Your browser does not support the PubReader view.
Go to this page to see a list of supporting browsers.
Korean Academic Society of Business Administration
[ Article ]
korean management review - Vol. 45, No. 5, pp.1645-1669
ISSN: 1226-1874 (Print)
Print publication date 31 Oct 2016
Received 19 Jul 2015 Revised 03 Apr 2016 Accepted 08 Jun 2016
DOI: https://doi.org/10.17287/kmr.2016.45.5.1645

기술수용모델에서 타인의 수용정도가 지각된 위험에 미치는 영향: 웨어러블 기기를 중심으로

박상준* ; 손삽**
*(주저자, 교신저자) 전북대학교 경영학부, 빅데이터비스니스연구소 psj@jbnu.ac.kr
**(공저자) 중국 산동사범대학교 관리과학과 공학부 sunsa87n@naver.com
The Effect of Other’s Adoptions on Perceived Risk in Technology Acceptance Model: Focused on Wearable Device
Sang-June Park* ; Sa Sun**
*Department of Business Administration (Research Institute of Big Data Business), Chonbuk National University, First Author and Corresponding Author
**School of Management Science and Engineering, Shandong Normal University, Co-Author

초록

기술수용모델은 잠재적 혁신수용자가 혁신(신기술 또는 신제품)을 어떤 과정을 통해 수용하게 되는지에 관한 프레임웍을 제공하고 있고, Bass 확산모델은 사회 시스템 안에서 타인과의 상호작용을 통해 혁신이 확산되는 과정에 관한 프레임웍을 제공하고 있다. 즉, 기술수용모델은 혁신에 대한 개인수준의 혁신 채택과정을 설명하고 있으며, Bass 확산모형은 혁신의 채택자와 잠재적 채택자간의 상호작용에 기반하여 집단수준의 혁신 채택과정을 설명하고 있다는 측면에서 두 모델은 깊은 연관성이 있다. 본 연구는 지각된 위험을 통해 두 모델이 연결될 수 있음에 주목하고, 혁신에 대한 지각된 위험을 통해 기술수용모델과 확산모델에 어떻게 통합될 수 있는 살펴보고 있다. 이를 위해, 지각된 위험의 역할에 관한 기술수용모델의 선행연구의 다양한 견해를 정리하고, 타인의 혁신수용 수준의 증가는 잠재적인 혁신수용자의 지각된 위험을 줄이고 최종적으로는 혁신에 대한 수용의도를 높여 준다는 실증분석 결과를 도출하고, 이를 바탕으로 기술수용모델과 확산모델의 통합을 시도하였다. 본 연구의 결과는 기술수용모델과 혁산모델의 통합모델 개발의 단서를 제공하고 있다는 측면에서 그 의의가 있다고 할 수 있다.

Abstract

The Technology Acceptance Model (TAM) explains an individual’s cognitive acceptance process of an innovation (i.e., a new product or service). It specifies the causal linkages between two key beliefs (i.e., perceived usefulness and perceived easy of use) and an individual’s attitude and intention to adopt an innovation. In contrast, the Bass Model (BM) explains the acceptance process of an innovation which is defined by two forces in a social system: One is the effect of imitators and the other is the effect of imitators. The former is referred to as the external effect which is independent from others in a diffusion system and the latter is referred to as the internal effect which is dependent on others in the system. The TAM may be linked with the BM because the both models explain the adoption process of an innovation even though their frameworks are different. The integration of the two models may allow researchers to systematically understand the adoption process of an innovation. Thus, we tried to link the two models based on the role of perceived risk in the adoption process. The previous studies have presented different roles of perceived risk in the adoption process of an innovation. Some researchers treat the perceived risk as an influential variable on consumers’ adoption intentions whereas others do it as a mediating variable in the adoption process. Thus, we conducted an experiment study to identify the true role of perceived risk in the adoption process. Subjects for the experiment study were 160 university students in Korea. They were randomly assigned to one of three conditions which represent different levels of others’ adoptions of a new product: Other’s choice probabilities of a new product were 0, 0.2, and 0.5 in the three conditions.

