Predicting Accuracy of Early Cost Estimates Using Factor Analysis and Multivariate Regression

The importance of accurate estimates during the early stages of capital projects has been widely recognized for many years. Early project estimates represent a key ingredient in business unit decisions and often become the basis for a project’s ultimate funding. However, a stark contrast arises when comparing the importance of early estimates with the amount of information typically available during the preparation of an early estimate. Such limited scope definition often leads to questionable estimate accuracy. Even so, very few quantitative methods are available that enable estimators and business managers to objectively evaluate the accuracy of early estimates. The primary objective of this study was to establish such a model. To accomplish this objective, quantitative data were collected from completed construction projects in the process industry. Each of the respondents was asked to assign a one-to-five rating for each of 45 potential drivers of estimate accuracy for a given estimate. The data were analyzed using factor analysis and multivariate regression analysis. The factor analysis was used to group the 45 elements into 11 orthogonal factors. Multivariate regression analysis was performed on the 11 factors to determine a suitable model for predicting estimate accuracy. The resulting model, known as the estimate score procedure, allows the project team to score an estimate and then predict its accuracy based on the estimate score. In addition, a computer software tool, the Estimate Score Program, was developed to automate the estimate score procedure. The multivariate regression analysis identified 5 of the 11 factors that were significant at the α = 10% level. The five factors, in order of significance, were basic process design, team experience and cost information, time allowed to prepare the estimate, site requirements, and bidding and labor climate.     

Discriminant Analysis for Predicting Ranges of Cost Variance in International Construction Projects

Unanticipated market conditions as well as project-related risks can easily lead to cost overruns in international construction projects. For a contractor to be financially successful in international projects, a careful examination of the project is a prerequisite to understanding the cost variance characteristics. Based on the reasonably accurate characterization of the cost performance, the markup or contingency amount is determined to ensure both a decent level of profit and a good chance of winning the contract. This paper presents a classification model to categorize international construction projects, particularly faced by Korean contractors, into five cost-variation classes: extreme cost overrun, moderate cost overrun, neutral, moderate cost saving, and extreme cost saving. The model is able to characterize an international project for its cost performance prediction in comparison to the contractor’s initial cost estimate. A linear discriminant analysis is utilized to develop the predictive classification model with the support of the bootstrap method. Tests show that the proposed model is able to help cost estimators determine a proper level of cost contingency before bidding on an international project.     

Using Risk Analysis to Determine Construction Project Contingencies

A contingency allowance is an amount of money used to provide for uncertainties associated with a construction project. Traditionally, it is a percentage addition on top of the base estimate. Estimating using risk analysis (ERA) is a methodology that can be used to substantiate the contingency by identifying uncertainties and estimating their financial implications. A study of the effect of ERA was carried out to compare the variability and consistency of the contingency estimates between non-ERA and ERA projects. This paper presents results of a survey that compares a total of 287 non-ERA and 45 ERA projects. The results show a highly significant difference in variation and consistency between these groups. It indicates successful use of the ERA method for public works projects to reduce unnecessary and exaggerated allowance for risk. However, the contingency allowance for ERA projects was still considered high. Improvement and refinement of the ERA method as well as recommendations on capital budgeting policy are suggested.     

在Power builder环境下实现选矿厂微机核子秤系统的设计开发

介绍丁核子秤的基本工作原理和微机核子秤的硬件组成，介绍了在Windows2000操作系统下，用Power Builder实现系统的原理，提出了一种用微机核子秤计量选矿厂动态固体物料的方法，标定结果表明，微机核子秤的计量误差≤1％，并且用户可以方便的进行历史记录的联网查询打印，为选矿企业的办公自动化提供基础数据。     

Data Preprocessing–Based Parametric Cost Model for Building Projects: Case Studies of Korean Construction Projects

For construction to progress smoothly, effective cost estimation is vital, particularly in the conceptual and schematic design stages. In these early phases, despite the fact that initial estimates are highly sensitive to changes in project scope, owners require accurate forecasts which reflect their supplying information. Thus, cost estimators need reliable estimation strategies. In practice, parametric cost estimation, which utilizes historical cost data, is the most commonly used method in these initial phases. Therefore, compilation of historical data pertaining to appropriate cost variance governing parameters is a prime requirement. However, data mining (data preprocessing) for denoising internal errors or abnormal values must be performed before this compilation. To address this issue, this research proposes a statistical methodology for data preprocessing. Moreover, a statistically preprocessed data–based parametric (SPBP) cost model is developed based on multiple regression equations. Case studies of Korean construction projects verify that the model enhances cost estimate accuracy and reliability than conventional cost models.     

