Search

In the transportation design-build (DB) industry, the responsibility of the design is transferred to the design-build team from the owner. One of the critical issues for state departments of transportation (DOTs) is design professional liability. To cover designers’ professional negligence, design professional liability insurance (DPLI) should ensure satisfactory coverages in DB projects for state DOTs. The objective of this study is to identify the variability of the DPLI policy requirements that are found in DOT DB projects. This study conducts content analysis and comparative analysis of 15 DOT archival data that consist of design-build agreements and requests for proposals. This study determines six common elements of DPLI requirements: (1) types of DPLI, (2) indemnifying party, (3) coverage amount, (4) extended reporting period, (5) retroactive date, and (6) supplemental policies. The results show that these DPLI policy elements depend on the available customizable options and requirements. Some DOTs tend to explicitly state all six elements, while other DOTs require a few of these six elements. The findings also explain the significant characteristics and implementation of each policy element. Its findings contribute to a better understanding of DPLI requirements and provide opportunities for decision-makers to reduce issues related to insurance coverage gaps.

The primary objective of this research is to characterize job market trends and identify patterns in Inclusion, Diversity, Equity, and Accountability (IDEA) and Race, Ethnicity, and Language (REAL) in the construction industry. Workforce IDEA and REAL are major concerns in the construction industry. The construction industry has challenges of embracing the workforce IDEA and REAL such as age, language, sexual orientation, and disability. IDEA and REAL have impacts on hiring as well. However, there is a lack of data and research related to IDEA and REAL for the construction industry. In this respect, this research collects construction job market data using web scraping. Text mining techniques are then applied to detect words related to IDEA, REAL, job types, and wage changes during the web scraping period. We devise a new data-driven text mining model including the web scraping technique to provide market trends and identify patterns related to IDEA and REAL in the construction industry. This research will contribute to the body of knowledge of capturing the data regarding IDEA and REAL by harvesting large-scale data across disciplines in a searchable and organized structure.

Cost estimates for Lump Sum (LS) pay items are typically completed using historical information from similar projects or knowledge from subject matter experts. Since LS pay items are mainly unitless and do not have a consistent relationship with their quantities, it imposes a critical burden on estimating accurate prices of LS pay items for highway projects. State highway agencies (SHAs) often encounter significant variations in prices of LS pay items throughout the project development process. Inaccuracies of prices of LS pay items can cause significant cost escalation, project delay, and scope change. However, the current literature indicates that few studies have focused on exploring factors affecting the prices of LS pay items for highway projects. Thus, the overarching objective of this study is to identify and analyze factors affecting the prices of LS pay items used for highway projects. This study analyzed Traffic Control Lump Sum (TCLS) and Grading Complete Lump Sum (GCLS) pay items collected in the state of Georgia, using statistical analysis. This study identified the relationships between the prices of the LS pay items and important project-related factors, such as construction cost, estimated contract time, and major projects. The findings of this study help SHAs estimate more accurate prices of LS pay items and develop more accurate construction costs for highway projects.

The objectives of this research are to analyze empirical Right of Way (ROW) acquisition process records to quantitatively determine key project features influencing ROW acquisition durations and examine the spatial variation of the features’ effects. This research used database of 495 projects that finished ROW acquisition process between the year 2010 and 2019 by Georgia Department of Transportation. The multiple linear regression is performed to identify significant variables that impact acquisition duration. Then, the geographically weighted regression analysis is conducted to examine spatial variations of variables’ effects across the geographical locations. Acquisition durations tend to increase as the number of parcels and the average cost estimate per parcel increases, the design is completed by consultant or regional office, and the type of work is roadway and widening projects. The analysis results indicate that variables’ effects vary throughout areas of the state. Therefore, ROW practitioners should consider giving different weights to project features depending on the project’s location when setting the ROW acquisition schedule to reduce risks of schedule delays and cost overruns. It is anticipated that findings of this research will provide insights to ROW practitioners on how to improve ROW acquisition timeline estimations and better manage the risks.

