Abstract
Nowadays, regardless of the popularity and credibility of Decision Support Systems (DSS), measuring the efficacy of the decisions taken by the DSS is yet to be proven. As previous works identifies the complexities involved in measuring the efficiency of DSS, most of the time DSS efficiency is case dependent. The list of methods for collecting and analyzing data, building models, deployment models, data and model integration, and finally taking decisions are some of the major issues related to measuring DSS effectiveness. This paper focuses on measuring the effectiveness of DSS. The paper highlights the issues that still need to be addressed with efficient frameworks. Based on the literature review and discussion presented in Section I and II, this study proposed a framework and its implementation. Presents how the proposed model can improve the previous work. The major findings of this study reflect that every decision made by DSS is based on the collected data, analyzed by DSS tools, as well as depends on the developed models. Therefore, this study illustrated that each component of DSS plays vital role in measuring the effectiveness of DSS whatever the case and problem for which the DSS has been built and implemented for. In addition, the supporting methods and measuring factors for each component are other findings of this study. Any decision taken by DSS will be evaluated separately in order to measure the effectiveness of the system. The proposed framework resembles a new framework for the decision makers working in any industry.
Highlights
A decision support system (DSS) is a kind of information system that is developed to help organizations in storing, managing, analyzing and supporting managers in decision making process [1]
In the late 1960s, an updated version of information system proposed based on model-oriented was known as decision support system in order to support organizational decision making process [1]
Given that DSS consists of four major components; namely, user interface, data, model, and knowledge base [15], this research proposes a framework that is component dependent for measuring the effectiveness of DSS by considering the importance of each DSS component to measure their impacts on decisions, and overcoming the associated complexities of decision optimization
Summary
A decision support system (DSS) is a kind of information system that is developed to help organizations in storing, managing, analyzing and supporting managers in decision making process [1]. Given that DSS consists of four major components; namely, user interface, data, model, and knowledge base [15], this research proposes a framework that is component dependent for measuring the effectiveness of DSS by considering the importance of each DSS component to measure their impacts on decisions, and overcoming the associated complexities of decision optimization. The explanation regarding the list of alternatives and decision-making criteria given by [13], suggests that DSS effectiveness can be measured based on different types of decision They purposed that building DSS is based on data analysis and reports generated by a DSS with the help of model based and knowledge base. The above literatures highlight the major components of DSS (i.e. data, model, knowledge, user interface) can be considered as a part of a framework for measuring the effectiveness of decision support system. An efficient and automated building of knowledge base, where different kinds of techniques can apply such as; data mining, classification of data, rules building, and prediction tools
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