Determinants of Undergraduates’ Continuance Intention and Actual Behavior to Play Mobile Games In Chongqing, China

Main Article Content

Yingjie Li
Siriwan Kitcharoen


Purpose: The widespread use of the Internet and the increasing of sophisticated production of online games have brought great changes to the life of college students. Consequently, this paper examines the determinants of undergraduate student’s continuance intention and actual behavior to play online mobile games in Chongqing, China. The conceptual framework proposes causal relationships between attitudes, utilitarian outcome expectations, hedonic outcome expectations, subjective norms, time constraint, continuance intentions and actual behavior. Research design, data and methods: Data were collected from 500 undergraduate students in Chongqing. Nonprobability sampling were employed, including judgmental sampling, quota sampling and convenience sampling. Before the data collection, the index of item-objective congruence (IOC) and Cronbach's Alpha were applied to approve validity and reliability. Structural equation model (SEM) and confirmatory factor analysis (CFA) were used for data analysis, including model fit, reliability and validity. Results: Attitude, utilitarian outcome expectation, hedonic outcome expectation, subjective norms, time constraints significantly influence continuance intention. Furthermore, the continuance intention has the strongest influence on the actual behavior of mobile games among students. Conclusions: All hypotheses were proved to be consistent with the research objectives. The results from this study will be useful for mobile game developers and marketers in formulating appropriate applications that will attract more consumers.


Download data is not yet available.

Article Details

How to Cite
Li, Y., & Kitcharoen, S. (2022). Determinants of Undergraduates’ Continuance Intention and Actual Behavior to Play Mobile Games In Chongqing, China. AU-GSB E-JOURNAL, 15(2), 206-214.
Author Biographies

Yingjie Li

School of Journalism and Media, Southwest University, China.

Siriwan Kitcharoen

Full-time Lecturer, Graduate School of Business and Advanced Technology Management, Assumption University.


Ajzen, I. (1985). From Intentions to Actions: A Theory of Planned Behavior. In J. Kuhl & J. Beckmann (Eds.), Action Control: From Cognition to Behavior (pp. 11-39). Springer Berlin Heidelberg.

Ajzen, I. (1991). Theory of planned behavior. Organization Behavior and Human Decision Process, 50(2), 179-211.

Allport, G. W. (1935). Attitudes. In C. Murchison (Ed.), A handbook of social psychology (pp. 789-994). Clark University Press.

Appel, G., Libai, B., Muller, E., & Shachar, R. (2020). On the monetization of mobile apps. International Journal of Research in Marketing, 37(1), 93-107.

Banerjee, S., Konishi, H., & Sönmez, T. (2001). Core in a simple coalition formation game. Social Choice and Welfare, 18(1), 135-153.

Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107(2), 238-246.

Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly, 25(3), 351-370.

Chang, I. C., Liu, C. C., & Chen, K. (2014). The effects of hedonic/utilitarian expectations and social influence on continuance intention to play online games. Internet Research, 24(1), 21-45.

Childers, T. L., Carr, C. L., Peck, J., & Carson, S. (2001). Hedonic and utilitarian motivations for online retail shopping behavior. Journal of Retailing, 77, 421.

Chinomona, R. (2013). An Investigation of Online Gaming Constraints and Continuance Intention in South Africa: A Student Perspective. Mediterranean Journal of Social Sciences, 4(14), 287-295.

Choi, D., & Kim, J. (2004). Why people continue to play online games: In search of critical design factors to increase customer loyalty to online contents. Cyber Psychology & Behavior, 7(1), 11-24.

Cialdini, R. B., Kallgren, C. A., & Reno, R. R. (1991). A focus theory of normative conduct: A theoretical refinement and reevaluation of the role of norms in human behavior. Advances in Experimental Social Psychology, 24(20), 1-243.

Crano, W., & Prislin, R. (2006). Attitudes and Persuasion. Annual review of psychology, 57(1), 345-374.