PurposeIn classical perspective, projects under a certain size are not feasible for P3. However, there is an emerging trend on using P3 to deliver projects which are frequently at small- to medium- size to meet ever-increasingly complex social needs, including enhancing lifecycle performance of existing facilities, designing and building for resilience and sustainability, ensuring cost effectiveness of public spending and fostering innovation. In contrast with the increasing implementation, small and medium P3s, especially those in the United States, receive little attention in existing studies. This study aims at answering the question: in the context of US, what features of those small- to medium- sized P3s with success records enable the selection of P3 as delivery method.Design/methodology/approachBy critically reviewing the literature, this study synthesizes and discusses the challenges in classical perspective. The authors use a framework drawn from the transaction cost to propose two types of enabling features that could contribute to the success of small and medium P3s. The proposed enabling features are supported by case study of twelve identified small- to medium- sized P3s which have reached financial closure as of 2018 in the United States.FindingsThe results show how the identified enabling opportunities have been used in these cases to enhance the viability of the P3 model in the infrastructure market. The two types of features are high tolerance enabler explained by the expectations on indirect and non-monetary compensations, and cost reduction enablers including: (1) being in the sectors with well-established traditions on using private investments; (2) having developers with expertise on infrastructure finance; (3) being in the jurisdictions with favorable legislative environment and (4) having less-uncertain future project revenue.Originality/valueThis study, for the first time, critically examines the enabling features of the P3 model for delivering small and medium infrastructure projects in the United States. This research sheds light on the credibility and viability of small- to medium- sized P3 and increases the confidence in policy makers to promote this model.

The objective of this project is to identify current management practices developed by various state departments of transportation (DOTs) for right of way (ROW) acquisition and explore poss...

Megabridge projects are those that cost more than $500 million to complete from the planning stages through completion of construction. In the evolving field of transportation design–build ...

Transportation infrastructure around the world is under pressure to perform with ever-changing climate scenarios, unpredictable disasters, and stress on resources stemming from rapid urbanization and population growth. Current approaches to developing resilience applied to the transportation system focus primarily on engineering resilience and do not explicitly deal with deep uncertainties arising from climate change. This paper reviews adaptation, a critical aspect of a resilient system in an uncertain and changing environment, as applied in the transportation resilience literature. It compares and contrasts the status of adaptive resiliency in transportation with that in other fields to highlight gaps and research opportunities. The paper then presents Dynamic Adaptive Planning (DAP) as a method for dealing more effectively with deep uncertainty in decision making and offers an approach that combines economic analysis with DAP to enhance decision making under external uncertainties, such as natural disasters, with financial constraints. It presents a case study of the San Francisco–Oakland Bridge to demonstrate the economic benefits of DAP. This paper provides transportation practitioners with guidance on the application of DAP and insight into the economic benefits of such an approach to decision making in various settings including emergency response planning, long-range planning, maintenance and renewal planning, and operations planning. The paper also identifies areas for possible future research combining financial theory with DAP as important in developing more robust decision-making frameworks for handling deep uncertainty.

Uncertainties about construction cost and operational revenues are two major risks in transportation public–private partnership (P3) projects. These uncertainties put projects at risk of being unable to fulfill annual debt repayment obligations. When a project generates insufficient cash flow to service the debt in a certain year, it normally has to go for short-term financing by borrowing short-term loans. With the help of revenue risk-sharing mechanisms, supported projects may be able to get rid of unexpected interest disbursement. The objectives of this paper are twofold: ( 1 ) evaluate the refinancing cost of P3 highway projects caused by cash flow shortage; and ( 2 ) critically examine the option value of contingent finance support and compare it with the option value of minimum revenue guarantee on saving refinancing cost for debt repayment. An integrated real options valuation model is created that utilizes utility method for pricing the technical project risk (e.g., construction cost overruns), and utilizes a risk-neutral option pricing method for pricing the market risk (e.g., future traffic). The proposed model has good transferability in relation to involving various risk factors, no matter technical risks or market risks, random variables or random processes. The proposed model helps stakeholders better understand and measure the burden of assuring annual debt repayment under uncertain cash flow. The stakeholders can use the proposed model to evaluate the value of the revenue risk-sharing mechanisms on reducing refinancing cost.

