A study of Chinese consumers’ adoption behaviour toward virtual fitting rooms

References

• Banks, A. (2016). Augmented reality examples: How fashion & retail are using it. Retrieved from https://www.highsnobiety.com/2016/07/25/augmented-reality-examples/
   Google Scholar
• Beck, M., & Crié, D. (2018). I virtually try it … I want it! virtual fitting room: A tool to increase on-line and off-line exploratory behavior, patronage and purchase intentions. Journal of Retailing and Consumer Services, 40, 279–286.
   Web of Science ®Google Scholar
• Behling, D. U. (1992). Three and a half decades of fashion adoption research: What have we learned? Clothing and Textiles Research Journal, 10(2), 34–41.
   Google Scholar
• Benoff, J. (2012). The webcam social shopper’s 1st Facebook integration. Retrieved from http://staging.zugara.com/wss2/virtual-dressing-room-facebook-integration/
   Google Scholar
• Blazquez, M. (2014). Fashion shopping in multichannel retail: The role of technology in enhancing the customer experience. International Journal of Electronic Commerce, 18(4), 97–116.
   Web of Science ®Google Scholar
• Cambre, M. A., & Cook, D. L. (1985). Computer anxiety: Definition, measurement, and correlates. Journal of Educational Computing Research, 1(1), 37–54.
   Google Scholar
• Cheng, M. (2017). eCommerce in China – the future is already here. Retrieved from https://www.pwccn.com/en/industries/retail-and-consumer/publications/total-retail-survey-2017-china-cut.html
   Google Scholar
• Cho, S., & Workman, J. E. (2015). College students’ frequency of use of information sources by fashion leadership and style of information processing. Fashion and Textiles, 2(1), 25.
   Web of Science ®Google Scholar
• Coleman, L. D. (2017). What to expect from China's $46 Billion AI focus as it hits CES. Retrieved from https://www.forbes.com/sites/laurencoleman/2017/12/10/what-to-expect-from-chinas-46-billion-ai-focus-as-it-hits-ces/
   Google Scholar
• Davis, F. D. (1985). A technology acceptance model for empirically testing new end-user information systems: Theory and results. Doctoral dissertation. Massachusetts Institute of Technology.
   Google Scholar
• 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.
   Web of Science ®Google Scholar
• Dawndasekare, D. M. S. P. K., Subhasinghe, V. C. S., Hemendra, K. H. S., Anuradha, P. K., & Niroshika, A. (2016). The Real-time Virtual Fitting Room: VFIT.
   Google Scholar
• Eraslan Yalcin, M., & Kutlu, B. (2019). Examination of students’ acceptance of and intention to use learning management systems using extended TAM. British Journal of Educational Technology, 50(5), 2414–2432.
   Web of Science ®Google Scholar
• Erra, U., Scanniello, G., & Colonnese, V. (2018). Exploring the effectiveness of an augmented reality dressing room. Multimedia Tools and Applications, 77(19), 25077–25107.
   Web of Science ®Google Scholar
• Fishbein, M., & Ajzen, I. (1977). Belief, attitude, intention, and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.
   Google Scholar
• Gao, Y., Brooks, E. P., & Brooks, A. L. (2014, June). The performance of self in the context of shopping in a virtual dressing room system. In International Conference on HCI in Business (pp. 307–315). Springer, Cham.
   Google Scholar
• Goldsmith, R. E., Freiden, J. B., & Kilsheimer, J. C. (1993). Social values and female fashion leadership: A cross-cultural study. Psychology & Marketing, 10(5), 399–412.
   Google Scholar
• Hackbarth, G., Grover, V., & Mun, Y. Y. (2003). Computer playfulness and anxiety: Positive and negative mediators of the system experience effect on perceived ease of use. Information & Management, 40(3), 221–232.
   Web of Science ®Google Scholar
• 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.
   Web of Science ®Google Scholar
• Huang, T. L., & Liao, S. (2015). A model of acceptance of augmented-reality interactive technology: The moderating role of cognitive innovativeness. Electronic Commerce Research, 15(2), 269–295.
   Web of Science ®Google Scholar
• Huang, N., & Qin, G. (2011, May). A study of online virtual fitting room adoption based on UTAUT. In 2011 International Conference on E-Business and E-Government (ICEE) (pp. 1–4). IEEE.
   Google Scholar
• Hwang, Y., & Kim, D. J. (2007). Customer self-service systems: The effects of perceived Web quality with service contents on enjoyment, anxiety, and e-trust. Decision Support Systems, 43(3), 746–760.
   Web of Science ®Google Scholar
• Igbaria, M., Schiffman, S. J., & Wieckowski, T. J. (1994). The respective roles of perceived usefulness and perceived fun in the acceptance of microcomputer technology. Behaviour & Information Technology, 13(6), 349–361.
   Web of Science ®Google Scholar
• Kim, J. B. (2012). An empirical study on consumer first purchase intention in online shopping: Integrating initial trust and TAM. Electronic Commerce Research, 12(2), 125–150.
   Web of Science ®Google Scholar
• Kim, J., & Forsythe, S. (2008). Adoption of virtual try-on technology for online apparel shopping. Journal of Interactive Marketing, 22(2), 45–59.
