Journal of Digital Convergence (디지털융복합연구)

The Society of Digital Policy and Management (한국디지털정책학회)
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An Empirical Effect of the Belief Variables on Recommendation Intention for Using Kiosk Service

키오스크 서비스의 추천의도에 영향을 미치는 신념변수에 관한 실증적 분석

  • Lee, Eun Mi (Department of Business Administration and Accounting, Changshin University)
  • 이은미 (창신대학교 경영회계학과)
  • Received : 2019.04.02
  • Accepted : 2019.06.20
  • Published : 2019.06.28
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Abstract

The purpose of this study is to identify belief variables of kiosk that affect satisfaction and recommendation intention by applying vertically extended technology acceptance model (TAM). As results of this study are as follows. Firstly, the perceived usefulness and perceived ease of use have an impact on satisfaction statistically. Second, the perceived usefulness and perceived enjoyment of the kiosk showed a positive(+) influence on the recommendation intention. Third, users who satisfied with kiosk service have strong recommendation intention to their friends, family and colleagues so on. These findings support that the usefulness and usability of the new information technology identified in the existing technology acceptance model is a key variable affecting user reactions (satisfaction and recommendation intention). Additionally, the perceived enjoyment is an important factor as new belief variable for explaining the formation of recommendation intention through satisfaction of kiosk service. The results of this study contribute to verifying the empirical model between the belief variables(perceived usefulness, perceived ease of use, perceived enjoyment) and the recommendation intention.

본 연구는 수직적으로 확장된 기술수용모델(TAM)을 토대로 사용자반응에 영향을 미치는 주요한 신념변수인 지각된 유용성과 지각된 사용용이성에 지각된 유희성을 추가하고, 키오스크 서비스의 만족과 추천의도에 영향을 미치는 신념변수의 영향력을 실증적으로 검증해보고자 하였다. 그 결과, 첫째, 키오스크의 유용성과 사용편리성을 지각하면 만족하는 것으로 나타났다. 둘째, 키오스크의 지각된 유용성과 지각된 유희성은 키오스크 서비스의 추천의도에 유의한 정(+)의 영향을 미치는 것으로 나타났다. 셋째, 키오스크 서비스에 만족한 사용자는 강한 추천의도를 가지는 것으로 나타났다. 이와 같은 연구결과는 기존 기술수용모델에서 규명한 새로운 정보기술의 유용성과 사용편리성이 사용자반응(만족과 추천의도)에 영향을 미치는 주요한 변수임을 재입증 해주고 있으며, 새롭게 추가한 지각된 유희성이 키오스크 서비스의 만족을 매개하지 않고도 추천의도를 활성화시킬 수 있다는 것을 의미한다. 본 연구의 결과는 키오스크 서비스의 지각된 유희성이 추가된 확장된 신념변수와 추천의도 간의 관계를 연구모형에 도입하고 실증적으로 검증했다는 점에서 의의가 있다고 판단된다.

Keywords

Table 1. Variables

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Table 2. Results of the Conceptual Reliability and Intent Validity Test for Independent Variables

