The Research Journal of the Costume Culture (복식문화연구)

The Costume Culture Association (복식문화학회)
권호 표지
DOI QR코드

DOI QR Code

Influencing factors on purchase intention for smart healthcare clothing by gender and age - Focused on TAM, clothing attributes, health-lifestyle, and fashion innovativeness -

스마트 헬스케어 의류 구매의도에 대한 성별과 연령대별 영향 요인 - 기술수용모델(TAM), 의복속성, 건강라이프스타일, 패션혁신성을 중심으로 -

  • Received : 2019.11.04
  • Accepted : 2019.12.06
  • Published : 2019.12.31
Download PDF
⟨ Previous Next ⟩

Abstract

Smart healthcare clothing combines IoT, new technology, and clothing construction to perform specific care functions, and its utility has been expanding rapidly within aging and diversified societies. However, the related market remains at an early stage of development due to limited regulation, lack of consumer awareness, and the need for not only technical development but promotion plans for potential users. This paper aims to analyze factors influencing purchase intention for smart healthcare clothing with biosignal monitoring, including variables in the Technology Acceptance Model (TAM), clothing attributes, health-related lifestyle factors, and fashion innovativeness. A survey was conducted on a sample of 300 males and 300 females ranging in age from 20 to 50 years, and data were analyzed using SPSS 21.0. The results show that perceived usefulness, perceived aesthetic attributes, health responsibility, and fashion innovativeness were overall significant predictors of using smart healthcare clothing. Additionally, perceived ease of use and physical activity in the male subsample, and perceived compatibility within the female group, also had significant effects. Furthermore, age was a determining factor; for subjects in the 30s age group, perceived usefulness, compatibility, and health responsibility had significant positive associations. The results of this study can provide basic guidelines for designing merchandising plans to expand user acceptance of smart healthcare clothing.

