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Research Article

Does Beauty Matter to Service Consumers? The Influence of Visual Appeal on Self-Service Technology (SST) Acceptance

Received 18 Dec 2023, Accepted 16 May 2024, Published online: 04 Jun 2024

References

  • Ahn, T., Ryu, S., & Han, I. (2007). The impact of Web quality and playfulness on user acceptance of online retailing. Information & Management, 44(3), 263–275. https://doi.org/10.1016/j.im.2006.12.008
  • Ajzen, I. (2006). Behavioral interventions based on the theory of planned behavior. tpb.intervention (umass.edu).
  • Ali, I., & Warraich, N. F. (2024). Meta-analysis of technology acceptance for mobile and digital libraries in academic settings using technology acceptance model (TAM). Global Knowledge, Memory and Communication, https://doi.org/10.1108/GKMC-09-2023-0360
  • Baron, J. (2006). Thinking and deciding. Cambridge University Press.
  • Berlyne, D. E. (1970). Novelty, complexity, and hedonic value. Perception & Psychophysics, 8(5), 279–286. https://doi.org/10.3758/BF03212593
  • Blut, M., Chowdhry, N., Mittal, V., & Brock, C. (2015). E-service quality: A meta-analytic review. Journal of Retailing, 91(4), 679–700. https://doi.org/10.1016/j.jretai.2015.05.004
  • 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. https://doi.org/10.1177/1094670516662352
  • Blut, M., Wang, C., Wünderlich, 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. https://doi.org/10.1007/s11747-020-00762-y
  • Bollen, K. A., & Pearl, J. (2013). Eight myths about causality and structural equation models. In Handbook of causal analysis for social research (pp. 301–328). Springer.
  • Bonnardel, N., Piolat, A., & Le Bigot, L. (2011). The impact of colour on website appeal and users’ cognitive processes. Displays, 32(2), 69–80. https://doi.org/10.1016/j.displa.2010.12.002
  • Cheung, M. W. (2009). Constructing approximate confidence intervals for parameters with structural equation models. Structural Equation Modeling: A Multidisciplinary Journal, 16(2), 267–294. https://doi.org/10.1080/10705510902751291
  • Cheung, M. W. (2015). Meta-analysis: A structural equation modeling approach. John Wiley & Sons.
  • Cheung, M. W., & Chan, W. (2005). Meta-analytic structural equation modeling: A two-stage approach. Psychological Methods, 10(1), 40–64. https://doi.org/10.1037/1082-989X.10.1.40
  • Chuan-Peng, H., Huang, Y., Eickhoff, S. B., Peng, K., & Sui, J. (2020). Seeking the “beauty center” in the brain: A meta-analysis of fMRI studies of beautiful human faces and visual art. Cognitive, Affective & Behavioral Neuroscience, 20(6), 1200–1215. https://doi.org/10.3758/s13415-020-00827-z
  • 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. https://doi.org/10.1287/mnsc.35.8.982
  • De Ruyter, K., Wetzels, M., & Kleijnen, M. (2001). Customer adoption of e‐service: An experimental study. International Journal of Service Industry Management, 12(2), 184–207. https://doi.org/10.1108/09564230110387542
  • DeLone, W. H., & McLean, E. R. (1992). Information systems success: The quest for the dependent variable. Information Systems Research, 3(1), 60–95. https://doi.org/10.1287/isre.3.1.60
  • 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. https://doi.org/10.1080/07421222.2003.11045748
  • Doulani, A. (2018). An assessment of effective factors in technology acceptance model: A meta-analysis study. Journal of Scientometric Research, 7(3), 153–166. https://doi.org/10.5530/jscires.7.3.26
  • Franque, F. B., Oliveira, T., Tam, C., & Santini, F. d O. (2021). A meta-analysis of the quantitative studies in continuance intention to use an information system. Internet Research, 31(1), 123–158. https://doi.org/10.1108/INTR-03-2019-0103
  • Galbraith, R. F. (1988). Graphical display of estimates having differing standard errors. Technometrics, 30(3), 271–281. https://doi.org/10.1080/00401706.1988.10488400
  • Gendolla, G. H. (2017). Comment: Do emotions influence action?–Of course, they are hypo-phenomena of motivation. Emotion Review, 9(4), 348–350. https://doi.org/10.1177/1754073916673211
  • Ghosh, M. (2024). Meta-analytic review of online purchase intention: Conceptualising the study variables. Cogent Business & Management, 11(1), 2296686. https://doi.org/10.1080/23311975.2023.2296686
  • Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2014). Multivariate data analysis: Pearson new international (7th ed.). Pearson.
