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.     

Causes of Bad Profit in Overseas Construction Projects

International construction projects do not necessarily produce a high level of profit, as opposed to what is generally expected of high-risk international attempts. Overseas construction projects tend to have various risk factors that can diminish project profitability. This paper provides a comprehensive hierarchical framework to investigate the cause-and-effect relationships of various profit-influencing factors for international construction projects. After long-term profitability trends are analyzed based on a total of 3,487 international projects performed by Korean global contractors during the last 4 decades, case surveys of 126 overseas projects are conducted to draw the criticalities of each factor and to develop a hierarchical framework. An in-depth comparative case study of 20 additional international projects is also performed to verify the applicability of the hierarchical framework. Finally, we present significant distinctions between successful and failed projects from the comparative case study.     

Contractor’s Risk Attitudes in the Selection of International Construction Projects

International construction involves all of the uncertainties common to domestic construction projects as well as risks specific to international transactions. Consequently, despite the worldwide trend toward globalization, a very small portion of contractors actively seek international contracts due to concerns of probable failures. This paper describes findings from experiments done to investigate the risk attitude and bid decision behavior in the selection of international projects. The participants demonstrated either weak risk seeking in profit situations or strong risk seeking toward loss situations when choosing between conflicting options of risky opportunities and sure payoffs. On the other hand, another experimental test attempting to investigate bid behavior when making a realistic bid or no-bid decision in a complicated international construction project reveals the prevailing risk aversion. Further, this paper finds the experimental supports for some of the errors and biases due to risk attitude that commonly exist in bid decisions in this area. Finally, we present lessons learned and guidelines to make a qualified bid decision through feedback with the participants.     

Time-Profit Trade-Off Analysis for Construction Projects

This paper presents a multiobjective optimization model that provides new and unique capabilities including generating and evaluating optimal/near-optimal construction resource utilization and scheduling plans that simultaneously minimize the time and maximize the profit of construction projects. The computations in the present model are organized in three major modules: (1) a scheduling module that develops practical schedules for construction projects; (2) a profit module that computes the project profit; and (3) a multiobjective module that searches for and identifies optimal/near optimal trade-offs between project time and profit. A large-scale construction project is analyzed to illustrate the use of the model and to demonstrate its capabilities in generating and visualizing optimal trade-offs between construction time and profit.     

ICRAM-1: Model for International Construction Risk Assessment

This paper presents a risk assessment model for international construction projects. The International Construction Risk Assessment Model (ICRAM-1) assists the user in evaluating the potential risk involved in expanding operations in an international market by analyzing risk at the macro (or country environment), market, and project levels. The paper discusses some of the existing models for country risk assessment, presents potential risk indicators at the macro, market, and project levels, and explains the ICRAM-1 methodology through an applied example. The ICRAM-1 provides a structured approach for evaluating the risk indicators involved in an international construction operation and is designed to examine a specific project in a foreign country. It can be used as a tool to quantify the risk involved in an international construction investment as one of the preliminary steps in project evaluation. Four main results are obtained from the ICRAM-1 analysis: (1) High-risk indicators; (2) impact of country environment on a specific project; (3) impact of market environment on a specific project; and (4) overall project risk.     

Risk Assessment Model of Tendering for Chinese Building Projects

This paper presents a risk assessment model for tendering of Chinese building projects on the basis of identification and evaluation of the major risk events in the Chinese construction market, investigations and interviews from which the factors inducing the risk events were determined, questionnaires on building projects within China’s borders, and the logistic regression method. The findings show that, to a certain extent, the risk of tendering for projects and the risk of a contracted project can be assessed through analysis of factors such as owner type, source of project financing, existence or lack of past cooperation between contractors and owners, the intensity of competition for tendering, the reasonableness of the bid price, and the degree of support from the contracting company to its projects. The model can serve as a supplementary tool for Chinese contractors in making decisions for project tendering within Chinese borders. At the same time, it is of reference significance for international contractors, enabling them to further understand the risks in the contract market for Chinese building projects.     

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.     

Neural Network Model to Support International Market Entry Decisions

Bidding for international construction projects is a critical decision for companies that aim to position themselves in the global construction market. Determination of attractive projects and markets where the competitive advantage of a company is high requires extensive environmental scanning, forecasting, and learning from the experience of competitors in international markets. In this paper, a neuronet model has been developed as a decision support tool that can classify international projects with respect to attractiveness and competitiveness based on the experiences of Turkish contractors in overseas markets. The model can be used to guide decision makers on which type of data should be collected during international business development and further help them to prepare priority lists during strategic planning. Information derived from the model demonstrates that the most important factors that increase attractiveness of an international project are availability of funds, market volume, economic prosperity, contract type, and country risk rating. Similarly, level of competition, attitude of host government, existence of strict quality requirements, country risk rating, and cultural/religious similarities are the most important factors that affect competitiveness of Turkish contractors in international markets.     

