“Your conversational partner is a chatbot” An Experimental Study on the Influence of Chatbot Disclosure and Service Outcome on Trust and Customer Retention in the Fashion Industry
Main Article Content
Keywords
Chatbot, Customer retention, Identity disclosure, Service outcome, Trust
Abstract
Should companies disclose their chatbots’ nonhuman identity or not? Previous studies have found both negative and positive consumer reactions to chatbot disclosure. This experimental study explores how trust and customer retention change when the nonhuman identity of the chatbot is revealed and when different service outcomes apply in the context of the German fashion industry. The results of this experiment provide evidence that disclosing chatbot identity influences neither trust nor customer retention, but service outcome has an effect on both. Companies should therefore focus on developing a functional customer service as chatbot failure has tremendous consequences for the volume of reliable customers and profits. The main limitation of this study is that the respondents were only shown screenshots, leaving the impact of a real interaction with chatbots undiscovered.
References
[1] Blut, M., Wang, C., Wünderlich, N. V.; Brock, C. (2021): Understanding anthropomor-phism in service provision: a meta-analysis of physical robots, chatbots, and other AI. In: Journal of the Academy of Marketing Science, pp. 632–658.
[2] Luo, X., Tong, S., Fang, Z.; Qu, Z. (2019): Frontiers: Machines vs. Humans: The Impact of Artificial Intelligence Chatbot Disclosure on
Customer Purchases. In: Marketing Science, vol. 38 (6), pp. 937-947.
[3] Mozafari, N., Weiger, W. H.; Hammerschmidt, M. (2021b): Trust me, I’m a bot – repercussions of chatbot disclosure in different service frontline settings. In: Journal of Service Management, vol. 33 (2), pp. 221-245.
[4] Belanche, D., Casaló, L. V., Flavián, C.; Schepers, J. (2020): Robots or frontline employees? Exploring customers’ attributions of
responsibility and stability after service failure or success. In: Journal of Service Management, pp. 267–289.
[5] Chizhik, A.; Zherebtsova, Y. (2020): Challenges of Building an Intelligent Chatbot, Proceedings of the International Conference” Internet and Modern Society“(IMS-2020).
[6] Adam, M., Wessel, M.;Benlian, A. (2021): AI-based chatbots in customer service and their effects on user compliance, in: Electronic
Markets, vol. 31, (2), pp. 427–445.
[7] Pesaran, H. (2003): Introducing a replication section. In: Journal of Applied Econometrics (1), pp. 111.
[8] Følstad, A., Nordheim, C. B.; Bjørkli, C. A. (2019): What Makes Users Trust a Chatbot for Customer Service? An Exploratory Interview
Study. In: Internet Science: 5th International Conference, vol. 2019, pp. 194–208.
[9] Ranaweera, C.; Prabhu, J. (2003): On the relative importance of customer satisfaction and trust as determinants of customer retention and positive word of mouth. In: Journal of Targeting, Measurement and Analysis for Marketing, vol. 12, pp. 82-90.
[10] Weiner, B. (2000): Attributional Thoughts about Customer Behaviour. In: Journal of Consumer Research, vol. 27 (3), pp. 382-387.
[11] Grewal, D., Roggeveen, A. L.; Nordfält, J. (2017): The Future of Retailing. In: Journal of Retailing (1), p. 1–6.
[12] Luce, L. (2019): Artificial Intelligence for Fashion. How AI is Revolutionizing the Fashion Industry, New York: Apress.
[13] Silvestri, B. (2020): The Future of Fashion: How the Quest for Digitization and the Use of Artificial Intelligence and Extended Reality Will Reshape the Fashion Industry After COVID-19. In: ZoneModa Journal, 10 (2), pp. 61-73.
[14] McKinsey & Company (2020): The State of Fashion 2021. Avialable at: https://www.mckinsey.com/~/media/mckinsey/industries/
retail/our%20insights/state%20of%20fashion/2021/the-state-of-fashion-2021-vf.pdf [Accessed: 23 August 2022].
[15] Hyken, S. (2017): AI And Chatbots Are Transforming The Customer Experience [Online]. Available at https://www.forbes.com/sites/shephyken/2017/07/15/ai-andchatbots-are-transforming-the-customerexperience/?sh=71bbe5ad41f7 [Accessed:19 December 2021].
[16] Candello, H., Pinhanez, C.; Figueiredo, F. (2017): Typefaces and the Perception of Humanness in Natural Language Chatbots, CHI
‘17: Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, pp.3476–3487.
[17] Skjuve, M., Haugstveit, I. M., Følstad, A.; Brandtzaeg, P. B. (2019): Help! Is my chatbot falling into the uncanny valley? An empirical
study of user experience in human-chatbot interaction. In: Human Technology, pp. 30–54.
[18] Corti, K.; Gillespie, A. (2016): Co-constructing intersubjectivity with artificial conversational agents: People are more likely to initiate repairs of misunderstandings with agents represented as human. In: Computers in Human Behavior, vol. 58, pp. 431–442.
