Abstracts – Browse Results
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Abuhussain, M (2020) An assessment of the Saudi Residential Buildings Envelope Code under the current and future climate change scenarios: the case for Jeddah in the hot and humid climate region, Unpublished PhD Thesis, , University of Liverpool.
Akade, S A (2017) Understanding the impact of culture on project execution in a developing country: an action research study of six international oil and gas companies in Nigeria, Unpublished PhD Thesis, School of Management, University of Liverpool.
Akinnola, P (2021) Improving project performance on construction projects through stakeholder management-an action research inquiry, Unpublished PhD Thesis, , University of Liverpool.
Aksenova, G (2020) The dark side of ecosystem orchestration: an empirical investigation of building information management in the digital built environment sector, Unpublished PhD Thesis, , University of Liverpool.
Al Hawsah, M O (2020) The impact of project sponsors' decisions on the success of projects: An action research study, Unpublished PhD Thesis, , University of Liverpool.
Al-Ashaikh, M H (1996) Project management in the public sector of Saudi Arabia, problems and solutions, Unpublished PhD Thesis, , University of Liverpool.
Al-Gathafi, M M (2005) Riskness of time and cost overruns and the effectiveness of risk response measure strategies in the Libyan construction industry, Unpublished PhD Thesis, Department of Architecture and Building Engineering, University of Liverpool.
Al-Hachami, Z (2020) Decision making in the oil and gas construction project management: structured VS discretionary, Unpublished PhD Thesis, , University of Liverpool.
Al-Omari, T (2004) Stochastic regression modelling of cost and duration overrun of construction projects implemented in Kuwait, Unpublished PhD Thesis, Department of Architecture and Building Engineering, University of Liverpool.
Alattyih, W (2015) Value creation and risk assessment for green building design in Saudi Arabia, Unpublished PhD Thesis, , University of Liverpool.
Aljarman, M (2016) Emerging risk from the application of building information modelling through the life cycle of projects, Unpublished PhD Thesis, Department of Architecture, University of Liverpool.
Alzaed, A (2012) User centered passive building design, Unpublished PhD Thesis, School of Architecture, University of Liverpool.
Alzahrani, A (2015) Uncovering the emerging risks from climate change scenarios and related climate change risk management in the building sector in the UK, Unpublished PhD Thesis, , University of Liverpool.
Alzahrani, S (2015) Dynamic simulation of the impact of risk events and risk cost in KSA PPP projects, Unpublished PhD Thesis, School of Engineering, University of Liverpool.
Bassanino, M N (1999) The perception of computer generated architectural images, Unpublished PhD Thesis, , The University of Liverpool (United Kingdom).
Binsarra, F A (2016) Uncovering the structure and the dynamic of information propagation in building, Unpublished PhD Thesis, School of Architecture, University of Liverpool.
Blyth, K A (2002) A computer model that forecasts the cash flow of building projects at the tender stage using stage payments, Unpublished PhD Thesis, School of Architecture and Building Engineering, University of Liverpool.
Elhag, T M S (2004) Tender price modelling: artificial neural networks and regression techniques, Unpublished PhD Thesis, School of Architecture & Building Engineering, University of Liverpool.
- Type: Thesis
- Keywords: artificial intelligence; cluster analysis; computing; construction cost; cost modelling; duration; interview; Monte Carlo simulation; neural network
- ISBN/ISSN:
- URL: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.400240
- Abstract:
Cost modelling in construction is the art and science of developing a reliable and effective estimation of the tender price of a project. Cost estimation is an experiencebased task, which involves evaluations of unknown circumstances and complex relationships of cost-influencing factors. Researchers argue that cost model developments lack rigour and consistent conceptual framework within which the performance of different models may be compared and evaluated. This study analyses construction cost models by classifying them into three groups according to the techniques used. These include deterministic models (regression analysis); probabilistic models (Monte Carlo simulation); and artificial intelligence models (neural networks). This research investigates the development of two methodologies for tender price estimation of buildings utilising neural computing and regression techniques. The emphasis is to provide clients and practitioners with a reliable tool, which would offer trustworthy advice and prediction of tender prices at an early stage of a construction project. The analysis in this research is based upon a data set of 230 office projects, newly constructed in the UK between 1983 and 1997. The cost data of these buildings consists of tender prices and 13 other cost influencing factors. The data extracted using the Building Cost Information Service (BCIS) database of the Royal Institution of Chartered Surveyors (RICS). Questionnaire survey and interviews were adopted to identify, evaluate and rank cost significant factors according to their degree of influence on tender prices. The practitioners involved in this stage were UK based quantity surveyors. Some of these cost variables formulate the basis for developing the tender estimation models. Cluster analysis was conducted to categorise the data set into more homogeneous project groups based upon the cost variables. The hypothesis is that developing estimation models using project categories would yield better performance and more efficient models. Self-Organising Maps (SOM), a type of neural networks, is used for the cluster analysis. Seventeen neural networks and thirteen regression models are developed for tender price estimation using different parameters and cost factors. The performance and efficiency of these models are analysed and compared before and after the cluster analysis of the data set. On the other hand, sensitivity analysis is conducted by developing fifty-five models to evaluate the effectiveness of different combinationso f network parameterso n the accuracyo f tenderp rice estimation. The research findings indicate that, when the whole data set of 230 office projects is used, both methodologies produced low accuracy and failed to map the relationship between the tender price and the selected influencing cost factors. On the contrary, after clustering the data set into coherent groups using Kohonen neural networks, the performance of both RA and ANN models increased dramatically, with many estimation accuracies above 80% and 90%, which is highly satisfactory for tender price estimation at an early stage of a project. The outcomes imply that: (a) clustering the projects into homogeneous categories is significant and key for model performance and accuracy; (b) after cluster analysis there is no significant difference in the performance of RA and ANN models, although the RA outperformed the ANN in some models. The results also reveal that for both methodologies the accuracy of the estimation models that utilised two cost factors (project area and duration) outperformed the estimation models that used 13 cost factors, which is an indication that area and duration are the most dominant cost determinant variables.
