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Research on Users’ Trust in Customer Service Chatbots Based on Human-Computer Interaction

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Big Data and Social Computing (BDSC 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1640))

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Abstract

As Human-Computer Interaction (HCI) moves towards deep collaboration, it is urgent to study users’ trust in chatbots. This study takes customer service chatbots as an example. Firstly, literature review is conducted on the relevant research on users’ trust in chatbots, and the value chain model of customer service chatbots is analyzed. Taking Taobaoxiaomi as the specific research object, we conducted in-depth interviews with 18 users, organized the interview data with value focused thinking method (VFT), constructed the users’ trust model of customer service chatbots, and carried out an empirical test by questionnaire survey. The results show that professionalism, response speed and predictability have positive effects on users’ trust in chatbots, while ease of use and human-likeness have no significant positive effects on users’ trust. Besides, brand trust has a positive impact on users’ trust in chatbots, risk perception negatively affects users’ trust in chatbots, and human support has no significant negative effect on users’ trust. Finally, privacy concerns have a moderating effect on environmental factors (brand trust, risk et al.). This study will deepen the understanding of human-computer trust and provide reference for the industry to improve chatbots and enhance users’ trust.

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References

  1. Følstad, A., Brandtzæg, P., et al.: Chatbots and the New World of HCI. Interactions 24(4), 38–42 (2017)

    Article  Google Scholar 

  2. Følstad, A., Nordheim, C.B., Bjrkli, C.A.: What makes users trust a Chatbot for customer service? an exploratory interview study. In: The Fifth International Conference on Internet Science – INSCI 2018 (2018). https://doi.org/10.1007/978-3-030-01437-7_16

  3. Grand View Research. Chatbot Market Size Worth $2,485.7 Million By 2028 | CAGR: 24.9%. https://www.grandviewresearch.com/press-release/global–chatbot—market, 2021–4/ 2021–5–29

    Google Scholar 

  4. Thompson, C.: May A.I. help you? New York Times (November 18). https://www.nytimes.com/interactive/2018/11/14/magazine/tech-design-ai-chatbot.html

  5. Luo, X., Tong, S., Fang, Z., et al.: Frontiers: machines vs. humans: the impact of artificial intelligence Chatbot disclosure on customer purchases. Mark. Sci. 38(6), 937--947 (2019)

    Google Scholar 

  6. Wilson, H.J., Daugherty, P.R., Morini-Bianzino, N.: The jobs that artificial intelligence will create. MIT Sloan Manage. Rev. 58(4), 14 (2017)

    Google Scholar 

  7. Froehlich A. Pros and cons of chatbots in the IT helpdesk. Informationweek.com. https://www.informationweek.com/strategic-cio/it-strategy/pros-and-cons-of-chatbots-in-the-it-helpdesk/a/d-id/1332942. Accessed 18 Oct 2018

  8. Dietvorst, B.J., Simmons, J.P., Massey, C.: Overcoming algorithm aversion: people will use imperfect algorithms if they can (even slightly) modify them. Manage. Sci. 64(3), 1155–1170 (2018)

    Article  Google Scholar 

  9. Kestenbaum, R.: Conversational commerce is where online shopping was 15 years ago —Can it also become ubiquitous? Forbes(June 27). https://www.forbes.com/sites/Richard%20Kestenbaum/2018/06/27/shopping-by-voice-is-small-now-but-it-has-huge-potential/?sh=40e52c907ba1

  10. Evert, V., Zarouali, B., Poels, K.: Chatbot advertising effectiveness: when does the message get through? Comput. Hum. Behav. 98, 150–157 (2019)

    Article  Google Scholar 

  11. Corritore, C.L., Kracher, B., Wiedenbeck, S.: On-line trust: concepts, evolving themes, a model. Int. J. Hum. Comput. Stud. 58(6), 737–758 (2003)

    Article  Google Scholar 

  12. Rotter, J.B.: A new scale for the measurement of interpersonal trust. J. Pers. 35(4), 651–665 (2010)

    Google Scholar 

  13. Arrow, K.E.: The Limits of Organization. Norton, Tempe (1974)

    Google Scholar 

  14. Baker, A.L., Phillips, E.K., Ullman, D., et al.: Toward an understanding of trust repair in human-robot interaction: current research and future directions. ACM Trans. Interact. Intell. Syst. 8(4), 1–30 (2018)