[19] Hendriks, F., Ou, C. X.J., Khodabandeh Amiri, A.; Bockting, S. (2020): The Power of Computer-Mediated Communication Theories
in Explaining the Effect of Chatbot Introduction on User Experience, Proceedings of the 53 Hawaii International Conference on System
Sciences.
[20] Rai, A. K.; Srivastava, M. (2014): Customer Loyalty: Concept, Context and Character. New York: McGraw Hill.
[21] Chen, J. V., Thi Le, H.; Tran, S. T. T. (2021): Understanding automated conversational agent as a decision aid: matching agent’s conversation with customer’s shopping task. In: Internet Research (4), pp. 1376–1404.
[22] Komiak, S.X., Benbasat, I. (2004), Understanding customer trust in agent-mediated electronic commerce, web-mediated electronic
commerce, and traditional commerce. In: Information Technology and Management, Vol. 5 No. ½, pp. 181-207.
[23] Siau, K.; Wang, W. (2018): Building Trust in Artificial Intelligence, Machine Learning, and Robotics. In: Cutter Business Technology
Journal, vol. 31 (2), pp. 47-53.
[24] Ameen, N., Tarhini, A., Reppel, A.; Anand, A. (2021): Customer experiences in the age of artificial intelligence. In: Computers in human behavior, vol. 114.
[25] Jin, R. (2010): Causal Attributions on Service Outcomes by Self-Service Technology Users, Purdue University.
[26] Kanazawa, S. (1992): Outcome or Expectancy? Antecedent of Spontaneous Causal Attribution. In: Personality and Social Psychology Bulletin, vol. 18 (6), pp. 659–668.
[27] van Vaerenbergh, Y., Orsingher, C., Vermeir, I.; Larivière, B. (2014): A Meta-Analysis of Relationships Linking Service Failure
Attributions to Customer Outcomes. In: Journal of Service Research, pp. 381–398.
[28] Gelbrich, K. (2010): Anger, frustration, and helplessness after service failure: coping strategies and effective informational support. In: Journal of the Academy of Marketing Science, pp. 567–585.
[29] Kumar, V., Bhagwat, Y.; Zhang, X. (2015): Regaining “Lost” Customers: The Predictive Power of First-Lifetime Behavior, the Reason
for Defection, and the Nature of the Win-Back Offer. In: Journal of Marketing, pp. 34–55.
[30] Silitonga, K. A. A., Ikhsan, R. B.; Fakhrorazi, A. (2020): Drivers of buyer retention in e-commerce: The role of transaction
characteristics and trust. In: Management Science Letters, pp. 3485–3494.
[31] Pidas AG (2018): Chatbot-Studie – Die digitalen Helfer im Praxistest. Available at: https://cdn2.hubspot.net/hubfs/5893787/
PIDAS_ZHAW_Chatbot_Studie_FINAL.pdf.
[32] Bhattacherjee, B. (2002): Individual Trust in Online Firms: Scale Development and Initial Test. In: Journal of Management Information Systems, pp. 211–241.
[2] Luo, X., Tong, S., Fang, Z.; Qu, Z. (2019): Frontiers: Machines vs. Humans: The Impact of Artificial Intelligence Chatbot Disclosure on
Customer Purchases. In: Marketing Science, vol. 38 (6), pp. 937-947.
[3] Mozafari, N., Weiger, W. H.; Hammerschmidt, M. (2021b): Trust me, I’m a bot – repercussions of chatbot disclosure in different service frontline settings. In: Journal of Service Management, vol. 33 (2), pp. 221-245.
[4] Belanche, D., Casaló, L. V., Flavián, C.; Schepers, J. (2020): Robots or frontline employees? Exploring customers’ attributions of
responsibility and stability after service failure or success. In: Journal of Service Management, pp. 267–289.
[5] Chizhik, A.; Zherebtsova, Y. (2020): Challenges of Building an Intelligent Chatbot, Proceedings of the International Conference” Internet and Modern Society“(IMS-2020).
[6] Adam, M., Wessel, M.;Benlian, A. (2021): AI-based chatbots in customer service and their effects on user compliance, in: Electronic
Markets, vol. 31, (2), pp. 427–445.
[7] Pesaran, H. (2003): Introducing a replication section. In: Journal of Applied Econometrics (1), pp. 111.
[8] Følstad, A., Nordheim, C. B.; Bjørkli, C. A. (2019): What Makes Users Trust a Chatbot for Customer Service? An Exploratory Interview
Study. In: Internet Science: 5th International Conference, vol. 2019, pp. 194–208.
[9] Ranaweera, C.; Prabhu, J. (2003): On the relative importance of customer satisfaction and trust as determinants of customer retention and positive word of mouth. In: Journal of Targeting, Measurement and Analysis for Marketing, vol. 12, pp. 82-90.
[10] Weiner, B. (2000): Attributional Thoughts about Customer Behaviour. In: Journal of Consumer Research, vol. 27 (3), pp. 382-387.
[11] Grewal, D., Roggeveen, A. L.; Nordfält, J. (2017): The Future of Retailing. In: Journal of Retailing (1), p. 1–6.