Crescenzi, A., Kelly, D., & Azzopardi, L. (2015). Time pressure and system delays in information search. In R. Baeza-Yates, M. Lalmas, A. Moffat & B. Ribeiro-Neto (Eds.), SIGIR '15: The 38th International ACM SIGIR conference on research and development in Information Retrieval (pp. 767-770). ACM Digital Library.

Delle, F. A., Massimini, F., & Bassi, M. (2011). Hedonism and eudaimonism in positive psychology In A. Delle Fave (Ed.), Psychological Selection and Optimal Experience Across Cultures: Social Empowerment through Personal Growth (pp. 3-18). Springer.

Diener, E. (2009). Subjective well-being. In E. Diener (Ed.), The science of well-being: The collected works of Ed Diener (pp. 11-58). Springer.

Doll, W., Xia, W., & Torkzadeh, G. (1994). A Confirmatory Factor Analysis of the End-User Computing Satisfaction Instrument. MIS Quarterly, 18(4), 453-461.

Eagly, A. H., & Chaiken, S. (1993). The psychology of attitudes (1st ed.). Harcourt Brace.

Elliot, S. N., Braden, J. P., & White, J. L. (2011). Assessing one and all: educational accountability for students with disabilities (1st ed.). Council foe Exceptional Children.

Fan, X., Duangekanong, S., & Xu, M. (2021). Factors Affecting College Students’ Intention to Use English U-learning in Sichuan, China. AU-GSB E-JOURNAL, 14(2), 118-129.

Fornell, C. G., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.

Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate Data Analysis: A Global Perspective (7th ed.). Pearson Education.

Hair, J., Black, W., Babin, B., Anderson, R., & Tatham, R. (2006). Multivariate Data Analysis (6th ed.). Pearson Prentice Hall.

Hassenzahl, M., & Tractinsky, N. (2006). User experience - A research agenda. Behaviour and Information Technology, 25(2), 91-97.

Hopwood, C. J., & Donnellan, M. B. (2010). How should the internal structure of personality inventories be evaluated?. Personality and Social Psychology Review, 14(3), 332-346.

Hsiao, C.-H., Chang, J.-J., & Tang, K.-Y. (2016). Exploring the influential factors in continuance usage of mobile social Apps: Satisfaction, habit, and customer value perspectives. Telematics and Informatics, 33(2), 342-355.

Jordan, W. C., & Graves, S. C. (1995). Principles on the benefits of manufacturing process flexibility. Management Science, 41(4), 577-594.

Jose, K. A., & Sia, S. K. (2022). Theory of planned behavior in predicting the construction of eco-friendly houses. Management of Environmental Quality, 33(4), 938-954.

Kim, D. J., & Hwang, Y. (2012). A study of mobile internet user’s service quality perceptions from a user’s utilitarian and hedonic value tendency perspectives. Information Systems Frontiers, 14(2), 409- 421.

Kitcharoen, K., & Vongurai, R. (2021). Factors Influencing Customer Attitude and Behavioral Intention Towards Consuming Dietary Supplements. AU-GSB E-JOURNAL, 13(2), 94-109.

Kline, R. B. (2011). Principles and practice of structural equation modeling (3rd ed.). Guilford Press.

Lee, W., & Choi, H. (2009). Understanding Meeting Planners' Internet Use Behavior: An Extension to the Theory of Planned Behavior. International Journal of Hospitality & Tourism Administration, 10(2), 109-128.

Limayem, M., Hirt, S. G., & Cheung, C. M. K. (2007). How habit limits the predictive power of intention: The case of information systems continuance. MIS Quarterly, 31(4), 705-737.

Liu, C., Yang, F., Zhao, Y., Jiang, Q., & Zhang, L. (2014). What does time constraint mean to information searchers? In D. Elsweiler, B. Ludwig, L. Azzopardi & M. L. Wilson (Eds.), Proceedings of the 5th information interaction in context symposium (pp. 227–230). ACM Digital Library.

