Abstract
It has been determined that there is insufficient explanation for people switching and continuously using mobile computing applications. Knowing and being able to explain this behavior was regarded as essential and might be useful to both application developers and researchers, particularly in forecasting future behavior. The objective of this study was to model the determinants influencing switching and continued use of mobile computing applications using Cronbach’s alpha and confirmatory factor analysis. Data were collected from academics in South African universities through a survey using structured questionnaires. Cronbach’s alpha and confirmatory factor analysis were used for reliability and validity testing [19]. Five decision variables were supported as significant with Cronbach’s alpha and confirmatory factor analysis. Model significance and strength were assessed using SEM to estimate the model’s coefficients [8]. The variance of the dependent variable, “continue use,” was 38%, and switching behavior was 32% as a contribution to this study.
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References
Abbas, H.A., Hamdy, H.I.: Determinants of continuance intention factor in Kuwait communication market: case study of Zain-Kuwait. Comput. Hum. Behav. 49, 648–657 (2015)
Ajzen, I., Fishbein, M.: A Bayesian analysis of attribution processes. Psychol. Bull. 82(2), 261 (1975)
Andrade, A.D., Doolin, B.: Information and communication technology and the social inclusion of refugees. MIS Q. 40(2), 405–416 (2016)
Bhattacherjee, A., Lin, C.P.: A unified model of IT continuance: three complementary perspectives and crossover effects. Eur. J. Inf. Syst. (2014)
Chen, W., Hirschheim, R.: A paradigmatic and methodological examination of information systems research from 1991 to 2001. Inf. Syst. J. 14(3), 197–235 (2004)
Creswell, J.W.: Qualitative Inquiry & Research Design: Choosing Among Five Approaches. 3rd edn. Sage, Los Angeles (2013)
Ebner, M.: Mobile applications for math education–how should they be done. In: Mobile Learning and Mathematics. Foundations, Design, and Case Studies, pp. 20–32 (2015)
Fan, Y., et al.: Applications of structural equation modelling (SEM) in ecological studies: an updated review. Ecol. Process. 5(1), 1–12 (2016)
Goodhue, D.L.: Understanding user evaluations of information systems. Manage. Sci. 41(12), 1827–1844 (1995)
Kgopa, A.T., Kekwaletswe, R.M., Pretorius, A.: A model for switching and continued use of mobile computing applications amongst South African academics’. South African J. Inf. Manage. 24(1), a1470 (2022). https://doi.org/10.4102/sajim.v24i1.1470
Kim, H.J., Lee, J.M., Rha, J.Y.: Understanding the role of user resistance on mobile learning usage among university students. Comput. Educ. 113, 108–118 (2017)
Middleton, C., Scheepers, R., Tuunainen, V.K.: When mobile is the norm: researching mobile information systems and mobility as post-adoption phenomena. Eur. J. Inf. Syst. 23(5), 503–512 (2014)
National Communications Authority: Quarterly Statistical Bulletin on Communications in Ghana 2(3), 211 (2017)
Ndayizigamiye, P., Kante, M., Shingwenyana, S.: An adoption model of mHealth applications that promote physical activity. Cogent Psychol. 7(1), 1764703 (2020)
Nel, J., Boshoff, C.: Cell phone banking adoption and the continuance of use in an internet-banking context: a study of consumer cognitive evaluations, PHD, Department of Business Management, Marketing Management: University of Pretoria (2013)
Osah, O., Kyobe, M.: User continuance intention towards mobile technology-enabled services in developing regions, PHD, Department of Information System: University of Cape Town (2015)
Osakwe, J.O., Iyawa, M.U.G., Florich, K.: Enabling quality education in Namibia through mobile learning technologies. The high school teachers’ perspective. In: Proceedings IST-Africa Week Conference (IST-Africa), pp. 1–9) (2018)
Pallant, J.: SPSS Survival Manual: A Step by Step Guide to Data Analysis using IBM SPSS. Routledge (2020)
Pomykalski, J.J., Dion, P., Brock, J.L.: A structural equation model for predicting business student performance. J. Educ. Bus. 83(3), 159–164 (2008)
Purnami, L.D., Agus, A.A.: The effect of perceived value and mobile game loyalty on in-app purchase intention in mobile game in Indonesia (case study: mobile legend and love nikki). ASEAN Mark. J. 12(1), 9–19 (2020)
Ray, S., Kim, S.S., Morris, J.G.: Research note-online users’ switching costs: their nature and formation. Inf. Syst. Res. 23, 197–213 (2012)
Rouibah, K.: Switching factors in mobile service providers: qualitative study from an Arab country. In: International Conference on Transformations and Innovations in Management (ICTIM-17) (2017)
Salo, M., Makkonen, M.: Why do users switch mobile applications? Trialing behavior as a predecessor of switching behavior. Commun. Assoc. Inf. Syst. 42, 386–407 (2018)
Subhadin, R.: App adoption and switching behavior: applying the extended TAM in smart phone App adoption and switching behaviour. J. Inf. Syst. Technol. Manage. 14, 239–261 (2017). https://www.scielo.br/pdf/jistm/v14n2/1807-1775-jistm-14-02-00239.pdf. Accessed 2 Jun 2019
Tran, V.D.: Using mobile food delivery applications during the COVID-19 pandemic: Applying the theory of planned behavior to examine continuance behavior. Sustainability 13(21), 12066 (2021)
Tutubala, N., Mathonsi, T.E.: A hybrid framework to improve data security in cloud computing. In: 2021 Big Data, Knowledge and Control Systems Engineering (BdKCSE), pp. 1–5. IEEE (2021)
Van der Merwe, M.C.: A comparison between switching intension and switching behavior in the South African mobile telecommunications industry, DCom Marketing Management, University of Pretoria (2015)
Yavuz, M., Çorbacioğlu, E., Başoğlu, A.N., Daim, T.U., Shaygan, A.: Augmented reality technology adoption: case of a mobile application in Turkey. Technol. Soc. 66, 101598 (2021)
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Kgopa, A.T., Kekwaletswe, R., Pretorius, A. (2023). An Empirical Analysis of the Switching and Continued Use of Mobile Computing Applications: A Structural Equation Model. In: Silhavy, R., Silhavy, P. (eds) Networks and Systems in Cybernetics. CSOC 2023. Lecture Notes in Networks and Systems, vol 723. Springer, Cham. https://doi.org/10.1007/978-3-031-35317-8_13
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