Goal Programming and Mathematical Modelling for Developing a Capacity Planning Decision Support System-Based Framework in Higher Education Institutions

• Published in: Applied sciences 2022-02, Vol.12 (3), p.1702
• Main Authors: Makki, Anas A., Sindi, Hatem F., Brdesee, Hani, Alsaggaf, Wafaa, Al-Hayani, Abdulmonem, Al-Youbi, Abdulrahman O.
• Format: Article
• Language: English
• Subjects: admission; capacity planning; Case studies; Decision support systems; DSS; Economic growth; Education; enrollment; Enrollments; Expenditures; Financial planning; Goal programming; Government spending; Higher education; Higher education institutions; Infrastructure; Institutions; Instructional aids; KAU; Mathematical models; Planning; Student retention
• ISSN: 2076-3417; 2076-3417
• DOI: 10.3390/app12031702

Achieving the Saudi Kingdom’s vision 2030 in the higher education sector requires higher education institutions to make a significant simultaneous change in their current practices. This encompasses the transitioning of government-funded educational institutions to be financially independent. Therefore, a prompt, agile transition is required while maintaining a positive socioeconomic impact, entrepreneurship and innovation, and high-quality education. This necessitates the transition to lean processes and the review of current practices. One of the most vital processes in educational institutions is student admission/enrollment capacity planning. This study puts forward a capacity planning decision support system (DSS)-based framework for university student enrollment. The framework was applied to the case of KAU, where current practice and challenges are presented, and from which data were collected. A top-down/bottom-up approach was followed and applied using the goal programming technique and a developed mathematical model, respectively. Results show that the proposed framework effectively affects student admission/enrollment capacity planning on strategic and operational levels. Moreover, it can be used in other planning aspects of higher education in universities, such as human resources planning, teaching load planning, faculty-to-student ratios, accreditation, quality requirements, lab capacity planning, equipment/teaching aids procurement, and financial planning, to mention a few. The implications of this study include assisting decision-makers in higher education institutions in matching their admission/enrollment capacity of student numbers between the macro-strategic and the micro-operational level.