Budgeting Owner’s Construction Contingency

This paper attempts to find ways to reduce an owner’s construction contingency budget such that just enough contingency is allocated that will allow the owner to deal with uncertainties but at the same time not tie up valuable funds that can be used for other activities. It is suggested that the common practice of allocating a fixed owner contingency (e.g., 10% of the contract value) to all projects contracted out by an owner is not appropriate. Instead, a methodology is proposed whereby the owner (1) analyzes historical project data; (2) identifies the line items that are problematic; (3) takes the necessary measures at the preconstruction stage to streamline these line items with respect to site conditions, time constraints, constructability issues, and project scope; and (4) finally budgets contingency funds based on this information. A case study was conducted to analyze the contingencies budgeted and actually spent by an owner in nine parking lot projects. The findings indicated that a systematic approach such as the methodology proposed in this paper is likely to minimize the owner’s contingency budget.     

Methodology for Automating the Identification and Localization of Construction Components on Industrial Projects

Even though engineered components, such as pipe spools and structural steel elements, generally account for a significant percentage of the total installed cost of an industrial project, current industry practices still rely on human ability to track thousands of these components individually after they are received at the job site. These site-tracking practices are inefficient and error prone. This paper presents an approach for automating the identification and localization of construction components on large industrial projects. The proposed approach combines advanced sensing devices and localization mechanisms. The appropriate combination of global positioning system and radio-frequency identification (RFID) facilitates an infrastructure-free data collection process capable of detecting a large number of RFID-tagged components in short amounts of time. Based on the collected data, localization mechanisms precisely estimate the coordinates of the tagged components. Field experiments on real construction scenarios demonstrated the feasibility of the proposed methodology.     

Estimation of Cost Contingency for Air Force Construction Projects

Risk and associated cost overruns are critical problems for construction projects, yet the most common practice for dealing with them is the assignment of an arbitrary flat percentage of the construction budget as a contingency fund. Therefore, our goal was to identify significant variables that may influence, or serve as indicators of, potential cost overruns. We analyzed data from 203 Air Force construction projects over a full range of project types and scopes using multiple linear regression to develop a model to predict the amount of required contingency funds. The proposed model uses only data that would be available prior to the award of a construction contract. The variables in the model were categorized as project characteristics, design performance metrics, and contract award process influences. Based on the performance metric used, the model captures 44% of actual cost overruns versus the 20% captured by the current practice. Furthermore, application of the model reduces the average contingency budgeting error from 11.2 to only 0.3%.     

Residential Building Projects: Building Cost Indicators and Drivers

Time and costs are considered to be substantial success factors of building construction projects. In Germany, early cost estimates are provided by multiplying the cost indicator with the gross floor area. When preparing these estimates, the question arises as to which specific cost indicator has to be selected? The relevant cost drivers provide guidance for this selection. Drivers show which parameters are the determinants for the selection of the project-specific cost indicators. However, currently these drivers are not known for building construction projects in the German-speaking region. The relevant cost drivers for residential properties in Germany are identified by using regression analysis. These drivers are the median floor height, the share of the ancillary area for services, the construction duration, and the compactness of the building. Of the four cost drivers, the median floor height proved to have the greatest explanatory significance. The method proves to be suitable for answering the research question. However, some theoretically relevant drivers were not available for the properties being examined. Therefore, these drivers have to be followed up and examined during future studies. Detailed information should be included especially about materials, the planning and construction process, and specific data about various dimensions of the building.     

Quantiative Methodology for Determination of Cost Contingency in International Projects

This paper presents a quantitative methodology to determine financial impacts of the risk factors during the bidding stages of international construction projects. Project and country data of 26 construction projects from 21 countries were collected for evaluation of the international risk factors. The factors impacting cost contingency were identified using correlation and regression analysis techniques. The results indicated that four factors had major contributions for explaining the variations in the contingency levels. A regression model including the significant factors was developed to support bidding contingency decisions. The methodology presented provides a robust and practical statistical approach for determination of contingency by focusing on important risk factors. Details regarding model development and validation are presented along with a discussion on study limitations.     