[12] Luce, L. (2019): Artificial Intelligence for Fashion. How AI is Revolutionizing the Fashion Industry, New York: Apress.
[13] Silvestri, B. (2020): The Future of Fashion: How the Quest for Digitization and the Use of Artificial Intelligence and Extended Reality Will Reshape the Fashion Industry After COVID-19. In: ZoneModa Journal, 10 (2), pp. 61-73.
[14] McKinsey & Company (2020): The State of Fashion 2021. Avialable at: https://www.mckinsey.com/~/media/mckinsey/industries/
retail/our%20insights/state%20of%20fashion/2021/the-state-of-fashion-2021-vf.pdf [Accessed: 23 August 2022].
[15] Hyken, S. (2017): AI And Chatbots Are Transforming The Customer Experience [Online]. Available at https://www.forbes.com/sites/shephyken/2017/07/15/ai-andchatbots-are-transforming-the-customerexperience/?sh=71bbe5ad41f7 [Accessed:19 December 2021].
[16] Candello, H., Pinhanez, C.; Figueiredo, F. (2017): Typefaces and the Perception of Humanness in Natural Language Chatbots, CHI
‘17: Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, pp.3476–3487.
[17] Skjuve, M., Haugstveit, I. M., Følstad, A.; Brandtzaeg, P. B. (2019): Help! Is my chatbot falling into the uncanny valley? An empirical
study of user experience in human-chatbot interaction. In: Human Technology, pp. 30–54.
[18] Corti, K.; Gillespie, A. (2016): Co-constructing intersubjectivity with artificial conversational agents: People are more likely to initiate repairs of misunderstandings with agents represented as human. In: Computers in Human Behavior, vol. 58, pp. 431–442.
[19] Hendriks, F., Ou, C. X.J., Khodabandeh Amiri, A.; Bockting, S. (2020): The Power of Computer-Mediated Communication Theories
in Explaining the Effect of Chatbot Introduction on User Experience, Proceedings of the 53 Hawaii International Conference on System
Sciences.
[20] Rai, A. K.; Srivastava, M. (2014): Customer Loyalty: Concept, Context and Character. New York: McGraw Hill.
[21] Chen, J. V., Thi Le, H.; Tran, S. T. T. (2021): Understanding automated conversational agent as a decision aid: matching agent’s conversation with customer’s shopping task. In: Internet Research (4), pp. 1376–1404.
[22] Komiak, S.X., Benbasat, I. (2004), Understanding customer trust in agent-mediated electronic commerce, web-mediated electronic
commerce, and traditional commerce. In: Information Technology and Management, Vol. 5 No. ½, pp. 181-207.
[23] Siau, K.; Wang, W. (2018): Building Trust in Artificial Intelligence, Machine Learning, and Robotics. In: Cutter Business Technology
Journal, vol. 31 (2), pp. 47-53.
[24] Ameen, N., Tarhini, A., Reppel, A.; Anand, A. (2021): Customer experiences in the age of artificial intelligence. In: Computers in human behavior, vol. 114.
[25] Jin, R. (2010): Causal Attributions on Service Outcomes by Self-Service Technology Users, Purdue University.
[26] Kanazawa, S. (1992): Outcome or Expectancy? Antecedent of Spontaneous Causal Attribution. In: Personality and Social Psychology Bulletin, vol. 18 (6), pp. 659–668.
[27] van Vaerenbergh, Y., Orsingher, C., Vermeir, I.; Larivière, B. (2014): A Meta-Analysis of Relationships Linking Service Failure
Attributions to Customer Outcomes. In: Journal of Service Research, pp. 381–398.
[28] Gelbrich, K. (2010): Anger, frustration, and helplessness after service failure: coping strategies and effective informational support. In: Journal of the Academy of Marketing Science, pp. 567–585.
[29] Kumar, V., Bhagwat, Y.; Zhang, X. (2015): Regaining “Lost” Customers: The Predictive Power of First-Lifetime Behavior, the Reason
for Defection, and the Nature of the Win-Back Offer. In: Journal of Marketing, pp. 34–55.
[30] Silitonga, K. A. A., Ikhsan, R. B.; Fakhrorazi, A. (2020): Drivers of buyer retention in e-commerce: The role of transaction
characteristics and trust. In: Management Science Letters, pp. 3485–3494.
[31] Pidas AG (2018): Chatbot-Studie – Die digitalen Helfer im Praxistest. Available at: https://cdn2.hubspot.net/hubfs/5893787/
PIDAS_ZHAW_Chatbot_Studie_FINAL.pdf.
[32] Bhattacherjee, B. (2002): Individual Trust in Online Firms: Scale Development and Initial Test. In: Journal of Management Information Systems, pp. 211–241.
Article Sidebar
Published
Mar 20, 2023
Section
Article
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
How to Cite
“Your conversational partner is a chatbot”: An Experimental Study on the Influence of Chatbot Disclosure and Service Outcome on Trust and Customer Retention in the Fashion Industry. (2023). Journal of Applied Interdisciplinary Research, 1, 10-27. https://doi.org/10.25929/jair.v1i1.113