Switching Intention of Smart Appliance : A Perspective of the Push-Pull-Mooring Framework

스마트 가전의 전환의도에 영향을 미치는 요인에 관한 연구 : Push-Pull-Mooring의 관점

  • Park, HyunSun (BK21+, School of Business Administration, Kyungpook National University) ;
  • Kim, Sanghyun (School of Business Administration, Kyungpook National University)
  • 박현선 (경북대학교 경영학부 BK21플러스) ;
  • 김상현 (경북대학교 경영학부)
  • Received : 2017.12.12
  • Accepted : 2018.02.20
  • Published : 2018.02.28


As the next generation technology, leading 4th industrial revolution has been progressed, the goods and services converged by the technology are being released in a market. The smart appliances among them attracts users' attentions as a key promising industry. Thus, this study investigates the factors that influence switching intention to smart appliances based on Push-Pull-Mooring framework. We collected 217 survey responses and formed structural equation modeling with AMOS 22.0. The results show that functional deprivation, money deprivation, alternative attractiveness had an effect on the switching intention to smart appliances. In addition, low switching cost is related to the relationship between external variables and switching intention. The results expect to provide useful information to the smart appliance-related companies.


  1. K. Wu, J. Vassileva & Y. Zhao. (2017). Understanding Users' Intention to Switch Personal Cloud Storage Services: Evidence from the Chinese Market. Computers in Human Behavior, 68, 300-314. DOI : 10.1016/j.chb.2016.11.039
  2. X. Peng, Y. Zhao, & Q. Zhu. (2016). Investigating User Switching Intention for Mobile Instant Messaging Application: Taking WeChat as an Example. Computers in Human Behavior, 64, 206-216. DOI : 10.1016/j.chb.2016.06.054
  3. H. W. Jang, N. Y, Kwak & C. C. Lee. (2017). Study on Factors Affecting Intention of Switching China's Mobile Telecommunication Service-Focusing on PPM Theory. Journal of Digital Convergence, 15(7), 169-180. DOI : 10.14400/JDC.2017.15.7.169
  4. J. U. Kim & S. T. Park. (2013). An Empirical Study on Factors Influencing a Consumer's Switching Behavioral Intention in the Internet Shopping Mall Environment. Journal of Digital Convergence, 11(1), 199-209.
  5. C. Ye & R. Potter. (2011). The Role of Habit in Post-Adoption Switching of Personal Information Technologies: An Empirical Investigation. Communications of the Association for Information Systems, 28(1), 585-610.
  6. J. C. Nunnally. (1978). Psychometric Theory (2nd), New York: McGraw-Hill.
  7. D. W. Barclay, C. A. Higgins & R. L. Thompson. (1995). The Partial Least Squares(PLS) Approach to Causal Modeling: Personal Computer Adoption and Use as an Illustration. Technology Studies, 2(2), 285-309.
  8. C. Fornell & D. F. Larcker. (1981). Structural Equation Models with Unobservable Variables and Measurement Error: Algebra and Statistics. Journal of Marketing Research, 18(3), 382-388. DOI : 10.2307/3151335
  9. Korea Association of Smart Home. (2011, Spring). Smart era, Smart Information Appliance. Smart Home Focus. 44-51.
  10. D. G. Lee, S. J. Lee & B. J. Choi. (2012). An Empirical Study on Intentions to Use of Smart TV. Journal of Digital Convergence, 10(4), 107-118.
  11. J. H. Park & M. K. Kim. (2016). Factors Influencing the Low Usage of Smart TV Services by the Terminal Buyers in Korea. Telematics and Informatics, 33(4), 1130-1140. DOI : 10.1016/j.tele.2016.01.001
  12. H. S. Bansal, S. F. Taylor & Y. S. James. (2005). Migrating to New Service Providers: Toward a Unifying Framework of Consumers' Switching Behaviors. Journal of the Academy of Marketing Science, 33(1), 96-115. DOI : 10.1177/0092070304267928
  13. B. Moon. (1995). Paradigms in Migration Research: Exploring 'Mooring' as a Schema. Progress in Human Geography, 19(4), 504-524. DOI : 10.1177/030913259501900404
  14. H. T. Yi & M. S. Yeom. (2016). An Investigation into the Determination of Show-Rooming: Focused on Migration Theory. Journal of Korea Service Management Society, 17(4), 65-88. DOI : 10.15706/jksms.2016.17.4.004
  15. E. Ravenstein. (1889). The Laws of Migration: Second Paper. Journal of the Royal Statistical Society, 52(2), 241-305.
  16. J. K. Hsieh, Y. C. Hsieh, H. C. Chiu & Y. C. Feng. (2012). Post-adoption Switching Behavior for Online Service Substitutes: A Perspective of the Push-Pull-Mooring Framework. Computers in Human Behavior, 28(5), 1912-1920. DOI : 10.1016/j.chb.2012.05.010
  17. H. H. Chang, K. H. Wong & S. Y. Li. (2017). Applying Push-Pull-Mooring to Investigate Channel Switching Behaviors: M-Shopping Self-Efficacy and Switching Costs as Moderators. Electronic Commerce Research and Applications, 24, 50-67. DOI : 10.1016/j.elerap.2017.06.002
  18. Y. H. Fang & K. Tang. (2017). Involuntary Migration in Cyberspaces: The Case of MSN Messenger Discontinuation. Telematics and Informatics, 34, 177-193. DOI : 10.1016/j.tele.2016.05.004
  19. Y. Sun, D. Liy, S., Chen, X. Wu & X. L. Shen. (2017). Understanding Users' Switching Behavior of Mobile Instant Messaging Applications: An Empirical Study from the Perspective of Push-Pull-Mooring Framework. Computers in Human Behavior, 75, 727-738. DOI : 10.1016/j.chb.2017.06.014
  20. Y. Xu, Y. Yang, Z. Cheng & J. Lim. (2014). Retaining and Attracting Users in Social Networking Services: An Empirical Investigation of Cyber Migration. Journal of Strategic Information Systems, 23, 239-253. DOI : 10.1016/j.jsis.2014.03.002
  21. I. C. Chang, C. C. Liu & K. Chen. (2014). The Push, Pull and Mooring Effects in Virtual Migration for Social Networking Sites. Information Systems Journal, 24(4), 323-346. DOI : 10.1111/isj.12030
  22. National IT Industry Promotion Agency. (2012). Smart Appliance Strategy of Global Corporation, IT Spot Issue.
  23. Korea Technology and Information Promotion Agency for SMEs. (2017). Technology Roadmap for SME. 2017-2019.
  24. R. M. Baron & D. A. Kenny. (1986). The Moderator-Mediator Variable Distinction in Social Psychological Research: Conceptual, Strategic, and Statistical Considerations. Journal of Personality & Social Psychology, 51(6), 1173-1182. DOI : 10.1037//0022-3514.51.6.1173
  25. G., Premkumar & K. Ramamurthy. (1995). The Role of Interorganizational and Organizational Factors on the Decision Model for Adoption of Interorganizational Systems. Decision Sciences, 26(3), 303-336. DOI : 10.1111/j.1540-5915.1995.tb01431.x