## 6 Higher Education Student Enrollment Capacity Planning Methods & Techniques
### Methods Based on Decision Support Systems  
#### 6.2.1 Background and Literature  
Decision support systems (DSS) have been devised as a relatively new and innovative approach to goal programming for higher education institutions to plan financials, allocate resources, devise admission policy, manage enrollment and funds, plan budgets, and schedule classrooms. DSS employs complex systems and gigantic databases to achieve the above-mentioned goals. Therefore, researchers have made several attempts to develop DSS to cope with one or more of these goals. One of the areas of DSS which has received special attention from researchers is related to resource allocation in higher education institutions. In 1981, [PERSON] and [PERSON] et al. devised a DSS based on goal programming tested in a large higher education institution in the USA to support four decision-makers having varied problem-solving views to fulfill multiple conflicting objectives [29]. In 1991, [PERSON] devised a DSS to determine an optimal enrollment policy for a higher education institution in Kuwait. The proposed DSS consisted of an academic performance analysis module, demographic growth/regression analysis module, and student allocation module. This method had received positive feedback from the concerned decision-makers [30]. In 2005, [PERSON] and [PERSON] devised a university capacity planning (UNICAP) DSS for a German university to optimize enrollment capacity planning and decision making employing the simulation/evaluation of strategic plans. The DSS integrated data from varied sources, applied online analytical processing (OLAP) techniques and allowed the interaction of decision-makers to test various strategies and their implications [31]. Additionally, in 2007, [PERSON] and [PERSON] also presented an assessment methodology for educational capacity planning and resource utilization using a DSS with integrated input data sources and a graphical front-end for decision-makers for output presentation [32]. In 2010, [PERSON] and [PERSON] developed a decision support system to meet an academic program's supply and demand needs contributing directly to optimal resource management. A system dynamics model was devised to achieve the goals [33]. In 2013, [PERSON] devised an intelligent DSS for enrollment management in higher education institutions employing multi aggregator models and evolutionary computing such as fuzzy logic, genetic algorithms, neuro-networks, and probabilistic reasoning [34]. In 2015, [PERSON] and [PERSON] presented a conceptual model of the admission system to assess university admission capacity with different factors affecting students' performance [35]. [PERSON] and [PERSON] (2015), [PERSON] (2013), and [PERSON] and [PERSON] (2012) have all emphasized the importance of data mining and the potential advantages of using it in higher education, showing the need for more systematic decision-making support systems [35; 36; 37]. In 2017, [PERSON] and [PERSON] et al. devised a system dynamics approach to build simulation models that could be utilized to study the dynamic and dynamic interactions between student flows, infrastructure investments, and staff ratios in Syrian higher education institutions [38]. In 2018, [PERSON] and [PERSON] et al. devised a new method based on a hybrid strategic decision support system to solve the KSA student enrollment capacity planning problem. It used demographic data of KSA to present the experimental results [16]. In 2020, [PERSON] used statistical data analysis of a DSS on students' intake for university admission using Dagon University students' data for an effective decision-making process [39]. It could be observed from the previous literature that DSS is a strong approach advising the decision-making process, especially when making decisions in complex system situations with the existence of big databases. Student admission/enrollment capacity planning is regarded as a complex process in educational institutions.