The Effects of Chatbot Service Quality, Trust, and Satisfaction on Chatbot Reuse Intention and Store Reuse Intention

JI,, S. , & CHA,, A. (2020). The Effects of Chatbot Service Quality, Trust, and Satisfaction on Chatbot Reuse Intention and Store Reuse Intention. The Journal of Industrial Distribution & Business, 11(12), 29-38, https://doi.org/https://doi.org/10.13106/jidb.2020.vol11.no12.29

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Abstract

Purpose: The purpose of this study is to empirically analyze the effect of chatbot service quality, chatbot trust, and chatbot satisfaction on chatbot reuse intention and store reuse intention. Research design, data, and methodology: We reviewed the literature on domestic and international chatbots, established hypotheses, and analyzed them. We empirically analyzed the process model in which chatbot service quality (interaction quality, information quality) has a positive effect on chatbot trust and chatbot satisfaction, and that chatbot trust and satisfaction positively affect chatbot reuse intention and store reuse intention. A survey was conducted on 212 people who had used shopping mall chatbots and financial service chatbots after demonstrating the shopping mall chatbot video. Structural equation modeling was conducted by using AMOS 24.0 to test the proposed relationships. Results: As a result of the empirical analysis, the effects of interaction quality on chatbot trust and information quality on chatbot satisfaction were not supported, but the rest of the hypotheses were statistically significant. It was found that the information quality of chatbot service had a positive effect on chatbot trust, but did not significantly affect chatbot satisfaction. In addition, the interaction quality of the chatbot positively affects the satisfaction of the chatbot, but it does not significantly affect the trust of the chatbot. Chatbot trust was found to have a positive effect on chatbot satisfaction. Chatbot trust and chatbot satisfaction were found to have a positive influence on the intention to reuse the chatbot. And, chatbot trust and chatbot satisfaction were found to have a positive influence on store reuse intention. Conclusions: The findings of this study offer significant theoretical and managerial contributions in the context of chatbot. Chatbots should enhance customer contact quality management from the perspective of total customer experience management rather than partial function. When providing a chatbot service, it is more desirable to give priority to providing accurate information to increase trust, and at the same time to improve customer satisfaction by increasing the quality of interaction. And in order to increase the competitive advantage of companies, the purpose of introducing chatbots should be clarified and approached strategically.

keywords: Chatbot Service Quality, Trust, Satisfaction, Chatbot Reuse Intention, Store Reuse Intention

Reference

Anderson, J. C., & Narus, J. A. (1990). A model of distributor firm and manufacturer firm working partnerships. Journal of Marketing, 54(1), 42-58.

Anderson, R. E., & Srinivasan, S. S. (2003). E-satisfaction and eloyalty; A contingency framework. Psychology & Marketing, 20(2), 123-138.

Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74-94.

Beatty, S. E., Mayer, M., Coleman, J. E., Reynolds, K. E., & Lee, J. (1996). Customer-sales associate retail relationships. Journal of Retailing, 72(3), 223-247.

Berry, L. L., & Parasuraman, A. (1992). Prescriptions for a service quality revolution in America. Organizational Dynamics, 20(4), 5-15.

Biong, H., & Selnes, F. (1997). The strategic role of the salesperson in established buyer-seller relationships. Journal of Business-to-Business Marketing, 3(3), 39-78.

Bitner, M. J. (1995). Building service relationships: It’s all about promises. Journal of the Academy of Marketing Science, 23(4), 246-251.

Chattaraman, V., Kwon, W., Gilbert, J., & Ross, K. (2019). Should AI-based, conversational digital assistants employ social-or task-oriented interaction style? A task-competency and reciprocity perspective for older adults. Computers in Human Behavior, 90, 315-330.

Chattaraman, V., Kwon, W. S., & Gilbert, J. (2012). Virtual agents in retail web sites: Benefits of simulated social interaction for older users. Computers in Human Behavior, 28(6), 2055-2066.

10.

