Consumer Acceptance Model of Smart Clothing according to Innovation

  • Chae, Jin-Mie (Department of Home Economics Education, Chung-Ang University)
  • Received : 2009.04.02
  • Accepted : 2009.06.01
  • Published : 2009.06.30

Abstract

This study identified the appropriateness of acceptance models of smart clothing and differences in the hypothesis of the path to clothing acceptance by classifying consumers depending on the level of technology innovation and fashion innovation through the extended TAM (Technology Acceptance Model) presented by Chae (2009). 815 copies of data were collected from adults over twenty living in major South Korean cities and analyzed them using a SPSS 15.0 and AMOS 5.0 package. Based on the average value of technology innovation and fashion innovation, the respondents were classified into: Group 1 with high technology innovation and fashion innovation, Group 2 with high technology innovation but low fashion innovation, Group 3 with low technology innovation but high fashion innovation, and Group 4 with low technology innovation and fashion innovation. The appropriateness of models for the four classified groups was verified. The analysis proved that an extended TAM for each classified group explains the acceptance process of smart clothing; especially the appropriateness of model of Group 1 and Group 4 was comparatively higher than other groups. Perceived usefulness was revealed as the key variable that affects consumer attitudes to accept smart clothing. Perceived ease of use has indirect positive effects on consumer attitudes passing through perceived usefulness and clothing involvement partly exerted impacts on consumer attitudes and the intention of acceptance. The mediating role of attitudes to explain the intention of the acceptance of smart clothing is high and suggests that it is necessary to take a positive role to help the consumer perceive the functional and useful aspects of the clothing.

