Content-, system-, and hardware-related effects on the experience of flow in VR gaming

References

• I. D. C. (2020). Worldwide augmented and virtual reality guide.
   Google Scholar
• Agarwal, R., & Karahanna, E. (2000). Time flies when you’re having fun: Cognitive absorption and beliefs about information technology usage. MIS Quarterly, 24(4), 665. https://doi.org/10.2307/3250951
   Web of Science ®Google Scholar
• Aguirre-Urreta, M., & Hu, J. (2019, May). Detecting common method bias: performance of the Harman’s single-factor test. SIGMIS Database, 50(2), 45–70. https://doi.org/10.1145/3330472.3330477
   Web of Science ®Google Scholar
• Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T
   Web of Science ®Google Scholar
• Algahtani, M., Altameem, A., & Baig, A. R. (2021). An extended UTAUT2 model to explain the adoption of virtual reality technology in health centers: An empirical study based in Riyadh. International Journal of Computer Science and Network Security, 21(3), 219–228. https://doi.org/10.22937/IJCSNS.2021.21.3.30
   Google Scholar
• Anthes, C., Garcia-Hernandez, R. J., Wiedemann, M., & Kranzlmuller, D. (2016). State of the art of virtual reality technology. 2016 IEEE Aerospace Conference (pp. 1–19). https://doi.org/10.1109/AERO.2016.7500674
   Google Scholar
• Aydin, G. (2015). Adoption of gamified systems: A study on a social media gamification website. International Journal of Online Marketing, 5(3), 18–37. https://doi.org/10.4018/IJOM.2015070102
   Google Scholar
• Bagozzi, R. P., Yi, Y., & Phillips, L. W. (1991). Assessing construct validity in organizational research. Administrative Science Quarterly, 36(3), 421–458. https://doi.org/10.2307/2393203
   Web of Science ®Google Scholar
• Bailenson, J., Patel, K., Nielsen, A., Bajscy, R., Jung, S.-H., & Kurillo, G. (2008). The effect of interactivity on learning physical actions in virtual reality. Media Psychology, 11(3), 354–376. https://doi.org/10.1080/15213260802285214
   Web of Science ®Google Scholar
• Barhorst, J. B., McLean, G., Shah, E., & Mack, R. (2021). Blending the real world and the virtual world: Exploring the role of flow in augmented reality experiences. Journal of Business Research, 122, 423–436. https://doi.org/10.1016/j.jbusres.2020.08.041
   Web of Science ®Google Scholar
• Bellalouna, F. (2020). Industrial case studies for digital transformation of engineering processes using the virtual reality technology. Procedia CIRP, 90, 636–641. https://doi.org/10.1016/j.procir.2020.01.082
   Google Scholar
• Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107(2), 238–246. https://doi.org/10.1037/0033-2909.107.2.238
   PubMed Web of Science ®Google Scholar
• Biocca, F. (1992). Will simulation sickness slow down the diffusion of virtual environment technology? Presence: Teleoperators and Virtual Environments, 1(3), 334–343. https://doi.org/10.1162/pres.1992.1.3.334
   Google Scholar
• bitkom. (2020). Die Zukunft der Consumer Technology: Marktentwicklung, Trends, Mediennutzung, Technologien, Geschäftsmodelle. https://www.bitkom.org/Bitkom/Publikationen/Die-Zukunft-der-Consumer-Technology-2021-Marktentwicklung-Mediennutzung-Trends-Technologien
   Google Scholar
• Boyle, E. A., Connolly, T. M., Hainey, T., & Boyle, J. M. (2012). Engagement in digital entertainment games: A systematic review. Computers in Human Behavior, 28(3), 771–780. https://doi.org/10.1016/j.chb.2011.11.020
   Web of Science ®Google Scholar
• Bressler, D. M., & Bodzin, A. M. (2013). A mixed methods assessment of students’ flow experiences during a mobile augmented reality science game: Flow experience with mobile AR. Journal of Computer Assisted Learning, 29(6), 505–517. https://doi.org/10.1111/jcal.12008
   Web of Science ®Google Scholar
• Bullock, H. E., Harlow, L. L., & Mulaik, S. A. (1994). Causation issues in structural equation modeling research. Structural Equation Modeling: A Multidisciplinary Journal, 1(3), 253–267. https://doi.org/10.1080/10705519409539977
   Web of Science ®Google Scholar
• Carroll, M., Osborne, E., & Yildirim, C. (2019). Effects of VR gaming and game genre on player experience. 2019 IEEE Games, Entertainment, Media Conference (GEM) (pp. 1–6). https://doi.org/10.1109/GEM.2019.8811554
   Google Scholar
• Cenfetelli, R. T., & Bassellier, G. (2009). Interpretation of formative measurement in information systems research. MIS Quarterly, 33(4), 689. https://doi.org/10.2307/20650323
   Web of Science ®Google Scholar
• Cheong, J. H., & Park, M.-C. (2005). Mobile internet acceptance in Korea. Internet Research, 15(2), 125–140. https://doi.org/10.1108/10662240510590324
   Web of Science ®Google Scholar
• Chin, W. W. (1998a). Issues and opinion on structural equation modeling. MIS Quarterly, 22(1), 7–16. https://www.jstor.org/stable/249674
   Web of Science ®Google Scholar
• Chin, W. W. (1998b). The partial least squares approach to structural equation modeling. In G. A. Marcoulides (Ed.), Modern methods for business research (pp. 295–336). Erlbaum.
