Construction Research Congress 2014: Construction in a Global Network

Three-dimentional (3D) topological analysis for building models can facilitate construction planning remarkably in detecting construction activity interferences and deriving partial building models based on topological and locational constraints to meet the demands from team collaboration and task distribution. A widely used 3D topology framework is the 9-Intersection-Model (9-IM) that describes two spatial objects' topological relationship by identifying intersects among their exterior, boundary, and interior. However, some existing building models using Boundary representation (B-rep) (i.e., CAD) do not naturally carry information about each 3D object's exterior, boundary, and interior and thus, challenge arises in topological analysis for building models. Most collision detection algorithms only detect whether two 3D objects intersect with one another but do not support the analysis of detailed topological relationships. This study presents a vertex examination method (VEM) that enables a full range of 3D topological analyses for building models with B-rep, using the Minkowski-sum calculation. Each vertex of a 3D object is examined by conducting Minkowski-sum with the volume of another 3D object to identify their vertex-volume relationship. The topological relationship between two 3D objects can be determined based on the vertex-volume relationship pattern. This method complements the 3D collision detection by enabling 3D topological analysis between any 3D objects with B-rep. It is expected to benefit many construction planning tasks, such as site layout, workspace management, and scheduling, by facilitating analytical reasoning and operation on building models. Last, the method limitations and the potential to extend to 4D topological analysis are discussed.

Accurate and rapidly produced 3D models of the as-built environment can be significant assets for a variety of civil engineering scenarios. Starting with a point cloud of a scene--generated using laser scanners or image-based reconstruction method--the user must first identify collections of points that belong to individual surfaces, and then fit surfaces and solid geometry objects appropriate for the analysis. When performed manually, this task often is prohibitively time consuming and, in response, several research groups recently have focused on developing methods for automating the modeling process. Because of the limitations of the data collection processes, as well as the complexity of as-built scenes, automated 3D modeling still presents many challenges. To overcome existing limitations, in this paper we propose a new region growing method for robust context-free segmentation of unordered point clouds based on geometrical continuities. In our method, only one parameter is required to be set by the user to account for the desired level of abstraction. Preliminary experimental results from two challenging scenes of the built environment demonstrate that our method can account for variability in point cloud density, surface roughness, curvature, and clutter within a single scene.

Decisions made and approaches taken in mechanical, electrical, and plumbing (MEP) design coordination largely depend on knowledge and expertise of professionals from multiple disciplines. Furthermore, the use of Building Information Modeling (BIM) in MEP design coordination has increasedgreatly the amount and quality of available data. However, what information should be pulled from the model and what approaches should be taken to perform various coordination tasks still largely relies on expert knowledge. This study compares the behaviors of experienced BIM coordinators with at least three years of experience on model-based design coordination with novices who are tech-savvy but have limited project experience when performing certain coordination tasks. A scenario-based experiment that includes a series of clashes in MEP models was designed to examine the information used, actions taken, and questions asked during the coordination activities by experts and novices so as to compare the differences of these two groups. Results provide insights on what experts' knowledge needs to be captured during MEP design coordination, and furthermore, how to improve novices' performance by reusing captured knowledge from experts.

Although hands-on practices are considered the most effective training method for crane operators, they are always expensive and dangerous to be performed at the actual worksite. As an alternative, virtual reality and simulator technology provide a close-to-reality experience in lifting operation while minimizing costs and hazards. However, the virtual environment in current training systems are static and designed ahead of time rather than representing an as-built construction site with its dynamic construction resource (workers, equipment, materials). Such a drawback greatly limits the effectiveness of virtual training systems. To advance virtual training for crane operators, this research presents a framework toward constructing as-built virtual training environments by integrating Building Information Modeling (BIM) and real-time location tracking technology in a virtual environment. Implementing the proposed framework, a virtual training system for lifting tasks at an actual construction site was developed. The results of a pilot test show that such an approach canconstruct as-built work scenarios effectively and potentially assess and improve operator proficiency in a virtual training environment.

For the past few decades, construction researchers have investigated the potential of simulation modeling in providing decision makers with insights into different aspects of a project. Simulation can assist in studying the performance of an engineering system during early planning, preconstruction, execution, and maintenance. Typically this is done by providing means and methods for preparing work plans, look-ahead schedules, and what-if analysis. However, most existing construction simulation paradigms address long-term planning and scheduling needs. Work is still needed to disseminate the use of simulation-based decision making in short-term operations-level planning and control during project execution phase. Simulation models, and in particular, discrete event simulation (DES) models often are employed to gain insight into the performance of systems that are repetitive yet stochastic in nature. A good example of such systems that can be found in almost all industries is queuing systems. In construction, queues are ubiquitous because of specific project plans, resource allocation patterns, or operational bottlenecks. Certain client-server interaction schemes determine the properties by which a queue is characterized and subsequently modeled in a computer simulation model. This paper presents a methodology that enables data collection, fusion, and mining from construction resources in a queuing system to discover necessary knowledge and generate and update corresponding simulation models.

Despite of the simplicity of their individuals, social insect societies are structured social organizations that accomplish complex tasks that far exceed the individual capacities of a single insect. These self-organized systems offer possibilities for inspiring new and future solutions and technologies to benefit human construction practice. Biomimetic research of this kind studies systems that have evolved in the natural world to imitate and apply them in processes to benefit humans. We present the social insects' main building-behavior principles and their potential to influence the building industry and human building processes, considering process stages and durations, communication and information flow, governance, functional specialization of workers, supply chains, and materials. We review existing biomimetic applications in different fields related to construction management with respect to biological swarm systems and social insects in particular. Finally, we identify opportunities for examining and enhancing building construction processes, inspired by the behavioral principles of the social insects.

The use of Building Information Modeling or Virtual Design and Construction (BIM/VDC) in construction is prompting cultural change in the industry. The resulting research presents differences in self-perceived skill level between construction workers whose duties include the use of BIM/VDC and those whose duties do not. Further breakdown of results is presented for women and men across such job duties. Existing literature was analyzed to synthesize a list of 36 skills applicable to construction management professionals. Data from 122 survey respondents of construction management professionals across the United States was collected and analyzed. Findings suggest that differences in skill sets exist in construction professionals between those who do and do not use BIM/VDC. Results identify 14 skills across four competency categories that may be related to the use of BIM/VDC: five for both men and women, with an additional six for women only and three for men only.

This paper proposes a framework for estimating size of temporary facilities, a crucial task for construction site layout planning. Underestimation of facility size can lead to facility space shortage, productivity loss, and safety problems; overestimation results in lack of space for other facilities. Some temporary facilities have fixed or predetermined sizes. For other facilities, size depends on progress of activities and may vary over project duration. This study focuses on the latter, and implements simulation as a suitable planning tool to estimate size of activity-dependent facilities. Existing studies on site layout planning do not fully address this topic, and current practiceoften is based on experts' experience. In this study, simulation is implemented to model the construction process, and space is considered a resource in the model. Utilization of the resource over time indicates the space requirement trend over the project time. The main contribution of this work is estimation of the maximum required size of activity-dependent facilities and its variation over time. The case study presented demonstrates practicality of the proposed approach and capability of simulation in this area.

To gain deep insight into the underlying causation and identify correspondent management strategies in the prevention of construction workers' unsafe behaviors, a conceptual system dynamics model was proposed. This paper mainly focuses on the confidence building of the model through model testing, which basically contains tests of model structure, model behavior, and model's policy implication. First, the conceptual model is quantifiedbefore the formal process of model tests. Second, the paper applies semistructured interviews for the structure-verification test to ensure the model's appropriateness in depicting the structure of the actual system. Third, tests of model behavior, such as extreme-condition tests and behavior-reproduction tests, are conducted so as to demonstrate the plausibility of the patterns and behaviors the model generates. Fourth, the model's policy implication tests are presented to examine whether the model's responses to predesigned policies are consistent with the actual system. As a result, the model shows confidence in revealing the underlying causation of unsafe behaviors, which can be used as reference to the routine safety management in practice. Further suggestions for the application of the model as a tool of simulation in real construction projects also are given.

Today, most viewing of electronic drawings on construction sites takes place on mobile devices with limited screen size. Most of the current software interfaces still use a static display method, scaling drawings to fit the screen. Even though there are limitations because of small screen size on mobile devices, they have the benefit of being equipped with a variety of sensors, such as magnetometers, accelerometers, and gyroscopes. Some studies have looked at the use of these sensors to enhance further user interaction in areas such as gaming and texting. However, no study has considered the design of a user interface for construction drawing navigation using these sensors. To this end, the objective of this study is to develop a touch-free interface to navigate construction drawings using motion sensing. The interface was developed on Apple Inc.'s iOS platform and tested on an iPad tablet device. Motion sensor data, from the accelerometer and gyroscope, were used to pan and zoom the document with spatial movements. This study provides an innovative means to navigate large, layered drawings on small tablet devices. The algorithm used to develop the interface can be embedded in different applications for better navigation of layered construction drawings.

Together with the architecture, engineering, construction, and operation (AECO) industry widely adopting Building Information Modeling (BIM) technologies, there also has been an increase in research activities to develop efficient solutions for bringing BIM into a mobile augmented reality (MAR) environment. MAR provides an easy-to-learn and easy-to-use method of accessing information by allowing users to retrieve information in an intuitive way by visually parsing the environment and relating information in the form of augmentations to specific objects in specific places. Bringing a BIM model to a MAR environment poses several challenges, technically and logistically. In this paper, an overview of a method that practitioners can use to consolidate, optimize, and visualize their data and models in a MAR environment will be explained and then the technical and logistical issues within that process are discussed in detail. Geometry translation, indoor localization, attribute assignment, and registration are some examples of brining BIM to a MAR environment. Understanding the challenges and issues through the BIM to MAR method will provide practitioners in the AECO industry, as well as researchers in academia, a framework for creating more efficient workflows for this translation.

Throughout the economies of the world, the construction industry plays an important role. A major share of the activities within the industry takes place in the housing market. Since the mid1990s, increases in housing prices have been observed frequently in a variety of countries. To explain the price increases, researchers from a multitude of disciplines have studied the housing markets. However, research output from construction management domain is scarce. This research study presents an agent-based model (ABM) named Housing Market Laboratory (HoML) for the purpose of testing hypotheses related to housing price formations. The model comprises three types of agents representing developers, households, and land owners who trade two commodities simultaneously: land and housing units. Combining rules adapted from standard urban economics with a cellular spatial model, HoML allows agents to interact using bilateral bid and ask prices. Although the focus of this research paper is the theoretical underpinnings of the land use and housing models, several experiments are presented to demonstrate the use of the model. The results of these experiments suggest that HoML conforms to the behaviors of earlier models. Furthermore, an experiment focusing on developer behavior demonstrate the potential of HoML in exploring differing objectives of agents that trade in housing markets.

Systematic condition assessment on high-quantity low-cost highway assets requires frequent reporting on location and up-to-date status of these assets. Recent research on video-based assessment of assets have focused primarily on detecting traffic signs during data collection and are not applicable to other assets, such as guardrails and light poles. To overcome such limitations, this paper presents fast graph-based segmentation and super-parsing algorithms, which efficiently segment highway assets from 2D video streams. Using a fast graph-based segmentation algorithm, superpixels are obtained from each frame, and their appearance is computed using a histogram of textons and dense SIFT-descriptors. A likelihood ratio score is obtained for each superpixel and an asset label that maximizes the ratio is assigned. Given a frame to be interpreted, the algorithm performs global matching against the training set, followed by superpixel-level matching and efficient Markov Random Field (MRF) optimization. The MRF simultaneously labels video frame regions into semantic and geometric classes of assets. Experimental results are presented on the Virginia Tech Smart Road research facility on a 2.2 mile highway. The work contributes to the body of knowledge by detecting 3D assets that previously have not been detectable bystate-of-the-art methods. It also enables further development of techniques that can recognize subcategories of highway assets.

Safety continues to be among the top issues in the construction industry after experiencing 738 fatalities in the United States in 2011. Among all construction operations, excavation is one of the most hazardous because of its possible cave-ins, contact with objects and equipment, bad air, and so on. Until today, most safety inspectors still are inspecting the site manually, making the inspection time consuming and error prone. This paper presents a method that automatically identifies cave-in safety risks in construction excavation. It first extracts relevant safety rules from OHSA standards and industrial best practices. Then it collects a set of point cloud data of a construction site under excavation using laser scanning, registering, and cleaning the point cloud data afterward. Finally, it develops an automated identification algorithm on the basis of those rules and applies the algorithm to the data to identify potential cave-in risks by analyzing geometrical properties. An experimental trial also is conducted in this paper, and results show that the method identifies those cave-in risks successfully. The presented method actively monitors the fast changing situations of construction sites under excavation and helps inspectors and project managers make good safety decisions, preventing accidents and fatalities.

Owners, architects, and engineers are highly concerned about the sustainability and energy performance of proposed buildings. Evaluating and analyzing the potential energy consumption of buildings at the conceptual design stage is very helpful for designers when selecting the design alternative that leads to a more energy efficient facility. Building Information Modeling (BIM) assists designers assess different design alternatives at the conceptual stage of a building life so that effective energy strategies are attained within the green building constraints. As well, at that stage, designers can select the right type of building materials that have great effect on the building's life cycle energy consumption and operating costs. The aim of this paper is to propose an integrated method that links BIM, energy analysis, and cost-estimating tools with the green building certification system. The successful development of the proposed method helps owners and designers evaluatedesign alternatives, taking into consideration the sustainability constraints in an efficient and timely manner. BIM's tool is customized to allow its integration with the energy analysis application to identify the potential gain or loss of energy for the building, detect andevaluate its sustainability based on the U.S. or Canadian Green Building Council (USGBC or CaGBC) rating systems, and approximately estimate the costs of construction early at the conceptual design stage. An actual building project is used to illustrate the workability and capability of the proposed method.

The built environment provides a significant opportunity to reduce energy consumption and the associated environmental effects. Researchers have focused on how the Building Information Model (BIM) can be used effectively during the design phase to model energy efficient retrofits. However, research on the use of BIM during the operational phase to aid in energy conservation has been limited. The research presented in this paper focuses on the integration of real-time energy consumption data of building occupants into the spatial context through BIM. Real-time energy consumption data were collected, and a standardized Industry Foundation Class (IFC) BIM with geometric, material, and construction information was created for a test-bed building in New York City. To link data in the IFC with energy consumption data we developed a novel ontology that merges the existing IFC class hierarchy with newly defined energy use classes using relationship classes. The process entails identifying the specific geometric information in a BIM that corresponds to energy usage.

This research investigates the role of 4D visualizations in enhancing mindfulness in construction project coordination. We introduce the mindfulness concept—defined as capacity to detect (potential) operational errors and take corrective action—to make a comparison of two distinctive coordination practices. To this end, manual and 4D-supported coordination of three cases of three inner city reconstruction projects were examined. Observations were structured using five principles underlying mindfulness. Four of these principles supported our hypotheses that 4D allows managers to anticipate and contain errors better. We conclude by describing how 4D's focus on operational interdependencies helps to detect potential conflicts, increases resistance to simplifications through detailed visualizations, and enables development of containment strategies. Such practices eventually reduce conflicts, delays, and cost overruns, enhancing the reliability of coordination processes.

Locating a specific utility or finding oneself in an unfamiliar facility can be difficult and time consuming. The ability to visualize the location in real time can reduce the time for manual searching and locating. The proposed research is to utilize commercially available radio frequency identification (RFID) technology for real-time visualization and location tracking in a BIM model. The scope is passive RFID tracking technology and Building Information Modeling (BIM). A novel approach is presented that utilizes current localization techniques and algorithms. A prototype application has been developed that connects the RFID readers with a BIM model and database. Preliminary results demonstrate the feasibility of locating a user inside buildings in actual time. Significantly, the visualization will enableusers to pinpoint themselves and a utility in a model, saving time and money.

In the AEC industry, globally distributed teams are becoming more common, BIM adoption is increasing, and effective time management is essential for remaining competitive. Therefore, understanding how to maximize BIM for construction coordination using collaborative technologies becomes crucial. Observations from a 2012 industry case study with a five-member distributed team led this research team to hypothesize that importing a 3D model into a 3D virtual world would improve team collaboration with models because using cues in the 3D environment (including avatar position) affords more efficient communication and having independent viewpoints allows a greater number of coordination issues to be discovered. This paper reports on a collaborative experiment with four different universities in 2013, in which we observed six geographically distributed nine-member teams as they conducted work using two different communication technologies: A commercial collaboration platform in which team members view models via desktop sharing, and a 3D virtual world in which the students were able to "walk through" the building model. We found that the teams using the 3D software were able to communicate ideas more quickly and had significantly more discoveries. By contrast, the teams using desktop sharing software often required a detailed verbal explanation when communicating specific ideas.

Simulation is a proven technique for effective construction site layout planning and resource optimization. Historical data is used as input for task durations in traditional simulation approaches. These data are fed into activity cycle diagrams that do not consider spatial constraints. Cell-based simulation with real-time location data can be implemented for more realistic modeling and incorporating spatial changes on the site during project execution. Despite the potential, very little research has been done. The objective of this research is to develop a framework of utilizing real-time data for spatial simulation of cyclic activities on a construction site. Continuous data were collected using a global positioning system, and a cell-based simulation model was developed for spatial consideration of earthmoving cycles. The potential of analyzing and visualizing the effects of varying resource combinations on productivity and traffic congestion onsite were explored. The approach will aid in increasing insight and awareness for decision making in resource management, site layout, and internal traffic control plan. It also will serve as an education and training tool for project managers.

Excessive absenteeism on construction projects can affect project performance in many adverse ways. Traditionally, to combat absenteeism, construction managers have used formal controls (e.g., penalties); however, these approaches frequently have proved ineffective at eliciting desired changes in workers attendance motivation. Therefore, researchers have begun modeling how social controls can be exploited to achieve organizational objectives. In this paper, we developed an agent-based model to investigate how project structure affects the spread of social norms related to absenteeism on construction projects, which in turn affects the net absence rate. Three experiments were conducted testing the effect of three different project structures (no worker turnover, modest worker turnover, and high worker turnover) in scenarios of moderate (0-5%), moderately high (5-10%), and high (10-15%) initial worker absence rates. Results indicate that the diffusion of project culture on construction sites both can benefit and harm absence rates. With mild absenteeism, more stable project structures aid in the spread of negative culture and worsen the absence rate. Alternatively, with excessive initial absenteeism, more stable project structures help diffuse positive absence culture. Understanding that social norm diffusion can create positive or negative feedback loops, construction managers can take advantage of this to help achieve administrative objectives.

The need for development of reliable and efficient real-time data acquisition systems recently has attracted a great deal of attention in the construction industry, basically because of the demands for highly frequent updates in most visualization, optimization, and coordination-related applications. The predominant data that have been used in the construction industry so far is rather less accurate. Moreover, the conventional methods of data acquisition are based on fieldwork that is time consuming, expensive, and labor intensive. Accuracy of original data and efficiency of data acquisition could be enhanced using new LiDAR technologies. LiDAR is the advanced remote sensing technology that is able to provide 3D data with centimeter to millimeter level accuracy effectively and efficiently. However, the implementation of 3D data for accurate as-built creation is still challenging, especially for openings and fine details of the construction objects in an indoor environment. This paper presents a framework for rapid as-built modeling using 3D point cloud data captured by a handheld LiDAR The procedure involves five key stages from data capturing to create a final model. This paper reports the implementation of the framework using the state-of-the-art mobile LiDAR to analyze fine details of a sample building. LiDAR data of a sample building in an indoor environment is captured using a mobile laser scanner and is analyzed after registration and segmentation processes. The reconstructed model using the as-built data is compared with the existing 2D AutoCAD plans of the sample building and the traditional measurements to verify the accuracy of the proposed method. The results of this ongoing study confirm that the proposed model development technique can serve as a reliable tool for accurate development of rapid as-built building models (rABM). The accuracy ranges from 5 to 30 mm, depending on the object size and position. The proposed algorithm was shown to be highly efficient in identifying the main visible components in the buildings.

