Examining the relationship between consumer innovativeness and trust in chatbot applications: A study on Turkish banking sector

Yıl 2022, Sayı: 63, 59 - 85, 30.12.2022

Sevda Deneçli , Öykü Yıldız , Ceyda Deneçli

https://doi.org/10.26650/CONNECTIST2022-1171397

Öz

Life has transformed rapidly with technology taking on a dominant position in our time. The developments in the field of the internet and the point that web technology has reached has created radical changes in the way of life of today’s individuals. Businesses also benefit from the opportunities that technology had provided them in how they reach their consumers. Businesses are using these technologies more and more every day to reach consumers who are constantly open to interaction thanks to technological tools. This is especially true in the service sector and e-commerce sites, where the effects of the digital transformation in banking are seen more clearly. Banks have started to use artificial intelligence-based robots in the customer relations process. In the present study, the general development of artificial intelligence-based chatbots was examined and their use in the rapidly digitalizing banking field was discussed. In this context, the approaches of innovative consumers to chatbot applications of banks were evaluated. The research was carried out on 407 people who were reached by convenience sampling method, using a questionnaire as a data collection method. However, since 13 people stated that they do not use internet or mobile banking, the analyzes were carried out on the answers of 394 participants. A correlation analysis was conducted to reveal whether the innovativeness level of consumers is related to their trust in chatbot applications. The research results show that there is no significant relationship between the “competence dimension” (r=0.06; p<0,01) and “benevolence dimension” (r=0.06; p<0,01) of consumer trust towards chatbot applications and consumer innovativeness; however, study revealed that there is a significant relationship between the “integrity dimension” (r=0.17; p<0,01) of trust and consumer innovativeness.

Anahtar Kelimeler

Artificial intelligence, chatbot, digitalization, innovative consumer, consumer cxperience

Tüketici yenilikçiliği ve chatbot uygulamalarına güven arasındaki ilişkinin incelenmesi: Türk bankacılık sektörü üzerine bir araştırma

Öz

Teknolojinin çağımızda başat bir konuma gelmesiyle birlikte yaşam hızlı bir biçimde dönüşmüştür. Özellikle internet alanındaki gelişmeler, web teknolojisinin geldiği nokta günümüz bireylerin yaşayış biçiminde köklü değişiklikler yaratmıştır. İşletmeler de tüketicilerine ulaşırken teknolojinin söz konusu olanaklarından yararlanmaktadır. İşletmeler, teknolojik araçlar sayesinde, sürekli etkileşime açık tüketicilere ulaşmak için hergeçen gün bu teknolojilere daha fazla başvurmaktadır. Özellikle de hizmet sektöründe; e-ticaret sitelerinde, bankacılık alanında dijital dönüşümün etkileri daha net bir biçimde görülmektedir. Bankalar yapay zekâ temelli bu robotları günümüzde müşteri ilişkileri sürecinde kullanmaya başlamıştır. Çalışmada, yapay zekâ temelli sohbet robotlarının genel olarak gelişimi irdelenerek, hızla dijitalleşen bankacılık alanında kullanımı ele alınmıştır. Bu bağlamda çalışmada yenilikçi tüketicilerin bankaların sohbet robotu uygulamalarınabyaklaşımları değerlendirilmiştir. Araştırma, veri toplama yöntemi olarak anket kullanılarak kolayda örnekleme yöntemiyle ulaşılmış 407 kişi üzerinde gerçekleştirilmiştir. Ancak 13 kişi internet ya da mobil bankacılık kullanmadığını belirttiğinden analizler 394 katılımcının cevapları üzerinden gerçekleştirilmiştir. Tüketicilerin yenilikçilik seviyelerinin Chatbot uygulamalarına duydukları güven ile ilişkili olup olmadığını ortaya koymak amacıyla korelasyon analizi gerçekleştirilmiştir. Araştırma sonuçları chatbot uygulamalarına yönelik tüketici güveninin ‘yetkinlik boyutu’ (r=0.06; p<0,01) ve ‘yardım boyutu’ (r=0.06; p<0,01)ile tüketici yenilikçiliği ile arasında anlamlı bir ilişki olmadığını; ancak güvenin ‘doğruluk boyutu’ (r=0.17; p<0,01) ile tüketici yenilikçiliği arasında anlamlı bir ilişki olduğunu ortaya koymuştur.