   Google Scholar
• Choi, B., & Baek, Y. (2011). Exploring factors of media characteristic influencing flow in learning through virtual worlds. Computers & Education, 57(4), 2382–2394. https://doi.org/10.1016/j.compedu.2011.06.019
   Web of Science ®Google Scholar
• Chung, J., & Tan, F. B. (2004). Antecedents of perceived playfulness: An exploratory study on user acceptance of general information-searching websites. Information & Management, 41(7), 869–881. https://doi.org/10.1016/j.im.2003.08.016
   Web of Science ®Google Scholar
• Cobb, S. V. G., Nichols, S., Ramsey, A., & Wilson, J. R. (1999). Virtual Reality-Induced Symptoms and Effects (VRISE). Presence: Teleoperators and Virtual Environments, 8(2), 169–186. https://doi.org/10.1162/105474699566152
   Web of Science ®Google Scholar
• Csikszentmihályi, M. (1975). Play and intrinsic rewards. Journal of Humanistic Psychology, 15(3), 41–63. https://doi.org/10.1177/002216787501500306
   Web of Science ®Google Scholar
• Csikszentmihályi, M. (1990). Flow: The psychology of optimal experience. Harper and Row.
   Google Scholar
• Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319. https://doi.org/10.2307/249008
   Web of Science ®Google Scholar
• Deloitte. (2020). Extended reality studie 2020: marktanalyse und prognose. Extended Reality Study 2020: Market analysis and forecast.
   Google Scholar
• De Wulf, K., Schillewaert, N., Muylle, S., & Rangarajan, D. (2006). The role of pleasure in web site success. Information & Management, 43(4), 434–446. https://doi.org/10.1016/j.im.2005.10.005
   Web of Science ®Google Scholar
• Diamantopoulos, A., Riefler, P., & Roth, K. P. (2008). Advancing formative measurement models. Journal of Business Research, 61(12), 1203–1218. https://doi.org/10.1016/j.jbusres.2008.01.009
   Web of Science ®Google Scholar
• Du, W., Liang, R., & Liu, D. (2022). Factors influencing school teachers’ continuous usage intention of using VR technology for classroom teaching. SAGE Open, 12(3), 21582440221114324. https://doi.org/10.1177/21582440221114325
   Web of Science ®Google Scholar
• Erfani, M., El-Nasr, M. S., Milam, D., Aghabeigi, B., Lameman, B. A., Riecke, B. E., Maygoli, H., & Mah, S. (2010). The effect of age, gender, and previous gaming experience on game play performance. In P. Forbrig, F. Paternó, & A. M. Pejtersen (Eds.), Human–computer interaction (Vol. 332, pp. 293–296). Springer. https://doi.org/10.1007/978-3-642-15231-3_33
   Google Scholar
• Fabrigar, L. R., Wegener, D. T., MacCallum, R. C., & Strahan, E. J. (1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods, 4(3), 272–299. https://doi.org/10.1037/1082-989X.4.3.272
   Web of Science ®Google Scholar
• Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Addison-Wesley Pub. Co.
