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Fusion of Fuzzy Multi-Criteria Decision Making Approaches for Discriminating Risk with Relate to Software Project Performance: A Prospective Cohort Study

Fusion of Fuzzy Multi-Criteria Decision Making Approaches for Discriminating Risk with Relate to Software Project Performance: A Prospective Cohort Study
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Author(s): Arun Kumar Sangaiah (VIT University, India)and Vipul Jain (Victoria University of Wellington, New Zealand)
Copyright: 2017
Pages: 27
Source title: Handbook of Research on Fuzzy and Rough Set Theory in Organizational Decision Making
Source Author(s)/Editor(s): Arun Kumar Sangaiah (VIT University, India), Xiao-Zhi Gao (University of Eastern Finland, Finland)and Ajith Abraham (Machine Intelligence Research Labs, USA)
DOI: 10.4018/978-1-5225-1008-6.ch003

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Abstract

The prediction and estimation software risks ahead have been key predictor for evaluating project performance. Discriminating risk is vital in software project management phase, where risk and performance has been closely inter-related to each other. This chapter aims at hybridization of fuzzy multi-criteria decision making approaches for building an assessment framework that can be used to evaluate risk in the context of software project performance in following dimensions: 1) user, 2) requirements, 3) project complexity, 4) planning and control, 5) team, and 6) organizational environment. For measuring the risk for effectiveness of project performance, we have integrated Fuzzy Multi-Criteria Decision Making (FMCDM) and Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) approaches. Moreover the fusion of FMCDM and TOPSIS has not been adequately investigated in the exiting studies.

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