   Web of Science ®Google Scholar
• Kim, J., & Hahn, K. H. (2012). Effects of personal traits on generation y consumers’ attitudes toward the use of mobile devices for communication and commerce. Human Technology: An Interdisciplinary Journal on Humans in ICT Environments, 8(2), 133–156.
   Google Scholar
• Kim, H. S., & Hong, H. (2011). Fashion leadership and hedonic shopping motivations of female consumers. Clothing and Textiles Research Journal, 29(4), 314–330.
   Web of Science ®Google Scholar
• Kim, H., & Karpova, E. (2010). Consumer attitudes toward fashion counterfeits: Application of the theory of planned behavior. Clothing and Textiles Research Journal, 28(2), 79–94.
   Web of Science ®Google Scholar
• Kim, D. E., & LaBat, K. (2013). Consumer experience in using 3D virtual garment simulation technology. Journal of the Textile Institute, 104(8), 819–829.
   Web of Science ®Google Scholar
• Kuo, B. C., Roldan-Bau, A., & Lowinger, R. (2015). Psychological help-seeking among Latin American immigrants in Canada: Testing a culturally-expanded model of the Theory of Reasoned Action using path analysis. International Journal for the Advancement of Counselling, 37(2), 179–197.
   Web of Science ®Google Scholar
• Lee, J., Kim, J., & Choi, J. Y. (2019). The adoption of virtual reality devices: The technology acceptance model integrating enjoyment, social interaction, and strength of the social ties. Telematics and Informatics, 39, 37–48.
   Web of Science ®Google Scholar
• Liang, D. (2017). Research on virtual fitting and intelligent e-commerce system. Sci-tech Innovation and Productivity, 218(6), 61.
   Google Scholar
• Liaw, C., & Chen, C. (2013). The impact of virtual fitting room technology on consumers’ online purchase intention. Management and Administrative Sciences Review, 2(1), 23–35.
   Google Scholar
• Meuter, M. L., Ostrom, A. L., Bitner, M. J., & Roundtree, R. (2003). The influence of technology anxiety on consumer use and experiences with self-service technologies. Journal of Business Research, 56(11), 899–906.
   Web of Science ®Google Scholar
• Michon, R., Yu, H., Smith, D., & Chebat, J. C. (2007). The shopping experience of female fashion leaders. International Journal of Retail & Distribution Management, 35(6), 488–501.
   Google Scholar
• Ochwat, D. (2017). The DressingRoom by Gap Mobile App. Retrieved from https://shoppermarketingmag.com/dressingroom-gap-mobile-app
   Google Scholar
• Pavlou, P. A. (2003). Consumer acceptance of electronic commerce: Integrating trust and risk with the technology acceptance model. International Journal of Electronic Commerce, 7(3), 101–134.
   Web of Science ®Google Scholar
• 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.
   Google Scholar
• Reynolds, F. D., & Darden, W. R. (1973). Fashion theory and pragmatics – case of midi. Journal of Retailing, 49(1), 51–62.
   Web of Science ®Google Scholar
• Saadé, R., & Bahli, B. (2005). The impact of cognitive absorption on perceived usefulness and perceived ease of use in on-line learning: An extension of the technology acceptance model. Information & Management, 42(2), 317–327.
   Web of Science ®Google Scholar
• Schrank, H. L., Sugawara, A. I., & Kim, M. (1982). Part 2: Comparison of Korean and American fashion leaders. Home Economics Research Journal, 10(3), 235–240.
   Google Scholar
• Sekhavat, Y. A. (2016). Privacy preserving cloth try-on using mobile augmented reality. IEEE Transactions on Multimedia, 19(5), 1041–1049.
   Web of Science ®Google Scholar
• Suki, N. M., & Suki, N. M. (2011). Exploring the relationship between perceived usefulness, perceived ease of use, perceived enjoyment, attitude and subscribers’ intention towards using 3G mobile services. Journal of Information Technology Management, 22(1), 1–7.
   Google Scholar
• Van der Heijden, H. (2003). Factors influencing the usage of websites: The case of a generic portal in The Netherlands. Information & Management, 40(6), 541–549.
   Web of Science ®Google Scholar
• Van der Heijden, H. (2004). User acceptance of hedonic information systems. MIS Quarterly, 28(4), 695–704.
   Web of Science ®Google Scholar
• 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.
   Web of Science ®Google Scholar
• Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273–315.
   Web of Science ®Google Scholar
• 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.
   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(3), 425–478.
   Web of Science ®Google Scholar
• Yang, K., & Forney, J. C. (2013). The moderating role of consumer technology anxiety in mobile shopping adoption: Differential effects of facilitating conditions and social influences. Journal of Electronic Commerce Research, 14(4), 334.
   Web of Science ®Google Scholar
• Yuan, M., Khan, I. R., Farbiz, F., Yao, S., Niswar, A., & Foo, M. (2013). A mixed reality virtual clothes try-on system. IEEE Transactions on Multimedia, 15(8), 1958–1968.
   Web of Science ®Google Scholar
• Zhang, B., & Kim, J. H. (2013). Luxury fashion consumption in China: Factors affecting attitude and purchase intent. Journal of Retailing and Consumer Services, 20(1), 68–79.
   Google Scholar
• Zhang, T., Wang, W. Y. C., Cao, L., & Wang, Y. (2019). The role of virtual try-on technology in online purchase decision from consumers’ aspect. Internet Research, 29(3), 529–551.
   Web of Science ®Google Scholar