  • Hoegg, J., & Alba, J. W. (2008). A role for aesthetics in consumer psychology. In C. P. Haugtvedt, P. M. Herr & F. R. Kardes (Eds.), Handbook of consumer psychology (pp. 733–754). Taylor & Francis Group.
  • Huh, Y. U., Keller, F. R., Redman, T. C., & Watkins, A. R. (1990). Data quality. Information and Software Technology, 32(8), 559–565. https://doi.org/10.1016/0950-5849(90)90146-I
  • Hunter, J. E., & Schmidt, F. L. (2004). Methods of meta-analysis: Correcting error and bias in research findings. Sage.
  • Ingham, J., & Cadieux, J. (2016). From E-shopping system quality to the consumer’s intention to return: A meta-analytic study of the mediation of attitude, usefulness, enjoyment, and trust [Paper presentation]. 2016 49th Hawaii International Conference on System Sciences (HICSS) (pp. 3556–3564). https://doi.org/10.1109/HICSS.2016.445
  • ISO 9241-11. (2018). Ergonomics of human-system interaction. Part 11: Definitions and concepts. ISO 9241-11.
  • Jak, S. (2015). Meta-analytic structural equation modelling. Springer.
  • Jiang, Z., Wang, W., Tan, B. C., & Yu, J. (2016). The determinants and impacts of aesthetics in users’ first interaction with websites. Journal of Management Information Systems, 33(1), 229–259. https://doi.org/10.1080/07421222.2016.1172443
  • Kawabata, H., & Zeki, S. (2004). Neural correlates of beauty. Journal of Neurophysiology, 91(4), 1699–1705. https://doi.org/10.1152/jn.00696.2003
  • Kim, H. (2019). Trustworthiness of unmanned automated subway services and its effects on passengers’ anxiety and fear. Transportation Research Part F: Traffic Psychology and Behaviour, 65, 158–175. https://doi.org/10.1016/j.trf.2019.07.014
  • Kim, H. (2021). Service design for public transportation to address the issue of females’ fear of crime. Transportation, 48(1), 167–192. https://doi.org/10.1007/s11116-019-10043-5
  • Kim, J., Fiore, A. M., & Lee, H. (2007). Influences of online store perception, shopping enjoyment, and shopping involvement on consumer patronage behavior towards an online retailer. Journal of Retailing and Consumer Services, 14(2), 95–107. https://doi.org/10.1016/j.jretconser.2006.05.001
  • Lavie, T., & Tractinsky, N. (2004). Assessing dimensions of perceived visual aesthetics of web sites. International Journal of Human-Computer Studies, 60(3), 269–298. https://doi.org/10.1016/j.ijhcs.2003.09.002
  • Lee, C., & Coughlin, J. F. (2015). PERSPECTIVE: Older adults’ adoption of technology: An integrated approach to identifying determinants and barriers. Journal of Product Innovation Management, 32(5), 747–759. https://doi.org/10.1111/jpim.12176
  • Lindgaard, G., Fernandes, G., Dudek, C., & Brown, J. (2006). Attention web designers: You have 50 milliseconds to make a good first impression!. Behaviour & Information Technology, 25(2), 115–126. https://doi.org/10.1080/01449290500330448
  • Magsamen, S. (2019). Your brain on art: The case for neuroaesthetics [Paper presentation]. Cerebrum: The Dana Forum on Brain Science, 2019.
