EZZEePOT EASE OF USE PERCEPTION STUDY

Mohd Hafiz Abdul Halim; Franklin Hazley Lai; Syahrul Nizam  Salam

Mohd Hafiz Abdul Halim
Franklin Hazley Lai
Dr Syahrul Nizam Salam

Keywords: Mobile Applications, Financial Transaction Records, Ease of Use Perception

Abstract

The main challenge that Kona Bites is dealing with is the lack of an application for recording financial transactions online. Therefore, the study leads to the implementation of the ADDIE model to plan the development of the EZZEePOT mobile application (Gustafson & Branch, 2001) and further analyze the commercialization potential through SWOT, TOWS and 4P analysis. The factors influencing the perceived ease of use of EZZEePOT are also analyzed in this study in accordance with the Venkatesh et al. (2003) Theory of Acceptance and Use of Technology (UTAUT). 12 staff members of Kona Bites who use the application every working day represent the study sample. Sampling using purposive sampling and data analysis using GNU software, PSPP. The data is interpreted based on percentage values, mean and standard deviation. The results of the study show that the commercialization potential of the EZZEePOT mobile application to Kona Bites staff can be extended to Small and Medium Industries (SME) businesses. The results of this study show that Kona Bites staff have a significantly high influence on the intention to actually use this application for the factors of performance expectancy and effort expectancy. Therefore, this factor has a significant effect on the actual use of the EZZEePOT application. Nevertheless, the results of this study show that Kona Bites staff have a moderately significant influence on the intention to actually use this application for the facilitating conditions factor.

References

Ain, N., Ghazali, N., & Yusof, SM (2023). Design and development of mobile application: Nursery.com application. Multidisciplinary Applied Research and Innovation, 4 (1), 74–81. https://doi.org/10.30880/mari.2023.04.01.015

Al-Shihi, H., Sharma, SK, & Sarrab, M. (2018). Neural network approach to predict mobile learning acceptance. Education and Information Technologies, 23 (5), 1805–1824. https://doi.org/10.1007/s10639-018-9691-9

Davis, FD, Bagozzi, RP, & Warshaw, PR (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35 (8), 982–1003. https://doi.org/10.1287/mnsc.35.8.982

Gay, LR, Mills, GE, & Airasian, P. (2012). Educational research: Competencies for analysis and applications (10th ed.). New Jersey: Pearson Education Inc.

Gray, R., Owen, D., & Maunders, K. (1987). Corporate social reporting: Accounting and accountability. Prentice-Hall International.

Gustafson, KL, & Branch, RM (2001). Survey of instructional development models . New York: ERIC Clearinghouse on Information & Technology.

Jabbar, WA, Tiew, LY, & Ali Shah, NY (2024). Internet of things enabled parking management system using long range wide area network for smart city. Internet of Things and Cyber-Physical Systems , 4 , 82–98. https://doi.org/10.1016/j.iotcps.2023.09.001

Mohamad Hazeel Amirul Zainuddin, N., Mohd Yasin, S., & Computer Science and Information Technology, F. (2022). Budget Planner Application Development (iBudget) [Budget Planner Application Development (iBudget)]. Applied Information Technology And Computer Science, 3 (1), 878–888. https://doi.org/10.30880/aitcs.2022.03.01.059

Pallant, J. (2016). SPSS survival manual (6th ed.). New York, USA: McGraw-Hill Education.

Venkatesh, V., & Morris, MG (2000). Why don't men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior. MIS Quarterly, 24(1), 115-139.

Wong, AY, & Khadijah Daud. (2017). Headmaster technology leadership in Malaysian elementary schools. Journal of Education and Learning (EduLearn) , 11(2), 154. https://doi.org/10.11591/edulearn.v11i2.5573