The current inability to timely ascertain cost and schedule outcomes in construction projects is highly detrimental to a construction industry characterized by endemic deviations. This study hypothesizes that organizational behaviors have a strong effect on the team’s ability to generate accurate cost and schedule predictions early, as opposed to late, in the project delivery process. A mixed-method research approach sequentially combined nonparametric statistical analyses of survey responses to quantify the influence of behaviors on predictability and research charrettes with subject matter experts to assess the findings and characterize practical applications. Multiple behavioral factors, such as those associated with the design of incentives or the reporting environment, were documented to have a significant effect on predictability. This study contributes with a novel combination of behavioral and predictability focus to the body of knowledge in forecasting. Such knowledge has been constrained within the silo of estimating techniques and, hence, without the consideration of behaviors and their impact on timeliness.

As a departure from the current state of practice, this study proposes to evaluate cost and schedule performance based on the early and accurate prediction of final outcomes, as opposed to the prevalent and reactive evaluation of final cost and schedule deviations at completion. Getting to know early in the delivery process the actual outcomes of a project enables project and corporate managers to undertake informed and proactive actions in a timely manner. To enable the assessment of predictability performance, a novel predictability index metric is proposed, investigated, and discussed. Based on the statistical analysis of data for 135 completed projects representing $29 billion in total installed costs, the predictability index measure is characterized and the major influencing factors on project predictability performance are unveiled. Also, actual case studies are discussed to illustrate the tangible benefits associated with the assessment of predictability performance to the project delivery process.

The occurrence of events affecting project performance cannot likely be eliminated, and hence their early identification and communication become critical to efficiently mitigate their impact. This research devised a taxonomy for the classification of events that can influence a project with 36 event types grouped in 10 event categories. The frequency of occurrence of events, and their impact on cost, schedule, and predictability performances were statistically determined based on information gathered from 135 recently completed projects. The statistical results demonstrate and quantify the long-held perception that the frequency of an event is often inversely proportional to its impact on project performance. In addition, qualitative evidence collected from subject-matter experts was leveraged to provide complementary insights and explanations beyond the statistical results. The results of this study are of interest to both practitioners and academics.

As female's participation in the US labor force continues to grow, there is a need to separate workplace injuries suffered by men and women. Statistics showed that women faced different types of injuries compared to men, especially on workplace violence. For example, women faced more fatality from workplace violence, and murders by personal acquaintances than men. The authors’ study shows that women faced different types of workplace hazards and the risks have been increasing over the past years. Some analysis suggests that some jobs better protect women and the others. The study also finds that there is a lack of understanding of the different safety issues each gender faces, and the lack of data or separation of data between genders. This paper focuses on the main events of fatal and nonfatal injuries among women in all industries, especially on homicides and assaults to shed lights on the gender gaps on safety issues and the need for more gender-specific research and data.