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Delineating where stability occurs in a contract provides the window of opportunity for procurement officials to positively affect cost and schedule outcomes. While the concept of a Cost Performance Index (CPI) "stability rule" has been routinely cited by Earned Value Management (EVM) authors since the early 1990's, more recent research questions the veracity of this stability rule. This paper resolves the controversy by demonstrating that the definition of stability matters. We find a morphing of the stability definition over time, with three separate definitions permeating the literature. Next, an analysis of Department of Defense contracts for both cost and schedule stability properties finds that the veracity of the stability rule is intricately tied to the definition used.

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.

Selecting suitable and competent partners is an important prerequisite to improve the performance of collaborative product innovation (CPI). The purpose of this paper is to propose an integrated multi-criteria approach and a decision optimization model of partner selection for CPI from the perspective of knowledge collaboration.

First, the criteria for partner selection are presented, considering comprehensively the knowledge matching degree of the candidates, the knowledge collaborative performance among the candidates, and the overall expected revenue of the CPI alliance. Then, a quantitative method based on the vector space model and the synergetic matrix method is proposed to obtain a comprehensive performance of candidates. Furthermore, a multi-objective optimization model is developed to select desirable partners. Considering the model is a NP-hard problem, a non-dominated sorting genetic algorithm II is developed to solve the multi-objective optimization model of partner selection.

A real case is analyzed to verify the feasibility and validity of the proposed model. The findings show that the proposed model can efficiently select excellent partners with the desired comprehensive attributes for the formation of a CPI alliance.

Theoretically, a novel method and approach to partner selection for CPI alliances from a knowledge collaboration perspective is proposed in this study. In practice, this paper also provides companies with a decision support and reference for partner selection in CPI alliances establishment.

We analyze fluctuations in inflation and the nominal exchange rate under optimal monetary policy with local currency pricing by developing two-country DSGE local currency pricing and producer currency pricing models. We estimate our models using Bayesian techniques with Japanese and US data, and calculate impulse response functions. Our estimation results show that local currency pricing is strongly supported against producer currency pricing. From the estimated parameters, we show that completely stabilizing consumer price index inflation is optimal from the viewpoint of minimizing welfare costs and that completely stabilizing consumer price index inflation is consistent with completely stabilizing the nominal exchange rate.

This research paper aims to examine the Dutch disease syndrome in the more diversified economies of the Economic and Social Commission of Western Asia (ESCWA).

An econometric model was applied to observe the impact of this syndrome on the different sectors of the economy. A regression analysis examined the relationship between this inflow of capital and lagging sector of these economies. Similarly, Granger‐causality was applied to determine the direction of causality between the variables.

Results indicate that worker remittances, foreign grants, and oil revenues are the main factors behind the Dutch syndrome in the ESCWA region. Channeling remittances through investments, subsidizing output of lagging sectors, and imposing higher import tariffs are recommended to reduce the negative externalities of the Dutch disease.

It is to be noted that the paper has some limitations since data/statistics for the ESCWA region may not be totally reliable.

The paper sheds some light on the impact of this syndrome in the developing economies of Western Asia.

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 a project monitoring and control technique that enables the forecasting of a project's duration. Many EVM metrics and project duration forecasting methods have been proposed. However, very few studies have compared their accuracy and stability.

This paper presents an exhaustive stability and accuracy analysis of 27 deterministic EVM project duration forecasting methods. Stability is measured via Pearson's, Spearman's and Kendall's correlation coefficients while accuracy is measured by Mean Squared and Mean Absolute Percentage Errors. These parameters are determined at ten percentile intervals to track a given project's progress across 4,100 artificial project networks with varied topologies.

Findings support that stability and accuracy are inversely correlated for most forecasting methods, and also suggest that both significantly worsen as project networks become increasingly parallel. However, the AT + PD-ESmin forecasting method stands out as being the most accurate and reliable.

Implications of this study will allow construction project managers to resort to the simplest, most accurate and most stable EVM metrics when forecasting project duration. They will also be able to anticipate how the project topology (i.e., the network of activity predecessors) and the stage of project progress can condition their accuracy and stability.

Unlike previous research comparing EVM forecasting methods, this one includes all deterministic methods (classical and recent alike) and measures their performance in accordance with several parameters. Activity durations and costs are also modelled akin to those of construction projects.

The purpose of this paper is to examine the level of theory building in public procurement by reviewing and classifying manuscripts published in the Journal of Public Procurement (JoPP) from 2001 to 2016.

The articles are divided into four important periods: discovery, agenda setting, embracing and expansion and consolidation. The articles are classified according to a hierarchical level of theory building composed of six levels: rapporteurs, reporters, testers, qualifiers, builders and expanders.

Key findings indicate that public procurement, in light of JoPP publications from 2001 to 2016, is at the tester level. There is also increase in the classification of articles with high level of theoretical contribution over time.