A System-of-Systems Model to Simulate the Complex Emergent Behavior of Vehicle Traffic on an Urban Transportation Infrastructure Network

Transportation agencies face escalating challenges in forecasting the traffic demand. Traditional prediction methods focused on individual transportation sectors and failed to study the inter-dependencies between the different transportation systems. Hence, there is a need for more advanced and holistic modeling techniques. To this end, this paper models and analyses an urban transportation system-of-systems incorporating seven various systems: population and GDP, CO2 emission, gasoline price and total vehicle trips, traffic demand, public and private transportation, transportation investment, and traffic congestion. Accordingly, this research simulates transportation networks as a collection of task-oriented systems that combine their resources to form a complex system with increased functionality. The goal of this paper is to understand the traffic complex behavior of urban transportation networks and to study the interdependencies between the different variables. The proposed framework could be implemented to any urban city, county, state, or country. The developed model incorporates a hybrid modeling approach that includes: logistic model, system dynamics, stochastic cellular automata, chaos theory, and Lotka-Volterra model. The final model is demonstrated using a case study. The contribution of this paper lies in modeling the transportation network as a dynamic system of systems rather than as static model as provided in previous studies

Modeling And Understanding Dispute Causation In The US Public-Private Partnership Projects

The partnership between the public and private sectors has led to a new and innovative way of delivering infrastructure projects that is referred to as public-private partnership (PPP). There are various benefits associated with PPP delivery methods including risk sharing, access to private funding, innovation, and flexibility, among others. Despite the proved benefits, contract conflicts and disputes are very common in PPP projects. While previous research studies examined the risks and the potential causes of conflicts in PPP projects, little-to-no research efforts were directed to study and model the interconnectivities between the different causes of conflicts in PPP agreements. To this end, the aim of this paper is to fill the gap in knowledge by providing a deeper understanding of the causalities or relationships between the different factors that cause disputes in PPP projects in the United States. The authors used a comprehensive analytical approach that involved three primary steps. First, 37 PPP case studies of infrastructure and construction projects were collected and analyzed using manual content analysis. Second, social network analysis was conducted to study the interdependencies between the different causal factors leading to disputes in PPP in general and in relation to Execution, Investment and Operation, and Third-Party Claims, in particular. Third, association rule analysis was conducted to identify key associations between the different causal factors that may trigger the three different types of PPP disputes. The findings showed that the key causes of disputes in PPP projects are related to (1) legal and regulatory, (2) payment and financial, and (3) poor management. While Execution-related disputes were found to be caused by complex interactions of causal factors, dispute causation of Investment and Operation-related and Third-Party Claims-related disputes seemed to be less simplistic. As such, the outcomes of this paper highlighted the important aspects required to avoid dispute occurrence in PPP projects. Ultimately, this paper contributes to the body of knowledge by providing directions for scholars and practitioners toward the aspects and interdependencies that require optimization and/or thorough consideration to avoid dispute occurrence and subsequently ensure successful implementation of PPPs

The Impact of Offsite Construction on the Workforce: Required Skillset and Prioritization of Training Needs

Offsite construction has showed great potential in addressing many of the industry\u27s problems. While multiple research efforts have been directed at examining different offsite construction aspects, few studies investigated the workforce-related aspects. Therefore, this study aims to address this knowledge gap by examining the impact of offsite construction on the workforce, as represented by the following five workforce categories: offsite, onsite, engineering and design, construction and fabrication, and administrative workforce. To this end, this paper (1) determined the impact of offsite construction on the skillset (reskilling or upskilling) and the demand (shrink or growth) for the offsite and onsite construction workforce occupations; (2) evaluated the impact of offsite construction on the technical and managerial skills of the engineering, construction, and administrative workforce occupations; and (3) identified the specific required skills that need to be incorporated into the offsite construction training programs for the workforce. The results showed that the skillsets for all offsite and onsite workforce occupations need to be upskilled. While the demand for the offsite construction workforce will increase, the demand for around 79% of the onsite workforce occupations will decrease. The findings also reflected that a total of 20 main skills are needed for the offsite construction engineering and design workforce, a total of 24 key skills are needed for the construction and fabrication workforce involved in offsite construction operations, and 22 skills are needed for the offsite construction administrative workforce. This study adds to the body of knowledge by helping offsite construction industry practitioners in workforce planning and management, in the prioritization of training needs and programs, and in identifying the required skillset to improve the quality of the workforce involved in the offsite construction operations

