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Innovation has always been the engine of economic growth. Nowadays, billions are disbursed every year on research and universities are working increasingly closely with industries to help them developing new products and processes. This involvement of industries has set the level of expectations very high, whereby the above means that higher education institutes (HEIs) face a huge challenge. Thus, to maintain this important role and be more competitive, HEIs are trying to assure a high level of quality by following standards and guidelines as part of their academic tradition by using a sophisticated quality management system (QMS). This can help the coordination of activities in the organization to control and improve the efficiency and effectiveness of its performance (Petkovska & Gjorgjeska, 2013)
This paper introduces a new KPI-based decision evaluation system to enhance QMS for HEIs. In fact, decision support systems (DSSs) are sufficiently mature and very important for any organization regardless of their domain (education, automotive, finance, etc.) (Power, Sharda, & Burstein, 2015). Unfortunately, this concept is not well introduced in the field of education despite its proven results within other domains. And even when it is, it simply analyzes current and historical status and does not take advantage from past decisions and its impact on the institution.
The proposed approach differentiates between “first-level” knowledge and “advanced-level” knowledge. The “first-level” knowledge is widely used by traditional DSSs. It transforms data into knowledge and presents gathered knowledge to the end users, helping them in their decisions. It is essentially data manufactory with the purpose of helping users to obtain knowledge. This knowledge offered to end-users does not include information about the decision itself, namely the evaluation, responsibility (decision-maker), decision time and affected domain. The extended version of the “first-level” knowledge - “advanced” knowledge - includes the knowledge provided by the first level and extends it with the knowledge about the decision itself (Rezgui, 2014).
This article presents a reference architecture for the new approach called a KPI-based decision evaluation system and its integration in QMSs for HEIs. Accordingly, the remainder of this paper is organized as follows. After a brief introduction and presentation of the research methodology, section three provides the main background information about quality management systems (QMSs), decision support systems (DSSs) and their use in HEIs. In addition, we will discuss the decision-making process. In section four, the proposed KPI-based DES will be explained. Section five shows the reference architecture of the KPI-based DES with its characteristics and components. Subsequently, the steps followed to integrate DES in QMS for HEIs are detailed in section six. Section seven presents the main outcomes of the proposed solutions and shows how DES can enhance QMS for HEIs. The article then concludes with a brief summary regarding the contribution of this content.