Examining the Customer Experience of Using Banking Chatbots and Its Impact on Brand Love: The Moderating Role of Perceived Risk

References

• Agarwal, A., and M. R. Singh. 2018. The relationship between retail experience, customer satisfaction, and behavioral intentions: Exploring the consumer shopping behavior in unorganized retail settings. Indian Journal of Marketing 48 (1):9–27. doi:10.17010/ijom/2018/v48/i1/120733.
   Google Scholar
• Aiken, L. S., S. G. West, and R. R. Reno. 1991. Multiple regression: Testing and interpreting interactions. Newbury Park, CA: Sage.
   Google Scholar
• Albert, N., and D. Merunka. 2013. The role of Brand love in consumer-brand relationships. Journal of Consumer Marketing 30 (3):258–66. doi:10.1108/07363761311328928.
   Google Scholar
• Anderson, E. W., C. Fornell, and D. R. Lehmann. 1994. Customer satisfaction, market share, and profitability: Findings from Sweden. The Journal of Marketing 58 (3):53–66. doi:10.1177/002224299405800304.
   Web of Science ®Google Scholar
• Baron, R. M., and D. A. Kenny. 1986. The moderator-mediator variable distinction in socialpsychological research: conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology 51 (6):1171–82.
   Web of Science ®Google Scholar
• Batra, R., A. Ahuvia, and R. P. Bagozzi. 2012. Brand love. Journal of Marketing 76 (2):1–16. doi:10.1509/jm.09.0339.
   Web of Science ®Google Scholar
• Benoit 2016. Generation Y: chatbots for Millennials? Retrieved from http://blog.livingactor.com/generation-y-chatbots-for-millennials/ (accessed February 2018).
   Google Scholar
• Bernazzani, S. 2018. How chatbots can improve user experience. Retrieved from https://blog.hubspot.com/service/chatbots-user-experience (accessed April 2018).
   Google Scholar
• Bhattacharjee, A., and G. Premkumar. 2004. Understanding changes in belief and attitude toward information technology usage: A theoretical model and longitudinal test. MIS Quarterly 28:229–54. doi:10.2307/25148634.
   Web of Science ®Google Scholar
• Browne, M. W., and R. Cudeck. 1992. Alternative ways of assessing model fit. Sociological Methods & Research 21 (2):230–58.
   Web of Science ®Google Scholar
• Brown, I., and R. Jayakody. 2008. B2C e-commerce success: A test and validation of a revised conceptual model. The Electronic Journal Information Systems Evaluation 11 (3):167–84.
   Google Scholar
• Carbone, L. P., and S. H. Haeckel. 1994. Engineering customer experiences. Marketing Management 3 (3):8.
   Google Scholar
• Carroll, B. A., and A. C. Ahuvia. 2006. Some antecedents and outcomes of Brand love. Marketing Letters 17 (2):79–89. doi:10.1007/s11002-006-4219-2.
   Web of Science ®Google Scholar
• Chen, Y. S., and S. Y. Huang. 2017. The effect of task-technology fit on purchase intention: The moderating role of perceived risks. Journal of Risk Research 20 (11):1418–38. doi:10.1080/13669877.2016.1165281.
   Web of Science ®Google Scholar
• Clikeman, P. M. 1999. Improving information quality. Internal Auditor 56:32.
   Google Scholar
• Damghanian, H., A. Zarei, and M. A. Siahsarani Kojuri. 2016. Impact of perceived security on trust, perceived risk, and acceptance of online banking in Iran. Journal of Internet Commerce 15 (3):214–38. doi:10.1080/15332861.2016.1191052.
   Web of Science ®Google Scholar
• Davis, F. D. 1989. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly 13 (3):319–39. doi:10.2307/249008.
   Web of Science ®Google Scholar
• Dawar, N., and N. Bendle. 2018. Marketing in the age of alexa. Retrieved from https://hbr.org/2018/05/marketing-in-the-age-of-alexa (accessed June 2018).
   Google Scholar
• Delone, W. H., and E. R. McLean. 1992. Information systems success: The quest for the dependent variable. Information Systems Research 3 (1):60–95. doi:10.1287/isre.3.1.60.
   Web of Science ®Google Scholar
• Delone, W. H., and E. R. McLean. 2003. The delone and McLean model of information systems success: A Ten-Year update. Journal of Management Information System 19 (4):9–30.
   Web of Science ®Google Scholar
• Desaulniers, S. 2016. Chatbots rise and the future may be ‘re-written’. Retrieved from http://www.cnbc.com/2016/04/08/chatbots-rise-and-thefuture-may-be-re-written.html (accessed January 2018).
   Google Scholar
• Dowling, G. R., and R. Staelin. 1994. A model of perceived risk and intended risk-handling activity. Journal of Consumer Research 21 (1):119–34. doi:10.1086/209386.
   Web of Science ®Google Scholar
• Dreyer, T. 2016. Survey finds half of consumers would prefer to conduct all customer service via messaging. Retrieved from https://venturebeat.com/2016/12/12/new-survey-and-insights-about-what-consumers-want-in-a-chatbot/ (accessed April 2018).
