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Duffield, C F (2001) An evaluation framework for privately funded infrastructure projects in Australia, Unpublished PhD Thesis, , University of Melbourne.
Fayek, A (1996) A competitive estimating and tendering strategy model for use in the civil engineering construction industry, Unpublished PhD Thesis, , University of Melbourne.
Gurmu, A (2017) An investigation into construction management practices influencing labour productivity in multi-storey building projects, Unpublished PhD Thesis, , University of Melbourne.
- Type: Thesis
- Keywords: buildability; market; construction equipment; multi-storey; best practice; construction method; human resource management; materials management; productivity; project planning; site layout; Australia; sectoral comparison; interview
- ISBN/ISSN:
- URL: http://hdl.handle.net/11343/194881
- Abstract:
Productivity improvement in construction projects is essential for the economic growth of a country, for increasing the profit margin of contractors and for reducing the project delays and the related consequences such as liquidated damages. Previous studies indicate that management related problems are negatively influencing labour productivity in construction projects. However, understanding the management practices which are suitable for improving productivity in specific project type in a certain location, planning the appropriate practices, monitoring the implementation of the planned practices, and assessing whether the implemented practices are associated with high or low productivity can help to increase productivity. Previous studies identified the best practices for increasing productivity in infrastructure and industrial construction projects in North America. However, it is possible that none of these practices is suitable to enhance productivity in multi-storey building construction projects in Australia as the management practices and their effectiveness would depend on the context such as differences in the resources supply chain within the local market, local regulatory requirements and project types. Furthermore, there is little or no research conducted on what these practices might be and which of them are the most important in the context of multi-storey building projects in Victoria State, Australia. Also, no research has been conducted on how the management practices that could enhance productivity in multi-storey building projects are measured, planned, monitored and evaluated. Additionally, no tool has been developed to predict a productivity value or a probability of exceeding a certain productivity value when the levels of planning of the management practices are known. The purpose of this research is to identify the management practices that have the potential to improve productivity in multi-storey building construction projects, refine and validate scoring tools for measuring, planning, controlling and evaluating the practices in the context of building projects, and develop a tool for predicting the probability of exceeding a baseline productivity factor when the levels of planning of the management practices are determined. The research adopted a two-phase exploratory sequential mixed methods design. During Phase-I, in-depth interviews were conducted with 19 experts who have been involved in the delivery of multi-storey building projects. The qualitative data was analysed, construction management practices that have the potential to improve productivity were identified, and the unweighted scoring tools for the practices were prepared. In Phase-II, quantitative data was collected from 39 principal contractors on 39 projects using questionnaires. During stage I of the quantitative data analysis, the data collected from the 39 principal contractors’ experts regarding the relative importance of the practices in enhancing the productivity of multi-storey building projects were analysed to prioritise the practices identified in Phase I, and on that basis, the weighted scoring tools were prepared. During stage II of the quantitative data analysis, the data collected from the 39 multi-storey building projects were analysed to validate the scoring tools and to develop as well as validate the logistic regression model for predicting the probability of exceeding baseline productivity factor using a sigmoid graph when the scores of the practices are known. Overall, 47 construction management practices that have the potential to improve productivity in multi-storey building projects in the context of Victoria State, Australia have been identified and prioritised. The practices ‘well-defined scope of works,’ ‘safety and health policy,’ and ‘safety and health plan’ are found to be the three most important practices. The findings of the correlation analyses revealed that all the 47 construction management practices are positively associated with productivity. The output of linear regression analysis also indicated that there is a positive and statistically significant relationship between productivity and the management practices. The findings of Friedman test showed that the practices ‘well-defined scope of work,’ ‘safety and health policy,’ ‘safety and health plan,’ ‘hazard analysis,’ ‘long-lead materials identification,’ ‘safe work method statement’ and ‘toolbox safety meetings’ are equally important to improve productivity in multi-storey building projects. The study revealed that high levels of implementation of the construction management practices are associated with low levels of project delays. The use of practices also varied according to the project costs. Long-lead materials identification, procurement plans for materials, and materials delivery schedule are found to be the three most important construction materials management practices. Construction equipment maintenance, construction equipment procurement plan, and construction equipment productivity analysis are identified as the three construction equipment management practices. Traffic control plan, project start-up plan, machinery positioning strategy, project completion plan, and dynamic