Anahtar Kelimeler

Yapay zekâ, chatbot, dijitalleşme, yenilikçi tüketici, tüketici deneyimi

Kaynakça

• Adamopoulou, E. and Moussiades, L. (2020). An Overview of Chatbot Technology, IFIP International Federation for Information Processing, Maglogiannis et al. (Eds.): AIAI 2020, IFIP AICT 584, pp. 373–383, Springer: Switzerland. DOI:10.1007/978-3-030-49186-4_31
• Barış, A. (2020). A New Business Marketing Tool: Chatbot, GSI Journals Serie B: Advancements in Business and Economics, 3(1): 31-46. https://doi.org/10.5281/zenodo.4030216
• Bass, F.M. (1969) A New Product Growth Model for Consumer Durables. Management Science, 15, 215-227. Bilgici Oğuz, C. (2019). Sosyal Medya, Büyük Veri ve Yapay Zekanın Dijital Halkla İlişkilerdeki Rolü, (pp. 117- 140), In ed. Elif Başak Sarıoğlu, Dijital Halkla İlişkiler, Eğitim Yayınevi.
• Bowen, E. K. ve M. K. Starr.(1994). Basic Statistics for Business and Economics, McGraw Hill, s.372.
• Brill, T. M., Munoz, L. and Miller, R. J. (2019). Siri, Alexa, and other digital assistants: a study of customer satisfaction with artificial intelligence applications, Journal of Marketing Management, 1401-1436. https://doi. org/10.1080/0267257X.2019.1687571
• Büyüköztürk, Ş. (2006). Sosyal Bilimler İçin Veri Analizi El Kitabı. 6th Edition. İstanbul: Pegem Publications.
• Chung, M., Ko, E., Joung, H. and Kim, S.J. (2020). Chatbot e-service and customer satisfaction regarding luxury brands, Journal of Business Research, 117, 587-595. https://doi.org/10.1016/j.jbusres.2018.10.004
• Cui, L., Huang, S., Wei, F., Tan, C., Duan, C. and Zhou, M. (2017). SuperAgent: A Customer Service Chatbot for E-commerce Websites, Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics-System Demonstrations, 97–102 Vancouver, Canada, July 30 - August 4, 2017.
• Dahiya, M. (2017). A Tool of Conversation: Chatbot, International Journal of Computer Sciences and Engineering,5(5), 158-161.
• Davis, J. J., (1997). Advertising Research: Theory and Practice. New Jersey: Prentice Hall.
• Donepudi, P. K. (2017). Machine Learning and Artificial Intelligence in Banking, Engineering International, 5(2), 83-86. https://doi.org/10.18034/ei.v5i2.490
• Eren, B.A. (2021). Determinants of customer satisfaction in chatbot use: evidence from a banking application in Turkey, International Journal of Bank Marketing, 294-311.
• Gonçalves, G. S., Ribeiro, T. de L. S., Teixeira, J. E. V. and Costa, B. K. (2022). The deployment of chatbot to improve customer service in higher education institutions during COVID-19. International Journal of Innovation - IJI, São Paulo, 10(1), 178-203.
• Hwang, S. and Kim, J. (2021). Toward a Chatbot for Financial Sustainability, Sustainability 2021, 13, 1-18. https:// doi.org/10.3390/su13063173
• Ischen, C., Arajuo, T., Voorveld, H., Noort, G. and Smit, E. (2020). Privacy Concerns in Chatbot Interactions, (pp.34-48). In, eds. Asbjørn Følstad, Theo Araujo, Symeon Papadopoulos, Effie Lai-Chong Law, Ole-Christoffer Granmo, Ewa Luger, Petter Bae Brandtzaeg, Chatbot Research and Design: Third International Workshop, CONVERSATIONS 2019 Amsterdam, The Netherlands, November 19–20, 2019, Revised Selected Papers, Switzerland: Springer.
