A framework for managing uncertainty in information system project selection: an intelligent fuzzy approach

Abstract

ABSTRACTInformation System Project (ISP) Selection is the most significant strategic consideration to each management of organizations, in terms of business intelligence (BI) as critical factors must be considered from large volume of information, known as Big Data (BD). In today’s competitive environment, the main objective is selecting suitable and effective ISP to reduce the risk of investment, maximize overall performance of management of organization by mitigating uncertainty. As these types of decisions generally involve several criteria and it is often necessary to compromise among possibly conflicting factors, the multiple criteria decision making (MCDM) becomes a useful approach to solve this kind of problem. This paper establishes a novel intelligent model by integrating fuzzy Shannon entropy and Fuzzy Technique for Order Preference by Similarity to Ideal Solution Method (FTOPSIS) techniques as a decision tool for solving MCDM problem using linguistic values, which smoothly aids decision makers dealing with uncertain or incomplete information without losing existing quantitative information. The novelty of this paper is to propose a framework of BI in management of an organization to determine suitable ISP where all the meaningful information, relevant knowledge and visualization retrieved by analyzing BD based on decision making to enhance any organizational performance worldwide.