參考文獻 |
Aburbeian, A. M., Owda, A. Y., & Owda, M. (2022). A Technology Acceptance Model Survey of the Metaverse Prospects. Ai, 3(2), 285-302. https://doi.org/10.3390/ai3020018
Ajzen, I. (1991). The theory of planned behavior. Organizational behavior and human decision processes, 50(2), 179-211.
Akour, I. A., Al-Maroof, R. S., Alfaisal, R., & Salloum, S. A. (2022). A conceptual framework for determining metaverse adoption in higher institutions of gulf area: An empirical study using hybrid SEM-ANN approach. Computers and Education: Artificial Intelligence, 3, 100052.
Al-Ghaith, W. A. (2016). Applying decomposed theory of planned behaviour towards a comprehensive understanding of social network usage in Saudi Arabia. International Journal of Information Technology and Computer Science (IJITCS), 8(5), 52.
Almarzouqi, A., Aburayya, A., & Salloum, S. A. (2022). Prediction of User’s Intention to Use Metaverse System in Medical Education: A Hybrid SEM-ML Learning Approach. IEEE Access, 10, 43421-43434.
Alsharhan, A., Salloum, S. A., & Aburayya, A. (2022). Technology acceptance drivers for AR smart glasses in the middle east: A quantitative study. International Journal of Data and Network Science, 6(1), 193-208.
Alzahrani, A. I., Mahmud, I., Ramayah, T., Alfarraj, O., & Alalwan, N. (2017). Extending the theory of planned behavior (TPB) to explain online game playing among Malaysian undergraduate students. Telematics and Informatics, 34(4), 239-251.
Aziz, S., Md Husin, M., & Hussin, N. (2017). Conceptual framework of factors determining intentions towards the adoption of family takaful-An extension of decomposed theory of planned behaviour. International Journal of Organizational Leadership, 6, 385-399.
Baker, E. W., Hubona, G. S., & Srite, M. (2019). Does “being there” matter? The impact of web-based and virtual world’s shopping experiences on consumer purchase attitudes. Information & Management, 56(7), 103153.
Bandura, A. (1986). Social foundations of thought and action. Englewood Cliffs, NJ, 1986(23-28).
Banerjee-Guénette, P., Bigford, S., & Glegg, S. M. (2020). Facilitating the implementation of virtual reality-based therapies in pediatric rehabilitation. Physical & Occupational Therapy In Pediatrics, 40(2), 201-216.
Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological bulletin, 88(3), 588.
Bhattacherjee, A. (2000). Acceptance of e-commerce services: the case of electronic brokerages. IEEE Transactions on systems, man, and cybernetics-Part A: Systems and humans, 30(4), 411-420.
Bollen, K. A. (1989). A new incremental fit index for general structural equation models. Sociological methods & research, 17(3), 303-316.
Breivik, E., & Olsson, U. H. (2001). Adding variables to improve fit: The effect of model size on fit assessment in LISREL. Structural equation modeling: Present and future, 169-194.
Cheon, J., Lee, S., Crooks, S. M., & Song, J. (2012). An investigation of mobile learning readiness in higher education based on the theory of planned behavior. Computers & education, 59(3), 1054-1064.
Childers, T. L., Carr, C. L., Peck, J., & Carson, S. (2001). Hedonic and utilitarian motivations for online retail shopping behavior. Journal of retailing, 77(4), 511-535.
Cox, A. M., Guzman, I., Cromer, K. W., & Bagui, S. (2017). Virtual Worlds, Virtual Reality, and Augmented Reality: Differences in Purchase Intentions Based on Types, Users, and Sex. Journal of Virtual Worlds Research, 10(1).
Dacko, S. G. (2017). Enabling smart retail settings via mobile augmented reality shopping apps. Technological Forecasting and Social Change, 124, 243-256.
Dahiya, R., & Gayatri. (2017). Investigating Indian Car Buyers’ Decision to Use Digital Marketing Communication: An Empirical Application of Decomposed TPB. Vision: The Journal of Business Perspective, 21(4), 385-396. https://doi.org/10.1177/0972262917733175
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340.