According to the empirical study, the perceived risk has a main effect on individuals’ adoption intentions. Thus, based on the empirical finding, we proposed an integration model of the two models (i.e., TAM and BM) in which the external effect of the BM is represented as a function of the perceived usefulness and easy of use whereas the internal effect of the BM is done as a function of the perceived risk. We believe that the proposed model may give researchers some valuable insights on consumers’ adoption behaviors of an innovation.

Keywords:

Technology Acceptance Model, Bass Model, Perceived Risk, Perceived Usefulness, Perceived Easiness

키워드:

기술수용모델, 지각된 유용성, 지각된 용이성, 지각된 위험, 확산모델

References

  • 강경영·진현정(2007), “혁신기술수용모델(TAM)을 적용한 스마트 의류구매의도 연구,” 한국의류학회지, 31(8), 1222-1221.
  • 강수련·김이경(2011), “웨어러블 컴퓨터에서 피트의문제: 의복구성학을 적용한 디자인 프로세스의 도입,” 한국패션디자인학회지, 11(4), 9-134.
  • 고민현·권순동(2008), “인터넷 커뮤니티에서 수용자 참여가 밀착도와 지속적 이용의도에 미치는 영향,” 경영정보학연구, 18(2), 41-72.
  • 구동모(2003), “혁신기술수용모델을 응용한 인터넷 쇼핑행동 고찰,” 경영정보학연구, 13(1), 141-170.
  • 김광재(2010), “혁신의 확산 연구에 대한 메타분석,” 한국언론학보, 54(2), 31-56.
  • 김문구·박종현(2006), “와이브로 서비스 이용의도에 미치는 영향 요인에 관한 연구: 확장된 TAM 모형을 중심으로,” 한국경영정보학회 춘계학술대회, 790-800.
  • 김보연·강민철·이상근(2006), “인지적 몰입이 개인의 기술 수용에 미치는 영향: MP3 플레이어에 대한 실증 연구,” 경영정보학연구, 16(1), 45-69.
  • 나윤규·홍병숙·강성민(2008), “인터넷 쇼핑에서의 지각된 가치와 위험이 패션상품 구매의도에 미치는 영향에 관한 연구,” 한국의류학회지, 32(8), 1213-1225.
  • 노경섭(2014), 제대로 알고 쓰는 논문 통계분석: SPSS & AMOS 21, 한빛아카데미.
  • 노미진·이경탁(2012), “소셜커머스 수용에 있어서 지각된 위험의 영향력: 집단주의 조절효과 분석,” 경영학연구, 41(1), 57-87.
  • 박상준·김현철(2003), “고객만족모형의 기대 딜레마: 확산과 기대불일치의 통합모형,” 한국경영과학회지, 28(2), 61-74.
  • 박재진(2004), “소비자의 인터넷쇼핑 행동에 영향을 미치는 요인에 관한 연구,” 광고학연구, 15(3), 289-315.
  • 배두환(2013), “스마트폰 사용의도에 관한 연구: 신뢰, 자기효능감, 플로우와 기술수용모델을 중심으로,” e-비즈니스연구, 14(2), 47-68.
  • 백상용(2000), “PC 이용과 놀이성의 관례에 대한 연구,” 경영정보학연구, 10(4), 101-113.
  • 백상용(2009), “조절변수 탐색을 위한 기술수용모형 메타분석,” 경영학연구, 38(5), 1353-1380.
  • 손경희·이현규(2003), “매체, 소비자, 제품 특성이 지각위험과 구매의도에 미치는 영햐,” 정보시스템연구, 12(1), 117-144.
  • 손승혜·최윤정·황하성(2011), “기술수용모델을 이용한 초기 이용자들의 스마트폰 채택 행동 연구,” 한국언론학보, 55(2), 227-251.
  • 심진보(2010), “컨버전스 환경 하에서 통신, 방송 결합상품 수용의도에 영향을 미치는 서비스 특성 연구,” 기술혁신연구, 18(2), 59-89.
  • 오상현·김상현(2006), “기술수용모델의 확장과 인터넷 뱅킹 이용행동에 관한 연구: 신뢰와 적합성의 역할을 중심으로,” 경제연구, 24(1), 175-205.
  • 유복희·채명수(2015), “해외직접구매 수용에 영향을 미치는 요인에 관한 탐색적 연구: 기술수용모델과 온라인쇼핑 수용모델 요인들을 중심으로,” 유통연구, 20(2), 247-265.
  • 유연재·김정식(2012), “전자제품에서 기술수용모형의 확장: 지각된 제품혁신성과 지각된 위험을 중심으로,” 한국심리학회지: 소비자·광고, 13(3), 365-402.
  • 유필화·이승희(1994), “신제품 수용시 소비자의 혁신저항에 관한 연구,” 경영학연구, 23(3), 217-250.
  • 유재현·박철(2010), “기술수용모델 연구에 대한 종합적 고찰,” Enture Journal of Information Technology, 9(2), 31-50.
  • 유재현·박철(2012), “소비자의 하이테크 제품 수용 및 수용 후 행동에 관한 연구: 스마트 폰을 중심으로,” 경영학연구, 41(3), 423-456.
  • 이국용·선종학·강성수(2005), “온라인 전자뱅킹 서비스 이용에 있어서 지각위험과 태도의 매개적 역할에 관한 연구,” 산업경제연구, 18(2), 825-852.
