Organizing Large Projects: How Managers Decide

Now tools will help managers design organization structures for large engineering and construction projects. An improved understanding of how managers decide in structuring project organizations is necessary to develop these tools and to assist managers in the systematic design of organizations tailored to meet project goals under unique situations. This paper reports a portion of results from research conducted to determine current practices in project organization design. The conclusion that adaptation dominates this process leads to several implications for industry professionals and researchers wishing to improve project performance. Recognizing the role of adaptation in current practices of organizational structuring will allow managers to avoid inertia and systematically design organizations. Researchers can assist by expanding variables in organization theory to better capture project situation and structure and by developing new tools to assist in systematic organization design.     

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.     

Fast and Accurate Risk Evaluation for Scheduling Large-Scale Construction Projects

This paper presents the development of a novel probabilistic scheduling model that enables fast and accurate risk evaluation for large-scale construction projects. The model is designed to overcome the limitations of existing probabilistic scheduling methods, including the inaccuracy of the program evaluation and review technique (PERT) and the long computational time of the Monte Carlo simulation method. The model consists of three main modules: PERT model; fast and accurate multivariate normal integral method; and a newly developed approximation method. The new approximation method is designed to focus the risk analysis on the most significant paths in the project network by identifying and removing insignificant paths that are either highly correlated or have high probability of completion time. The performance of the new model is analyzed using an application example. The results of this analysis illustrate that the new model was able to reduce the computational time for a large-scale construction project by more than 94% while keeping the error of its probability estimates to less than 3%, compared with Monte Carlo Simulation methods.     

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.     

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.     

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.     

Embodying Product and Process Flexibility to Cope with Challenging Project Deliveries

Four factors make it challenging to manage semiconductor fabrication facility (“fabs”) projects: technical complexity of the product design, need to compress the project duration, need to reduce upfront costs, and unexpected project changes. The strategies employed by practitioners to cope with these challenges form an intricate puzzle. We empirically develop a framework that provides a structure for helping to solve this puzzle, which comprises two principles: investing upfront in a flexible product design and structuring a flexible process. Empirical findings reveal that project teams make commitments early on by overdesigning but also postpone critical decisions by differentiating the scope of their work. Project teams employ other strategies such as increasing communication, using modular architectures, engaging in four-dimensional computer-based modeling, and fabricating components and subsystems off-site. Our analysis yields understanding on the purposes and performance tradeoffs of these strategies, and on how they embody the two principles. Project managers may find the framework useful when deciding which strategies best suit other equally challenging projects.     

Evaluation of Risk Factors Leading to Cost Overrun in Delivery of Highway Construction Projects

Accurate owner budget estimates are critical to the initial decision-to-build process for highway construction projects. However, transportation projects have historically experienced significant construction cost overruns from the time the decision to build has been taken by the owner. This paper addresses the problem of why highway projects overrun their predicted costs. It identifies the owner risk variables that contribute to significant cost overrun and then uses factor analysis, expert elicitation, and the nominal group technique to establish groups of importance ranked owner risks. Stepwise multivariate regression analysis is also used to investigate any correlation of the percentage of cost overrun with risks, together with attributes such as highway project type, indexed cost, geographic location, and project delivery method. The research results indicate a correlation between the reciprocal of project budget size and percentage cost overrun. This can be useful for owners in determining more realistic decision-to-build highway budget estimates by taking into account the economies of scale associated with larger projects.     

Risk Evaluation in Resource Allocation

Conventional resource allocation procedures implicitly assume that the availability of resources is certain. In real life situations, their availability is, at times, uncertain. A Risk Evaluation Model (REM) is proposed to systematically evaluate the uncertainty of resource availability and generate several alternatives having varying project completion time, cost, and performance probability. REM can aid a contractor in “bid∕no‐bid” decision‐making, an entrepreneur in investment decision‐making, and a consultancy organization in corporate planning.     

Float Allocation Using the Total Risk Approach

Float ownership is one of the controversial issues in the litigation of delay claims. As float time does not always affect the overall project completion time, many believe that this time can be used by any of the project parties and that it does not belong to a particular party. This study introduces the “total risk approach” for float allocation, a new approach that integrates several current approaches to allocate float among project parties. The approach is based on the basic concept that the party who has the greatest risk in a project should be entitled to float ownership and deserves compensation from other project parties who increase the risk associated with the project by consuming the float. This new approach takes into consideration the changes in float that may occur as a result of actions that delay or accelerate the project’s schedule.     

