Assessment of the Role of Enterprise Resource Planning (ERP) Implementation on Machakos University’s User Performance
Enterprise resource planning (ERP) systems occupy one of the largest and most important areas of information systems implementation in organisations in the world today. This study assessed the role of ERP implementation on Machakos University’s user performance. This study determined the relationship between enterprise resource planning system technology utilisation and user performance, system quality and user performance, and information quality and user performance. This study focused on user performance as compared to most studies that look into performance at the organisational level. The study made use of ICT models of adoption as its guidance. The implementation aspect was viewed from three perspectives, which include system technology utilisation, information quality, and finally, the system quality of the ERP system. Each aspect was analysed, and its effect on ERP system users was established in part and discussed. Data collection involved the use of questionnaires regarding the user performance of the ERP. Pearson’s correlation analysis was the statistical tool analyse the quantitative data. Microsoft Excel was used to capture data and transferred later into SPSS for detailed analysis, while descriptive statistics was used to help understand the characteristics of the study population. Computations from quantitative analysis pointed out respectively that Pearson’s correlation coefficient of technology utilisation = 0.686, system quality = 0.682, information quality = 0.757 and user performance (P-Value = 0.000) under the mediation of technology acceptance. This affirmed that for an ERP system, technology utilisation, system quality, information quality, respectively, and user performance have a statistically significant linear relationship (p < .05). Results also indicated that the magnitude or strength of the association is a strong one for each one of them since each of the aspects had its results within the range (.5 < | r | <.9). Characteristics of adopted technology, if well integrated together with the user tasks and abilities, and then coupled with appropriate system quality and information quality, resulted in enhanced user performance of an institution and by recommendation, such should form the backbone of an ERP as entails its design and implementation
Abugabah, A., Sanzogni, L., & Alfarraj, O. (2015). Evaluating the impact of ERP systems in higher education. The International Journal of Information and Learning Technology.
Ahmed, Z., Eryilmaz, E., & Alzahrani, A. I. (2022). IS diffusion: A dynamic control and stakeholder perspective. Information & management, 59(1), 103572.
Al-Emran, M. (2021). Evaluating the use of smartwatches for learning purposes through the integration of the technology acceptance model and task-technology fit. International Journal of Human-Computer Interaction, 37(19), 1874-1882.
Alloush, O. A. A., & Mahendrawathi, E. (2020). ERP Systems in Higher Education: A Systematic Literature Review. SISFO VOL 9 NO 2, 9.
Alyoussef, I. Y. (2021). E-Learning acceptance: The role of task–technology fit as sustainability in higher education. Sustainability, 13(11), 6450.
Andrianto, A. (2019). Impact of Enterprise Resource Planning (ERP) implementation on user performance: studies at University of Jember. Paper presented at the Journal of Physics: Conference Series.
Awad, R., Aljaafreh, A., & Salameh, A. (2022). Factors Affecting Students’ Continued Usage Intention of E-Learning During COVID-19 Pandemic: Extending Delone & Mclean IS Success Model. International Journal of Emerging Technologies in Learning, 17(10).
Baller, S., Dutta, S., & Lanvin, B. (2016). Global information technology report 2016: Ouranos Geneva.
Bamufleh, D., Almalki, M. A., Almohammadi, R., & Alharbi, E. (2021). User acceptance of Enterprise Resource Planning (ERP) systems in higher education institutions: A conceptual model. International Journal of Enterprise Information Systems (IJEIS), 17(1), 144-163.
BBC News 24. (2016, September 23). Grant Paling from Nebulas answers questions submitted for #BBCaskthis in relation to the Yahoo data breach announced today 23/09/2016 [Video]. YouTube. https://youtu.be/O32Pse_7W_I
Çelik, K., & Ayaz, A. (2022). Validation of the Delone and McLean information systems success model: a study on student information system. Education and Information Technologies, 27(4), 4709-4727.
Commission for University Education. (2019). Copyright© 2019 Commission for University Education. Nairobi; Printed in Kenya.
Cruz-Torres, W., Alvarez-Risco, A., & Del-Aguila-Arcentales, S. (2021). Impact of Enterprise Resource Planning (ERP) implementation on performance of an education enterprise: a Structural Equation Modeling (SEM).
