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Construction projects are susceptible to cost and time overruns. Variations from planned schedule and cost estimates can result in huge losses for owners and contractors. In extreme cases, the viability of the project itself is jeopardised as a result of variations from baseline plans. Hence new methods and techniques which assist project managers in forecasting the expected variance in schedule and cost should be developed. This paper proposes a judgment‐based forecasting approach which will identify schedule variances from a baseline plan for typical construction projects. The proposed forecasting approach adopts multiple regression techniques and further utilises neural networks to capture the decision‐making procedure of project experts involved in schedule monitoring and prediction. The models developed were applied to a multistorey building project under construction and were found feasible for use in similar construction projects. The advantages and limitations of these two modelling process for prediction of schedule variance are discussed. The developed models were integrated with existing project management computer systems for the convenient and realistic generation of revised schedules at appropriate junctures during the progress of the project.

The purpose of this paper is to propose an integrated earned value management (EVM) approach to control quality, cost, schedule and risk of projects.

This study represents a new EVM framework by considering a quality control index. Particularly, some control indices and cumulative buffers are defined by two proposed, methods, namely the linear- and Taguchi-based methods. These methods are implemented in three different projects in different industries.

According to the results, integration of the quality index creates a better control situation by providing more accurate information. Hence, project managers could comprehensively monitor the status of important factors to make more precise decisions while maintaining the simplicity of their analysis.

From the methodological and theoretical features, this paper offers new visions because, to the best of authors’ knowledge, no comparable study has been conducted before.

We review what is known and what is still unknown about the process of revealing the impact of unreliability on travel choices. We do this from the perspective of a demand-modelling practitioner who wishes to allow for the benefits from improved reliability in the assessment of a transport scheme. We discuss the travel responses affected by unreliability, the requirements from the data used to model these responses, the explanatory variables used in these models and the additional information required as input when applying them. One of our findings is that there is a conflict between existing studies in their conclusions about the aversion to early arrival. Another notion is that it is unclear whether the common simplified treatment of the distribution of preferred arrival times is acceptable. We also suggest that the dominance of departure time shifting as a primary response to unreliability might refute the common assumptions about travellers' choice hierarchy, which was established without considering the impact of unreliability; this raises questions about the robustness of assignment models that do not allow time shifting.

This research examines how the cost performance of defense contracts varies among the Air Force, Army, Navy, and the Department of Defense (DoD) and among five major defense contractors: Boeing, Lockheed Martin, Northrop Grumman, Raytheon, and General Dynamics. Data for these analyses was extracted from the recently established Defense Acquisition Management Information Retrieval (DAMIR) web-based interface for management information on Major Defense Acquisition Programs (MDAP). Note that, in addition to the three military services, MDAP data is also reported for DoD itself.

Data analysis indicates that the Navy ranks last among the military services and DoD in cost performance for MDAP contracts, while the Air Force ranks best. Of the defense contractors, Raytheon ranks last in cost performance and General Dynamics is next to last. Furthermore, the Navy contracts more frequently with Raytheon and General Dynamics than do the other services or DoD. Explanatory factors for poor cost performance may be due to factors such as the Navy's lack of oversight, the quality of the acquisition workforce, the defense contractors’ cost inefficiency, ethical lapses, or weak corporate governance, or combinations of these factors.

In addition, the schedule performance data was also identified. Tests of statistical significance on the schedule performance difference generally yield no results except for one relationship which indicates that the Navy is more likely to have Acquisition Program Baseline (APB) schedule breaches than its counterparts. Finally, cost performance data is examined for statistically significant differences between the two major categories of defense contracts: fixed-price contracts and cost-plus contracts. However, no significant findings were discovered.

The desire to improve efficiency has led both academics and practitioners to embrace various technologies to aid managers to discharge their functions. Recently, there has been a growing interest amongst construction researchers on the use of computer vision and image‐processing techniques to automatically capture work in progress. Reported findings are promising; however, those previous studies fall short of providing a reporting mechanism to aid decision making. The purpose of this paper is to develop a reporting model based on progress captured using computer vision.

The paper first presents trends in research relating to use of computer vision in the monitoring of work in progress. It then employs the unified modelling language to present the conceptual development of the model. The computerised reporting model is developed using the visual basic programming language.

The key elements of the model are computations of cost‐schedule variances, payments and cash flows. Results of a test on a hypothetical case show that the model accurately computes the metrics.

The reporting model serves to provide managers with a quick and easy means of interpreting work progress captured using computer vision. It reinforces the value of already existing work on the application of computer vision techniques to the measurement of work in progress on construction sites.

This study aims to review earned value management (EVM)-relative methods, including the original EVM, earned schedule method (ESM) and earned duration management (EDM(t)). This study then proposes a general implementation procedure and some basic principles for the selection of EVM-relative methods.