Analytical Framework for the Choice of Dispute Resolution Methods in International Construction Projects Based on Risk Factors

International construction projects provide opportunities for developing countries to advance in the global economy and for international construction and design firms to increase their profit and market share. Despite the attractive opportunities that international construction offers, international contractors are faced with many challenges and difficulties when moving into international markets. Many risks are associated with international construction, whether external or project-specific risks. Those risks affect how contract clauses are written, including the dispute resolution clause. This paper discusses the different dispute resolution methods employed in international construction contracts and develops an analytical framework (DRM-Risk matrix) suggesting the use of specific dispute resolution methods depending on the risks expected in the project. The matrix may eventually help international contractors in the selection of the appropriate dispute resolution method during contract formation depending on the risks involved in a project.     

Ontology for Relating Risk and Vulnerability to Cost Overrun in International Projects

Risk management is about identifying risks, assessing their impacts, and developing mitigation strategies to ensure project success. The difference between the expected and actual project outcomes is usually attributed to risk events and how they are managed throughout the project. Although there are several reference frameworks that explain how risks can be managed in construction projects, a major bottleneck is the lack of a common vocabulary for risk-related concepts. Poor definition of risk and patterns of risk propagation in a project decrease the reliability of risk models that are constructed to simulate project outcomes under different risk occurrence scenarios. This study aims to extend previous studies in risk management by presenting an ontology for relating risk-related concepts to cost overrun. The major idea is that cost overrun depends on causal relations between various risk sources (namely, risk paths) and sources of vulnerability that interfere with these paths. Ontology is used to develop a database system that represents risk event histories of international construction projects and to construct a model for estimation of cost overrun. It will form the basis of a multiagent system that can be used to simulate the negotiation process among project participants about sharing of costs considering the risk allocation clauses in the contract, sources of vulnerability, and causal relations between risk events and their impacts. The ontology is constructed by interaction with Turkish contractors working in international markets and extensive literature review on risk-related concepts. The validation test results provide evidence that the ontology is fairly effective to help Turkish contractors to assess cost overrun by considering sources of vulnerability and risk in international construction projects.     

Statistical Analysis on the Cost and Duration of Public Building Projects

A probabilistic model is proposed to predict the risk effects on time and cost of public building projects. The research goal is to utilize a real history data in estimating project cost and duration. The model results can be used to adjust floats and budgets of the planning schedule before project commencement. Statistical regression models and sample tests are developed using real data of 113 public projects. The model outputs can be used by project managers in the planning phase to validate the schedule critical path time and project budget. The comparison of means analysis for project cost and time performance indicated that the sample projects tend to finish over budget and almost on schedule. Regression models were developed to model project cost and time. The regression analysis showed that the project budgeted cost and planned project duration provide a good basis for estimating the cost and duration. The regression model results were validated by estimating the prediction error in percent and through conducting out-of-sample tests. In conclusion, the models were validated at a probability of 95%, at which the proposed models predict the project cost and duration at an error margin of ±0.035% of the actual cost and time.     

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.     

Prototype Model for Build-Operate-Transfer Risk Assessment

The build-operate-transfer (BOT) approach for project delivery, where the private sector has to finance, design, build, operate, and maintain the facility and then transfer it to the government after a specified concession period, is now gaining widespread popularity in developing countries. Compared with conventional project delivery methods, BOT sponsors expose themselves to a high risk, so that special attention must be paid to analyzing and managing risks. The identification, analysis, and allocation of various types of risks are an important aspect for the validation of privately promoted infrastructure projects. The BOT risk model presented in this paper is a prototype evaluation model that provides a logical, reliable, and consistent procedure for assessing the BOT project risk. The proposed model introduced the BOT risk index (F), which relied on the actual performance of eight main BOT risk areas. Two different modeling approaches were used in constructing this index: a new developed and an adapted Dias and Ioannou model. Not only can this index be used for BOT projects’ risk evaluation, but also for ranking them to select the lowest risk project as well.     

Effect of Preconstruction Planning Effort on Sheet Metal Project Performance

The complexity of construction industry requires the identification of work tasks and the coordination of interactions among them. As a result, construction planning is considered to be one of the most critical steps toward success and is the main focus of past research. Consequently, little research has been performed regarding the preconstruction planning, which is the planning completed by the contractor in the period between project award and project execution. This paper focuses on sheet metal preconstruction planning, primarily that of mechanical and heating ventilations and air conditioning contractors. The research was completed in three phases: phase one gathered data on the current state of preconstruction planning, phase two developed a model sheet metal preconstruction planning process to be used by sheet metal contractors, and phase three validated the model preconstruction planning process. Based on project data collected for this research, projects that used a planning process similar to the model process performed more successfully—they achieved an average profit margin of 23% while projects that were poorly planned experienced an average profit margin of ?3%.     

Nature of Engineering Consulting Projects

Engineering consulting firms usually collect data such as cost and man-hour expenditures. Although these data help analyze project profit and productivity, they lack the information on the project nature to examine work and analyze the root causes of performance. This study investigates the nature of engineering consulting projects in terms of uncertainty and equivocality (U&E). A questionnaire was designed to collect project U&E data from 108 project managers. The U&E scores were analyzed, further linked to and tested on a consulting firm’s profit, productivity, project type, phase, duration, and owner data. It is found that project nature does not affect profit or productivity; engineering design work needs more data acquisition and analysis than problem definition and interpretation. Other results show insightful patterns about engineering projects that can be useful references to the engineering services industry.     

