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The Extended Technology Acceptance Model According to Smart Clothing Types

스마트 의류제품 유형에 따른 확장된 혁신기술수용모델

  • Chae, Jin-Mie (Dept. of Apparel Fashion & Business, Hansung University)
  • Received : 2009.09.07
  • Accepted : 2010.03.10
  • Published : 2010.04.30

Abstract

The Technology Acceptance Model (TAM) presented by Davis (1989) has been regarded as highly explanatory as well as the clearest model in explaining consumers' adoption of innovative technology or products. Existing studies have expanded the model by adding related external variables to improve the explanation depending on the type of innovative technology. This study expanded TAM by adding two more variables, namely consumers' technology innovation and clothing involvement considering the feature of smart clothing. The objectives of this study are as follows: 1. to suggest the extended TAM in explaining the adoption process of smart clothing, 2. to verify the differences in the path hypotheses according to the type of smart clothing. A total of 815 effective samples were collected from adults over 20 years old, and AMOS 5.0 package was employed for data analysis. As a result, it was proved that the extended TAM was appropriate for explaining the process of adopting smart clothing according to the path hypotheses of smart clothing types. Technology innovation and clothing involvement were confirmed as antecedent variables in affecting TAM. The perceived usefulness appeared to be a more crucial variable than the perceived ease of use and attitude was found to be an important parameter in adopting smart clothing. Considering the path hypotheses of MP3 playing clothes, perceived usefulness had a direct influence on acceptance intention unlike other types of smart clothing. As for photonic clothes, the influence of perceived ease of use on attitude was supported while it was rejected in the case of MP3 playing clothes and sensing sportswear.

Keywords

References

  1. 강경영, 진현정. (2007). 혁신기술수용모델(TAM)을 적용한 스마트 의류 구매의도 연구. 한국의류학회지, 31(8), 1211-1221.
  2. 구동모. (2003). 혁신기술수용모델 (TAM) 을 응용한 인터넷 쇼핑행동 고찰. 경영정보학연구, 13(1), 141-170.
  3. 김계수. (2004). AMOS 구조방정식 모형 분석. SPSS 아카데미.
  4. 김준우, 문형도. (2007). e-biz 기술: 정보기술수용이론(TAM)의 대안적 모델의 개발에 관한 연구. e-비즈니스연구, 8(2), 423-450.
  5. 김혜원. (1996). 소비자의 의복관여도와 의복만족도에 관한 연구: 서울과 대구의 남녀대학생을 중심으로. 이화여자대학교 석사학위논문.
  6. 노형진. (2003). SPSS/AMOS에 의한 사회조사분석-범주형 데이터분석 및 공분산 구조분석-. 형설출판사.
  7. 류은정. (1991). 의복관여도에 따른 의복구매행동에 관한 연구: 서울시내 여대생을 중심으로. 이화여자대학교 석사학위논문.
  8. 박선형, 이주현. (2001). 웨어러블 컴퓨터(Wearable Computer)개념을 기반으로 한 디지털 패션상품의 디자인 가능성 탐색 I. 패션비즈니스, 5(3), 111-128.
  9. 이은옥. (2007). 패션제품의 T-Commerce에 관한 연구: TAM 모형을 중심으로. 성신여자대학교 석사학위논문.
  10. 이정섭, 장시영. (2003). 기술수용모델의 확장과 사용자의 정보시스템 수용. 경영학연구, 32(5), 1415-1451.
  11. 이정순. (2002). 스마트 의복의 전망 및 개발사례 연구. 충남생활과학연구지, 15(1), 64-75.
  12. 이현미. (2008). 웨어러블 컴퓨터의 수용과 소비자 세분화에 관한 연구: 혁신기술 수용모델(TAM)을 중심으로. 이화여자대학교 박사학위논문.
  13. 이희경, 이영진, 이주현. (2006). 디지털 컬러 제3보. 한국색채디자인학회추계학술지, 2006(1), 55-58.
  14. 장정무, 김종욱, 김태웅. (2004). 무선인터넷서비스 수용의 영향요인 분석: 플로우이론을 가미한 기술수용모델의 확장. 경영정보학연구, 14(3), 93-120.
  15. 조현승, 김진형, 박선민, 유재훈, 이주현. (2006). MP3 기능 스마트 재킷의 상용화 모형 개발. 감성과학, 9(4), 377-383.
  16. 한국산업기술평가원. (2003). 산업기술혁신 5개년 계획 산업별보고서.
  17. 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
  18. Agarwal, R., & Karahanna, E. (2000). Time flies when you're having fun: cognitive absorption and beliefs about information technology usage. MIS Quartly, 24(4), 665-694. https://doi.org/10.2307/3250951
  19. 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
  20. Bernoff, J., Morrissette, S., & Clemmer, K. (1998). Technographics service explained. Forrester Report 1, Issue 0.
  21. Byrne, B. M. (2001). Structural Equation Modeling with AMOS: Basic Concepts, Applications, and Programming. Mahwah, New Jersey: Lawrence Erlbaum Associates Publishers.
  22. Chattopadhyay, A., & Basu, K. (1990). Humor in advertising: the moderating role of prior brand evaluation. Journal of Marketing Research, 27(4), 466-476.
  23. Chen, L. D. (2000). Consumer Acceptance of Virtual Stores: a Theoretical Model and Critical Success Factors for Virtual Stores. Unpublished doctoral dissertation, University of Memphis.
  24. 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
  25. 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
  26. Engel, J. F., Blackwell, R. D., & Miniard, P. W. (1995). Consumer Behaviour (8th ed.). Forth Worth, Texas: The Dryden Press.
  27. 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
  28. Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research. Boston, Massachusetts: Addison-Wesley.
  29. Gatignon, H., & Robertson, T. S. (1985). A propositional inventory for new diffusion research. Journal of Consumer Research, 11(4), 849-867. https://doi.org/10.1086/209021
  30. Goldsmith, R. E., & Hofacker, C. F. (1991). Measuring consumer innovativeness. Journal of the Academy of Marketing Science, 19(3), 209-221. https://doi.org/10.1007/BF02726497
  31. 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
  32. 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
  33. Mathieson, K. (1991). Predicting user intentions: Comparing the technology acceptance model with theory of planned behavior. Information Systems Research, 2(3), 173-191. https://doi.org/10.1287/isre.2.3.173
  34. Mann, S. (1997). Smart clothing: The wearable computer and wearcam. Personal Technologies, 1(1), 21-27. https://doi.org/10.1007/BF01317885
  35. Midgley, D. F., & Dowling, G. R. (1978). Innovativeness: The concept and its measurement. Journal of Consumer Research, 4(4), 229-242. https://doi.org/10.1086/208701
  36. Ruth, C. J. (2000). Applying a Modified Technology Acceptance Model to Determine Factors Affecting Behavioral Intentions to Adopt Electronic Shopping on the World Wide Web: A structural equation modeling approach. Unpublished doctoral dissertation, Drexel University.
  37. Szanja, B. (1994). Software evaluation and choice: Predictive validation of the technology acceptance instrument. MIS Quarterly, 18(3), 319-324. https://doi.org/10.2307/249621
  38. 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
  39. 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. https://doi.org/10.1111/j.1540-5915.1996.tb01822.x
  40. Venture Development Corporation. (2005). Wearable Systems: Global Market Demand Analysis, 2nd Edition. Vol III: Infotainment Solutions.

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