   Google Scholar
• Francis, L. J., & Greer, J. E. (1999). Measuring attitude towards science among secondary school students: The affective domain. Research in Science & Technological Education, 17(2), 219–226. https://doi.org/10.1080/0263514990170207
   Google Scholar
• Ghuman, D., & Griffiths, M. (2012). A cross-genre study of online gaming: Player demographics, motivation for play, and social interactions among players. International Journal of Cyber Behavior, Psychology and Learning, 2(1), 13–29. https://doi.org/10.4018/ijcbpl.2012010102
   Google Scholar
• Griffiths, M. D., Davies, M. N. O., & Chappell, D. (2003). Breaking the stereotype: The case of online gaming. CyberPsychology & Behavior, 6(1), 81–91. https://doi.org/10.1089/109493103321167992
   PubMedGoogle Scholar
• Guo, M., & Chan-Olmsted, S. M. (2015). Predictors of social television viewing: How perceived program, media, and audience characteristics affect social engagement with television programming. Journal of Broadcasting & Electronic Media, 59(2), 240–258. https://doi.org/10.1080/08838151.2015.1029122
   Web of Science ®Google Scholar
• Guo, Y. M., & Poole, M. S. (2009). Antecedents of flow in online shopping: A test of alternative models. Information Systems Journal, 19(4), 369–390. https://doi.org/10.1111/j.1365-2575.2007.00292.x
   Web of Science ®Google Scholar
• Hadwick, A. (2019). XR Industry Insight Report 2019-2020. VR Intelligence.
   Google Scholar
• Hair, J. F., Anderson, R. E., Babin, B. J., & Black, W. C. (Eds.). (2010). Multivariate data analysis (7th ed.). Pearson.
   Google Scholar
• Hair, J. F., Howard, M. C., & Nitzl, C. (2020). Assessing measurement model quality in PLS-SEM using confirmatory composite analysis. Journal of Business Research, 109, 101–110. https://doi.org/10.1016/j.jbusres.2019.11.069
   Web of Science ®Google Scholar
• Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203
   Web of Science ®Google Scholar
• Hamari, J., Malik, A., Koski, J., & Johri, A. (2019). Uses and gratifications of Pokémon Go: Why do people play mobile location-based augmented reality games? International Journal of Human–Computer Interaction, 35(9), 804–819. https://doi.org/10.1080/10447318.2018.1497115
   Web of Science ®Google Scholar
• Hamari, J., & Sjöblom, M. (2017). What is eSports and why do people watch it? Internet Research, 27(2), 211–232. https://doi.org/10.1108/IntR-04-2016-0085
   Web of Science ®Google Scholar
• Harman, H. H. (1967). Modern factor analysis (2nd ed.). University of Chicago Press.
   Google Scholar
• Hartl, E., & Berger, B. (2017). Escaping reality: Examining the role of presence and escapism in user adoption of virtual reality glasses. Proceedings of the 25th European Conference on Information Systems (ECIS) (pp. 2413–2428).
   Google Scholar
• Hassenzahl, M. (2008). User experience (UX): Towards an experiential perspective on product quality. Proceedings of the 20th International Conference of the Association Francophone d’Interaction Homme-Machine on - IHM (Vol. 8, pp. 11). https://doi.org/10.1145/1512714.1512717
   Google Scholar
• Hennig-Thurau, T, & Houston, M. B. (2019). Entertainment science. In Data analytics and practical theory for movies, games, books, and music. Springer Nature.