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace 1. Journal of applied social psychology, 22(14), 1111-1132.
Deloitte 德勤中國. (2021). 元宇宙系列白皮書-未來已來 全球XR產業洞察.
Dickinger, A., Arami, M., & Meyer, D. (2008). The role of perceived enjoyment and social norm in the adoption of technology with network externalities. European Journal of Information Systems, 17(1), 4-11. https://doi.org/10.1057/palgrave.ejis.3000726
Doll, W. J., Xia, W., & Torkzadeh, G. (1994). A confirmatory factor analysis of the end-user computing satisfaction instrument. MIS quarterly, 453-461.
Duan, H., Li, J., Fan, S., Lin, Z., Wu, X., & Cai, W. (2021). Metaverse for Social Good Proceedings of the 29th ACM International Conference on Multimedia,
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: an introduction to theory and research.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 18(1), 39-50.
Gartner. (2022). Predicts 2022: 4 technology bets for building the digital future. Gartner Report. https://www.businesswire.com/news/home/20220207005085/en
George, D., & Mallery, P. (2003). SPSS for Windows Step by Step: A Simple Guide and Reference, 11.0 Update (4th Edition). Allyn & Bacon.
Glegg, S. M., Holsti, L., Velikonja, D., Ansley, B., Brum, C., & Sartor, D. (2013). Factors influencing therapists′ adoption of virtual reality for brain injury rehabilitation. Cyberpsychology, Behavior, and Social Networking, 16(5), 385-401.
Hair, J. F. (2009). Multivariate data analysis.
Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (1998). Multivariate data analysis . Uppersaddle River. Multivariate Data Analysis (5th ed) Upper Saddle River, 5(3), 207-219.
Hollensen, S., Kotler, P., & Opresnik, M. O. (2022). Metaverse–the new marketing universe. Journal of Business Strategy.
Hsieh, J. P.-A., Rai, A., & Keil, M. (2008). Understanding digital inequality: Comparing continued use behavioral models of the socio-economically advantaged and disadvantaged. MIS quarterly, 97-126.
Hsu, M.-H., & Chiu, C.-M. (2004). Predicting electronic service continuance with a decomposed theory of planned behaviour. Behaviour & Information Technology, 23(5), 359-373.
Hsu, M.-H., Yen, C.-H., Chiu, C.-M., & Chang, C.-M. (2006). A longitudinal investigation of continued online shopping behavior: An extension of the theory of planned behavior. International journal of human-computer studies, 64(9), 889-904.
Hu, L. t., & 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.
Hung, S.-W., Chang, C.-W., & Ma, Y.-C. (2021). A new reality: Exploring continuance intention to use mobile augmented reality for entertainment purposes. Technology in Society, 67, 101757.
Hung, S.-Y., Tsai, J. C.-A., & Chou, S.-T. (2016). Decomposing perceived playfulness: A contextual examination of two social networking sites. Information & Management, 53(6), 698-716.
Hwang, I. (2022). The Effects of Metaverse Related Self-determination on Intention to Continuous Use Through Intrinsic Motivation: Moderating Effect of Member Trust. Journal of Society for e-Business Studies, 27(2).
Hwang, R., & Lee, M. (2022). The Influence of Music Content Marketing on User Satisfaction and Intention to Use in the Metaverse: A Focus on the SPICE Model. Businesses, 2(2), 141-155. https://doi.org/10.3390/businesses2020010
Ilham, D., & Simorangkir, D. (2020). Discernible Impact of Fashion‘s Online Shopping With Mobile-Augmented Reality (AR) Application on the Consumer‘s Perspective in Indonesia. Conference Series,
Iwanaga, J., Loukas, M., Dumont, A. S., & Tubbs, R. S. (2021). A review of anatomy education during and after the COVID‐19 pandemic: Revisiting traditional and modern methods to achieve future innovation. Clinical Anatomy, 34(1), 108-114.
