Selection of Project Delivery Method in Transit: Drivers and Objectives

This paper describes the results of research on alternative project delivery methods in transit projects in the United States. The research, sponsored by the Transit Cooperative Research Program, aimed to identify those factors that drive the decision in the choice of project delivery method. A rigorous case study analysis based on on-site structured interviews with the directors of several transit projects was used to identify decision drivers and the rationale behind the delivery method selection decision in transit agencies. The nine case studies conducted in this research represent a cross section of delivery methods, including design-bid-build/multiprime, construction manager-at-risk, design/build, and design/build-operate-maintain. The interviewees agreed that the use of alternative delivery methods have resulted in savings in schedule and cost for transit agencies. The research also found that achieving aggressive schedule compression is the most influential factor when selecting alternative delivery methods. Also, implementation of a formal risk analysis as part of the project development process appears to improve the project’s chances of meeting budget and schedule objectives.     

Owner’s Risks versus Control in Transit Projects

This paper studies the characteristics of different project delivery methods in public transit projects with respect to the owner’s project control and its share in project risks. The most appropriate project delivery method is selected early in the project life cycle based on a number of objectives and criteria set forth by the owner. The ability to manage risk effectively and owner’s control over the project are among the most important factors for selecting the delivery method. These two factors are highly interrelated. This paper discusses the interaction of risk and control in the context of the project delivery method. Results of several interviews with transit authorities are used to ensure the validity of findings. This paper shows that higher control over the project is achieved only if the owner is willing to accept more risks. In other words, there is no delivery method that allows the owner to enjoy high levels of control and minimum risk simultaneously.     

Multiobjective Linear Programming Model for Scheduling Linear Repetitive Projects

Linear repetitive construction projects require large amounts of resources which are used in a sequential manner and therefore effective resource management is very important both in terms of project cost and duration. Existing methodologies such as the critical path method and the repetitive scheduling method optimize the schedule with respect to a single factor, to achieve minimum duration or minimize resource work breaks, respectively. However real life scheduling decisions are more complicated and project managers must make decisions that address the various cost elements in a holistic way. To respond to this need, new methodologies that can be applied through the use of decision support systems should be developed. This paper introduces a multiobjective linear programming model for scheduling linear repetitive projects, which takes into consideration cost elements regarding the project’s duration, the idle time of resources, and the delivery time of the project’s units. The proposed model can be used to generate alternative schedules based on the relative magnitude and importance of the different cost elements. In this sense, it provides managers with the capability to consider alternative schedules besides those defined by minimum duration or maximizing work continuity of resources. The application of the model to a well known example in the literature demonstrates its use in providing explicatory analysis of the results.     

Analysis of Federal Design-Build Request for Proposal Evaluation Criteria

This study’s objective is to identify the benefits federal owners are seeking through the design-build process by analysis of research data gathered from 110 requests for proposal (RFP) evaluation plans issued for $1.5 billion of federal work by 11 different agencies. The output from this study was then compared to a 1996 study whose authors sought to analyze the reasons cited by owners to use design-build project delivery. That study included a survey of 108 owners of public and private projects, which represented over $12.5 billion of construction. The goal of comparing the 1996 survey with the results of the new research project is to discover correlations between owner attitudes and the selection criteria identified in government RFPs. The comparison produced some interesting results. First, although owners in 1996 cited schedule as the most significant reason for selecting design-build delivery, the federal RFP content analysis found it to carry a very low average weight. Another finding shows that federal RFPs give price a very heavy weight in the government selection processes, again differing significantly from the previous survey of owner attitudes. Finally, the current study found that the qualifications of the firms and individuals that formed the design-build team were significantly more important than the proposed technical design approach. Thus, this paper concludes that the typical federal agency was looking for a low price from a well-qualified design-build team.     