   Google Scholar
• Herz, M., & Rauschnabel, P. A. (2019). Understanding the diffusion of virtual reality glasses: The role of media, fashion and technology. Technological Forecasting and Social Change, 138, 228–242. https://doi.org/10.1016/j.techfore.2018.09.008
   Web of Science ®Google Scholar
• Hill, K. J., & Howarth, P. A. (2000). Habituation to the side effects of immersion in a virtual environment. Displays, 21(1), 25–30. https://doi.org/10.1016/S0141-9382(00)00029-9
   Web of Science ®Google Scholar
• Hino, H. (2015). TV Today, Mobile TV Tomorrow? Extrapolating Lessons from Israeli Consumers’ Adoption of Innovative TV Viewing Technology. International Journal on Media Management, 17(2), 69–92. https://doi.org/10.1080/14241277.2015.1030748
   Web of Science ®Google Scholar
• Hirschman, E. C. (1983). Predictors of self-projection, fantasy fulfillment, and escapism. The Journal of Social Psychology, 120(1), 63–76. https://doi.org/10.1080/00224545.1983.9712011
   Web of Science ®Google Scholar
• Hoffman, D. L., & Novak, T. P. (2009). Flow online: Lessons learned and future prospects. Journal of Interactive Marketing, 23(1), 23–34. https://doi.org/10.1016/j.intmar.2008.10.003
   Web of Science ®Google Scholar
• Holsapple, C. W., & Wu, J. (2007). User acceptance of virtual worlds: The Hedonic framework. ACM SIGMIS DATABASE: The DATABASE for Advances in Information Systems, 38(4), 86–89. https://doi.org/10.1145/1314234.1314250
   Google Scholar
• Hou, Y., Kang, S., & Moon, T. (2019). Customers’ continuous usage intention of Virtual Reality (VR) product. In R. Lee (Ed.), Software engineering, artificial intelligence, networking and parallel/distributed computing (pp. 14–26). Springer International Publishing. https://doi.org/10.1007/978-3-319-98367-7_2
   Google Scholar
• Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. https://doi.org/10.1080/10705519909540118
   Web of Science ®Google Scholar
• Iacobucci, D. (2009). Everything you always wanted to know about SEM (structural equations modeling) but were afraid to ask. Journal of Consumer Psychology, 19(4), 673–680. https://doi.org/10.1016/j.jcps.2009.09.002
   Web of Science ®Google Scholar
• IDC. (2019). Worldwide augmented and virtual reality spending guide.
   Google Scholar
• IDC. (2022). AR/VR headset shipments grew dramatically in 2021, thanks largely to meta’s strong quest 2 volumes, with growth forecast to continue, according to IDC. https://www.idc.com/getdoc.jsp?containerId=prUS48969722
   Google Scholar
• Jackson, S. A., & Marsh, H. W. (1996). Development and validation of a scale to measure optimal experience: The flow state scale. Journal of Sport & Exercise Psychology, 18(1), 17–35. https://doi.org/10.1123/jsep.18.1.17
   Web of Science ®Google Scholar
• Jang, Y., & Park, E. (2019). An adoption model for virtual reality games: The roles of presence and enjoyment. Telematics and Informatics, 42, 101239. https://doi.org/10.1016/j.tele.2019.101239
   Web of Science ®Google Scholar
• Jarvis, C. B., MacKenzie, S. B., & Podsakoff, P. (2003). A critical review of construct indicators and measurement model specification in marketing and consumer research. Journal of Consumer Research, 30(2), 199–218. https://doi.org/10.1086/376806
   Web of Science ®Google Scholar
• Jung, Y., Perez-Mira, B., & Wiley-Patton, S. (2009). Consumer adoption of mobile TV: Examining psychological flow and media content. Computers in Human Behavior, 25(1), 123–129. https://doi.org/10.1016/j.chb.2008.07.011
   Web of Science ®Google Scholar
• Kaczmarek, L. D., Misiak, M., Behnke, M., Dziekan, M., & Guzik, P. (2017). The Pikachu effect: Social and health gaming motivations lead to greater benefits of Pokémon GO use. Computers in Human Behavior, 75, 356–363. https://doi.org/10.1016/j.chb.2017.05.031
   Web of Science ®Google Scholar
• Kampling, H. (2018). The role of immersive virtual reality in individual learning. Hawaii International Conference on System Sciences. https://doi.org/10.24251/HICSS.2018.173
   Google Scholar
• Katz, E., Blumler, J. G., & Gurevitch, M. (1973). Uses and gratifications research. Public Opinion Quarterly, 37(4), 509. https://doi.org/10.1086/268109
   Web of Science ®Google Scholar
• Katz, E., Blumler, J. G., & Gurevitch, M. (1974). Utilization of mass communication. In E. Katz & J. G. Blumler (Eds.), The uses of mass communication (pp. 19–32). SAGE publications.
