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Within earned value management, the cost performance index (CPI) and the critical ratio (CR) are used to generate the estimates at completion (EACs). According to the research in the 1990s, estimating the final contract’s cost at completion (CAC) using EAC_CR is a quicker predictor of the actual final cost versus using EAC_CPI. This paper aims to investigate whether this trend stills holds for modern department of defense contracts.

Accessing the Cost Assessment Data Enterprise (CADE) database, 451 contracts consisting of 863 contract line item numbers (CLINs) were initially retrieved and analyzed in three stages. The first replicated the work conducted in 1990s. The second stage entailed calculating 95 per cent confidence intervals and hypothesis tests regarding percentage accuracy of EACs for a contract’s final CAC. Lastly, regression analysis was conducted to characterize major, moderate and minor influencers on EAC reliability.

For modern contracts, EAC_CR aligns more with EAC_CPI and no longer demonstrates early accuracy of a contract’s final CAC. Contract percentage completion strongly reduced the per cent error of estimating CAC, while cost-plus-fixed-fee contracts and those with no work breakdown structure greater than Level 2 negatively affected accuracy.

To militate against optimism of early assessment of a contract's true cost.

This paper provides empirical evidence that EAC_CR behaves more like EAC_CPI with respect to modern contracts, suggesting that today’s contracts have relatively high SPI. Therefore, caution is warranted for program managers when estimating the CAC from contract initiation up to and slightly beyond the mid-point of completion.

The most common technique to determine the predicted final cost of a Department of Defense (DoD) acquisition contract, or the Estimate at Completion (EAC), involves the use of performance indices to adjust the EAC. Other methods including simple linear regression and time series analysis have been developed to predict the final cost, but these methods are not widely publicized or have limited applicability. As a potential remedy, this research utilizes the historical contract data reported in the Defense Acquisition Executive Summary database and provides to the analyst a set of five working multiple regression models. Useful over the life of the contract, they accurately predict the final cost of the average major weapons system contract using contractor Cost Performance Report data.

Earned Value Management (EVM) is widely used as a project performance measurement and forecasting technique. Nonetheless, it has not been fully explored in Pakistani construction industry; where conventional progress reporting methodology (CPRM) is being followed having certain confines. It reports only the financial progress of a project, expresses feeble association between the duration and cost of activities, and forecasts flawed schedule and completion cost. This research implements EVM on under-construction building projects in Pakistan, and compares its upshots with the projects' actual records and with the outcomes of CPRM.

To assess the implementation of EVM on building projects, a set of specific criteria was established. Work Breakdown Structure, Organization Breakdown Structure and Control Points were established. The study has compared the EVM metrics with CPRM outcomes on three under-study building projects, and has deliberated on their mutual differences as well as their relationship with actual cost and schedule performance. Monthly figures of actual spending and completed activities were periodically recorded and compared with planned values for status indication. The graphs were generated to observe the correlation between the results of EVM and CPRM. The data was then extrapolated to forecast the schedule and cost values at completion.

The study discovered that trends of EVM in quantifying the project's cost and schedule performance were strongly correlated and were closer to the actual progress. It has also verified the EVM's soundness in forecasting the cost and schedule, required for project's completion. Contrarily, CPRM metrics could not precisely visualize the current and future, cost and schedule performance.

The case study concludes that EVM's incorporation in progress reporting regime can revolutionize the assessment procedures in Pakistan by rightly indicating the project's current status as well as visualizing the future performance. The study's methodology can also be extrapolated in other countries having similar work environment and economic conditions.

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.

The purpose of this paper is to determine the project completion time and cost under non-deterministic conditions using interval gray numbers (IGNs).

The earned value management (EVM) method based on the IGN has been developed.

The EVM method based on the IGN has been verified by a numerical example that can be applied to construction projects.

The EVM method, based on the gray numbers, reduces the budget and time shortage risk. Also, using this method, the managers would not be restricted to provide very exact values in their progress reports in the non-deterministic conditions.

One notable and significant point in all projects during the execution process is to estimate the project completion time and cost. However, non-deterministic conditions for both planned and actual physical completion percentage of projects have not been considered for predicting the project completion time and cost in the literature. Therefore, the novelty of this paper is the prediction of project completion time and cost under non-deterministic conditions using IGN.

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.

Successful performance and execution of construction projects depend highly on a good project control system capable of tracking and reporting project status on a desired time interval. The purpose of this paper is to propose such a control system by integrating spreadsheet and Visual Basic for Application to produce a customized tracking system for Pipeline Relocation Programs under Engineering, Procurement and Construction Management (EPCM) contracts.

The project status reporting system (PSRS) proposed here was developed to produce a single page summary report that would include scope information, financial status, descriptive status updates and top-level task schedules. This information is retrieved from various sources and transformed further utilizing specific formulas and algorithm needed to compute the budget and schedule status of the pipe relocation project. A practical case study is used to demonstrate its unique application.

The system has successfully integrated project finance and schedule information into a central control hub. Financial and schedule performance of a project is tracked and monitored by the PSRS automatically.

The proposed system utilizes the powerful computing capability of MS Excel and the user-friendly VBA programming tool to customize the reporting needs of a project and program environment. The proposed system, whose functionality has been validated by the intended users, tries to achieve a balance between simplicity, accuracy and effectiveness for the flow of information at a much lower cost compared to the other readily available project control software.

The purpose of this study was to investigate the stability of the cost performance index (CPI) for environmental remediation projects as the topic is not addressed in the literature. CPI is defined as the earned value of work performed divided by the actual cost of the work, and CPI stability represents the point in time in a project after which the CPI varies by less than 20 percent (measured in different ways).

After collecting monthly earned value management (EVM) data for 136 environmental remediation projects from a United States federal agency in fiscal years 2012 and 2013, the authors used the nonparametric Wilcoxon signed-rank test to analyze CPI stability. The authors also used nonparametric statistical comparisons to identify any significant relationships between CPI stability and independent variables representing project and contract characteristics.

The CPI for environmental projects did not stabilize until the projects were 41 percent complete with respect to project duration. The most significant factors contributing to CPI stability were categorized into the following managerial insights: contractor qualifications, communication, stakeholder engagement, contracting strategy, competition, EVM factors, and macro project factors.

As CPI stability for environmental remediation projects has not been reported in the literature, this research provides new insights to help project managers understand when the CPIs of environmental remediation projects stabilize and which factors have the most impact on CPI stability.

The purpose of this paper is to investigate a set of risk-related factors influencing the earned value management (EVM) concept as an assessment technique in evaluating the progress of modern sustainable infrastructure construction projects.

A qualitative research approach has been adopted for identifying risk-related factors influencing EVM concept from a literature review and through interviewing industry personnel, followed by an inductive process to form sets of key factors and their measuring items.

EVM is a common method for assessing project performance. A weakness of this approach is that EVM assessment in its current form does not measure the impact of a number of project performance factors that result from the complexity of modern infrastructure construction projects, and thus does not accurately assess their impact in this performance. This paper discusses and explains a range of potential risk factors to evaluating project performance such as sustainability, stakeholder requirements, communication, procurement strategy, weather, experience of staff, site condition, design issues, financial risk, subcontractor, government requirements and material. In addition, their measuring items were identified.

This research assists projects managers to improve the evaluation process of infrastructure construction performance by incorporating a range of factors likely to impact on that performance and which are not included in current EVM calculations.

This research addresses the need to include in the EVM calculation a range of risk factors affecting the performance of infrastructure projects in Australia and therefore makes this calculation a more reliable tool for assessing project performance.