Examining the Role of Industry Partnerships, Competencies, and Career Services in Shaping Graduate Employability and Employer Satisfaction
Main Article Content
Abstract
Aim/Purpose: This study examined the roles of curriculum relevance, work-based education, industry partnerships, career services, skills, and digital competencies in shaping graduate employability outcomes and employer satisfaction within the Thai higher education context. Drawing on employer perspectives and institutional practices, the study explored how higher education institutions can better prepare graduates for evolving labor market demands. It examined the extent to which these institutional factors contribute to workplace readiness, career success, and employer perceptions of graduate performance. By integrating evidence from international literature and the Thai context, the study provides a comprehensive framework for understanding the drivers of employability and offers insights for strengthening workforce development and sustainable economic competitiveness.
Methodology: In this study, a quantitative cross-sectional research design was employed. Data were collected through a structured questionnaire administered to 200 employers and industry supervisors with direct experience hiring, supervising, or evaluating graduates. Participants were selected using purposive and snowball sampling to ensure relevant expertise, followed by snowball sampling to broaden industry representation. The survey instrument was adapted from established employability and work-based education frameworks and measured seven constructs using a five-point Likert scale. Before full deployment, the instrument was pilot tested with 50 employers to assess clarity, reliability, and content validity. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to evaluate the measurement and structural models. Reliability and validity were assessed using Cronbach’s alpha, composite reliability, factor loadings, average variance extracted, and discriminant validity measures, ensuring the robustness of the findings.
Findings: The findings demonstrated that graduate employability outcomes were the central determinant of employer satisfaction, exerting a strong positive effect (ß = .672, p < .001) and explaining 45.1% of the variance, indicating that employers prioritized graduates’ work readiness, performance capability, and practical competencies over institutional reputation. Among institutional factors, career services (ß = .281, p = .017) and graduate skills and competencies (ß = .269, p = .008) were the strongest predictors of employability outcomes, underscoring the critical role of structured career guidance, employability coaching, and competency-based skill development in facilitating effective school-to-work transitions. Industry partnerships (ß = .256, p = .001) and work-based education (ß = .113, p = .013) also significantly enhanced employability by aligning graduate capabilities with labor market needs through employer engagement, internships, cooperative education, and applied learning opportunities. In contrast, curriculum design showed no significant direct effect on employability outcomes (ß = .040, p = .662), suggesting that formal curricula alone are insufficient without experiential learning and career support mechanisms. Overall, the model demonstrated strong reliability, validity, and explanatory power, explaining 74.6% of the variance in employability outcomes and confirming the robustness of the selected institutional determinants.
Contribution/Impact on Society: This study contributes to the graduate employability literature by examining relationships among industry partnerships, skills and competencies, work-based education, career services, employability outcomes, and employer satisfaction within the Thai higher education context. The findings indicate that career services, skills and competencies, industry partnerships, and work-based education are positively associated with employability outcomes, while curriculum design does not demonstrate a significant direct effect. The study also found that employability outcomes were positively associated with employer satisfaction. These findings provide empirical evidence that may inform higher education institutions and policymakers in designing strategies to strengthen the alignment between educational provision and labor market expectations.
Recommendations: To enhance graduate employability and employer satisfaction, higher education institutions should strengthen industry partnerships through expanded internships, cooperative education, and employer-led projects to better align with labor market needs. Institutions should also enhance both technical and transversal skills development, including digital literacy, critical thinking, communication, and adaptability through competency-based curricula. Work-based education should be systematically embedded into academic programs to provide sustained experiential learning and industry exposure. In addition, career services should be modernized through digital platforms, AI-enabled tools, and personalized mentoring to support career planning and job placement. Finally, structured mechanisms for employer feedback should be integrated into curriculum design and quality assurance processes to ensure continuous improvement and labor market responsiveness. Collectively, these strategies require coordinated action among universities, employers, and policymakers to strengthen the education-to-employment pathway.