Keywords

References

  1. Adams, D. A., Nelson, R. R., & Todd, P. A. (1992). Perceived usefulness, ease of use, & usage of information technology: A replication. MIS Quarterly, 16(2), 227-247 https://doi.org/10.2307/249577
  2. Agarwal, R., & Karahanna, E. (2000). Time flies when you're having fun: Cognitive absorption and beliefs about information technology usage. MIS Quarterly, 24(4), 665-694 https://doi.org/10.2307/3250951
  3. Agarwal, R., & Prasad, J. (1998). A conceptual and operational definition of personal innovation in the domain of information technology. Information Systems Research, 9(2), 204-215 https://doi.org/10.1287/isre.9.2.204
  4. Agarwal, R., & Prasad, J. (1999). Are individual differences germane to the acceptance of new information technologies?. Decision Sciences, 30(2), 361-391 https://doi.org/10.1111/j.1540-5915.1999.tb01614.x
  5. Chae, J. M. (2009). Extending the technology acceptance model for smart clothing. Journal of Korean Home Economics Association, 47(7), 99-110
  6. Chattopadhyay, A., & Basu, K. (1990). Humor in advertising: The moderating role of prior brand evaluation. Journal of Marketing Research, 27, 466-476 https://doi.org/10.2307/3172631
  7. Chen, L. D., Gillenson, M. L., & Sherrell, D. L. (2002). Enticing online consumers: An extended technology acceptance perspective. Information & Management, 39(8), 705-719 https://doi.org/10.1016/S0378-7206(01)00127-6
  8. Cho, H. K., Lee, J. H., Lee, C. K., & Lee, M. H. (2006). An exploratory research for development of design of sensor-based smart clothing: Focused on the healthcare clothing based on bio-monitoring technology. Korean Journal of the Science of Emotion & Sensibility, 9(2), 141-150
  9. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340 https://doi.org/10.2307/249008
  10. Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982-1003 https://doi.org/10.1287/mnsc.35.8.982
  11. Fishbein, M. (1963). An investigation of the relationships between beliefs about an object and the attitude toward that object. Human Relations, 16(3), 233-240 https://doi.org/10.1177/001872676301600302
  12. Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Boston, MA: Addison-Wesley
  13. Goldsmith, R. E., & Hofacker, C. F. (1991). Measuring consumer innovation. Journal of the Academy of Marketing Science, 19(3), 209-221 https://doi.org/10.1177/009207039101900306
  14. Hong, B. S., & Oh, H. J. (2001). Clothing purchasing behavior based on innovation in e-commerce and risk perception. The Chung-Ang Journal of Human Ecology, 14, 233-256
  15. Igbaria, M., Zinatelli, N., Cragg, P., & Cavaye, A. L. M. (1997). Personal computing acceptance factors in small firms: A structural equation model. MIS Quarterly, 21(3), 279-305 https://doi.org/10.2307/249498
  16. Jackson, C. M., Chow, S., & Leitch, R. A. (1997). Toward an understanding of the behavioral intention to use an information system. Decision Sciences, 28(2), 357-389 https://doi.org/10.1111/j.1540-5915.1997.tb01315.x
  17. Kang, K. Y., & Jin, H. J. (2007). A study on consumers' clothing buying intention adopted by the technology acceptance model. Journal of the Society of Clothing and Textile, 31(8), 1211-1221 https://doi.org/10.5850/JKSCT.2007.31.8.1211
  18. Kim, H. N., & Rhee, E. Y. (2001). Consumer segmentation of clothing products by fashion conformity / innovation and their reference groups. Journal of the Korean Society of Clothing and Textiles, 25(7), 1341-1352
  19. Kim, H. R., Hong, S. M., & Lee, M. K. (2005). Consumer evaluations of convergence products. Korean Journal of Marketing, 7(1), 1-20
  20. Kim, S. H. (1999). A study on the structure of clothing consumption value and the relation between clothing consumption value and, clothing involvement and fashion leadership. Unpublished doctoral dissertation, Ewha Woman's University, Seoul, Korea
  21. Koo, D. M. (2003). An investigation on consumer's internet shopping behavior explained by the technology acceptance model. The Journal of MIS Research, 13(1), 141-170
  22. Lee, E. O. (2007). A study on T-Commerce of fashion item: Focused on TAM model. Master's thesis, Sungshin Women's University, c
  23. Lee, H. M. (2008). The Study on the acceptance of wearable computers and consumer segmentation: Based on the Technology Acceptance Model (TAM). Unpublished doctoral dissertation, Ewha Woman's University, Seoul, Korea
  24. Lee, J. H. (2004). Digital clothing for practical life. Fiber Technology and Industry, 8(1), 11-18
  25. Lee, J. S. (2002). The prospect and developed case of smart clothing. Chungnam Journal of Home Economics, 15(1), 64-75
  26. Park, H. J., & Lee, J. H. (2002). An explorative research for possibility of digitalwear based on motiondetective input technology as apparel product and a suggestion of the design prototypes(1). Korean Journal of the Science of Emotion & Sensibility, 5(1), 33-48
  27. Park, J. J. (2004). Factors influencing consumer intention to shop online. The Korean Journal of Advertising, 15(3), 289-315
  28. Park, S. H., and Lee J. H. (2001). An exploratory research for design of digital fashion product based on the concept of 'Wearable Computer'(1). Journal of Fashion Business, 5(3), 111-128
  29. Venkatesh, V. (2000). Determinants of perceived ease of use: Integration control, intrinsic motivation, and emotion into the technology acceptance model. Information Systems Research, 11(4), 342-365 https://doi.org/10.1287/isre.11.4.342.11872
  30. Venkatesh, V., and Morris, M. G. (2000). Why don't men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behaviour. Management Information Systems Quarterly, 24(1), 115-139 https://doi.org/10.2307/3250981
  31. Venture Development Corporation. (2005). Wearable systems: Global market demand analysis, 2nd Edition. Vol III: Infotainment Solutions
  32. Yook, H. M. (2003). Development of usability evaluation criteria for smart jacket design. Master's thesis, Yonsei University, Seoul, Korea
  33. Yun, H. L. (2007). Impact of innovative characteristics and perceived risk of smart clothing on attitude toward products and purchase intention: Fashion lifestyle of Korean and US undergraduate students. Master's thesis, Yonsei University, Seoul, Korea