Chung, M., Ko, E., Joung, H., & Kim, S. (2020). Chatbot eservice and customer satisfaction regarding luxury brands. Journal of Business Research, 117, 587-595.

11.

Cunningham, J. B., & MacGregor, J. (2000). Trust and the design of work complementary constructs in satisfaction and performance. Human Relations, 53(12), 1575-1591.

12.

Das, T. K., & Teng, B. S. (1998). Between trust and control:Developing confidence in partner cooperation in alliances. Academy of Management Review, 23(3), 491-512.

13.

DeLone, W. H., & McLean, E. R. (1992). Information systems success: The quest for the dependent variable. Information Systems Research, 3(1), 60-95.

14.

DeLone, W. H., & McLean, E. R. (2003). The DeLone and McLean model of information systems success: A ten-year update. Journal of Management Information Systems, 19(4), 9-30.

15.

Fernandes, T., & Oliveira, E. (2021). Understanding consumers’acceptance of automated technologies in service encounters:Drivers of digital voice assistants adoption. Journal of Business Research, 122, 180-191.

16.

Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 18(3), 382-388.

17.

Go, E., & Sundar, S. S. (2019). Humanizing chatbots: The effects of visual, identity and conversational cues on humanness perceptions. Computers in Human Behavior, 97, 304-316.

18.

Grönroos, C. (1984). A service quality model and its marketing Implications. European Journal of Marketing, 18(4), 36-44.

19.

Hill, J., Ford, W. R., & Farreras, I. G. (2015). Real conversations with artificial intelligence a comparison between humanhuman online conversations and human-chatbot conversations. Computers in Human Behavior, 49, 245-250.

20.

Hsu, M. H., Chang, C. M., Chu, K. K., & Lee, Y. J. (2014). Determinants of repurchase intention in online group-buying:The perspectives of DeLone & McLean IS success model and trust. Computers in Human Behavior, 36, 234-245.

21.

Hwang, Y., Park, S., & Choi, S. M. (2020). A Study of the factors influencing attitude and behavioral intentions toward AI speakers among non-users. Journal of Media Economics &Culture, 18(1), 31-71.

22.

Jeong, H. S., & Kim, Y. I. (2019). The effect of chatbot quality on chatbot trust and brand trust. Journal of the Korean Society of Costume, 69(3), 1-14.

23.

Jin, B. (2019). Evaluative messages from conversational agents:A relational perspective. Journal of the HCI Society of Korea, 14(3), 13-20.

24.

Kaplan, A., & Haenlein, M. (2019). Siri, Siri in my hand, Who is the fairest in the Land? On the interpretations, illustrations and implications of artificial intelligence. Business Horizons, 62(1), 15-25.

25.

Kaplan, A., & Haenlein, M. (2020). Rulers of the world, unite!The challenges and opportunities of artificial intelligence. Business Horizons, 63(1), 37-50.

26.

Kim, M., Seo, B. G., & Park, D. H. (2019). Development process for user needs-based chatbot: Focusing on design thinking methodology. Journal of Intelligence and Information Systems, 25(3), 221-238.

27.

Kowalczuk, P. (2018). Consumer acceptance of smart speakers: A mixed methods approach. Journal of Research in Interactive Marketing, 12(4), 418-431.

28.

Kwak, J., Kim, N., & Kim, M. S. (2019). The relationship among chatbot’s characteristics, service value, and customer satisfaction. International Journal of Industrial Distribution & Business, 10(3), 45-58.

29.

Lee, M. K., & Park, H. (2019). Exploring factors influencing usage intention of chatbot-chatbot in financial service. Journal of Korean Society for Quality Management, 47(4), 755-765.

30.

Lee, M., & Cunningham, L. F. (2001). A cost/benefit approach to understanding service loyalty. Journal of Services Marketing, 15(2), 113-130.

31.

Macintosh, G., & Lockshin, L. S. (1997). Retail relationships and store loyalty: A multi-level perspective. International Journal of Research in Marketing, 14(5), 487-497.

