Research on User Experience and Brand Attitudes of Chatbots
With the advancement of artificial intelligence technology, most companies are aware of the profound potential of artificial intelligence in commercial marketing. Man-machine dialogue has become the latest trend in marketing customer service. However, chatbots are often considered to be lack of intelligent or unfriendly conversion, which instead reduces the communication effect of chatbots. To ensure that chatbots represent the brand image and provide a good user experience, companies and users attach great importance. In this study, customer service chatbot was used as the research sample. The research variables are based on the theory of artificial intelligence emotions, integrating the technology acceptance model and innovation diffusion theory, and the three aspects of pleasure, arousal, and dominance of the human-machine PAD (Pleasure, Arousal and Dominance) dimension. The results show that most of the participants have a higher acceptance of innovative technologies and are high pleasure and arousal in the user experience. Participants still have traditional gender (female) service stereotypes about customer service chatbots. Users who have high trust in using chatbots can easily enhance brand acceptance and easily accept brand messages, extend the trust of chatbots to trust in the brand, and develop a positive attitude towards the brand.
[1] Gartner (2019). Chatbots Will Appeal to Modern Workers. https://www.gartner.com/smarterwithgartner/chatbots-will-appeal-to-modern-workers/
[2] Lin H-F. (2006). Understanding Behavioral Intention to Participate in Virtual Communities. Cyber Psychology and Behavior. 9, 540–547.
[3] Holtgraves T., Ross S. J., Weywadt C. R., Han, T. L. (2007). Perceiving artificial social agents. Computers in Human Behavior, Computers in Human Behavior 23(5), 2163-2174.
[4] Brandtzaeg, P. B., Følstad, A. (2017). Why people use chatbots. In Proceedings of the International Conference on Internet Science, 377-392, Cham, Switzerland.
[5] Bugel, M. Verhoef, P. C. & Buunk, A. P. (2011). Customer intimacy and commitment to relationships with firms in five different sectors: Preliminary evidence. Journal of Retailing and Consumer Services 18(4), 247-258.
[6] Rau, Gao, & Ding, (2008). Intimate and Friendship on Facebook: discovering Intimate on Facebook.
[7] Wickens, C., Hollands, J., Banburry, S., & Parasuraman, R. (2013). Engineering Psychology and Human Performance. New York: Pearson Education Inc.
[8] Rohm, A., Gao, T. Sultan, F. ＆ Pagani, M. (2012). Brand in the Hand: A Cross-Market Investigation of Consumer Acceptance of Mobile Marketing. Business Horizons 55(5), 485-493.
[9] Jahangir, N. & Begum, N. (2007). The Role of Perceived Usefulness, Perceived Ease of Use, Security and Privacy, And Customer Attitude to Engender Customer Adaptation In The Context Of Electronic Banking. African Journal of Business Management, 2(1), 32-40.
[10] Davis F. D. (1989). Perceived Usefulness, Perceived Ease of Use, And User Acceptance of Information Technology. MIS Quarterly, 13, 319–340.
[11] Legris, P., Ingham, J., & Collerette, P. (2003). Why Do People Use Information Technology? A Critical Review of the Technology Acceptance Model. Information and Management, 40(3), 191−204.
[12] Rogers, E.M. (2003). Diffusion of Innovations. Simon and Schuster, New York.
[13] Kulviwat S, Bruner II GC, Kumar A. (2007). Toward A Unified Theory of Consumer Acceptance Technology. Psychology and Marketing, 24, 1059–1084.
[14] Wang Z, & Scheepers H. (2012). Understanding The Intrinsic Motivations of User Acceptance of Hedonic Information Systems: Towards A Unified Research Model. Communications of the Association for Information Systems. 30, 255–274.
[15] Simpson, J. A. (2007). Psychological Foundations of Trust. Current Directions I n Psychological Science, 16(5), 264-268.
[16] Madsen, M. A. ＆ Gregor, S. (2000). Measuring Human-Computer Trust. Semantic Scholar. https://www.semanticscholar.org/paper/Measuring-Human-Computer-Trust-Madsen-Gregor/b8eda9593fbcb63b7ced1866853d9622737533a2
[17] Moray, N. Inagaki, T. & Itoh, M. (2000). Adaptive Automation, Trust, and Self-Confidence in Fault Management of Time-Critical Tasks. Journal of Experimental Psychology, 6(1), 44-45.