  • Martindale, C. (1988). Aesthetics, psychobiology, and cognition. In F. Farley & R. Neperud (Eds.), The foundations of aesthetics, art, and art education (pp. 7–42). Praeger.
  • Martínez-López, F. J., Pla-García, C., Gázquez-Abad, J. C., & Rodríguez-Ardura, I. (2016). Hedonic motivations in online consumption behaviour. International Journal of Business Environment, 8(2), 121–151. https://doi.org/10.1504/IJBE.2016.076628
  • McDougall, S. J., & Reppa, I. (2008). Why do I like it? The relationships between icon characteristics, user performance and aesthetic appeal. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 52(18), 1257–1261. https://doi.org/10.1177/154193120805201822
  • Meuter, M. L., Ostrom, A. L., Roundtree, R. I., & Bitner, M. J. (2000). Self-service technologies: Understanding customer satisfaction with technology-based service encounters. Journal of Marketing, 64(3), 50–64. https://doi.org/10.1509/jmkg.64.3.50.18024
  • Moher, D., Liberati, A., Tetzlaff, J., & Altman, D. G, PRISMA Group*. (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. Annals of Internal Medicine, 151(4), 264–269, W64. https://doi.org/10.7326/0003-4819-151-4-200908180-00135
  • Nelson, R. R., Todd, P. A., & Wixom, B. H. (2005). Antecedents of information and system quality: An empirical examination within the context of data warehousing. Journal of Management Information Systems, 21(4), 199–235. https://doi.org/10.1080/07421222.2005.11045823
  • Nickerson, R. S. (1998). Confirmation bias: A ubiquitous phenomenon in many guises. Review of General Psychology, 2(2), 175–220. https://doi.org/10.1037/1089-2680.2.2.175
  • Norman, D. (2013). The design of everyday things (Revised and expanded edition). Basic Books.
  • Palmer, S. E., & Griscom, W. S. (2013). Accounting for taste: Individual differences in preference for harmony. Psychonomic Bulletin & Review, 20(3), 453–461. https://doi.org/10.3758/s13423-012-0355-2
  • Palmer, S. E., Schloss, K. B., & Sammartino, J. (2013). Visual aesthetics and human preference. Annual Review of Psychology, 64(1), 77–107. https://doi.org/10.1146/annurev-psych-120710-100504
  • Pantano, E., & Priporas, C. (2016). The effect of mobile retailing on consumers’ purchasing experiences: A dynamic perspective. Computers in Human Behavior, 61, 548–555. https://doi.org/10.1016/j.chb.2016.03.071
  • Peterson, R. A., & Brown, S. P. (2005). On the use of beta coefficients in meta-analysis. The Journal of Applied Psychology, 90(1), 175–181. https://doi.org/10.1037/0021-9010.90.1.175
  • Prescient & Strategic Intelligence (2022). Self-service technology market to generate revenue worth $76.78 billion by 2030. https://www.psmarketresearch.com/press-release/self-service-technology-market
  • Rai, A., Lang, S. S., & Welker, R. B. (2002). Assessing the validity of IS success models: An empirical test and theoretical analysis. Information Systems Research, 13(1), 50–69. https://doi.org/10.1287/isre.13.1.50.96
  • Rana, N. P., Dwivedi, Y. K., Williams, M. D., & Weerakkody, V. (2015). Investigating success of an e-government initiative: Validation of an integrated IS success model. Information Systems Frontiers, 17(1), 127–142. https://doi.org/10.1007/s10796-014-9504-7
