User Experience (UX) with Mobile Devices: A Comprehensive Model to Demonstrate the Relative Importance of Instrumental, Non-Instrumental, and Emotional Components on User Satisfaction

References

• Al-Emran, M. (2021). Evaluating the use of smartwatches for learning purposes through the integration of the technology acceptance model and task-technology fit. International Journal of Human–Computer Interaction, 37(19), 1874–1882. https://doi.org/10.1080/10447318.2021.1921481
   Web of Science ®Google Scholar
• Al-Emran, M., Al-Maroof, R., Al-Sharafi, M. A., & Arpaci, I. (2022). What impacts learning with wearables? An integrated theoretical model. Interactive Learning Environments, 30(10), 1897–1917. https://doi.org/10.1080/10494820.2020.1753216
   Web of Science ®Google Scholar
• Andone, I., Błaszkiewicz, K., Eibes, M., Trendafilov, B., Montag, C., & Markowetz, A. (2016, September). How age and gender affect smartphone usage [Paper presentation]. Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: adjunct (pp. 9–12), Heidelberg, Germany. https://doi.org/10.1145/2968219.2971451
   Google Scholar
• Aranyi, G., & Van Schaik, P. (2016). Testing a model of user‐experience with news websites. Journal of the Association for Information Science and Technology, 67(7), 1555–1575. https://doi.org/10.1002/asi.23462
   Web of Science ®Google Scholar
• Attig, C., & Franke, T. (2020). Abandonment of personal quantification: A review and empirical study investigating reasons for wearable activity tracking attrition. Computers in Human Behavior, 102, 223–237. https://doi.org/10.1016/j.chb.2019.08.025
   Web of Science ®Google Scholar
• Basha, N. K., Aw, E. C. X., & Chuah, S. H. W. (2022). Are we so over smartwatches? Or can technology, fashion, and psychographic attributes sustain smartwatch usage? Technology in Society, 69, 101952. https://doi.org/10.1016/j.techsoc.2022.101952
   Web of Science ®Google Scholar
• Bölen, M. C. (2020). Exploring the determinants of users’ continuance intention in smartwatches. Technology in Society, 60, 101209. https://doi.org/10.1016/j.techsoc.2019.101209
   Web of Science ®Google Scholar
• Bongard-Blanchy, K., Bouchard, C., Bonnardel, N., Lockner, D., & Aoussat, A. (2015). User experience dimensions in product design: A consolidation of what academic researchers know and what design practitioners do. Journal of Design Research, 13(2), 107–124. https://doi.org/10.1504/JDR.2015.069754
   Google Scholar
• Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern Methods for Business Research, 295(2), 295–336.
   Google Scholar
• Chin, W. W. (2009). How to write up and report PLS analyses. Handbook of partial least squares: Concepts, methods and applications (pp. 655–690). Springer Berlin Heidelberg.
   Google Scholar
• Cho, W. C., Lee, K. Y., & Yang, S. B. (2019). What makes you feel attached to smartwatches? The stimulus–organism–response (S–O–R) perspectives. Information Technology & People, 32(2), 319–343. https://doi.org/10.1108/ITP-05-2017-0152
   Web of Science ®Google Scholar
• Choi, J., & Kim, S. (2016). Is the smartwatch an IT product or a fashion product? A study on factors affecting the intention to use smartwatches. Computers in Human Behavior, 63, 777–786. https://doi.org/10.1016/j.chb.2016.06.007
   Web of Science ®Google Scholar
• Chuah, S. H. W. (2019). Wearable XR-technology: Literature review, conceptual framework and future research directions. International Journal of Technology Marketing, 13(3–4), 205–259. https://doi.org/10.1504/IJTMKT.2019.104586
   Google Scholar
• Chuah, S. H. W., Rauschnabel, P. A., Krey, N., Nguyen, B., Ramayah, T., & Lade, S. (2016). Wearable technologies: The role of usefulness and visibility in smartwatch adoption. Computers in Human Behavior, 65, 276–284. https://doi.org/10.1016/j.chb.2016.07.047
   Web of Science ®Google Scholar
• Cvetković, B., Szeklicki, R., Janko, V., Lutomski, P., & Luštrek, M. (2018). Real-time activity monitoring with a wristband and a smartphone. Information Fusion, 43, 77–93. https://doi.org/10.1016/j.inffus.2017.05.004
   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), 319–340. https://doi.org/10.2307/249008
   Web of Science ®Google Scholar
• Deng, L., Turner, D. E., Gehling, R., & Prince, B. (2010). User experience, satisfaction, and continual usage intention of IT. European Journal of Information Systems, 19(1), 60–75. https://doi.org/10.1057/ejis.2009.50
   Web of Science ®Google Scholar
• Forlizzi, J., & Battarbee, K. (2004, August). Understanding experience in interactive systems [Paper presentation]. Proceedings of the 5th Conference on Designing Interactive Systems: processes, Practices, Methods, and Techniques (pp. 261–268), Cambridge, MA.