Over the past few years, the use of 3D digitization and modeling for 3D remodeling of cultural heritage has become increasingly common. The most commonly used technologies include surveys, CAD tools, and traditional photogrammetry with control points. These approaches are, however, time consuming and can be costly, and therefore may be impractical for large-scale sites. Modeling in 3D using point clouds from laser-scanned data and more automated image-based modeling have become possible. Photogrammetry is one of the most cost-effective approaches we could use to gather the physical information of an object, because data can be collected using a consumer level digital camera. However, it also has its drawbacks in the level of accuracy. Wondering whether the 3D model created by using photos would be acceptable for the use of construction planning, we created a 3D model of a historic building on our campus, which was under renovation, and investigated how the 3D model was appreciated by architects and contractors working on the renovation project. We measured the accuracy level of the 3D model and identified the deficiencies of this approach. This paper presents our findings and responses from the construction professionals who reviewed the 3D model in the BIM/CAVE.

Mechanical contractors play a vital role during construction of a building project, which could affect the overall project success significantly. Traditional 2D paper-based solutions for design and fabrication of mechanical, electrical, and plumbing (MEP) components has proven to be an inefficient and fractured method to communicate the project design. Moreover, if a problem arises during construction, such as clashes between MEP systems and structural components, the problem often has to be solved onsite, which is not cost efficient, because it often requires rework. Therefore, most mechanical contractors today are switching from traditional paper-based workflows to adopting Building Information Modeling (BIM) processes into their practices. One of the greatest benefits of BIM is that it facilitates exploring clashes and coordination issues within a virtual environment instead of in the field, consequently reducing requests for information and change orders along with the associated health and safety risks. This paper presents a case study based on content analysis results of the interviews conducted with two leading Midwest mechanical contractor companies. It explores current BIM applications, such as clash detection and fabrication, benefits and challenges of implementing BIM within both companies. The first major finding of this research is that BIM standards and manuals are helpful tools for the development and implementation of BIM models. Also found is that contractors need to make adjustments to their workflows to achieve better results with their BIM implementations. Finally, there is a need to investigate how to use BIM models for facility management in an effective manner and possibly fuse them with building automation systems.

The construction industry has sought many forms of improvements to materials and methods to increase productivity. Prefabrication in products, components, and systems has made some headway in this arena, but overall productivity still remains largely flat as measured against all other nonfarm industries in the United States. One new technology that is starting to garner interest in the vertical construction industry is the use of LiDAR scanning, currently used primarily for large-scale geospatial measuring, data capturing, and modeling. This paper explores the potential for using this technology on smaller interior components, namely gypsum panel installation, and presents a qualitative pilot proof of concept study to compel further quantitative research. As a method, LiDAR was used to produce a dense registered point cloud from which "slices" were extracted from a VDC model, which were then used to produce prefabrication drawings for gypsum panels and measured against actual conditions. As a large-scale ubiquitous material, incremental improvements to gypsum installation could have a significant effect on overall productivity in vertical construction.

Energy management in buildings is about operating and maintaining many complex energy systems used by buildings' occupants. The generation and collection of energy-related building information commonly is fragmented, created over the building's life cycle by different teams with different objectives, and stored in different systems. The development of BIM systems has helped in storing this various information. However, the knowledge utilized in maintaining energy systems also has to be captured to develop a building portfolio that is comprehensive enough to benefit buildings' owners, occupants, and energy managers. Capturing knowledge in digital format is always a challenge when developing such systems. Therefore, this research proposes an innovative means for capturing energy-related knowledge when monitoring and maintaining building performance by the integration of a spoken dialogue system (SDS) with BIM models. SDS presents a natural language interface where the expert's utterances are understood and answered back in speech format. The advancements in spoken dialogue technology will be employed to enable capturing and retrieving experts/occupants' knowledge with the system interviewing the expert concerning the problem at hand. This interface also allows easier searching for solutions to new problems with a more comprehensive retrieval of information.

This study proposes a 3D visualization model in highway design/construction that electronically represents information of highway projects. The 3D model will be based on the Standard for the Exchange of Product (STEP) model data, which is an open standard, so it can be used as data structures. Because the design model includes integrated resources to represent 3D geometric shape and project management information of the infrastructure, the built visualization model will allow end users to extract the necessary data from the object-based 3D intelligent model. This integrated data model is expected to provide practical engineering information to improve the design/construction process. This study presents the framework for the integration of application programs, such as existing 3D CAD programs used in practice by applying the STEP-based information model and information technologies. With the system integration framework comprised of the information model, data repository, application program, and application programming interface, this research proposes establishing a prototype system according to the system integration framework so that end users can manage information of an infrastructure in an integrated computing environment. The final output of this research is to present a methodology to generate a construction schedule automatically from infrastructure facility design information. This method is performed by the full connection between construction quantity take-off analysis and design information by using the information model.

One of the premises of Building Information Modeling (BIM) is to provide a repository for all building-related data throughout its life cycle. However, the use of current models developed in existing BIM-based software rarely goes beyond the construction phase. During a facility's management, these models are treated as static information sources that contain the as-built data. Making BIM-based models dynamic to represent the real-time building information introduces various opportunities for facility managers to obtain accurate information about the state of various systems. In this paper, we introduce an approach used to connect the sensor data to the IFC-based BIM. We use a geothermal bridge deck deicing system, which involves embedded sensors as a case study. The real-time monitoring of these sensor data is crucial for assessing the state of the bridge deck under different climate conditions. First, we describe our model in Revit and use the data we collected from temperature sensors. These sensor data subsequently is fused into the IFC-based BIM and processed for visualization through the development of new add-ins in Revit. Finally, all the sensor data should be monitored easily in BIM for condition assessment.

Building Information Modeling (BIM) recently has been recognized as a powerful tool among construction stakeholders. The BIM technology not only enables decision makers access to reliable and accurate information but also facilitates project management processes during bidding, preconstruction, construction, and postconstruction. However, possible applications of BIM technology are less considered for the purpose of the end-of-life operations, such as cost-benefit analysis of demolition waste management. This study aims to identify potential application of BIM in demolition waste management so that decision makers can base their decisions on reliable and accurate information. For this purpose, three most common demolition waste management alternatives are proposed, and the cost-benefit analysis is formulated based on building-related and constant variables. The variables are further categorized based on their data sources into four categories including drawings and onsite survey, literature, official statistics and regulations, and real-life data from surveys. Finally, a case study of a one-story wood-frame residential building is simulated to demonstrate the potential application of BIM in supporting cost-benefit analysis of demolition waste management. The result of this study can be used as the backbone for developing a BIM-based waste management tool.

Road maintenance programs generally are divided into three categories: routine maintenance;periodic maintenance; and the rehabilitation of roads, slab culverts, and bridges. Although the budgets for these maintenance activities are planned prudently, based on the engineer's estimate, changes usually occur in the work plans after the maintenance work starts. The road maintenance activities are broken down into packages, and each package is awarded to the lowest bidding contractor. Progress made on the contract is recorded on a monthly basis, and the reports are generated on a monthly, quarterly, or yearly basis for each region or for an entire country. To perform these works more efficiently, software known as the Road Maintenance Management System (RMMS) was designed and implemented in 47 regions of the Kenya Rural Road Authority (KeRRA), Africa. The software is capable of tracking the change orders in every activity in the work plan and recording the construction progress in detail. As a main objective, this paper discusses the framework of the RMMS system. This paper also identifies five main road maintenance activities that experienced a high number of change orders for road maintenance projects of Kenya.

In every Department of Transportation (DOT), the majority of the budget is expended in maintaining roads, bridges, and interchanges. Generally, three types of road maintenance methods are used: in-house, method-based contract (MBC), and performance-based contract (PBC). Numerous research reports are available to assist DOT maintenance engineers or managers to choose a suitable road maintenance method for their typical maintenance activities. However, these engineers do not have time to read through the bulky reports and guidelines to choose an appropriate maintenance contracting method. The purpose of this study was to develop a stand-alone software tool to assist DOT maintenance engineers and managers in choosing the best method for road maintenance activities. Further, this study synthesized relevant literature to develop criteria for the selection methods. A literature review was conducted to identify the criteria for selecting the methods. The software tool based the selection of methods on a decision-tree diagram. Using this software, the user is able to print out the decision suggested by the software tool, a personal description of the user, project description, and the questions attended by the user. Recommendations regarding the use of this tool and suggestions for further study are discussed.

Boosting the communication at the process level has been identified as a promising strategy to improve construction productivity, safety, and quality. However, the capacity of classic paper-based information flow at work-front limits the transformation toward a construction paradigm able to access a ubiquitous data network. For this reason, "information superhighways" have to be constructed to connect the many information sources and sinks to enable highly productive practices supported by built-in smart agents. Not only is IT an essential tool for linking islands of information needed, but it opens opportunities for processing the data in real time using sophisticated processes. Included in the discussion are the lessons learned on the site-readiness to accommodate IT and incentives to foster collaboration, creation of rugged interfaces, and interoperability. The paper ends with an analysis of the data collected during the experimental testing of innovative prototype systems that encompassed the use of RFID tags, GPS, the Electronic Construction Kiosk (eCKiosk), wireless IP camera, and Bluetooth intercom. Results confirm the importance of involving the site personnel in the implementation of new concepts and the positive effects of a well-designed IT system to improve significantly process productivity and quality. Practical challenges caused by the nature of construction are highlighted.

The concept of "constructability" has been raised to optimize construction knowledge and experience in the design phase of construction projects to improve project performance. Previous research demonstrated the feasibility of an automated, rule-based constructability review through BIM implementation. The current work investigates the elicitation of constructability knowledge to achieve the automated process. With a case study, two frequently used knowledge elicitation methods—interview and document analysis—were applied to collect constructability knowledge on formwork selection for a concrete building project. Advantages of each technique indicate the need for combining the two elicitation methods as a means of triangulation to establish a comprehensive and accurate knowledge base for an automated, rule-based constructability review.

MacLeamy proposed a set of time-effort distribution curves, with a view to mainstreaming the adoption of Building Information Modeling (BIM) in the architecture, engineering, and construction (AEC) industry. Numerous researchers and practitioners have cited these curves, but no previous research has endeavored to draw actual time-effort distribution curves and analyze them. The aim of this paper is to introduce a novel approach to draw real-life, time-effort distribution curves and understand their implications. A data collection form is developed in this paper to record the efforts contributed to a project by various parties. The time-effort distribution curve can be drawn by using both data plotting and mathematical curve fitting. Two public housing projects, one with BIM support and the other without, were adopted in this paper for drawing the real-life, time-efforts distribution curves. It was found that the time-effort distribution curves in real-life projects are of little similarity to those reported by MacLeamy.

The growing use of digital technology in design and construction has brought a change in teaching dynamics. For example, serious games have shown great potential in enhancing the learning of dynamic construction concepts traditionally acquired through practical experience. One such example is the Virtual Construction Simulator 3 (VCS3) game, developed and implemented to engage students in an active learning environment by simulating the planning and managing of a construction project. Initial assessment of the VCS3 game has demonstrated benefits for both students' motivation and basic understanding of construction concepts. However, further assessment is required to demonstrate the benefits on higher order cognitive skills. This paper introduces the first step, the formulation of learning objectives for higher order cognitive skills in construction simulation gaming. Learning objectives from third- and fourth-year construction engineering courses, together with the previous VCS3 learning objectives, are analyzed and categorized. The learning objectives guiding the next phase of the VCS4 simulation game development are then presented from lower tohigher level thinking skills. This initial step opens the next phase in the development and assessment of the VCS4.

In architectural and civil engineering design, effective team collaboration is critical to creating functional built environments. To prepare future engineers for careers involving collaboration, this research paired first-year engineering students with similar extraversion five-factor model scores in dyads to complete an introductory bridge design project. To understand the benefits of this type of pairing, 29 teams were tasked with designing and constructing popsicle stick bridges using data collected over several semesters. During the project, students completed a peer review activity in which one team attempted to build and subsequently generate feedback about another team's design. Every dyad had an opportunity to generate feedback for another design, as well as receive feedback about their design. The students completed pretest and post-test assessments to provide their perceptions about their own designs before and after this prototyping activity. The analysis focused on the dynamics of team agreement regarding perceptions of the design and documentation. The paper finds correlations of openness and agreeableness to shifts in perception of performance in the design. Correlations also were found related to these factors, as well as conscientiousness for perception shifts related to documentation tasks. The findings of this research generally align with related prior works and illustrate how team personality traits can be tied to the way that the same type of formative feedback can be received differently by students.

Changes in the interaction of the different disciplines involved in building science during the 20th century have increased the divide between what is taught in the classrooms and what is later expected by the actual professional workplace However, recent advances in computer technology and demands that come from contemporary professional scenarios have begun to address this divide. This new reality has led to the development of an integrated interdisciplinary approach under the umbrella of integrated project delivery (IPD). Through IPD, the traditional consultant-based model has been substituted by an integrated model in which the various professions are required to work together from the beginning of the building project. The purpose of this paper is to describe an initiative aimed to implement an integrated minor degree to provide the substantial knowledge required to address these new professional scenarios. We call it "Transforming Building Design through Integrated Project Delivery in Architectural and Engineering Education." Through this initiative, students from both architecture and civil engineering schools jointly face scenarios that mimic actual professional challenges. This initiative will provide students the opportunity to develop solutions to real building design projects collaboratively using BIM and project-based learning.

Lean construction is growing in popularity throughout the architectural, engineeering, and construction industries. The concepts of lean construction promise to deliver construction projects with ever-increasing complexity and ever-shrinking resources effectively. As a result, many construction companies are beginning to use lean construction as standard operating procedure on their projects. Despite this trend, the concepts and practices of lean construction are not taught widely in undergraduate construction education programs. In response, one undergraduate construction management program redesigned the required scheduling course utilizing the Last Planner System^TM framework to introduce lean construction concepts. The goal of this course redesign was to integrate lean construction principles and practices while maintaining the traditional learning outcomes for a construction scheduling course. A comparison of course learning outcome assessment results after the redesign validated this approach. Recommendations are presented for implementing lean construction into similar construction education courses.

Research suggests that certain practices of the construction industry have left the construction profession with an unethical stigma. To curb such behaviorial perception, construction programs should provide students with an awareness of unethical practices of the profession as the first step toward ethical decision making. The intent of this study is to suggest a topic-based meta-framework for teaching ethics to construction students, highlighting what noneducational construction research considers ethical topics. This study uses qualitative textual analysis to extract ethical topics from noneducational research from 65 research papers that closely relates themes of construction and ethical issues of the profession. Emergent themes (modules) based on topic extraction groups into two categories of ethical issues in construction practice (i.e., professional issues and societal issues). It is the authors' hopes that the list of ethical topics and modules developed are a source of inspiration for those educators honored with the duty to instruct.

In the last five years, the construction management department at Southern Illinois University Edwardsville (SIUE) has offered two semester travel study courses with week-long travel study trips for students. One trip is to Mexico and one to Panama. The objective of these courses has been to provide students with an opportunity to learn about and be exposed to international construction projects and the culture of another country. Two other courses and similar trips are being considered for the future, but SIUE faculty found that trips to international destinations can be challenging to plan and are quite costly in time and money. Are the benefits of a travel study experience worth the cost? Are there less costly alternatives that can achieve similar benefits? In this paper a number of methods for providing international educational experience to students are examined. The fiscal costs of travel studies were found to be readily available, but the benefits were not quantified so easily. Overall it was determined that given the international nature of construction projects in the world today, students do need some type of international awareness and exposure as part of their educational program, but traditional travel study courses may not be the best option.

A new instructional medium called a massive online open course (MOOC) recently has become prevalent. Millions of learners from all over the world enroll in these available and affordable courses. Thousands of courses have been offered by distinguished institutes and instructors on a variety of evolving MOOC platforms. However, construction education has yet to take advantage of this popular medium. This paper offers a guideline for construction education to provide successful MOOC courses. Construction educators already are familiar with new educational technologies and active learning pedagogies. Combining these two familiar approaches can be a starting point for offering successful courses in MOOC. This paper suggests using team-based and problem-based learning approaches along with the MOOC delivery to increase the success and completion rate, which has been problematic in MOOC courses.

The "Parade of Trades" simulation is a well-known educational tool that illustrates the effect of dependence and variation on the performance of a production process. The Parade of Trades illustrates that when the production variability of interdependent trades increases, both the project duration and the trades' production losses increase. This paper describes and demonstrates an enhancement of the Parade of Trades simulation. The enhancement involves assigning a cost to reflect the cost of planning for different levels of variability. The addition of this parameter makes it possible to use the Parade game to explore new issues: The relation between planning costs, delays and production losses; and the distribution of planning effort and benefits among the process participants. This paper describes the rules of the modified game and simulates different strategies in a computer model. Such strategies involve decisions to increase the planning to reduce variability. The simulations demonstrate alternatives scenarios and evaluate the cost of planning against the benefits of reduced waste and delays for the different project trades. As a result, the Parade of Trades is used to raise several issues related to the costs and benefits of increased reliability, allocation of planning costs and benefits between the participants, and the need to align the trades' planning efforts with the project interests. This increases the value of the Parade of Trades as an educational tool.

The Construction Management (CM) program in Lyles College of Engineering (LCOE) at California State University, Fresno, recently completed significant revisions in its undergraduate curriculum, which is now featuring hands-on sustainability education. Service-learning has become an integral component of three core courses at different levels—freshman, sophomore, and senior. Each course mandates a minimum of 20-hour service-learning activities related to construction. In fall 2012, as part of the Southern California Gas Energy Efficiency and Education (EEE) Initiative, the CSU Center for Community Engagement awarded the CM program a grant in support of the development of a collaborative learning community including CM faculty, university service-learning staff, students, and community-based organizations. The goal was to enhance the quality of service-learning in energy conservation and efficiency. The CM faculty and community partners worked closely together throughout each semester to make continuous improvements in course contents and service-learning project activities. As a result students were provided with proper hands-on opportunities for deeper understanding of their course materials. This paper shares the learning outcomes from the community development in fall 2012 and spring 2013.

In partial fulfillment of the requirements for a capstone project, construction management students are required to prepare a construction project manual. Rather than copying and pasting from existing company manuals, a new experiment was conducted requiring the students to originate a project manual to cover the project in its different development phases. These were initiation, predesign, design, preconstruction, construction, handing over, and commissioning. Developed procedures had to be self-contained, including their purpose, scope, definitions, key performance indicators (KPI), and any relevant forms or checklists. Additional components included a responsibility assignment matrix (RAM) and a newly coined term, TPRC, which stands for tools, personnel, references, and controls. A flowchart was developed for each procedure to represent the flow of its activities graphically, as well as its inputs and outputs. The final deliverable consisted of a multiphased manual reflecting different project phases. Deliverables were evaluated and judged by a panel of construction professionals from the local industry, representing different project roles on a project team (clients, financiers, designers, construction managers, general contractors, subcontractors, and users). Further evaluation was conducted one year after graduation, gauging the former students' perceptions of the project manual and its applicability to their role in the construction industry.

The social quality of life (SQOL) for single-family housing residents can be improved by maximizing their thermal comfort, improving the quality of indoor lighting, and enhancing indoor air quality. These SQOL improvements often require additional initial housing costs and have a direct effect on the annual energy cost of housing units. Accordingly, the design and construction of single-family housing units need to be analyzed carefully and optimized to maximize the SQOL for their residents while minimizing the initial cost and the annual energy cost of the housing units. This study presents the development of a multi-objective optimization model that is capable of generating optimal trade-offs among these three important optimization objectives. An application example also is analyzed to illustrate the capabilities of the developed model.