  • Reber, R., Schwarz, N., & Winkielman, P. (2004). Processing fluency and aesthetic pleasure: Is beauty in the perceiver’s processing experience? Personality and Social Psychology Review: An Official Journal of the Society for Personality and Social Psychology, Inc, 8(4), 364–382. https://doi.org/10.1207/s15327957pspr0804_3
  • Reppa, I., & McDougall, S. (2022). Aesthetic appeal influences visual search performance. Attention, Perception & Psychophysics, 84(8), 2483–2506. https://doi.org/10.3758/s13414-022-02567-3
  • Rosenberg, M. S. (2005). The file‐drawer problem revisited: A general weighted method for calculating fail‐safe numbers in meta‐analysis. Evolution, 59(2), 464–468. https://doi.org/10.1554/04-602
  • Salloum, S. A., Alhamad, A. Q. M., Al-Emran, M., Monem, A. A., & Shaalan, K. (2019). Exploring students’ acceptance of e-learning through the development of a comprehensive technology acceptance model. IEEE Access, 7, 128445–128462. https://doi.org/10.1109/ACCESS.2019.2939467
  • Sarkar, S., Chauhan, S., & Khare, A. (2020). A meta-analysis of antecedents and consequences of trust in mobile commerce. International Journal of Information Management, 50, 286–301. https://doi.org/10.1016/j.ijinfomgt.2019.08.008
  • Scarantino, A. (2017). Do emotions cause actions, and if so how? Emotion Review, 9(4), 326–334. https://doi.org/10.1177/1754073916679005
  • Seddon, P. B. (1997). A respecification and extension of the DeLone and McLean model of IS success. Information Systems Research, 8(3), 240–253. https://doi.org/10.1287/isre.8.3.240
  • Shen, Y., Xu, W., Liang, A., Wang, X., Lu, X., Lu, Z., & Gao, C. (2022). Online health management continuance and the moderating effect of service type and age difference: A meta-analysis. Health Informatics Journal, 28(3), 14604582221119950. https://doi.org/10.1177/14604582221119950
  • Sonderegger, A., & Sauer, J. (2010). The influence of design aesthetics in usability testing: Effects on user performance and perceived usability. Applied Ergonomics, 41(3), 403–410. https://doi.org/10.1016/j.apergo.2009.09.002
  • Street, N., Forsythe, A. M., Reilly, R., Taylor, R., & Helmy, M. S. (2016). A complex story: Universal preference vs. individual differences shaping aesthetic response to fractals patterns. Frontiers in Human Neuroscience, 10, 213. https://doi.org/10.3389/fnhum.2016.00213
  • Tuch, A. N., Presslaber, E. E., Stöcklin, M., Opwis, K., & Bargas-Avila, J. A. (2012). The role of visual complexity and prototypicality regarding first impression of websites: Working towards understanding aesthetic judgments. International Journal of Human-Computer Studies, 70(11), 794–811. https://doi.org/10.1016/j.ijhcs.2012.06.003
  • Ullman, J. B. (2018). Structural equation modeling. In Using multivariate statistics (6th ed., pp. 731–836). Pearson.
  • Van der Geest, T., & Van Dongelen, R. (2009). What is beautiful is useful-visual appeal and expected information quality [Paper presentation]. 2009 IEEE International Professional Communication Conference, 1–5.