   Google Scholar
• EY Report. 2014. Banking on Technology: Perspectives on the Indian banking Industry. Retrieved online from http://www.ey.com/in/en/industries/financial-services/banking—capital-markets/ey-banking-on-technology-India-banking-industry (accessed April 2018).
   Google Scholar
• Fetscherin, M. 2014. What type of relationship do we have with loved brands? Journal of Consumer Marketing 31 (6/7):430–40. doi:10.1108/JCM-05-2014-0969.
   Google Scholar
• Gorla, N., T. M. Somers, and B. Wong. 2010. Organizational impact of system quality, information quality, and service quality. The Journal of Strategic Information Systems 19 (3):207–28. doi:10.1016/j.jsis.2010.05.001.
   Web of Science ®Google Scholar
• Grant, R. A. 1989. Building and testing a model of an information technology’s impact. In Proceedings of the tenth international conference on information systems, ed. J. I. DeGross, J. C. Henderson, and B. R. Konsynski, 173–184. Boston, MA.
   Google Scholar
• Hair, J. F., R. E. Anderson, R. L. Tatham, and W. C. Black. 1998. Multivariate data analysis. 1998. Upper Saddle River, NJ: Prentice Hall.
   Google Scholar
• Hair, J. F., W. C. Black, B. J. Babin, R. E. Anderson, and R. L. Tatham. 2006. Multivariate data analysis. Vol. 6. Upper Saddle River, NJ: Prentice Hall
   Google Scholar
• Hoxmeier, J. A., and C. DiCesare. 2000. System response time and user satisfaction: An experimental study of browser-based applications. AMCIS 2000 Proceedings, 347.
   Google Scholar
• Huber, F., F. Meyer, and D. A. Schmid. 2015. Brand love in progress–the interdependence of Brand love antecedents in consideration of relationship duration. Journal of Product and Brand Management 24 (6):567–79. doi:10.1108/JPBM-08-2014-0682.
   Web of Science ®Google Scholar
• Huber, M. W., C. A. Piercy, and P. G. Mckeown. 2008. Information systems: Creating business value. Hoboken, NJ: John Wiley & Sons, Incorporated.
   Google Scholar
• Im, I., Y. Kim, and H. J. Han. 2008. The effects of perceived risk and technology type on users’ acceptance of technologies. Information and Management 45 (1):1–9. doi:10.1016/j.im.2007.03.005.
   Web of Science ®Google Scholar
• ISO 9241. 1998. Ergonomic requirements for office work with visual display terminals (VDTs) – Part 11: Guidance on usability. Geneva, Switzerland: International Organization for Standardization.
   Google Scholar
• Jaakkola, E., A. Helkkula, and L. Aarikka-Stenroos. 2015. Service experience co-creation: Conceptualization, implications, and future research directions. Journal of Service Management 26 (2):182–205. doi:10.1108/JOSM-12-2014-0323.
   Web of Science ®Google Scholar
• Jain, R., J. Aagja, and S. Bagdare. 2017. Customer experience–a review and research agenda. Journal of Service Theory and Practice 27 (3):642–62. doi:10.1108/JSTP-03-2015-0064.
   Web of Science ®Google Scholar
• Joji, A., and J. Ashwin. 2012. Hedonic versus utilitarian values: The relative importance of real and ideal self to Brand personality and its influence on emotional Brand attachment. Vilakshan: The XIMB Journal of Management 9 (2):77.
   Google Scholar
• Karjaluoto, H., J. Munnukka, and K. Kiuru. 2016. Brand love and positive word of mouth: The moderating effects of experience and price. Journal of Product and Brand Management 25 (6):527–37. doi:10.1108/JPBM-03-2015-0834.
   Web of Science ®Google Scholar
• Kim, B., K. Park, and J. Kim. 2003. Satisfying different customer groups for IS outsourcing: A korean IS company’s experience. Asia Pacific Journal of Marketing and Logistics 15 (3):48–69. doi:10.1108/13555850310765006.
   Google Scholar
• Lai-Ming Tam, J. 2012. The moderating role of perceived risk in loyalty intentions: An investigation in a service context. Marketing Intelligence and Planning 30 (1):33–52. doi:10.1108/02634501211193903.
   Google Scholar
• Liu, X., and Q. Wang. 2005. Study on application of a quantitative evaluation approach for software architecture adaptability. Melbourne, Australia: Paper presented at the fifth international conference on Quality Software, 2005 (QSIC 2005).
   Google Scholar
• Love, B. 2015. Brand experience leads to brand love–retail fashion brand case.
   Google Scholar
• Martin, A., and D. Khazanchi. 2006. Information availability and security policy. Proceedings of the Twelfth Americas Conference on Information Systems, Acapulco, Mexico, 1257–1268.
   Google Scholar
• Mitchell, V. W. 1998. A role for consumer risk perceptions in grocery retailing. British Food Journal 100 (4):171–83. doi:10.1108/00070709810207856.
   Google Scholar
• Nunnally, J. 1978. Psychometric theory (2nd ed.). New York, NY: McGraw-Hill.
