The Influence of Facilitating Condition and Perceived Usefulness on Intention to Use Mobile Applications in Uganda
Abstract
Despite the fact that financial technology has received considerable attention in the macro-financial market sectors and in micro-financial units such as philanthropic works, in Uganda its actual use in Muslim Sacco's is very low. This research examines the effects of facilitating conditions and perceived usefulness on intention to use mobile application in Muslim Sacco's in Uganda. The underpinning theory of the study is the Technology Acceptance Model (TAM). This quantitative study examined the effect of facilitating condition and perceived usefulness on mobile applications users’ intention. The study employs SmartPLS to analyze the data from 229 respondents. It was discovered that the facilitating condition had a considerable positive impact on mobile applications users’ intention, hence, supporting H1. Simultaneously, perceived usefulness was revealed to have a considerable impact mobile applications users’ intention, supporting hypothesis H2. Such studies will form the groundwork for numerous inquiries to come purposely to expand the knowledge about the factors that influence technology usage in Uganda.
Downloads
References
Aharony, N. (2014, November 1). Factors Affecting Adoption of Facebook: An Exploratory Study of the LIS Community Perspective. Aharony College & Research Libraries. https://crl.acrl.org/index.php/crl/article/view/16394/17840
Arner, D. W., Buckley, R. P., & Dirk, A. (2018). Fintech for Financial Inclusion: A Framework for Digital Financial Transformation. Social Science Research Network. https://doi.org/10.2139/ssrn.3245287
Asiimwe, E, N. & Gronlund, A., (2015). MLCMS actual use, perceived use, and experiences of use. International Journal of Education and Development using Information and Communication Technology, 11(1), 101-212
Aslam, W., Arif, I., Atiq, Z., & Hussain, F. (2021). Connecting Mobile Application Features with Perceived Benefits in Determining Post-adoption Behaviour. FIIB Business Review, 10(4), 454-465. https://doi.org/10.1177/23197145211035748
Binyamin, S. (2019). Using the Technology Acceptance Model to Measure the Effects of Usability Attributes and Demographic. . . ResearchGate. https://doi.org/10.13140/RG.2.2.13874.96963
Binyamin, S. S., Rutter, M., & Smith, S. E. (2020). The moderating effect of gender and age on the students’ acceptance of learning management systems in Saudi higher education. Knowledge Management & E-Learning: An International Journal, 30–62. https://doi.org/10.34105/j.kmel.2020.12.003
Bolodeoku, P. B., Igbinoba, E. E., Salau, P., Chukwudi, C. K., & Idia, S. E. (2022). Perceived Usefulness of Technology and Multiple Salient Outcomes: The Improbable Case of Oil and Gas Workers. Heliyon, e09322. https://doi.org/10.1016/j.heliyon.2022.e09322
Bwiino, K., Lubogoyi, B., & Kituyi, G. M. (2018). Perceived Credibility of Social Networking Technologies in Uganda’s Institutions of Higher Learning. Global Journal of HUMAN-SOCIAL SCIENCE: G Linguistics & Education, 17(10). ResearchGate. https://www.researchgate.net/publication/322552211_Perceived_Credibility_of_Social_Networking_Technologies_in_Uganda's_Institutions_of_Higher_Learning
Chinomona, R. (2017). The influence of perceived ease of use and perceived usefulness on trust and intention to use mobile social software. African Journal for Physical, Health Education, Recreation and Dance, 19(June), 258-273. https://www.academia.edu/34069307/The_influence_of_perceived_ease_of_use_and_perceived_usefulness_on_trust_and_intention_to_use_mobile_social_software_technology_and_innovation
Chtourou, M., & Souiden, N. (2010). Rethinking the TAM model: time to consider fun. Journal of Consumer Marketing, 27(4), 336–344. https://doi.org/10.1108/07363761011052378
Commer, P. J., Sci, S., Sair, S. A., & Danish, R. Q. (2018). Effect of Performance Expectancy and Effort Expectancy on the Mobile Commerce Adoption Intention through Personal Innovativeness among. Pakistan Journal of Commerce and Social Sciences, 12(2), 501-520. https://www.researchgate.net/publication/327702133_Effect_of_Performance_Expectancy_and_Effort_Expectancy_on_the_Mobile_Commerce_Adoption_Intention_through_Personal_Innovativeness_among_Pakistani_Consumers
Diop, E. B., Zhao, S., & Van Duy, T. (2019). An extension of the technology acceptance model for understanding travelers’ adoption of variable message signs. PLOS ONE, 14(4), e0216007. https://doi.org/10.1371/journal.pone.0216007
Durgabhavani, K., & Krishnan, A. R. (2019). Perceived Usefulness And Its Impact On Online Shopping. International Journal of Marketing and Human Resource Management, 10(2). https://doi.org/10.34218/ijmhrm.10.2.2019.004
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/ebr-11-2018-0203
Hamzah, N., Haji-Othman, Y., & Cheumar, M. (2023). A Fintech-Backed Effective Mosque-Funds Mobilization and Collection Framework in Uganda. ITQAN: Journal of Islamic Economics, Management, and Finance, 2(1), 42–48. https://doi.org/10.57053/itqan.v2i1.15