  • 이원빈(2008), “모바일 커머스의 이용의도에 영향을 미치는 요인,” 경북대학교 대학원 석사학위논문.
  • 이학식·안광호·하영원(2005), 소비자행동: 마케팅전략적 접근, 제3판, 법문사.
  • 이현미(2009), “확장된 혁신기술수용모델을 이용한 웨어러블 컴퓨터의 수용에 관한 연구,” 복식문화연구, 17(6), 1155-1172.
  • 장정무·김종욱·김태웅(2004), “무선인터넷서비스 수용의 영향요인 분석: 플로우이론을 가미한 기술수용모델의 확장,” 경영정보학연구, 14(3), 93-120.
  • 주지혁(2013), “아이폰 이용자를 통해 본 스마트폰의 이용의도 예측모형 비교: 기술수용모형, 계획된 행동이론 및 통합모형을 중심으로,” 디지털정책연구, 11 (1), 89-97.
  • 정성률·허종호·강석준(2003), “인터넷 쇼핑몰 이용에 따른 소비자의 위험지각과 브랜드와 가격의 상태적 중요성,” 소비자학연구, 14(2), 19-43.
  • 전현모(2013), “외식소비자의 지각된 위험과 가치가 소셜커머스 이용의도에 미치는 영향: 기술수용모형을 중심으로,” 외식경영연구, 16(6), 199-222.
  • Admit, J.(1967), “Role of Product-related Conversation in the Diffusion of a Nwe Product,” Journal of Marketing Research, 4(3), 291-295. [https://doi.org/10.1177/002224376700400308]
  • Ajzen, I.(1985), From Intentions to Actions: A Theory of Planned Behavior, Action-Control: From Cognition to Behavior, Heidelberg: Springer. [https://doi.org/10.1007/978-3-642-69746-3_2]
  • Ajzen, I., and M. Fishbein(1980), Understanding Attitudes and Predicting Social Behavior, Englewood Cliffs, NJ: Prentice Hall.
  • Arndt, J.(1967), “Role of Product-Related Convertsations in the Diffusion of a New Product,” Journal of Marketing Research, 4(3), 291-295. [https://doi.org/10.1177/002224376700400308]
  • Arrow, K.(1965), Aspects of the Theory of Risk Bearing, Helsinki: Yrjӧ Hahnsson Foundation.
  • Arts, J. W. C., R. T. Frambach, and T. H. A. Bijmolt (2011), “Generalizations on Consumer Innovation Adoption: A Meta-Analysis on Drivers of Intention and Behavior,” International Journal of Research in Marketing, 28 (2), 134-144. [https://doi.org/10.1016/j.ijresmar.2010.11.002]
  • Ashraf, A. R., T. Narongsak, and A. Seigyoung (2014), “The Application of the Technology Acceptance Model Under Different Cultural Contexts: The Case of Online Shopping Adoption,” Journal of International Marketing, 22(3), 68-93. [https://doi.org/10.1509/jim.14.0065]
  • Bass, F. M.(1969), “A New Product Growth Model for Consumer Durables,” Management Science, 15(2), 215-227. [https://doi.org/10.1287/mnsc.15.5.215]
  • Baumgartner, H., and J. B. Steenkamp(1996), “Exploratory Consumer Buying Behavior: Conceptualization and Measurement,” International Journal of Research in Marketing, 13, 121-137. [https://doi.org/10.1016/0167-8116(95)00037-2]
  • Benbasat, I., D. Gefen, and P. A. Pavlou(2008), “Special Issue on Novel Perspectives of Trust in Information Systems,” MIS Quarterly, 32(2), 465-466.
  • Bettman, J. R., and C. W. Park(1980), “Effects of Prior Knowledge and Experience and Phase of the Choice Process on Consumer Decision Process: A Product Analysis,” Journal of Consumer Research, 7, 243-248. [https://doi.org/10.1086/208812]