   Google Scholar
• Katz, E., & Foulkes, D. (1962). On the use of the mass media as ‘escape’: Clarification of a concept. Public Opinion Quarterly, 26(3), 377–388. https://doi.org/10.1086/267111
   Web of Science ®Google Scholar
• Keshavarz, B., & Hecht, H. (2011). Validating an efficient method to quantify motion sickness. Human Factors: The Journal of the Human Factors and Ergonomics Society, 53(4), 415–426. https://doi.org/10.1177/0018720811403736
   PubMed Web of Science ®Google Scholar
• Kim, M. J., Lee, C.-K., & Preis, M. W. (2020). The impact of innovation and gratification on authentic experience, subjective well-being, and behavioral intention in tourism virtual reality: The moderating role of technology readiness. Telematics and Informatics, 49, 101349. https://doi.org/10.1016/j.tele.2020.101349
   Web of Science ®Google Scholar
• Kim, Y., & Ross, S. D. (2006). An exploration of motives in sport video gaming. International Journal of Sports Marketing and Sponsorship, 8(1), 28–40. https://doi.org/10.1108/IJSMS-08-01-2006-B006
   Google Scholar
• Kim, Y. K., & Trail, G. T. (2010). Constraints and motivators: A new model to explain sport consumer behavior. Journal of Sport Management, 24(2), 190–210. https://doi.org/10.1123/jsm.24.2.190
   Web of Science ®Google Scholar
• Knight, J. F., & Baber, C. (2005). A tool to assess the comfort of wearable computers. Human Factors: The Journal of the Human Factors and Ergonomics Society, 47(1), 77–91. https://doi.org/10.1518/0018720053653875
   PubMed Web of Science ®Google Scholar
• Kock, N. (2015). Common method bias in PLS-SEM: A full collinearity assessment approach. International Journal of E-Collaboration, 11(4), 1–10. https://doi.org/10.4018/ijec.2015100101
   Web of Science ®Google Scholar
• Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer behavior. Information Systems Research, 13(2), 205–223. https://doi.org/10.1287/isre.13.2.205.83
   Web of Science ®Google Scholar
• Krcmar, M., & Strizhakova, Y. (2009). Uses and gratifications as media choice. In T. Hartmann (Ed.), Media choice: A theoretical and empirical overview. Routledge .
   Google Scholar
• Kunz, R. E., & Santomier, J. P. (2020). Sport content and virtual reality technology acceptance. Sport, Business and Management: An International Journal, 10(1), 83–103. https://doi.org/10.1108/SBM-11-2018-0095
   Google Scholar
• Kunz, R., Telkmann, V., & Zabel, C. (2021). XR aus Nutzersicht. In C. Zabel, V. Telkmann, & G. Heisenberg (Eds.),Cross reality (XR) in Deutschland (97–110). Nomos. https://doi.org/10.5771/9783748925514-97
   Google Scholar
• Lang, B. (2021). Beat Saber has sold 4m copies & 40m Songs. Road to VR. Retrieved October 6, 2021, from https://www.roadtovr.com/beat-saber-4-million-units-milestone-revenue/
   Google Scholar
• Lawrie, E. (2020). What went wrong with virtual reality? [online]. BBC News. Retrieved October 6, 2021, from https://www.bbc.com/news/business-50265414
   Google Scholar
• Lee, M. (2009). Understanding the behavioural intention to play online games: An extension of the theory of planned behaviour. Online Information Review, 33(5), 849–872. https://doi.org/10.1108/14684520911001873
   Web of Science ®Google Scholar
• Lee, -C.-C., Hsiao, K.-L., & Chen, -C.-C. (2020). Exploring the benefit and sacrifice factors of virtual reality gameplay. Frontiers in Psychology, 11, 251. https://doi.org/10.3389/fpsyg.2020.00251
   PubMedGoogle Scholar
• Lewis, G. N., Woods, C., Rosie, J. A., & Mcpherson, K. M. (2011). Virtual reality games for rehabilitation of people with stroke: Perspectives from the users. Disability and Rehabilitation: Assistive Technology, 6(5), 453–463. https://doi.org/10.3109/17483107.2011.574310
   PubMedGoogle Scholar
• Li, H., Liu, Y., Xu, X., Heikkilä, J., & van der Heijden, H. (2015). Modeling hedonic is continuance through the uses and gratifications theory: An empirical study in online games. Computers in Human Behavior, 48, 261–272. https://doi.org/10.1016/j.chb.2015.01.053
