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• e expected cost of any construction project. The accuracy of such estimate has a serious effect on the expected profit of the construction contractor. Hence, a certain contingency premium should be added to the base estimate to increase the level of confidence. Such premium is materially affected by many factors. Through this research, the main factors that are expected to affect the accuracy of the building construction project’s cost estimate were clearly identified. Twelve factors are identified as the most important factors. These factors were: economic instability, quality of firm’s project planning and management, relevant experience of estimating team, availability of management and finance plans, ability of estimating team, labor and equipment required, estimating method, project location, periodical payments, accuracy of bidding documents provided by client, competent and leadership of project manager and impact of project schedule (expected delay).

  Pertinent cost data of a selected sample of construction projects are investigated to show the effect of these factors on the construction project cost variance. Finally, a Neural Network model was developed that can greatly help to assess the expected cost variance of any future construction project. Cost variance is considered as an indicator for the accuracy of the cost estimating process. The validity of the proposed model is tested to confirm that the model could assess the expected cost variance at a satisfactory level of accuracy.

   

   

   

   

  CHAPTER ONE

  INTRODUCTION

   

  1.1 Overview

  Many factors affect the accuracy of building construction projects’ cost estimating which should be considered in the early stage of the estimating process. Some factors can incorrectly increase the estimated costs and the possibility of contractual disputes between the various parties involved. Other factors can help the estimator to decrease the unnecessary cost of an item and hence lead to successful tendering in a very competitive market.

  Therefore, accurate estimating requires detailed study of the biding documents and the environmental situation. It also involves a careful analysis of all projects’ data in order to arrive to the most accurate estimate of the probable cost consistent with the bidding time available and the accuracy and completeness of the information submitted.

  1.2 Problem Statement

  The impact of inaccurate cost estimating on construction business is

  significant. Overestimated cost result in submitting a high tender price by the contractor, which could lead to the tender being unacceptable to client. On the other hand, an underestimated cost may lead to a situation where a contractor incurs losses on the contracts awarded by clients. Contractor needs to identify these factors and assign cost variance related it.

  This study is an attempt to identify the main factors affecting the accuracy of cost estimate in building construction. Such factors that the estimator should consider when preparing a cost estimating. Then, developing a model that assesses related cost variance so that it will lead to:

  • Minimize cost variance that is an indicator of accuracy of cost estimating.
  • Avoid the contractor’s submission of an overestimated bid.
  • Enhance the effectiveness of the cost control process.

  1.3 Scope and Objectives

  Many factors affect accuracy of construction projects cost estimating. Through this study, factors affecting building construction projects cost estimating are discussed. Design-bid-build projects (DBB), either executed by governmental or private companies and selected in an open tendering are selected for the scope of this study.

  The main objectives of this study are:

  • Identifying factors affecting the accuracy of the building construction projects cost estimating process.
  • Determining and testing the severity of factors that affect the accuracy of the building construction projects’ cost estimating using analysis of data collected from questionnaire form.
  • Measuring the effects of the factors that severely affect the accuracy of the cost estimates and trying to link them.
  • Developing a model that can be used to assess the expected cost variance. Identifying such variance can help in accurately determining the risk premium that should be added to the estimated cost.

  1.4 Research Methodology

  This study is conducted in the following sequence:

  • A literature review carried out to investigate the previous works in this research area.
  • Identification of factors affecting the accuracy of cost estimating process based on the previous literature review.
  • A questionnaire survey carried out to identify the most important cost estimating factors in the Egyptian construction market.
  • Pertinent data of a selected sample of building construction projects collected. The analysis of such data will help to show how the previously identified cost estimating factors can affect the accuracy of the cost estimating process. Cost variance is an indicator for the accuracy of the cost estimating process.
  • Developing a neural network model using BrainMaker professional for windows version 3.7. The model is used as a tool to assess the expected cost variance of any future building project. The model training steps are shown in detail along with the required inputs and outputs.

  Eventually, the validity of the proposed model is evaluated to find out the ability of the proposed model to predict the expected cost contingency.

  • Finally, based on this analysis, some recommendations are provided to improve the accuracy of the cost estimating process.

  1.5 Thesis Organization

  This section describes the phases of this research classified by chapter as follows. Chapter one presents thesis introduction. Chapter two is a literature review for the main factors affecting accuracy of building construction projects’ cost estimating based on the previous studies. Chapter three presents the data collection process. Chapter four provides analysis of the collected projects’ data along with their effect on cost estimating accuracy. Chapter five clarifies methodology of the proposed neural networks model development. Such model can be used for assessing the average variance between the estimated cost and actual cost. Finally, Chapter six presents summary, conclusions and recommendations of this research.

CHALLENGES CONSTRUCTION ESTIMATORS ENCOUNTER WHEN ESTIMATING CONSTRUCTION PROJECTS