Ali Mohammed, Alashwal (2012) Developing a project learning model considering fragmentation in construction / Ali Mohammed Alashwal. PhD thesis, University of Malaya.
Abstract
Learning in construction has received growing attention due to such benefits as enhancing performance, reducing the repetition of mistakes, and achieving competitive advantages. However, most studies in the field have focused on organizational level of learning, paying less attention to project level and ignoring the influence of project characteristics on learning process. Therefore, the purpose of the current study is to develop a project learning model that considers fragmentation as a distinguishing character of projects. Fragmentation is defined in the current study as a multi-dimensional (hierarchical) concept indicated by level of integration, collaboration, coordination, barriers, decoupling of specializations, and spanning knowledge across boundaries. Project learning involves two dimensions, intra-project and inter-project learning, which are also identified as multi-dimensional latent constructs. The current study proposes a theoretical model that assumes a negative effect of fragmentation on project learning. However, to what extent fragmentation impacts learning and how learning can be achieved within a fragmented context remain unclear. To fill these gaps, a mixed methodology of qualitative and quantitative studies was adopted. The purpose of the qualitative study was to explore factors that enable learning within fragmentation. It involved in-depth interviews with 11 professionals in construction projects. The purpose of the quantitative study was threefold: to test the theoretical model; to develop the measurement scales of fragmentation, project learning, and enablers; and to validate the results of the qualitative study. Using a questionnaire survey, the data were collected from 36 big building projects (Grade 7) in Kuala Lumpur and Selangor, Malaysia. The study targeted professionals working in these projects and collected 203 valid questionnaires. Data analysis has involved parallel analysis, principal component analysis (PCA), and confirmatory factor analysis (CFA) to develop and validate second-order (hierarchical) measurement models of fragmentation and project learning. The relationships among fragmentation, project learning, and enablers were tested using partial least squares-path iv modeling (PLS-PM), a variance-based approach to structural equation modeling (SEM). The full model, comprises measurement and structural models, was analyzed using SmartPLS software. Model’s quality, reliability, and validity were attained. The results affirmed a negative significant influence of fragmentation on both intra- and inter-project learning. Further analysis indicated a partial mediating effect of the enablers of project learning. The results are expected to contribute to the body of knowledge in three main areas. Firstly, the hierarchical measurement scales of fragmentation and project learning can be used by future studies. Secondly, the enablers provide an explanation of how learning occurs within fragmentation. This implies greater focus on these factors to attain learning in construction projects. Lastly, the full model of project learning is sensible and appropriate for construction projects as it reflects their unique nature. However, further studies are recommended to generalize the model.
Actions (For repository staff only : Login required)
![[img]](http://studentsrepo.um.edu.my/style/images/fileicons/application_pdf.png)