It is necessary to develop standardized methods and metrics that effectively and efficiently study, measure, and analyze the wide range of effects of the construction processes. The narrow focus of the currently available assessment methods does not address the technical, environmental, economic, social/cultural, and individual sustainability indicators adequately, nor the temporal, spatial, and behavioral aspects of sustainability. This paper utilized a systems approach that is based on the three novel benchmarks—nature, work, and flow—thatpreviously were proposed by the second author. "Work" defines the socio-behavioral relationships among the construction products and the actors of the built environment. "Nature" focuses on the effects of the built process on the environment through studying the interaction between the actors, processes, and the end products within a host system. "Flow" identifies the changes within the community host systems and the effects of these changes on the natural and socio-economic settings. To this end, the authors applied this innovative framework to five different projects including a highway, streets, and drainage project; solar energy; wastewater treatment; and vertical construction. Results indicate that the proposed systems approach provides an improved holistic understanding of the environmental, social, and economic effects of these projects.

High-performance (HP) buildings are known for the holistic approach to design and construction project delivery, which encompasses various performance goals, such as energy efficiency, environmental considerations, and occupants' well-being. Compared to traditional buildings, HP projects require closer integration in the design and construction process. Researchers have used conventional qualitative analysis to identify successful strategies in facilitating integration, and quantitative methods of research to rank such techniques in order of effectiveness. However, there have not been significant attempts in evaluating the joint causal effect of such strategies and uncovering the causal mechanisms that underlie successful HP projects. Utilizing a new methodology called fuzzy set-qualitative comparative analysis (fs-QCA), we analyzed the configurations of integration strategies used in more than 30 HP projects. We found that the four elements of setting ambitious environmental goals, having committed and trustworthy team members, using advanced information management technologies, and early and frequent involvement of the key team members create a sufficient recipe for achieving a high level of energy efficiency. Our analysis also shows that in the presence of these elements, contractual agreements do not produce a necessary element, as contractual barriers can be overcome with leadership, information systems, and work processes that engender an environment of trust, openness, and ambition.

As the nation moves toward more sustainable energy and environmental standards, it is important to examine all sources of fuel consumption and pollution, including heavy-duty diesel (HDD) construction equipment. To quantify these sources at the project level, they must be identified with their respective activities. A case study was performed on an Oklahoma Department of Transportation (ODOT) bridge replacement project to establish a baseline of actual-world activity, equipment, fuel use, and emissions data. These data were collected on a daily basis via jobsite visits and included specific information, such as the equipment's model year, engine horsepower, and hours worked. These data were used to estimate fuel use and emissions based on calculations from the EPA's NONROAD model. Using these estimates, traditional project management techniques were expanded to evaluate the energy and environmental effects of the project in addition to the economic effects. Histograms and cumulative frequency diagrams (s-curves) were created to summarize fuel use and emissions on a daily and project total basis. These results were combined with the preliminary and final ODOT pay items and quantities to define new fuel use and emission factors based on quantity of work completed, dollars of work completed, and specific activities. Recommendations include using the new fuel use and emission factors to identify activities with high energy and environmental effects, as well as evaluating various mitigation strategies.

Buildings are one of the United States's largest consumers of energy. Measures to decrease energy consumption often are overlooked during the building design process. One of the major barriers in design of buildings is the absence of tools to help architects and designers during the preliminary design stages. Therefore, the objective of this study is to develop an estimating tool to assess the energy performance and economic benefits of radiant barrier insulation in the temperate climate region in the United States. The developed tool is based on transient 3D finite element models that were validated based on the results of an experimental field study. The results of the 3D finite element models were used to develop a set of multiple-linear regression equations to predict the thermal and energy performances of radiant barrier insulation. The simulations run hour by hour for the entire year using the typical meteorological year (TMY2) weather data. Each simulation takes less than 30 seconds, allowing for very fast comparisons of different design scenarios. It is expected that the developed tool will simplify the integration of energy efficiency in residential building design and construction. Results show that attic radiant barrier can reduce building energy consumption by up to 12%. Results also indicate that cost savings in the temperate region ranges from $7 in Idaho to $41 in Connecticut in 2011.

In recent years, resource depletion and environmental pollution represent major concerns for society. According to the Environmental Protection Agency (EPA), construction is considered as the third largest industry sector in terms of contributions to greenhouse gas (GHG) emissions in the United States. The negative environmental effects of construction processes have been increasing quickly in the world because of the large number of continuing construction projects. Buildings are one of the main consumers of energy and thus important contributors to the emission of greenhouse gases into the atmosphere. Buildings consume 40% of energy, 65% of electricity, and produce 30% of greenhouse gas emissions. In the current study, a multi-objective optimization model using harmony-search algorithm is proposed to find the optimum design of building based on the building design parameters and climate conditions. Life-cycle analysis methodology is used to assess design alternatives for both economical and environmental criteria. This model is employed to minimize the carbon dioxide equivalent (CO₂-eq) emissions and the life-cycle cost (LCC) of a typical single-family house. The multi-objective model proves to be efficient, and a set of optimal combinations (Pareto optimal solution) is obtained.

Compared with the conventional stick-built construction method, panelized construction offers greater sustainability in terms of energy, waste, and emissions reduction. The empirical research presented in this paper addresses the carbon footprint of panelized construction by quantifying and comparing the carbon emissions during the framing stage between panelized and conventional stick-built construction methods. The data for quantifying the emissions of panelized construction are collected from a prefabrication plant, Landmark Building Solutions (LBS), whereas the data for conventional construction are drawn from previous research of one of the coauthors. The framing phase of panelized construction, including panel fabrication in the plant, panel transportation to the site, and panel erection onsite is investigated and compared with the stick-built method. The associated emission comparison includes operational emissions and embodied emissions; the former has to do with direct emissions during fabrication and construction, and the latter is related to resources during the process, measured in terms of embodied emissions. Different research methods, such as reviews of accounting records and discussion with experts in a task-group setting, are customized to different elements. The research results indicate that carbon emissions are reduced significantly through the use of a panelized construction method compared to the conventional stick-built method.

Most zero carbon buildings (ZCBs) to date are low-rise, with high-rise often considered impossible to achieve zero carbon because of enormous difficulties in socio-technical perspectives. This paper aims to explore the future of high-rise toward zero carbon drawing on the theory of socio-technical systems. Grounded on this theory, ZCBs are examined as social-technical systems, and the technologies and key stakeholders are embedded in the social, cultural, and political environments. The research was carried out through a case study of the first ZCB of three stories in Hong Kong and a workshop with the key stakeholders of buildings. It was found that the delivery solution of the case ZCB was considered to be technically infeasible for new buildings in Hong Kong of typical 40 stories because of geographic constraints. The use of emerging technologies must be explored for enhanced technical feasibility. The split among contributions of end users, the building industry, and the energy sector to carbon emission reductions was considered crucial to developing a practical ZCB definition for Hong Kong. Approaches based on socio-technical systems should help influence end users' attitudes toward reducing energy consumption and enable integrated project delivery of high-rise buildings toward zero carbon.

In recent years there has been increasing attention to sustainability in the construction literature. This paper contributes to this work by mapping legitimacy theory to existing frameworks intended to define the sustainability of water, sanitation, and hygiene (WASH) projects. Legitimacy has been shown to affect organizational continuity, which is similar to this paper's definition of the social sustainability of infrastructure, namely, that it continues to be used and maintained by end users over time. Past work has built sets of indicators that are used to assess sustainability. This paper describes some prominent and widely applied frameworks for sustainability in WASH. Specifically, the frameworks reviewed here are from or are based on publications from UN-Water, the World Health Organization, Water for People, Engineers Without Borders-USA, the Canadian International Development Agency, the U.S. Environmental Protection Agency, the U.S. Peace Corps, and the IRC Triple-S program. The components from this analysis then are mapped to the constructs of legitimacy theory. The frameworks are compared to previous results to see if the components of legitimacy known to be important in promoting sustainable infrastructure are present in sustainability frameworks. This will allow practitioners to fine-tune sustainability frameworks using empirically proven research results.

Investments in commercial energy retrofits are exposed to unique types of risks that can be placed into two categories of risk: market risks (risks because of volatile market conditions) and private risks (risks because of volatile energy consumptions). By identifying such risks as a major contributor to the financial barrier, most studies to date have focused on market risks, yet these studies lacked consideration of the effect of private risks. In response, this paper aims to present a real options valuation (ROV) that aids in determining the financial effects of private risks on commercial energy retrofit investments. In particular, the study focuses on the valuation of phased investments in a large building portfolio under private risks that contribute to the option to defer (wait and see). The ROV adapts the binomial lattice method based on the level of volatility that is estimated using Monte Carlo simulation. The ROV results of the one-phase strategy are compared to those of the two-phase strategy to quantify the benefit of the increased managerial flexibility of the phased investments. The valuation presented in this paper is expected to help building owners and investors make better informed decisions in commercial energy retrofits and, as a result, effectively overcome the financial barrier.

There is a growing awareness of the need for adopting sustainable practices in the construction industry. Included in this is an emphasis on reducing the carbon footprint of site construction activities as a supplement to the more commonly reported preconstruction-phase design and material selection issues. To date, only a modest amount of attention has focused on reducing the direct carbon emissions of site activities, but with growing legislation and social pressure, this will change. Construction activities rely on high-energy-use equipment, and so there is a case for looking at emission abatement options and their costs. The paper examines a number of major-energy-use site activities on two construction projects, their direct emissions, associated abatement options, and the respective costs of these abatements. Earthworks, demolition, and concrete placement are focused on. Abatement beyond business as usual (BAU) is examined and options ranked. Interestingly, it is found for the cases studied that simple options, such as reducing travel distances, sawcutting, and stockpiling waste prior to removal, have the most cost-effective abatement potential. It is acknowledged that each project is unique, and best options may vary from project to project. However, the methodology presented in the paper will stay the same across all projects, and the need to do similar studies across each project will remain so as to improve sustainability of the overall construction industry.

The use of innovative sustainable technologies (IST) has been regarded as an effective approach to enhancing energy efficiency and reducing carbon emissions of buildings. However, contractors face significant challenges in the selection of IST. The reported challenges in the literature include lack of skills and knowledge, uncertainties, risks and the rapid development of a large number of technological alternatives, and decision criteria. The selection process emerges as a multi-attribute, value-based task that includes both qualitative and quantitative factors, which often are assessed with imprecise data and human judgments. This paper aims to establish the decision criteria for the selection of IST for achieving low-carbon existing retail buildings with a focus on the main contractor's perspective. The arguments are informed by the combination of literature review and an indepth case study with a leading United Kingdom contractor. Five broad decision criteria are identified systematically drawing on the contractor's practice. The established criteria are weighted and ranked using the analytic hierarchy process and expert opinions, with margin opportunity being the most important, followed by repeat business, investment costs, differentiation, and transferability. The findings should facilitate the integration of various facets of the selection process and stimulate contractors to use IST.

The objective of initiating sustainability principles is to build structures with reduced environmental effects. The success of achieving this objective usually is measured during the operations and maintenance phases of the project. However, the effect of the construction phase itself, particularly that of construction equipment, is sometimes overlooked. This paper presents a methodology to forecast emissions during construction, thereby providing a chance to quantify construction emissions and develop strategies to mitigate them. The methodology is demonstrated for a road construction project that includes utility work. The methodology forecasts the quantity of pollutants emitted by construction vehicles and equipment and the fuel used based on project characteristics, such as cost and total area of pavement. Data were obtained from the contractor, RS Means, and the U.S. Environmental Protection Agency. The pollutants addressed include CO₂, NO_x, hydrocarbons, CO, particulate matter, and SO₂. The results of this research show that demolition activities are the largest contributors to emissions. They also show that front-end loaders and backhoe loaders produce significantly greater emissions than some other equipment types. Construction and design professionals can use the results from this research to forecast emissions and fuel use during the planning and design phases of projects.

In addition to addressing the basic need of shelter, building envelopes must address concerns of load transfer, energy efficiency, durability, and resilience with respect to natural and human-produced disasters, among other structural and aesthetic concerns. This paper discusses the key barriers to the use of low-tech compressed earth blocks in a resilient and sustainable manner. The paper also presents a process improvement approach through which low-tech masonry approaches can be used to provide a context-appropriate, cost-effective resilient solution. Typical compressive strength values of masonry can range from 7 MPa to 20 MPa forcommonly used concrete masonry units (CMU). Compressed earthen masonry usually peaks at somewhere between 3 and 5 MPa. When working with these lower numbers, general concerns arise from masonry being an elastic-brittle material and become more significant. This paper adopts a process improvement approach to propose a stabilization strategy that can be used to enhance the quality of blocks produced. Fibers are included in the blocks in this research to address susceptibility to local failure when the masonry is exposed to impact load from, for example, flying debris in a high wind region. The process improvement approach is used to optimize the use of fiber in compressed earth blocks and also explore the feasibility of using a low-strength, soil-cement mortar to achieve strength compatibility with the optimized blocks.

Meeting our national infrastructure challenges will require that we answer the question posed by the National Academy of Engineering (NAE): "How can we make our processes more effective, more quality conscious, more flexible, simpler, and less expensive?" In this paper, we share one approach to identify solutions meeting the "simpler" characteristic of NAE's question. Through an interdisciplinary literature review, we characterize "elegant" solutions—those that meet user needs with minimal complexity. Whereas elegance can appear simple in hindsight, it represents a deeper understanding of the actual problem. As with other project outcomes, elegance is dependent on infrastructure project delivery processes: an owner who contracts with a designer to provide a reduction in traffic is encouraging a more elegant solution than an owner who specifies that the designer must add an additional lane. Behavioral scientists have developed choice architecture theory, which is being applied to improve decision processes in fields from medicine to law to finance. We believe choice architecture also could be used to arrange infrastructure delivery processes to encourage elegance. We describe our reasoning by connecting behavioral science theory and common infrastructure project delivery scenarios. We hope this paper begins a discussion to identify and motivate future research in this area.

Integration of disciplines and project participants is prescribed widely as a major remedy to improve effectiveness and efficiency of construction projects. In the context of sustainable high-performance (SHP) projects, integrated design (ID) approach encourages implementation of systems-thinking and early intense collaboration of project stakeholders during the design phase. The desired outcomes in this context would be buildings that not only are cost effective but also have superior energy and sustainability performance over their life cycle. The present paper reports on a research project that attempted to develop and validate a framework for evaluation of the ID teams of SHP projects. The research applied a mixed-method (qualitative–quantitative) research methodology. First, qualitative research (case study and interview) and literature review were used to create a pool of evaluation factors and items that could be used for evaluation/measurement of the performance of the ID teams. These items were generated and organized based on the context, input, process, and product (CIPP) evaluation model. Then, in quantitative phase of research, the evaluation items were tested for reliability and validity by deploying a cross-sectional questionnaire survey of LEED-rated projects and statistical analysis of the collected responses. The research finally proposed a validated framework for evaluation of the ID teams of SHP projects, which consisted of four major elements: an evaluation model based on the CIPP model, 27 evaluation factors, 65 evaluation items, and a measurement format.

Providing energy-consumption feedback has the potential to change people's behavior, a reality that has led to significant energy-usage reductions in residential buildings. However, it is challenging to provide feedback in commercial and educational buildings, because it is difficult to track occupants' behaviors and their corresponding energy usage—especially for temporary occupants. To make providing such feedback possible in commercial and educational buildings, this paper presents a coupled system that monitors the energy load for occupants who have wi-fi-enabled devices. The system benchmarks energy loads using an energy monitoring system that simultaneously detects occupancy and roughly estimates the residents' location through Wi-Fi access points. A preliminary experiment was conducted in an educational building to illustrate the data processing procedure and to test the validity of the system. The experiment results suggest that the event of wireless connection is a valid indication of energy load variation. The proposed system is the prototype of a coupled system that, in the future, will be able to estimate an individual's energy load through an indoor positioning system and, in turn, provide corresponding energy-consumption feedback.

Solar photovoltaic (PV) systems are currently the most competent renewable energy methods to retrofit in and offset electricity for existing and newly constructed school buildings. Increase in electricity prices every year, depletion of fossil fuel reserves, disturbance in hydrological patterns, and damage to the present environment has given stimulation to search for the most viable and effectual solution—to offset public schools need for electricity. The present study is focused on public schools in the state of Washington. The purpose of this study is to determine efficiency of solar PV for public schools and its coherence with the school community. Seventeen public schools were analyzed as case studies. Life-cycle costs were quantified and the acceptance of PV systems from a social context (from members of the school community) was investigated qualitatively. Quantitative and qualitative analyses performed identifies these schools as being influenced with installation of PV, renewable energy education as a new learning curve among students, and as being socially acceptable to school communities.

Heavy-duty diesel (HDD) construction equipment consumes significant amounts of fuel and consequently emits substantial quantities of pollutants. The purpose of this paper is to demonstrate three different predictive modeling methodologies for estimating fuel use and emission rates for HDD construction equipment based on real-world, workplace data. Engine performance data for five-wheel loaders, including manifold absolute pressure (MAP), revolutions per minute (RPM), and intake air temperature (IAT) were used to develop prediction models for fuel use and emission rates of nitrogen oxides (NO_x), hydrocarbons (HC), carbon monoxide (CO), carbon dioxide (CO₂), and particulate matter (PM). For each wheel loader, predictive models were developed using simple linear regression (SLR), multiple linear regression (MLR), and an artificial neural network (ANN). Results indicate that the ANN models accounted for the highest percentage of variability in the data compared with SLR and MLR based on values of the coefficient of determination (R²) for each model. Further, a variable impact analysis was conducted to determine which variables have the most significant effect on fuel use and emission rates for the wheel loaders.

There has been an increasing demand for maximizing the environmental, social, and economic value of our built infrastructure for supporting sustainable construction. However, a major gap still exists in the areas of value analysis; there is no formal model to conceptualize, represent, and reason about value and valuation of our built infrastructure. This paper presents our work in the area of formal axiology-based, sustainability-oriented value analysis of building projects. "Axiology" is a theory of values and worth. Our formal axiology is a theory-based, semantic model for analyzing and assessing the value (worth) of building projects on the basis ofenvironmental, social, and economic values of stakeholders (e.g., energy conservation, safety, economic growth). The first step toward developing our formal axiology is discovering stakeholder values in the context of building projects. Value discovery is the process of identifying the values that are relevant to a particular system. In this paper, we focus on presenting our value discovery work for educational building projects. We discovered stakeholder values from project documents and value literature, and from using stakeholder questionnaire surveys. The paper discusses the questionnaire design, survey results, results analysis, and conclusions in terms of how educational building projects are related to the environmental, social, and economic values of stakeholders. The paper also presents the modeling of these discovered values in the form of a concept hierarchy (taxonomy) as part of our formal axiological modeling.

Lebanon suffers from a chronic problem of electricity shortages, and therefore power outages are common. Electricite du Liban (EDL), the national electricity provider, covers 61% of the total electricity demand, whereas 58% of private households and nearly 100% of commercial and industrial enterprises are using backup generation as an alternative power supply. With the escalation of the electricity supply crisis, several solutions and mitigation plans have been put into action with a total estimated cost of $6.52 billion covering infrastructure, supply, and legal framework. This paper focuses on energy efficiency measures within the commercial sector, which accounts for more than 20% of Lebanon's energy consumption. A literature review is used to formulate a set of hypotheses highlighting the factors that will positively affect the success of an energy efficiency program adopted by businesses in the commercial sector in Lebanon. This paper is part of an ongoing research project that examines user behavior modifications via questionnaires, interviews, and case study analyses with decision makers and end users.

Several international tools and standards (e.g., LEED, BREEAM) exist for evaluating the level of sustainability of buildings and neighborhoods. Nonetheless, they still are not available in the context of new city-scale developments. Although such sustainability appraisal tools are important, of special interest to practitioners is how to ensure that their requirements are well integrated in a proposed city master plan (MP). New eco-city development is the focus of this study. A concise preproject planning process, consisting of stages and activities, is proposed as a guide to assist the design manager of a new eco-city construction project. The proposed process covers the concept phase and assists in evaluating the concept MP alternatives in light of predefined sustainability requirements.

The performance of terrestrial materials, tools, and equipment has synergized over thousands of years. As the prospect of mining and construction in space increases, mining and construction engineers are challenged to design and test technologies that will perform under conditions totally different from those on Earth. The Space Mining and Construction Laboratory (SMCL) at the University of New South Wales has been working on several research projects experimenting with new building methods and materials for space. Of course, sustainability in these extreme environments is critical as the supply of material, machinery, and other necessities from Earth is cost prohibitive. The goal of every project is to design solutions that rely more than 95% on in situ resources (ISRUs). This paper presents the ongoing experimental work in lunar and asteroid mining, waterless concrete, and in situ thermal energy storage.