Project Delivery System Selection under Uncertainty: Multicriteria Multilevel Decision Aid Model

Selecting an optimal project delivery system is a critical task that owners should do to ensure project success. This selection is a complex decision-making process. The complexity arises from the uncertain or not well-defined parameters and/or the multiple criteria structure of such decisions. In this study, a decision aid model using the analytical hierarchy process (AHP) coupled with rough approximation concepts is developed to assist the owners. The selection criteria are determined by studying a number of benchmarks. The model ranks the alternative delivery systems by considering both benchmark results and owner’s opinion. In interval AHP, an optimization procedure is performed via obtaining the upper and the lower linear programming models to determine the interval priorities for alternative project delivery systems. In cases having incomparable alternatives, which is the most likely case in uncertain decision making, the model uses rough set-based measures to reduce the number of decision criteria to a subset, which is able to fully rank the alternatives. To illustrate the applicability and usefulness of this methodology, a real world case study will be demonstrated.     

Fuzzy Logic Approach for Activity Delay Analysis and Schedule Updating

This paper presents a fuzzy logic model that integrates daily site reporting of activity progress and delays, with a schedule updating and forecasting system for construction project monitoring and control. The model developed assists in the analysis of the effects of delays on a project’s completion date and consists of several components: An as-built database integrated with project scheduling; a list of potential causes for delays; a procedure to categorize delays; a method of estimating delay durations utilizing fuzzy logic; a procedure that updates the schedule; and, a procedure that evaluates the effects and likely consequences of delays on activity progress. This model is of relevance to researchers since it makes a contribution in project scheduling by developing a complete approach for handling the uncertainty inherent in schedule updating and activity delay analysis. It also advances the application of fuzzy logic in construction. It is of relevance to construction industry practitioners since it provides them with a useful technique for incorporating as-built data into the schedule, assessing the impact of delays on the schedule, and updating the schedule to reflect the consequences of delays and corrective actions taken. The use of fuzzy logic in the model allows linguistic and subjective assessments to be made, and thereby suits the actual practices commonly used in industry.     

Systematic Evaluation of Construction Equipment Alternatives: Case Study

Selecting the right equipment for the project is inherently a multifaceted cost and benefit evaluation process that is further compounded by the complexity of today’s building projects and the lack of systematic tools for the consideration of soft factors. This paper presents a detailed application example of a model based on an analytical hierarchy process (AHP) approach. This model was developed to address the difficulties experienced during the multifaceted process. The example illustrates how an AHP-based model helps address the multitude of qualitative, intangible factors, both among the factors themselves and then vis-à-vis costs, by means of a systematic and traceable process. The method enables project managers and their equipment selection teams to exercise their knowledge, intuition, and professional judgment, and at the same time to address the context and specifics of the particular projects under examination. The example should be helpful for construction practitioners dealing with similar equipment selection issues. Researchers may find interest in the implementation of a multiattribute-decision-making method for a typical construction management problem.     

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.     

Time-Cost Optimization of Construction Projects with Generalized Activity Constraints

Time-cost analysis is an important element of project scheduling, especially for lengthy and costly construction projects, as it evaluates alternative schedules and establishes an optimum one considering any project completion deadline. Existing methods for time-cost analysis have not adequately considered typical activity and project characteristics, such as generalized precedence relationships between activities, external time constraints, activity planning constraints, and bonuses/penalties for early/delayed project completion that would provide a more realistic representation of actual construction projects. The present work aims to incorporate such characteristics in the analysis and has developed two solution methods, an exact and an approximate one. The exact method utilizes a linear/integer programming model to provide the optimal project time-cost curve and the minimum cost schedule considering all activity time-cost alternatives together. The approximate method performs a progressive project length reduction providing a near-optimal project time-cost curve but it is faster than the exact method as it examines only certain activities at each stage. In addition, it can be easily incorporated in project scheduling software. Evaluation results indicate that both methods can effectively simulate the structure of construction projects, and their application is expected to provide time and cost savings.     