Quantification of the State of Practice of Offsite Construction and Related Technologies: Current Trends and Future Prospects

Although some researchers and practitioners have perceived that the current reliance on offsite construction methods is high, other studies have hypothesized that the use of offsite construction techniques is still considered to be somehow limited. To this end, this paper aims to quantify the state of practice of offsite construction in terms of current trends and future prospects for the overall industry as well as the following main sectors: industrial, building and commercial, and infrastructure. First, a questionnaire was formed, pilot-tested, distributed, and completed by 100 construction practitioners. Second, the questionnaire\u27s internal and external validity and reliability were examined using statistical analysis. Third, the research findings were validated. The results showed that the future offsite construction operations will be different from the current operations by shifting from single-trade fabrication to modularization, shifting from customized offsite construction components to standardized offsite construction components, shifting from permanent offsite construction structures to relocatable or portable offsite construction structures, and shifting the reliance on single-skilled labor to multiskilled labor. In addition, 87% of industry practitioners perceive that the future offsite construction growth rate in the coming decade will be higher than that of the previous decade. This research also showed that offsite construction will become the norm rather than the exception because (1) the current average offsite construction percentage of 33.64% will substantially grow to reach an average of 54.9% in the future, (2) the offsite construction industry will grow 4.33 times, on average, in the coming decade, (3) companies are planning to increase their offsite construction utilization rate by an average of 5.03-fold, and (4) the offsite construction automation percentage will increase by 7% in the future. The research outcomes also provided guidance on the key technologies that the industry shall currently invest in and consider leveraging in the future

Key Factors Affecting Labor Productivity in Offsite Construction Projects

Offsite construction has been shown to possess many advantages and benefits in dealing with the construction industry\u27s challenges, which include poor labor productivity. Nevertheless, all previous productivity-related research studies have focused mainly on factors impacting labor productivity in traditional stick-built construction methods. This paper filled this knowledge gap by following a multistep interrelated research methodology. First, a research team of 19 construction professionals and academics developed and distributed an industry survey to (1) quantify the likelihood of occurrence and relative impact of risk factors that adversely impact labor productivity in offsite construction projects; (2) identify and prioritize key risk factors that adversely affect labor productivity in offsite construction operations; and (3) examine how labor productivity risk factors are perceived by various project stakeholders. Second, different statistical analysis tests and methods (i.e., internal and external reliability, statistically significant differences, clustering analysis, and concordance analysis) were used to critically analyze the results and draw conclusions. Based on a total of 100 responses and 20 labor productivity risk factors, the findings reflected that the top five risk factors adversely affecting labor productivity in offsite construction projects included (1) unskilled labor and improper workforce training and development; (2) poor logistics; (3) errors, omissions, and rework; (4) work area congestion and overcrowding; and (5) insufficient coordination. Also, the findings indicated that labor productivity factors can be clustered into two groups: factors with high overall risk and factors with low overall risk on offsite construction labor productivity; 80% of the risk factors were found to fall into the first category. The results of this study also reflected the need for offsite construction companies and industry practitioners to carefully establish mitigation plans and corrective actions for the identified key risk factors adversely affecting offsite construction labor productivity. This study adds to the body of knowledge by exploring and ranking productivity factors in offsite construction projects. Ultimately, this study will help the industry and research communities better understand factors affecting offsite construction labor productivity, more effectively direct future efforts to enhance labor performance, and devise productivity improvement strategies