   Google Scholar
• 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. https://doi.org/10.2307/3150980
   Google Scholar
• Gupta, M., Sinha, N., Singh, P., & Chuah, S. H. W. (2020). Gender differences in the wearable preferences, device and advertising value perceptions: Smartwatches vs. fitness trackers. International Journal of Technology Marketing, 14(2), 199–225. https://doi.org/10.1504/IJTMKT.2020.110127
   Google Scholar
• Goh, J. C. L., & Karimi, F. (2014). Towards the development of a ‘user-experience’technology adoption model for the interactive mobile technology. HCI in Business: First International Conference, HCIB 2014, Held as Part of HCI International 2014, Heraklion, Crete, Greece, June 22-27, 2014. Proceedings 1 (pp. 620–630). Springer International Publishing.
   Google Scholar
• Gross, A., & Bongartz, S. (2012, October). Why do I like it? Investigating the product-specificity of user experience. Proceedings of the 7th Nordic Conference on Human-Computer Interaction: Making Sense through Design (pp. 322–330). Association for Computing Machinery.
   Google Scholar
• Hassenzahl, M. (2003). The thing and I: Understanding the relationship between user and product. In M. A. Blythe, K. Overbeeke, A. F. Monk, & P. C. Wright (Eds.), Funology. Human-computer interaction series (Vol 3). Springer. https://doi.org/10.1007/1-4020-2967-5_4
   Google Scholar
• Hassenzahl, M. (2006). Hedonic, emotional, and experiential perspectives on product quality. Encyclopedia of human computer interaction (pp. 266–272). IGI Global.
   Google Scholar
• Hassenzahl, M. (2018). The thing and I: Understanding the relationship between user and product. Funology 2: From usability to enjoyment (pp. 301–313). Springer.
   Google Scholar
• Hassenzahl, M., Diefenbach, S., & Göritz, A. (2010). Needs, affect, and interactive products–Facets of user experience. Interacting with Computers, 22(5), 353–362. https://doi.org/10.1016/j.intcom.2010.04.002
   Web of Science ®Google Scholar
• Hassenzahl, M., & Tractinsky, N. (2006). User experience-a research agenda. Behaviour & Information Technology, 25(2), 91–97. https://doi.org/10.1080/01449290500330331
   Web of Science ®Google Scholar
• Hedman, J., & Gimpel, G. (2010). The adoption of hyped technologies: A qualitative study. Information Technology and Management, 11(4), 161–175. https://doi.org/10.1007/s10799-010-0075-0
   Web of Science ®Google Scholar
• 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
   Web of Science ®Google Scholar
• Karapanos, E., Zimmerman, J., Forlizzi, J., Martens, J. B. (2009, April). User experience over time: An initial framework. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 729–738). Association for Computing Machinery.