Earthen masonry generally is brittle, weak, and poor in damage resilience. There is historical evidence that natural fibers, such as straw and horsehair, have been used to reinforce earthen masonry to prevent desiccation cracks and improve tensile strength. However, fibers also have been known to affect mechanical properties negatively, such as with compressive strength (an important quality control parameter for load-bearing masonry) by creating voids and lowering density. This paper reports on findings of a study directed at investigating the feasibility of avoiding such problems in compressed and stabilized earth blocks through optimizing the fiber length when using soil from Newberry, FL. Standard polypropylene fibers were selected for the study. The two lengths of fibers studied were 54 mm and 27 mm. The test results showed a general improvement in compressive strength of the fiber reinforced matrices compared to the unreinforced ones. Although an improvement in modulus of rupture (MOR) was observed for matrices reinforced with 54 mm fibers, results varied for the other fiber-reinforced matrices. An improvement in post-initial crack behavior was observed for all fiber-reinforced matrices compared to the unreinforced ones. The 54 mm fibers yielded the best results based on the influence on MOR, compressive strength, and deformability compared with the other matrices.

Approximately 95 million metric tons of asphalt is recycled each year in the United States, making it one of the most recycled materials. The technology for use of close to 100% recycled asphalt (RAP) is available. This study examines how owners of projects view the idea of using 100% RAP. The objectives of this study were to obtain city, town, county, and state government officials' opinions on the use of 100% RAP and to find out how respondents felt about the use of RAP in their current asphalt roads. A survey was sent to 250 industry officials from all over the country. Statistical tests were conducted to see if the results were indicative of the population. Results show that there is some hesitation in the use of 100% recycled asphalt because of the unknown properties of the asphalt, past performance issues dealing with asphalt containing less than 100% RAP, and the unknown life expectancy of the 100% recycled asphalt. Also, it was determined that 100% recycled asphalt would have to be less expensive than current asphalt on the market for it to be attractive.

The selection of highway pavement design and construction strategies traditionally are based on the life-cycle cost analysis (LCCA) of different alternatives. However, with the growing concerns on sustainable development, the environmental aspects of these alternatives start to attract more attention, and even become the essential component of decision-making criteria. The objective of this study was to assess long-life pavement design strategies based on the principles of sustainability, in particular costs and greenhouse gas (GHG) emissions. The evaluation process consists of three steps: design simulation, life-cycle cost analysis (LCCA) and life-cycle assessment (LCA) that focuses on the environmental effects of different alternatives. A multibillion dollar major road construction project currently being implemented in Hong Kong was chosen as a case study to illustrate the analysis procedure. The results show that the integration of design simulations and LCCA and LCA models is effective to predict the economic and environmental performance of road construction projects. The analysis enables decision makers to understand the sustainable implications of different pavement design strategies, as well as to identify a solution that optimizes the needs for cost saving and environmental conservation.

Building construction, operation, and maintenance altogether account for nearly one-third of global carbon emissions. In Hong Kong, buildings contribute to 90% of electricity consumption and 60% of greenhouse gas emissions. Energy-efficient building has emerged as an effective approach to reducing energy consumption and carbon emissions. This paper aims to estimate the energy saving potential of different energy-efficient measures for office buildings that are an important sector of commercial buildings in Hong Kong. The energy efficient measures were identified using a four-tier framework covering building envelope, building services, renewable energy and human behavior. The potentials of the measures in reducing energy consumption were estimated using eQUEST Software. The results show that building services and building envelope are the main areas to be addressed for achieving energy-efficient office building design. The use of more efficient HVAC systems and low-emissivity windows are revealed as most favored measures for reducing energy consumption of office buildings in Hong Kong. The findings should inform low-energy building design in hot and humid subtropical urban environments.

In pursuit of sustainable buildings, construction professionals must overcome the challenge of selecting a combination of building assemblies and materials that satisfy all project objectives, including sustainability. Optimization techniques have been used in the selection process of optimal or near optimal solutions on the basis of multiple building objectives, such as project cost, duration, and environmental effects. SimulEICon is a tool that can aid researchers in understanding relationships among multiple project objectives. In addition, the tool can help design and construction professionals properly select building materials and components. SimulEICon is applied to a case study that includes the construction of the building envelope. The results show that, at least in theory, there does not exist a design solution that is clearly dominating and always chosen in different scenarios using Monte Carlo simulation. In addition, trade-off relationships mostly are observed between time and cost, as well as time and CO₂ emissions. It is interesting to observe that the case study shows a nontrade-off behavior between cost and CO₂ emissions in many cases. Certainly, future studies are needed to verify these observations further.

Balance of systems (BoS) includes all costs related to solar beyond the photovoltaic (PV) modules and inverter system. BoS constitutes 78% of the cost of rooftop residential PV systems and 73% of the cost of commercial rooftop PV systems. An essential step in reducing the overall cost of PV systems is a systematic approach to labor costs reduction, supported by an understanding and quantification of the activities that make up the installation process. Historically, time and motion studies have occurred on standardized factory floors, but these have been extended to the construction industry. Now this method is extended to solar PV systems, addressing barriers, such as nonstandardized hardware, ad-hoc nomenclature, ad-hoc processes, and varying contextual parameters. The proposed methodology takes a three-pronged approach to addressing these barriers, including initiating a formalized domain specific language (DSL), utilizing a flexible site log, and creating a robust data repository. The preliminary data from multiple residential sloped-roof and commercial flat-roof sites provide comprehensive testing and validation of the proposed methodology. The data collected are used to identify the theoretical minimum installation and suggest the application of lean construction practices to reduce further installation labor and overall BoS costs by more than 50%.

Integrated project delivery (IPD) has proven an effective delivery system in the private sector as evidenced in recently completed case study projects. Despite this success, case study researchers assert IPD currently is not being used in the public sector because of state laws limiting the delivery systems available for public owners and the difficulty of changing these laws. This paper examines a set of building construction projects undertaken by one public owner over a 12-year period, specifically the change orders associated with these design-bid-build projects. The authors analyze these change orders to determine whether this owner could have realized the same benefit as private owners if IPD had been available as a delivery method. The authors hypothesize that owners often use change orders to ensure their own satisfaction postdesign because the design intent does not match their specific requirements (i.e., owner requested changes), and the collaborative nature of IPD would lower the need for such changes significantly, providing added value to the owner because of a more complete project scope being determined earlier and with contractor input during the design phase. This paper presents data to support these hypotheses illustrating the benefits of IPD for public owners, and in turn, building a compelling case for adopting IPD in the public sector.

This paper presents a new method for activity analysis of construction workers using inexpensive RGB+depth sensors. This is an important task, as no current workforce assessment method can provide detailed and continuous information to help project managers identify bottlenecks affecting labor's productivity. Previous work using RGB-D images focuses on action recognition form short video sequences wherein only one action is represented within each video. Automating this analysis for long sequences of RGB-D images is challenging because the start and the end of each action is unknown, recognizing single actions is still challenging, and there are no data sets and validation metrics to evaluate algorithms. Given an input sequence of RGB-D images, our algorithm divides it into temporal segments and automatically classifies the observed actions. To do so, the algorithm first detects body postures in real time. Then a kernel density estimation (KDE) model is trained to model classification scores from discriminatively trained bag-of-poses action classifiers. Further, a hidden Markov model (HMM) labels sequences of actions that are most discriminative. The performance of our model is tested on unprecedented data sets of actual drywall construction operations. Experimental results, in addition to the perceived benefits and limitations of the proposed method, are discussed in detail.

Injuries from falls and overexertion during ladder climbing activities are common in construction. To prevent ladder-related injuries, it is important to understand why those injuries occur. Thus, there has been significant research effort put into identifying mechanisms and causes of falls and work-related musculoskeletal disorders (WMSDs) from ladder climbing. These include epidemiological studies, studies on the mechanical aspects of ladder-related injuries, and biomechanical studies. Biomechanical analysis during ladder climbing has been implemented widely to understand the fundamental causes of ladder-related injuries in terms of musculoskeletal stresses on the human body. However, previous experimental approaches that use marker-based or IMU (Inertial Measurement Unit)-based motion capture and force transducers to collect motion and force data for biomechanical analysis are limited because of the difficulty in mimicking all of the possible situations that can happen during ladder climbing on actual worksites. To address this issue, we propose onsite biomechanical analysis for ladder-climbing activities by combining vision-based motion capture systems and force prediction models. To test the feasibility of the proposed method, we conducted a case study. As a result, we found that the method has true potential to broaden our understanding of the causes of falls from ladders and of WMSDs by estimating musculoskeletal stresses on the human body during ladder climbing without using any invasive measures.

Construction worker absenteeism can damage project performance significantly, but the complex nature of absence behavior does not offer a simple explanation for this phenomenon. We have very limited knowledge, in particular, of the social aspect of construction workers' absence behavior (e.g., social norms, social influence, and absence culture), which has been found to be important factors in shaping employees' behavior in organizations but often has been overlooked by construction managers. Therefore, more studies on this social aspect of construction workers' absence behavior are warranted, especially for designing interventions for absence behavior on projects, if needed. In this research, the relationships between workers' perception/attitudes and their absence behavior are investigated using a mixed-research methodology incorporating agent-based modeling and surveying. Using this methodology, we have found that high levels of social adaptation can be a cause of a low absence level in work groups, particularly when workers have a high level of strictness in self-regulation, because social norms of low absenteeism can emerge in this condition and are reinforced by low levels of peers' absence over time. With this result, it is suggested that construction managers foster favorable social norms in groups, rather than focus only on formal rule enforcement targeting individuals.

In an attempt to evaluate the efficiency of labor-intensive construction operations, project managers compare actual with historical productivity for equivalent operations. However, this approach to examining productivity only provides a relative benchmark for efficiency and may lead to the characterization of operations as authentically efficient when in reality such operations may be only comparably efficient. Optimal labor productivity—the highest sustainable productivity achievable in the field under good management and typical field conditions—can provide an absolute benchmark for gauging performance. This optimal productivity level is lower than the productivity frontier—the theoretical maximum achieved under perfect conditions—because of system inefficiencies, which emerge because of factors outside the control/influence of project managers. Conversely, optimal labor productivity tends to be higher than actual labor productivity—the productivity achieved in the field—because of operational inefficiencies, which are the result of suboptimal managerial strategies. Estimating the magnitude of these system and operational inefficiencies will help project managers determine optimal labor productivity. This paper develops a two-pronged strategy for estimating optimal labor productivity. The first prong represents a top-down approach that estimates optimal productivity by introducing system inefficiencies into the productivity frontier. A qualitative factor model is used to determine the effect of system inefficiencies. This top-down approach yields the upper level estimation of optimal labor productivity. The second prong is a bottom-up approach that determines optimal labor productivity by removing noncontributory work from actual productivity in a discrete event simulation. This bottom-up approach generates the lower level estimation of optimal labor productivity. An average of the upper and lower limits reveals the best estimate for optimal labor productivity. In conjunction with a relevant literature study and a discussion of the two-pronged approach's methodology, this paper ultimately analyzes data from a pilot study, presents results, and evaluates the feasibility of this two-pronged strategy for estimating optimal labor productivity in construction operations.

The communication of a project's design to craft professionals can affect project performance significantly. Despite advancements in 3D computer modeling and integrated information systems in recent decades, the spatial design is still primarily delivered to the construction workforce in 2D drawings of various views. These views must be combined and encoded to understand all orientations of the engineering element effectively. Three-dimensional computer aided design (3D CAD) and additive manufacturing (3D printing) provide promising alternative formats for presenting spatial engineering information. By asking craft professionals to complete a reconstructing task of a simple structural frame using 2D drawings, a 3D CAD interface, and a 3D printed model, the cognitive workload demands can be measured. After completing the task, the craft professionals were surveyed on their perceptions of mental workload in six main factors using the NASA Task Load Index (TLX): mental demand, physical demand, temporal demand, performance, effort, and frustration. In addition, the subjects provided insights into their preferences for the different model types. Lower workload scores generally are desirable and indicate lower demands on an individual's mental resources, allowing for concurrent processing of other information. The results found that a physical 3D model, on average, requires lower composite cognitive workloads than either 2D drawings or a 3D computer model. The paper's primary contribution to the overall body of knowledge is the understandng of the cognitive demands of craft professionals when presented with spatial engineering information in various formats.

Mechanical, electrical, and plumbing (MEP) systems coordination is a process during the preconstruction phase through which the proposed location and route of each system components are specified. The MEP coordination process has changed significantly because of utilization of Building Information Modeling (BIM). There is a gap in knowledge regarding productivity measurement of a MEP coordination team. Moreover, there is a need for research to enhance our understanding about important factors affecting productivity of MEP coordination. The main objectives of this research are to document approaches for conducting MEP coordination using BIM, identify metrics for measuring productivity of MEP coordination, and identify factors affecting MEP coordination productivity. A questionnaire survey was conducted to achieve these objectives. The survey shows that the most frequently used metric for conducting MEP coordination using BIM is square feet of coordinated area per total coordination hour. Moreover, experience level of MEP coordination team members is the top factor thataffects MEP coordination productivity. The findings of this study indicate that the construction industry lacks a systematic procedure to record information to track, measure, and compare MEP coordination productivity across different coordination projects.

Productivity benchmarking has been an elusive element for construction companies around the world. With the advent of the Internet, many companies have attempted Web-based database and benchmarking efforts since the late 1990s. However, an industry consensus on a collaborative database and benchmarking tool has yet to be established. New opportunities are being generated for efficient and free database services that are challenging the established paradigm. Google fusion tables (GFT) Web application was launched in 2009 and has been evolving ever since release. GFT provides a user-friendly, collaborative, and interactive database tool that is available to the public on an international scale at no charge. This tool provides users with options to publish their data on another site, make it publically available and discoverable by search engines, or keep it private. The research presented in this paper aims to develop a pilot database using GFT for the storage and management of data from work-sampling observations for designated work trades on a project located in Calgary, Alberta, Canada. Data were uploaded to the Google cloud to commence the pilot database. The collected data werecomplemented further by the tool's charts and shared with participating parties. The application of GFT as a data management system was tested against a selected company's extranet and individually assessed through the survey of the users of the pilot program.

Construction industry labor productivity is an important metric that provides feedback about task, project, and industry level trends and improvements. However, labor productivity for the construction industry historically hasbeen elusive to define, both qualitatively and quantitatively. Existing research studies and methods have provided different calculation methods at a variety of levels (task, project, industry), but none proved universally satisfying. This study generated a new metric using RS MeansBuilding Construction Cost Data. The metric was derived using labor and cost information from a sample of RS Means' construction activities. The sampled data were indexed and combined to generate labor productivity metrics (output per labor hour and output per labor cost). The research findings present a construction industry productivity metric based on RS Means' data that is reliable, repeatable, and developed from a consistent and accurate data source. The study results showed a slightly sporadic but consistent decline in both output per labor hour and cost from 1990 through 2012. With this new metric, construction professionals now will be able to analyze industry level productivity by means of a commonly used industry reference manual.

Labor productivity frontier is the theoretical maximum production level per unit of time that can be achieved in the field under perfect conditions. This level of productivity is an abstraction that is useful in the estimation of optimal productivity for labor-intensive operations. This paper reports on a pilot study performed to evaluate the feasibility of a dual approach for estimating the productivity frontier for a simple electrical installation. The first approach involves estimating the productivity frontier by using observed durations from a time and motion study. The movements of a worker are captured by multiple synchronized video cameras. The actions that make up a particular task are identified from the video frames and categorized into contributory and noncontributory actions. The best series of contributory actions are identified based on the shortest time taken to complete a task, and a synthetic worker model is used to determine the productivity frontier as the sum of the shortest durations for each action. The second approach involves estimating the productivity frontier by using estimated durations on the same time and motion study. The probability distributions that best represent action durations are identified, and the productivity frontier is defined as the sum of the lowest values from each of the distributions at a 95% confidence interval. The highest labor productivity value from these two strategies is taken as the best estimate of the productivity frontier. An accurate estimate of labor productivity frontier is the first step toward developing a process that will allow project managers to determine the efficiency of their labor-intensive construction operations by comparing actual versus optimal (rather than actual versus historical) productivity. Toward this end, this paper reviews relevant literature, presents the details of the proposed dual approach, introduces results from the pilot study, and evaluates the feasibility of this methodology for estimating the labor productivity frontier.

One of the main goals of the solar energy industry is making solar technologies cost-competitive with other forms of energy. In particular, balance-of-system (BoS) costs associated with the installation of photovoltaic (PV) systems require significant cost savings to stay competitive with conventional energy sources. Significant potential for cost savings exists through increasing the productivity of the labor force installing the system. A gap in knowledge exists regarding approaches to measuring and improving solar installation labor productivity. The objectives of this research were to design a proper method for conducting time and motion studies for solar contractors, collect and aggregate data related to installation practices, and examine factors that affect solar installation labor productivity. To achieve these objectives, the Georgia Technology Research Institute (GTRI) laboratory, in partnership with the Rocky Mountain Institute (RMI), conducted time and motion studies on residential and commercial projects sites to collect and document data on the steps in the installation process of PV systems. An aggregation and analysis of data recorded for each step in these studies were performed to estimate the time to accomplish each task and identify the patterns that affect labor productivity. For this research, the proposed time and motion study approach was examined on two residential and commercial solar installation projects. The findings of the research show that conducting proper time and motion studies can determine the time spent on solar PV installations activities to understand better which activities consume the most labor time and what types of contextual variables have greater effects on installation labor productivity.

Strategic workforce management decisions (e.g., hiring, training, and staffing) have a direct effect on the cost, schedule, and quality of work. This paper presents the preliminary findings of a survey of construction/site managers representing a set of building construction projects in Lebanon. The survey serves to capture current workforce conditions and management practices in an environment that is dominated by residential construction projects and a transient or migrant workforce. Despite the international location of the survey, the results indicate a worker demographic similar to that found in the southwestern United States and other areas with significant residential construction. The results also serve to highlight the significance of basic management techniques in reducing absenteeism: adopting training programs to increase the skill level of workers, providing incentives to increase the tenure of workers onsite, and arranging the working schedule to favor less overtime.

Construction labor productivity remains of great importance because of its direct effect on project costs. Numerous parameters (factors and practices) that critically affect labor productivity have been identified in past studies through expert knowledge obtained from surveys. The objective of this paper was to explore whether there is a gap in experts' knowledge in identifying the critical parameters by comparing their perspectives to the results of data-driven analyses of the parameters and labor productivity field data. This paper presents a methodology for identifying critical parameters using both a factor survey and a data-driven approach. The factor survey approach ranks the critical parameters based on the responses of both project management and trade level personnel on a project. The data-driven approach ranks the parameters based on their degree of influence on productivity through filter feature selection on data collected from the actual project. Results of the comparison of factor rankings from the project management perspective, trade perspective, and data-driven approach indicate a major discrepancy between the experts' perspectives and the data-driven results suggesting a need for verification of expert-based results with additional field studies of factors affecting labor productivity.

Building Information Modeling (BIM) and its implementation have been reshaping the construction industry continuously. Fundamental changes are taking place to address the dual challenges of BIM in technology utilization and business operation. The lack of competent BIM talent has been identified as a major obstacle in BIM transformation. However, there has been little published research on the effects of BIM on the future workforce and how companies can adapt to BIM-driven business transitions with appropriate workforce planning and talent acquisition. This paper discusses key issues in workforce planning and adaptation strategies for companies that are looking into BIM adoption. The paper reviews and identifies the unique skill set requirements of BIM and desired changes in current talent planning and acquisition practices. A preliminary workforce planning/succession model is proposed to facilitate industry adaptation to BIM at the company level. The model outlines the procedures that companies could follow to align workforce analysis with their strategic goals oriented to BIM business; identify competency and skill gaps in the existing workforce; create and implement development plans; and monitor, assess, and continuously improve workforce plans. A case study was performed to verify the model. Results of this research provide valuable insights into intellectual preparation in companies that are at the early stage of BIM adoption and implementation.