新一代高效节能热轧带钢生产线--ESP 无头带钢生产线

介绍了ESP无头带钢生产线的生产规模及产品、工艺流程、主要设备组成及其在投资、生产、节能环保等方面的优势。 ESP无头带钢生产线能以低成本高效稳定生产极具附加值的薄规格产品，实现节能减排、提高板带的组织性能稳定性、均匀性、成材率及板厚板形精度、实现部分“以热代冷”，可以作为未来热轧带钢生产线的发展方向。     

Achieving Multiple Project Objectives through Contingency Management

Project managers use budgets to satisfy multiple objectives such as cost control, short durations, and high quality. Contingency funds are included in project budgets to manage risk and achieve project goals. Understanding how managers use budget contingencies requires a dynamic information processing model of how managers bridge the gap between high project complexity and limited managerial capacity. The results of collecting contingency management practices of real estate development project managers is reported and a dynamic simulation model of contingency management described. The model is used to test hypotheses of the effectiveness of aggressive and passive management strategies on cost, timeliness, and facility value. Managers were found to pursue general project objectives in their management of contingency. An aggressive strategy was found to be more robust but performed poorer than a passive strategy. Conclusions include the prevalence of trade-offs between robust and high-performance contingency management policies in construction projects and the importance of incorporating uncertainty into project planning and management.     

Military Facility Cost Estimation System Using Case-Based Reasoning in Korea

Numerous cost estimations are made repetitively in the initial stages of construction projects in response to ongoing scope changes and often need to be recalculated frequently. In practice, the square foot method, considered an effective method for time-saving, is widely used. However, this method requires a great amount of effort to calculate a unit price and does not consider the uniqueness of each case. Thus, the use of the square foot method could bring about unwanted consequences. For example, in the case of military projects in Korea, significant differences have been reported between estimations made using this method and the actual costs. In an effort to deal with this challenging issue, this research develops a military facility cost estimation (MilFaCE) system, based on case-based reasoning (CBR), using case data from 422 construction projects at 16 military facilities. Based on system validation experiments involving 10 military officers (engineers), the effectiveness of the system in terms of estimation accuracy and user-friendliness is confirmed. Consequently, this research can be a CBR application example of construction cost estimation and a basis for further research into the development of cost estimate systems.     

Relating Cost Growth from the Initial Estimate to Design Fee for Transportation Projects

Intuitively, there should be a relationship between the size of the design fee for a transportation project and the quality of the resulting design. This study sought that relationship by looking at the fee expressed as a percentage of the construction cost and the final construction cost growth from the engineer’s initial estimate of the construction cost at the time the design contract was awarded. The research team analyzed 31 projects from the Oklahoma Turnpike Authority with a total construction value of $90 million. The projects were divided into road and bridge projects. Based on the results of the analysis, it seems that as the design fee decreases, the absolute percentage of construction cost growth from the engineer’s early estimate increases. The relationship is strongest for bridge projects, which tend to be more technically complex to design than roadway projects. This confirms for U.S. projects the result of an earlier study in Saudi Arabia. This paper concludes that the design fee should be viewed as an investment at a point in time where the ability to impact the project is the highest and can accrue the benefit of reduced cost growth.     

One Company's Experience with Design∕Build: Labor Cost Risk and Profit Potential

This paper offers the data from one construction company's experiences with design∕build. Specifically, the paper presents an analysis of the company's labor cost risk based on a case study of two similar projects. One project was a typical design∕bid∕build job and the other was a design∕build job. The design∕build project experienced consistently greater fluctuations in the labor cost. These fluctuations seem to indicate that it is very difficult to accurately estimate labor costs for design∕build projects, thus adding to the risk of such projects. The second half of the paper presents an account of this same company's overall profit experience with design∕build work. Profit margins were analyzed using three categories—design∕build versus non-design∕build, client-specific design∕build, and design∕build construction types. The design∕build projects' average profit margin was 3.5 percentage points greater than that for the non-design∕build work.     