Jang, J., Ko, Y., Shin, W. S., & Han, I. (2021). Augmented Reality and Virtual Reality for Learning: An Examination Using an Extended Technology Acceptance Model. IEEE Access, 9, 6798-6809. https://doi.org/10.1109/access.2020.3048708
Javornik, A., Rogers, Y., Moutinho, A. M., & Freeman, R. (2016). Revealing the shopper experience of using a" magic mirror" augmented reality make-up application. Conference on Designing Interactive Systems,
Kanimozhi, S., & Selvarani, A. (2019). Application of the decomposed theory of planned behaviour in technology adoption: A review. International Journal of Research and Analytical Reviews, 6(2), 735-739.
Karacan, C. G. (2019). Exploring factors that predict pre-service English teachers’ intentions to use augmented reality using decomposed theory of planned behavior.
Karacan, C. G., & Polat, M. (2022). Pre-Service Language Teachers′ Development of Augmented Reality Applications: A Qualitative Inquiry Into Their Intention of Augmented Reality Use. In Emerging Concepts in Technology-Enhanced Language Teaching and Learning (pp. 66-87). IGI Global.
Karagöz, C. (2022). Analyzing Teachers’ Views Toward the Use of EBA during Covid-19 Pandemic Based on the Technology Acceptance Model Middle East Technical University].
Kim, J. (2021). Advertising in the Metaverse: Research agenda. Journal of Interactive Advertising, 21(3), 141-144.
Kim, J., & Forsythe, S. (2008). Adoption of Virtual Try-on technology for online apparel shopping. Journal of Interactive Marketing, 22(2), 45-59. https://doi.org/10.1002/dir.20113
Kim, M. J., & Hall, C. M. (2019). A hedonic motivation model in virtual reality tourism: Comparing visitors and non-visitors. International Journal of Information Management, 46, 236-249. https://doi.org/10.1016/j.ijinfomgt.2018.11.016
Kline, T. (2005). Psychological testing: A practical approach to design and evaluation. Sage.
Kuo, F.-Y., & Young, M.-L. (2008). Predicting knowledge sharing practices through intention: A test of competing models. Computers in Human Behavior, 24(6), 2697-2722. https://doi.org/10.1016/j.chb.2008.03.015
Lancere de Kam, E., & Diefenbach, J. (2020). Understanding the Digital Future: Applying the Decomposed Theory of Planned Behaviour to the Generation Y′s Online Fashion Purchase Intention while Creating and Using a Customised Avatar. In.
Levac, D., Glegg, S., Colquhoun, H., Miller, P., & Noubary, F. (2017). Virtual reality and active videogame-based practice, learning needs, and preferences: a cross-Canada survey of physical therapists and occupational therapists. Games for health journal, 6(4), 217-228.
Lin, H.-F. (2007). Predicting consumer intentions to shop online: An empirical test of competing theories. Electronic Commerce Research and Applications, 6(4), 433-442.
Lin, J.-H. T., Wu, D.-Y., & Tao, C.-C. (2018). So scary, yet so fun: The role of self-efficacy in enjoyment of a virtual reality horror game. New Media & Society, 20(9), 3223-3242.
Lowry, P. B., Gaskin, J., Twyman, N., Hammer, B., & Roberts, T. (2012). Taking ‘fun and games’ seriously: Proposing the hedonic-motivation system adoption model (HMSAM). Journal of the association for information systems, 14(11), 617-671.
MacCallum, R. C., & Hong, S. (1997). Power analysis in covariance structure modeling using GFI and AGFI. Multivariate behavioral research, 32(2), 193-210.
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
McDonald, R. P., & Ho, M.-H. R. (2002). Principles and practice in reporting structural equation analyses. Psychological methods, 7(1), 64.
Merikivi, J., & Mantymaki, M. (2009). Explaining the continuous use of social virtual worlds: An applied theory of planned behavior approach. 2009 42nd Hawaii International Conference on System Sciences,
Merle, A., Senecal, S., & St-Onge, A. (2012). Whether and how virtual try-on influences consumer responses to an apparel web site. International Journal of Electronic Commerce, 16(3), 41-64.