  • Crespo, Ά. H., I. R. Del Bosque, and M. M. G. S. Sánchez(2009), “The Influence of Perceived Risk on Internet Shopping Behavior: A Multidimensional Perspective,” Journal of Risk Research, 12(2), 259-277. [https://doi.org/10.1080/13669870802497744]
  • Davis, F. D.(1989), “Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology,” MIS Quarterly, 13(3), 319-339. [https://doi.org/10.2307/249008]
  • Davis, F. D., R. P. Bagozzi, and R. R. Warshaw (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]
  • Featherman, M., and M. Fuller(2003), “Applying TAM to E-Services Adoption: The Moderating Role of Perceived Risk,” Proceedings of the 36th Hawaii International Conference on System Sciences. [https://doi.org/10.1109/HICSS.2003.1174433]
  • Featherman, M. S., and P. A. Pavlou(2003), “Predicting E-Services Adoption: A Perceived Risk Facets Perspective,” International Journal of Human-Computer Studies, 59(4), 451-474. [https://doi.org/10.1016/S1071-5819(03)00111-3]
  • Featherman, M. S., and J. D. Wells(2004), “The Intangibility of E-Services: Effects on Artificiality, Perceived Risk, and Adoption,” In Proceedings of the 37th Hawaii International Conference on System Sciences, 177-187.
  • Fourt, L. A., and J. W. Woodlock(1960). “Early Prediction of Market Success for New Grocery Products,” Journal of Marketing, 25(2), 31-38. [https://doi.org/10.1177/002224296002500206]
  • Ha, S., and L. Stoel(2009), “Consumer E-Shopping Acceptance: Antecedents in a Technology Acceptance Model,” Journal of Business Research, 62, 565-571.
  • Hirschman, E. C.(1980), “Innovativeness, Nevelty Seeking and Consumer Creativity,” Journal of Consumer Research, 7, 283-295.
  • Ho, T.-H., S. Li, S.-E. Park, and Z.-J. Shen(2012), “Customer Influence Value and Purchase Acceleration in New Product Diffusion,” Marketing Science, 31(2), 236-256. [https://doi.org/10.1287/mksc.1110.0701]
  • Hong, S. J., J. Y. L. Thong, J. Y. Moon, and K. Y. Tam(2008), “Understanding the Behavior of Mobile Data Services Consumers,” Information Systems Frontiers, 10, 431-445. [https://doi.org/10.1007/s10796-008-9096-1]
  • Im, I., Y. Kim, and H. Han(2008),“The Effects of Perceived Risk and Technology Type on Users’ Acceptance of Technologies,” Information and Management, 45, 1-9. [https://doi.org/10.1016/j.im.2007.03.005]
  • Jarvenpaa, S. L., N. Tractinsky, and M. Vitale (2000), “Consumer Trust in an Internet Store,” Information Technology and Management, 1(1), 45-71. [https://doi.org/10.1023/A:1019104520776]
  • Kahneman, D., and A. Tversky(1979), “Prospect Theory: An Analysis of Decision under Risk,” Econometrica, 47(2), 263-292. [https://doi.org/10.2307/1914185]
  • Khalifa, M., and N. K. Shen(2008), “Explaining the Adoption of Transactional B2C Mobile Commerce,” Journal of Enterprise Information Management, 21(2), 110-124. [https://doi.org/10.1108/17410390810851372]