   Web of Science ®Google Scholar
• Lin, H.-F. (2009). Examination of cognitive absorption influencing the intention to use a virtual community. Behaviour & Information Technology, 28(5), 421–431. https://doi.org/10.1080/01449290701662169
   Web of Science ®Google Scholar
• Lin, J. J. W., & Parker, D. E. (2007). User experience modeling and enhancement for virtual environments that employ wide-field displays. In V. G. Duffy (Ed.), Digital human modeling (Vol. 4561, pp. 423–433). Springer. https://doi.org/10.1007/978-3-540-73321-8_49
   Google Scholar
• MacKenzie, S. B., & Podsakoff, P. M. (2012). Common method bias in marketing: Causes, mechanisms, and procedural remedies. Journal of Retailing, 88(4), 542–555. https://doi.org/10.1016/j.jretai.2012.08.001
   Web of Science ®Google Scholar
• Malik, A., Hiekkanen, K., Hussain, Z., Hamari, J., & Johri, A. (2020). How players across gender and age experience Pokémon Go? Universal Access in the Information Society, 19(4), 799–812. https://doi.org/10.1007/s10209-019-00694-7
   Web of Science ®Google Scholar
• Manis, K. T., & Choi, D. (2019). The virtual reality hardware acceptance model (VR-HAM): Extending and individuating the technology acceptance model (TAM) for virtual reality hardware. Journal of Business Research, 100, 503–513. https://doi.org/10.1016/j.jbusres.2018.10.021
   Web of Science ®Google Scholar
• Merhi, M. I. (2016). Towards a framework for online game adoption. Computers in Human Behavior, 60, 253–263. https://doi.org/10.1016/j.chb.2016.02.072
   Web of Science ®Google Scholar
• Michailidis, L., Balaguer-Ballester, E., & He, X. (2018). Flow and immersion in video games: The aftermath of a conceptual challenge. Frontiers in Psychology, 9, 1682. https://doi.org/10.3389/fpsyg.2018.01682
   PubMed Web of Science ®Google Scholar
• Mütterlein, J. (2018). The three pillars of virtual reality? Investigating the roles of immersion, presence, and interactivity. Hawaii International Conference on System Sciences. https://doi.org/10.24251/HICSS.2018.174
   Google Scholar
• Mütterlein, J., & Hess, T. (2017). Immersion, presence, interactivity: Towards a joint understanding of factors influencing virtual reality acceptance and use. AMCIS 2017 Proceedings. Americas Conference on Information Systems, Boston.
   Google Scholar
• Mütterlein, J., Jelsch, S., & Hess, T. (2018). Specifics of collaboration in virtual reality: How immersion drives the intention to collaborate. PACIS 2018 Proceedings.
   Google Scholar
• Mütterlein, J., Kunz, R. E., & Baier, D. (2019). Effects of lead-usership on the acceptance of media innovations: A mobile augmented reality case. Technological Forecasting and Social Change, 145, 113–124. https://doi.org/10.1016/j.techfore.2019.04.019
   Web of Science ®Google Scholar
• Netemeyer, R. G., Bearden, W. O., & Sharma, S. (2003). Scaling procedures: Issues and applications. Sage Publications.
   Google Scholar
• Nunnally, J. C. (1978). An overview of psychological measurement. In B. B. Wolman (Ed.), Clinical diagnosis of mental disorders (pp. 97–146). Springer US. https://doi.org/10.1007/978-1-4684-2490-4_4
   Google Scholar
• Palmer, J. W. (2002). Web site usability, design, and performance metrics. Information Systems Research, 13(2), 151–167. https://doi.org/10.1287/isre.13.2.151.88
   Web of Science ®Google Scholar
• Park, K., Cha, M., Kwak, H., & Chen, K.-T. (2017). Achievement and friends: Key factors of player retention vary across player levels in online multiplayer games. Proceedings of the 26th International Conference on World Wide Web Companion - WWW ’17 companion, (pp. 445–453). https://doi.org/10.1145/3041021.3054176
   Google Scholar
• Peukert, C., Pfeiffer, J., Meer, M., Pfeiffer, T., & Weinhardt, C. (2019). Acceptance of imagined versus experienced virtual reality shopping environments: Insights from two experiments. Proceedings of the 27th European Conference on Information Systems (ECIS). 27th European Conference on Information Systems (ECIS), Stockholm & Uppsala, Sweden.