   Google Scholar
• Kim, S. H. (2014). A study on adoption factors of Korean smartphone users: A focus on TAM (Technology Acceptance Model) and UTAUT (Unified Theory of Acceptance and Use of Technology). Advanced Science and Technology Letters, 57(1), 27–30. https://doi.org/10.14257/astl.2014.57.07
   Google Scholar
• Koul, S., & Eydgahi, A. (2017). A systematic review of technology adoption frameworks and their applications. Journal of Technology Management & Innovation, 12(4), 106–113. https://doi.org/10.4067/S0718-27242017000400011
   Google Scholar
• Krey, N., Chuah, S. H. W., Ramayah, T., & Rauschnabel, P. A. (2019). How functional and emotional ads drive smartwatch adoption: The moderating role of consumer innovativeness and extraversion. Internet Research, 29(3), 578–602. https://doi.org/10.1108/IntR-12-2017-0534
   Web of Science ®Google Scholar
• Kulviwat, S., Bruner, G. C., II., & Al-Shuridah, O. (2009). The role of social influence on adoption of high tech innovations: The moderating effect of public/private consumption. Journal of Business Research, 62(7), 706–712. https://doi.org/10.1016/j.jbusres.2007.04.014
   Web of Science ®Google Scholar
• Lacroux, A. (2011). Les avantages et les limites de la méthode «Partial Least Square»(PLS): UNE illustration empirique dans le domaine de la GRH. Revue de Gestion Des Ressources Humaines, N° 80(2), 45–64. https://doi.org/10.3917/grhu.080.0045
   Google Scholar
• Lallemand, C., & Koenig, V. (2017, September). How could an intranet be like a friend to me? Why standardized UX scales don’t always fit. Proceedings of the European Conference on Cognitive Ergonomics (pp. 9–16). Association for Computing Machinery.
   Google Scholar
• Lallemand, C., Koenig, V., Gronier, G., & Martin, R. (2015). Création et validation d’une version française du questionnaire AttrakDiff pour l’évaluation de l’expérience utilisateur des systèmes interactifs. European Review of Applied Psychology, 65(5), 239–252. https://doi.org/10.1016/j.erap.2015.08.002
   Google Scholar
• Law, E. L. C., Roto, V., Hassenzahl, M., Vermeeren, A. P., & Kort, J. (2009, April). Understanding, scoping and defining user experience: A survey approach. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 719–728). Association for Computing Machinery.
   Google Scholar
• Li, T., Xia, T., Wang, H., Tu, Z., Tarkoma, S., Han, Z., & Hui, P. (2022). Smartphone app usage analysis: Datasets, methods, and applications. IEEE Communications Surveys & Tutorials, 24(2), 937–966. https://doi.org/10.1109/COMST.2022.3163176
   Web of Science ®Google Scholar
• Liu, X., Chen, T., Qian, F., Guo, Z., Lin, F. X., Wang, X., & Chen, K. (2017, June). Characterizing smartwatch usage in the wild [Paper presentation]. Proceedings of the 15th Annual International Conference on Mobile Systems, Applications, and Services (pp. 385–398), Niagara Falls, NY. https://doi.org/10.1145/3081333.3081351
   Google Scholar
• Ma, Q., Chan, A. H., & Chen, K. (2016). Personal and other factors affecting acceptance of smartphone technology by older Chinese adults. Applied Ergonomics, 54, 62–71. https://doi.org/10.1016/j.apergo.2015.11.015
   PubMed Web of Science ®Google Scholar
• Minge, M., & Thüring, M. (2018). Hedonic and pragmatic halo effects at early stages of user experience. International Journal of Human-Computer Studies, 109, 13–25. https://doi.org/10.1016/j.ijhcs.2017.07.007
   Web of Science ®Google Scholar
• Minge, M., Thüring, M., & Wagner, I. (2016, September). Developing and validating an English version of the meCUE questionnaire for measuring user experience. Proceedings of the human factors and ergonomics society annual meeting (Vol. 60, pp. 2063–2067). SAGE Publications. https://doi.org/10.1177/1541931213601468
   Google Scholar
• Nascimento, B., Oliveira, T., & Tam, C. (2018). Wearable technology: What explains continuance intention in smartwatches? Journal of Retailing and Consumer Services, 43, 157–169. https://doi.org/10.1016/j.jretconser.2018.03.017
   Web of Science ®Google Scholar
• Nieroda, M. E., Mrad, M., & Solomon, M. R. (2018). How do consumers think about hybrid products? Computer wearables have an identity problem. Journal of Business Research, 89, 159–170. https://doi.org/10.1016/j.jbusres.2018.04.024
