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Although numerous studies have examined alternative project delivery methods (APDMs), most of these studies have focused on the relationship between these methods and improved project performance. Limited research identifies how to successfully add these methods within architectural, engineering and construction (AEC) organizations. The purpose of this paper is to identifying organizational change management (OCM) practices that, when effectively executed, lead to increased success rates of adopting APDMs in owner AEC organizations.

Seven OCM practices were identified through a comprehensive literature review. Then, through a survey of 140 individuals at 98 AEC organizations, the relationships between OCM practices and organizational adoption of APDMs were established.

The findings indicate that OCM practices with the strongest relationship to successful APDM adoption are realistic timeframe, effective change agents, workloads adjustments, senior-leadership commitment and sufficient change-related training.

Adopting APDMs can be extremely difficult and requires significant organizational change efforts to ensure the change is a success. Organizations that are implementing APDMs for the first time should consider applying the OCM practices that this study identifies as most related to successful APDM adoption.

This study contributes to the existing body of knowledge by identifying the OCM practices that are most significantly associated with successfully adopting APDMs.

Construction organizations' investment in effective talent-development programs is a key strategy in attracting, developing and retaining staff. Such programs are especially important given the current challenges in the construction workforce, including labor shortages, an aging workforce, generational differences in the workforce, supply chain disruptions and the need to effectively train staff in the skills that are essential in a constrained labor environment. To address these challenges, this study proposes a performance measurement strategy that construction companies can use as input to design their talent development programs.

The strategy intends to assess the performance of project managers and develop criteria that define categories of their performance, including the top performers' category. This enables construction organizations to provide each project manager with individualized training that addresses areas of weakness and in turn, develops the skills that correspond with being top performers. The proposed strategy was developed and tested by surveying the immediate supervisors of 187 project managers working for general and specialty contractors in the United States. Principal component analysis was used to develop a single performance construct from seven performance criteria.

This construct was used to organize the project managers into the categories of top, above-average and below-average performers. According to the findings, top-performing project managers have well-rounded skills in the areas of leadership, communication, technical proficiency and overall job knowledge.

The outcomes of this study can help construction organizations focus their talent-development programs on the skills most associated with PMs being top performers.

This study provides construction organizations with a comprehensive performance-measuring construct to focus their talent-development programs on the skills most associated with top-performing project managers. Researchers can use this study as a foundation for further understanding how performance is related to various construction professions.

The purpose of this study is to describe how the University of Minnesota's capital program implemented risk management metrics on 266 construction projects and to present the results of the risk metrics.

The implementation of Weekly Risk Reports (WRR) on the university construction projects captured information on the internal and external efforts related to minimizing project risks. The report implemented captured project risks, management plans, cost changes and schedule delays.

Findings reveal that the university was able to effectively capture project risk metrics through the WRR. The risk metrics identified the risks categories that impacted the 266 project costs and schedules. Through these findings, the university has a better understanding of how their internal stakeholders create the greatest risk to impacting the project cost and schedule. This paper presents the risk impacts collected from the 266 projects.

A complete analysis of the risk metrics was limited in this research due to the extensive measurements collected. Future analysis will provide additional findings from the risk information.

The paper presents both the implementation and the risk management measurements used within a capital program of a major university to provide understanding of the common risks that are involved with capital projects.

This paper aims to quantify the impact of craft worker shortage on construction project safety performance.

A database of 50 North American construction projects completed between 2001 and 2014 was compiled by taking information from a research project survey and the Construction Industry Institute Benchmarking and Metrics Database. The t-test and Mann-Whitney test were used to determine whether there was a significant difference in construction project safety performance on projects with craft worker recruiting difficulty. Poisson regression analysis was then used to examine the relationship between craft worker recruiting difficulty and Occupational Safety and Health Administration Total Number of Recordable Incident Cases per 200,000 Actual Direct Work Hours (TRIR) on construction projects.

The result showed that the TRIR distribution of a group of projects that reported craft worker recruiting difficulty tended to be higher than the TRIR distribution of a group of projects with no craft worker recruiting difficulty (p-value = 0.004). Moreover, the average TRIR of the projects that reported craft worker recruiting difficulty was more than two times the average TRIR of projects that experienced no craft recruiting difficulty (p-value = 0.035). Furthermore, the Poisson regression analysis demonstrated that there was a positive exponential relationship between craft worker recruiting difficulty and TRIR in construction projects (p-value = 0.004).