Estimating Performance Time for Construction Projects

The prediction of performance time for construction projects is a problem of interest to both researchers and practitioners. This research seeks to gain insight into the significant factors impacting construction duration by developing a regression model. Data were collected for 856 facility projects completed between 1988 and 2004. These data were analyzed using Bromilow’s time-cost (BTC) model (1969) as well as multiple linear regression. The multiple linear regression model was found to provide the most acceptable prediction. As in the BTC model and previous research reported in the literature, a significant correlation was found to exist between cost and duration. However, several other factors were also identified that resulted in significantly lower than average construction durations. These include projects completed within certain management groupings, managed by a certain construction agent, and designed by in-house personnel.     

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.     

Neurofuzzy Decision Support System for Efficient Risk Allocation in Public-Private Partnership Infrastructure Projects

The performance of public-private partnership (PPP) infrastructure projects is largely contingent on whether the adopted risk allocation (RA) strategy is efficient. Theoretical frameworks drawing on the transaction cost economics and the resource-based view of organizational capability are able to explain the underlying mechanism but unable to accurately forecast efficient RA strategies. In this paper, a neurofuzzy decision support system (NFDSS) was developed to assist in the RA decision-making process in PPP projects. By combining fuzzy and neural network techniques, a synthesized fuzzy inference system was established and taken as the core component of the NFDSS. Evaluation results show that the NFDSS can forecast efficient RA strategies for PPP infrastructure projects at a highly accurate and effective level. A real PPP infrastructure project is used to demonstrate the NFDSS and its practical significance.     

REILP Approach for Uncertainty-Based Decision Making in Civil Engineering

The civil and environmental decision-making processes are plagued with uncertain, vague, and incomplete information. Interval linear programming (ILP) is a widely applied mathematical programming method in assisting civil and environmental decision making under uncertainty. However, the existing ILP decision approach is found to be ineffective in generating operational schemes for practical decision support due to a lack of linkage between decision risk and system return. In addition, the interpretation of the ILP solutions represented as the lower and upper bounds of decision variables can cause problems of infeasibility and nonoptimality in the resulted implementation schemes. This study proposed a risk explicit ILP (REILP) approach to overcome the limitations of existing ILP approaches. The REILP explicitly reflects the tradeoffs between risk and system return for a decision-making problem under an interval-type uncertainty environment. A risk function was defined to enable finding solutions which maximize system return while minimizing system risk, hence leading to crisp solutions that are feasible and optimal for practical decision making. A numerical experiment on land-use decision making under total maximum daily load was conducted to illustrate the REILP approach. The model results show that the REILP approach is able to efficiently explore the interval uncertainty space and generate an optimal decision front that directly reflects the tradeoff between decision risks and system return, allowing decision makers to make effective decision based on the risk-reward information generated by the REILP modeling analysis.     

Risk/Reward Compensation Model for Civil Engineering Infrastructure Alliance Projects

A risk/reward model is described as that which aligns project participants’ behaviors toward the achievement of a project’s performance objectives through the use of incentives. A risk/reward model typically includes the following mechanisms: risk/reward shared percentages among nonowner participants, project cost risk/reward, noncost risk/reward, risk cap, and achievability of performance targets. This paper examines the influence of a risk/reward model on the behavior of project participants. Twenty-nine industry practitioners from eight civil infrastructure project alliances were interviewed. The interviews revealed that individual features of a risk/reward model identified had merits, but the achievability of performance targets model appeared to be the most appropriate for promoting positive behaviors within the project team. Additionally, it was found that all incentive aspects of the model examined led to positive and constructive behaviors occurring due to their perceived fairness and equity of payment structure. Participants indicated that having a commercial interest in an alliance’s performance outcomes ensured collaboration and engagement throughout the project’s life cycle. It is concluded that risk/reward sharing is pivotal to obtaining a successful project outcome for the procurement of civil engineering infrastructure projects when using an alliance.     

