DOI QR코드

DOI QR Code

스마트패션제품 수용에 관한 연구 - 확장된 기술수용모형 실증연구 -

A study on acceptance of smart fashion products - An empirical test of an extended technology acceptance model -

  • Jeong, So Won (Dept. of Clothing & Textiles, Sangmyung University) ;
  • Roh, Jung-Sim (Dept. of Clothing & Textiles, Sangmyung University)
  • 투고 : 2016.04.15
  • 심사 : 2016.04.29
  • 발행 : 2016.04.30

초록

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.

키워드

참고문헌

  1. 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
  2. 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
  3. 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.
  4. 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
  5. Chuttur, M. Y. (2009). Overview of the technology acceptance model: Origins, developments and future directions. Working Papers on Information Systems, 9(37), 9-37.
  6. 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
  7. 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
  8. 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
  9. 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
  10. 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
  11. 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
  12. Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2009). Multivariate data analysis (7th ed.). Upper Saddle River, NJ: PrenticeHall.
  13. 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
  14. 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
  15. 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
  16. 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
  17. 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. https://doi.org/10.29049/rjcc.2009.17.6.1155
  18. 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
  19. 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
  20. 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
  21. 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
  22. Rogers, E. M. (2003). Diffusion of innovations (5th ed.). NY: Free Press.
  23. 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
  24. 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

피인용 문헌

  1. Consumers’ perceptions of interactive digital signage in a fashion store vol.26, pp.6, 2018, https://doi.org/10.29049/rjcc.2018.26.6.836
  2. 혁신의 확산 혹은 혼란 - 스마트 의류 잠재적 채택자 관점 - vol.26, pp.2, 2016, https://doi.org/10.29049/rjcc.2018.26.2.157
  3. Consumer resistance to innovation: smart clothing vol.7, pp.None, 2016, https://doi.org/10.1186/s40691-020-00210-z