Perceived Usefulness, Perceived Enjoyment, Trust, and Continuance Intention
DOI:
https://doi.org/10.61841/1qm5n466Keywords:
Perceived usefulness, Perceived enjoyment, Trust, , Continuance intention.Abstract
Users consistency in using mobile apps has become significantly important for the app- related technology development. The aim of this paper is to investigate the effects of perceived usefulness, perceived enjoyment, and trust on the users’ continuance intention to use mobile apps. This paper proposed a research framework to identify the predictors of continuance intention of mobile apps users and highlight the users experience when using mobile apps. Data were collected from mobile apps users in Malaysia. This study used structural equation modeling (SEM) with AMOS statistical software to test the research framework using a standardized and structured self-administered questionnaire. The results generate suggestions for mobile apps developers to prioritize perceived enjoyment, and trust in their planning to retain their users to continuously using the mobile apps. Although many studies have focused on continuance intention, but, still lack of studies have examined the behavior of individual differences based on demographics, such as continuance intention of mobile apps users in Malaysia. It generates useful guidance for mobile apps developers, specifically, aims on mobile apps users in Malaysia to effectively retain them in using their mobile apps.
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References
[1] Akter, S., Ray, P., & D’Ambra, J. (2013). Continuance of mhealth services at the bottom of the pyramid: The roles of service quality and trust. Electronic Markets, 23(1), 29-47.
[2] Ary, D., Jacobs, L. C., & Razavieh, A. (2002). Introduction to research in education. Belmont, California: Wadsworth/Thomson Learning.
[3] Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411-423.
[4] Boomsma, A. (1983). On the robustness of LISREL (Maximum Likelihood Estimation) against small sample size and non- normality. Rijksuniversiteit Groningen, Amsterdam: Sociometric Research Foundation.
[5] Bhattacherjee, A., & Premkumar, G. (2004). Understanding changes in belief and attitude toward information technology usage: A theoretical model and longitudinal test. MIS Quarterly, 28(2), 229-254.
[6] Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation- confirmation model. MIS Quarterly, 25(3), 351-370.
[7] Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.
[8] Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace. Journal of Applied Psychology, 22(14),
[9] 1111-1132.
[10] Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
[11] Guilford, J. P. (1956). Fundamental statistics in psychology and education. New York, NY: McGraw-Hill.
[12] Gefen, D., & Straub, D. (2000). The relative importance of perceived ease of use in IS adoption: A study of e-commerce. Journal of AIS, 1(8), 1-30.
[13] Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis. Upper Saddle River, New Jersey: Pearson Prentice Hall.
[14] Hong, S. J., Thong, Y. L., Moon, J. Y., & Tam, K. Y. (2008). Understanding the behavior of mobile data services consumers. Information System Frontier, 10, 431-445.
[15] Ku, Y. C., Chen, R., & Zhang, H. (2013). Why do users continue using social networking sites? An exploratory study of members in the United States and Taiwan. Information & Management, 50(7), 571-581.
[16] Liao, C. H., Tsou, C. W., & Huang, M. F. (2007). Factors influencing the usage of 3G mobile services in Taiwan. Online Information Review, 31(6), 759-774.
[17] Lu, L., & Ling, S. (2009). Adoption intentions of Taiwanese passengers to use self check-in services on international flight routes. Journal Chinese Institute Transportation, 21(3), 299-328.
[18] Liu, Y., & Li, H. (2010). Mobile internet diffusion in China: An empirical study. Industrial Management & Data Systems, 110(3), 309-324.
[19] Lei, M., & Lomax, R. G. (2005). The effect of varying degrees of non-normality in structural equation modeling. Structural Equation Modeling, 12(1), 1-27.
[20] Mou, J., Shin, D. H., & Cohen, J. (2016). Understanding trust and perceived usefulness in the consumer acceptance of an e- service: A longitudinal investigation. Behavior &
[21] Information Technology, 36(2), 125-139.
[22] Ou, C. X., Pavlou, P. A., & Davison, R. M. (2014). Swift guanxi in online marketplaces: The role of computer-mediated communication technologies. MIS Quarterly, 38(1), 209-230.
[23] Pedersen, P. E. (2005). Adoption of mobile internet services: An exploratory study of mobile commerce early adopters. Journal of Organizational Computing and Electronic Commerce, 15(2), 203-222.
[24] Sun, Y., Liu, L., Peng, X., Dong, Y., & Barnes, S. J. (2014). Understanding Chinese users’ continuance intention toward online social networks: An integrative theoretical model. Electronic Markets, 24(1), 57-66.
[25] Susanto, A., Chang, Y., & Ha, Y. (2016). Determinants of continuance intention to use the smartphone banking services: An extension to the expectation-confirmation model. Industrial Management & Data Systems, 116(3), 508-525.
[26] Teo, T. S. (2001). Demographic and motivation variables associated with internet usage activities. Internet Research, 11(2), 125-137.
[27] Watson, C., Mccarthy, J., & Rowley, J. (2013). Consumer attitudes towards mobile marketing in the smart phone era. International Journal of Information Management, 33(5), 840-849.
[28] Xiuyuan, G., Zhiying, L., Xiabing, Z., & Tailai, W. (2018). Why are experienced users of WeChat likely to continue using the app? Asia Pacific Journal of Marketing and Logistics, 30(4), 1013-1039. doi.10.1108/APJML-10-2017-0246
[29] Yoon, S., Kim, S., Kim, J., & You, Y. (2016). A study on the impact of consultants’ nonverbal communication on customer satisfaction, trust, and long-term relationship orientation of the client firm. Indian Journal of Science and Technology, 9(26), 1-8.
[30] Zhou, Z., Jin, X-L., & Fang, Y. (2014). Moderating role of gender in the relationships between perceived benefits and satisfaction in social virtual world continuance. Decision Support Systems, 65, 69-79.
[31] Zhou, T. (2013). An empirical examination of continuance intention of mobile payment services. Decision Support Systems, 54(2), 1085-1091.
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