This paper defines a framework for analyzing and predicting trust-based relationships in networks of project participants when they utilize different decision-making methods. The paper first presents different types of trust and attributes that facilitate establishing and promoting trust. Next the paper presents a range of decision methods and attributes that help differentiate these methods in terms of how team roles are assigned, objectives are defined and prioritized, alternatives are generated and communicated, and preferences are gathered. Qualitative assessments determine the decision attributes each decision method supports and the potential effect of each decision attribute on each trust-building attribute. Overlaying the two assessments is a qualitative assessment of the effect of each decision method on each trust-building attribute and overall trust. The paper outlines hypotheses about the effect of decision methods on trust. For example, one hypothesis is that methods that involve a broader array of decision method attributes are likely to promote system- and cognitive-based trust. The paper provides a plan for hypotheses testing, as well as recommendations on progressing decision methods with greater effect on trust.

Specialty subcontractors enter construction projects because of their expertise or possession of special machineries and skilled workers or both. Like other project-based organizations, specialty subcontractors gain their organizational knowledge during projects. However, experiencing specific limited tasks several times in different circumstances raises their level of knowledge over that of other parties and impedes knowledge deterioration over time. This organizational knowledge distinguishes them from other parties involved in construction projects. Despite their critical role in the construction industry, specialty subcontractors have not received enough attention from academia. This study looks at the procedures of different knowledge that specialty subcontractors acquire through their experience and the way they use it in their future jobs. This study proposes a decision-making model exercised by the specialty contractors, which differentiates events from routines. The model was validated through interviews with constructional professionals. This model clarifies the potential contribution of subcontractors in managing knowledge in different stages of construction projects.

Sewer construction in urban areas often has significant effects on work zone traffic control, traffic flow, and safety. Contractors typically introduce night shifts to meet contract schedule and reduce traffic congestion. However, there is a lack of understanding of how shift work is associated with labor productivity in sewer construction. This research investigated labor productivity of 10 major activities in sewer and drainage construction in Ho Chi Minh City, Vietnam, when these activities were performed in both day and night shifts. Levene's tests and t-tests were employed to analyze the data and investigate the research hypothesis. Results revealed that four activities were significantly sensitive to shift work and the other six activities were not. Pavement cutting and timber piling activities had higher productivity in day shifts. In contrast, steel sheet piling and manhole concreting were more productive in night shifts. Labor productivity of excavation, formwork installation, rebar fabrication/installation, pipe installation, sand filling, and asphalt pavement was not significantly different between the two shifts. The results were verified by the experienced site managers/engineers through structured interviews. The findings from this paper help contractors effectively manage their sewer projects by allocating resources appropriately to construction activities between the day and night shifts.

This paper discusses a research project to develop a "knowledge-based information system for construction cost estimating and scheduling" (KISCCES). To accomplish the goal, researchers developed a prototype project management system that can produce pictorial data for all involved parties, and cost and schedule in a nearly real-time basis. The scope of the research project includes transferring pictorial data via the wireless network, measuring construction productivity using time-lapse video, and developing a graphic user interface for cost estimating and scheduling. The tasks for this project are outlined as follows: conduct literature review, purchase necessary software and hardware, define measurement data for each activity, conduct field experiments in construction projects to transmit time-lapse video wirelessly and consistently, and develop a prototype graphic user interface to estimate cost and duration on a nearly real-time basis. Upon development of the KISCCES, the researchers evaluated the estimated cost and schedule by statistically comparing it with estimates by construction industry experts.

Automated environmental compliance checking requires automated extraction of rules from environmental regulatory textual documents, such as energy conservation codes and U.S. Environmental Protection Agency (EPA) regulations. Automated rule extraction requires complex text processing and analysis for information extraction and subsequent formalization of the extracted information into computer-processable rules. In our automated compliance checking (ACC) approach, we first classify the text into predefined categories to filter out irrelevant text, thereby improving further semantic information extraction and compliance reasoning efficiency. The categories used are predefined in a semantic text classification (TC) topic hierarchy. In this paper, we present our machine-learning-based TC algorithm for classifying clauses in environmental regulatory documents based on the TC topic hierarchy. In developing our TC algorithm, different text preprocessing techniques, machine learning algorithms, and performance improvement strategies were tested and evaluated. Our final TC algorithm was tested on 10 regulatory documents, such as the 2012 International Energy Conservation Code, and evaluated in terms of precision and recall. The algorithm achieved around 96% and 85% recall and precision, respectively, on the testing data.

Automating the process of compliance checking is expected to reduce the time and cost of the process, as well as reduce the probability of making compliance assessment errors. Automated reasoning is essential for enabling the automation of compliance checking. Among the different types of formally defined logic, which has varying degrees of descriptive capability, first order logic (FOL) is the most widely used for logical inference making. In this paper, we present our FOL-based representation method for supporting automated regulatory compliance checking in construction. The expressivity of FOL is leveraged to describe various concepts and their relations in construction regulations. Prolog is the most widely used logic programming language and reasoner. We used B-Prolog (an implementation of Prolog) for implementing our proposed method. We tested the method on representing and reasoning about quantitative requirements in Chapter 12 of the 2006 edition of the International Building Code. We developed 109 instances of project information as the test set. We tested the performance of our proposed method in detecting noncompliance instances. Using automatically extracted and transformed regulatory information (and represented in the form of logic clauses), we achieved 0.929 and 0.981 for precision and recall in detecting noncompliance instances, respectively. We also compared automated checking to manual checking in terms of the time efficiency. Automated checking takes a time shorter than 1/10,000 of that for manual checking.

Building information models (BIMs)increasingly are applied throughout a building's life cycle for various applications, such as building renovation, energy simulation, and performance analysis in the architecture, engineering construction, and facility management (AEC/FM) domain. In a traditional approach, as-is BIM is primarily manually created from point clouds, which is labor intensive, costly, and time consuming. This paper introduces a method to create as-is 3D building models automatically from an unorganized point cloud collected by a 3D laser scanner. The collected raw data are downsized and segmented to individual plane segments. Then, boundary estimation method and building component recognition methods are applied to recognize all building components as individual objects and visualize them as polygons. The proposed method was tested on outdoor point cloud data to validate its feasibility and evaluate its performance. The analyzed results showed that the proposed method would simplify and accelerate the as-is building model creation process.

Demand has been growing for 3D reconstruction of as-built pipelines that occupy large areas within operating plants. In practice, measurements are efficiently performed using laser-scanning technology; however, reconstructing an as-built pipeline from this laser-scanned data remains challenging. The data acquired from the plant facility can be incomplete because of complex occlusion, or it can be affected by noise because of the reflective surfaces of the pipelines and other parts. The aim of this study was to propose a method for generating models of entire pipelines that include straight pipes, elbows, reducers, and tee pipes from laser-scanned data. The proposed 3D reconstruction method for as-built pipelines is divided into three main tasks: identifying the types and locations of the pipelines from the laser-scanned data, segmenting the pipelines into each type of pipe form, and reconstructing the pipelines' geometry and topology and generating models of them. Field experiments were performed at an operating industrial plant to validate the proposed method. The results revealed that the proposed method indeed can contribute to the automation of 3D reconstruction of as-built pipelines.

Accidental falls (slips, trips, and falls from height) are the leading cause of death and injury on a construction site. Assessing the risk of such falls, therefore, becomes a fundamental step toward reducing these accidents. However, the quantitative assessment of a fall risk for construction workers is still very challenging because of sparse data related to fall accidents. Recently, there has been a growing interest in the identification of near-miss fall accidents to utilize them as supplementary data for fall-risk assessments. Current documentation for near-miss fall accidents is based on workers' self-reporting, a fact that adds variability to the data. In response, this research introduces a method that can detect near-miss fall incidents based on inertial measurement units (IMUs). A preliminary laboratory experiment collects data on ironworkers' typical movements, postures, and near-miss fall accidents. Workers' postures and movements are recognized through supervised classification algorithms; near-miss fall incidents during the classified posture/movement are quantifiably detected based on the time-series anomaly detection approach. Such research helps to identify the possibility of fall accidents more precisely according to worker's activity data. Additionally, documenting near-miss fall data provides quantitative data for ironworkers' fall-risk assessment, a significant step forward in the field.

Three-dimensional (3D) imaging technologies, in particular 3D laser scanners, are becoming more accessible and more accurate. These advances are providing engineers and architects with vast quantities of raw, geometric data. Whereas this data is visually appealing and intuitive to the human eye, it contains very little meaning beyond that. The research presented in this paper presents and compares methods for attributing meaning to dense 3D point clouds. Two of the methods developed and presented utilize 2D and 3D Hough transforms to represent the points as lines and planes. The third method uses point segmentation techniques to group points belonging to the same plane. The initial focus is on structural steel systems and connections modeling for analysis of reuse. The advantages and disadvantages of each method are outlined, and each method is evaluated for its potential to provide engineers and architects with useful and meaningful point clouds from 3D laser scanners. The point segmentation techniques exhibit the most potential by allowing for the location and orientation of any surface to be identified.

Spatial data collection in urban environments for the extraction of building inventory information is important for many applications, such as urban planning, storm water management, hazard mitigation, vulnerability assessment, and loss estimation, to name a few. Creating and updating building inventory databases in large and developing urban environments benefits from efficient data acquisition and data processing techniques. This study leveraged and integrated the advantages of ground-based mobile laser scanning and aerial photography through an automated method to extract building inventory information. The integration of terrestrial and aerial data enables the identification of buildings in the data set and the extraction of both roof polygons and wall footprints. The presented method was evaluated with actual data sets collected from a typical residential area. The area of roof polygons extracted by the automated approach differs by less than 5% when compared to manually calculated values. Also, the proposed method allows for accurate extraction of walls captured within the point cloud.

The continuous improvement in the function and performance of unmanned aerial systems (UASs) promotes the need for specific research to integrate this leading-edge technology into various applications across Departments of Transportation (DOTs). DOTs of several states have started looking into using UAS technology for different purposes from tracking highway construction projects and performing structure inventories to road maintenance and monitoring roadside environmental conditions, as well as many other traffic management or safety issues, albeit individually focusing on specific usage scenarios. This study investigates various divisions and offices within a Department of Transportation to determine the operational requirements for UAS usage in specific divisions that have the potential to implement this technology to aid and supplement their daily operations. Through a series of interviews with subject matter experts at the management and operational levels, a matrix of user requirements for tasks that have the potential to use UAS was developed. This matrix is mapped to a UAS technical matrix that embeds the technological and technical requirements for development of a potential UAS. These matrices can be used by other DOTs for defining the design specifications for UAS that can fulfill their construction-related operational requirements.

The detection of pavement surface defects is a critical task in assessing and monitoring pavement condition. A number of image-based approaches have emerged in recent years to automate the process of surface defect detection. A prominent technology is the consumer depth camera, a camera that captures not only images but also the varying distance between scene objects and the camera itself in a format of 3D point clouds, similar to 3D point clouds obtained via light detection and ranging (LiDAR). The main challenge in applying a consumer depth camera to pavement defects detection lies in the low resolution and high random noise of the raw data. This paper presents a method that effectively addresses this challenge. It starts by filtering the signal noise using disciplined convex optimization and then enhances the resolution via moving least square up-sampling. This newly created method was tested in the field to detect different types of pavement defects including cracks, ruts, and potholes. It was found to be effective in detecting and quantifying pavement defects to provide quantitative information to support informed decision making in pavement management.

Point clouds collected by laser scanners have been used in various architecture, engineering, and construction (AEC) projects. Effective uses of laser scanners on job sites require reducing the interferences of data collection with field activities while ensuring the data quality. Existing laser scan planning methods focused on visibility analysis with limited considerations about the level of detail (LOD) of collected point clouds even though LOD is a function of factors other than visibility. This limitation leads to insufficient LOD of certain features in point clouds for decision support. This paper presents a laser scan planning approach that integrates geometric feature clustering and data quality checking methods for addressing this limitation. The inputs of this approach include an as-designed model integrating LOD requirements of geometric features. The algorithm first clusters geometric features to reduce the computational complexity of scan planning. It then uses a sensor model of laser scanning to generate a "feasible space" for scanning each cluster of features. After that, it assesses the number of features covered at candidate scanning locations and pinpoints scanning positions covering more features with less scans. The results in a case study show that this approach outperforms manual scan planning in data's LOD.

Abnormally long operation cycles of pilot tube microtunneling (PTMT) can cause construction delays, difficulties of project coordination, and equipment maintenances costs because of improper operations. Manually logging and analyzing abnormal operation cycles is tedious and time consuming. This paper presents an approach that enables automated identification and analysis of abnormal cycles of PTMT based on automatically logged PTMT operational data. The data collection instrument is a data logger that automatically records time-series of hydraulic pressures of boring machines from pressure transducers attached to their hydraulic lines. Different PTMT operations (e.g., boring, retracting) result in different patterns in these time-series. The authors developed an approach that automatically recognizes time-series patterns representing operation cycles of three phases of PTMT installation. This approach uses an artificial neural network (ANN) to classify a time-series as belonging to a certain PTMT phase, and then applies an adaptive anomaly detection algorithm (AADA) to clean and split the time-series into operation cycles. The results from a case study show that this automated approach enables users to analyze abnormal cycles of PTMT and gain insights about how to improve PTMT productivity.

Modularization and preassembly are parts of a trend toward staged fabrication that has been developing in the construction industry in many parts of the world over the past few decades. Successful delivery and transportation of materials in staged fabrication processes always has been a key challenge. Although substantial advances in modularization and prefabrication have been achieved recently, there is still a significant rate of damages and defects occurring during transportation and shipment. In addition, there are inaccuracies in staged-fabricated assemblies because of manually intensive quality control during the fabrication process. Thus, there is a significant need to monitor the fabrication processes continuously to avoid significant rework costs and delays. This paper presents an automated approach to register laser scanned data, which represents as-built status, with 3D CAD models for prefabricated steel assemblies. Moreover, automated registration enhances 3D tolerance analysis for automated quality control of prefabricated assemblies. An iterative closest point (ICP)-based model is used for automated registration in the presented paper. An experimental study is conducted to validate the proposed model for monitoring the fabrication and installation processes. Experimental results show that the presented approach can be used to detect defected parts or fabrication inaccuracies precisely and quickly.

Existing buildings now represent the greatest opportunity to improve building energy performance. Building energy simulation is becoming increasingly important, because the simulation results can assist the decision makers to reach the solution quickly for improving building energy efficiency and reducing environmental effects. However, most of the time, there is no available as-is 3D building models for the existing buildings to conduct energy simulation. Today, it is a common practice to obtain point clouds of existing buildings through3D laser scanning technologies for as-is building modeling. Current methods using point clouds need manual processes to prepare thermal zones based on point clouds data, which is very time consuming and labor intensive. This paper introduces an automated thermal zone creation method to create both a building zone and room zones. A building thermal envelope was extracted from 3D point clouds. Then, 2D building floor plans were used as references to determine the location and size of each thermal zone accurately. A preliminary experiment has been conducted on a residential house to validate the proposed method, and the created building components and thermal zones were imported successfully into a building energy simulation program and ready for various energy analyses.

Efficient onsite data acquisition of a construction project enables the comparison of the actual state of the project to the as-plan state so that potential delays can be identified early within the project life cycle. Traditionally, onsite data are collected manually, a time consuming, costly and error-prone task, and therefore not justifiable in modern construction management. To overcome the challenges corresponding to such manual approaches, the application of automated progress monitoring of construction sites has attracted the attention of researchers. To enable an effective application, it is necessary to evaluate the reliability of the available technologies in collecting onsite data. In this paper, a qualitative evaluation of the applicability of the state-of-the-art automated progress monitoring technologies, namely camera, LiDAR, and 3D range imaging, has been carried out. A set of experiments has been carried out to compare the time of data collection for each technology. LiDAR provides the most accurate 3D estimates. The time of data collection of the Leica HDS6100 laser scanner is shown to be seven times faster than that of the DSLR camera in an indoor construction site simulated laboratory. However, the cost of LiDAR devices is the major economical drawback of the technology.

Recent research efforts on improving construction progress monitoring have focused mainly on model-based assessment methods. In these methods, the expected performance typically is modeled with 4D BIM, and the actual performance is sensed through the 3D image-based reconstruction method or laser scanning. Previous research on 4D augmented reality (4D AR) models—which fuse 4D BIM with point clouds generated from daily site photologs—and also laser scan versus BIM, have shown that it is possible to conduct occupancy-based assessments, and as an indicator of progress, detect whether BIM elements are present in the scene. However, to detect deviations beyond typical work breakdown structure (WBS) in 4D BIM, these methods also need to capture operation-level details (e.g., current stage of concrete placement: formwork, rebars, concrete). To overcome current limitations, this paper presents methods for sampling and recognizing construction material from image-based point cloud data and using that information in a statistical form to infer the state of progress. The proposed method is validated using the 4D AR model generated for a building construction site. The preliminary experimental results show that it is feasible to sample and detect construction materials from the images that are registered to a point cloud model and use frequency histograms of the detected materials to infer the actual state of progress for BIM elements.

The level of automation in the construction industry stands in stark contrast to other engineering industries, such as automobile manufacturing, wherein most of the tasks are done by machines with minimal oversight from human operators. This disparity can be attributed to the distinctive nature of construction vis-à-vis manufacturing: customized projects, uncontrolled outdoor worksites, and necessary collaboration among disparate entities. New approaches toward control are required to address these challenges. This paper introduces a novel method that enables the automation of entire construction operations by using discrete event simulation models to orchestrate and actuate robots on the construction site. It is hypothesized that the adoption of this method would enable hitherto unexperienced levels of operation productivity and quality, and cost, and time savings, as well as reduction in safety incidents on construction worksites. A preliminary demonstration of the orchestration of small-scale electronically operated equipment models in the actual workplace using a DES model also is presented in this paper.

To assist crane operators in rapidly perceiving 3D working environments at dynamic construction sites, an automated rapid 3D workspace modeling method is proposed in this paper. A custom-designed laser scanner system was utilized to collect point cloud data; multiple video camera arrays were used to recognize and track the dynamic objects quickly, such as a crane boom. The dynamic target object's point clouds were updated separately by a smart scan method. At the same time, the point cloud data of previously scanned static work environments were merged to the dynamic scan data. The raw point cloud from extracted target areas wasconverted rapidly into a 3D surface model, using the convex hull algorithm, after a process of downsizing the raw data to increase the data processing speed. The performance of the proposed method was tested at a steel frame building construction site. Both the generated dynamic target's surface models and the point cloud of static surroundings were presented wirelessly to a remote crane operator. The field test results demonstrated that the proposed rapid dynamic target modeling method would improve the crane operation productivity and safety significantly by distinguishing a dynamic surface model being controlled by the operator from the point cloud of existing static environment in 3D views.

This paper investigates the relationships and interrelationships associated with the commonly accepted U.S. economic indicators and stock prices of major construction equipment manufacturers. The authors developed a three-step research methodology that comprises data collection, hypotheses development, and statistical analysis. Various U.S. economic indicators (i.e., real gross domestic product, inflation rate, Turner Construction cost Index, price of gold, and price of crude oil) were analyzed relative to the stock prices of U.S. construction equipment manufacturers (i.e., Caterpillar, Deere & Company, and Manitowoc). In general, relationships among the three construction equipment companies did notparallel each other consistently with respect to the various economic indicators. Perhaps one of the most telling findings was that no significant relationships were found between the stock prices of Caterpillar or Manitowoc and GDP or construction cost index. However, there were significant relationships between the stock prices of Deere & Company, GDP, and the construction cost index. Equally as telling, Caterpillar stock price did not correlate with the U.S. unemployment rate. Also, it became obvious that the stock price of Caterpillar was clearly different than that of Deere & Company and Manitowoc. In addition, through close inspection of the nearly perfect correlation between GDP and the construction cost index, it appears that the 2007 collapse of the U.S. construction industry, and consequently the U.S. economy, could have been predicted through a casual investigation of construction material and labor costs. This research opens horizons for abandoning the notion of studying the construction industry solely using residential construction (i.e., housing market), realizing that the construction sector involves other significant decision-making variables.