Cumulative Effect of Project Changes for Electrical and Mechanical Construction

Change is inevitable on construction projects, primarily because of the uniqueness of each project and the limited resources of time and money that can be spent on planning, executing, and delivering the project. Change clauses, which authorize the owner to alter work performed by the contractor, are included in most construction contracts and provide a mechanism for equitable adjustment to the contract price and duration. Even so, owners and contractors do not always agree on the adjusted contract price or the time it will take to incorporate the change. What is needed is a method to quantify the impact that the adjustments required by the change will have on the changed and unchanged work. Owners and our legal system recognize that contractors have a right to an adjustment in contract price for owner changes, including the cost associated with materials, labor, lost profit, and increased overhead due to changes. However, the actions of a contractor can impact a project just as easily as those of an owner. A more complex issue is that of determining the cumulative impact that single or multiple change orders may have over the life of a project. This paper presents a method to quantify the cumulative impact on labor productivity for mechanical and electrical construction resulting from changes in the project. Statistical hypothesis testing and correlation analysis were made to identify factors that affect productivity loss resulting from change orders. A multiple regression model was developed to estimate the cumulative impact of change orders. The model includes six significant factors, namely: Percent change, change order processing time, overmanning, percentage of time the project manager spent on the project, percentage of the changes initiated by the owner, and whether the contractor tracks productivity or not. Sensitivity analysis was performed on the model to study the impact of one factor on the productivity loss (%delta). The model can be used proactively to determine the impacts that management decisions will have on the overall project productivity. They may also be used at the conclusion of the project as a dispute resolution tool. It should be noted that every project is unique, so these tools need to be applied with caution.     

Master Builder Project Delivery System and Designer Construction Knowledge

The master builder system for designing and building construction projects was the dominant project delivery system in the construction industry during the early part of the 20th century. Master builders were generally charged with both design and construction services for a project. During the last half of the 20th century, many different systems for project delivery with fragmented responsibilities have replaced the master builder system. Reducing the use of the master builder system has led to the creation of elaborate systems for managing projects in the construction industry. In order to investigate the use of the master builder delivery system and other systems, a research project was conducted that included reviewing (1) the history of the construction industry, (2) project delivery systems, (3) constructability issues, (4) construction industry fragmentation, (5) the results of a survey of architecture, engineering, and construction professionals from the San Francisco Bay Area in California on the current processes they use for training engineers and architects, (6) an analysis of the survey results, (7) construction industry recommendations, and (8) conclusions based on the survey results and analysis. The information obtained from the research project, including the survey and an analysis of the results, is included in this document. The results of the research indicate that reduction in the use of the master builder project delivery system and the rise of numerous fragmented delivery systems have limited the designer’s knowledge of construction processes.     

Web-Enabled System Dynamics Model for Error and Change Management on Concurrent Design and Construction Projects

Construction projects are uncertain and complex in nature often because of iterative cycles caused by errors and changes. These errors and changes impair project performance and, consequently, cause schedule and cost overruns to be prevalent. Iterative cycles are more detrimental when design and construction are concurrent and often force activities to proceed without complete information. In an effort to address this issue, this paper presents the information technology aspect of the dynamic planning and control methodology (DPM), which provides a mechanism that will analyze the impact of negative iterative cycles on construction performance. In order to guarantee a smooth application of this method to real-world projects, DPM has been developed by integrating several existing methods around a core system dynamic model for quality and change management and then implementing these methods into a web-based collaborative environment. A case project, applying the developed web-based DPM, shows great potential in facilitating on-site decision making by virtue of its support of data analysis as well as real-time information sharing.     

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.     