Management of Change Orders in Infrastructure Transportation Projects

The Illinois Department of Transportation (IDOT) will handle many upcoming projects due to the recent statewide infrastructure strategic plan and the fast-track efforts affecting many infrastructure projects amid COVID-19. Nevertheless, many change orders are anticipated to occur on IDOT\u27s projects. Thus, this paper examines the proper contractual management of changes within IDOT infrastructure transportation projects by following a research method based on the integration between a desktop analysis and a focus group analysis. The desktop analysis involved collecting information and data from existing resources, case studies, and documents related to change orders. The focus group analysis involved consulting with change order experts to verify that the outcome of each research step is useful and to validate the final outcomes of the paper. Based on 50 documented major change orders in IDOT projects and three litigated cases, two findings are provided. First, the top causes for key change orders within IDOT projects include contract administration, allowable contingencies, quantity omission or error, differing site conditions, and design changes. Second, the most critical change order related challenges within IDOT\u27s infrastructure projects include approval procedures, compensation considerations, and applicable laws. This paper offers flowcharts, synopsis of opportunities and risks, and a checklist to help the contracting parties better administer change orders. Ultimately, the contributions of this paper to the practice include: (1) minimizing the number and amount of change orders, (2) helping the contracting parties better understand how their individual responsibilities contribute to the proper processing and management of changes and variations, (3) offering contractors the ability to visualize the different steps involved in the approval of change orders, (4) assisting the project stakeholders in identifying change order-related areas for improvement, and (5) allowing project owners to better mitigate, manage, and administer the contractual aspects of change orders

Evaluation and Prediction of the Hazard Potential Level of Dam Infrastructures Using Computational Artificial Intelligence Algorithms

Failures of dams cause immense property and environmental damages and take thousands of lives. As such, the goal of this paper is to evaluate and predict the hazard potential level of dams in the US using a comparative approach based on computational artificial intelligence (AI) algorithms. The research methodology comprised data collection from the National Inventory of Dams (NID); data preprocessing; data processing; and model selection and evaluation. To this end, the authors: (1) identified the best subset of variables that affect the prediction of the hazard potential level of dams in the US; (2) investigated the performance of two AI computational algorithms: artificial neural networks (ANNs) and k-nearest neighbors (KNNs) for the evaluation and prediction of the hazard potential levels of US dams; and (3) developed a decision support tool that could be used by the agencies responsible for the management of dams in the US with the capability to predict the hazard potential with good accuracy. The obtained results reflected that the ANN algorithm yielded better accuracy compared to the KNN algorithm. In addition, the conclusions indicated that 19 variables pertaining to dams in the US could affect the hazard potential level of dams. The output is a decision support system that is able to evaluate the hazard potential of dams with a prediction accuracy of 85.70%. This study contributes to the management in engineering’s body of knowledge by devising a data-driven framework that is valuable for dams’ owners and authorities. Ultimately, the developed computational AI algorithm could be used to evaluate and predict the hazard potential level of US dams with good accuracy while minimizing the efforts, time, and costs associated with formal inspection of the dams

Impact of Dynamic Workforce and Workplace Variables on the Productivity of the Construction Industry: New Gross Construction Productivity Indicator