    Article  Google Scholar 

  15. Mayer, R.C., Davis, J.H., Schoorman, F.D.: An integrative model of organizational trust. Acad. Manag. Rev. 20(3), 709–734 (1995)

    Article  Google Scholar 

  16. Rousseau, D.M., Sitkin, S.B., Burt, R.S., et al.: Not so different after all: a cross-discipline view of trust. Acad. Manag. Rev. 23(3), 393–404 (1998)

    Article  Google Scholar 

  17. Glikson, E., Woolley, A.W.: Human trust in artificial intelligence: review of empirical research. Acad. Manag. Ann. 14(2), 627–660 (2020)

    Article  Google Scholar 

  18. Coeckel bergh, M.: Can we trust robots?. Ethics Inf. Technol. 14(1), 53--60 (2012)

    Google Scholar 

  19. Desai, M., Stubbs, K., Steinfeld, A., et al.: Creating Trustworthy Robots: Lessons and Inspirations from Automated Systems (2009)

    Google Scholar 

  20. Hancock, P.A., Billings, D.R., Schaefer, K.E., et al.: A meta-analysis of factors affecting trust in human-robot interaction. Hum. Factors 53(5), 517–527 (2011)

    Article  Google Scholar 

  21. Nordheim, C.B.: Trust in Chatbots for customer service–findings from a questionnaire study (2018)

    Google Scholar 

  22. Ho, C.C., Macdorman, K.F.: Revisiting the uncanny valley theory: developing and validating an alternative to the godspeed indices. Comput. Hum. Behav. 26(6), 1508–1518 (2010)

    Article  Google Scholar 

  23. Mcknight, D.H., Carter, M., Thatcher, J.B., et al.: Trust in a specific technology: an investigation of its components and measures. ACM Trans. Manag. Inf. Syst. 2(2), 12 (2011)

    Article  Google Scholar 

  24. Bertinussen, N.C., Asbjrn, F., Alexander, B.C.: An initial model of trust in Chatbots for customer service—findings from a questionnaire study. Interact. Comput. 31(3), 317—335 (2019)

    Google Scholar 

  25. Keeney, R.L.: Value-focused thinking : a path to creative decisionmaking (1992)

    Google Scholar 

  26. Keeney, R.L.: Creativity in MS/OR: value-focused thinking—creativity directed toward decision making. Interfaces 23(3), 62–67 (1993)

    Article  Google Scholar 

  27. Mcknight, D.H., Choudhury, V., Kacmar, C.: Developing and validating trust measures for e-commerce: an integrative typology. Inf. Syst. Res. 13(3), 344–359 (2002)

    Article  Google Scholar 

  28. Drevin, L., Kruger, H.A., Steyn, T.: Value-focused assessment of ICT security awareness in an academic environment. Comput. Secur. 26(1), 36–43 (2007)

    Article  Google Scholar 

  29. Deng, C.H., Lu, Y.B.: Research on VFT-based trust construction framework for mobile commerce. Sci. Technol. Manag. Res. 03, 185–188 (2008)

    Google Scholar 

  30. Keeney, R.L.: Value-focused Thinking. Harvard University Press, Cambridge (1992)

    MATH  Google Scholar 

  31. Sheng, H., Nah, F.H., Siau, K.: Strategic implications of mobile technology: a case study using value-focused thinking. J. Strateg. Inf. Syst. 14(3), 269–290 (2005)

    Article  Google Scholar 

  32. Lin, H., et al.: An empirical study on the difference of influencing factors between trust and distrust in consumers’ first online shopping. Mod. Inf. 35(4), 5 (2015)

    Google Scholar 

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Acknowledgments

This work is supported by 2019, Digital Transformation in China and Germany: Strategies, Structures and Solutions for Ageing Societies, GZ 1570. Also supported by the Research Project of Shanghai Science and Technology Commission (No.20dz2260300) and The Fundamental Research Funds for the Central Universities.

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Correspondence to Feng Liu or Jiayin Qi .

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Lv, Y., Hu, S., Liu, F., Qi, J. (2022). Research on Users’ Trust in Customer Service Chatbots Based on Human-Computer Interaction. In: Meng, X., Xuan, Q., Yang, Y., Yue, Y., Zhang, ZK. (eds) Big Data and Social Computing. BDSC 2022. Communications in Computer and Information Science, vol 1640. Springer, Singapore. https://doi.org/10.1007/978-981-19-7532-5_19

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  • DOI: https://doi.org/10.1007/978-981-19-7532-5_19

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