32.

Marketsandmarket(2019). Chatbot market by component(solutions and services), usage(websites and contact centers), technology, deployment model, application (customer support and personal assistant), organization size, vertical, and region-global forecast to 2024. USA, MarketsandMarkets INC. https://www.marketsandmarkets.com/Market-Reports /smartadvisor-market-72302363.html

33.

Mayer, R. C., Davis, J. H., & Schoorman, F. D. (1995). An integrative model of organizational trust. Academy of Management Review, 20(3), 709-734.

34.

McDougall, G. H. G., & Levesque, T. (2000). Customer satisfaction with services: Putting perceived value into the equation. Journal of Services Marketing, 14(5), 392-410.

35.

McLean, G., & Osei-Frimpong, K. (2019). Hey Alexa...Examine the variables influencing the use of artificial intelligent inhome voice assistants. Computers in Human Behavior, 99, 28-37.

36.

Mimoun, M. S., Poncin, B. I., & Garnier, M. (2017). Animated conversational agents and e-consumer productivity: The roles of agents and individual characteristics. Information &Management, 54(5), 545-559.

37.

Moorman, C., Deshpande, R., & Zaltman, G. (1993). Factors affecting trust in market research relationships. Journal of Marketing, 57(1), 81-101.

38.

Oliver, R. L. (1980). A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of Marketing Research, 17(4), 460-469.

39.

Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1988). SERVQUAL: A multiple-item scale for measuring consumer perceptions of service quality. Journal of Retailing, 64(1), 12-40.

40.

Park, S., & Choi, S. M. (2018). A understanding the factors influencing satisfaction and continued use intention of AI speakers : Focusing on the utilitarian and hedonic. Values Information Society & Media, 19(3), 159-182.

41.

Qiu, H., Li, M., Shu, B., & Bai, B. (2020). Enhancing hospitality experience with service robots: The mediating role of rapport building. Journal of Hospitality Marketing & Management, 29(3), 247-268.

42.

Ribbink, D., Van Riel, A. C., Liljander, V., & Streukens, S. (2004). Comfort your online customer: Quality, trust and loyalty on the internet. Managing Service Quality: An International Journal, 14, 446-456.

43.

Rust, R. T., & Oliver, R. L. (1994). Service quality: Insights and managerial implications from the frontier. In: Rust, R.T., &Oliver, R. L., Eds., Service Quality: New Directions in Theory and Practice, 1-19. Sage Publications, Thousand Oaks.

44.

Shankar, V., Smith, A. K., & Rangaswamy, A. (2003). Customer satisfaction and loyalty in online and offline environments. International Journal of Research in Marketing, 20(2), 153-175.

45.

Sirdeshmukh, D., Singh, J., & Sabol, B. (2002). Consumer trust, value and loyalty in relational exchanges. Journal of Marketing, 66(1), 15-37.

46.

Suh, C. J., & Yoon, J. O. (2019). The effects of perceived chatbot service quality on customer satisfaction and word of mouth. Journal of Korea Service Management Society, 20(1), 201-222.

47.

Toader, D-C, Boca, G., Toader, R., Măcelaru, M., Toader, C., Ighian, D. & Rădulescu, A. T. (2020). The effect of social presence and chatbot errors on trust. Sustainability, 12(1), 256.

48.

van Pinxteren, M., Wetzels, R., Rüger, J., & Wetzels, M. (2019). Trust in humanoid robots: Implications for services marketing. Journal of Services Marketing, 33(4), 507-518.

49.

Zeithaml, V. A., Berry, L. L., & Parasuraman, A. (1996). The behavioral consequences of service quality. Journal of Marketing, 60(2), 31-46.

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Article Contents

Vol.11 No.12

The Effects of Chatbot Service Quality, Trust, and Satisfaction on Chatbot Reuse Intention and Store Reuse Intention

Abstract

Reference

The Journal of Industrial Distribution & Business