Risk,Process Maturity,and Project Performance: An Empirical Analysis of US Federal Government Technology Projects

In recent years, there has been increasing pressure on the US federal government to reduce spending and improve the management of its technology projects. Mitigating the adverse impact of risks on the performance of these projects presents a significant challenge for its stakeholders. Our research examines this challenge in two steps. First, we identify and define a set of salient risks in federal technology projects—specifically, complexity risk and contracting risk in the planning process, and execution risk in the execution process. Next, we investigate whether higher levels of process maturity, assessed by the Capability Maturity Model Integration (CMMI) framework, mitigate the negative effect of project risks on project performance. The analysis of time‐series data collected from 82 federal technology projects across 519 quarterly time periods indicates that each of the three types of risks has a significant negative effect on project performance. This finding highlights the practical significance of managing these risks in the federal technology project context. Further, we find that increasing levels of process maturity attenuate the negative effect of project risks on the performance of federal technology projects. However, the attenuation effects are consequential only at high levels of project risks; at low levels of project risk, increasing levels of process maturity can adversely affect project performance. To demonstrate the financial implications of increasing process maturity levels in federal technology projects, we examine the magnitude of project cost savings (and overruns) across different levels of CMMI and project risks. In summary, our study contributes to the sparse literature on public sector operations by addressing the understudied context of federal technology projects, and provides a nuanced examination of the implications of process maturity in managing the risk to performance relationship in such projects.     

The Tradeoffs of Inclusionary Zoning: What Do We Know and What Do We Need to Know?

Inclusionary zoning (IZ), a controversial planning tool for supplying affordable housing, grew significantly during the 2000s' housing boom in the USA. We review the resultant scholarly literature on IZ. Our key reading is that IZ can include both tradeoffs and practical efforts to address them. There is also a need for additional research. More specifically, we find that IZ programs (i) have many components and vary considerably; (ii) can increase affordable housing production and social integration, but there can be a tradeoff between these goals; and (iii) can have slight adverse market effects, but cost-offsets can help mitigate the outcomes. Finally, we discuss the need for more research, particularly in-depth case studies and make suggestions.     

The fallacy of the five million women: A re-estimate

Explicit policy to control fertility in the United States to date has focussed on the “unmet need” for contraceptive services in 1966 among an estimated five million poor and near-poor women. This paper reestimates the number of women in need of contraceptive services by disaggregating (on the basis of tabulations from the Current Population Surveys for 1966 and 1967, and the 1965 National Fertility Study) all poor and near-poor women into 54 subgroups differentiated by age, marital status, religion, and color. Data from the 1965 National Fertility Study, and from other studies, are then used to estimate for each subgroup deductions for sterility, pregnancy, waiting time for conception, and negative attitudes toward and current use of contraception. The residual number of women who both want and require contraceptive services, but do not have them, is estimated to be 1.2 million, rather than 4.6 million. The fact that the re-estimate takes into account both existing contraceptive practice and negative attitudes toward family limitation accounts for much of the difference between it and the original figure.     

Comparison of some common ratio estimators using pitman measure of nearness

In this article we compare some common ratio estimators for estimating the population total of a given characteristic. The sampling schemes considered are simple random sampling (S.R.S.) and S.R.S.under stratification. The comparisons are made using the Pitman Nearness criterion under the model-based approach. The error term is assumed normal with mean zero and variance σg(x). The function g(x) is a known function of the auxiliary variable x. Special interest is on the cases of g(x) =l and x. The result is found the same as that using MSE criterion, although the PN is very different from the MSE intrinsically.     

Estimation of Fuel Coefficients of Cement Production: A Fixed-Effects Approach to Nonlinear Regression

Fuel coefficients of cement production—one for each process of production—are estimated by explicitly accounting for the multiple-kiln structure of cement plants. Unobserved heterogeneity across plants is found to be significant. Furthermore, since the estimable model is nonlinear in exogenous variables and parameters, a fixed-effects estimator for nonlinear regression is used to obtain the estimates.     

Preliminary test estimators in double sampling with two auxiliary variables

An attempt has been mads to suggest some estimators for population mean in double sampling with two auxiliary variables., alternative to the usual regression estimator. When the experimenter has partial Information about the mean of the auxiliary variable or variables, preliminary test estimators can be used. The bias, mean square error, relative efficiency and optimum allocation of sample sizes are obtained for the suggested estimators.     

Forecasting models for developing control scheme to improve furnace run length

In petrochemical industries, the gaseous feedstock like ethane and propane are cracked in furnaces to produce ethylene and propylene as main products and the inputs for the other plant in the downstream. A problem of low furnace run length (FRL) increases furnace decoking and reduces productivity along with the problem of reducing life of the coil. Coil pressure ratio (CPR) and tube metal temperature (TMT) are the two most important performance measures for the FRL to decide upon the need for furnace decoking. This article, therefore, makes an attempt to develop the prediction models for CPR and TMT based on the critical process parameters, which would lead to take the necessary control measures along with a prior indication for decoking. Regression-based time series and double exponential smoothing techniques are used to build up the models. The effective operating ranges of the critical process parameters are found using a simulation-based approach. The models are expected to be the guiding principles eventually to increase the average run length of furnace.     

Likelihood‐based inferences about the mean area under a longitudinal curve in the presence of observations subject to limits of detection

Comparison of groups in longitudinal studies is often conducted using the area under the outcome versus time curve. However, outcomes may be subject to censoring due to a limit of detection and specific methods that take informative missingness into account need to be applied. In this article, we present a unified model‐based method that accounts for both the within‐subject variability in the estimation of the area under the curve as well as the missingness mechanism in the event of censoring. Simulation results demonstrate that our proposed method has a significant advantage over traditionally implemented methods with regards to its inferential properties. A working example from an AIDS study is presented to demonstrate the applicability of our approach. Copyright © 2015 John Wiley & Sons, Ltd.