Browse > Article
http://dx.doi.org/10.5805/SFTI.2022.24.2.229

Factors driving Fashion Chatbot Reliability -Focusing on the Mediating Effect of Perceived Intelligence and Positive Cognition-  

Lee, Ha Kyung (Dept. of Clothing & Textiles, Chungnam National University)
Yoon, Namhee (Human Ecology Research Center, Korea University)
Publication Information
Fashion & Textile Research Journal / v.24, no.2, 2022 , pp. 229-240 More about this Journal
Abstract
This study explores the effect of anthropomorphism on fashion chatbot reliability, mediated by perceived intelligence and cognitive evaluation. The moderating effects of individuals' need for human interaction between chatbot anthropomorphism and perceived intelligence, cognitive evaluation, and chatbot reliability are also explored. Participants, who were recruited through the online research firm, responded to questions after watching a video clip showing a conversation with a fashion chatbot on a mobile screen. The data were collected through Mturk, a crowdsourcing platform with an online research panel. All responses (N = 212) were analyzed using SPSS 26.0 for the descriptive statistics, frequency analysis, reliability analysis, exploratory factor analysis, and PROCESS procedure. The results demonstrate that chatbot anthropomorphism increases chatbot reliability, and this is mediated by chatbot intelligence. Although chatbot anthropomorphism increases cognitive evaluation, the effect of cognitive evaluation on chatbot reliability is not significant; thereby, the effect of chatbot anthropomorphism on chatbot reliability is not mediated by the cognitive evaluation. The direct effect of anthropomorphism on chatbot reliability is also moderated by individuals' need for human interaction. For participants with a high need for human interaction, chatbot anthropomorphism increases chatbot reliability; however, anthropomorphism does not significantly affect chatbot reliability for participants with a low need for human interaction. The study's findings contribute to expanding the literature on consumers' new technology acceptance by testing the antecedents affecting service reliability.
Keywords
fashion chatbot; anthropomorphism; perceived intelligence; positive cognition; reliability;
Citations & Related Records
Times Cited By KSCI : 6  (Citation Analysis)
연도 인용수 순위
1 Blut, M., Wang, C., Wunderlich, N. V., & Brock, C. (2021). Understanding anthropomorphism in service provision - A meta-analysis of physical robots, chatbots, and other AI. Journal of the Academy of Marketing Science, 49(4), 632-658. doi:10.1007/s11747-020-00762-y   DOI
2 Solomon, M. R., Surprenant, C., Czepiel, J. A., & Gutman, E. G. (1985). A role theory perspective on dyadic interactions - The service encounter. Journal of Marketing, 49(1), 99-111. doi:10.1177/002224298504900110   DOI
3 Breakwell, G. M., Fife-Schaw, C., Lee, T., & Spencer, J. (1986). Attitudes to new technology in relation to social beliefs and group memberships - A preliminary investigation. Current Psychological Research & Reviews, 5(1), 34-47.   DOI
4 Broadbent, E., Jayawardena, C., Kerse, N., Stafford, R.Q., & MacDonald, B.A. (2011, August). Human-robot interaction research to improve quality of life in elder care - An approach and issues. Paper presented at Workshops at the Twenty-Fifth AAAI Conference on Artificial Intelligence, San Francisco, CA, pp. 13-19
5 Yoo, J. (2020). Design and implementation of library chatbot for non-face-to-face reference services. Korean Society for Information Management, 37(4), 151-179. doi:10.3743/KOSIM.2020.37.4.151   DOI
6 Sung, Y. S., & Park, E. (1995). 광고에 대한 감정의 유형화: 유발된 감정과 느낀 감정 [Types of emotions about advertising - Triggered and natural emotions], The Korean Journal of Advertising, 6(2), 7-49.
7 Pan, L. Y., & Chiou, J. S. (2011). How much can you trust online information? Cues for perceived trustworthiness of consumer-generated online information. Journal of Interactive Marketing, 25(2), 67-74. doi:10.1016/j.intmar.2011.01.002   DOI
8 Park, M. J. (2013). The effect of information quality on consumers' cognitive, emotional and behavioral responses in group-buying social commerce -focused on technology acceptance model-. Journal of the Korean Society of Design Culture, 19(3), 293-303.
