A weighted graduate employability index for faculty-level benchmarking
DOI:
https://doi.org/10.55573/JISED.118783Keywords:
Graduate employability, composite index, faculty benchmarking, graduate outcomes, sensitivity analysisAbstract
Graduate employability involves multiple dimensions that cannot be represented adequately by employment status alone. This study develops a weighted Graduate Employability Index (GEI) for faculty-level benchmarking at Universiti Teknologi MARA (UiTM), Malaysia, using aggregated data from the 2025 Graduate Tracer Study. The source data represent responses from 56,895 graduates who graduated in 2025, which were subsequently aggregated into faculty-level values for institutional reporting. Thirteen institutional graduate employability indicators across 26 faculties were transformed onto a common 0–100 scale using min–max normalisation and aggregated using a predefined weighting scheme. The indicators were assigned weights of 5%, 7.5%, or 10% according to their relative contribution within the institutional benchmarking framework. Faculty GEI scores were ranked, with particular attention given to the Top 10 faculties. Sensitivity analysis was conducted as a robustness check by moderately redistributing the indicator weights while retaining the same 13 indicators. The resulting ranking showed very high agreement with the principal GEI ranking (Spearman's rho = 0.993), while the composition of the Top 10 group remained unchanged. These findings indicate that the principal faculty-level benchmarking result was stable under the tested weight variation. The proposed GEI provides a transparent and interpretable approach for integrating multiple graduate employability indicators into a single comparative measure for institutional benchmarking and performance monitoring.
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References
Akhtar, P., Moazzam, M., Ashraf, A., & Khan, M. N. (2024). The interdisciplinary curriculum alignment to enhance graduates' employability and universities' sustainability. The International Journal of Management Education, 22, 101037. https://doi.org/10.1016/j.ijme.2024.101037
Alam, M. J., Noman, S., Mujib, M. N. I., & Khan, W. S. (2025). An assessment of graduates skills gap for sustainable employability during the 4IR in Bangladesh. Social Sciences & Humanities Open, 12, 101780. https://doi.org/10.1016/j.ssaho.2025.101780
Alemu, M., & Yismaw, B. (2022). Understanding waiting time from graduation to first employment: Survival analysis-based evidence from Ethiopia. Education Research International, 2022, Article 9001679. https://doi.org/10.1155/2022/9001679
Basir, N. M., Wahab, D. A., Zubair, Y. Z., & Jani, R. (2023). Determinants of graduates' starting salary using CHAID analysis. Jurnal Ekonomi Malaysia, 57(2), 135–147. https://doi.org/10.17576/JEM-2023-5702-10
Basir, N. M., Zubairi, Y. Z., Jani, R., & Wahab, D. A. (2022). Soft skills and graduate employability: Evidence from Malaysian tracer study. Pertanika Journal of Social Sciences & Humanities, 30(4), 1975–1989.
Bol, T., Ciocca Eller, C., van de Werfhorst, H. G., & DiPrete, T. A. (2019). School-to-work linkages, educational mismatches, and labor market outcomes. American Sociological Review, 84(2), 275–307. https://doi.org/10.1177/0003122419836081
Brown, J. L., Hammer, S., Perera, H. N., & McIlveen, P. (2022). Relations between graduates' learning experiences and employment outcomes: A cautionary note for institutional performance indicators. International Journal for Educational and Vocational Guidance, 22, 137–156.
Dacre Pool, L., & Sewell, P. (2007). The key to employability: Developing a practical model of graduate employability. Education + Training, 49(4), 277–289. https://doi.org/10.1108/00400910710754435
De Montis, A., Serra, V., Calia, G., Trogu, D., & Ledda, A. (2021). To weight or not to weight, that is the question: The design of a composite indicator of landscape fragmentation. Applied Sciences, 11(7), 3208. https://doi.org/10.3390/app11073208
Gómez-Parra, M.-E., & Marín, F. J. (2026). Comparing student perspectives on employability through bilingual education. Discover Education, 5, 456. https://doi.org/10.1007/s44217-026-01518-6
Harvey, L. (2001). Defining and measuring employability. Quality in Higher Education, 7(2), 97–109. https://doi.org/10.1080/13538320120059990
Kelemen, A., Szabo, Z., Bozoki, S., Szadoczki, Z., & Hartvig, A. (2024). A sensitivity analysis of composite indicators: Min/max thresholds. Environmental and Sustainability Indicators, 23, 100453. https://doi.org/10.1016/j.indic.2024.100453
Latifis, K., Sidiropoulos, A., & Evangelidis, G. (2026). International university rankings: Composite indicators and methodological approaches. Frontiers in Research Metrics and Analytics, 11, 1828850. https://doi.org/10.3389/frma.2026.1828850
Ministry of Higher Education Malaysia. (2026). Graduate tracer study 2025 [Institutional dataset].
OECD & Joint Research Centre. (2008). Handbook on constructing composite indicators: Methodology and user guide. OECD Publishing. https://doi.org/10.1787/9789264043466-en
Pham, T., Soltani, B., & Singh, J. K. N. (2024). Employability capitals as essential resources for employment obtainment and career sustainability of international graduates. Journal of Further and Higher Education, 48(4), 436–448. https://doi.org/10.1080/0309877X.2024.2344771
Rakowska, A., & de Juana-Espinosa, S. (2021). Ready for the future? Employability skills and competencies in the twenty-first century: The view of international experts. Human Systems Management, 40(5), 669–684. https://doi.org/10.3233/HSM-201062
Roesch, M., Gerritse, M., & Karreman, B. (2026). Careers in multinational enterprises. Journal of International Economics, 161, 104236. https://doi.org/10.1016/j.jinteco.2026.104236
Saisana, M., Saltelli, A., & Tarantola, S. (2005). Uncertainty and sensitivity analysis techniques as tools for the quality assessment of composite indicators. Journal of the Royal Statistical Society: Series A, 168(2), 307–323. https://doi.org/10.1111/j.1467-985X.2005.00350.x
Spearman, C. (1904). The proof and measurement of association between two things. The American Journal of Psychology, 15(1), 72–101. https://doi.org/10.2307/1412159
Taherdoost, H., & Madanchian, M. (2024). The impact of survey response rates on research validity and reliability. In A. Rahal & M. Adorján (Eds.), Design and validation of research tools and methodologies (pp. 183–212). IGI Global. https://doi.org/10.4018/979-8-3693-1135-6.ch009
Tomlinson, M. (2017). Forms of graduate capital and their relationship to graduate employability. Education + Training, 59(4), 338–352. https://doi.org/10.1108/ET-05-2016-0090
Uddin, M., Bal, H., Hoque, N., & Mamun, A. (2026). Entrepreneurship education and graduate employability in emerging economies: A moderated–mediated model of employability orientation and career awareness. The International Journal of Management Education, 24, 101415. https://doi.org/10.1016/j.ijme.2026.101415
Ustaoglu, E., Ortega Lopez, G., & Gutierrez-Alcoba, A. (2023). Building composite indicators for the territorial quality of life assessment in European regions: Combining data reduction and alternative weighting techniques. Environment, Development and Sustainability.
Yorke, M. (2006). Employability in higher education: What it is—What it is not. Higher Education Academy.