Production System Loading–Cycle Time Relationship in Residential Construction

Production home building possesses characteristics similar to manufacturing processes, such as the construction of more or less similar houses repeatedly and a growing demand for mass customization of homes. As a result of these similarities, larger homebuilders often attempt to view their production system as an assembly line process. However, the management tools generally utilized by these home builders are those used in other sectors of the construction industry, such as critical path method scheduling, cost estimating, and earned value analysis. These management tools do not provide an explanation or control/prediction tools for many undesirable situations that arise during home building, such as increasing cycle time which slows delivery of product to consumers and increases project capital costs, and increasing amounts of work in process that increases capital investment and thereby decreases company financial performance. In order to bring better management tools to the residential construction industry, this study examines relationships between cycle time, work in process, system throughput, new construction starts, and the capacity of the production system using building permit data for new single family homes in Chandler, Ariz. The applicability of Little’s law, a basic equation used in factory production management models, to a residential production system is examined. This study shows a definite, predictable relationship between cycle time, work in process, and production system throughput. It provides a pathway for further study of production system characteristics that have historically not been included in construction management models, with the expectation of developing new construction management tools that will account for more of the characteristics of construction production systems that affect project performance and company financial performance.     

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.     

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.     

Predicting Performance of Design-Build and Design-Bid-Build Projects

Design-build (DB) and design-bid-build (DBB) are two principal project delivery systems used in many countries. This paper reports on models constructed to predict performance of DB and DBB projects on 11 areas, using project-specific data collected from 87 building projects. The study included collecting, checking, and validating industry data, and the statistical development of multivariate linear regression models for predicting project performance. Robust models are developed to predict construction and delivery speeds of DB and DBB projects. Gross floor area of the project is the most significant factor affecting speed. Besides this, for DBB projects, contractors’ design ability, and adequacy of plant and equipment would ensure speedy completion of the projects. For DB projects, if the contract period is allowed to vary during tender evaluation, this would slow down the project. Robust models to predict turnover and system quality of DB projects are also constructed. A DB contractor’s track record is an important variable. They must have completed past projects to acceptable quality and have ability in financial, health and safety management.     

Cost Information Model for Managing Multiple Projects

Construction companies must deal with several projects at once, but a system to manage multiple projects is not fully developed yet. The first step towards developing such system is to design an information model that is suitable for managing multiple projects. This paper presents the cost-based project modeling (CBPM) method in contrast to the traditional activity-based project modeling methods. The CBPM uses cost as a core of the model along with other project information organized around it. The CBPM serves as a platform for integrating project information from multiple projects. Various types of construction costs are hierarchically modeled to generate corporate-wide information such as project performances, cash flows, and other predictive indicators. Based on the information model, an object-oriented database was developed to contain cost data across several projects. In the model, a module that connects to external systems is built into the model to enhance interactivity with the legacy systems and the industry standards. A prototype system was developed and tested with actual project data to validate the information processing capabilities of the model. The findings from the test indicate construction cost can be an excellent medium that can organize various types of information of multiple projects.     

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.     

Greening Project Management Practices for Sustainable Construction

Environmentally sustainable building construction has experienced significant growth during the past 10 years. The public is becoming more aware of the benefits of green construction as prominent politicians, celebrities, documentarians, and journalists highlight the built environment’s impact on greenhouse gas emissions and natural resource consumption. Other factors, including higher energy prices, increased costs of building materials, and regulatory incentives, are also pushing the green building market to grow and expand. However, barriers to green building continue to exist, including the ability to deliver a green project within acceptable cost constraints. In order for project managers to deliver sustainable construction according to clients’ cost expectations, modifications must be made to traditional project management processes and practices. The objective of this paper is to suggest specific modifications to conventional building practices to optimize the delivery of cost-efficient green building projects. This paper presents an overview of research related to the costs and trends of green building and uses these research findings to make recommendations for greening project management practices for the construction industry. Our research results show that greening project management practices can add significant value to a sustainable construction project while delivering it within acceptable cost constraints. A detailed analysis using matrix present specific adjustments to traditional project management practices, with a premise that a green project improves its chances for financial success if a cross-discipline team is involved at the earliest stages and throughout the project.