. Dumas, "To disclose or not to disclose? Status distance and self-disclosure in diverse environments," Academy of Management Review, Vol. 34. No. 4, pp. 710-732. 2009. DOI : 10.5465/AMR.2009.44886051 

  15. M. A. Hoffman, and G. P. Spencer, "Effect of interviewer self-disclosure and interviewer-subject sex pairing on perceived and actual subject behavior," Journal of Counseling Psychology, Vol. 24, No. 5, pp. 383-390, 1977. DOI : 10.1037/0022-0167.24.5.383 

  16. M. A. Hoffman-Graff, "Interviewer use of positive and negative self-disclosure and interviewer-subject sex pairing," Journal of Counseling Psychology, Vol. 24, No. 3, pp. 184-190, 1977. DOI : 10.1037/0022-0167.24.3.184 

  17. M. K. Lee, S. Kiesler, J. Forlizzi, S. Srinivasa, and P. Rybski, "Gracefully mitigating breakdowns in robotic services," In 2010 5th ACM/ IEEE International Conference on Human-Robot Interaction (HRI), IEEE, pp. 203-210, March, 2010. DOI : 10.1109/HRI.2010.5453195 

  18. A. Mehrabian, "Silent messages," Belmont, CA: Wadsworth, 1971. 

  19. J. E. Shin and J. H. Eun, "Study on Emoticon Design Elements for Emotional Communication," Korean Study of Basic Design & Art, Vol. 18, No. 6, pp. 351-362. 2017. 

  20. M. Reyes, I. Meza, and L. A. Pineda, "The positive effect of negative feedback in HRI using a facial expression robot," In International Workshop on Cultural Robotics, pp. 44-54. Springer, Cham, August, 2015. DOI : 10.1007/978-3-319-42945-8_4 

  21. J. Park and J. Joo, "A behavioral Ecoomic Approach to Increase Users' Intention to Continue to Use the Voice Recognition Speakers: Anthropomorphism," Design Convergence Study, Vol. 17, No. 3, pp. 41-53, 2018 DOI : /10.31678/sdc.70.3 

  22. S. I. Chung, and K. H. Han, "Consumer Perception of Chatbots and Purchase Intentions: Anthropomorphism and Conversational Relevance," International Journal of Advanced Culture Technology, Vol. 10, No. 1, pp. 211-229, 2022. DOI : 10.17703/IJACT.2022.10.1.211 

  23. C. H. Oh, "Artificial Intelligence Contact Center Strategy for Differentiated Customer Experience," Hankyung, 2021. Available : https://www.hankyung.com/it/article/202103315476i 

  24. S. Park, Y. Jung, and H. Kang, "Effects of Personalization and Types of Interface in Task-Oriented Chatbot," The Journal of Convergence on Culture Technology (JCCT), Vol. 7, No. 1, pp. 595-607, 2021. DOI : 10.17703/JCCT.2021.7.1.595 

  25. M. Desai, P. Kaniarasu, M. Medvedev, A. Steinfeld, and H. Yanco, "Impact of robot failures and feedback on real-time trust," In 2013 8th ACM/ IEEE International Conference on Human -Robot Interaction (HRI), pp. 251-258, IEEE, March, 2013. DOI : 10.1109/HRI.2013.6483596 

  26. M. Kim, "Effects of Nonverbal Communication in National Assembly Candidates' Broadcast Speech on Viewers Depending on Involvement - Voice, Gaze and Gesture," Master Thesis, Sogang University, 2005. 

  27. P. Ekman, and W. V. Friesen, "The Repertoire of Nonverbal Behavior: Categories, origins, usage, and coding," Semiotica, Vol. 1, No. 1, pp. 49-98, 1969. DOI : 10.1515/9783110880021.57 

  28. M. K. Lee, and H. Park, "Exploring Factors Influencing Usage Intention of Chatbot - Chatbot in Financial Service," Journal of Korean Society for Quality Management, Vol. 47, No. 4, pp. 755-765, 2019. DOI : 10.7469/JKSQM.2019.47.4.755 

  29. H. J. Gwon, and J. Y. Lee, "A Study on the Reliability of Voice Payment Interface," Journal of the Korean Society for Information Management (JKOSIM), Vol. 38, No. 3, pp. 101-140, 2021. 

  30. K. S. Hone and R. Graham, "Towards a tool for the Subjective Assessment of Speech System Interfaces (SASSI)," Natural Langague Engineering, Vol. 6, No. 3-4, pp. 287-303. 2000. DOI : https://doi.org/10.1017/S1351324900002497 

  31. A. Mahmood, J. W. Fung, I. Won, and C. M. Huang, "Owning Mistakes Sincerely: Strategies for Mitigating AI Errors," In CHI Conference on Human Factors in Computing Systems, pp. 1-11, April, 2022. DOI : 10.1145/3491102.3517565 

  32. Y. S. Kang and B. R. Choi, "Effects of Emoticons on Intention to Use in Online Financial Counseling Service: Moderating Roles of Agent Type and Subjective Financial Knowledge," The Knowledge Management Society of Korea, Vol. 20, No. 4, pp. 99-108, 2019. DOI : 10.15813/kmr.2019.20.4.006 

  33. H. Chin, and M. Y. Yi, "Voices that Care Differently: Understanding the Effectiveness of a Conversational Agent with an Alternative Empathy Orientation and Emotional Expressivity in Mitigating Verbal Abuse," International Journal of Human-Computer Interaction, Vol. 38, No. 12, pp. 1-15, 2022. DOI : 10.1080/10447318.2021.1987680 

  34. A. Cheshin, A. Rafaeli, and N. Bos, "Anger and happiness in virtual teams: Emotional influences of text and behavior on others' affect in the absence of non-verbal cues," Organizational behavior and human decision processes, Vol. 116, No. 1, pp. 2-16, 2011. DOI:10.1016/j.obhdp.2011.06.002 

  35. Makebot, "Korean Chatbot Trend Report," 2019. Available : https://brunch.co.kr/@makebotai/8 

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