Valuing Flexibility in Architecture, Engineering, and Construction Information Technology Investments

When investing in information technology (IT) applications, construction managers implicitly account for the value of adding future applications to the original investment as the business and technical environment changes. A real option model links uncertainty to the value of an underlying traded asset, providing an objective measure of this managerial flexibility. A case study that investigated the value of options to extend a general contractor’s software platform showed that it is possible to construct a real option model which measures the value of this flexibility, since the major risk (the architect’s adoption rate) is external to the investing organization. In another case study, a contractor evaluated the value of the pilot project in view of the information it is expected to generate. Since the risks are internal, a decision analysis model is used instead of a binary option model. The results show that it is possible to quantify the value of managerial flexibility for IT investments in the architecture, engineering, and construction industry, but that the proper method to use is contingent on the nature of the investment project.     

Formulating Procurement Selection Criteria through Case-Based Reasoning Approach

An appropriate procurement system is a catalyst to the success of a construction project. In practice, the solutions and outcomes of previous procurement selection decisions could be extremely useful in supporting decision making. As a technique that captures and reuses experiential knowledge, case-based reasoning (CBR) has a high potential for modeling the procurement selection decision within a complex dynamic environment. This paper examines the suitability of CBR approaches for procurement selection. The process involved in procurement selection is examined first. A conceptual framework for case-based procurement selection is proposed. The structure of a prototype model on procurement selection criteria (PSC) formulation is presented in this paper. The model applies the CBR approach to procurement criteria selection irrespective of the variability in the characteristics of the client, project, and external environment.     

Concurrent Engineering Approach to Reducing Design Delivery Time

A common method used to reduce project delivery time is to overlap sequential activities. Evolution and sensitivity characterizations of design activities provide a practical tool for identifying overlapping opportunities. The faster the evolution of information in an activity, the less risky it is to begin a downstream activity before the upstream activity is finalized. Also, the lower the sensitivity to changes in upstream information, the less risky it is to overlap activities. A methodology for determining the evolution and sensitivity of design activities has been developed through a series of expert interviews. The evolution of an activity can be determined by evaluating the levels of design optimization, constraint satisfaction, external information exchange, and standardization. The sensitivity of an activity can be determined by evaluating activity constraints, input variables, and the level of design integration. This framework for characterizing design activities in terms of evolution and sensitivity will lead to significant reductions in project delivery times.     

Exploring the Bidding Situation for Economically Most Advantageous Tender Projects Using a Bidding Game

Most open tendering procedures in the real world are highly complex, uncertain, and costly. With an increasing emphasis on the quality and value of procurement, economically most advantageous tender (EMAT) has been widely adopted as an alternative contract-awarding criteria, which has changed competitive strategies in the construction industry. A conceptual model of competitive bidding in EMAT is first established to reflect the credibility of the bidding situation. A bidding game for EMAT projects is performed by 24 participants to partially test the conceptual model. The result reveals that the game has the potential to reveal important factors in the bidding situation, simulate competitive bidding behaviors, and explore competitive advantages in the EMAT bidding process. The learning effect from the game should be useful for contractors who are preparing to deliver optimal tenders in EMAT projects.     

Relative Effectiveness of Project Delivery and Contract Strategies

Project delivery systems define the roles and responsibilities of the parties involved in a project. They also establish an execution framework in terms of sequencing of design, procurement, and construction. The decision made in the selection of a project delivery system for a project impacts all phases of execution of the project and greatly impacts the efficiency of project execution. Such decisions should be facilitated by thorough analysis. Structured, quantitative decision analysis processes have been shown to have several benefits over the simplistic, holistic, and informal processes that typically characterize subjective evaluations. However, a dearth of quantitative values of project delivery systems established and validated through research has invariably left project managers with no alternative than to make project delivery selection decisions on the basis of subjective evaluations. Development of the needed quantitative values for application in a decision analysis process would greatly enhance the quality of the decision-making process and provide a defensible rationale for selection of project delivery systems for capital projects. This paper presents research findings that provide the needed quantitative values in this area. Based on the quantitative values defined here, interested parties can develop and implement quantitative evaluation of project delivery alternatives to identify the optimal solution for a given project. Multicriteria decision analysis was found to be the suitable approach for a quantitative, analytical evaluation of project delivery systems. Consequently, the quantitative values presented in this paper were developed in accordance with the requirements of the multicriteria decision analysis technique known as simple multiattribute rating technique with swing weights (SMARTS). Utilizing the quantitative values presented here and applying the analysis technique of SMARTS, a decision support tool has been developed and validated for the Construction Industry Institute. The decision support tool is presently being utilized by member companies of the Construction Industry Institute that were privy to its development. With the presentation of the quantitative values in this paper, other parties interested in developing similar tools would benefit from the research results presented here.