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In bot we trust: A new methodology of chatbot performance measures

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  • Przegalinska, Aleksandra
  • Ciechanowski, Leon
  • Stroz, Anna
  • Gloor, Peter
  • Mazurek, Grzegorz

Abstract

Chatbots are used frequently in business to facilitate various processes, particularly those related to customer service and personalization. In this article, we propose novel methods of tracking human-chatbot interactions and measuring chatbot performance that take into consideration ethical concerns, particularly trust. Our proposed methodology links neuroscientific methods, text mining, and machine learning. We argue that trust is the focal point of successful human-chatbot interaction and assess how trust as a relevant category is being redefined with the advent of deep learning supported chatbots. We propose a novel method of analyzing the content of messages produced in human-chatbot interactions, using the Condor Tribefinder system we developed for text mining that is based on a machine learning classification engine. Our results will help build better social bots for interaction in business or commercial environments.

Suggested Citation

  • Przegalinska, Aleksandra & Ciechanowski, Leon & Stroz, Anna & Gloor, Peter & Mazurek, Grzegorz, 2019. "In bot we trust: A new methodology of chatbot performance measures," Business Horizons, Elsevier, vol. 62(6), pages 785-797.
    • Handle: RePEc:eee:bushor:v:62:y:2019:i:6:p:785-797
    DOI: 10.1016/j.bushor.2019.08.005
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    References listed on IDEAS

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    1. Yuehuan He & Oleksandr Romanko & Alina Sienkiewicz & Robert Seidman & Roy Kwon, 2021. "Cognitive User Interface for Portfolio Optimization," JRFM, MDPI, vol. 14(4), pages 1-15, April.
    2. Tao Zhang & Chao Feng & Hui Chen & Junjie Xian, 2022. "Calming the customers by AI: Investigating the role of chatbot acting-cute strategies in soothing negative customer emotions," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(4), pages 2277-2292, December.
    3. Massaro, Alessandro & Magaletti, Nicola & Cosoli, Gabriele & Giardinelli, Vito O. M. & Leogrande, Angelo, 2022. "Text Mining Approaches Oriented on Customer Care Efficiency," MPRA Paper 112300, University Library of Munich, Germany.
    4. Gkinko, Lorentsa & Elbanna, Amany, 2023. "Designing trust: The formation of employees’ trust in conversational AI in the digital workplace," Journal of Business Research, Elsevier, vol. 158(C).
    5. Kamoonpuri, Sana Zehra & Sengar, Anita, 2023. "Hi, May AI help you? An analysis of the barriers impeding the implementation and use of artificial intelligence-enabled virtual assistants in retail," Journal of Retailing and Consumer Services, Elsevier, vol. 72(C).
    6. James Lappeman & Siddeeqah Marlie & Tamryn Johnson & Sloane Poggenpoel, 2023. "Trust and digital privacy: willingness to disclose personal information to banking chatbot services," Journal of Financial Services Marketing, Palgrave Macmillan, vol. 28(2), pages 337-357, June.
    7. Tran, Anh D. & Pallant, Jason I. & Johnson, Lester W., 2021. "Exploring the impact of chatbots on consumer sentiment and expectations in retail," Journal of Retailing and Consumer Services, Elsevier, vol. 63(C).
    8. Dung Minh Nguyen & Yen-Ting Helena Chiu & Huy Duc Le, 2021. "Determinants of Continuance Intention towards Banks’ Chatbot Services in Vietnam: A Necessity for Sustainable Development," Sustainability, MDPI, vol. 13(14), pages 1-24, July.
    9. Na Cai & Shuhong Gao & Jinzhe Yan, 2024. "How the communication style of chatbots influences consumers’ satisfaction, trust, and engagement in the context of service failure," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-11, December.
    10. Huang, Yu-Shan (Sandy) & Dootson, Paula, 2022. "Chatbots and service failure: When does it lead to customer aggression," Journal of Retailing and Consumer Services, Elsevier, vol. 68(C).
    11. Sewoong Hwang & Jonghyuk Kim, 2021. "Toward a Chatbot for Financial Sustainability," Sustainability, MDPI, vol. 13(6), pages 1-18, March.
    12. Mark Anthony Camilleri & Ciro Troise, 2023. "Live support by chatbots with artificial intelligence: A future research agenda," Service Business, Springer;Pan-Pacific Business Association, vol. 17(1), pages 61-80, March.
    13. Le, Hoang Tran Phuoc Mai & Park, Jungkun & Lee, Sangwoo, 2023. "Emotion and trust in virtual service assistant design for effective service recovery," Journal of Retailing and Consumer Services, Elsevier, vol. 74(C).
    14. Ciechanowski, Leon & Jemielniak, Dariusz & Gloor, Peter A., 2020. "TUTORIAL: AI research without coding: The art of fighting without fighting: Data science for qualitative researchers," Journal of Business Research, Elsevier, vol. 117(C), pages 322-330.
    15. Mahendar Goli & Anoop Kumar Sahu & Surajit Bag & Pavitra Dhamija, 2023. "Users' Acceptance of Artificial Intelligence-Based Chatbots: An Empirical Study," International Journal of Technology and Human Interaction (IJTHI), IGI Global, vol. 19(1), pages 1-18, January.
    16. Hossein Hassani & Xu Huang & Emmanuel Silva & Mansi Ghodsi, 2020. "Deep Learning and Implementations in Banking," Annals of Data Science, Springer, vol. 7(3), pages 433-446, September.
    17. Liu, Wenlong & Jiang, Min & Li, Wangjie & Mou, Jian, 2024. "How does the anthropomorphism of AI chatbots facilitate users' reuse intention in online health consultation services? The moderating role of disease severity," Technological Forecasting and Social Change, Elsevier, vol. 203(C).
    18. Massilva Dekkal & Manon Arcand & Sandrine Prom Tep & Lova Rajaobelina & Line Ricard, 2024. "Factors affecting user trust and intention in adopting chatbots: the moderating role of technology anxiety in insurtech," Journal of Financial Services Marketing, Palgrave Macmillan, vol. 29(3), pages 699-728, September.

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