[18] Mayer, R. C., Davis, J. H., & Schoorman, F. D. (1995). An Integrative Model of Organizational Trust. The Academy of Management Review, 20(3), 709-734. doi:10.2307/258792
[19] Lee, J. D. & See, K. A. (2004). Trust in Automation: Designing for Appropriate Reliance. Human Factors: The Journal of Human Factors and Ergonomics Society. 50-80.
[20] Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in Online Shopping: An Integrated Model. MIS Quarterly, 27(1), 51-90. doi:10.2307/30036519
[21] Li, Y.M. Yeh, Y. S. (2010). Increasing trust in mobile commerce through design aesthetics. Computers in Human Behavior, 26, 673–684.
[22] Corritore, C. L., Kracher, B., & Wiedenbeck, S. (2003). On-line trust: Concepts, evolving themes, a model. International Journal of Human-Computer Studies, 58(6), 737-758. doi:10.1016/s1071-5819(03)00041-7
[23] Hassanein K, Head M. (2007). Manipulating Perceived Social Presence Through the Web Interface and Its Impact on Attitude Towards Online Shopping. International Journal of Human-Computer Studies, 65, 689–708.
[24] Yin D, Bond S, Zhang H. (2013). Anxious or Angry? Effects of Discrete Emotions on the Perceived Helpfulness of Online Reviews. MIS Quarterly 2013; 38:539–560.
[25] Mehrabian A., & Russell J. A. (1974) An approach to environmental psychology. Cambridge: The MIT Press.
[26] Corritore, C. L., Marble, R., Wiedenbeck, S., Kracher, B., & Chandran, A. (2005). Measuring on-line trust of websites: Credibility, perceived ease of use, and risk. Paper presented at the Americas Conference on Information Systems, Omaha, USA.
[27] Nordheim, C. B. (2018). Trust in chatbots for customer service – findings from a questionnaire study Supervisors, Master thesis at the Department of Psychology University of Oslo.
[28] Adam, M. Wessel, M. & Benlian, A. (2020). AI-based chatbots in customer service and their effects on user compliance, Electronic Markets. DOI： 10.1007/s12525-020-00414-7
[1] Gartner (2019). Chatbots Will Appeal to Modern Workers. https://www.gartner.com/smarterwithgartner/chatbots-will-appeal-to-modern-workers/
[2] Lin H-F. (2006). Understanding Behavioral Intention to Participate in Virtual Communities. Cyber Psychology and Behavior. 9, 540–547.
[3] Holtgraves T., Ross S. J., Weywadt C. R., Han, T. L. (2007). Perceiving artificial social agents. Computers in Human Behavior, Computers in Human Behavior 23(5), 2163-2174.
[4] Brandtzaeg, P. B., Følstad, A. (2017). Why people use chatbots. In Proceedings of the International Conference on Internet Science, 377-392, Cham, Switzerland.
[5] Bugel, M. Verhoef, P. C. & Buunk, A. P. (2011). Customer intimacy and commitment to relationships with firms in five different sectors: Preliminary evidence. Journal of Retailing and Consumer Services 18(4), 247-258.
[6] Rau, Gao, & Ding, (2008). Intimate and Friendship on Facebook: discovering Intimate on Facebook.
[7] Wickens, C., Hollands, J., Banburry, S., & Parasuraman, R. (2013). Engineering Psychology and Human Performance. New York: Pearson Education Inc.
[8] Rohm, A., Gao, T. Sultan, F. ＆ Pagani, M. (2012). Brand in the Hand: A Cross-Market Investigation of Consumer Acceptance of Mobile Marketing. Business Horizons 55(5), 485-493.
[9] Jahangir, N. & Begum, N. (2007). The Role of Perceived Usefulness, Perceived Ease of Use, Security and Privacy, And Customer Attitude to Engender Customer Adaptation In The Context Of Electronic Banking. African Journal of Business Management, 2(1), 32-40.
[10] Davis F. D. (1989). Perceived Usefulness, Perceived Ease of Use, And User Acceptance of Information Technology. MIS Quarterly, 13, 319–340.
[11] Legris, P., Ingham, J., & Collerette, P. (2003). Why Do People Use Information Technology? A Critical Review of the Technology Acceptance Model. Information and Management, 40(3), 191−204.
[12] Rogers, E.M. (2003). Diffusion of Innovations. Simon and Schuster, New York.
[13] Kulviwat S, Bruner II GC, Kumar A. (2007). Toward A Unified Theory of Consumer Acceptance Technology. Psychology and Marketing, 24, 1059–1084.