Research Limitation: This study was limited by its focus on a restricted number of higher education institutions and industries in Thailand, which may constrain the generalizability of findings. The reliance on self-reported employer data may have introduced common method, social desirability, or perceptual biases. In addition, the study examined a defined set of institutional factors, while excluding broader contextual influences such as organizational culture, governance structures, labor market conditions, and policy environments. Finally, the cross-sectional design limited its ability to capture changes in employability outcomes over time.
Future Research: Future studies should employ longitudinal or mixed method approaches to capture changes in employability outcomes and employer satisfaction over time. Expanding the scope to include multiple institutions, industries, and contextual variables such as organizational culture and national policy frameworks would further enhance understanding.
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Copyright: Asia-Pacific International University reserve exclusive rights to publish, reproduce and distribute the manuscript and all contents therein.
References
Andrews, J., & Higson, H. (2008). Graduate employability: “Soft skills” versus “hard” business knowledge—A European study. Higher Education in Europe, 33(4), 411–422. https://doi.org/10.1080/03797720802522627
Bari, L. (2025). Connecting academia and industry: Change management in curriculum co-design. Industry and Higher Education, 39(4), 395–407. https://doi.org/10.1177/09504222251354894
Basilaia, G., & Kvavadze, D. (2020). Transition to online education in schools during a SARS-CoV-2 coronavirus (COVID-19) pandemic in Georgia. Pedagogical Research, 5(4), em0060. https://doi.org/10.29333/pr/7937
Becker, G. S. (1964). Human capital: A theoretical and empirical analysis, with special reference to education. Columbia University Press.
Billett, S. (2011). Curriculum and pedagogic bases for effectively integrating practice-based experiences. Australian Learning and Teaching Council. https://catalogue.nla.gov.au/catalog/5154788
Bridgstock, R. (2009). The graduate attributes we’ve overlooked: Enhancing graduate employability through career management skills. Higher Education Research & Development, 28(1), 31–44. https://doi.org/10.1080/07294360802444347
CEDEFOP. (2021). Bridging innovation and learning in TVET. https://www.cedefop.europa.eu/en/publications-and-resources/publications/4196
Chin, W. W., Marcolin, B. L., & Newsted, P. R. (2003). A partial least squares latent variable modeling approach for measuring interaction effects: Results from a Monte Carlo simulation study and an electronic-mail emotion/adoption study. Information Systems Research, 14(2), 189–217. https://doi.org/10.1287/isre.14.2.189.16018
Cooper, L., Orrell, J., & Bowden, M. (2010). Work integrated learning: A guide to effective practice. Routledge. https://doi.org/10.4324/9780203854501
Ferns, S. J., Zegwaard, K. E., Pretti, T. J., & Rowe, A. D. (2025). Defining and designing work-integrated learning curriculum. Higher Education Research & Development, 44(2), 371–385. https://doi.org/10.1080/07294360.2024.2399072
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104
García-Aracil, A., & Van der Velden, R. (2008). Competencies for young European higher education graduates: Labor market mismatches and their payoffs. Higher Education, 55(2), 219–239. https://doi.org/10.1007/s10734-006-9050-4
Gefen, D., Straub, D., & Boudreau, M.-C. (2000). Structural equation modeling and regression: Guidelines for research practice. Communications of the Association for Information Systems, 4, Article 7. https://doi.org/10.17705/1CAIS.00407
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (PLS-SEM) (2nd ed.). Sage.
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2022). A primer on partial least squares structural equation modeling (PLS-SEM) (3rd ed.). Sage.