site layout plan are found to be the top five practices which are related to construction methods. Well-defined scope of work, short interval plan, buildability review, construction work packages, and regulatory requirement are found to be the five most important pre-construction phase management practices. Clear delegation of responsibility, stability of organizational structure, and crew composition are found to be the three most important human resource management practices. Finally, safety and health policy, safety and health plan, and hazard analysis are the three most important safety and health practices. The scoring tools which can be used to measure, plan, monitor and evaluate the management practices have been refined and validated. Thus, the scoring tools for construction materials management practices, construction equipment management practices, pre-construction phase management practices, management practices related to construction methods, human resource management practices, and safety and health practices are prepared and validated. The baseline scores against which the users of the scoring tools assess the adequacy of their practices have been determined and validated. The baseline scores can be used as benchmarks to evaluate if the planned or implemented management practices on a certain multi-storey building project would be associated with high or low productivity. Hence, the baseline scores for the overall management practices, construction materials management practices, construction equipment management practices, pre-construction phase management practices, management practices related to construction methods, human resource management practices, and safety and health practices are set. Logistic regression models that can be used for predicting the probability of exceeding baseline productivity factors are built and validated. The associated sigmoid graphs have been developed to determine the corresponding probabilities when the scores of the construction management practices are known. Thus, the logistic regression models for predicting the probability of exceeding baseline productivity factors based on the aggregated scores of the construction management practices as well as based on the scores of construction materials management practices, construction equipment management practices, preconstruction phase management practices, management practices related to construction methods, human resource management practices, and safety and health practices are built and validated. Additionally, linear regression models which are used to predict the productivity factors of multi-storey building projects based on the scores of the construction management practices are developed and validated. The study has practical implications. Contractors involved in the construction of multi-storey buildings in Victoria State, Australia can implement the identified practices to enhance productivity in their projects. They can also measure their management practices and evaluate whether their practices are adequate or not. Furthermore, the contractors can use the probability-based predictive model to assess the risk of low productivity for specific levels of implementations of the construction management practices. During the project planning phase, the management practices scoring tools can be used to plan appropriate practices which can be implemented to potentially increase productivity. Moreover, the productivity predicting tools can be used to estimate the productivity of a certain multi-storey building project based on the levels of planning of the management practices. By using the estimated productivity, the likelihood of occurrence of project delays can be predicted, and corrective actions can be taken prior to commencing the construction of the project. During the construction phase, the scoring tools can be used to control the implementation of the planned practices. Finally, during the project closure phase, the scoring tools can be used to evaluate whether the implemented practices are associated with the predicted productivity. If not, lessons can be learnt, and suitable practices can be planned for future projects. This research contributes to the body of knowledge in construction management by identifying and prioritising the management practices which are suitable to enhance labour productivity in multi-storey building construction projects. The findings of the study can facilitate international comparisons as well as sectoral comparison and provide useful information for future researchers and companies seeking construction works in Australia. This study also contributes to the growth accounting framework (neoclassical economic growth theory) by investigating the under-researched areas of the drivers of labour productivity. The technological advancement and capital deepening are the two main factors which were explained by the theory. However, the theory did not provide an in-depth explanation of the management practices. This research increases the understanding of the importance of the management practices for increasing labour productivity in the context of multi-storey building projects.
Horman, M J (2000) Process dynamics: Buffer management in building project operations, Unpublished PhD Thesis, , University of Melbourne.
Jennings, I C (1997) Systemic integration in construction project organisations, Unpublished PhD Thesis, , University of Melbourne.
Karunaratne, R (2022) Optimisation of prefabricated modular-integrated residential construction using hybrid customisation methods, Unpublished PhD Thesis, , University of Melbourne.
Kenley, R (1986) Construction project cash flow modelling, Unpublished PhD Thesis, Department of Architecture and Building (Now Faculty of Architecture, Building and Planning), University of Melbourne.
London, K (2004) Construction supply chain procurement modelling, Unpublished PhD Thesis, , University of Melbourne.
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Xu, M (2010) The value of critical project decisions: measurement and modelling, Unpublished PhD Thesis, , University of Melbourne.