Strategies for effective value management practice in construction industry
Value Management (VM) enhances project life cycle value through its application in both design and construction phases. VM is slowly being accepted by several governmental agencies, which is in contrast to the private industry’s procurement of construction services where VM is less received. This di...
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| Format: | Thesis |
| Language: | eng eng |
| Published: |
2017
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| Online Access: | https://etd.uum.edu.my/7830/1/Depositpermission_s94701.pdf https://etd.uum.edu.my/7830/2/s94701_01.pdf |
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| Summary: | Value Management (VM) enhances project life cycle value through its application in both design and construction phases. VM is slowly being accepted by several governmental agencies, which is in contrast to the private industry’s procurement of construction services where VM is less received. This dissertation explores the development of VM methodology through the joint use of a finite element software (Etabs) and genetic algorithm (GA) optimisation design to minimise the cost value of buildings by optimising structural elements. The objectives were to develop a new optimisation algorithm and apply the results to control construction project costs. The investigated VM methods involved conducting building value analysis in the design stage. To demonstrate the validity and efficiency of the proposed optimisation algorithm, various case studies were conducted in Malaysia. The results indicated that the proposed VM algorithm could improve building outcomes and support owners’ control of project investment actively at the design stage, and improve the utilisation of funds more effectively. Additional techniques were also employed, namely a questionnaire survey (quantitative) and a series of interviews (qualitative). The survey included a demographic section regarding the respondent characteristics, and the VM section that asks about the application of VM at the respondent’s workplace. Meanwhile, in depth interviews were conducted using an interview protocol on 25 respondents regarding details of VM applications amongst construction project teams. The quantitative data were subjected to descriptive statistical method analysis using statistical software, while the qualitative data were subjected to pattern matching methods, and cross-case and constant comparative data analysis. The outcomes of this research offer alternative perspectives for clients and construction professionals to have a better and deeper understanding about the constraints and strategies that exist to assist in the successful implementation of VM. |
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