Lopez, I., & Ruiz, S. (2011). Explaining website effectiveness: the hedonic-utilitarian dual mediation hypothesis. Electronic Commerce Research & Applications, 10(1), 49-58.

Luo, M. M., Chea, S., & Chen, J. S. (2011). Web-based information service adoption: a comparison of the motivational model and the uses and gratifications theory. Decision Support Systems, 51(1), 21-30.

Markus, M. L. (1987). Toward a ‘critical mass’ theory of interactive media: universal access, interdependence and diffusion. Communication Research, 14(5), 491-511.

Maule, A. J., Hockey, G. R. J., & Bdzola, L. (2000). Effects of time-pressure on decision-making under uncertainty: Changes in affective state and information processing strategy. Acta Psychologica, 104(3), 283-301.

Nunnally, J. C., & Bernstein, I. H. (1994). The Assessment of Reliability. Psychometric Theory, 3, 248-292.

Petty, R. E., Wegener, D. T., & Fabrigar, L. R. (1997). Attitudes and attitude change. Annual Review of Psychology, 48, 609-647.

Pollach, I. (2011). The readership of corporate websites. Journal of Business Communication, 48(1), 27-53.

Qiu, Y., & Fang, D. (2017, August 8). Investigation report on the influence of mobile students' daily study and life. FX361.

Rauschnabel, P. A., Rossmann, A., & Dieck, M. C. T. (2017). An adoption framework for mobile augmented reality games: the case of Pokémon Go. Computers in Human Behavior, 76, 276-286.

Sharma, G. P., Verma, R. C., & Pathare, P. (2005). Mathematical modeling of infrared radiation thin layer drying of onion slices. Journal of Food Engineering, 71(3), 282-286.

Sica, C., & Ghisi, M. (2007). The Italian versions of the Beck Anxiety Inventory and the Beck Depression Inventory-II: Psychometric properties and discriminant power. In M.A. Lange (Ed.), Leading - Edge psychological tests and testing research (pp. 27-50). Nova.

Sonderegger, A., Zbinden, G., Uebelbacher, A., & Sauer, J. (2012). The influence of product aesthetics and usability over the course of time: a longitudinal field experiment. Ergonomics, 55(7), 713–730.

Wang, J. (2017).The computer program structure for assigning individuals to populations: Easy to use but easier to misuse. Molecular Ecology Resources, 17(5), 981-990.

Wang, X., Goh, D., & Lim, E. (2020). Understanding Continuance Intention toward Crowdsourcing Games: A Longitudinal Investigation. International Journal of Human-Computer Interaction, 36(6), 1-10.

Waterman, A. S. (2008). Reconsidering happiness: a eudaemonist’s perspective. The Journal of Positive Psychology, 3(4), 234-252.

Wei, P. S., & Lu, H. P. (2014). Why do people play mobile social games? An examination of network externalities and of uses and gratifications. Internet Research, 24(3), 313-331.

Wheaton, B., Muthen, B., Alwin, D. F., & Summers, G. (1977). Assessing reliability and stability in panel models. Sociological Methodology, 8, 84-136.

White, K. M., Smith, J. R., Terry, D. J., Greenslade, J. H., & McKimmie, B. M. (2009). Social influence in the theory of planned behaviour: The role of descriptive, injunctive, and in‐group norms. British Journal of Social Psychology, 48(1), 135-158.

Wicker, A. (1969). Attitudes versus actions: The relationship of verbal and overt behavioral responses to attitude objects. Journal of social issues, 25(4), 41-78.

Wu, J. H., & Wang, Y. M. (2006). Measuring KMS success: A respecification of the DeLone and McLean’s model. Information and Management, 43(6), 728-739.

Wu, J., & Liu, D. (2007). The effects of trust and enjoyment on intention to play online games. Journal of Electronic Commerce Research, 8(2), 128-140.