[14] Wang Z, & Scheepers H. (2012). Understanding The Intrinsic Motivations of User Acceptance of Hedonic Information Systems: Towards A Unified Research Model. Communications of the Association for Information Systems. 30, 255–274.
[15] Simpson, J. A. (2007). Psychological Foundations of Trust. Current Directions I n Psychological Science, 16(5), 264-268.
[16] Madsen, M. A. ＆ Gregor, S. (2000). Measuring Human-Computer Trust. Semantic Scholar. https://www.semanticscholar.org/paper/Measuring-Human-Computer-Trust-Madsen-Gregor/b8eda9593fbcb63b7ced1866853d9622737533a2
[17] Moray, N. Inagaki, T. & Itoh, M. (2000). Adaptive Automation, Trust, and Self-Confidence in Fault Management of Time-Critical Tasks. Journal of Experimental Psychology, 6(1), 44-45.
[18] Mayer, R. C., Davis, J. H., & Schoorman, F. D. (1995). An Integrative Model of Organizational Trust. The Academy of Management Review, 20(3), 709-734. doi:10.2307/258792
[19] Lee, J. D. & See, K. A. (2004). Trust in Automation: Designing for Appropriate Reliance. Human Factors: The Journal of Human Factors and Ergonomics Society. 50-80.
[20] Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in Online Shopping: An Integrated Model. MIS Quarterly, 27(1), 51-90. doi:10.2307/30036519
[21] Li, Y.M. Yeh, Y. S. (2010). Increasing trust in mobile commerce through design aesthetics. Computers in Human Behavior, 26, 673–684.
[22] Corritore, C. L., Kracher, B., & Wiedenbeck, S. (2003). On-line trust: Concepts, evolving themes, a model. International Journal of Human-Computer Studies, 58(6), 737-758. doi:10.1016/s1071-5819(03)00041-7
[23] Hassanein K, Head M. (2007). Manipulating Perceived Social Presence Through the Web Interface and Its Impact on Attitude Towards Online Shopping. International Journal of Human-Computer Studies, 65, 689–708.
[24] Yin D, Bond S, Zhang H. (2013). Anxious or Angry? Effects of Discrete Emotions on the Perceived Helpfulness of Online Reviews. MIS Quarterly 2013; 38:539–560.
[25] Mehrabian A., & Russell J. A. (1974) An approach to environmental psychology. Cambridge: The MIT Press.
[26] Corritore, C. L., Marble, R., Wiedenbeck, S., Kracher, B., & Chandran, A. (2005). Measuring on-line trust of websites: Credibility, perceived ease of use, and risk. Paper presented at the Americas Conference on Information Systems, Omaha, USA.
[27] Nordheim, C. B. (2018). Trust in chatbots for customer service – findings from a questionnaire study Supervisors, Master thesis at the Department of Psychology University of Oslo.
[28] Adam, M. Wessel, M. & Benlian, A. (2020). AI-based chatbots in customer service and their effects on user compliance, Electronic Markets. DOI： 10.1007/s12525-020-00414-7
@article{"International Journal of Business, Human and Social Sciences:80422", author = "Shu-Yin Yu", title = "Research on User Experience and Brand Attitudes of Chatbots", abstract = "With the advancement of artificial intelligence technology, most companies are aware of the profound potential of artificial intelligence in commercial marketing. Man-machine dialogue has become the latest trend in marketing customer service. However, chatbots are often considered to be lack of intelligent or unfriendly conversion, which instead reduces the communication effect of chatbots. To ensure that chatbots represent the brand image and provide a good user experience, companies and users attach great importance. In this study, customer service chatbot was used as the research sample. The research variables are based on the theory of artificial intelligence emotions, integrating the technology acceptance model and innovation diffusion theory, and the three aspects of pleasure, arousal, and dominance of the human-machine PAD (Pleasure, Arousal and Dominance) dimension. The results show that most of the participants have a higher acceptance of innovative technologies and are high pleasure and arousal in the user experience. Participants still have traditional gender (female) service stereotypes about customer service chatbots. Users who have high trust in using chatbots can easily enhance brand acceptance and easily accept brand messages, extend the trust of chatbots to trust in the brand, and develop a positive attitude towards the brand.", keywords = "Brand attitude, chatbot, emotional interaction, user experience.", volume = "15", number = "8", pages = "543-7", }