Preparing accurate cost estimates for highway projects always has been challenging for transportation agencies. It is a common problem that the lowest submitted bid significantly deviates f...

The major objective of this research is to investigate construction job market for developing multiskilled labor in the construction industry using web scraping and text mining techniques. The construction industry has been suffered from the skilled labor shortage. To resolve the shortage and pertinent problems, multiskilled labor utilization strategies have been presented in construction. Although extensive research has been conducted over multiskilling strategies, it is still uncertain what skill sets are desirable to foster and utilize multiskilled labor efficiently in construction projects. To fill the gap, this research investigates skill sets for multiskilled labor development in construction using web scraping technique. We analyze texts of companies' job openings and provide the latest trends in what skill sets are beneficial for workers to get employed. The results provide skilled labor with the information of what kind of skill sets required to meet industrial needs. This research will contribute to the body of knowledge by expanding the multiskilling strategies through the data-driven analysis of real construction job market.

Project management organizational structure plays an important role in state highway agencies as part of a network of complex relations that links a project management unit (PMU) and subject matter experts (SMEs) to tasks and resources for project development and aligns the functions for project management strategy. However, there is a lack of studies that studied the project management organizational structure of state DOTs in terms of the relative position of the dedicated PMU with other functional offices and the authority level of project managers (PMs). Thus, the primary objective of this paper is to analyze the state DOTs’ project management organizational structures and recommended practices of organizational structures for project management. This paper conducted, a survey, an extensive content analysis, and interviews with PMs and SMEs in state DOTs. The primary contribution of this study to the overall body of knowledge is the insights of state DOTs’ organizational structures by conceptualizing the relationships among the PMU and functional offices within the organization and identifying the state of practices in project management organizational structures.

Accurately forecasting the construction expenditure cash flow of transportation projects is critical for state departments of transportation (state DOTs) to secure sufficient funding to cov...

Purpose Building energy benchmarking is required for adopting an energy certification scheme, promoting energy efficiency and reducing energy consumption. It demonstrates the current level of energy consumption, the value of potential energy improvement and the prospects for additional savings. This paper aims to create a new data envelopment analysis (DEA) model that overcomes the limitations of existing models for building energy benchmarking. Design/methodology/approach Data preparation: the findings of the literature search and subject matter experts’ inputs are used to construct the DEA model. Particularly, it is ensured that the included variables would not violate the fundamental assumption of DEA modeling, DEA convexity axiom. New DEA formulation: controllable and non-controllable variables, e.g. weather conditions, are differentiated in the new formulation. A new approach is used to identify outliers to avoid skewing the efficiency scores for the rest of the buildings under consideration. Efficiency analysis: three distinct efficiencies are computed and analyzed in benchmarking building energy: overall, pure technical, and scale efficiency. Findings The proposed DEA approach is successfully applied to a data set provided by a utility management and energy services company that is active in the multifamily housing industry. Building characteristics and energy consumption of 124 multifamily properties in 15 different states in the USA are found in the data set. Buildings in this data set are benchmarked using the new DEA energy benchmarking formulation. Building energy benchmarking is also conducted in a time series manner showing how a particular building performs across the period of 12 months compared with its peers. Originality/value The proposed research contributes to the body of knowledge in building energy benchmarking through developing a new outlier detection method to mitigate the impact of super-efficient and super-inefficient buildings on skewing the efficiency scores of the other buildings; avoiding ratio variables in the DEA formulation to adhere to the convexity assumption that existing DEA methods do not follow; and distinguishing between controllable and non-controllable variables in the DEA formulation. This research contributes to the state of practice through providing a new energy benchmarking tool for facility managers and building owners that strive to relatively rank the energy-efficiency of their properties and identify low-performing properties as investment targets to enhance energy efficiency.

