A study on acceptance of smart fashion products - An empirical test of an extended technology acceptance model - Jeong, So Won; Roh, Jung-Sim;
Using the extended technology acceptance model (TAM), the study aimed to understand consumers` adoption process for smart fashion products. The research model was designed to examine the impacts of perceived ease of use and usefulness on attitude and behavior intention toward smart fashion products based on the technology innovativeness, enjoyment, and subjective norm variables. An online survey was conducted on consumers by employing a marketing research company. A total of 230 useable responses were obtained. Confirmatory Factor Analysis (CFA) was performed to test the measurement model. The proposed hypotheses were tested by employing the Structural Equation Model (SEM). The results found a positive impact of perceived ease of use on usefulness and a positive influence of usefulness on attitude and behavior intention. Attitude had a positive effect on behavior intention. In addition, technology innovativeness was found to have a positive influence on perceived ease of use and enjoyment had a positive influence on usefulness and attitude. Subjective norm predicted behavior intention. The findings of the study contribute to smart fashion literature and have important implications for smart fashion product developers and marketers, as they offer insights into the important role of technology innovativeness, enjoyment, and subjective norms perceived by consumers in improving attitudes and behavior intentions toward the products. Limitations and future research directions are discussed.
Agarwal, R., & Prasad, J. (1998). A conceptual and operational definition of personal innovativeness in the domain of information technology. Information Systems Research, 9(2), 204-215. doi:10.1287/isre.9.2.204
Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modelling in practice: A review and recommended two-stage approach. Psychological Bulletin, 103(3), 411-423. doi:10.1037/0033-2909.103.3.411
Celik, H. E., & Yilmaz, V. (2011). Extending the technology acceptance model for adoption of e-shopping by consumers in Turkey. Journal of Electronic Commerce Research, 12(2), 152-164.
Chae, J. M. (2010). Consumers' acceptance of smart clothing: A comparison between perceived group and non-perceived group. Journal of the Korean Society of Clothing and Textiles, 34(6), 969-981. doi:10.5850/JKSCT.2010.34.6.969
Chuttur, M. Y. (2009). Overview of the technology acceptance model: Origins, developments and future directions. Working Papers on Information Systems, 9(37), 9-37.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. doi:10.2307/249008
Davis, F. D., Bagozzi, R. P., & Warchaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982-1003. doi:10.1287/mnsc.35.8.982
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace. Journal of Applied Social Psychology, 22(14), 1111-1132. doi:10.1111/j.1559-1816.1992.tb00945.x
Fu, F. Q., & Elliott, M. T. (2013). The moderating effect of perceived product innovativeness and product knowledge on new product adoption: An integrated model. Journal of Marketing Theory and Practice, 21(3), 257-272. doi:10.2753/MTP1069-6679210302
Ha, S., & Stoel, L. (2009). Consumer e-shopping acceptance: Antecedents in a technology acceptance model. Journal of Business Research, 62(5), 565-571. doi:10.1016/j.jbusres.2008.06.016
Ha, Y., & Im, H. (2014). Determinants of mobile coupon service adoption: Assessment of gender difference. International Journal of Retail & Distribution Management, 42(5), 441-459. doi:10.1108/IJRDM-08-2012-0074
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2009). Multivariate data analysis (7th ed.). Upper Saddle River, NJ: PrenticeHall.
Hsu, C. L., & Lu, H. P. (2004). Why do people play on-line games? An extended TAM with social influences and flow experience. Information & Management, 41(7), 853-868. doi:10.1016/j.im.2003.08.014
Kang, K. Y., & Jin, H. J. (2007). A study of consumers' clothing buying intention adopted by the technology acceptance model. Journal of the Korean Society of Clothing and Textiles, 31(8), 1211-1221. doi:10.5850/JKSCT.2007.31.8.1211
Kim, J. & Forsythe, S. (2010). Factors affecting adoption of product virtualization technology for online consumer electronics shopping. International Journal of Retail & Distribution Management, 38(3), 190-204. doi:10.1108/09590551011027122
Ko, A. R., & Kim, S. H. (2014). A study on fashion brand's SNS marketing: Based on technology acceptance model (TAM). The Research Journal of the Costume Culture, 22(6), 1011-1027. doi:10.7741/rjcc.2014.22.6.1011
Lee, H. M. (2009). A study on the acceptance of wearable computers based on the extended technology acceptance model. The Research Journal of the Costume Culture, 17(6), 1155-1172.
Noh, M. J., & Park, H. H. (2011). Acceptance of the smart clothing according to trend and information innovation. The Journal of the Korea Contents Association, 11(11), 350-363. doi:10.5392/JKCA.2011.11.11.350
Park, H. (2014, February 28). 패션디자인과 ICT 융복합 활성화를 통한 패션의류산업의 신성장 전략 [Growth strategy of fashion clothing industry by integrating fashion design and ICT convertgence]. Korea Institute for Industrial Economics & Trade, Retrieved April 21, 2016 from http://www.kiet.re.kr/kiet_web/?sub_num=8&state=view&idx=47793
Park, H. H., & Noh, M. J. (2012). The influence of consumers' innovativeness and trust on acceptance intention of sensor-based smart clothing. Fashion & Textile Research Journal, 14(1), 24-36. doi:10.5805/KSCI.2012.14.1.024
Porter, C. L., & Donthu, N. (2006). Using the technology acceptance model to explain how attitudes determine Internet usage: The role of perceived access barriers and demographics. Journal of Business Research, 59(9), 999-1007. doi:10.1016/j.jbusres.2006.06.003
Rogers, E. M. (2003). Diffusion of innovations (5th ed.). NY: Free Press.
Suh, S. E., & Roh, J. S. (2015). A study on smart fashion product development trends. The Research Journal of the Costume Culture, 23(6), 1097-1115. doi:10.7741/rjcc.2015.23.6.1097
Yang, K. (2010). Determinants of US consumer mobile shopping services adoption: Implications for designing mobile shopping services. Journal of Consumer Marketing, 27(3), 262-270. doi:10.1108/07363761011038338