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One of the significant higher education problems is resource allocation, once it involves contrasting decisions, it affects the performance of universities (Ho et al., 2006), and their ability to borrow funds has practical limits (Kleinmuntz, 2007). Universities of all dimensions, types, and objectives face this problem. At public universities, dealing with budgeting problems is even more difficult as they use funds from their taxpayers to provide educational services.
Governments, however, have cut funding for higher education because of public pressure in several countries, which has prompted many of them to look for ways to meet the needs of society without spending too much money on taxpayers (Ho et al., 2006; Liefner, 2003). Hence, universities must manage their processes optimally and maintain their performance in order to collect adequate funding to meet their necessary expenditures.
Higher education institutions’ goals are different and conflicting in many aspects, and they must improve the provision of beneficial results for the interests of society, given an extremely complex and competitive environment (Martins et al., 2019). Within this context, circumstantial evidence suggests that web-based Decision Support Systems (DSSs) combined with multiple criteria decision aiding/making (MCDA / M) methods is an appropriate way to assist decision-makers in solving resource allocation or budgeting problems (Ho et al., 2006; Montibeller et al., 2009; Mustafa & Goh, 1996; Power, 2016; Efrain Turban et al., 2011). They can improve decision quality, change the structure and functioning of organizations (Bhargava et al., 2007; Efrain Turban et al., 2011), they can represent all the objectives in a single decision problem (de Almeida et al., 2015), and this is the reason why we focus on these methods.
By definition, a Decision Support System is a computer-based information system that supports decision-makers to use data and models to solve semi-structured and unstructured problems (Sprague Jr. & Carlson, 1982). Also, DSSs help stakeholders assess and lead current situations for better decision-making (Edelhauser & Ionică, 2014). All kinds of DSS can be implemented using Web technologies and can become web-based DSS. Its application can increase access and use, reduce support and training costs, allows extensive capabilities to the users (Power, 2016), and that is the reason we consider its applicability for this research.
Furthermore, there is the concept of Multiple Criteria Decision Support Systems (MCDSSs), considered as a "specific" sort of system within the broad family of DSS (Korhonen et al., 1992). The aim is to provide support for structuring the problem, eliciting preferences, and analyzing the results so that the decision-makers (DMs) can focus on the core of the problem while the technical issues are taken care of by the computer (Mustajoki & Hämäläinen, 2007). The use of an effective web-based Decision Support System (DSS) to incorporate MCDA / M research into the decision-making process is, therefore, an essential tool for addressing the challenge of allocating resources in universities.
Besides, according to Ho, Dey & Higson (Ho et al., 2006), there are four major higher education decision problems: resource allocation, performance measurement, budgeting, and scheduling. Performance measurement is the most common decision problem studied (Carlucci et al., 2019; Ho et al., 2006; Mustafa & Goh, 1996). However, in most Higher Education institutions, funding is performance-related. Therefore, the quality of all universities is heavily dependent on how much funding they receive (Ho et al., 2006).
Moreover, most approaches related to resource allocation problems consider only one single objective, unlike MCDA / M methods, that can handle multiple conflicting objectives at the same time, and they coincide with real situations faced by the universities (Ho et al., 2006; Mustafa & Goh, 1996). Consequently, it is possible to go beyond in the decision sciences literature on how to apply these models in practice.