The purpose of this study is to determine the relative importance of key results areas (KRAs) and develop key performance indicators (KPIs) for construction portfolio performance management. The research methodology consists of the following steps: (1) Designing and conducting a fact-finding survey of owners and contractors to determine the relative importance of KRAs; (2) Designing and conducting structured interviews to develop KPIs; and (3) Assessing the usefulness of the results. Unlike the literature that has consistently highlighted the importance of risk management for construction portfolio performance management, risk management is not among top five KRAs (schedule, cost, cash flow, change management and safety) identified in the survey. This represents the significant gap in how research community and industry look at portfolio performance management. When it comes to dashboard development, contractors and owners have different KRAs within their dashboard for portfolio management. The limited knowledge about the relative importance of KRAs is one of the most important barriers towards managing project portfolios. This study is the first attempt to critically examine the literature and practice of construction portfolio performance management in order to highlight noteworthy differences between KRAs studied by the research community and implemented by the industry.

Several state departments of transportation (state DOTs) have encountered significant challenges to accurately estimate costs of their highway projects. It is not uncommon that states’ DOT ...

Risk factor identification is a critical topic in the construction industry. It is vital for the various construction firms and industry stakeholders to understand the different types of ri...

In the integrated environment of design-build (DB), design risk is transferred from the owner to the DB team. One significant challenge to DB projects is design liability. This study discus...

The highway construction cost index (HCCI) is a composite indicator that reflects the price trend of the highway construction industry. Most available indexes exhibit significant variation,...

Design-build (DB) projects are getting more implementations in the United States. Several studies indicate that the DB project delivery system has advantages in project cost and schedule pe...

Assuring quality management is essential for a project’s success for a specific price and within a specific time period. With an increasing number of highway projects being delivered by the...

20% of US energy consumption and their consequential environmental impacts are associated with building sector. Previous studies show that approximately 30% of a building's life cycle energy is attributed to its embodied energy. This study focuses on the residential buildings in the City of Atlanta and describes the trend of embodied energy and emissions of residential buildings in the city considering the 1970s transition in construction industry. The major objective of this research is to create a process-based Life Cycle Assessment (LCA) model to compare the embodied impacts of residential buildings constructed by two separate pre-1970s and post-1970s construction trends. For this purpose, the residential buildings have been categorized into two groups of buildings built before 1970s and built after 1970s. The 1-story and 2-story buildings have also been analyzed separately. The results indicated that residential buildings built before 1970s have lower embodied energy and impacts per square meter than residential buildings built after 1970s. This difference is in its highest for GWP which is 3.75–4.04 times higher for buildings built after 1970s. AP, ODP and SP come next with approximately 72%, 45% and 22% increase respectively for their 1-story models built after 1970s and with approximately 75%, 75% and 15% increase respectively for their 2-story models built after 1970s. Additionally, 2-story residential buildings have lower embodied energy and environmental impacts per square meter in comparison to 1-story residential buildings for all building scenarios and impacts.

Recently, construction-defect litigation has upsurged across the United States. Disputes arise due to a variety of reasons, and result in a range of negative impacts on construction project...

The Disadvantaged Business Enterprise (DBE) Program was established to provide opportunities for businesses owned and controlled by socially and economically disadvantaged individuals, such...

This research develops a systematic methodology to deeply mine tremendous volumes of design logs (that are generated from Building Information Model (BIM) design process) to discover social networks in BIM-based collaborative design practices and examine the relationship between the characteristics of the design social network and production performance of designers. Firstly, a data extraction procedure consisting of data harvesting, parsing, and cleaning is proposed to obtain BIM design logs in a Comma Separated Values (CSV) format from several designers over the course of working on multiple projects. Secondly, a metric of working together on joint cases is proposed to build up a weighted sociogram that is consisting of performers P, relations R, and weights W. Lastly, a number of indicators are defined to measure and analyze structural characteristics of the discovered BIM-based collaborative network at macro-, meso-, and micro- levels. A dataset of design logs that involves 51 designers working on 82 projects with 620,492 lines of commands, provided by a major international design firm, is used as a case study to demonstrate the feasibility and applicability of the developed approach in this research. Results indicate that: (i) Strong positive correlations exist across all centrality measures calculated based on the discovered social network of BIM-based collaborative design where designers located in the center of the interaction map (with the greatest degree centralities), such as designers “#2” and “#24”, are generally those who provide the shortest communication channels (with highest betweenness centralities) and are most reachable for others (with highest closeness centralities); and (ii) All the node centrality measures are significantly and positively related to the production performance of designers in the BIM-based collaborative network. Particularly, the measured node degree centrality by weight is capable of explaining the greatest percentage of variations (71.13%) in the production performance of designers. This research contributes to: (a) The state of knowledge by proposing a novel methodology that is capable of capturing and modeling collaborations among designers from tremendous event logs to discover social networks; and (b) The state of practice by providing insight into a better understanding of relationships between sociological network characteristics and production performance of designers within a design firm.