9 Erebak, S., & Turgut, T. (2019). Caregivers' attitudes toward potential robot coworkers in elder care. Cognition, Technology and Work, 21(2), 327-336. doi:10.1007/s10111-018-0512-0   DOI
10 Yoo, H., & Lee, J. (2019). A study on the development of interaction design framework based on personality of customized chatbot design. Journal of Integrated Design Research, 18(1), 77-94. doi:10.21195/jidr.2019.18.1.005   DOI
11 Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1985). A conceptual model of service quality and its implications for future research. Journal of Marketing, 49(4), 41-50. doi:10.1177/002224298504900403   DOI
12 Hirschman, E. C., & Holbrook, M. B. (1982). Hedonic consumption - Emerging concepts, methods and propositions. Journal of Marketing, 46(3), 92-101. doi:10.1177/002224298204600314   DOI
13 Frijda, N. H. (1993). Moods, emotion episodes, and emotions. In M. Lewis & J. M. Haviland (Eds.), Handbook of Emotions (pp. 381-403). New York, NY: The Guilford Press.
14 Gardner, L., & Leshner, G. (2016). The role of narrative and other-referencing in attenuating psychological reactance to diabetes self-care messages. Health Communication, 31(6), 738-751. doi:10.1080/10410236.2014.993498   DOI
15 Hayes, A. F. (2021). Introduction to mediation, moderation, and conditional process analysis - A regression-based approach (3rd ed.). New York, NY: Guilford Publications.
16 Hwang, M. H., Lee, W. S., Hwang, H., Park, Y. S., Lim, Y. K., & Jeon, B. Y. (2021). Designing and validating chatbot counseling algorithms to alleviate smartphone addiction among adolescents. Journal of the HCI Society of Korea, 16(4), 33-42. doi:10.17210/jhsk.2021.12.16.4.33   DOI
17 DiSalvo, C. F., Gemperle, F., Forlizzi, J., & Kiesler, S. (2002). All robots are not created equal - The design and perception of humanoid robot heads. Proceedings of the 4th Conference on Designing Interactive Systems: Processes, Practices, Methods, and Techniques, England, pp.321-326. doi:10.1145/778712.778756   DOI
18 Butler, B. S., & Gray, P. H. (2006). Reliability, mindfulness, and information systems. MIS Quarterly, 30(2), 211-224. doi:10.2307/25148728   DOI
19 Cho, G., & Yun, J. Y. (2019). UX evaluation of financial service chatbot interactions. Journal of the HCI Society of Korea, 14(2), 61-69. doi:10.17210/jhsk.2019.05.14.2.61   DOI
20 Collier, J. E. & Kimes, S. E. (2013). Only if it is convenient: Understanding how convenience influences self-service technology evaluation. Journal of Service Research, 16(1), 39-51. doi:10.1177/1094670512458454   DOI
21 Epley, N., Waytz, A., & Cacioppo, J. T. (2007). On seeing human: A three-factor theory of anthropomorphism. Psychological Review, 114(4), 864-886. doi:10.1037/0033-295X.114.4.864   DOI
22 Preacher, K. J., & Hayes, A. F. (2004). SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behavior Research Methods, Instruments, & Computers, 36(4), 717-731. doi:10.3758/BF03206553   DOI
23 Park, H. J. (2020a). A study on the effectiveness of chat-bot service on service value and service acceptance attitude - Case study of "D" Airlines. International Journal of Tourism and Hospitality Research, 34(11), 111-124. doi:10.21298/IJTHR.2020.11.34.11.11   DOI
24 Park, J. (2020b, July 14). "조건 갖춰졌다", 지금이 챗봇 도입 적기 ["The conditions are met". This is the right time to introduce a chatbot]. IT Daily. Retrieved March 2, 2022, from http://www.itdaily.kr/news/articleView.html?idxno=101902
25 Park, J. H., Yun G. I., & Min, S. T. (2019). Trends in artificial intelligence-based chatbot system technology. Korea Information Processing Society Review, 26(2), 39-46.