Building energy benchmarking is required for adopting an energy certification scheme, promoting energy efficiency, and reducing energy consumption. Several methods, such as data envelopment analysis (DEA), were proposed to perform building energy benchmarking. However, existing DEA building energy benchmarking models are subject to several limitations. Current DEA models are sensitive to data outliers such that even a single outlier can result in dramatic changes in efficiency scores of all buildings in a peer group of buildings. In addition, current DEA models cannot determine whether change of the energy-efficiency score of a building is a result of the change of energy efficiency in the building itself or the change of energy efficiency in the peer group of buildings. The objective of this research is to create a peer-wise building energy benchmarking model based on a novel DEA method that is capable of selecting significant factors, detecting outliers in the peer group of buildings, and decomposing changes in energy efficiency into two components (self-efficiency change and peer-efficiency change). To achieve this objective, the following research process was constructed. We devised an approach based on data cloud analysis to detect and remove outlier buildings that affect the DEA benchmarking results significantly. We formulated an innovative DEA benchmark model to calculate the peer-wise, energy-efficiency score of buildings considering the effect of building scales on energy efficiency. We created an energy-efficiency measure based on the Malmquist index to decompose changes in the building energy-efficiency score. We applied the proposed DEA model to benchmark energy efficiency of multifamily properties. The proposed benchmark model is beneficial to building owners and facility managers, because it identifies underperforming buildings and sets these as energy improvement priorities and self-comparable efficiency changes.

Bid/no bid decisions are crucial for the business continuity of a contractor. Thus, the decision should be made carefully within the context of the short- and long-term strategy of the organization. Despite the availability of several models, this decision commonly is made based on past experience and subjective judgments. This study aims to show how ANFIS can be used as a decision support tool by contractors during the bid/no bid decision process for international construction projects. Review of the literature revealed that 52 factors may affect a contractor's bid/no bid decision. These factors were categorized into six main groups, which are bidding documents-related factors, contractor-related factors, project-related factors, contract-related factors,host country-related factors, and opportunity-related factors. Having identified these factors, a questionnaire was designed to identify each factor's relative importance. The questionnaire was applied to a large-scale contractor, and actual data from 151 international projects were obtained. An ANFIS model was developed via MATLAB software program using the collected data. The proposed ANFIS model integrates the learning advantage of neural networks with fuzzy logic that represents the human reasoning mechanism. The statistical indicators revealed that the performance of the proposed model is satisfactory.

Volatility in price of critical materials used in transportation projects, such as asphalt cement, leads to considerable uncertainty about project cost. This uncertainty can lead to price speculation and inflated bid prices submitted by highway contractors to protect against possible price increases. One of the most common risk sharing strategies widely used by transportation agencies is price adjustment clauses (PAC) that divide potential upside and downside risk of material prices between contractors and owners. However, it is not clear whether offering PAC reduces risk premium of bids submitted by highway contractors. The research objective of this paper is to assess the effect of offering PAC for asphalt cement on submitted bids of one of the most common asphalt mixture line items. Data on 1520 highway projects consisting of the asphalt line item bidded out in the state of Georgia from 1998 to 2013 were collected to analyze the effects of PAC on bid prices. Multivariate regression analysis was conducted to evaluate the effect of several factors, such as project size, number of bidders, asphalt cement price, and availability of PAC on unit price bids material prices submitted by highway contractors. It was found that eligibility for PAC is not a statistically significant explanatory variable to explain the variation of submitted bid prices for the asphalt mixture items.

Significant changes in highway construction cost are problematic for cost estimation, bid preparation, and investment planning of highway construction projects in the United States. Analysis of the temporal relationships between highway construction cost, macroeconomic, and construction and energy market indicators helps to have a better understanding about highway construction cost changes within the U.S. macroeconomic, and construction and energy market context. This temporal analysis helps to identify leading indicators of highway construction costs. Leading indicators of highway construction costs are indicators, which past values contain information that is useful for forecasting the future values of highway construction costs. The research objective is to analyze the temporal relationship between highway construction costs and macroeconomic, and construction and energy market indicators using multivariate time-series tests. The data set under study includes National Highway Construction cost index (NHCCI) provided by Federal Highway Administration (FHWA) and indicators representing macroeconomic condition (producer price index, gross domestic product (GDP), GDP implicit price deflator, Dow Jones industrial average, money supply, prime loan rate, unemployment rate, federal funds rate, and consumer price index), construction market condition (number of housing starts, number of building permits, construction spending, average hourly earnings, average weekly hours, and employment rate in construction), and energy market condition (crude oil price). Research results show that crude oil price and average hourly earnings are the leading indicators of NHCCI. The research findings contribute to the body of knowledge by filling the gap in knowledge about the leading indicators of highway construction costs. The research findings contribute to the state of practice by helping cost estimators, budget planners, and construction market analysts explain highway construction cost variations and forecast the future trends to improve the accuracy of their budgets, estimates, and bids.

Transportation agencies and highway contractors are facing great challenges of variations in construction costs for transportation projects. Significant volatility in costs of construction materials, such as asphalt cement, is one of the most important drivers of uncertainty about transportation project costs. This type of uncertainty leads to serious difficulties for contractors in estimating project costs accurately. However, there is little knowledge about how asphalt cement price fluctuates over time. This gap in knowledge makes it difficult for contractors and transportation agencies to estimate project costs accurately. The research objective of this paper was to model fluctuations of asphalt cement price by using an appropriate stochastic process. It is concluded that the geometric brownian motion (GBM) is a good stochastic process to model random variations of asphalt cement price over time. A probabilistic approach based on the Monte Carlo simulation is applied on the GBM model to simulate future random paths for asphalt cement price index. It is expected that this work helps contractors and transportation agencies systematically analyze variations in the price of asphalt cement and develop more accurate estimations for their transportation projects.

Evaluation of coordination performance in a project network requires reliable measures and monitoring methods for effective management. Recent literature includes studies addressing the relationship between coordinative activity and the configuration of communication networks. In these works, the role of network centrality is investigated through the basic standard centrality measures of degree, betweenness, and closeness. Current social network analysis research emphasizes new formulations of centrality measures for robust structural analysis of project networks. This paper presents a novel approach for measuring network centrality using the concept of information centrality. It is based on the idea that all paths carry information. The significance of information centrality values for the actors in a directional signage project at Istanbul Sabiha Gokcen International Airport is investigated. A centrality index is defined for each firm based on the average of the four measures of centrality. Findings suggest the existence of a high correlation between coordination scores and the centrality indexes. A centrality index augmented by an information centrality measure has potential for assessing the coordination performance in construction management research, and it is promising for the structural analysis of project communication networks.

Economic slowdown and construction demand shrinkage reduces the profit backlog for construction contractors and negatively affects their profit margins. The resulting fierce competition for jobs forces construction companies to look for more sophisticated analytical tools to analyze and improve their bidding strategies. For each contractor, bidding strategy is a decision-making process that is driven by the firm's financial goals with the final objective of maximizing the firm's gross profit and surpassing the break-even point. This paper proposes a methodology to model and analyze different bidding strategies with hybrid agent based-system dynamics (AB-SD) simulation. To capture the winning ratio of different bidding strategies, two generic types of agents are defined. One is "regular" contractors, for whom the markup calculation process is only an internal decision, and the other is "learning" contractors, who, as adaptive agents, gradually enhance their prediction capabilities with learning mechanisms. The results of demonstrative simulations based on the proposed methodology show that the learning capability of a construction firm can improve its bid-hit ratio and financial performance effectively.

Surveys and other opinion-based data collection techniques are prevalent across various disciplines. However, a lengthy controversy over employing the traditional descriptive and inferential statistics for this type of data continues. In the field of construction engineering and management (CEM), conducting experimental research is a challenging task because of the dynamic and transient nature of the construction industry. As a result, CEM researchers studying topics that involve human behaviors in the construction process must employ research methods that use categorical level measurements to collect data based on expert judgment and opinion. Although the interval between ordinal values is not always equal, researchers often perform parametric descriptive and inferential statistics for their data. These analyses may lead to inappropriate results or indefensible conclusions. This paper reviews measurement scales to obtain expert opinion and associated appropriate statistical analyses. The paper analyzes 151 manuscripts published in the 12 issues of the Journal of Construction Engineering and Management (JCEM) from January to December 2012 to identify the typical statistical applications used in CEM research. The paper describes interconnection between scales of measurement and statistical applications and then provides recommendations for CEM researchers to select appropriate statistics tests corresponding to a given data set. In particular, the paper discusses when and how researchers can employ traditional descriptive and inferential statistics to analyze categorical and ordinal data to enhance validity and reliability of the given study.

Masonry construction is labor intensive. Its operations involve little to no mechanization and require a large number of crews made up of workers with diverse skills. Relationships among crews are tight and very dependent. Often tasks have to be completed concurrently, and crews have to share resources and workspace to complete their work. One of the problems masonry contractors face is the need to design crews, that is, determine the number of crews and the composition of each crew to be used effectively in the construction process to maximize workflow. This study proposes a mixed integer optimization model to assist contractors in the allocation of crews in masonry projects. To address realistic scenarios experienced by the contractors on masonry construction jobsites, the model incorporates the rules that contractors use for crew design and makeup, as well as time constraints. In addition, the model considers workers' needs, such as labor stability. The proposed model can be a valuable tool to assist masonry stakeholders in the process of allocating crews while meeting contractor's requirements and workers' needs.

Highway bridge infrastructure is a key aspect of the U.S. transportation system. Efficient maintenance is important for preserving the integrity and improving the condition of aging national bridge infrastructure. Highway bridge condition typically is assessed using visual inspections and accompanying nondestructive field tests. This paper presents a solution that leverages low-cost structural health monitoring (SHM) sensor data and the cumulative knowledge of bridge inspectors to monitor bridge conditions. The developed solution utilizes a central database to store infrastructure inventory, inspection, and SHM information. The paper presents the Bridge Inspection Toolkit (BIT)—an innovative software solution that provides condition assessment decision-making support to bridge inspection documentation. Condition assessment support is provided by integrating the BIT with functionality that allows inspectors access to intelligent interpretation of SHM data. The BIT also allows inspectors access to condition assessment data corresponding to equivalent components, recorded by other responders, thus allowing them to draw on the collective experience and judgment of peers. The implementation of the inspection solution developed in this research introduces a greater degree of objectivity into condition ratings assessed by bridge inspectors. Condition assessment data gathered using the presented methods helps in effectively rating bridge infrastructure capacity and efficiently allocating maintenance resources.

The objective of this paper was to understand how flow and topology affect resilience and robustness of codependent infrastructure and natural system networks. This paper represents these codependent infrastructure and natural systems as an integrated network system (INS) and develops metrics to measure resilience and robustness based on the understanding of network connections and flow characteristics. The paper presents a mathematical framework founded in system dynamics and viability theory that can be used to formulate metrics of robustness and resilience for an INS. As each of these factors are a function of the system "structure," a graph theoretic approach is used to represent and analyze the INS. The research builds on recent work indicating that the topology of a network determines its vulnerabilities. The immediate contribution of this paper is that it lays the mathematical foundations for measuring robustness and resilience of the INS and identifies methods to characterize its topology and flow through it. In the long run, this research is likely to support a platform that proactively will identify and prepare for unexpected disruptions to infrastructure services while reducing undesirable environmental hazards.

It is essential to build, maintain, and use our transportation systems in a manner that meets our current needs while addressing the social and economic needs of future generations. In today's world, transportation congestion causes serious negative effects to our societies. To this end, researchers have been utilizing various statistical methods to study the flow of traffic into the road networks better. However, these valuable studies cannot realize their true potential without solid indepth understanding of the connectivity between the various traffic intersections. This paper bridges the gap between the engineering and social science domains. To this end, the authors propose a dynamic social network analysis framework to study the centrality of the existing road networks. This approach utilizes the field of network analysis where visualization and modeling techniques allow capturing the relationships, interactions, and attributes of and between network constituents and mathematical measurements facilitate analyzing quantitative relationships within the network. Connectivity and the importance of each intersection within the network will be understood using this method. The authors conducted social network analysis (SNA) using two studies in the state of Louisiana. Results indicate intersection SNA modeling aligns with current congestion studies and transportation planning decisions.

Over the past two decades, governments around the world have been embracing public-private partnerships (PPPs) as an alternative approach in the provision of infrastructure. PPPs have their merits in remedying financial shortages in public sectors and improving infrastructure performance, but they must be selected carefully on the basis of value for money when compared to conventional procurement. Value for money analysis as an evaluation method has been widely used to ensure feasibility, accountability, and transparency in PPPs, although little is known with respect to its effectiveness and appropriate theoretical foundations. By mapping theoretical foundations and practical analysis methods, this paper reports the weakness and inadequacy of current value for money analysis. The study especially explores existing theoretical foundations and empirical evidence for PPP value for money and highlights paths for future research.

In recent years, recovery efforts following major disasters, such as the 2004 Indian Ocean tsunami, have highlighted the need to understand better what factors lead to the long-term recovery of communities. Previous studies have found wide variation in outcomes of reconstruction programs, and, although there have been increasing numbers of individual and small case studies of disaster recovery in recent years, there have been few broad comparative studies that explain long-term recovery outcomes. In this paper, we specifically focus onhow strategic interventions following the tsunami(including community participation, construction oversight, recovery agency presence and embeddedness in the community, and recovery funds) affected the success of housing recovery programs. To answer the question, "What actions can aid community recovery following a disaster?", we employed fuzzy-set qualitative comparative analysis (fsQCA) to determine what recovery strategies led to successful post-tsunami housing recovery in communities of Tamil Nadu, India. Data were collected through observations, interviews, and documentation on recovery outcomes and suspected conditions that affected recovery in the 15 villages. Based on the analysis, the recovery agency's embeddedness in communities, community participation during the recovery process, and agency oversight during reconstruction are necessary for successful housing reconstruction.

Tornadoes cause great hardship and economic loss to U.S. communities each year. The lack of quantitative information associated with real damage states of individual buildings results in inaccurate loss estimates and hampers effective decision making for mitigation, response, and recovery. A near real-time tornado loss estimation tool was developed and tested as part of this work. The GIS-based damage assessment tool employs post-event point cloud data collected by terrestrial scanners and pre-event aerial images. The tool automatically calculates the percentage of roof and wall damage at the individual building scale, which is used as input to empirical or statistical loss estimation methods. An accuracy analysis through a set of controlled experiments indicated that for typical point cloud density (greater than 25 points/m²), the tool results in less than 10% error in detection of pre- and post-event roof/wall surfaces. The GIS-based tool was validated with data sets collected after the 2013 Moore, OK, tornado and produced detailed percentage of damage for buildings, which was not provided by infield inceptions.

A project delivery system is defined as the comprehensive process by which a facility is designed and constructed. The traditional design-bid-build (DBB) system is sequential and often leads to inefficiencies; therefore, alternative project delivery methods (APDM) were developed to increase stakeholder integration and enhance project performance and have gained popularity in the design and construction industries. However, the use of APDM has not yet gained traction in the emerging trenchless construction industry, which focuses on the installation of underground infrastructure with minimal disruption to surface activities, such as traffic and business. The traditional lack of information sharing between engineers and contractors renders trenchless construction projects ideal candidates for APDM. Design engineers often are unfamiliar with trenchless construction means and methods, and constructors traditionally have not been involved during the design phase. APDM can be used to bridge this gap by enabling contractors to provide early insights, which can result in benefits over traditional methods. This paper discusses how APDM can improve the performance of trenchless construction projects through analyzing case studies of existing APDM trenchless projects. The findings demonstrate the potential performance effect of APDM on trenchless construction projects, namely cost savings ranging from 2 to 44%.

Water infrastructure provides services essential for the health and economic well-being of societies. These systems pose potential vulnerabilities, such as their inability to provide service when a disruptor alters the network. In shrinking cities, the per capita cost for maintaining infrastructure increases because of the reduced population maintaining an infrastructure footprint designed for a larger population. Decommissioning water infrastructure potentially may reduce costs and improve a community's public health by decreasing the presence of stagnant water and slowing pipeline deterioration rates that result from reduced flows. However, decommissioning presents challenges, such as maintaining adequate services and emergency demands. Additionally, criteria, such as future land use and network connectivity, must be considered to determine if decommissioning is appropriate. This paper examines the feasibility of decommissioning water infrastructure in shrinking cities. Decommissioning strategies were examined in the context of two midwestern cities in the United States using water infrastructure models developed in EPANET. The disruptors modeled included decommissioning and demand decline to evaluate the systems' ability to provide adequate service and emergency demands. This study demonstrates that decommissioning water infrastructure is a viable option for potentially reducing maintenance costs within these fiscally strained cities.

Departments of Transportation (DOTs) have had a problem in determining cost estimates to maintain road assets so that they can operate at a high level of service. These cost estimates are crucial during budget planning for road maintenance activities. DOT managers have to plan a budget for road maintenance activities before the beginning of each fiscal year. For this, they need information regarding the conditions of the road assets and the cost to improve the level of service of these assets. The main goal of this study was to build a tool that would assist DOT managers in cost estimation of road improvement programs. Using this tool, DOT personnel enter the conditions of the road assets, using a grading system similar to that used by American Society of Civil Engineers (ASCE) annual "report card," and enters the cost of the maintenance work needed to improve the grade. Once these data are entered into the system, the tool calculates the cost to improve the road assets. This tool links the database with an interactive map using the geographical information system (GIS); in this way, managers can view the condition of road assets.

This paper presents a vision for resilience-based planning in civil infrastructure using a system-of-systems framework. The distinguishing traits of system-of-system analysis are explained and evaluated with respect to the required dimensions of analysis in resilience-based planning. The application of the proposed framework is demonstrated in the context of financial planning for highway transportation infrastructure. The proposed framework facilitates an integrated analysis in which planning decisions are evaluated in terms of their effects on the resilience of infrastructure systems at four levels: asset, network, subnational, and national. Thus, it provides a tool for evaluation of planning decisions and prioritization of the allocation of constrained resources. Realization of the importance of resilience in infrastructure systems is emerging; therefore, this study is significant in exploring the dimensions of analysis and the required functionalities for resilience-based planning in infrastructure systems.

Hurricane Sandy, the worst storm of its type hitting the state of New Jersey and the city of New York in generations caused devastating damages to the region's infrastructure, properties, and businesses. A variety of geospatial information acquisition technologies have been used after the landing of Hurricane Sandy to support critical decision making related to search and rescue, damage assessment, environmental risk analysis, debris removal, and rebuilding processes. The challenge is to match the best sensing method to the desired post-disaster applications. This paper describes the first large-scale application of mobile terrestrial laser scanning technology in post-hurricane situations for supporting disaster recovery operations in the United States. Several innovative data analysis approaches for supporting damage assessment and flood resilience analysis are presented in the paper. Opportunities and challenges in using mobile terrestrial laser scanning to support post-disaster recovery operations are discussed to highlight future research directions.

Catastrophic disasters can cause fatal damage to civil infrastructures and facilities that provide basic services to the region. The malfunctioning restoration conditions (e.g., resource supply system and work environment) and lifeline systems (e.g., electric power) in the region have a significant influence on an individual facility restoration operation. Therefore, it is necessary to analyze the effect of regional-level recovery conditions for a successsful implementation of the facility restoration operation. Because it is hard to analyze interactions among diverse recovery efforts with a single stand-alone simulation approach, this research introduces a hybrid simulation framework for post-disaster facility restoration management. This is based on data exchange among different simulation modules of regional-level restoration conditions, lifeline systems, and facility operation. The use of hybrid simulation enables users to utilize each advantage of different simulation methods fully. The simulation results of the prototype imply that external recovery conditions can have significant effects on a facility restoration operation, which highlights the necessity of considering external conditions for project management after a disaster. A better understanding of the surrounding conditions (i.e., the effect of the resource supply system, work environment, and lifeline system) can thus support project managers in implementing appropriate restoration planning to avoid project delays.

