Comparing Internal and External User Perceptions of a National Research Funding Information System (NRFIS): A Comparative Study
DOI:
10.46729/ijstm.v7i1.1380Published:
2026-01-20Downloads
Abstract
Digital transformation in the public sector requires information systems that provide consistent and equitable services to diverse stakeholder groups. A National Research Funding Information System (NRFIS) has become a strategic digital platform for managing research funding processes end-to-end across government institutions, universities, and research organizations. While previous evaluations have examined such systems using structural models, limited attention has been given to differences in perceptions between internal stakeholders and external research stakeholders. This study compares user perceptions regarding System Quality (SY), Information Quality (IQ), Service Quality (SQ), Use (UE), User Satisfaction (US), and Net Benefits (NB) between internal and external users of NRFIS. A total of 335 respondents participated, comprising 290 external stakeholders and 45 internal stakeholders. Descriptive results show that internal users consistently reported higher perceptions across all constructs: SY (4.28 vs. 3.94), IQ (4.42 vs. 3.99), SQ (4.39 vs. 3.87), UE (4.42 vs. 3.97), US (4.47 vs. 3.98), and NB (4.56 vs. 3.95). Chi-Square tests confirm statistically significant differences across all constructs (p < 0.01). Mann–Whitney U tests further validate substantial median differences (all p < 0.001). These findings demonstrate robust perception gaps between user groups, highlighting the need for improved onboarding, training, and support mechanisms for external stakeholders. This study contributes to digital governance literature by revealing structural disparities in user experience and provides policy recommendations for enhancing inclusiveness and effectiveness of NRFIS-based research funding services.
References
[1] Almutairi, H., & Subramanian, G. H., An empirical application of the DeLone and McLean model in the Kuwaiti private sector, Journal of Computer Information Systems, vol. 45, no. 3, 2005, pp. 113–122.
[2] Davis, F. D., Perceived usefulness, perceived ease of use, and user acceptance of information technology, MIS Quarterly, vol. 13, no. 3, 1989, pp. 319–340.
[3] DeLone, W. H., & McLean, E. R., The DeLone and McLean model of information systems success: A ten-year update, Journal of Management Information Systems, vol. 19, no. 4, 2003, pp. 9–30. https://doi.org/10.1080/07421222.2003.11045748
[4] Ebrahim, Z., & Irani, Z., E-government adoption: Architecture and barriers, Business Process Management Journal, vol. 11, no. 5, 2005, pp. 589–611.
[5] Gable, G. G., Sedera, D., & Chan, T., Reconceptualizing information system success: The IS-Impact model, Journal of the Association for Information Systems, vol. 9, no. 7, 2008, pp. 377–408.
[6] Gil-Garcia, J. R., & Pardo, T. A., E-government success factors, Government Information Quarterly, vol. 22, no. 2, 2005, pp. 187–216.
[7] Gorla, N., Somers, T. M., & Wong, B., Organizational impact of system, information, and service quality, Journal of Strategic Information Systems, vol. 19, no. 3, 2010, pp. 207–228.
[8] Iivari, J., An empirical test of the DeLone–McLean model of IS success, The Database for Advances in Information Systems, vol. 36, no. 2, 2005, pp. 8–27.
[9] Ives, B., Olson, M. H., & Baroudi, J. J., Measurement of user information satisfaction, Communications of the ACM, vol. 26, no. 10, 1983, pp. 785–793.
[10] Landrum, H., Prybutok, V., Struke, D., & Zhang, X., Measuring IS system service quality, Informing Science, vol. 11, 2008, pp. 135–153.
[11] Mahmud, A., Prayogo, D., Susilowati, N., et al., System and information quality impact on net benefits, Management and Accounting Review, vol. 22, no. 1, 2023, pp. 106–127.
[12] Nelson, R. R., Todd, P. A., & Wixom, B. H., Antecedents of information and system quality, Journal of Management Information Systems, vol. 21, no. 4, 2005, pp. 199–235.
[13] Papadomichelaki, X., & Mentzas, G., e-GovQual: A multiple-item scale for e-government service quality, Government Information Quarterly, vol. 29, no. 1, 2012, pp. 98–109.
[14] Parasuraman, A., Zeithaml, V. A., & Berry, L. L., SERVQUAL: A multiple-item scale, Journal of Retailing, vol. 64, no. 1, 1988, pp. 12–40.
[15] Petter, S., DeLone, W., & McLean, E., Measuring IS success, European Journal of Information Systems, vol. 17, no. 3, 2008, pp. 236–263.
[16] Petter, S., DeLone, W. H., & McLean, E. R., Information systems success: The quest for the dependent variable, Journal of Management Information Systems, vol. 29, no. 4, 2013, pp. 7–62.
[17] Rahayu, D. N., & Setiyani, L., SLR and VOSViewer analysis of the D&M model, International Journal of Science, Technology & Management, vol. 3, no. 1, 2022.
[18] Rai, A., Lang, S. S., & Welker, R. B., Assessing the validity of IS success models, Information Systems Research, vol. 13, no. 1, 2002, pp. 50–69.
[19] Rana, N. P., Dwivedi, Y. K., Williams, M. D., & Weerakkody, V., Citizen adoption of e-government, Information Systems Frontiers, vol. 19, 2017, pp. 547–568.
[20] Shareef, M. A., Dwivedi, Y. K., Stamati, T., & Williams, M. D., E-government service quality: Conceptual framework, Government Information Quarterly, vol. 31, no. 2, 2014, pp. 149–161.
[21] United Nations Department of Economic and Social Affairs, E-Government Development Index (EGDI), United Nations, New York, 2024.
[22] Wang, R. Y., & Strong, D. M., Beyond accuracy: What data quality means to data consumers, Journal of Management Information Systems, vol. 12, no. 4, 1996, pp. 5–33.
[23] Wixom, B. H., & Todd, P. A., User satisfaction and technology acceptance, Information Systems Research, vol. 16, no. 1, 2005, pp. 85–102.
License
Copyright (c) 2026 International Journal of Science, Technology & Management
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Downloads
How to Cite