26 Qiu, H., Li, M., Shu, B., & Bai, B. (2020). Enhancing hospitality experience with service robots. Journal of Hospitality Marketing and Management, 29(3), 247-268. doi:10.1080/19368623.2019.1645073   DOI
27 Seo, J. P. (2019, February 15). 개인 패션 코디네이터 '챗봇'이 온다 [Personal fashion coordinator "Chatbot" is coming]. Fashion Insight. Retrieved March 10, 2022, from http://www.fi.co.kr/main/view.asp?idx=65190
28 Sobel, M. E. (1982). Asymptotic confidence intervals for indirect effects in structural equation models. Sociological Methodology, 13, 290-312. doi:10.2307/270723   DOI
29 Song, Y. J., & Choi, S. M. (2020). The effects of chatbots' anthropomorphism and self-disclosure on consumers' perceptions of and attitude toward the chatbots. Journal of the HCI Society of Korea, 15(1), 17-28. doi:10.17210/jhsk.2020.03.15.1.17   DOI
30 Jeong, S. W., & Park, J. S. (2020). Impacts of technology anxiety and perceived productivity on attitude toward self-service technology - The moderating role of need for interaction. The Research Journal of the Costume Culture, 28(4), 480-491. doi:10.29049/rjcc.2020.28.4.480   DOI
31 Katsyri, J., Forger, K., Makarainen, M., & Takala, T. (2015). A review of empirical evidence on different uncanny valley hypotheses. Frontiers in Psychology, 6, 1-16. doi:10.3389/fpsyg.2015.00390   DOI
32 Huang, M. H., & Rust, R. T. (2018). Artificial intelligence in service. Journal of Service Research, 21(2), 155-172. doi:10.1177/1094670517752459   DOI
33 Evans, K.R., & Brown, S.W. (1988). Strategic options for service delivery systems. In C.A. Ingene & G.L. Frazier (Eds.), Proceedings of the AMA Summer Educators' Conference (pp. 207-212). Chicago, IL: American Marketing Association. doi:10.1007/978-3-642-36172-2_200957.   DOI
34 Evanschitzky, H., Iyer, G. R., Pillai, K. G., Kenning, P., & Schutte, R. (2015). Consumer trial, continuous use, and economic benefits of a retail service innovation - The case of the personal shopping assistant. Journal of Product Innovation Management, 32(3), 459-475. doi:10.1111/jpim.12241   DOI
35 Fishbein, M. (1963). An investigation of the relationships between beliefs about an object and the attitude toward that object. Human Relations, 16(3), 233-239.   DOI
36 Kang, S. Hyun, B. E., & Kim, G. S. (2020). A study on the integration process between chatbot builder and online shopping mall for big data search - Focused on Kakao AI platform. Journal of East and Central Asian Studies, 31(3), 31-46.
37 Kim, T., Cha, H. S., Park, C., & Wi. J. H. (2020). Identifying factors affecting chatbot use intention of online shopping mall users. Knowledge Management Research, 21(4), 211-225. doi:10.15813/kmr.2020.21.4.011   DOI
38 Ledingham, J. A. (1984). Are consumers ready for the information age. Journal of Advertising Research, 24(4), 31-37.
39 Kim, O. K., & Yun, J. Y. (2019). A convergence study on the chatbot (voice-based/messenger-based) in mobile shopping and user experience in app services. The Korean Society of Science & Art, 37(2), 47-59. doi:10.17548/ksaf.2019.03.30.47   DOI
40 Kim, M., Yeom, J. Y., Hung, H., & Lim, C. I. (2021a). A review of research on artificial intelligence chatbot in education through the lens of activity theory. The Journal of Educational Information and Media, 27(2), 699-721. doi:10.15833/KAFEIAM.27.2.699   DOI
41 Kim, T. M., Jo, J. I., & Kim, J. G. (2021b). A cloud-based ordering chatbot for retail stores. Journal of Information Technology and Architecture, 18(2), 137-146. doi: 10.22865/jita.2021.18.2.137   DOI
42 Zeithaml, V. A., Parasuraman, A., & Malhotra, A. (2000). A conceptual framework for understanding e-service quality - Implications for future research and managerial practice(Vol. 115). Cambridge, MA: Marketing Science Institute.
43 Parasuraman, A., Zeithaml, V. A., & Berry, L. (1988). SERVQUAL - A multiple-item scale for measuring consumer perceptions of service quality. In J. Dawson, A. Findlay, & L. Sparks (Eds), The Retailing Reader (pp. 12-40). New York, NY: Routledge.