  • Venkatesh, V. (2000). Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information Systems Research, 11(4), 342–365. https://doi.org/10.1287/isre.11.4.342.11872
  • Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273–315. https://doi.org/10.1111/j.1540-5915.2008.00192.x
  • Venkatesh, V., & Davis, F. D. (1996). A model of the antecedents of perceived ease of use: Development and test. Decision Sciences, 27(3), 451–481. https://doi.org/10.1111/j.1540-5915.1996.tb00860.x
  • Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204. https://doi.org/10.1287/mnsc.46.2.186.11926
  • Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 3, 27, 425–478. https://doi.org/10.2307/30036540
  • Venkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 1, 36, 157–178. https://doi.org/10.2307/41410412
  • Wolfe, J. M., & Horowitz, T. S. (2017). Five factors that guide attention in visual search. Nature Human Behaviour, 1(3), 0058. https://doi.org/10.1038/s41562-017-0058
  • Wu, W., Lee, C., Fu, C., & Wang, H. (2013). How can online store layout design and atmosphere influence consumer shopping intention on a website? International Journal of Retail & Distribution Management, 42(1), 4–24. https://doi.org/10.1108/IJRDM-01-2013-0035
  • Xiang, L., Zheng, X., Lee, M. K., & Zhao, D. (2016). Exploring consumers’ impulse buying behavior on social commerce platform: The role of parasocial interaction. International Journal of Information Management, 36(3), 333–347. https://doi.org/10.1016/j.ijinfomgt.2015.11.002
  • Xu, J., Benbasat, I., & Cenfetelli, R. T. (2013). Integrating service quality with system and information quality: An empirical test in the e-service context. MIS Quarterly, 37(3), 777–794. https://doi.org/10.25300/MISQ/2013/37.3.05
  • Zhang, H., Lu, Y., Wang, B., & Wu, S. (2015). The impacts of technological environments and co-creation experiences on customer participation. Information & Management, 52(4), 468–482. https://doi.org/10.1016/j.im.2015.01.008

Studies Used for the Meta-Analysis

  • Abu-Taieh, E. M., AlHadid, I., Abu-Tayeh, S., Masa’deh, R., Alkhawaldeh, R. S., Khwaldeh, S., & Alrowwad, A. (2022). Continued intention to use of M-banking in Jordan by integrating UTAUT, TPB, TAM and service quality with ML. Journal of Open Innovation: Technology, Market, and Complexity, 8(3), 120. https://doi.org/10.3390/joitmc8030120
  • Alalwan, A. A., Dwivedi, Y. K., & Rana, N. P. (2017). Factors influencing adoption of mobile banking by Jordanian bank customers: Extending UTAUT2 with trust. International Journal of Information Management, 37(3), 99–110. https://doi.org/10.1016/j.ijinfomgt.2017.01.002
  • Alalwan, A. A., Dwivedi, Y. K., Rana, N. P., & Algharabat, R. (2018). Examining factors influencing Jordanian customers’ intentions and adoption of internet banking: Extending UTAUT2 with risk. Journal of Retailing and Consumer Services, 40, 125–138. https://doi.org/10.1016/j.jretconser.2017.08.026
  • Al-Debei, M. M. (2014). The quality and acceptance of websites: An empirical investigation in the context of higher education. International Journal of Business Information Systems, 15(2), 170–188. https://doi.org/10.1504/IJBIS.2014.059252
  • Al‐hawari, M. A., & Mouakket, S. (2010). The influence of technology acceptance model (TAM) factors on students’e‐satisfaction and e‐retention within the context of UAE e‐learning. Education, Business and Society: Contemporary Middle Eastern Issues, 3(4), 299–314. https://doi.org/10.1108/17537981011089596
  • Alqahtani, H., Kavakli, M., & Sheikh, N. U. (2018). Analysis of the technology acceptance theoretical model in examining users’ Behavioural intention to use an augmented reality app (IMAPCampus). International Journal of Engineering and Management Research, 8(5), 37–49. https://doi.org/10.31033/ijemr.8.5.6
  • An, J. (2005). Correlates and predictors of consumers’ health information and services usage behavior on the internet: A structural equation modeling approach. New York University.
  • Arenas Gaitán, J., Peral Peral, B., Jerónimo, R., & A, M. (2015). Elderly and internet banking: An application of UTAUT2. Journal of Internet Banking and Commerce, 20(1), 1–23.
