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|dc.contributor.advisor||Chang Wook Kang||-|
|dc.description.abstract||The advancements in the field of project management have driven researchers to take heed of numerous issues related with evaluating and managing complexity in projects, which demonstrates the evident significance of the subject. Among several key factors, organisational factors make up a large portion of project complexity as previous research confirms. While several project complexity measures do exist, every measure has its limit and evaluates project complexity from its own criteria. Furthermore, existing literature lacks modelling of these organisational factors to explore the interrelationships between them. One of the aims of this study is to identify and model these factors to assist project managers in handling organisational factors of project complexity in a more regulated fashion. The study emphasises on the concept of complexity in the sense that it is a risk which is, most of the time, unable to measure and no such assessment is carried out. Project complexity is an intangible as well as a subjective matter which is mostly overlooked in projects. The relevant literature speaks about the immense importance of the factors of organisational complexity. Hence the proposed methodology intends to transform this subjective and neglected issue into a more objective and noticeable one. The study focuses on quantifying complexity, induced by the organisational factors, and developing such a measure to aid the decision-making process. The proposed methodology is termed as HYBRID, referring to the two employed techniques, and developed in two stages. The interrelationships between the constructs of organisational complexity are modelled using Structural Equation Modelling (SEM) technique. A survey was carried out and the model was validated using 150 valid questionnaires received from project management professionals working in four different geographical locations. Findings of the modelling include the noticeable effect of project size on project complexity as well as other factors. Positive effects of project variety and the interdependencies on project complexity are also observed. Since the objective was to create a measure of complexity, Project Complexity Rank (PCR) is finally proposed in the second stage to assist decision makers in evaluating complexity for smooth execution of projects. The technique employed is Analytic Hierarchy Process (AHP). For a relatively robust judgment, this work takes into the uncertainty or vagueness that interrupts the process of decision making by integrating AHP with Fuzzy theory, i.e. using Fuzzy AHP (FAHP). A solid foundation has to be laid for decision-making so that the level of incorrectness can be maintained at minimum. Therefore, the outcome of SEM, variables in final model and their structural coefficients and factor loadings, is used as an input to FAHP for developing PCR. Final outcome is the rank of project being assessed based on complexity. The proposed methodology was implemented in an educational institute where five ongoing projects were evaluated. Initial judgment of Project Director, Project Manager and project team on the ongoing projects, based on the criteria and sub-criteria obtained from SEM results, was solicited. Using PCR the projects’ ranks were obtained. They planned to use PCR to convince higher management for bringing in necessary changes in the organisational structure so that the risk of complexity in projects could be tackled wisely.||-|
|dc.title||Hybrid Methodology to Assess the Risk of Project Complexity||-|
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