Extensive destruction and damage to communities in the aftermath of large-scale disasters such as hurricanes, floods, and earthquakes can cause substantial disorder in social and economic activity. The ensuing repercussions to social and economic systems lead to considerable uncertainty in continuing existing construction projects and implementing new reconstruction is problematic for accurately determining construction costs and making appropriate investment decisions. A large-scale disaster magnifies the importance of empirically examining variations in construction costs. Therefore, the overarching objective of this research is to analyze submitted unit price bids for superpave asphaltic concrete line items for highway projects let in the state of Louisiana after hurricanes Katrina and Rita. We employ two-way analysis of variance and a cumulative sum (CUSUM) control chart to monitor and detect changes in submitted unit price bids for hurricane- and non-hurricane-impacted areas. The results of the CUSUM control chart indicate that unit price bids for asphalt line items in the impacted areas significantly increased immediately after Hurricane Katrina and Rita hit the Gulf of Mexico, and those in the non-hurricane-impacted areas significantly increased six months after the hurricane. The findings of this research enable transportation agencies to more closely estimate the cost of rebuilding highway projects and make more-informed investment decisions for highway recovery programs in the aftermath of large-scale disasters.

Purpose Faults in the actual outdoor performance of Building Integrated Photovoltaic (BIPV) systems can go unnoticed for several months since the energy productions are subject to significant variations that could mask faulty behaviors. Even large BIPV energy deficits could be hard to detect. The purpose of this paper is to develop a cost-effective approach to automatically detect faults in the energy productions of BIPV systems using historical BIPV energy productions as the only source of information that is typically collected in all BIPV systems. Design/methodology/approach Energy productions of BIPV systems are time series in nature. Therefore, time series methods are used to automatically detect two categories of faults (outliers and structure changes) in the monthly energy productions of BIPV systems. The research methodology consists of the automatic detection of outliers in energy productions, and automatic detection of structure changes in energy productions. Findings The proposed approach is applied to detect faults in the monthly energy productions of 89 BIPV systems. The results confirm that outliers and structure changes can be automatically detected in the monthly energy productions of BIPV systems using time series methods in presence of short-term variations, monthly seasonality, and long-term degradation in performance. Originality/value Unlike existing methods, the proposed approach does not require performance ratio calculation, operating condition data, such as solar irradiation, or the output of neighboring BIPV systems. It only uses the historical information about the BIPV energy productions to distinguish between faults and other time series properties including seasonality, short-term variations, and degradation trends.

Engineering News-Record (ENR), a professional magazine in the field of global construction engineering, publishes Construction Cost Index (CCI) every month. Cost estimators and contractors assess projects, arrange budgets and prepare bids by forecasting CCI. However, fluctuations and uncertainties of CCI cause irrational estimations now and then. This paper aims at achieving more accurate predictions of CCI based on a network approach in which time series is firstly converted into a visibility graph and future values are forecasted relied on link prediction. According to the experimental results, the proposed method shows satisfactory performance since the error measures are acceptable. Compared with other methods, the proposed method is easier to implement and is able to forecast CCI with less errors. It is convinced that the proposed method is efficient to provide considerably accurate CCI predictions, which will make contributions to the construction engineering by assisting individuals and organizations in reducing costs and making project schedules.