Long‐Range Forecasting Highway Construction Costs

In the process of decision making for design and execution of highway construction projects, long‐range cost forecasting is one of the most significant and complicated problems. This paper describes the development of a model that enables the user to make long‐range cost projections, taking into consideration general characteristics of the highway construction industry, as well as pertinent local conditions. The model presented uses conventional statistical methods to represent the main categories of typical jobs in the highway construction industry. From these categories, a composite model is created by assigning different weights to the input elements costs and then choosing a series of indicators to predict price trends for each separate element of the composite model. Use of this model reveals that bid volume in a certain area is a factor that has significant influence upon cost forecasts. This paper is accompanied by a case study based on actual data from highway construction projects performed for the Florida Department of Transportation in the years 1968–1981.     

Project Performance versus Use of Technologies at Project and Phase Levels

Lack of information regarding technology benefits along with uncertain competitive advantage from new technology have resulted in industry reluctance to implement new technologies. An industry-wide survey was used to collect project data from more than 200 capital facility projects on the issue of technology usage and overall project success. Twenty-two research hypotheses are presented and analyzed according to five different data class variables: industry sector, total installed cost, public versus private, greenfield versus expansion versus renovation, and typical versus advanced projects. Findings pertaining to associations between project success and technology usage at the project and phase level are discussed. The results of this research indicate that several technologies may contribute significantly to project performance in terms of cost and schedule success, particularly for certain types of projects. In addition, project schedule success is more closely associated with technology utilization than is project cost success. Findings from this study can provide companies with information on technology benefits and whether to use certain technologies.     

基于VR技术的非煤矿山火灾应急培训系统的开发

为了克服非煤矿山矿井火灾传统应急培训方式效果不佳和部分培训内容难以实现的问题,设计了包含项目基本介绍、事故场景体验、人员角色体验和综合考核评价4个子系统的矿井火灾应急培训系统功能框架。利用3Ds Max三维建模软件和Unity3D游戏引擎建立了矿井火灾虚拟场景,通过C#语言脚本编程和HTC VIVE头显设备实现学员与矿井火灾虚拟场景的交互,从而完成了系统的开发,并对系统进行了评估。评估结果表明,VR培训系统的用户体验指标一般是PPT培训的2~4倍,其中沉浸性是PPT培训的22.5倍,培训效果指标一般是PPT培训的1~2倍,说明基于VR技术的矿井火灾应急培训系统的用户体验和培训效果更好。     

NPV-at-Risk Method in Infrastructure Project Investment Evaluation

Strategic capital investment decisions are crucial to a business firm. The decision to invest in privately financed infrastructure projects requires careful consideration, because they are exposed to high levels of financial, political, and market risks. The project appraisal methods should incorporate analysis of these risks. A number of capital-investment decision methods can take risks into account, but each of them focuses on different factors and has its limitations. Thus, a more vigorous method is needed. A systematic classification of existing evaluation methods shows that it is possible to develop a new method—the net-present-value-at-risk (NPV-at-risk) method—by combining the weighted average cost of capital and dual risk-return methods. The evaluation of two hypothetical power projects shows that the NPV-at-risk method can provide a better decision for risk evaluation of, and investment in, privately financed infrastructure projects.     

Assessing the Accuracy of Cash Flow Models: The Significance of Payment Conditions

Cash flow forecasting methods have evolved to allow detailed predictions for individual projects. These methods, principally the cost-schedule integration (CSI) technique, make extensive use of project estimate and schedule data. An implicit assumption of these methods has been that accuracy is largely a function of the quality of data available to the model. To the writers’ knowledge, there has been no assessment of the ability of project specific cash-flow models to accurately predict cash flows given accurate input data. This paper makes two contributions. First, two complementary methods are presented—pattern matching logic and factorial analysis—that provide an ability to assess the accuracy of cash flow models. Second, through demonstration of these methods using data from two projects, a critique is made of the ability of existing CSI models to accurately predict cash flows. The paper concludes by recommending extensions of CSI models to include more detailed payment conditions, including differential payment lags, components for materials and labor, and payment frequency. A further conclusion is the call for more research to better understand the balance between managers’ need for information and the ability of predictive models to provide that information.