Selecting Appropriate Project Delivery System: Fuzzy Approach with Risk Analysis

The selection of an appropriate project delivery system that suits all project and owner needs is one of the key decisions to a successful project. Therefore, this decision should be made based on thorough analysis. In this paper, a fuzzy multiattribute decision-making (FMADM) model is developed. The model accounts for uncertainties and imprecision in the decision space as well as fuzziness in the nature of the decision attributes. The model utilizes fuzzy decision-making approach in order to evaluate the membership function corresponding to the utility of each project delivery alternative. Project delivery system alternatives are ranked using fuzzy technique for order preference by similarity to ideal solution (TOPSIS) method based on their utility membership functions and by evaluating the distance of each project delivery alternative from fuzzy ideal solutions. In the TOPSIS method, alternatives are ranked based on their closeness coefficient (CC). In addition, the risk attitude of the decision maker is considered in the model by using derived utility membership functions corresponding to the risk attitude of the decision maker. The model is applied to a petrochemical project as a case study. In the case study, the model outcome that ranked Turnkey system as the best system conforms to the lessons learned by the decision maker from several past projects. Moreover, sensitivity analysis is done in the case study. The results show the significant value of the FMADM model for selecting appropriate project delivery system for projects.     

Probabilistic Approach for Budgeting in Portfolio of Projects

This paper presents a mathematical model for calculating the budgetary impact of increasing the required confidence level in a probabilistic risk assessment for a portfolio of projects. The model provides a rational approach for establishing a probabilistic budget for an individual project in such a way that the budget for a portfolio of projects will meet a required confidence level. The use of probabilistic risk assessment in major infrastructure projects is increasing to cope with major cost overruns and schedule delays. The outcome of the probabilistic risk assessment is often a distribution for project costs. The question is at what level of confidence (i.e., the probability that budget would be sufficient given the cost distribution) should be used for establishing the budget. The proposed method looks at a portfolio of such projects being funded by the same owner. The owner can establish a target probability with respect to its annual budget. The model can help the owner establish confidence level for individual projects and also examine the effect of changing the confidence level of the portfolio budget on the budget and the confidence level of individual projects. The paper is relevant to practitioners because it provides a methodology for establishing confidence levels by the owner agencies in the emerging field of cost risk assessment for infrastructure projects. A numerical example is provided using actual transit project data to demonstrate the model application.     

Prediction System for Change Management in Construction Project

Changes are the main causes of delays and cost overruns in construction projects. Various change management systems have been developed to minimize the impacts of changes and to facilitate good project management. This paper presents a change prediction system using activity-based dependency structure matrix (DSM) to facilitate change management. DSM is used to model the process that may occur as a result of changes. Consequently changes can be predicted by setting the change criteria for each activity in the form of rework scope. Furthermore, Monte Carlo simulation is introduced to analyze the change probability of activities involved in construction projects. The effectiveness of the prediction system is verified by applying this system to an office building project. This study provides a useful tool for project management teams to manage changes proactively and efficiently.     

Risk Assessment Methodology for Underground Construction Projects

This paper presents a risk assessment methodology for underground construction projects. A formalized procedure and associated tools were developed to assess and manage the risks involved in underground construction. The suggested risk assessment procedure is composed of four steps of identifying, analyzing, evaluating, and managing the risks inherent in construction projects. The main tool of the proposed risk assessment methodology is the risk analysis software. The risk analysis software is built upon an uncertainty model based on fuzzy concept. The fuzzy-based uncertainty model is designed to consider the uncertainty range that represents the degree of uncertainties involved in both (1) probabilistic parameter estimates and (2) subjective judgments. Other tools developed in this study include the survey sheets for collecting risk-related information and the detail check sheets for risk identification and analysis. The paper finally discusses a detailed case study of the developed risk assessment methodology performed for a subway construction project in Korea.     

Portfolio Cash Assessment Using Fuzzy Systems Theory

Gaps between cash outflows and inflows throughout the life cycle of construction projects can create extended periods of low cash availability for a construction contractor, jeopardizing the financial stability of the business. A number of researchers have therefore attempted to model cash availability at a project level. However, at a firm level, financial stability is more thoroughly examined as a function of the cash flows related to multiple projects. This paper proposes a methodology on the basis of fuzzy systems theory to forecast cash requirements of a portfolio of projects for a construction firm, taking into account the effect of changing portfolio composition on portfolio cash-flow risk. Portfolio cash-flow risk is calculated from a variance matrix created by using covariance among cash flows of pairs of projects. Expert opinions of a group of highway construction contractors regarding project selection, project risk assessment and cash control were collected to create a fuzzy proportional derivative (PD) model that predicts portfolio risk for a construction firm. The model was assessed by the same group of contractors for overall logic (if/then rule base), appropriateness of cash-flow calculations (moving weights of cost categories), and practicality through application on a hypothetical test case. The paper concludes that a fuzzy proportional derivative model can be an effective tool to establish trends in cash-flow availability and risk across a portfolio of construction projects.