   Google Scholar
• Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903. https://doi.org/10.1037/0021-9010.88.5.879
   PubMed Web of Science ®Google Scholar
• Potts, R., & Yee, L. (2019). Pokémon Go-ing or staying: Exploring the effect of age and gender on augmented reality game player experiences in public spaces. Journal of Urban Design, 24(6), 878–895. https://doi.org/10.1080/13574809.2018.1557513
   Web of Science ®Google Scholar
• Procci, K., James, N., & Bowers, C. (2013). The effects of gender, age, and experience on game engagement. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 57(1), 2132–2136. https://doi.org/10.1177/1541931213571475
   Google Scholar
• Qin, H., Patrick Rau, P.-L., & Salvendy, G. (2009). Measuring player immersion in the computer game narrative. International Journal of Human–Computer Interaction, 25(2), 107–133. https://doi.org/10.1080/10447310802546732
   Web of Science ®Google Scholar
• Rauschnabel, P. A., Rossmann, A., & Tom Dieck, M. C. (2017). An adoption framework for mobile augmented reality games: The case of Pokémon Go. Computers in Human Behavior, 76, 276–286. https://doi.org/10.1016/j.chb.2017.07.030
   Web of Science ®Google Scholar
• Rebenitsch, L., & Owen, C. (2016). Review on cybersickness in applications and visual displays. Virtual Reality, 20(2), 101–125. https://doi.org/10.1007/s10055-016-0285-9
   Web of Science ®Google Scholar
• Regan, C. (1997). Some effects of using virtual reality technology. In R. J. Seidel & P. R. Chatelier (Eds.), Virtual reality, training’s future? (pp. 77–83). Springer US. https://doi.org/10.1007/978-1-4899-0038-8_9
   Google Scholar
• Rubin, A. M. (1983). Television uses and gratifications: The interactions of viewing patterns and motivations. Journal of Broadcasting, 27(1), 37–51. https://doi.org/10.1080/08838158309386471
   Web of Science ®Google Scholar
• Rynarzewska, A. I. (2018). Virtual reality: A new channel in sport consumption. Journal of Research in Interactive Marketing, 12(4), 472–488. https://doi.org/10.1108/JRIM-02-2018-0028
   Web of Science ®Google Scholar
• Sagnier, C., Loup-Escande, E., Lourdeaux, D., Thouvenin, I., & Valléry, G. (2020). User acceptance of virtual reality: An extended technology acceptance model. International Journal of Human–Computer Interaction, 36(11), 993–1007. https://doi.org/10.1080/10447318.2019.1708612
   Web of Science ®Google Scholar
• Sarstedt, M., Ringle, C. M., & Hair, J. F. (2017). Partial least squares structural equation modeling. In C. Homburg, M. Klarmann, & A. Vomberg (Eds.), Handbook of market research (pp. 1–40). Springer International Publishing. https://doi.org/10.1007/978-3-319-05542-8_15-1
   Google Scholar
• Shevchuk, N., Degirmenci, K., & Oinas-Kukkonen, H. (2019). Adoption of gamified persuasive systems to encourage sustainable behaviors: Interplay between perceived persuasiveness and cognitive absorption. ICIS 2019 Proceedings. Fortieth International Conference on Information Systems, Munich.
   Google Scholar
• Shin, D. (2012). 3DTV as a social platform for communication and interaction. Information Technology & People, 25(1), 55–80. https://doi.org/10.1108/09593841211204344
   Web of Science ®Google Scholar
• Shmueli, G., Sarstedt, M., Hair, J. F., Cheah, J.-H., Ting, H., Vaithilingam, S., & Ringle, C. M. (2019). Predictive model assessment in PLS-SEM: Guidelines for using PLSpredict. European Journal of Marketing, 53(11), 2322–2347. https://doi.org/10.1108/EJM-02-2019-0189
   Web of Science ®Google Scholar
• Sjöblom, M., Törhönen, M., Hamari, J., & Macey, J. (2017). Content structure is king: An empirical study on gratifications, game genres and content type on Twitch. Computers in Human Behavior, 73(3), 161–171. https://doi.org/10.1016/j.chb.2017.03.036
   Google Scholar
• Steuer, J. (1992). Defining virtual reality: Dimensions determining telepresence. Journal of Communication, 42(4), 73–93. https://doi.org/10.1111/j.1460-2466.1992.tb00812.x
   Web of Science ®Google Scholar
• Tan, F. B., & Chou, J. P. C. (2011). Dimensions of autotelic personality and their effects on perceived playfulness in the context of mobile information and entertainment services. Australasian Journal of Information Systems, 17(1). https://doi.org/10.3127/ajis.v17i1.527
   Google Scholar
• Tom Dieck, D., Tom Dieck, M. C., Jung, T., & Moorhouse, N. (2018). Tourists’ virtual reality adoption: An exploratory study from Lake District National Park. Leisure Studies, 37(4), 371–383. https://doi.org/10.1080/02614367.2018.1466905
   Web of Science ®Google Scholar
• Torres, R., Johnson, V., & Imhonde, B. (2014). The impact of content type and availability on eBook reader adoption. Journal of Computer Information Systems, 54(4), 42–51. https://doi.org/10.1080/08874417.2014.11645721
   Web of Science ®Google Scholar
• Trübswetter, N., & Bengler, K. (2013). Why should I use ADAS? Advanced driver assistance systems and the elderly: Knowledge, experience and usage barriers. Proceedings of the 7th International Driving Symposium on Human Factors in Driver Assessment, Training, and Vehicle Design (pp. 495–501).