Misirlis, N., & Munawar, H. B. (2022). An analysis of the technology acceptance model in understanding university students′ behavioral intention to use metaverse technologies.
Mäntymäki, M., Merikivi, J., Verhagen, T., Feldberg, F., & Rajala, R. (2014). Does a contextualized theory of planned behavior explain why teenagers stay in virtual worlds? International Journal of Information Management, 34(5), 567-576. https://doi.org/10.1016/j.ijinfomgt.2014.05.003
Morgan Stanley. (2022). The Metaverse - The Next Mobile Internet? Morgan Stanley). M. Stanley.
Mostafa, L. (2022). Measuring Technology Acceptance Model to use Metaverse Technology in Egypt. مجلةالبحوثالماليةوالتجارية, 23(3), 118-142.
Mulaik, S. A., James, L. R., Van Alstine, J., Bennett, N., Lind, S., & Stilwell, C. D. (1989). Evaluation of goodness-of-fit indices for structural equation models. Psychological bulletin, 105(3), 430.
Muylle, S., Moenaert, R., & Despontin, M. (2004). The conceptualization and empirical validation of web site user satisfaction. Information & Management, 41(5), 543-560.
Newzoo. (2021). Introduction to the Metaverse.
Nissim, Y., & Weissblueth, E. (2017). Virtual reality (VR) as a source for self-efficacy in teacher training. International Education Studies, 10(8), 52-59.
Nunnally, J. C. (1994). Psychometric theory 3E. Tata McGraw-hill education.
Oh, J.-H. (2021). A study on factors affecting the intention to use the Metaverse by applying the extended technology acceptance model (ETAM): focused on the virtual world Metaverse. The Journal of the Korea Contents Association, 21(10), 204-216.
Park, S.-M., & Kim, Y.-G. (2022). A Metaverse: Taxonomy, components, applications, and open challenges. IEEE Access, 10, 4209-4251.
Park, S., & Kang, Y. J. (2021). A Study on the intentions of early users of metaverse platforms using the Technology Acceptance Model. Journal of Digital Convergence, 19(10), 275-285.
Plotkina, D., & Saurel, H. (2019). Me or just like me? The role of virtual try-on and physical appearance in apparel M-retailing. Journal of Retailing and Consumer Services, 51, 362-377. https://doi.org/10.1016/j.jretconser.2019.07.002
Radoff, J. (2021). The Metaverse Value-Chain. https://medium.com/building-the-metaverse/the-metaverse-value-chain-afcf9e09e3a7
Ramalingam, V., LaBelle, D., & Wiedenbeck, S. (2004). Self-efficacy and mental models in learning to program. Proceedings of the 9th annual SIGCSE conference on Innovation and technology in computer science education,
Ramayah, T., & Ignatius, J. (2005). Impact of perceived usefulness, perceived ease of use and perceived enjoyment on intention to shop online. ICFAI Journal of Systems Management (IJSM), 3(3), 36-51.
Reed Smith. (2021). Guide to the Metaverse.
Rese, A., Baier, D., Geyer-Schulz, A., & Schreiber, S. (2017). How augmented reality apps are accepted by consumers: A comparative analysis using scales and opinions. Technological Forecasting and Social Change, 124, 306-319. https://doi.org/10.1016/j.techfore.2016.10.010
Rogers, E. M. (1983). Diffusion of innovations.
Rogers, E. M. (2003). Diffusion of innovations. In Diffusion of Innovations (pp. 551-551).
Rospigliosi, P. a. (2022). Metaverse or Simulacra? Roblox, Minecraft, Meta and the turn to virtual reality for education, socialisation and work. Interactive Learning Environments, 30(1), 1-3. https://doi.org/10.1080/10494820.2022.2022899
Ryan, R. M., & Deci, E. L. (2000). Intrinsic and extrinsic motivations: Classic definitions and new directions. Contemporary educational psychology, 25(1), 54-67.
Saleem, M., Kamarudin, S., Shoaib, H. M., & Nasar, A. (2021). Influence of augmented reality app on intention towards e-learning amidst COVID-19 pandemic. Interactive Learning Environments, 1-15.