  • Kim, S.(2008), “Moderating Effects of Job Relevance and Experience on Mobile Wireless Technology Acceptance: Adoption of a Smartphone by Individuals,” Information and Management, 45, 387-393. [https://doi.org/10.1016/j.im.2008.05.002]
  • Kotler, P., and G. Armstrong(1994), Principles of Marketing(6 Edition), New Jersey: Prentice-Hall.
  • Lambert, Z. V.(1972), “Perceptual Patterns, Information Hanling and Innovativeness,” Journal of Marketing Research, 9, 427-431. [https://doi.org/10.1177/002224377200900412]
  • Lee, M. C.(2009), “Factors Influencing the Adoption of Internet Banking: An Integration of TAM and TPB with Perceived Risk and Perceived Benefit,” Electronic Commerce Research and Applications, 8, 130-141. [https://doi.org/10.1016/j.elerap.2008.11.006]
  • Lekvall, P., and C. Wahlbin(1973), “A Study of Some Assumptions Underlying Innovation Diffusion Functions,” Swedish Journal of Economics, 75(4), 362-377. [https://doi.org/10.2307/3439146]
  • Li, Y. H., and J. W. Huang(2009), “Applying Theory of Perceived Risk and Technology Acceptance Model in the Online Shopping Channel, WOrld Academy of Science,” Engineering and Technology, 53, 919-925.
  • Liu, X., and K. K. Wei(2003), “An Empirical Study of Product Differences in Consumers’ E-Commerce Adoption Behavior,” Electronic Commerce Research and Applications, 2(3), 229-239.
  • Luo, X., H. Li,, J. Zhang, and J. P. Shim(2010), “Examining Multi-dimensional Trust and Multi-faceted Risk in Initial Acceptance of Emerging Technologies: An Empirical Study of Mobile Banking Services,” Decision Support Systems, 49, 222-234. [https://doi.org/10.1016/j.dss.2010.02.008]
  • Mahajan, V., E. Muller, and F.M. Bass(1990), “New-product Diffusion Models: A Review and Directions for Research,” Journal of Marketing, 54(1), 1-26.
  • Mansfield, E.(1961), “Technical Change and the Rate of Imitation,” Econometrica, 29(4), 741-766. [https://doi.org/10.2307/1911817]
  • Meade, N., and T. Islam(2006), “Modelling and Forecasting the Diffusion of Innovation: A 25-year Review,” International Journal of Forecasting, 22(3), 519-549.
  • Midgley, D. F., and G. R. Dowling(1978), “Innovativeness: The Concept and Its Measurement,” Journal of Consumer Research, 4, 229-242.
  • Moore, G. E.(1965), “Cramming More Components onto Integrated Circuits,” Electronics Magazine, April, 114-117.
  • Park, Y., and J. V. Chen(2007), “Acceptance and Adoption of the Innovative use of Smartphone,” Industrial Management and Data Systems, 107(9), 1349-1365.
  • Pavlou, P. A.(2003), “Consumer Acceptance of Electronic Commerce: integrating Trust and Risk with the Technology Acceptance Model,” International Journal of Electronic Commerce, 7(3), 101-134. [https://doi.org/10.1080/10864415.2003.11044275]