After completing an intensive literature review, this study conducts a case study to examine the forecasting performance of project duration using the EVM, ESM and EDM(t) methods.

When the project is expected to finish on time, ESM with a performance factor equal to 1 is the recommended method. EDM(t) would be the most reliable method during a project's entire lifetime if EDM(t) is expected to be delayed based on past experience.

As this research conducts a case study with only one building construction project, the results might not hold true for all types of construction projects.

EVM, ESM and EDM(t) are simple and data-accessible methods. With the help of a general implementation procedure, applying all three methods would be better. The power of the three methods is definitely larger than that of choosing only one for complex construction projects.

Previous studies have discussed the advantages and disadvantages of EVM, ESM and EDM(t). This study amends the available outcomes. Thus, for schedulers or researchers interested in implementing EVM, ESM and EDM(t), this study can provide more constructive instructions.

The objective of this paper is to develop an efficient project management system to track and control construction activities for contractors and/or project managers.

The work package model is utilized to break down project data into activities and work tasks. The data structure of a project is represented using the entities‐relationship methodology. A relational database stores all of the project data. The earned value method calculates the cost and schedule variances. The internet‐based platform with three‐tier client‐server architecture is chosen for system implementation.

The developed project database stores all of the project data necessary to perform project control functions. The implementation of the project database management system is efficient. The developed system provides real‐time data sharing and a collaborating environment in support of project control.

Time and cost control are essential management functions for achieving successful delivery of engineering, procurement and construction (EPC) projects. The developed system can assist contractors and/or project managers in tracking and control of their construction projects in a real‐time manner.

The concept of “earned value” can be very useful in controlling large, expensive projects. It offers a consistent view across time and across a number of projects. It can be complex to use, but it offers sophisticated progress monitoring. Outlines the basic concepts and shows how earned value is used to measure, monitor and control large and complex projects.

The purpose of this paper is to develop models to forecast final budget and duration of a highway construction project during construction stage.

Highway construction project data are collected and analyzed to find out factors affecting project final budget and duration before developing the forecasting models, research for which is based on the principle of Artificial Neural Network (ANN). The forecasting results obtained from the proposed method are compared with those obtained from the current method based on earned value.

Factors affecting final budget and duration are presented. The forecasting results obtained from the proposed method based on ANN application are more accurate and stable than those obtained from the current method based on earned value.

Factors affecting final budget and duration may differ if applied in other countries, since the project data were collected in the Kingdom of Thailand. The forecasting models, therefore, must be reconsidered for better outcomes.

The study presents a useful tool for the highway construction project manager to predict project final budget and duration. The results can potentially provide early warning of over‐budget and schedule delay.

The ANN models to forecast final budget and duration of highway construction projects during the construction stage, developed by using project data reflecting continual and seasonal cycle data, can provide better predicting results.

Integrated project delivery (IPD) is highly recommended to be utilised with building information management (BIM), specifically with BIM level-3 implementation process. Extant literature highlights the financial management challenges facing the proposed integration. These challenges are mainly related to the IPD compensation and the conventional cost control approaches that are not consistent with IPD principles. As such, this paper presents an integration of several methods to support automating risk/reward sharing amongst project parties thus enhancing IPD core team members’ relationship.

The literature review was used to highlight the challenges that face the IPD-based cost management practices such as the risk sharing/reward sharing amongst IPD core team members and potential methods to bridge the revealed IPD gap. A framework was developed by integrating the activity-based costing (ABC) – as a method to analyse the cost structure – and earned value management (EVM) to develop mathematical models that can determine the three main IPD financial transactions (i.e. …) fairly. To demonstrate the applicability of the developed system, a real-life case study was used, in which, promising results were collected in regard to visualising the cost control data and understanding of the accumulative status of the project cost and schedule for team members.

A centralised cost management system (CCMS) for IPD is developed to enable the IPD cost structure as well as automating the risk-sharing/reward-sharing calculations. This system is linked with a web-based management system to display the output of proposed risk-sharing/reward-sharing models. Moreover, a novel grid is developed to show the project status graphically and to respect the diversity in core team members backgrounds. In addition, the case study showed that the proposed integration of different methods (ABC, EVM, BIM and web-based management system) is interoperable and applicable.

This research presents a comprehensive solution to the most revealed challenges in cost management practices in IPD implementation. The outcome of this research contributes to the body of knowledge through presenting new extensions of the EVM to be used with the IPD approach to calculate risk/reward. Moreover, the implementation of the proposed tools such as centralised cost management system (CCMS) and CCMS for IPD web system will enhance/foster the implementation of the IPD in conjunction with BIM process.