   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, 425–478.
   Web of Science ®Google Scholar
• Venkatesh, V., Thong, J., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157. https://doi.org/10.2307/41410412
   Web of Science ®Google Scholar
• Vishwanath, A. (2015). The psychology of the diffusion and acceptance of technology. In S. S. Sundar (Ed.), The handbook of the psychology of communication technology (1st ed. pp. 311–331). Wiley. https://doi.org/10.1002/9781118426456.ch14
   Google Scholar
• Voiskounsky, A., & Wang, S. (2014). Flow experience while computer gaming: Empirical study. Open Journal of Social Sciences, 2(8), 1–6. https://doi.org/10.4236/jss.2014.28001
   Google Scholar
• Wan, C.-S., & Chiou, W.-B. (2006). Psychological motives and online games addiction: A test of flow theory and humanistic needs theory for Taiwanese adolescents. CyberPsychology & Behavior, 9(3), 317–324. https://doi.org/10.1089/cpb.2006.9.317
   PubMedGoogle Scholar
• Weech, S., Kenny, S., Lenizky, M., & Barnett-Cowan, M. (2020). Narrative and gaming experience interact to affect presence and cybersickness in virtual reality. International Journal of Human–Computer Studies, 138, 102398. https://doi.org/10.1016/j.ijhcs.2020.102398
   Web of Science ®Google Scholar
• Weibull, L. (1985). Structural factors in gratifications research. In K. E. Rosengren, L. A. Wenner, & P. Palmgreen (Eds.), Media gratifications research: Current perspectives (pp. 123–157). Sage.
   Google Scholar
• Whitton, N. (2014). Digital games and learning: Research and theory. Routledge.
   Google Scholar
• Witmer, B. G., & Singer, M. J. (1998). Measuring presence in virtual environments: A presence questionnaire. Presence: Teleoperators and Virtual Environments, 7(3), 225–240. https://doi.org/10.1162/105474698565686
   Web of Science ®Google Scholar
• Wloka, M. M., & Greenfield, E. (1995). The virtual tricorder: A uniform interface for virtual reality. Proceedings of the 8th Annual ACM Symposium on User Interface and Software Technology - UIST (Vol. 95, pp. 39–40). https://doi.org/10.1145/215585.215647
   Google Scholar
• Wu, J.-H., Wang, S.-C., & Tsai, -H.-H. (2010). Falling in love with online games: The uses and gratifications perspective. Computers in Human Behavior, 26(6), 1862–1871. https://doi.org/10.1016/j.chb.2010.07.033
   Web of Science ®Google Scholar
• Yan, Y., Chen, K., Xie, Y., Song, Y., & Liu, Y. (2019). The effects of weight on comfort of virtual reality devices. In F. Rebelo & M. M. Soares (Eds.), Advances in ergonomics in design (Vol. 777, pp. 239–248). Springer International Publishing. https://doi.org/10.1007/978-3-319-94706-8_27
   Google Scholar
• Yildirim, C. (2019). Cybersickness during VR gaming undermines game enjoyment: A mediation model. Displays, 59, 35–43. https://doi.org/10.1016/j.displa.2019.07.002
   Web of Science ®Google Scholar
• Yoo, S., Ackad, C., Heywood, T., & Kay, J. (2017). Evaluating the actual and perceived exertion provided by virtual reality games. Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems (pp. 3050–3057). https://doi.org/10.1145/3027063.3053203
   Google Scholar