  • Bashir, I., & Madhavaiah, C. (2015). Consumer attitude and behavioural intention towards Internet banking adoption in India. Journal of Indian Business Research, 7(1), 67–102. https://doi.org/10.1108/JIBR-02-2014-0013
  • Chang, C., Liang, C., Yan, C., & Tseng, J. (2013). The impact of college students’ intrinsic and extrinsic motivation on continuance intention to use English mobile learning systems. The Asia-Pacific Education Researcher, 22(2), 181–192. https://doi.org/10.1007/s40299-012-0011-7
  • Chen, C., Shih, B., & Yu, S. (2012). Disaster prevention and reduction for exploring teachers’ technology acceptance using a virtual reality system and partial least squares techniques. Natural Hazards, 62(3), 1217–1231. https://doi.org/10.1007/s11069-012-0146-0
  • Cheng, Y. (2012a). Effects of quality antecedents on e‐learning acceptance. Internet Research, 22(3), 361–390. https://doi.org/10.1108/10662241211235699
  • Cheng, Y. (2012b). The effects of information systems quality on nurses’ acceptance of the electronic learning system. The Journal of Nursing Research: JNR, 20(1), 19–30. https://doi.org/10.1097/JNR.0b013e31824777aa
  • Chiu, C., Chang, C., Cheng, H., & Fang, Y. (2009). Determinants of customer repurchase intention in online shopping. Online Information Review, 33(4), 761–784. https://doi.org/10.1108/14684520910985710
  • Collier, J. E. (2006). Examining customers’ intentions to use self-service technology through utilitarian and hedonic value judgments. Retrieved May 12, 2021, from http:// search proquest.co /docview /304910318?accountid = 5027.
  • Collier, J. E., L. Sherrell, D., Babakus, E., & Blakeney Horky, A. (2014). Understanding the differences of public and private self-service technology. Journal of Services Marketing, 28(1), 60–70. https://doi.org/10.1108/JSM-04-2012-0071
  • Demoulin, N. T., & Djelassi, S. (2016). An integrated model of self-service technology (SST) usage in a retail context. International Journal of Retail & Distribution Management, 44(5), 540–559. https://doi.org/10.1108/IJRDM-08-2015-0122
  • Duarte, P., Silva, S. C., Linardi, M. A., & Novais, B. (2022). Understanding the implementation of retail self-service check-out technologies using necessary condition analysis. International Journal of Retail & Distribution Management, 50(13), 140–163. https://doi.org/10.1108/IJRDM-05-2022-0164
  • Fearnley, M. R., & Amora, J. T. (2020). Learning management system adoption in higher education using the extended technology acceptance model. IAFOR Journal of Education, 8(2), 89–106. https://doi.org/10.22492/ije.8.2.05
  • Gupta, G., Zaidi, S. K., Udo, G., & Bagchi, K. (2015). The influence of theory of planned behavior, technology acceptance model, and information system success model on the acceptance of electronic tax filing system in an emerging economy. The International Journal of Digital Accounting Research. https://doi.org/10.4192/1577-8517-v15_6
  • Ha Rajak, A. N., Pg Abu Bakar, D. N. N., Lajim, N. D. A., Haji Kamarulzaman, N. H. S., Haji Karim, S. N. F., & Almunawar, M. N. (2018). E-learning services acceptance in higher educational institutes: A case study in Brunei. Education and Information Technologies, 23(6), 2341–2361. https://doi.org/10.1007/s10639-018-9720-8
  • Hubert, M., Blut, M., Brock, C., Backhaus, C., & Eberhardt, T. (2017). Acceptance of smartphone‐based mobile shopping: Mobile benefits, customer characteristics, perceived risks, and the impact of application context. Psychology & Marketing, 34(2), 175–194. https://doi.org/10.1002/mar.20982
  • Human, G., Ungerer, M., & Azémia, J. J. (2020). Mauritian consumer intentions to adopt online grocery shopping: An extended decomposition of UTAUT2 with moderation. Management Dynamics: Journal of the Southern African Institute for Management Scientists, 29(3), 15–37.