Evans, R C (2002) Dynamic cash flow forecasting model for construction contractors, Unpublished PhD Thesis, Department of Architecture and Building Engineering, University of Liverpool.
Feldbauer, R R (2019) Mindful project management: a framework to enhance underperformance managing large hospital builds by incorporating principles adapted from High Reliability Organizations, Unpublished PhD Thesis, School of Management, University of Liverpool.
Gee, S (2019) The development of an innovative, lean, mobile factory system to manufacture timber frame closed panels in temporary locations for use in the Assembly of Houses in the Affordable Rented Sector, Unpublished PhD Thesis, School of Architecture, University of Liverpool.
Gholami, E (2017) Exploiting BIM in energy efficient domestic retrofit: evaluation of benefits and barriers, Unpublished PhD Thesis, Department of Architecture, University of Liverpool.
Gkeredakis, E (2009) Explaining the distinctiveness of coordination through an in-depth study of a major construction project, Unpublished PhD Thesis, Management School, University of Liverpool.
Hepworth, A (2021) Decision-making in immature projects organisational environment: A mental model approach that influences conscientious critical thinking, Unpublished PhD Thesis, , University of Liverpool.
Ibrahim, A M (2019) A method to support leadership effectiveness in a construction project organisation in Nigeria, Unpublished PhD Thesis, School of Management, University of Liverpool.
Jervis, E (2015) Lowering CO2 emissions: a framework for overcoming institutional pressures and diffusing low carbon strategy throughout the construction supply chain, Unpublished PhD Thesis, School of Management, University of Liverpool.
Khodadadyan, A (2021) Living and future tools for risk assessment: an examination of the possibilities for fusion, Unpublished PhD Thesis, , University of Liverpool.
Kirkham, R J (2002) A stochastic whole life cycle cost model for a national health service acute care hospital building, Unpublished PhD Thesis, , University of Liverpool.
Kori, S i (2017) BIM business value creation for SME architectural firms in Nigeria using intellectual capital development, Unpublished PhD Thesis, School of Architecture, University of Liverpool.
Makwiranzou, C (2019) Building trust and managing risk between the client, consultant, and contractor in traditional and relational construction projects, Unpublished PhD Thesis, School of Management, University of Liverpool.
Morton, R R (1982) The speculative housebuilding industry in the nineteen seventies, Unpublished PhD Thesis, School of Architecture, University of Liverpool.
Munir, M (2020) Development of a building information modelling asset value realisation model, Unpublished PhD Thesis, School of Architecture, University of Liverpool.
Nizam Shaikh, R (2019) BIM-based investigation of total energy consumption in delivering buildings as a product, Unpublished PhD Thesis, , University of Liverpool.
Raimi, T (2017) Achieving customer satisfaction in a private housing organisation in Nigeria, Unpublished PhD Thesis, , University of Liverpool.
Salih, A (2020) Project management information system introduction: Challenges and remedies in a construction context, Unpublished PhD Thesis, , University of Liverpool.
Savva, C (2023) Lessons that can be learnt using action research strategies within TfL, Unpublished PhD Thesis, , The University of Liverpool (United Kingdom).
Sujan, S F (2020) A holistic and systemic model of collaboration in the AED industry, Unpublished PhD Thesis, , University of Liverpool.
Sutton, R M (2019) The development of a sustainable construction design process, Unpublished PhD Thesis, School of Engineering, University of Liverpool.
Tomlinson, J (1998) A premises occupancy cost forecasting model, Unpublished PhD Thesis, , The University of Liverpool.
Wanous, M (2000) A neurofuzzy expert system for competitive tendering in civil engineering, Unpublished PhD Thesis, Department of Architecture and Building Engineering, University of Liverpool.
Wellings, F (2005) The rise of the national housebuilder: A history of British housebuilders through the twentieth century, Unpublished PhD Thesis, , University of Liverpool.
Xi, J (2013) Evaluating the functional performance of small-scale public demountable buildings, Unpublished PhD Thesis, , University of Liverpool.
Zou, Y (2017) Building information modelling and knowledge-based risk management system, Unpublished PhD Thesis, School of Engineering, University of Liverpool.