Keywords

References

  1. Baek, M., Choi, H., & Lee, H. (2015). Age-specific acceptance intention over wearable smart healthcare device. Korean Journal Business Administration, 28(12), 3171-3189. doi:10.18032/kaaba.2015.28.12.3171
  2. Bagozzi, R. P., Davis, F. D., & Warshaw, P. R. (1992). Development and test of a theory of technological learning and usage. Human Relations, 45(7), 659-686. doi:10.1177/001872679204500702
  3. Chae, J. M. (2009). Consumer acceptance model of smart clothing according to innovation. International Journal of Human Ecology, 10(1), 23-33.
  4. Chae, J. M. (2010). The extended technology acceptance model according to smart clothing types. Korean Journal of Human Ecology, 19(2), 375-387. doi:10.5934/KJHE.2010.19.2.375
  5. Chae, J. M., Cho, H. S., & Lee, J. H. (2009). A study on consumer acceptance toward the commercialized smart clothing. Korean Journal of the Science of Sensibility, 12(2), 181-192.
  6. Cho, S., & Workman, J. (2011). Gender, fashion innovativeness and opinion leadership, and need for touch. Journal of Fashion Marketing and Management, 15(3), 363-382. doi:10.1108/13612021111151941
  7. Cho, Y. J., Choi, J. H., & Beak, H. K. (2010). Gender and age differences in evaluative criteria and information sources of functional clothing. Journal of the Korean Society of Costume, 60(9), 150-161.
  8. 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
  9. Hsiao, C. H., & Tang, K. Y. (2015). Examining a model of mobile healthcare technology acceptance by the elderly in Taiwan. Journal of Global Information Technology Management, 18(4), 292-311. doi:10.1080/1097198X.2015.1108099
  10. Hwang, C., Chung, T. L., & Sanders, E. A. (2016). Attitudes and purchase intentions for smart clothing. Clothing and Textiles Research Journal, 34(3), 207-222. doi:10.1177/0887302X16646447
  11. Kang, K. Y., & Jin, H. J. (2007). Innovativeness and technological innovativeness on attitudes and buying intention toward smart clothing. Fashion and Textile Research Journal, 9(1), 35-40.
  12. Kang, Y. S., Ha, Y., & Eun, Y. (2012). Health status and health-promoting lifestyle profile II of North Korean immigrants. Journal of Korean Academy of Community Health Nursing, 23(3), 231-243. doi:10.12799/jkachn.2012.23.3.231
  13. Ko, E., Sung, H., & Yun, H. (2008). The effect of innovation and perceived risk on product attitudes and intention to adopt smart wear. Journal of Global Academy of Marketing Science, 18(2), 94-111. doi:10.1080/12297119.2008.9707247
  14. Ko, E., Sung, H., & Yun, H. (2009). Comparative analysis of purchase intentions toward smart clothing between Korean and US consumers. Clothing and Textiles Research Journal, 27(4), 259-273. doi:10.1177/0887302X08327086
  15. Korea Textile Development Institute. (2018). 스마트 의류 시장 동향 및 성공을 위한 도전 과제 [Smart clothing market trend and challenge for success]. Retrieved October 20, 2019, from http://super.textopia.or.kr:8888/newsletter/180918/lib02_1.pdf
  16. Lee, S. I., Yoo, W. J., Park, H. S., & Kim, S. H. (2016). An empirical study on acceptance intention towards healthcare wearable device. The Journal of Information System, 25(2), 27-50. doi:10.5859/KAIS.2016.25.2.27
  17. Lee, S. Y., & Lee, K. (2018). Factors that influence an individual's intention to adopt a wearable healthcare device: The case of a wearable fitness tracker. Technological Forecasting and Social Change, 129(2018), 154-163. doi:10.1016/j.techfore.2018.01.002
  18. Lunney, A., Cunningham, N. R., & Eastin, M. S. (2016). Wearable fitness technology: A structural investigation into acceptance and perceived fitness outcomes. Computers in Human Behavior, 65, 114-120. doi:10.1016/j.chb.2016.08.007
  19. National Institute of Food and Drug Safety Evaluation. (2018). 스마트 헬스케어 의료기기 기술.표준 전략 보고서 [Report of Strategy for Smart Healthcare Medical Device Technology and Standard]. Retrieved October 20, 2019, from https://www.mfds.go.kr/brd/m_218/view.do?seq=33260&srchFr=&srchTo=&srchWord=&srchTp=&itm_seq_1=0&itm_seq_2=0&multi_itm_seq=0&company_cd=&company_nm=&page=1
  20. Nazarian, R. (2016, January 4). This sports bra is not only comfortable, it can track your fitness data. Retrieved December 17, 2019, from https://www.digitaltrends.com/health-fitness/ombra-omrun-news/
  21. Noh, M. J., & Park, H. H. (2011). An effect of the beliefs, perceived enjoyment, and trust on the acceptance about the smart clothing: Moderating effect of price consciousness of the smart clothing. Journal of Industrial Economics and Business, 24(4), 2473-2497.
  22. Noh, M. J., Park, H. H., & Jang, H. Y. (2011). An effect of the perceived value on the trust and acceptance intention of the smart clothing: Moderating effect of price involvement toward clothing. Journal of Business Research, 26(3), 123-147. https://doi.org/10.22903/JBR.2011.26.3.123
  23. Park, H. H., & Noh, M. J. (2011). The influence of product attribute of smart clothing on initial trust and purchase intention: Focused on sensor-based smart clothing. Family and Environment Research, 49(6), 13-22. doi:10.6115/khea.2011.49.6.013
  24. Perry, A., Malinin, L., Sanders, E., Li, Y., & Leigh, K. (2017). Explore consumer needs and design purposes of smart clothing from designers' perspectives. International Journal of Fashion Design, Technology and Education, 10(3), 372-380. doi:10.1080/17543266.2016.1278465
  25. Rogers, E. M. (2003). Diffusion of innovations (5th ed.). New York: The Free Press.
  26. Rogers, E. M., & Shoemaker, F. F. (1971). Communication of innovations; A cross-cultural approach. New York: The Free Press.
  27. Trend Spectrum. (2014, May 13). 캐나다 Omsignal, 스마트 의류 정식 출시 [Canada Omsignal, the of ficial release of smart clothing]. Retrieved December 17, 2019, from http://trendspectrum.co.kr/?p=18228
  28. 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. doi:10.1287/isre.11.4.342.11872
  29. Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204. doi:10.1287/mnsc.46.2.186.11926
  30. 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. doi:10.2307/30036540
  31. Walker, S. N., Sechrist, K. R., & Pender, N. J. (1995). Health promoting lifestyle profile II. Retrieved July 10, 2018, from University of Nebraska Medical Center, College of nursing Web site: https://www.unmc.edu/nursing/faculty/English_HPLPII.pdf
  32. Wood, E. E. (2016, March 28). Smart textile maker OmSignal is disrupting an industry by embracing it. Retrieved December 17, 2019, from https://www.itworldcanada.com/article/smart-textile-makeromsignal-is-disrupting-an-industry-by-embracingit/381920
  33. Zhang, M., Luo, M., Nie, R., & Zhang, Y. (2017). Technical attributes, health attribute, consumer attributes and their roles in adoption intention of healthcare wearable technology. International Journal of Medical Informatics, 108, 97-109. doi:10.1016/j.ijmedinf.2017.09.016

Cited by

  1. 리테일 서비스 로봇의 소비자 수용에 관한 연구 vol.28, pp.4, 2020, https://doi.org/10.29049/rjcc.2020.28.4.409
  2. 기술불안감과 지각된 생산성이 셀프서비스테크놀로지에 대한 태도에 미치는 영향 - 상호작용욕구의 조절효과를 중심으로 - vol.28, pp.4, 2019, https://doi.org/10.29049/rjcc.2020.28.4.480
  3. 스마트슈즈 위험지각이 스마트슈즈 유형별 구매의도에 미치는 영향 vol.23, pp.1, 2019, https://doi.org/10.5805/sfti.2021.23.1.84