Construction productivity is the industry\u27s predominant determinant of performance. Although the construction industry periodically provides large amount of data, existing studies have not fully exploited such data sets, especially relating to the overall productivity of the construction industry rather than labor productivity. This paper addresses this critical knowledge gap by statistically examining and modeling the causalities between different dynamic workforce and workplace variables and the productivity of the entire construction industry. Multivariate time-series data between 2006 and 2019 were collected for the productivity of the construction industry and 11 dynamic workforce and workplace variables: job openings, job hires, turnover or job separations, total compensation, gross job gains, gross job losses, average hourly earnings, fatalities, occupational injuries and illnesses, gross domestic product, and unemployment rate. Statistically significant relationships and causalities were examined between the response variable - productivity of the construction industry - and these 11 variables. A vector autoregression (VAR) framework was developed to model the temporal variations in the productivity of the construction industry. The developed VAR model was validated by predicting the construction productivity for the 2016-2019 period an acceptable mean average percentage error of 5.13%. Based on the findings, the paper concludes that (1) all considered dynamic workforce and workplace variables, except job openings, statistically cause fluctuations in the construction productivity; (2) the new concept of gross construction productivity is justified statistically and should be implemented in the construction industry; (3) the gross construction productivity is an additional valuable information that construction companies should consider to make different insightful and well-educated industry-related decisions; (4) the health of the construction industry needs to be studied based on the productivity of the industry as a whole rather than based on labor productivity alone; and (5) the construction industry should move toward the development of a notion of gross construction productivity indicator used to measure, evaluate, and predict the performance of the entire industry. Ultimately, this paper proposes a new indicator or index for gross construction productivity. The outcomes of this paper add to the body of knowledge by providing a better understanding of the impact of different dynamic workforce and workplace variables on the construction productivity and by offering a new concept called gross construction productivity

Enhancing the Knowledge of Construction Business Failure: A Social Network Analysis Approach

The failure of construction companies is quite crucial because it results in unfinished projects and responsibilities that in turn result in many losses to governments, economies, owners, creditors, and surety companies. Previous research on the prediction of construction business failure utilized insolvency causes that were either arbitrary or based on the availability of data. Many scholars have shown the absence of, and need for, a holistic framework for the identification of the causes of construction business failure. As such, this paper reviews previous literature incorporating construction business failure applications, with the objective of identifying existing knowledge, current gaps, and needed future research directions on the different failure factors in a comprehensive approach. To this end, the authors (1) performed a meta-Analysis of previous research work for a 30-year period spanning from 1988 to 2018; (2) identified and defined failure factors that impact the business operations of construction firms; and (3) utilized social network analysis to quantitatively identify the overlooked and missing construction business failure factors. Research results indicate that there are 20 factors that could collectively contribute to business failures of construction firms. It is also shown that there is a dire need for future research to better explore the impacts of some understudied critical factors, including the effect of inadequate company organizational structure and human capital on construction business failure. Another important finding is the absence of models that include a holistic incorporation of all 20 construction business failure factors. The findings herein are a significant contribution to the body of knowledge on construction business failure because they integrate the outcomes of previous works and use them to provide robust foundations for knowledge advancement. The presented guidelines are believed to close areas where an abundance of research work occurs and to unveil areas where additional research is necessary

Guidelines for Responding to COVID-19 Pandemic: Best Practices, Impacts, and Future Research Directions

Due to the novelty of coronavirus disease 2019 (COVID-19) and the lack of measurable data, no enough research studies have been conducted to provide guidelines for responding to the coronavirus pandemic. This paper addresses this critical knowledge gap through a methodology comprising two main steps. The first step involved reviewing the updated industry best practices developed by various organizations and government entities. The second step involved investigating the impacts of the coronavirus based on the available resources and expert opinions, which also were used to develop a synopsis of emerging research topics. This paper provided various beneficial outcomes and findings. First, the paper presents a concise and integrated resource of COVID-19-related best practices for the construction industry. Second, the paper determined that the pandemic is perceived to have short- and long-term impacts - including negative and positive consequences - on four main facets: (1) workforce-related issues; (2) project and workplace considerations; (3) procurement and supply chain implications; and (4) contractual, legal, and insurance aspects. Third, the paper provides future research streams and directions that could be examined by future studies to help in the transition toward the new normal. Ultimately, this paper adds to the body of knowledge by offering practitioners and researchers guidelines for responding to the COVID-19 pandemic in the construction sector