44 Lee, H. J., Fairhurst, A., & Cho, H. J. (2013). Gender differences in consumer evaluations of service quality - Self-service kiosks in retail. The Service Industries Journal, 33(2), 248-265. doi:10.1080/02642069.2011.614346   DOI
45 McDuff, D., & Czerwinski, M. (2018). Designing emotionally sentient agents. Communications of the ACM, 61(12), 74-83. doi:10.1145/3186591   DOI
46 Novak, T. P., & Hoffman, D. L. (2019). Relationship journeys in the internet of things - A new framework for understanding interactions between consumers and smart objects. Journal of the Academy of Marketing Science, 47(2), 216-237. doi:10.1007/s11747-018-0608-3   DOI
47 Gardner, M. P. (1985). Mood states and consumer behavior - A critical review. Journal of Consumer Research, 12(3), 281-300. doi:10.1086/208516   DOI
48 Meyer-Waarden, L., Pavone, G., Poocharoentou, T., Prayatsup, P., Ratinaud, M., Tison, A., & Torne, S. (2020). How service quality influences customer acceptance and usage of chatbots. SMR-Journal of Service Management Research, 4(1), 35-51. doi:10.15358/2511-8676-2020-1-35   DOI
49 Jeong, S. G., Hur, H. J., & Choo, H. J. (2020). The effect of fashion shopping chatbot characteristics on service acceptance intention - Focusing on anthropomorphism and personalization-. Journal of the Korean Society of Clothing and Textiles, 44(4), 573-593. doi:10.5850/JKSCT.2020.44.4.573   DOI
50 Kim, A., Cho, M., Ahn, J., & Sung, Y. (2019). Effects of gender and relationship type on the response to artificial intelligence. Cyberpsychology, Behavior and Social Networking, 22(4), 249-253. doi:10.1089/cyber.2018.0581   DOI
51 Meuter, M. L., Ostrom, A. L., Bitner, M. J., & Roundtree, R. (2003). The influence of technology anxiety on consumer use and experiences with self-service technologies. Journal of Business Research, 56(11), 899-906. doi:10.1016/S0148-2963(01)00276-4   DOI
52 Stroessner, S. J., & Benitez, J. (2019). The social perception of humanoid and non-humanoid robots - Effects of gendered and machinelike features. International Journal of Social Robotics, 11(2), 305-315. doi:10.1007/s12369-018-0502-7   DOI
53 Lee, H. (2018). A study on the optimal interaction for robot personification - Focusing on home service robots. Unpublished master's thesis, Ewha Womans University, Seoul.
54 Lee, H., & Leonas, K. K. (2021). Millennials' intention to use self-checkout technology in different fashion retail formats - Perceived benefits and risks. Clothing and Textiles Research Journal, 39(4), 264-280. doi:10.1177/0887302X20926577   DOI
55 Lee, S. K., & Yun, J. Y. (2019). A convergence study on chatbot persona and user experience of financial service - Focused on loan service. The Korean society of Science & Art, 37(4), 257-267. doi:10.17548/ksaf.2019.09.30.257   DOI
56 Mende, M., Scott, M. L., van Doorn, J., Grewal, D., & Shanks, I. (2019). Service robots rising - How humanoid robots influence service experiences and elicit compensatory consumer responses. Journal of Marketing Research, 56(4), 535-556. doi:10.1177/0022243718822827   DOI
57 Wilson, E. J., & Sherrell, D. L. (1993). Source effects in communication and persuasion research: A meta-analysis of effect size. Journal of the Academy of Marketing Science, 21(2), 101-112. doi:10.1007/BF02894421   DOI
58 Bartneck, C., Kulic, D., Croft, E., & Zoghbi, S. (2009). Measurement instruments for the anthropomorphism, animacy, likeability, perceived intelligence, and perceived safety of robots. International Journal of Social Robotics, 1(1), 71-81. doi:10.1007/s12369-008-0001-3   DOI
59 van Doorn, J., Mende, M., Noble, S. M., Hulland, J., Ostrom, A. L., Grewal, D., & Petersen, J. A. (2017). Domo arigato Mr. Roboto - Emergence of automated social presence in organizational frontlines and customers' service experiences. Journal of Service Research, 20(1), 43-58. doi:10.1177/1094670516679272   DOI
60 van Pinxteren, M. M. E., Ruud, W. H., Wetzels, J. R., Pluymaekers, M., & Wetzels, M. (2019). Trust in humanoid robots: implications for services marketing. Journal of Services Marketing, 33(4), 507-518. doi:10.1007/s11747-020-00762-y   DOI
61 Wirtz, J., Patterson, P. G., Kunz, W. H., Gruber, T., Lu, V. N., Paluch, S., & Martins, A. (2018). Brave new world - Service robots in the frontline. Journal of Service Management, 29(50), 907-931. doi:10.1108/JOSM-04-2018-0119   DOI
62 Wright, P. L. (1973). The cognitive processes mediating acceptance of advertising. Journal of Marketing Research, 10(1), 53-62. doi:10.2307/3149409   DOI
63 Bolton, R. N., McColl-Kennedy, J. R., Cheung, L., Gallan, A., Orsingher, C., Witell, L., & Zaki, M. (2018). Customer experience challenges. Journal of Service Management, 29(5), 776-808. doi:10.1108/JOSM-04-2018-0113   DOI
64 Miao, F., Kozlenkova, I. V., Wang, H., Xie, T., & Palmatier, R. W. (2022). An emerging theory of avatar marketing. Journal of Marketing, 86(1), 67-90. doi:10.1177/0022242921996646   DOI