Henseler, J., Dijkstra, T. K., Sarstedt, M., Ringle, C. M., Diamantopoulos, A., Straub, D. W., Ketchen, D. J., Hair, J. F., Hult, G. T. M., & Calantone, R. J. (2014). Common beliefs and reality about PLS: Comments on Rönkkö & Evermann (2013). Organizational Research Methods, 17(2), 182–209. https://doi.org/10.1177/1094428114526928
Jackson, D. (2015). Employability skill development in work integrated learning: Barriers and best practice. Studies in Higher Education, 40(2), 350–367. https://doi.org/10.1080/03075079.2013.842221
Jackson, D., & Bridgstock, R. (2021). What actually works to enhance graduate employability? The relative value of curricular, co-curricular, and extra-curricular learning and paid work. Higher Education, 81(4), 723–739. https://doi.org/10.1007/s10734-020-00570-x
Jackson, D., & Wilton, N. (2016). Developing career management competencies among undergraduates and the role of work-integrated learning. Teaching in Higher Education, 21(3), 266–286. https://doi.org/10.1080/13562517.2015.1136281
Kuo, Y.-C., Walker, A. E., Schroder, K. E. E., & Belland, B. R. (2014). Interaction, Internet self-efficacy, and self-regulated learning as predictors of student satisfaction in online education courses. The Internet and Higher Education, 20, 35–50. https://doi.org/10.1016/j.iheduc.2013.10.001
Mason, G., Williams, G., & Cranmer, S. (2009). Employability skills initiatives in higher education: What effects do they have on graduate labour market outcomes? Education Economics, 17(1), 1–30. https://doi.org/10.1080/09645290802028315
Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). McGraw-Hill.
OECD. (2020). Career ready? How schools can better prepare young people for working life in the era of COVID-19 (OECD Education
Working Papers No. 241). https://doi.org/10.1787/e1503534-en
OECD. (2023). OECD skills strategy Southeast Asia: Skills for a post-COVID recovery and growth. https://doi.org/10.1787/923bfd03-en
OECD. (2025). Education at a glance 2025: OECD indicators. https://doi.org/10.1787/1c0d9c79-en
Patacsil, F. F., & Tablatin, M. J. (2017). Exploring the importance of soft and hard skills as perceived by IT internship students and industry: A gap analysis. International Journal of Higher Education, 6(3), 1–11. https://doi.org/10.3926/jotse.271
Qenani, E., MacDougall, N., & Sexton, C. (2014). An empirical study of self-perceived employability: Improving the prospects for student employment success in an uncertain environment. Active Learning in Higher Education, 15(3), 199–213. https://doi.org/10.1177/1469787414544875
QS Quacquarelli Symonds. (2024). Quantifying the skills gap. https://www.qs.com/insights/quantifying-the-skills-gap
Raelin, J. A. (1997). A model of work-based learning. Organization Science, 8(6), 563–578. https://doi.org/10.1287/orsc.8.6.563
Savickas, M. L. (2005). The theory and practice of career construction. In S. D. Brown and R. W. Lent (Eds.), Career development and counseling: Putting theory and research to work (pp. 42–70). John Wiley & Sons.
Savickas, M. L. (2013). Career construction theory and practice. In S. D. Brown & R. W. Lent (Eds.), Career development and counseling (2nd ed., pp. 147–183). John Wiley & Sons.
Smith, C., Ferns, S., & Russell, L. (2014). The impact of work integrated learning on student work-readiness. Australian Government Office for Learning and Teaching. https://espace.curtin.edu.au/handle/20.500.11937/55398
UNESCO. (2020). Education for sustainable development: A roadmap. https://unesdoc.unesco.org/ark:/48223/pf0000374802
Van Laar, E., Van Deursen, A. J. A. M., Van Dijk, J. A. G. M., & De Haan, J. (2017). The relation between 21st-century skills and digital skills: A systematic literature review. Computers in Human Behavior, 72, 577–588. https://doi.org/10.1016/j.chb.2017.03.010
Watts, A. G., Bezanson, L., & McCarthy, J. (2014). The international symposia on career development and public policy: Retrospect and prospect. Australian Journal of Career Development, 23(3), 108–118. https://doi.org/10.1177/1038416214543390
World Bank Group. (2021). Learning and skills for a changing world. https://www.worldbank.org/ext/en/topic/education/skills-and-workforce-development
World Economic Forum. (2023, April 30). The future of jobs report 2023. https://www.weforum.org/publications/the-future-of-jobs-report-2023/
Yorke, M. (2006). Employability in higher education: What it is – what it is not. The Higher Education Academy. https://www.heacademy.ac.uk/knowledge-hub/employability-higher-education-what-it-what-it-not
