Abstract

Construction project costs often reach values higher than planned. Accuracy in project cost estimation is one of the most important criteria for project success, even for its sustainability.The main idea of this research is to examine the relationship between realized cost and contracted cost values for residential buildings. The aim of the research is to determine the mathematical relationship between realized and planned costs in the project implementation phase by using a few mathematical methods and some machine learning methods in comparison to linear regression. This would enable validation of methods themselves by comparing and evaluating the obtained relevant parameters.Comparison would be performed on two levels, based on its general characteristics, as well as on the results of their application on the basis of 24 building reconstructions and new buildings by comparing the mean absolute percentage error (MAPE) and the determination coefficient (R2) using Predictive Modelling Software DTREG (pronounced D-T-Reg). The relationship of realized and planned costs will be determined for the building as a whole and for certain types of construction works. That relationship would enable more realistic budget planning of similar future projects. Cost overrun factors will be analysed for particular types of construction works, as well as the probability of their occurrence, and what measures should be undertaken to prevent or reduce them in similar future projects. The phenomenon known in project planning as "optimism bias" will be analysed in the context of research focus of exceeding the construction cost.

Abstract

A building construction project cannot be completed successfully by only planning and scheduling. Project controlling that consists of project monitoring and updating, is the other critical stage. Construction materials cost and quality are becoming a severe problem in Ethiopia, especially in Ambo Town, where little consideration is given. The study tried to evaluate different factors affecting the materials cost and quality on building construction site, rank significant factors that are prevalently affecting the cost and quality of materials used for building projects from the point of view of the respondents, and established a model to optimize materials cost and materials quality using multilinear regression method to come up with the model best fit. Purposive sampling was used, and 180 questionnaires were administered to building construction firms to analyze Material cost Optimization and quality control ImprovementCase Study of Ambo Town. To achieve this, a questionnaire survey containing factors affecting Building construction material cost and quality, which were identified by literature and Interview, was analyzed by using the Relative Importance Index, Pearson's correlation, and Multilinear regression model. Variables are statistically significant at 95% confidence level is assessed that all of the independent variables are positively related to Building Construction material cost and quality. The RII results showed that Material Wastage minimization (RII = 0.908), Proper workmanship (RII= 0.859), Sufficient Training of workers/staff (RII = 0.876), Proper forecasting of materials price in the market (RII = 0.850), Using suitable, safe and secure storage (RII = 0.886), Quality checking for each delivery of the aggregates to the site (RII = 0.889), Cutting of materials ( glass, tiles, plywood) (RII = 0.870) and Design changes (RII = 0.770) were ranked as the most significant among factors affecting building construction materials. Also, two Multiple linear regression models were established for both dependent variables (material cost and material quality). The analysis results showed all independent variables were significant and had a strong positive relationship with dependent variables. The values of R2 for the developed equations indicated 0.771 for material cost and 0.777 for material quality. Hence, the basic recommendations such as planning and monitoring construction activities and inspection and verification of materials were anticipated to be exercised by key role players of the construction industry.