65 Mori, M. (1970). The uncanny valley. Energy, 7(4), 33-35.
66 Korolov, M. (2021, October 12). "2028년까지 연 35%씩 성장"... 꼭 알아야 할 'AI 챗봇' 상식 ["Growth 35% per year by 2028" ... common sense of 'AI Chatbot' that you must know]. CIO Korea. Retrieved March 12, 2022, from https://www.ciokorea.com/news/210374
67 Bitner, M. J., Booms, B. H., & Tetreault, M. S. (1990). The service encounter - Diagnosing favorable and unfavorable incidents. Journal of Marketing, 54(1), 71-84. doi:10.1177/002224299005400105   DOI
68 Yoon, Y. (2021). Prospects of using AI chabots in teaching speaking in primary English - With special reference to dialogflow. The Journal of Korea Elementary Education, 32, 15-28. doi:10.20972/kjee.32..202107.15   DOI
69 Anselmsson, J. (2001). Customer-perceived service quality and technology-based self-service. Unpublished doctoral dissertation, Lurid University, Lund
70 Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research - Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173-1182. doi:10.1037/0022-3514.51.6.1173   DOI
71 Blut, M., Wang, C., & Schoefer, K. (2016). Factors influencing the acceptance of self-service technologies - A meta-analysis. Journal of Service Research, 19(4), 396-416. doi:10.1177/1094670516662352   DOI
72 Bohner, G. & Wanke, M. (2002), Attitudes and Attitude Change. New York, NY: Psychology Press Ltd.
73 Lee, J. M., Jung, M., Lee, J., Kim, Y. E., & An, C. (2019). Consumer perception and adoption intention of artificial intelligent speaker - Non-users perspective. Journal of Consumer Studies, 30(2), 193-213. doi:10.35736/JCS.30.2.9   DOI
74 Youn, S., & Kim, S. (2019). Understanding ad avoidance on Facebook - Antecedents and outcomes of psychological reactance. Computers in Human Behavior, 98, 232-244. doi:10.1016/j.chb.2019.04.025   DOI
75 Choi, M. Y. (2021). The effect of personalized product recommendation service of online fashion shopping mall on service use behaviors through cognitive attitude and emotional attachment. Fashion and Textile Research Journal, 23(5), 586-597. doi.org/10.5805/SFTI.2021.23.5.586   DOI
76 Dabholkar, P. A. (1996). Consumer evaluations of new technology-based self-service options - An investigation of alternative models of service quality. International Journal of Research in Marketing, 13(1), 29-51. doi:10.1016/0167-8116(95)00027-5   DOI
77 Canning, C., Donahue, T. J., & Scheutz, M. (2014). Investigating human perceptions of robot capabilities in remote human-robot team tasks based on first-person robot video feeds. Proceedings of 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, USA, pp.4354-4361. doi:10.1109/IROS.2014.6943178.   DOI
78 Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982-1003. doi: 10.1287/mnsc.35.8.982   DOI
79 Fernandes, T., & Pedroso, R. (2017). The effect of selfcheckout quality on customer satisfaction and repatronage in a retail context. Service Business, 11(1), 69-92. doi:10.1007/s11628-016-0302-9   DOI
80 Byun, S. H., & Cho, C. H. (2020). The effect of the anthropomorphism level and personalization level on AI financial chatbot recommendation messages on customer response. The Korean Journal of Advertising and Public Relations, 22(2), 466-502. doi:10.16914/kadpr.2020.22.2.466   DOI
81 Zeithaml, V. A., & Gilly, M. C. (1987). Characteristics affecting the acceptance of retailing technologies - A comparison of elderly and nonelderly consumers. Journal of Retailing, 63(1), 49-68.
82 Zajonc, R. B. (1980). Feeling and thinking - Preferences need no inferences. American Psychologist, 35(2), 151-175. doi: 10.1037/0003-066X.35.2.151   DOI