Development of a fuzzy integral group model based on linguistic reasoning for project manager selection

• Main Author: Afshari, Ali Reza
• Format: Thesis
• Language: English
• Published: 2012
• Online Access: http://psasir.upm.edu.my/id/eprint/43421/1/FK%202012%2030R.pdf; http://psasir.upm.edu.my/id/eprint/43421/
• Institution: Universiti Putra Malaysia

An important phase of human resource management is project manager selection, which is concerned with identifying an individual from a pool of candidates suitable for a vacant position. As in many decision problems, project manager selection problem is very complex in real life. Some of the techniques in decision making are multi criteria decision making (MCDM) can be used for project manager selection process. Although many studies have investigated this problem, there are three missing links in existing studies: Firstly, based on literature review, there is no systematic and valid method for specifying the jobs requirements criteria have been presented. Secondly, group decision making (GDM) is a very important factor for solving the problem comprehensively. However, it has not been considered in the majority of the reviewed studies. Thirdly, possible dependencies between the criteria in the project manager selection model have not been considered in the existing studies. The main objective of this research is to develop an analytical hybrid methodology for project manager selection problem in order to identify criteria for project manager selection by an extension of Delphi method, to evaluate a candidate by a new group multi criteria decision making (GMCDM) model based on fuzzy set theory, and develop a model based on linguistic extension of fuzzy measures and fuzzy integrals for ranking candidates. The methodology of this research includes four stages. The objective of the first stage is to eliciting criteria hierarchy for project manager selection. In this stage, after reviewing pertinent literature, the Delphi based method was used to seek the criteria from managers and experts. The objective of the second stage is project manager evaluation based on new group fuzzy linguistic modeling for determining criteria importance and candidate ratings. The objective of the third stage is fuzzy aggregating and the objective of fourth stage is ranking the candidates based on new linguistic fuzzy measure and fuzzy integral model. The models were validated using three case studies of project manager selection in three project based companies for a project manager position. The effectiveness of the three new methods was demonstrated in these three case studies. The results showed that the proposed models are appropriate for selecting project manager considering dependency between criteria. Firstly, this study developed a structured method for criteria selection. The use of a structured criteria selection method encourages experts to focus on explicit and functional criteria, rather than to use inappropriate criteria. As a contribution to the knowledge, this study extended the classical Delphi technique through using the results of relevant literature review and discussion with experts to identify the selection criteria. Secondly, this study developed a linguistic extension for evaluation. Decision makers cannot express judgment in accurate numerical terms and use of linguistic labels makes decision judgment more reliable and informative for decision making. Thirdly, this study developed non additive method for aggregating stage in project manager selection. In the real world, in dealing with the multiple criteria decision making problems, the criteria are not independent. So they cannot be evaluated by conventional additive measures and there must be better methods to distinguish the preferences by applying a new nonlinear and non additive model, in which it is not necessary to assume independence.