Self-Efficacy and User Behavioural Intention to Use Online Consultation Management System

Mohamad Rahimi Mohamad Rosman, Mohammad Azhan Abdul Aziz, Mohd Akmal Faiz Osman, Noor Masliana Razlan


Consultation is an act of discussing certain issue between two or more parties. Consultation is considered very importance especially in the context of higher education. The Novel Coronavirus 2019 has shifted the education paradigm into digital dependency, including consultation management between students and academicians. However, lack of studies has been conducted on the roles of self-efficacy towards user behavioural intention to use online consultation management system in the aftermath of a pandemic. Therefore, the objective of this paper is to investigate the relationship between self-efficacy and user behavioural intention to use online consultation management system. An instrument was developed by adopting previous studies on technology acceptance. In term of respondents, 270 students were selected based on convenience sampling. Findings were analysed using Statistical Package for Social Sciences (SPSS) version 26 and SmartPLS version 3.2.8. Results show that all hypotheses were supported. Self-efficacy has a positive and significant relationship with perceived usefulness and ease of use. On the other hand, both perceived usefulness and ease of use has a significant and positive relationship with attitude towards using online consultation management system. 


Consultation; Self-efficacy; Behavioural intention; Attitude; System Development


Erchul, W. P. & Martens, B. K. Introduction to Consultation. In: School Consultation. Issues in Clinical Child Psychology. Springer, Boston, MA, 2002.

Rajaee M, Ahmadi A, Abedi M. Academic counseling effect on academic skill and success of Isfahan students. consultation researches. 2004;4(12): 41–52, 2004.

Rezaee, R., Nabeiei, P. & Sagheb, M. M. (2014). Evaluation of the consultation program in Shiraz University of Medical Sciences. J Adv Med Educ Prof. 2014 Jan; 2(1): 27–32, 2014.

White, E. R. Academic advising in a pandemic and beyond., 2020.

Odeh, M., & Yousef, M. The effect of covid-19 on the electronic payment system: Usage level trust and competence perspectives. Indonesian Journal of Electrical Engineering and Computer Science, 22(2), 1144-1155, 2021.

Davis, F. D. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340, 1989.

Isaac, O., & Mutahar, A. M. Internet Usage within Government Institutions in Yemen: An Extended Technology Acceptance Model (TAM) with Internet Self-Efficacy and Performance Impact Information System Strategic Planning View project SMART-Government View project, 2017.

Mutahar, A. M., Daud, N. M., Thurasamy, R., Isaac, O., & Abdulsalam, R. The Mediating of Perceived Usefulness and Perceived Ease of Use: The Case of Mobile Banking in Yemen. International Journal of Technology Diffusion (IJTD), 9(2), 21-40, 2018.

Ozturk, A. B., Bilgihan, A., Nusair, K., & Okumus, F. What keeps the mobile hotel booking users loyal? Investigating the roles of self-efficacy, compatibility, perceived ease of use, and perceived convenience. International Journal of Information Management, 36(6), 1350–1359, 2016.

Abdullah, F., Ward, R., & Ahmed, E. Investigating the influence of the most commonly used external variables of TAM on students’ Perceived Ease of Use (PEOU) and Perceived Usefulness (PU) of e-portfolios. Computers in Human Behavior, 63, 75–90, 2016.

Patricia Aguilera-Hermida, A. College students’ use and acceptance of emergency online learning due to COVID-19. International Journal of Educational Research Open, 1, 100011, 2020.

Sun, T., Tai, Z. & Tsai, K. Perceived ease of use in prior e‐commerce experiences: A hierarchical model for its motivational antecedents. Psychology and Marketing, 27 (9), 2010.

Hsiao, J. C., Moser C. Schoenebeck, S. & Dillahunt, T. R. The role of demographics, trust, computer self-efficacy, and ease of use in the sharing economy. COMPASS '18: Proceedings of the 1st ACM SIGCAS Conference on Computing and Sustainable Societies. June 2018, 1–11, 2018.

Mohamad Rosman, M. R., Ismail, M. N., & Masrek, M. N. How Engaging Are You? Empirical Evidence from Malaysian Research Universities. International Journal of Interactive Mobile Technologies (IJIM), 15(04), pp. 16-30, 2021.

S Baharuddin, N., & Mohamad Rosman, M. R. Factors affecting the usage of Library e-services in the aftermath of COVID-19 Pandemic. Academic Journal of Business and Social Sciences (AJoBSS), 4(1), 1-14, 2020.

O'Brien, H. L., & Toms, E. G. The development and evaluation of a survey to measure user engagement. Journal of the American Society for Information Science and Technology, 61(1), 50-69, 2010.

Masrek, M. N., Razali, M. H., Ramli, I., & Andromeda, T. User engagement and satisfaction: The case of web digital library. International Journal of Engineering and Technology (UAE), 7(4), 19-24, 2018.

Mohamad Rosman, M. R., Ismail, M. N., & Masrek, M. N. Investigating the determinant and impact of digital library engagement: a conceptual framework. Journal of Digital Information Management, 17(4), 214-226, 2019.

Bakker, A. B., & Demerouti, E. The job demands‐resources model: State of the art. Journal of managerial psychology, 22 (3), 2007.

Venkatesh, V., Thong, J. Y., Chan, F. K., Hu, P. J. H., & Brown, S. A. Extending the two‐stage information systems continuance model: Incorporating UTAUT predictors and the role of context. Information Systems Journal, 21(6), 527-555, 2011.

Nunnally, J.C. Psychometric theory. 2nd Edition, McGraw-Hill, New York, 1978.

Hair, J.F., Ringle, C.M., & Sarstedt, M. PLS-SEM: Indeed a silver bullet. The Journal of Marketing Theory and Practice, 19(2), 139-152, 2011.

Kock, N., & Hadaya, P. (2018). Minimum sample size estimation in PLS‐SEM: The inverse square root and gamma‐exponential methods. Information Systems Journal, 28(1), 227-261, 2018.

Hair Jr, J. F., Sarstedt, M., Hopkins, L., & Kuppelwieser, V. G. Partial least squares structural equation modeling (PLS-SEM). European business review, 26 (2), 106-121, 2014.

Wherry, R. J. A new formula for predicting the shrinkage of the coefficient of multiple correlation. The annals of mathematical statistics, 2 (4):440-457, 1931.

Cohen, J. Statistical power analysis for the behavioral sciences. 2nd ed. Hillsdale, NJ: Lawrence Erlbaum Associates, 1988.

DeLone, W. H., & McLean, E. R. The DeLone and McLean model of information systems success. Journal of Management Information Systems, 19(4), 9-30 2003.

Haglan, H. M., Mahmoud, A. S., AL-Jumaili, M. H., & Aljaaf, A. J. New ideas and framework for combating COVID-19 pandemic using IoT technologies. Indonesian Journal of Electrical Engineering and Computer Science, 22(3), 1565-1572, 2021.

Jahan, N., Shawon, M. A. H., Sadia, F., Nitu, D. K., Ribon, M. E. K., & Mahmud, I. Modelling consumer's intention to use iot devices: Role of technophilia. Indonesian Journal of Electrical Engineering and Computer Science, 23(1), 612-620, 2021.

Alotaibi, R., & Alghamdi, A. Studying faculty members’ readiness to use shaqra university e-learning platform. Indonesian Journal of Electrical Engineering and Computer Science, 22(3), 1556-1564, 2021.



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