   Web of Science ®Google Scholar
• Norman, D., Miller, J., & Henderson, A. (1995, May). What you see, some of what’s in the future, and how we go about doing it: HI at Apple Computer [Paper presentation]. Conference Companion on Human Factors in Computing Systems (p. 155), Denver, CO. https://doi.org/10.1145/223355.223477
   Google Scholar
• Ogbanufe, O., & Gerhart, N. (2018). Watch it! Factors driving continued feature use of the smartwatch. International Journal of Human–Computer Interaction, 34(11), 999–1014. https://doi.org/10.1080/10447318.2017.1404779
   Web of Science ®Google Scholar
• Park, Y., & Chen, J. V. (2007). Acceptance and adoption of the innovative use of smartphone. Industrial Management & Data Systems, 107(9), 1349–1365. https://doi.org/10.1108/02635570710834009
   Web of Science ®Google Scholar
• Raptis, D., Papachristos, E., Bruun, A., & Kjeldskov, J. (2022). Why did you pick that? A study on smartwatch design qualities and people’s preferences. Behaviour & Information Technology, 41(4), 827–844. https://doi.org/10.1080/0144929X.2020.1836259
   Web of Science ®Google Scholar
• Russell, J. A. (1980). A circumplex model of affect. Journal of Personality and Social Psychology, 39(6), 1161–1178. https://doi.org/10.1037/h0077714
   Web of Science ®Google Scholar
• Scapin, D., Senach, B., Trousse, B., & Pallot, M. (2012, January). User experience: Buzzword or new paradigm? [Paper presentation] ACHI 2012, the Fifth International Conference on Advances in Computer-Human Interactions), Valencia, Spain.
   Google Scholar
• Schrepp, M., Hinderks, A., & Thomaschewski, J. (2017). Design and evaluation of a short version of the user experience questionnaire (UEQ-S). International Journal of Interactive Multimedia and Artificial Intelligence, 4(6), 103–108. https://doi.org/10.9781/ijimai.2017.09.001
   Web of Science ®Google Scholar
• Shaw, H., Ellis, D. A., & Ziegler, F. V. (2018). The Technology Integration Model (TIM). Predicting the continued use of technology. Computers in Human Behavior, 83, 204–214. https://doi.org/10.1016/j.chb.2018.02.001
   Web of Science ®Google Scholar
• Talukder, M. S., Chiong, R., Bao, Y., & Hayat Malik, B. (2019). Acceptance and use predictors of fitness wearable technology and intention to recommend: An empirical study. Industrial Management & Data Systems, 119(1), 170–188. https://doi.org/10.1108/IMDS-01-2018-0009
   Web of Science ®Google Scholar
• Thüring, M., & Mahlke, S. (2007). Usability, aesthetics and emotions in human–technology interaction. International Journal of Psychology, 42(4), 253–264. https://doi.org/10.1080/00207590701396674
   Web of Science ®Google Scholar
• Van der Heijden, H. (2004). User acceptance of hedonic information systems. MIS Quarterly, 28( 4), 695–704. https://doi.org/10.2307/25148660
   Web of Science ®Google Scholar
• Van Der Linden, J., Amadieu, F., Vayre, E., & Van De Leemput, C. (2019). User experience and social influence: A new perspective for UX theory. Design, User Experience, and Usability. Design Philosophy and Theory: 8th International Conference, DUXU 2019, Held as Part of the 21st HCI International Conference, HCII 2019, Orlando, FL, USA, July 26–31, 2019, Proceedings, Part I 21 (pp. 98–112). Springer International Publishing.
   Google Scholar
• 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
   Web of Science ®Google Scholar
• 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
   Web of Science ®Google Scholar
• Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27, 425–478. https://doi.org/10.2307/30036540
   Web of Science ®Google Scholar
• 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
   Web of Science ®Google Scholar
• Yogasara, T., Popovic, V., Kraal, B., & Chamorro-Koc, M. (2011). General characteristics of anticipated user experience (AUX) with interactive products. Diversity and unity: Proceedings of IASDR2011, the 4th World Conference on Design Research (pp. 1–11). Delft University of Technology.
   Google Scholar
• Zarour, M., & Alharbi, M. (2017). User experience framework that combines aspects, dimensions, and measurement methods. Cogent Engineering, 4(1), 1421006. https://doi.org/10.1080/23311916.2017.1421006
   Web of Science ®Google Scholar