• İşeri, İ., Aydın, Ö. & Tutuk, K. (2021). Müşteri Hizmetleri Yönetiminde Yapay Zekâ Temelli Chatbot Geliştirilmesi, Avrupa Bilim ve Teknoloji Dergisi Özel Sayı 29, 358-365. https://doi.org/10.31590/ejosat.1025380.
• Joshi, H. (2021). Perception and Adoption of Customer Service Chatbots Among Millennials: An Empirical Validation in the Indian Context; 17th International Conference on Web Information Systems and Technologies (WEBIST 2021),197-208. 197 International Management Institute, New Delhi, India. DOI: 10.5220/0010718400003058
• Kasilingam, D.L. (2020), Understanding the attitude and intention to use smartphone chatbots for shopping. Technology in Society. 62.1-15. https://doi.org/10.1016/j.techsoc.2020.101280
• Kerly, A. Hall, P. and Bull, S. (2006). “Bring chatbots into education: Towards natural language negotiation of open learner models,” Knowledge-based Systems,. 20,177-185. https://doi.org/10.1016/j.knosys.2006.11.014.
• Kim, D. J., Ferrin, D. L., & Rao, H. R. (2008). A trust-based consumer decision-making model in electronic commerce: The role of trust, perceived risk, and their antecedents. Decision Support Systems, 44(2), 544-564. https://doi.org/10.1016/j.dss.2007.07.001.
• Kim H-W, Xu, Y & Gupta, S. (2012). Which is more important in Internet shopping, perceived price or trust? Electronic Commerce Research and Applications 11(3): 241–252. https://doi.org/10.1016/j. elerap.2011.06.003.
• Kline, R. B. (2011). Principles and Practice of Structural Equation Modeling. New York: Guilford Press.
• Kolodinsky JM, Hogarth JM, Hilgert MA. (2004) The adoption of electronic banking technologies by US customers. Int Journal of Bank Marketing. (pp. 238–259).
• Langer, M., and König, C. J. (2018). Introducing and testing the creepiness of situation scale (CRoSS). Frontiers in Psychology, 9, 2220.
• Lappeman, J. Marlie, S., Johnson, T. and Poggenpoel, S. (2022). Trust and digital privacy: willingness to disclose personal information to banking chatbot services, Journal of Financial Services Marketing, .1-21.
• Lui, A. and Lamb, G.W. (2018). Artificial intelligence and augmented intelligence collaboration: regaining trust and confidence in the financial sector, Information & Communications Technology Law, 27:3, 267-283.
• Machkour, B. and Abriane, A. (2020). Industry 4.0 and its Implications for the Financial Sector, Procedia Computer Science 177, 496–502. https://doi.org/10.1016/j.procs.2020.10.068
• Markets Insider (2022). Global chatbot market (2020 to 2026) - Rise in demand for AI-based chatbots to deliver enhanced customer experience presents opportunities. https://markets.businessinsider.com/news/stocks/ global-chatbot-market-2020-to-2026-rise-in-demand-for-ai-based-chatbots-to-deliver-enhanced- customer-experience-presents-opportunities-1030269345 adresinden 10 Aralık 2022 tarihinde alınmıştır.
• Mayer, R. C., & Davis, J. H. (1999). The effect of the performance appraisal system on trust for management: A field quasi-experiment. Journal of Applied Psychology, 84, 123–136. https://doi.org/10.1037/0021-9010.84.1.123 McKnight, D. H., Choudhury, V., & Kacmar, C. (2002). Developing and validating trust measures for e-commerce: An integrative typology. Information Systems Research, 13(3), 334–359. https://doi.org/10.1287/isre.13.3.334.81 Mogaji, E. and Nguyen, N.P. (2021). Managers’ understanding of artificial intelligence in relation to marketing financial services: insights from a cross-country study, International Journal of Bank Marketing. https://doi. org/10.1108/IJBM-09-2021-0440