  • Ji, Z., Yang, Z., Liu, J., & Yu, C. (2019). Investigating users’ continued usage intentions of online learning applications. Information, 10(6), 198. https://doi.org/10.3390/info10060198
  • Kim, J., & Forsythe, S. (2010). Adoption of dynamic product imagery for online shopping: Does age matter? The International Review of Retail, Distribution and Consumer Research, 20(4), 449–467. https://doi.org/10.1080/09593969.2010.504011
  • Kwangsawad, A., & Jattamart, A. (2022). Overcoming customer innovation resistance to the sustainable adoption of chatbot services: A community-enterprise perspective in Thailand. Journal of Innovation & Knowledge, 7(3), 100211. https://doi.org/10.1016/j.jik.2022.100211
  • Lee, H. (2008). Technology-based self-service kiosks in retailing: An optional channel for customer service. Tennessee Research and Creative Exchange.
  • Lee, H., & Lyu, J. (2019). Exploring factors which motivate older consumers’ self-service technologies (SSTs) adoption. The International Review of Retail, Distribution and Consumer Research, 29(2), 218–239. https://doi.org/10.1080/09593969.2019.1575261
  • Li, Q. (2020). Healthcare at your fingertips: The acceptance and adoption of mobile medical treatment services among chinese users. International Journal of Environmental Research and Public Health, 17(18), 6895. https://doi.org/10.3390/ijerph17186895
  • Lian, J. (2021). Why is self-service technology (SST) unpopular? Extending the IS success model. Library Hi Tech, 39(4), 1154–1173. https://doi.org/10.1108/LHT-01-2018-0015
  • Liao, C., To, P., Liu, C., Kuo, P., & Chuang, S. (2011). Factors influencing the intended use of web portals. Online Information Review, 35(2), 237–254. https://doi.org/10.1108/14684521111128023
  • Lin, P., Liang, T., Huang, H., & Li, Y. (2021). Design quality, relationship intimacy and continuance intention of mobile apps: An extension to the IS success model. Journal of Electronic Commerce Research, 22(4), 266–284.
  • Mclean, G., & Osei-Frimpong, K. (2019). Chat now… Examining the variables influencing the use of online live chat. Technological Forecasting and Social Change, 146(4), 55–67. https://doi.org/10.1016/j.techfore.2019.05.017
  • Moghavvemi, S., Paramanathan, T., Rahin, N. M., & Sharabati, M. (2017). Student’s perceptions towards using e-learning via Facebook. Behaviour & Information Technology, 36(10), 1081–1100. https://doi.org/10.1080/0144929X.2017.1347201
  • Mosquera, A., Juaneda-Ayensa, E., Olarte-Pascual, C., & Pelegrín-Borondo, J. (2018). Key factors for in-store smartphone use in an omnichannel experience: Millennials vs. nonmillennials. Complexity, (2018), 1–14. https://doi.org/10.1155/2018/1057356
  • Nazari-Shirkouhi, S., Badizadeh, A., Dashtpeyma, M., & Ghodsi, R. (2023). A model to improve user acceptance of e-services in healthcare systems based on technology acceptance model: An empirical study. Journal of Ambient Intelligence and Humanized Computing, 14(6), 7919–7935. https://doi.org/10.1007/s12652-023-04601-0
  • Oh, S. H., Kim, Y. M., Lee, C. W., Shim, G. Y., Park, M. S., & Jung, H. S. (2009). Consumer adoption of virtual stores in Korea: Focusing on the role of trust and playfulness. Psychology & Marketing, 26(7), 652–668. https://doi.org/10.1002/mar.20293
  • Pai, C., Wu, Z., Lee, S., Lee, J., & Kang, S. (2022). Service quality of social media-based self-service technology in the food service context. Sustainability, 14(20), 13483. https://doi.org/10.3390/su142013483
  • Park, J., Ha, S., & Jeong, S. W. (2021). Consumer acceptance of self-service technologies in fashion retail stores. Journal of Fashion Marketing and Management: An International Journal, 25(2), 371–388. https://doi.org/10.1108/JFMM-09-2019-0221
  • Puriwat, W., & Tripopsakul, S. (2017). Mobile banking adoption in Thailand: An integration of technology acceptance model and mobile service quality. University of Piraeus. International Strategic Management Association.