Shen, B., Tan, W., Guo, J., Zhao, L., & Qin, P. (2021). How to Promote User Purchase in Metaverse? A Systematic Literature Review on Consumer Behavior Research and Virtual Commerce Application Design. Applied Sciences, 11(23). https://doi.org/10.3390/app112311087
Shin, D. (2022). The actualization of meta affordances: Conceptualizing affordance actualization in the metaverse games. Computers in Human Behavior, 133. https://doi.org/10.1016/j.chb.2022.107292
Spielberg, S., Silvestri, A., Penn, Z., Cline, E., & De Line, D. (2018). Ready player one. Warner Bros USA.
Stephenson, N. (1992). Snow crash. Bantam Books.
Suh, W., & Ahn, S. (2022). Utilizing the Metaverse for Learner-Centered Constructivist Education in the Post-Pandemic Era: An Analysis of Elementary School Students. Journal of Intelligence, 10(1), 17.
Taylor, S., & Todd, P. (1995). Decomposition and crossover effects in the theory of planned behavior: A study of consumer adoption intentions. International journal of research in marketing, 12(2), 137-155.
Teo, A. C., Tan, G. W. H., Cheah, C. M., Ooi, K. B., & Yew, K. T. (2012). Can the demographic and subjective norms influence the adoption of mobile banking? International Journal of Mobile Communications, 10(6), 578-597.
Teo, T., & Noyes, J. (2011). An assessment of the influence of perceived enjoyment and attitude on the intention to use technology among pre-service teachers: A structural equation modeling approach. Computers & education, 57(2), 1645-1653.
Ullman, J. (2001). Structural equation modeling. U: BG Tabachnick, LS Fidel (ur.)-Using Multivariate Statistics. In: Allyn & Bacon, Needham Heights.
Valente, T. W. (1996). Network models of the diffusion of innovations. In: Springer.
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management science, 46(2), 186-204.
Verhagen, T., Feldberg, F., van den Hooff, B., Meents, S., & Merikivi, J. (2011). Satisfaction with virtual worlds: An integrated model of experiential value. Information & Management, 48(6), 201-207.
Wang, E. S.-T. (2014). Perceived control and gender difference on the relationship between trialability and intent to play new online games. Computers in Human Behavior, 30, 315-320.
Wright, S. (1921). Correlation and causation.
Xi, N., Chen, J., Gama, F., Riar, M., & Hamari, J. (2022). The challenges of entering the metaverse: An experiment on the effect of extended reality on workload. Inf Syst Front, 1-22. https://doi.org/10.1007/s10796-022-10244-x
Yeap, J. A. L., Ramayah, T., & Soto-Acosta, P. (2016). Factors propelling the adoption of m-learning among students in higher education. Electronic Markets, 26(4), 323-338. https://doi.org/10.1007/s12525-015-0214-x
Yim, M. Y.-C., Chu, S.-C., & Sauer, P. L. (2017). Is Augmented Reality Technology an Effective Tool for E-commerce? An Interactivity and Vividness Perspective. Journal of Interactive Marketing, 39, 89-103. https://doi.org/10.1016/j.intmar.2017.04.001
Yu, Z., & Song, X. (2021). User Intention of Anonymous Social Application “Soul” in China: Analysis based on an Extended Technology Acceptance Model. Journal of Theoretical and Applied Electronic Commerce Research, 16(7), 2898-2921. https://doi.org/10.3390/jtaer16070159
Yuan, Y. C., Cosley, D., Welser, H. T., Xia, L., & Gay, G. (2009). The diffusion of a task recommendation system to facilitate contributions to an online community. Journal of Computer-Mediated Communication, 15(1), 32-59.
Zolait, A. H. S., & Sulaiman, A. (2009). The influence of communication channels on internet banking adoption. Asian Journal of Business and Accounting, 2(1&2), 115-134.
愛立信消費者及產業研究室. (2022). 2030年十大消費者趨勢. |