The projects used to construct the database are heavily weighted towards industrial construction.

There have been significant long-term gains in construction safety within the USA. However, if recent craft shortages continue, the quantitative analyses presented herein indicate a strong possibility that more safety incidents will occur unless the shortages are reversed. Innovative construction means and methods should be developed and adopted to work in a safe manner with a less qualified workforce.

The Poisson regression model is the first model that quantifiably links project craft worker availability to construction project safety performance.

The purpose of this paper is to examine the relationships between the higher moments of returns (realized skewness and kurtosis) and subsequent returns at the industry level, with a focus on both empirical predictability and practical application via trading strategies.

Daily returns for 48 US industries over the period 1970–2019 from Kenneth French’s data library are used to calculate the higher moments and to construct short- and medium-term single-sort trading strategies. The analysis adjusts returns for common risk factors (market, size, value, investment, profitability and illiquidity) to confirm whether conventional asset pricing models can capture these relationships.

Past skewness positively relates to subsequent industry returns and this relationship is unexplained by common risk factors. There is also a time-varying effect in which the predictive role of skewness is much stronger over business cycle expansions than recessions, a result consistent with varying investor optimism. However, there is no significant relationship between kurtosis and subsequent industry returns. The analysis confirms robustness using both value- and equal-weighted returns.

The calculation of realized moments conventionally uses high-frequency intra-day data, regrettably unavailable for industries. In addition, the chosen portfolio-sorting method may omit some information, as it compares only average group returns. Nonetheless, the close relationship between skewness and future returns at the industry level suggests variations in returns unexplained by common risk factors. This enriches knowledge of market anomalies and questions yet again weak-form market efficiency and the validity of conventional asset pricing models. One suggestion is that it is possible to significantly improve the existing multi-factor asset pricing models by including industry skewness as a risk factor.

Given the relationship between skewness and future returns at the industry level, investors may predict subsequent industry returns to select better-performing funds. They may even construct trading strategies based on return distributions that would generate abnormal returns. Further, as the evaluation of individual stocks also contains industry information, and stocks in industries with better performance earn higher returns, risks related to industry return distributions can also shed light on individual stock picking.

While there is abundant evidence of the relationships between higher moments and future returns at the firm level, there is little at the industry level. Further, by testing whether there is time variation in the relationship between industry higher moments and future returns, the paper yields novel evidence concerning the asymmetric effect of stock return predictability over business cycles. Finally, the analysis supplements firm-level results focusing only on the decomposed components of higher moments.

The purpose of this paper is to investigate the association between unemployment insurance (UI) benefits and firms’ future performance as well as the association between UI benefits and volatility of firms’ future performance.

Quantitative analyses are used to perform empirical testing, and the variables in this study have been selected from previous literature. Empirical data consists of UI benefits data published from 2003 to 2012 on the US Department of Labor website, accounting data from Compustat, and stock return data from CRSP.

Unemployment benefits are positively associated with firms’ future earnings and cash flows. Also, unemployment benefits are negatively associated with volatility of firms’ future earnings and cash flows. Finally, the positive association between unemployment benefits and firms’ future performance is more pronounced for firms with larger changes in labor force, and the negative association between unemployment benefits and volatility of firms’ future performance is more pronounced for firms with higher labor force volatility and capital structure volatility.

To the extent that other correlated omitted variables exist, the readers are asked to interpret the findings in this paper with caution.

This study contributes to prior literature on labor economics, finance, and accounting. The findings may be of interest to academic researchers and policy makers.

Data from the 1984 Survey of Income and Program Participation are linked to longitudinal records from the Social Security Administration to examine the relationship between the long-term unemployment that prime-aged (ages 25–55) male workers experienced around the time of the 1980–1982 twin recessions with earnings, receipt of either Disability Insurance or Supplemental Security Income (DI-SSI) benefits, and mortality. Separate estimations are made for those who voluntarily and involuntarily left employment and the combined sample of these two groups. We find that 20 years later, long-term joblessness was associated with significantly lower earnings and higher likelihoods of the receipt of DI-SSI benefits as well as mortality.

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