• Neff, G. and Nagy, P. (2016). Talking to Bots: Symbiotic Agency and the Case of Tay, International Journal of Communication 10, 4915–4931.
• Pérez-Soler, S., Juárez-Puerta, S., Guerra, E. and Lara, J. (2021). Choosing a Chatbot Development Tool, IEEE SOFTWARE, 94-103. DOI: 10.1109/MS.2020.3030198
• Persaud, A. and Azhar, I. (2012), “Innovative mobile marketing via smartphones: are consumers ready?”, Marketing Intelligence & Planning, Vol. 30 No. 4, pp. 418-443. DOI: https://doi.org/10.1108/0263450121123 188.
• Przegalinska, A., Ciechanowski, L., Stroz, A., Gloor, P. and Mazurek, G. (2019). In bot we trust: A new methodology of chatbot performance measures, Business Horizons, 62, 785-797. DOI: 10.1016/j.bushor.2019.08.005
• Rajaobelina, L., Prom Tep, S., Arcand, M. and Ricard, L. (2021). Creepiness: Its antecedents and impact on loyalty when interacting with a chatbot, Psychol Mark.,38, 2339–2356. https://doi.org/10.1002/mar.21548
• Ridings, C.M., Gefen,D., Arinze,B. (2002). Some antecedents and effects of trust in virtual communities, Journal of Strategic Information Systems.,11, 271-295.
• Shawar, B. A. and Atwell, E.S. (2005) A chatbot system as a tool to animate a corpus. ICAME Journal: International Computer Archive of Modern and Medieval English Journal, 29. 5 - 24. ISSN 0801-5775.
• Shevlin, R. (2022). The 5 Hottest Technologies in Banking For 2022. https://www.forbes.com/sites/ ronshevlin/2021/12/31/the-5-hottest-technologies-in-banking-for-2022/?sh=229715c977dc
• Singh A., Shivam S., Ramasubramanian K., (2019), Apress, Building an Enterprise Chatbot: Work with Protected Enterprise Data Using Open Source Frameworks, Apress.
• Standford (2022). The turing test. https://plato.stanford.edu/entries/turing-test/ adresinden 10 Aralık 2022 tarihinde alınmıştır. Xiao, S., and Benbasat, I. (2002). The Impact of Internalization and Familiarity on Trust and Adoption of Recommendation Agents. Paper presented at the AIS SIG-HCI.
• Shridhar K. (2017) How Close Are Chatbots To Passing The Turing Test?, https://chatbotsmagazine.com/how- close-are-chatbots-to-pass-turing-test-33f27b18305e
• Turing, A. M. (1950). Computing Machinery and Intelligence, Mind, New Series, 59(236), 433-460, Oxford University Press on behalf of the Mind Association.
• Weizenbaum, J. (1966). Computational Linguistics, Communications of the ACM, 9(1), 36-45. https://doi. org/10.1145/365153.365168
• Plotkina, D., Dinsmore, J. and Racat, M. (2022), «Improving service brand personality with augmented reality marketing», Journal of Services Marketing, 36 (6), 781-799. DOI: 10.1108/JSM-12-2020-0519
• Xie, Y. H. (2008). Consumer Innovativeness and Consumer Acceptance of Brand Extensions. Journal of Product & Brand Management. 17(4), pp.235–243.
• Zumstein, D. and Hundertmark, S. (2017) Chatbots – An Interactive Technology for Personalized Communication, Transactions and Services, IADIS International Journal on WWW/Internet Vol. 15, No. 1, pp. 96-109.