  • Rauniar, R., Rawski, G., Yang, J., & Johnson, B. (2014). Technology acceptance model (TAM) and social media usage: An empirical study on Facebook. Journal of Enterprise Information Management, 27(1), 6–30. https://doi.org/10.1108/JEIM-04-2012-0011
  • Robertson, N., McDonald, H., Leckie, C., & McQuilken, L. (2016). Examining customer evaluations across different self-service technologies. Journal of Services Marketing, 30(1), 88–102. https://doi.org/10.1108/JSM-07-2014-0263
  • Şahin, F., & Şahin, Y. L. (2021). Examining the acceptance of e-learning systems during the pandemic: The role of compatibility, enjoyment and anxiety. International Technology and Education Journal, 5(1), 1–10.
  • Saplan, V. J. G., & Park, T. (2011). Analysis of mobile commerce usage in Korea. Logos Management Review, 9(3), 27–50.
  • Saprikis, V., Avlogiaris, G., & Katarachia, A. (2022). A comparative study of users versus non-users’ behavioral intention towards M-banking apps’ adoption. Information, 13(1), 30. https://doi.org/10.3390/info13010030
  • Saprikis, V., Markos, A., Zarmpou, T., & Vlachopoulou, M. (2018). Mobile shopping consumers’ behavior: An exploratory study and review. Journal of Theoretical and Applied Electronic Commerce Research, 13(1), 71–90. https://doi.org/10.4067/S0718-18762018000100105
  • Sharif, A., Afshan, S., & Qureshi, M. A. (2019). Acceptance of learning management system in university students: An integrating framework of modified UTAUT2 and TTF theories. International Journal of Technology Enhanced Learning, 11(2), 201–229. https://doi.org/10.1504/IJTEL.2019.098810
  • Shin, J. I., Chung, K. H., Oh, J. S., & Lee, C. W. (2013). The effect of site quality on repurchase intention in Internet shopping through mediating variables: The case of university students in South Korea. International Journal of Information Management, 33(3), 453–463. https://doi.org/10.1016/j.ijinfomgt.2013.02.003
  • Shyu, S. H., & Huang, J. (2011). Elucidating usage of e-government learning: A perspective of the extended technology acceptance model. Government Information Quarterly, 28(4), 491–502. https://doi.org/10.1016/j.giq.2011.04.002
  • Terzis, V., Moridis, C. N., Economides, A. A., & Mendez, G. R. (2013). Computer based assessment acceptance: A cross-cultural study in Greece and Mexico. Journal of Educational Technology & Society, 16(3), 411–424.
  • Tsai, T., Lin, W., Chang, Y., Chang, P., & Lee, M. (2020). Technology anxiety and resistance to change behavioral study of a wearable cardiac warming system using an extended TAM for older adults. PloS One, 15(1), e0227270. https://doi.org/10.1371/journal.pone.0227270
  • Wang, C. (2017). Consumer acceptance of self-service technologies: An ability–willingness model. International Journal of Market Research, 59(6), 787–802. https://doi.org/10.2501/IJMR-2017-048
  • Wang, K., & Lin, C. (2012). The adoption of mobile value‐added services: Investigating the influence of IS quality and perceived playfulness. Managing Service Quality: An International Journal, 22(2), 184–208. https://doi.org/10.1108/09604521211219007
  • Wixom, B. H., & Todd, P. A. (2005). A theoretical integration of user satisfaction and technology acceptance. Information Systems Research, 16(1), 85–102. https://doi.org/10.1287/isre.1050.0042

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