DeLone, W. H., & McLean, E. R. (2016). Information systems success measurement. Foundations and Trends® in Information Systems, 2(1), 1-116.
Glenn, D. I. (2012). Determining Sample Size, PEOD6. University of Florida.
ISO/IEC. (2020). ISO/IEC 25000:2014 Systems and software engineering - Systems and software Quality Requirements and Evaluation (SQuaRE).
Jami Pour, M., Mesrabadi, J., & Asarian, M. (2022). Meta-analysis of the DeLone and McLean models in e-learning success: the moderating role of user type. Online Information Review, 46(3), 590-615.
Justino, M. V., Tengeh, R. K., & Twum-Darko, M. (2022). Task-technology fit perspective of the use of m-commerce by retail businesses. Entrepreneurship and Sustainability Issues, 9(4), 320.
Mehta, N., Chauhan, S., & Kaur, I. (2022). Extending the story of IS success: a meta-analytic investigation of contingency factors at individual and organisational levels. European Journal of Information Systems, 31(5), 617-640.
Mustafa, A. S., Alkawsi, G. A., Ofosu-Ampong, K., Vanduhe, V. Z., Garcia, M. B., & Baashar, Y. (2022). Gamification of E-Learning in African Universities: Identifying Adoption Factors Through Task-Technology Fit and Technology Acceptance Model. In Next-Generation Applications and Implementations of Gamification Systems (pp. 73-96): IGI Global.
NOVIKOV, S. V., & SAZONOV, A. A. (2020). Improving the enterprise resource planning system based on digital modules of the industry 4.0 concept. Revista ESPACIOS, 41(05).
Ratna, S., Utami, H. N., Astuti, E. S., & Muflih, M. (2020). The technology tasks fit, its impact on the use of information system, performance and users’ satisfaction. VINE Journal of Information and Knowledge Management Systems.
ReportLinker. (2023). Information Technology Global Market Report 2023. GlobeNewswire
Rokhman, F., Mukhibad, H., Bagas Hapsoro, B., & Nurkhin, A. (2022). E-learning evaluation during the COVID-19 pandemic era based on the updated of Delone and McLean information systems success model. Cogent Education, 9(1), 2093490.
Santoso, R. W., Siagian, H., Tarigan, Z. J. H., & Jie, F. (2022). Assessing the benefit of adopting ERP technology and practicing green supply chain management toward operational performance: An evidence from Indonesia. Sustainability, 14(9), 4944.
Schräge, M., Muttreja, V., & Kwan, A. (2022). How the Wrong KPIs Doom Digital Transformation. MIT Sloan Management Review, 63(3), 35-40.
SIMON, K. G. (2021). Enterprises Resource Planning Implementation Aspects And Organisational Performance: A Case Of Egerton University, Kenya.
Sislian, L., & Jaegler, A. (2020). ERP implementation effects on sustainable maritime balanced scorecard: Evidence from major European ports. Paper presented at the Supply Chain Forum: An International Journal.
Soliman, M., & Karia, N. (2017). Antecedents for the success of the adoption of organisational ERP among higher education institutions and competitive advantage in Egypt. Engineering, Technology & Applied Science Research, 7(3), 1719-1724.
Taris, T. W., Kessler, S. R., & Kelloway, E. K. (2021). Strategies addressing the limitations of cross-sectional designs in occupational health psychology: What they are good for (and what not). In (Vol. 35, pp. 1-5): Taylor & Francis.
Xulu, V. C., & Suknunan, S. (2020). Enterprise Resource Planning (ERP) systems success: impact of employees’ perceptions and satisfaction on expected benefits in a manufacturing setting. Problems and Perspectives in Management, 18(2), 466.
Yamane, T. (1967:886). Statistics, An Introductory Analysis, 2nd Ed. New York: Harper and Row.
Yu Chung Wang, W., Pauleen, D., & Taskin, N. (2022). Enterprise systems, emerging technologies, and the data-driven knowledge organisation. In (Vol. 20, pp. 1-13): Taylor & Francis.
Copyright (c) 2023 Martin Mauye
This work is licensed under a Creative Commons Attribution 4.0 International License.