  • Peter, J. P., and M. J. Ryan(1976), “An Investigation of Perceived Risk at the Brand Level,” Journal of Marketing Research, 13(2), 184-188. [https://doi.org/10.1177/002224377601300210]
  • Pratt, J. W.(1964), “Risk Aversion in the Small an in the Large,” Econometrica, 32(1/2), 122-136. [https://doi.org/10.2307/1913738]
  • Ram, S.(1987), “A Model of Innovation Resistance,” Advances in Consumer Research, 14(1), 208-212.
  • Rammile, N., and J. Nel(2012), “Understanding Resistance to Cell Phone Banking Adoption Through the Application of the Technology Acceptance Model(TAM),” African Journal of Business Management, 6(1), 86-97. [https://doi.org/10.5897/AJBM11.635]
  • Rogers, E. M.(2003), Diffusion of Innovations(5th Edition), New York: Free Press.
  • Rust, R. T., J. J. Inman, J. Jia, and A. Zahorik (1999), “What You Don’t Know about Customer Perceived Quality: The Role of Customer Expectation Distribution,” Marketing Science, 18(1), 77-92.
  • Singer, T., R. Snozzi, G. Bird, P. Petrovic, G. Silani, M. Heinrichs, and R. J. Dolan (2008), “Effects of Oxytocin and Prosocial Behavior on Brain Responses to Direct and Vicariously Experienced Pain,” Emotion, 8, 781-791. [https://doi.org/10.1037/a0014195]
  • Steve, M.(1998), Definition of “Wearable Computer,” ICWC-98, Fairfax VA.
  • Stone, R. N., and F. W. Winter(1985), “Risk in Buyer Behavior Contexts: A Clarification,” Working Paper 1216 EWP 860505. Champaign, IL: College of Commerce and Business Administration, University of Illinois.
  • Talor, S., and P. A. Todd(1995), “Understanding Information Technology Usage: A Test of Competing Models,” Information Systems Research, 6(2), 144-176. [https://doi.org/10.1287/isre.6.2.144]
  • Venkatesh, V., and F. D. Davis(2000), “A theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies,” Management Science, 46(2), 186-204. [https://doi.org/10.1287/mnsc.46.2.186.11926]
  • Veryzer, J. R. W.(1998), “Key factors Affecting Customer Evaluation of Discontinuous New Products,” Journal of Product Innovation Management, 15(2), 136-150. [https://doi.org/10.1111/1540-5885.1520136]
  • Wu, J. H., and S. C. Wang(2005), “What Drives Mobile Commerce? An Empirical Evaluation of the Revised Technology Acceptance Model,” Information and Management, 42, 719-729. [https://doi.org/10.1016/j.im.2004.07.001]
  • Zikmund, W. G., and J. E. Scott(1973), “A Multivariate Analysis of Perceived Risk, Self-Confidence and information Sources,” Advances in Consumer Research, 1(4), 406-416.

• 저자 박상준은 현재 전북대학교 경영학부 마케팅 전공 교수로 재직 중이다. 고려대학교 심리학과를 졸업하였으며, KAIST에서 계량마케팅으로 석사 및 박사를 취득하였다. 박사 학위 취득 이후에는 대우경제연구소에서 연구위원으로 일하였으며, 미국 Rice대학에서 방문연구를 수행하였다. 주요연구분야는 고객만족경영, 소비자선택모형, 확산모형, 경쟁분석, 빅데이터 분석 등이다.

• 저자 손삽은 현재 중국 산동사범대학교 관리과학과 공학부 강사로 재직 중이다. 우석대학교 유통통상학부를 졸업하였으며, 전북대학교에서 경영학부 마케팅으로 석사를 취득하였다. 주요연구분야는 혁신제품의 소비자 수용, 소비자 만족 등의 하이테크마케팅이다.