   Google Scholar
• Oostenbrink, J. 2015. Financial impact of downtime decrease and performance increase of IT services. Bachelor’s thesis, University of Twente.
   Google Scholar
• Pan, Y., and Jackson, R. T. 2008. Ethnic difference in the relationship between acute inflammation and serum ferritin in US adult males. Epidemiology and Infection 136:421–43.
   PubMed Web of Science ®Google Scholar
• Pannu, A. 2015. Artificial intelligence and its application in different areas. Artificial Intelligence 4 (10):79–84.
   Google Scholar
• Pareigis, J. 2012. Customer experiences of resource integration: Reframing servicescapes using scripts and practices. Doctoral dissertation, Karlstads university.
   Google Scholar
• Pine, B. J., and J. Gilmore. 1998. Welcome to the experience economy. Harvard Business Review 78 (1):97–105.
   Google Scholar
• Podsakoff, P. M., S. B. MacKenzie, J. Y. Lee, and N. P. Podsakoff. 2003. Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology 88 (5):879. doi:10.1037/0021-9010.88.5.879.
   PubMed Web of Science ®Google Scholar
• Poushneh, A., and A. Z. Vasquez-Parraga. 2017. Discernible impact of augmented reality on retail customer’s experience, satisfaction and willingness to buy. Journal of Retailing and Consumer Services 34:229–34. doi:10.1016/j.jretconser.2016.10.005.
   Web of Science ®Google Scholar
• Price, D. 2018. Yes, chat bots are incredibly efficient. But your customers hate them. Retrieved from https://www.inc.com/dom-price/yes-chat-bots-are-incredibly-efficient-but-your-customers-hate-them.html (April 2018).
   Google Scholar
• Raudenbush, S. W., and A. S. Bryk. 2001. Hierarchical linear models: Applications and data analysis methods. Newbury Park, CA: Sage.
   Google Scholar
• Reibman, A. L., and M. Veeraraghavan. 1991. Reliability modeling: An overview for system designers [Electronic version]. Computer Magazine 24 (4):49–57. doi:10.1109/2.76262.
   Web of Science ®Google Scholar
• Richardson, A. 2010. Using customer journey maps to improve customer experience. Harvard Business Review 15 (1):2–5.
   Google Scholar
• Sarkar, A., and J. G. Sarkar. 2016. Devoted to you my love: Brand devotion amongst young consumers in emerging indian market. Asia Pacific Journal of Marketing and Logistics 28 (2):180–97. doi:10.1108/APJML-06-2015-0095.
   Web of Science ®Google Scholar
• Schlicht, M. 2016. The complete beginner’s guide to chatbots — chatbots magazine. Retrieved from https://chatbotsmagazine.com/the-complete-beginner-sguide- to-chatbots-8280b7b906ca#.5vs9cl5ut
   Google Scholar
• Schmitt, B. 1999. Experiential marketing. Journal of Marketing Management 15 (1–3):53–67. doi:10.1362/026725799784870496.
   Google Scholar
• Schou, C. 1996. Information systems security organization (ISSO) Glossary of INFOSEC and INFOSEC related terms, Vols. I & II. Idaho, USA: Idaho State University.
   Google Scholar
• Shapiro, S. C. 1992. Encyclopedia of artificial intelligence. 2nd ed. New York, NY: John Wiley & Sons.
   Google Scholar
• Shaw, C., and J. Ivens. 2002. Building great customer experience. New York, NY: Palgrave, Macmillan.
   Google Scholar
• Shawar, B. A., and E. Atwell. 2007. Different measurements metrics to evaluate a chatbot system. In Proceedings of the workshop on bridging the gap: Academic and industrial research in dialog technologies, 89–96. Rochester, NY: Association for Computational Linguistics.
   Google Scholar
• Soteriou, A. C., and R. B. Chase. 2000. A robust optimization approach for improving service quality. Manufacturing and Service Operations Management 2 (3):264–86. doi:10.1287/msom.2.3.264.12344.
   Google Scholar
• Sridhar, G. 2017. Conversational banking gains currency as chatbots become popular. Retrieved from https://www.thehindubusinessline.com/money-and-banking/conversational-banking-gains-currency-as-chatbots-become-popular/article9906700.ece in April 2018.
   Google Scholar
• Swanson, B. 1997. Maintaining IS quality. Information and Software Technology 39 (12):845–50. doi:10.1016/S0950-5849(97)00043-8.
   Web of Science ®Google Scholar
• Synder, B. 2015. Consumers love Samsung, but don’t trust Apple or Facebook. Retrieved from https://www.cio.com/article/2943642/consumer-technology/consumers-love-samsung-but-dont-trust-apple-or-facebook.html in May 2018.
   Google Scholar
• Trivedi, J. P., and H. Trivedi. 2018. Investigating the factors that make a fashion app successful: The moderating role of personalization. Journal of Internet Commerce 17 (2):170–87. doi:10.1080/15332861.2018.1433908.
   Web of Science ®Google Scholar
• Zhou, D., K. Nakatani, and T. T. Chuang. 2011. Data quality in collaborative commerce. International Journal of Information Quality 2 (3):264–78.
   Google Scholar