Infrastructure rehabilitation has been a tremendous challenge for municipalities and public agencies. Although several methods exist to allocate a limited rehabilitation budget among a large number of competing assets, no efforts provide solid economic reasoning or justification behind fund-allocation decisions. Thus, this paper introduces a new perspective in infrastructure rehabilitation, inspired by the broad array of concepts available in the science of microeconomics. The paper discusses four microeconomic theories and examines their applicability in the infrastructure domain: equilibrium between demand and supply to balance economic decisions, utility maximization through equitable return on spending,indifference curves for sensitivity analysis, and loss-aversion behavior of decision makers. Initial results of an actual case study of 1300 pavement sections proved the applicability of basic microeconomic concepts in the infrastructure rehabilitation domain.

Nondestructive testing (NDT) methods have been developed and employed as a means of rapid and effective structural inspection. Despite the various kinds of NDT methods developed for bridge inspection, not much study has been performed on their usage and effectiveness at a practical level. This paper presents an evaluation of NDT methods to identify how they are implemented in state agencies in the United States. The findings and analysis presented are based on the results obtained from a survey questionnaire targeted at Departments of Transportation (DOTs) in all U.S. states and territories. The survey questionnaire was initiated to clarify multiple issues regarding NDT implementation, such as identifying the types of inspection that involve NDT methods, effective methods of inspecting concrete structures, and so on. A total of 40 state agencies participated in the survey processing, and the major findings obtained from the states are explained in detail in this paper.

Many owner organizations use manual, visual methods for evaluating the condition of infrastructure. However, manual, visual evaluation is labor intensive, time consuming, and potentially dangerous. Advances in remote sensing technology, such as high-resolution, multispectral digital aerial photography and high-resolution airborne LiDAR provide new methods for collecting condition information on infrastructure assets that can be used for infrastructure management. To evaluate the potential for using remote sensing technology for infrastructure management, we compared data extracted from aerial photos and LiDAR with reference data on pavement surface conditions that were collected manually. The statistics of the spectral response of the bands within the digital aerial photographs and the elevation within the airborne LiDAR were extracted and correlated to the reference data using stepwise linear regression models. The results show that the spectral response in digital aerial photographs of 0.1524-m (6-in.) resolution and 1-m resolution with an infrared band closely match the reference data. The results also show that the elevation response in airborne LiDAR of 1-m resolution closely match the reference data. These results open the way for the future use of digital aerial photographs and LiDAR to assess the infrastructure system conditions remotely.

Being critical to modern economy and society, infrastructure must be sustainable to maintain long-term use value and to satisfy the future need for urban development and economic growth. Although existing knowledge and practice of evaluating sustainable infrastructure is focused primarily on an individual project or facility, research is needed to integrate sustainability into infrastructure evaluation at the system level (e.g., a city or region). The system level of sustainability evaluation is especially important to support public policy decision making on infrastructure investment. This paper presents an integrated framework of sustainability assessment for urban infrastructure systems. The framework adopts a hierarchy structure of indicators to measure sustainable infrastructure system. It also integrates factor analysis, TOPSIS model, entropy weight model, and combined evaluation method into the analysis and decision-making process. A region of Yangtze River Delta (YRD) in China is discussed as a case study to demonstrate the merit of the integrated framework. The evaluation results indicate that the sustainability of infrastructure system is different among the cities of YRD and is closely related to the economic development level and geographical position. Some cities, such as Shanghai, Nanjing, and Hangzhou with high economic development levels, have advanced infrastructure systems, whereas the infrastructure sustainability in some cities away from regional economic centers and lack of competitive industries are relatively low. This study provides an alternative methodology to assess the sustainability of urban infrastructure systems.

Environmental planning and permitting often is seen as one of the top reasons for delays in transportation projects. In design-build projects, this process is treated as the critical path to advertising the project. On all projects, many critical phases, such as right-of-way acquisition, final design, and construction cannot begin until the environmental planning process is complete. The objective of this study is to identify and analyze challenges to the environmental planning and permitting process, as well as opportunities for managing those challenges. To achieve this objective, a synthesis of transportation and design-build research was done, along with interviews with agency leaders at seven state Departments of Transportation (DOTs). Once these challenges and opportunities were identified, several environmental planning documents and design-build requests for proposals were reviewed to document their usage. Additional followup interviews were conducted with environmental planning experts from six of the state DOTs that were interviewed. This study contributes to the body of knowledge by providing comprehensive information on environmental planning and permitting challenges that must be managed on design-build transportation projects and opportunities for managing these challenges. The results of this study can help transportation agencies achieve higher levels of efficiency in the environmental planning and permitting process.

Construction projects primarily use three conventional delivery methods: design-bid-build (DBB), design-build (DB), and construction manager/general contractor (CMGC). Integrated project delivery (IPD) is an emerging delivery method that emphasizes the relational aspect among multiple organizations. It defines success by the outcomes of the project, not the individual organization's outcomes. This is a culture change for the construction industry as IPD attempts to assimilate organizations as a team to focus on the project goals. This study examines the association between project integration and contracting relationships using relational contract theory behavioral norms. Relational contract theory states that long-term contracts are complex and that the interactions, communication, and understanding among contracting organizations are the most critical and intricate aspects to the success of a contract. Contractual behavior norms are the expected behaviors occurring among contracting organizations, which can "make or break" a project. To determine the connection between project integration and relational contracting, this study uses a content analysis to investigate standard construction contract language for the existence and frequency of contractual behavior norms. The results of this exploration illustrate that behavior norms exist in construction contracts, construction contracts generally are relational in nature, and IPD contracts are more relational than DBB, DB, and CMGC contracts.

In this paper, analytical hierarchy process (AHP) and analytical network process (ANP) are compared as methods for determining relative weights of factors in selecting the most suitable project delivery system (PDS) for capital projects. The AHP considers the elements of each cluster as only affecting the elements of one other cluster and being affected by elements of one other cluster, whereas the ANP considers additional dependencies among elements. In selecting a PDS, interdependencies among factors of different categories exist, therefore ANP is considered here for its expected suitability. ANP requires additional effort in constructing a network and additional judgments. A network was developed by adding dependencies between specific elements to a hierarchy. Both methods were applied to a case study. ANP generally favored the factors that influenced additional elements through network connections. In the example analyzed, the overall ranking of factors by ANP was not consistent with all the pairwise comparisons, which reveals a limitation of the ANP. This paper augments the research in evaluating the appropriateness of AHP versus that of ANP in selecting the most suitable project delivery system. It provides an example of how the priorities of factors by hierarchy and by network differ for an actual decision problem.

In the global infrastructure market, unsolicited public-private partnership (UPPP) proposals have been promoted, and a number of countries have established incentive programs to encourage such proposals. Although public-private partnerships (PPPs) have been growing in the United States, development of infrastructure through UPPP is still an area in need of further development. In this research, 18 major national and international PPP companies working in the United States were surveyed about their perceptions of unsolicited PPP proposals in terms of the management of such proposals, adequacy of regulations, incentive programs, procurement stages and negotiations, procurement time and fees, and competing proposals. The analysis shows that a significant percentage of the surveyed companies has pursued, shortlisted, or awarded UPPP. Surprisingly, little less than half of the surveyed companies would not encourage UPPP in the United States. The reasons were rooted in government mismanagement of UPPP, transparency problems, and the lack of competition. The companies reported a lack of adequate guidelines and complained about the short bidding times for preparing competing proposals. The majority of the companies were not in favor of the UPPP incentive programs. It was concluded that significant work is needed for improving UPPP regulations and procurement processes.

Risk management is one of the key success factors of public-private partnerships (PPP) projects. Demand risk, being one of the major risks affecting PPP concessions, needs particular attention and effective management to avoid project failure. Thus, the objective of this study was to identify, rate, and prioritize these factors. The literature provides a list of core factors influencing demand in PPP projects. The full range of factors has been categorized into three groups of user characteristics, facility characteristics, and area characteristics. A questionnaire survey, based on receiving feedbacks from PPP stakeholders, is then used to rate and measure the relative importance of each influencing factor. Since the factors affecting demand risk interact with each other in a complex manner, demand risk identification should involve prioritizing the influencing factors considering their complex interactions. Hence, an analytic network process (ANP)-based technique for prioritizing demand risk factors in the PPP infrastructure concession has been developed. This prioritization process will help identify the most critical factors under each cluster to allow them to be given more attention and be subject to further analysis. The analysis shows that historical experience of paying and willingness to pay are the most important factors under user characteristics cluster, whereas fees of using the facility is most important under facility characteristics cluster, and employment level is most important under area characteristics.

Design-Build (DB) is an alternative project delivery system that is distinguished by a DB team acting as the single point of responsibility for a project where the design and construction phases overlap. There are two main methods used to procure DB services: single-step procurement and two-step procurement. This paper focuses on quantifying the resource expenditures of two-step DB projects through investigating both pre-award and post-award metrics. The pre-award metrics include the costs related to the request for qualification (RFQ) and request for proposal (RFP) phases, whereas the post-award metrics focus specifically on overall project performance (e.g., project cost, delivery schedule, etc.) The authors developed a detailed survey to collect data from public building projects procured using two-step design-build procurement methods. This paper presents preliminary results, specifically the data stemming from six two-step DB projects completed after 2005 and with total project costs ranging from $20.5 million to $299 million. Results of the analysis show the total cost to industry to develop full proposals is about 1% of the total project cost. Additionally, the total proposal cost to DB teams was reduced significantly because of stipend incentives offered by the owners.

When the Federal Aviation Reauthorization Act of 1996 established the Federal Aviation Administration (FAA) Airport Privatization Pilot Program, it was the intent of Congress to explore new sources of capital and investment from the private sector and pass the benefits and improvements to the users. During the existence of the pilot program it received 10 applications; the first successful concession in 2000 of the Stewart International Airport in New York was ended prematurely in 2007. The second closing has come through the use of a public-private partnership (PPP) in Puerto Rico. This deal is very different to a privatization, because ownership of the asset remains in the public hands, and benefits to the users are linked to specific operating standards. Required improvement is to the asset inside the concession agreement. Puerto Rico's project involved the 40-year lease for the financing, operation, maintenance, and improvement of the Luis Muñoz Marín (LMM) International Airport, a transaction worth $2.6 billion. A case study of the LMM airport concession is presented, and features of it are compared with two other transactions in the pilot program.

The design-build (DB) delivery system has been gaining popularity in the architecture, engineering, and construction (AEC) industry, in part because of the performance benefits it can offer to project stakeholders. Studies have been conducted to quantify these performance benefits in terms of commonly used metrics that include unit cost, cost growth, delivery speed, schedule growth, and project quality. This paper summarizes and organizes the construction literature that quantifies the differences in performance between DB and the more traditional design-bid-build (DBB) delivery system in terms of project cost, schedule, and quality. The paper discusses these findings in a meta-analysis format to uncover patterns, trends, or possible differences in the results. Interestingly, the study reveals that despite several research efforts, few present statistically significant comparative results for all key performance metrics. The paper contributes to the body of knowledge by summarizing two decades of DB performance research and identifying the range of project performance values that can be achieved using DB, which allows for an improved understanding of DB performance.

Construction procurement is recognized as a complex business process. Traditional procurement methodologies have received wide criticism although it remains popular with owners/clients, regardless of the published disadvantages and criticisms. This study assesses the future of traditional procurement and also evaluates the current popularity of traditional procurement against alternative approaches to construction procurement. To achieve research objectives, a questionnaire survey was conducted within British Columbia, Canada, to gauge the perspective of construction industry stakeholders. Respondents were asked to gauge 50 statements on a five-point Likert scale. A Web-based survey service was employed to ensure anonymity while providing a single point of contact for gathering results. As a majority of the interviewees were positioned professionally at management level or higher, a certain level of accuracy in the data collected was assured. Research findings revealed that the traditional procurement methods do not meet the need of the Canadian construction industry. Traditional procurement alone cannot support the unique needs of each and every project in Canada, thus the Canadian construction industry. The paper identifies alternative methods that offer similar value while maintaining competitive practices that permit contractors to compete equitably for work. Recommendations for further research include conducting case studies into traditional, partnering, and management specimens of procurement methods. Additionally, national level surveys of industry stakeholders would further benefit this research, thus providing an indication of the procurement status quo, as well as a better understanding of what the future may hold. The study is valuable for all the professionals involved with the construction industry in general.

Departments of Transportation (DOTs) in the United States maintain their roads either by using in-house workers or by out-sourcing the works to private contractors. Out-sourcing uses two types of road maintenance contracting methods, prescriptive or method-based contracting (MBC) and performance-based contracting (PBC). This study conducted a survey with all 50 state DOTs and the District of Columbia to determine current road maintenance practices during the last 10 years. The state DOTs responded to questions about factors that influenced their selection of in-house and out-sourcing methods. Further, the survey included questions related to the satisfaction level of DOTs with various benefits of in-house, MBC, and PBC methods. The DOTs rated the satisfaction levels for those three methods with regard to cost effectiveness, schedule advantage, quality delivered, and risk transfer. The survey results indicated that, on average, the respondents were more satisfied with the in-house method in comparison to MBC and PBC methods. The respondents stated that the in-house method yielded high cost savings and schedule effectiveness and provided better quality and low risk to the DOTs. Lessons learned were identified pertaining to these contracting methods.

A contractor has an obligation to complete work within the time for completion, and the employer should not impede the contractor in performing his or her obligations under the contract. To this end, if the contractor is prevented from completion by an act of prevention by the employer and there is no corresponding right to extend time for completion as a result of that act, or the time for completion is not properly extended, time becomes "at large." Accordingly, the contractor is not under the obligation to complete the work within the original time, although work should be completed within a reasonable time. This paper used a two-step research methodology where the time "at large" principle is explained within the context of the common law legal system and is consequently applied to various standard forms of contract. The standard forms of contract examined in this paper include the Joint Contracts Tribunal (JCT) Design and Build Contract of 2011, the World Bank Conditions of Contract (WB Contract) included in the Standard Bidding Documents for Procurement of Works (SBDW), the Federation of Consulting Engineers (FIDIC) Conditions of Contract for Construction issued in 1999, and the American Institute of Architects (AIA) Conditions of Contract for Construction (A201) of 2007. The authors highlighted the provisions related to delays and extension of time and mapped them to the principle of time at large to conclude when time could become at large under the subject contracts. This study helps employers and contractors who are entering into projects using any of these standard forms of contract within a common law legal system to avoid conflicts, claims, and disputes associated with or resulting from the time at large principle. This should support effective and efficient contract administration of construction projects.

Delays in construction projects are more commonplace than most of us wish. The intensified market competition is driving all to accept tighter schedules, shrinking budgets, and slimmer contingency allowances. Such pressures give rise to claims, disputes, and litigation in courts. Understanding how to utilize the critical path method (CPM) delay analysis methodologies (DAMs) is inevitable to resolving these problematic project situations. This study was initiated to investigate the level of awareness, frequency of usage, information needs, complexity of application, and success rate of each CPM DAM used in the Egyptian construction market where authors work or had worked previously. Research was conducted through a triangulation approach for data collection that employed a quantitative questionnaire and a qualitative interview. Distribution of questionnaires followed a thorough analysis of the market structure, size of organizations in the Egyptian construction market, and the required sample size to reflect the differences between the targeted groups sufficiently. Collected data were analyzed subsequently with the aid of SPSS software. An unbiased hypothetical determination of the level of awareness, usage, and success rate of each DAM among different groups within the Egyptian construction market shall develop an understanding of the DAMs that should be adopted for a more successful settlement and resolution of disputes.

Contractors may apply unevenly distributed markups to implement unbalanced bidding strategies, including, for example, front-end loading. However, these strategies make a cash flow model more complex than the balanced situation and make it cumbersome to search for an optimum strategy when varying the rate and distribution of said markup. This paper explores markup functions in cash flow modeling that utilize singularity functions for various unbalanced bidding scenarios. By considering the constraint that the total price of the unbalanced and balanced bids should be equal, the model complies with the rule of awarding contracts to the low bidder. This new cash flow model is constructive in two ways. First, different types of unevenly distributed markup functions are defined, and input parameters of those distributions can bemodified conveniently to facilitate the optimization process. Second, the model incorporates shifts of activity starts and finishes, which allows integrating it with scheduling toward multiple objective optimization.

Traditional scheduling techniques do not consider explicitly the spatial constraints and coordination requirements of activities or are limited to one progress dimension. Yet in practice, each activity strongly depends on the available workspace within a physical location, which should be optimized by a careful spatial coordination. Therefore, it is necessary to broaden current scheduling toward the capability of expressing space, including directional movements therein. Singularity functions previously were applied to model work quantities and durations in linear schedules. This research develops novel singularity functions that incorporate two dimensions of space plus time into the activity model. Options for different directions can be created easily by transformations of the equations. An algorithm was developed that considers spatial constraints and movements at the activity level and generates valid solutions. A step-by- step solved example is illustrated by an axonometric projection of the resulting schedule, which provides significant time gains compared to traditional approaches.

Significant improvements are achievable in the accuracy of cost estimates if cost models adequately incorporate issues of flexibility and uncertainty. This study evaluates the relational efficiencies of the fuzzy composition operators—the max-min and max-product—in establishing the final cost of water infrastructure projects. Cost and project data were collected on 1600 water infrastructure projects completed in the United Kingdom between 2000 and 2011. Neural network was first used to develop relative weightings of relevant cost predictors. These were then standardized into fuzzy sets to establish a consistent effect of each variable on the overall target cost. The strength and degree of relationship of the normalized cost predictor weightings and the fuzzified project attributes were combined using the max-min and max-product composition operators to obtain project cost predictions. The predictions from the two composition operators were compared with the actual cost figures. Results show comparable performance in the efficiency of the composition operators. Based on statistical correlations, the max-product composition operator achieved on average a deviation of 1.71% whereas the max-min composition had an average deviation of 1.86%. Improvements in the relational efficiency of neuro-fuzzy hybrid cost models could assist in developing a robust framework for realistic cost targets on construction projects.

In practice, the number of contracts and the categories of contractors to be called for bidding on nonserial repetitive projects under one major program often are estimated on the basis of intuition and experience. It may involve emotional reactions to existing surrounding conditions. Accordingly, the factors that form the possible different scenarios should be properly analyzed and evaluated. This paper introduces an analytical model that allows for decisions on the number of contracts and projects per contractor for different contractor categories within major construction infrastructure programs. These optimum decisions are reached using an integrated time and cost objective. Genetic algorithm has been employed for performing optimization. A computer-based model has been developed and validated.

Risk-contingencies can strongly influence cost certainty if properly evaluated and managed. Accuracy of early cost estimates is a major concern for construction industry practitioners in New Zealand, especially quantity surveyors. Several researchers have long expressed their concern about cost estimating inaccuracies by recognizing that the accuracy achieved in cost estimating has been less than desirable. The essence of having an accurate design stage cost estimate as a reliable budgetary tool is defeated if risk estimates are not incorporated or not properly evaluated if incorporated. Hence, project objectives regarding cost, time, and quality targets are threatened as contingency is proportional to the risk present in a construction project. Therefore, the aim of this study is to signify the design stage cost estimating as a function of risk-contingency reserve. This study is a literature-based theoretical exploration and part of an ongoing doctoral research on the budgetary reliability of a design stage elemental cost plan. As a first step, a detailed review of related literature was made to establish the risk elements inherent in preparing the design stage cost estimate. Secondly, various factors affecting design stage cost estimating accuracy in construction practice were identified by demonstrating the theoretical context. The insights gained from the foregoing steps then helped in devising theoretical concepts for securing the design stage cost estimate as a reliable budgetary tool that guarantees cost certainty for building projects through risk-contingency analysis.

