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Al-Turfi, S (2017) Best practice project management for the sustainable regeneration of Holy Karbala Province in Iraq, Unpublished PhD Thesis, , University of Bolton.

Arewa, A O (2014) An empirical analysis of commitment to health and safety and its effect on the profitability of UK Construction SMEs, Unpublished PhD Thesis, School of Engineering, University of Bolton.

Babangida, I (2014) Hierarchical structuring and evaluation of risks, uncertainties and technical challenges faced by building refurbishment contractors, Unpublished PhD Thesis, School of Engineering, University of Bolton.

Emam, H (2021) Optimising project controls for construction using BIM and Big Data Analytics, Unpublished PhD Thesis, , University of Bolton.

  • Type: Thesis
  • Keywords: accessibility; accuracy; skills; building information modelling; feedback; investment; project success; scheduling; time overrun; construction project; integration; project control; interview
  • ISBN/ISSN:
  • URL: http://ubir.bolton.ac.uk/3659/
  • Abstract:
    Construction projects are the main contributors to economies and the wealth of nations. The industry is perceived to lead to developments and prosperity in countries. Projects in the construction industry often have high investment during the construction stage. Advancements in science and development of human needs lead to more complex designs in response to new demands by end-users. Sophisticated designs make projects more difficult to manage and consequently increased the rate of budget and time overruns. A plethora of studies has been conducted to investigate the causes of delays in construction projects. A considerable proportion of these studies have reported poor planning, scheduling, and controls as top contributors to delays. Previous literature exploring project success factors were focused primarily on the cost, time and quality. The rise of technology has led to an exponential increase in the amount of data produced by the industry due to using systems for digital engineering, finance, and scheduling or using new technology that collates data and stores them in a central repository. The increase of data opens the potential for new horizons to use this data for informed decision-making. However, data within the industry is fragmented, inconsistent, and hard to link due to different segmentation and structuring objectives for data creators' objectives. This research aim is to formulate optimised integrated project controls to improve the success of projects. The first objective was to explore the factors affecting the success of projects beyond the traditionally studied cost, time and quality. The association between the efficiency of project controls and the success of projects was the main focus of objective three. The third objective was to investigate the relationship between project controls' efficiency and its three pillars: people, processes, and technology. The research's final objective is to test the impact of new technologies as BIM and big data analytics on the efficiency of project controls. The research methodology followed in this study is a sequential mixed method. In the first phase, literature was reviewed and gaps in knowledge were identified to justify the research. Job advertisements of project controls roles were analysed to determine the skills and knowledge required. These analyses were followed by a quantitative questionnaire that was developed to measure and test the hypothesis. The questionnaire was piloted to 25 participants and feedback incorporated in the final version. The questionnaire was administered online, and 610 participants completed the survey. Responses were analysed using statistical tools to validate the hypotheses of the studies. The results of the analysis were used to inform the design of semi-structured interviews. The research was concluded by conducting four interviews to understand the trends revealed in the survey. The correlation between project controls efficiency and projects' success was a modest positive correlation of value 0.63. The third objective analysis found a high correlation of people, processes, and systems to project controls' efficiency to be 0.864, 0.860, and 0.804, respectively. The analysis and results showed a modest correlation between efficient project controls and project success of value 0.63. The third objective investigated the association of the three pillars of project controls. Results indicate high correlations between people, processes, and systems and efficiency of project controls with values of 0.864, 0.860, and 0.804, respectively. The interviews analysis led to an integrated controls system that uses building information modelling (BIM) to integrate data and store it in a central repository. This data was then used to apply analytics concepts for enhancing decision-making. The system implemented under this study demonstrated a proof of concept on big data analytics and BIM integrations and how it improves accessibility to data in models. This study used the findings to drive theoretical and practical implementation. BIM and data analytics were mentioned as drivers for the efficiency of project controls. A conceptual framework was developed to integrate project controls function with BIM models. The framework was implemented by integrating BIM into business intelligence as part of the data analytics. A classification model for BIM elements was developed with high accuracy. The model results showing a high level of accuracy was implemented as part of this study. The design of semi-structured interview questionnaire. The research was concluded by conducting four interviews to gain in-depth understanding of trends revealed in survey. The analysis and results showed a high level of correlation between efficient project controls and project success. The second objective investigated the importance of the three pillars of project controls, and results indicate importance between people, systems and processes and efficiency of project controls. The interviews analysis led to design of an integrated controls system that uses building information modelling (BIM) to integrate data and store it in a central repository. This data was then used to apply analytics concepts for enhancing decision-making. The system implemented under this study is a proof of concept on how big data analytics and BIM can help improve project delivery.

Evans, M (2022) Strategic frameworks for managing lean construction on megaprojects: towards global integrated delivery and corporate governance, Unpublished PhD Thesis, , University of Bolton.

Ibbotson, K (2020) Prioritising carbon reduction in UK public sector flood and coastal risk management, Unpublished PhD Thesis, , University of Bolton.

Kaggiah, G M B (2022) Strategies for improving the sustainability of SMEs in the construction industry in Malawi, Unpublished PhD Thesis, , University of Bolton.

Kaunda, R T (2020) Project Delivery Methods impact on efficient delivery of road construction projects in Malawi, Unpublished PhD Thesis, , University of Bolton.

Mulenga, C Z (2020) Construction project performance in Zambia: A case study of public high schools, Unpublished PhD Thesis, , University of Bolton.

Sherratt, F S (2012) Constructing safety on sites: an exploration of the social construction of safety on large UK construction sites, Unpublished PhD Thesis, Department of Civil Engineering, University of Bolton.