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The pre-tender estimation process is still a hazy and inaccurate process, despite it has been practiced over decades, especially in Malaysia. The methods evolved over time largely depend on the amount of information available at the time of estimation. More often than not, the estimate produced during the pre-tender stage is far more than the tender cost of the project and sometimes, it is perilously underestimated and caused major problems to the client in the monetary planning. The purpose of this paper is to determine the most influential factors on the deviation of pre-tender cost estimation in Malaysia by conducting a survey.

Fuzzy logic, combined with artificial neural network method (fuzzy neural network) was then used to develop an estimating model to aid the pre-tender estimation process.

The results showed that the model is able to shift the cost estimation toward accuracy. This model can be used to improve the pre-tender estimation accuracy, enabling the client to take the necessary early measures in preparing the funding for a building project in Malaysia.

To the authors’ knowledge, this is the first study on tender price estimation standardization for a construction project in Malaysia. In addition, the authors have used factors from literature for the model, which shows the thoroughness of the developed model. Thus, the findings and the model developed in this study should be able to assist contractors in coming out with a more accurate tender price estimation.

Most of the previous studies conducted on the subject of subcontractors often focussed on a single phase of subcontracting practice; either on registration, selection of subcontractors or on monitoring of subcontractors without much integration to other different phases involved. Thus, on the basis of that reason, the purpose of this paper is to link the gap between different phases of subcontracting practice. This study also attempts to explore the relationships between the key criteria used by general contractors in selecting subcontractors before job awarding (CSSC) and the key criteria used for monitoring subcontractors during construction work (CMSC); which will then include an investigation of the effects these criteria have on project performance (PP).

The data obtained from a total of 162 G7 contractors in Malaysia were analysed. The interrelationships between the criteria and the effects of these criteria on PP were investigated simultaneously by employing a single model based on structural equation modelling (SEM) method.

The final model has discovered four major criteria that are often considered during the selection of subcontractors namely, “communication”, “relationship”, “general obligation” and “resource management” of a subcontractor. Meanwhile, the major criteria that are referred to in the monitoring of subcontractors are “workmanship”, “awareness of environment, health and safety” and “communication and relationship”. The four CSSC were found to be interrelated among themselves and affected CMSC during the construction stage. The research also revealed that the criteria used in monitoring subcontractor do affect the performance of a project. Thus, based on the result of this investigation, the monitoring of subcontractor is essential in discerning the performance level of a project.

An established SEM improves a subcontracting practice by creating platforms for CSSC, CMSC and PP to influence each other. With the gap between selection and monitoring subcontractors are filled, then the prediction of the subcontractors’ performance can be made possible.