Holden, R. J., & Karsh, B. (2010). The Technology Acceptance Model: Its past and its future in health care. Journal of Biomedical Informatics, 43(1), 159–172. https://doi.org/10.1016/j.jbi.2009.07.002
Jayatilleke, B. G., Ranawaka, G. R., Wijesekera, C., & Kumarasinha, M. C. (2018). Development of mobile application through design-based research. AAOU Journal, 13(2), 145–168. https://doi.org/10.1108/aaouj-02-2018-0013
Leong, L., Ooi, K., Chong, A. Y., & Lin, B. (2011). Influence of individual characteristics, perceived usefulness and ease of use on mobile entertainment adoption. International Journal of Mobile Communications, 9(4), 359. https://doi.org/10.1504/ijmc.2011.041141
McCord, M. A. (2007). TheoryHub Book: Technology Acceptance Model: Handbook of Research on Electronic Surveys and Measurements. IGI Global Publisher of Timely Knowledge. https://doi.org/10.4018/978-1-59140-792-8.ch038
Meyliana, M., Fernando, E., & Surjandy, S. (2019). The Influence of Perceived Risk and Trust in Adoption of FinTech Services in Indonesia. Commit Journal, 13(1), 31. https://doi.org/10.21512/commit.v13i1.5708
Morrison-Smith, S., & Ruiz, J. (2020). Challenges and barriers in virtual teams: a literature review. SN Applied Sciences, 2(6). https://doi.org/10.1007/s42452-020-2801-5
Rauniar, R., Rawski, G., Yang, J., & Johnson, B. M. (2014). Technology acceptance model (TAM) and social media usage: an empirical study on Facebook. Journal of Enterprise Information Management, 27(1), 6–30. https://doi.org/10.1108/jeim-04-2012-0011
Rowan, P., Garvey, K., Zhang, B. Z., Soriano, M. C., Umer, Z., Cloud, K., Cracknell, D., Singh, A. K., Kutosi, S., & Ahimbisibwe, D. (2018). FinTech in Uganda: Implications for Regulation. Social Science Research Network. https://doi.org/10.2139/ssrn.3621272
Roy, S., & Sinha, I. (2014). Determinants of Customers’ Acceptance of Electronic Payment System in Indian Banking Sector - A Study. International Journal of Scientific & Engineering Research, 5(1), 177–187. https://www.ijser.org/researchpaper/Determinants-of-Customers-Acceptance-of-Electronic-Payment.pdf
Singh, S., Sahni, M. M., & Kovid, R. K. (2020). What drives FinTech adoption? A multi-method evaluation using an adapted technology acceptance model. Management Decision, 58(8), 1675–1697. https://doi.org/10.1108/md-09-2019-1318
Stocchi, L., Pourazad, N., Michaelidou, N., Tanusondjaja, A., & Harrigan, P. (2021). Marketing research on Mobile apps: past, present and future. Journal of the Academy of Marketing Science, 50(2), 195–225. https://doi.org/10.1007/s11747-021-00815-w
Teo, T., & Noyes, J. (2014). Explaining the intention to use technology among pre-service teachers: a multi-group analysis of the Unified Theory of Acceptance and Use of Technology. Interactive Learning Environments, 22(1), 51–66. https://doi.org/10.1080/10494820.2011.641674
Thomas, T. D., Singh, L., & Gaffar, K. (2013). The Utility of the UTAUT Model in Explaining Mobile Learning Adoption in Higher Education in Guyana. International Journal of Education and Development Using Information and Communication Technology, 9(3), 71-85.ResearchGate. https://www.researchgate.net/publication/259479186
Torno, A., Werth, O., Nickerson, A., Breitner, M., C. (2021). More than Mobile Banking – A Taxonomy-based Analysis of Mobile Personal Finance Applications. Conference: Twenty-Fifth Pacific Asia Conference on Information Systems (PACIS), 1-14. https://aisel.aisnet.org/pacis2021/179
Tsai, W., Wu, Y., Cheng, C., Kuo, M., Chang, Y., Hu, F., Sun, C., Chang, C., Chan, T., Chen, C., Lee, C., & Chu, C. (2021). A Technology Acceptance Model for Deploying Masks to Combat the COVID-19 Pandemic in Taiwan (My Health Bank): Web-Based Cross-sectional Survey Study. Journal of Medical Internet Research, 23(4), e27069. https://doi.org/10.2196/27069
Tun-Pin, Keng-Soon, C., Yen-San, W. C., Pui-Yee, Y., Hong-Leong, C., Shwu-Shing, J. T., & Ng. (2019). An Adoption of Fintech Service in Malaysia. South East Asia Journal of Contemporary Business, Economics and Law, 5(18), 73–92. https://seajbel.com/wp-content/uploads/2019/05/seajbel5-VOL18_241.pdf
Uganda National Planning Authority. (2020, July 1). Third National Development Plan (NDPIII) 2020/21-2024/25. Uganda Vision 2040, 3(3), 341. http://www.npa.go.ug/wp-content/uploads/2020
Venkatesh, V., Morris, M. A., Davis, G. B., & Davis, F. D. (2003). User Acceptance of Information Technology: Toward a Unified View. Management Information Systems Quarterly, 27(3), 425. https://doi.org/10.2307/30036540
Yang, H., & Yoo, Y. (2004). It’s all about attitude: revisiting the technology acceptance model. Decision Support Systems, 38(1), 19–31. https://doi.org/10.1016/s0167-9236(03)00062-9
Zeidy, I., A., (2022, August 11). The Role of Financial Technology (FINTECH) in Changing Financial Industry and Increasing Efficiency in the Economy. Common Markets for Eastern and Southern Africa, 1(1), 1-20. https://www.studypool.com/documents/20505579/the-role-of-financial-technology-1-
