Information and Communication Technology for Development for Africa. First International Conference, ICT4DA 2017, Bahir Dar, Ethiopia, September 25–27, 2017, Proceedings

Research Article

Towards Group Fuzzy Analytical Hierarchy Process

Download
131 downloads
  • @INPROCEEDINGS{10.1007/978-3-319-95153-9_27,
        author={George Musumba and Ruth Wario},
        title={Towards Group Fuzzy Analytical Hierarchy Process},
        proceedings={Information and Communication Technology for Development for Africa. First International Conference, ICT4DA 2017, Bahir Dar, Ethiopia, September 25--27, 2017, Proceedings},
        proceedings_a={ICT4DA},
        year={2018},
        month={7},
        keywords={Multi criteria decision making Group Fuzzy Analytical Hierarchy Process Partners evaluation and selection problem},
        doi={10.1007/978-3-319-95153-9_27}
    }
    
  • George Musumba
    Ruth Wario
    Year: 2018
    Towards Group Fuzzy Analytical Hierarchy Process
    ICT4DA
    Springer
    DOI: 10.1007/978-3-319-95153-9_27
George Musumba1,*, Ruth Wario2,*
  • 1: Dedan Kimathi University of Technology
  • 2: University of Free State
*Contact email: george.musumba@dkut.ac.ke, wariord@ufs.ac.za

Abstract

Group decision making takes place in almost all domains. In building construction domain, a team of contractors with disparate specializations collaborate. Little research has been done to propose group decision making technique for this domain. As such, specific teams’ competitiveness enhancements are minimal as it takes more time for individual evaluators to choose the right partners. Qualitative and quantitative methods were used. Themes and categorizations were based on deductive approach. Subsequently, Group Fuzzy Analytical Hierarchy Process (GFAHP), Multi-Criteria Decision Making (MCDM) algorithm, was designed and applied. It uses all evaluation criteria unlike Fuzzy AHP (FAHP) which excludes some criteria that are assigned zero weights. GFAHP reduces the number of pairwise comparisons required when a large number of attributes are to be compared. Validation of the technique carried out by five case studies, show that GFAHP is approximately 98.7% accurate in the selection of partners.