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Construction and evaluation of pairwise comparison matrices for a decision situation follows problem decomposition into a hierarchy. The general structure of a decision matrix is given in Figure 2.
Figure 2: General structure of a decision matrix
In one of the leading studies by the inventor of the AHP methodology, Thomas Saaty, it is argued that mathematical modelling in decision-making provides the perfect interface between human social traits and computational science (Saaty 2001). This is consistent with the current global trend where science is at the centre of efforts to make the globe computationally legible.
In the Kenyan context, Parastatals are legally anchored in the State Corporations Act, Chapter 446 (Riany 2021). They are organised into eight functional categories: financial, manufacturing, regulatory, public universities, training and research, service, regional development authorities, and tertiary education (Kepha et al. 2023; Government of Kenya 2023). Their primary purpose is to deliver government services to the citizens.
In their role, Parastatals acquire operational resources by following laid-down rules and guidelines. This framework has a significant influence on performance (Ongeti and Machuki 2018). Currently, metrics are used to measure the performance of Parastatals. However, these metrics largely use absolute rather than relative measurement for each variable under consideration. The main challenge with this approach is that it is difficult to properly rank performance and identify areas of improvement, especially in a highly interdependent decision situation (Saaty, 2008b). Absolute measurement in ICT selection and prioritisation problems, which is strongly connected to the performance of
Parastatals, may be incomplete. Ideally, decision variables leading to their acquisition should be weighted, and the best alternative chosen. Arguably then, the performance of the Kenyan Parastatals would to some degree be dependent on their effective utilisation of modern tools to support decision-making. Globally, the new decision- making paradigm calls for inclusivity, transparency, room for interrogation, and further process improvement. To this end, MCDM has been widely adopted by researchers and industry practitioners as a mathematically sound and reliable approach to selection based on systematic evaluation of alternatives. The application of this technique has continued to permeate disciplines from medicine to engineering to ISandT (Konomura et al., 2023; Daimi and Rebai, 2023; Kirmizi and Kocaoglu, 2020), and in energy projects and validation assignments (Godfrey et al., 2022; Raza et al., 2023), and in the prioritisation of government services (Saadi et al. 2017).
The literature provides overwhelming evidence of increased use of MCDM, especially the AHP method, in modelling selection and prioritisation problems across public service functions (Konomura et al. 2023; Veisi et al. 2022; Canco et al. 2021). However, no evidence suggests that Kenyan Parastatals have adopted any or a combination of MCDM techniques.
In a recent study, the AHP method was used in GIS software selection for science and engineering students (Kostić-
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