DJTJBT_2019_v17n6_113_t0002.png 이미지

Table 3. The result of discriminant Validity

DJTJBT_2019_v17n6_113_t0003.png 이미지

Table 4-1. The result of hypothesis1

DJTJBT_2019_v17n6_113_t0004.png 이미지

Table 4-2. The result of hypothesis2

DJTJBT_2019_v17n6_113_t0005.png 이미지

Table 4-3. The result of hypothesis3

DJTJBT_2019_v17n6_113_t0006.png 이미지

References

  1. P. J. Hu, O. R. Sheng & K. Y. Ram (1999). Examining the technology acceptance model using physician acceptiance of telemedicine technology. Journal of Management Information Systems Research, 16(2), 91-112.
  2. F. D. Davis. (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
  3. V. Venkatesh & 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
  4. V. Venkatesh. (2000). Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information System Research, 11(4), 342-365. https://doi.org/10.1287/isre.11.4.342.11872
  5. J. W. Moon & Y. G. Kim. (2001). Extending the TAM for a World-Wide-Web context. Information & management, 38(4), 217-230. https://doi.org/10.1016/S0378-7206(00)00061-6
  6. H. Sun & P. Zhang. (2006). Causal relationships between perceived enjoyment and perceived ease of use: An alternative approach. Journal of the Association for Information Systems, 7(9), 618-645. https://doi.org/10.17705/1jais.00100
  7. H. Sun & P. Zhang. (2008). An exploration of affect factors and their role in user technology acceptance: Mediation and causality. Journal of the American Society for Information Science and Technology, 59(8), 1252-1263. https://doi.org/10.1002/asi.20819
  8. X. Tong. (2010). A cross-national investigation of an extended technology acceptance model in the online shopping context. International Journal of Retail & Distribution Management, 38(10), 742-759. https://doi.org/10.1108/09590551011076524
  9. E. Park, S. Baek, J. Ohm & H. J. Chang. (2014). Determinants of player acceptance of mobile social network games: An application of extended technology acceptance model. Telematics and Informatics, 31(1), 3-15. https://doi.org/10.1016/j.tele.2013.07.001
  10. F. D. Davis, R. P. Bagozzi & P. R. Warshaw. (1992). Extrinsic and intrinsic motivation to use computers in the workplace. Journal of Applied Social Psychology, 24(14), 11-32.
  11. M. Igbaria, J. Iivari & H. Maragahh. (1995). Why do individuals use computer technology? A Finnish case study. Information & Management, 29(5), 227-238. https://doi.org/10.1016/0378-7206(95)00031-0
  12. S. G Jung & J. H. Yang. (2013). A study on relationship among relational benefits, satisfaction and customer loyalty: focused on the moderating effects of consumer's innovativeness & rationality. Journal of Marketing Management Research, 18(2), 47-72.
  13. J. Kim, N. Christodoulidou & Y. Choo. (2013). Factors influencing customer acceptanceof kiosks at quick service restaurants. Journal of Hospitality and Tourism Technology, 4(1), 40-63. https://doi.org/10.1108/17579881311302347
  14. S. H. Lee & D. W. Lee. (2018). A study on ICT technology leading change of unmanned store. Journal of the Korea Convergence Society, 8(4), 109-114.
  15. M. L. Meuter, A. L. Ostrom, R. I. Roundtree & M. J. Bitner. (2000). Self-service technologies: understanding customer satisfaction with technology-based service encounters. Journal of marketing, 64(3), 50-64. https://doi.org/10.1509/jmkg.64.3.50.18024
  16. R. P. Bagozzi. (2007). The legacy of the technology acceptance model and aproposal for a paradigm shift. Journal of the Association for Information Systems, 8(4), 244-254. https://doi.org/10.17705/1jais.00122
  17. B. O. Jeong. (2016). Effects of perceived usefulness, perceived ease of use and perceived enjoyment on intention to use tourism application: moderating effects of demographic characteristics. International Journal of Tourism and Hospitality Research, 30(1), 101-121. https://doi.org/10.21298/IJTHR.2016.01.30.1.101
  18. C. W. Yoo, Y. J. Kim, J. H. Moon & Y. C. Choe. (2008). The effect of Herding behavior and perceived usefulness on intention to purchase e-learning content: comparison analysis by purchase experience. Journal of MIS Research, 18(4), 105-130.
  19. C. S. Ong & J. Y. Lai. (2006). Gender differences in perceptions and relationships among dominants of e-learning acceptance. Computers in Human Behavior, 22(5), 816-829. https://doi.org/10.1016/j.chb.2004.03.006
  20. H. C. Yang & I. K. Jeong. (2011). A study of the characteristics of different smart-phone user types: between users and non-users of applications. Journal of Cyber Society & Culture, 2(1), 17-49.
  21. T. S. H. Teo, V. K. G. Lim & R. Y. C. Lai. (1999). Intrinsic and extrinsic motivation in internet usage. The International Journal of Management Science, 27, 25-37.
  22. R. Oliver. (1980). Measurement and evaluation of satisfaction process in retail setting. Journal of Retailing, 57(Fall), 25-48.
  23. J. D. Barsky & R. Labagh. (1992). A strategy for customer satisfaction. Cornell Hotel and Restaurant Administration Quality, 33(5), 32-40. https://doi.org/10.1177/001088049203300524
  24. S. D. Kim & Y. K. Ha. (2016). The mediating effects of customer-company identification on the relationship between service quality and referral intention: focused on the hotel restaurants. Tourism Research, 41(2), 1-19.
  25. R. Oliver. (1997). Satisfaction: A behavioral perspective on the consumer. New York: The McGraw-Hill Companies, Inc. International Eddition.
  26. R. Oliver & J. Swan. (1989). Consumer perceptions of interpersonal equity and satisfaction in transactions : A field survey approach. Journal of Marketing, 53(April), 21-35. https://doi.org/10.1177/002224298905300305
  27. Jone D. Holmes & J. D. Lett, Jr. (1977). Product sampling and world-of-mouth. Journal of Advertising Research, 17(October), 35-40.
  28. S. H. Ju, M. Y. Song & B. K. Kim. (2018). The effect of personal trait on perceived value and recommendation intention: focus on one-person media contents. Journal of the Korea Convergence Society, 9(12), 159-167. https://doi.org/10.15207/JKCS.2018.9.12.159
  29. V. Venkatesh & M. G. Morris. (2000). Why don't men ever stop to ask for directions? Genders, scial influence, and their role in thechnology acceptance and usage behavior. MIS Quarterly, 24(1), 115-139. https://doi.org/10.2307/3250981
  30. J. J. Cronin & S. A. Taylor. (1992). A loguitudinal analysis of the impact of service changes on customer attitudes. Journal of Marketing, 55, 1-9.
  31. L. Harris & M. Goode. (2004). The four levels of Loyalty and the pivotal role of trust: A sudy of online service dynamics. Journal of Retailing, 80(2), 139-158. https://doi.org/10.1016/j.jretai.2004.04.002
  32. Jum C. Nunnally. (1967). Psychimetric Theory. 1st ed., New York: McGraw-Hill.