Determinants of Usage Intention of LINE Users in Taiwan


With the huge user base, LINE has become an important medium of mobile communications in the world. This study attempts to explore the factors influencing usage intention for LINE users. Drawing on the theory of planned behavior (TPB), this study adds three antecedents, including perceived enjoyment, perceived critical mass, and self-efficacy into the TPB model, and further examines the moderating effect of frequent users on the causal relationships. A structural equation modeling is used and 458 LINE users in Taiwan are investigated. The results reveal that perceived enjoyment and perceived critical mass are positively associated with behavioral attitude. Also, self-efficacy is positively associated with perceived behavioral control. Moreover, behavioral attitude, subjective norms, and perceived behavioral control are positively associated with usage intention, and the causal relationships are significantly varied between frequent and infrequent users.

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Chen, M. and Yen, Y. (2015) Determinants of Usage Intention of LINE Users in Taiwan. Modern Economy, 6, 1090-1100. doi: 10.4236/me.2015.610105.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] Tsao, W.Y. (2014) Enhancing Competitive Advantages: The Contribution of Mediator and Moderator on Stickiness in the LINE. Journal of Retailing and Consumer Services, 21, 933-941.
[2] Ajzen, I. (1991) The Theory of Planned Behavior. Organizational Behavior and Human Decision Processes, 50, 179-211.
[3] Salancik, G.R. and Pfeffer, J. (1978) Social Information-Processing Approach to Job Attitudes and Task Design. Administrative Science Quarterly, 23, 224-253.
[4] Bandura, A. (1986) Social Foundations of Thought and Action. Prentice-Hall, Englewood Cliffs.
[5] Teo, T. and Lee, C.B. (2010) Explaining the Intention to Use Technology among Student Teachers: An Application of the Theory of Planned. Campus-Wide Information Systems, 27, 60-67.
[6] Ball, P. (2004) Critical Mass: How One Thing Leads to Another. Farrar, Straus and Giroux.
[7] Moon, J.-W. and Kim, Y.-G. (2001) Extending the TAM for a World-Wide-Web Context. Information & Management, 38, 217-230.
[8] Ellison, N., Steinfield, C. and Lampe, C. (2006) Spatially Bounded Online Social Networks and Socialcapital: The Role of Facebook. The Annual Conference of the International Communication Association, 36, 1-37.
[9] George, J.F. (2004) The Theory of Planned Behavior and Internet Purchasing. Internet Research, 14, 198-212.
[10] Taylor, S. and Todd, P.A. (1995) Understanding Information Technology Usage: A Test of Competing Models. Information Systems Research, 6, 144-176.
[11] Millward, S. (2013) Line Reveals latest User Numbers in Japan, Thailand, Chinese Taipei, Indonesia.
[12] Johnson, G.M. (2008) Cognitive Processing Differences between Frequent and Infrequent Internet Users. Computers in Human Behavior, 24, 2094-2106.
[13] Nunnally, J.C. (1978) Psychometric Theory. 2nd Edition, McGraw-Hill, New York.
[14] Robert, M.L. and Wortzel, L.H. (1979) New Life-Style Determinants of Women’s Food Shopping Behavior. Journal of Marketing, 43, 28-39.
[15] Anderson, J. and Gerbing, D.W. (1988) Structural Equation Modeling in Practice: A Review and Recommended Two-Step Approach. Psychological Bulletin, 103, 411-423.
[16] Fornell, C. and Larcker, D.F. (1981) Evaluating Structural Equations with Unobservable Variables and Measurement error. Journal of Marketing Research, 18, 39-50.
[17] Cheung, G.W. and Rensvold, R.B. (2002) Evaluating Goodness-of-Fit Indexes for Testing Measurement Invariance. Structural Equation Modeling: A Multidisciplinary Journal, 9, 233-255.
[18] Byrne, B.M. (2010) Structural Equation Modeling with AMOS. Routledge, New York.
[19] Yang, K. and Lee, H.-J. (2010) Gender Differences in Using Mobile Data Services: Utilitarian and Hedonic Value Approaches. Journal of Research in Interactive Marketing, 4, 142-156.
[20] Maddux, J.E. (1995) Self-Efficacy, Adaptation, and Adjustment: Theory, Research, and Application. Plenum Press, New York.
[21] Fang, Y.-H., Chiu, C.-M. and Wang, E.T.G. (2011) Understanding Customers’ Satisfaction and Repurchase Intentions—An Integration of IS Success Model, Trust, and Justice. Internet Research, 21, 479-503.

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