The Oregon Department of Transportation (ODOT) was interested in standardizing methodology for estimating costs of engineering and related services for purposes of negotiating contracts for those services. To accomplish this objective, current ODOT procedures, as well as those of other transportation agencies, were studied. Recommended best practices generally were consistent across ODOT and other transportation agencies, so the emphasis of the research became documenting those procedures and compiling databases to aid in the estimating process. Two databases of ODOT projects were compiled. Databases include estimated consultant hours by tasks and descriptive information, such as project type, number of nonstandard drawings, total project cost, number of subconsultants, and other factors. The databases were analyzed to identify relationships between project characteristics and consultant contract hours required. Results of these analyses are presented. A procedure for use of the databases was developed. This paper summarizes the results of the research.

Cash flow modeling is crucial to contractorsto sustain business. Contractors carry out multiple activities within a single project wherein the change of the start times of the activities have varying effect on the values of periodical negative cumulative balances and the other cash-flow parameters. Thus, changing the activities' start times leads consequently to changes in the value of the maximum negative cumulative balance and other cash-flow parameters as well. Schedule-driven cash flow models typically are generated to identify the effect of activities start times on projects' cash flow parameters. In this paper, Monte Carlo simulation technique has been employed to generate schedules and their associated cash flow parameters. The activities' start times are assumed to follow uniform discrete probability distributions with the minimum and maximum values representing the early and late start times respectively. Further, the proposed simulation model considered the stochastic nature of cash-in and cash-out transactions by incorporating the effect of 43 qualitative factors. Three scenarios are defined; each scenario incorporates a different number of qualitative factors. Advanced sensitivity analysis is performed to measure the effect of changing the start times on cash flow using the correlation coefficients. Finally, the proposed simulation model help practitioners identify the activities that highly affect the cash flow and provides a metric to measure the strength of their impact.

Supply chain management" emerged as a concept when benefits of collaboration within and beyond the capacities of individual organizations were witnessed. It was found that the collaborative efforts in reducing total supply chain costs were effective in a fragmented supply chain. The challenge in supply chain cost analysis is posed in interface costs where multiple organizations are involved in occurring costs. Many of the overhead costs in a supply chain are interface costs affected by the business process of upstream or downstream stakeholders as well as their own. Difficulty in developing a cost model pertaining to overhead costs leads to challenges in developing a supply chain cost model. This paper proposes a metric-based supply chain cost model using activity-based costing to help understand how each activity affects total supply chain costs, followed by a case study. A supply chain coordinator needs to understand not only the whole supply chain costs but also the costs of primary processes, many of which are interdependent. The paper contributes to the knowledge of construction supply chain management in that a supply chain cost model using activity-based costing is presented.

The accuracy of early cost estimates is critical to the success of construction projects. The selected tender price (clients' building cost) usually is seen in previous research as a holistic dependent variable when examining early stage estimates. Unlike other components of construction cost, the amount of contingencies is decided by clients/consultants with consideration of early project information. Cost drivers of contingencies estimates are associated with uncertainty and complexity and include project size, schedule, ground condition, construction site access, market condition, and so on. A path analysis of 133 United Kingdom school building contracts was conducted to identify effects of nine major cost drivers on the determination of contingencies by different clients/cost estimators. This research finds that gross floor area (GFA), schedule and requirement of air conditioning have statistically significant effects on the contingency determination. The mediating role of schedule between gross floor area and contingencies (GFA→Schedule→Contingencies) was confirmed with the Soble test. The total effects of the three variables on contingencies estimates were obtained with the consideration of this indirect effect. The squared multiple correlation (SMC) of contingencies (=0.624) indicates the identified three variables can explain 62.4% variance of contingencies, and it is comparatively satisfactory considering the heterogeneity among different estimators, unknown estimating techniques, and different projects.

A project is adjudged successful if it is completed on time, within the budgeted cost, and meets client's expectations. However, there is the global issue of construction cost and time overruns, which have contributed to poor project performance. Contractors always have been seen as the culprits in this regard, whereas the contractor is not solely involved in construction projects. There are other project team members who determine the path of the project success. This study assesses the causes of cost overruns, viewing this from the contractor's assessment of the contribution of the project team members. The study was conducted using questionnaire surveys in which 100 questionnaires were distributed to contractors using purposive sampling; data were analyzed by the use of descriptive statistics. The results show that lack of adequate precontract planning and project team coordination are the most significant factors among construction professionals leading to cost overruns. The study made recommendations, which are of benefit to the client, project team members, and contractors.

Heterogeneous photocatalysis for self-cleaning and air purifying construction materials, using titanium dioxide (TiO₂) nanoparticles, is a promising and fast growing technology. Much of the focus of recent research has been concentrated on understanding photodegradation benefits, such as the reduction of nitrogen oxides. Few researchers have investigated the potential adverse effects because of application of photodegradation. Potential trade-offs include the adverse environmental effects from photodegradation intermediates, photodegradation end products, or TiO₂ nanoparticles released to the environment, either into the atmosphere or the water. As a result, potentially harmful compounds—TiO₂ nanoparticles and nitrates—released to water from photocatalytic concrete pavements were measured. The amount of nitrates eluted to water was measured after 4.5 h of photocatalytic oxidation (PCO) of nitrogen oxide (NO_x) using environmental settings, which would provide the most NO_x reduced and nitrates created. After 4.5 h of photocatalytic activity, 8.984 μmols of nitrates were released to water accounting for 49% of the theoretical amount of nitrates created. In addition, the amount of the titanium element was measured using inductive coupled plasma atomic emission spectrometry (ICP-AES). Titanium nanoparticles were not detected in any of the water samples.

For many years in the Ghanaian construction industry, ordinary Portland cement (OPC) has been known to be the main binding agent widely used for construction. However, in recent times, the cement market in the country has seen the entrance of Portland Limestone cement (PLC). Data regarding ordinary Portland cement and clay pozzolana (CP) is available but with PLC-CP mixes, there remains absolutely no data. In this work PLC was incorporated with different percentages of CP ranging between 10% and 40%. The CP was characterized based on physical, chemical, and mineralogical properties. Technical parameters, such as normal consistency and setting times, were analyzed on the formulated paste while strength analysis was performed on the batch mixes of formulated mortars. The results indicated that both the consistency and setting times appreciated as compared with only PLC paste, whereas the compressive strength of PLC mortars incorporated with CP fell slightly lower than the controlled PLC mortar.

Biodeterioration of concrete surfaces on vertical elements of bridges represents a serious challenge to the highway infrastructure in the state of Louisiana, not only for its poor aesthetic appeal but also because of the accelerated deterioration that biofilm causes on concrete. This paper investigates the causes of biofilm proliferation on concrete, the consequences that these living organisms have on concrete, and the best methods used to control and eliminate biofilm growth on concrete. A literature review was conducted, and a survey was developed and distributed among different states' DOTs to determine current biofilm preventing and cleaning practices and their effectiveness. The survey results show that not all the states have biofilm growth, and that those that do are located in warm and humid geographical locations. Results also suggest that the main cause of biodeterioration of concrete surfaces is caused by micro-organisms' activity present at the surface. Furthermore, current practices used to prevent and clean biofilms growth are pressure washing, biocides, and addition of self-cleaning photocatalytic nano titanium dioxide (TiO₂) coatings to concrete surfaces. Results also suggest that the use of self-cleaning photocatalytic nano TiO₂ coatings appears to be the most effective method in preventing microbial growth on concrete surfaces.

Renewable energy from photovoltaic (PV) systems is poised to reach the major milestone of grid parity in the coming years because of substantial decreases in the cost of silicon based PV technologies. One of the remaining hurdles to overcome to achieve grid parity is the balance-of-system (BoS) cost, which includes all of the costs other than the PV modules and electrical inverters. This paper presents a novel approach to the problem of racking and mounting for utility scale PV power plants and urban canopy applications with a new racking system design and installation process model. The goal of this design is to provide the most cost-effective racking system for utility scale PV arrays. This system, called the Quad Pod, is predicated on the principles of preassembly to minimize labor cost and ultra-efficient, long-span truss design to minimize material cost. Additionally, both approaches yield significant improvements in installation time and worker safety and comfort.

The 21st century requires the incorporation of sustainable means and methods in all phases of construction to ensure that future generations will have the same benefits we currently enjoy. Leadership in Environment and Energy Design (LEED) is now moving the green building industry forward. The use of passive air cooling/ventilation systems is a technology that aligns itself with LEED requirements by promoting advanced energy performance through elimination of excess fuel/energy consumption to cool buildings. Few modern passive air cooling/ventilation systems exist in the United States but one successful installation has been constructed at the Zion National Park visitor's center (ZNPVC) in southern Utah. Our research has investigated the use of an ancient Iranian passive air cooling/ventilation system called "BAD GIR" (meaning "wind catcher" in Persian) as an answer to the need for passively cooling structures in southwestern United States Both Iran and Utah contain high desert plateaus with both having similar climates and topography. The constructability, methodology, and viability of BAD GIR technology for residential and small commercial applications in Utah and surrounding arid regions will be studied and proposed as an architectural structure for a visitor's center on the Timbisha Indian Tribal lands in Death Valley, CA.

Increasing trends toward urbanization can lead to increased exposure to transportation noise from automobiles and aircraft. Interestingly, current aircraft noise guidelines primarily are based on outdoor sound levels even though most people spend the majority of their time indoors. A research project is being conducted that provides insight into how typical residential envelopes affect indoor sound levels, with a focus on noise from commercial aircraft overflights. A pilot, single-room "test house" has been built using typical mixed-humid climate region construction techniques, and the outdoor-to-indoor transmission of sound is being directly measured. The test house results are being used to validate and improve computer models that can be used to simulate outdoor-to-indoor transmission of sound. These models will allow for flexibility in future work to simulate a wide range of construction types for other U.S. climate regions, as well as effects of acoustic and energy retrofits. The improved models developed through this project, therefore, will help improve understanding of expected acoustic performance for typical construction types around the United States including design alterations that can help insulate homes from aircraft noise.

Industrial construction includes a wide range of construction projects, such as petroleum refineries and chemical plants. These involve several trades, such as civil, mechanical, and electrical. Different trades carry out different tasks on these projects, and often depend on scaffolds to access their work areas. Quantification of scaffold requirements of large projects is difficult because of variability in work area heights and congestion and the multiple trades that need to be serviced by the scaffold system. Traditional estimating methods rely on percentages of direct trade hours or volume of work area and usually result in significant deviation from real scaffold costs. The study presented in this paper aims to develop better understanding and estimates of scaffold needs for industrial construction sites, based on analysis of data collected from a mega-project over the course of two and a half years by a major contractor. The study seeks to discover patterns and reliable correlations that may exist between required scaffold hours and other work attributes that can allow for development of a reliable estimation model. The paper presents the results of initial analysis and exploration of data mining experiments, in addition to the challenges faced and future research recommendations.

Value engineering (VE) frequently is applied to construction projects for better project scope recognition and for elimination of unnecessary cost without affecting the functional requirements of individual components of constructed facilities. A critical phase in the application of value engineering is the evaluation of generated alternatives based on the defined criteria for that purpose. Limited work has been carried out for the automation of this process yet without adequate visualization for the components being considered. This paper presents an automated model for design professionals, owners, and members of VE teams to evaluate and compare different design alternatives of project components using multiattributed criteria, as well as integrating that model with visualization capabilities to assist designers and stakeholders in making related decisions. The analytic hierarchy process (AHP) is used to develop a multiattributed decision support model for evaluating competing alternatives. The model is then integrated with BIM to provide visualization capabilities and assist in cost estimating of the project components being considered. A prototype model that integrates the project BIMwith RS Means cost data and AHP has been developed. The model has been applied to a case project and evaluates and ranks generated alternatives in its output report.

Evaluation and optimization of energy consumption in construction projects are key to reducing the environmental footprint of construction and project direct costs. Construction projects consume energy in different forms and for various purposes including equipment and tools operation, material embodied energy, and jobsite maintenance. Previous research studies on the environmental effects of construction focused on evaluating greenhouse gasses or total energy consumption assuming average fuel consumption rates. Therefore, the effect of resource utilization and other planning decisions on energy consumption is not fully understood. In addition, most of these studies focused only on material manufacturing or building maintenance with minor focus on evaluating energy consumption during the construction phase. This paper, therefore, presents the preliminary stage for developing a new framework to evaluate the effect of several planning decisions (e.g., resource selection and productivity, construction methods, overtime working policies) on fuel and energy consumption during the construction phase. The proposed framework is designed to identify the main variables affecting energy consumption and their practical ranges, schedule construction projects for different resource utilization scenarios and calculate the associated energy consumption, and evaluate the energy performance of these scenarios to identify the most efficient ones.

Construction projects are becoming plagued more than ever by conflicts, claims, and disputes. To this end, performance measurement has become a commonly used tool for evaluating processes, managing human resources, and formulating corrective strategies. One of the most important aspects of performance measurement is the ability to perform benchmarking. Using case studies of projects carried out by the U.S Army Corps of Engineers (USACE) in its Vicksburg District, this paper investigates how benchmarking potentially can be used to evaluate and measure performance of the associated contractors. The utilized methodology encompassed three interdependent steps where the authors collected project data for 40 contractors who performed work for USACE using internal file reviews, defined the associated performance measures, and analyzed the results to identify areas in which contractors needed to improve to increase efficiency. The authors identified five performance measures including quality control, timely performance, effectiveness of management, compliance with labor standards, and compliance with safety standards. These measures were applied on a five-point rating system and categorized using three characteristic groups including use of subcontractors, contract modifications, and final contract price. This research provides an opportunity to promote changes within the Vicksburg District based on knowing strengths and weaknesses.

A well-known method of improving productivity in the construction industry is modularization, in which a portion of potential site-based work is carried out in fabrication/assembly shops. The construction industry as a whole, however, makes little use of modularization. Previous studies have identified how modularization is used now, as well as the obstacles to applying it to projects. To help achieve wider and more effective use of modularization, the Construction Industry Institute's (CII) Research Team 283 in 2013 identified 21 critical success factors (CSFs). Information that is still missing, however, is the current level of CSF accomplishment on actual modular projects. This work collects such information and analyzes the general status, degree, and timing of CSFs accomplishment. This work finds that what appear to be challenging but valuable opportunities to increase modularization are higher degrees of accomplishment in early completion recognition, investment in studies, and owner-delay avoidance. Moreover, this paper recommends earlier accomplishment on the following CSFs: module envelope limitations, alignment on drivers, module fabricator capability, and vendor involvement. This understanding of how well the industry accomplishes modularization CSFs should provide insight into how to achieve higher levels of modularization.

Takt time is a design parameter used in production settings, whether it is manufacturing or construction, tuning the rate of work output to the customer's rate of demand. Recent industry experiments have shown that takt-time planning and execution of construction work can yield significant benefits in regard to time savings, money savings, improved quality, and other benefits. In this paper we describe our action-research implementation of takt-time planning by means of a case study on an approximately $2.5 million retrofit of a floor in an operating healthcare facility. We illustrate the takt-time planning process using excerpts from one-on-one meetings with subcontractors on the integrated project delivery team. The commercial terms combined with these subcontractors' willingness to express flexibility in their means and methods, as well as sequencing of work, made it possible to trade off pains and gains among team members for the sake of optimizing the project's takt-time plan. We situate the takt-time planning process in the context of the levels of the last planner system, comprising master scheduling, reverse phase scheduling, make-ready planning, and commitment planning. Execution of the takt-time plan is underway. We conclude that takt-time planning helps to pose many questions that must be answered in production system design.

The U.S. Army Corps of Engineers (USACE) created a checklist to ensure all proposed government projects meet a minimum set of guidelines. They coined the checklist BCOE: Biddability, constructability, operability, and environmental. This project management review process incorporates a plethora of constantly changing input from USACE employees around the globe. The most current construction practices, the newest building configurations, the most recent ingenious method to perform are all captured by the USACE database to support the BCOE process. Using case studies of projects carried out at the Engineer Research and Development Center (ERDC), this paper investigates how proper utilization of the USACE's BCOE project management process can reduce conflicts, oversights, cost overruns, and other deleterious actions that can inversely affect the successful outcome of a project. The utilized methodology utilized encompassed three interdependent steps where the authors collected project data for five projects that were carried out in ERDC, analyzed the efficiency and effectiveness of the BCOE process, and consequently collected additional project data for another 15 ERDC projects for further indepth analysis. When properly executed, the BCOE review process was proven beneficial to ensuring the successful completion of a project through improved communication.

Panelized/modular construction is increasingly adopted within the industry as a primary construction method, with in-plant fabrication and onsite assembly as two of the main processes. Each of these two processes involves a different emphasis regarding productivity improvement: for in-plant fabrication, manufacturing process management is the main focus, whereas for onsite assembly, scheduling and management of assembly operations are of particular interest. This paper proposes a generic approach by which to generate the onsite schedule automatically based on a Building Information Model (BIM), considering the structural supporting and topological relationships among building elements, as well as knowledge of steel panel construction. The BIMis developed in an Autodesk Revit environment, based on which precedence relationships of elements are derived automatically and is utilized to perform the onsite schedule through the Autodesk Revit application programming interface (API). The generated schedule results are exported into Microsoft Project for further analysis, such as resource leveling. A case example is provided to demonstrate and validate the methodology. This paper explores the implementation of BIM, with the scheduling of panelized construction as the focus. This research lays the foundation for further implementation of BIM using Autodesk Revit.

The complexities inherent in scheduling the execution of process plant turnaround projects present distinctive challenges to project managers in identifying the shortest project duration while determining the optimum crew size. In collaboration with a major plant turnaround contractor in Alberta, we monitored the execution of an oil refinery turnaround project. We looked into management processes in regard to turnaround project schedules development and skilled-labor resource allocation. This research conceptualizes a labor resource provision optimization methodology in the complex and dynamic context of turnaround scheduling to objectively quantify and reduce the crew size. The optimum quantities of specialty trades to be employed in the field can be determined objectively so as to staff a crew with sufficient skilled-labor resources while also minimizing the duration in executing a turnaround work package.

Despite the large demand for natural gas (NG) that is needed to produce clean energy and resource sufficiency, entry into the NG-related construction market is limited by the inherent risks. Especially, the early stage of projects, such as planning or feasibility study, is more crucial on the uncertainty perspective than other following stages, such as engineering or construction. Thus, it is necessary to implement a project screening model in the early stage of a project. This study proposes a project screening model for gas plants that incorporates two analysis aspects: market environment analysis and gas field analysis. Market environment analysis evaluates a country's political stability and the stability of the project from the market perspective. Gas field analysis evaluates technical property, participant stability, and the stability of the target project from the project perspective. Finally, a case analysis is performed using the gas field project in South Africa. The case analysis uses documents of actual gas field development and interviews with site managers. Thus, the gas field site manager validated the proposed model and confirmed its usability. When user integrate their own expertise and experiences with this model, the model will be able to support reasonable decisions.

In today's business environment, the coordination of just-in-time (JIT) production and transportation is one of the most challenging aspects to ensure timely delivery of materials to distributed customers. Several risk factors make JIT supply chains more vulnerable and methods for analyzing and understanding supply chain risks are still needed in construction. This paper describes the implementation of failure mode, effects, and criticality analysis (FMECA) tool and discrete event simulation to assess supply chain risks, identify vulnerabilities, and measure the effect of disruptions of a ready-mix concrete supply chain. Interviews with concrete batch plant managers and current demand, production, and delivery performance data served as input for analysis. We provided a systematic method that can be used by concrete suppliers to improve planning and delivery of ready-mix concrete. Different mitigation strategies were suggested based on our findings.

The Oklahoma Department of Transportation (ODOT) currently spends at least $600,000 per year to collect pavement condition data for their highways. Every two years, the entire pavement network is updated with new data. ODOT now has more than 16 years of pavement condition assessment data that provides a rich time-series data set. This paper presents results of a current research project sponsored by the Oklahoma Transportation Center (OkTC) that focuses on using these data to assess the current pavement deterioration curves that are central to ODOT's pavement management system. In this study, the research team assessed the pavement condition assessment data in a structured manner to evaluate the performance of the currently used age-based pavement management models. Furthermore, the research team developed new models or calibrated the existing models for the purpose of providing more accurate and reliable planning for pavement maintenance and rehabilitation activities. The performance of the new or calibrated models was compared with the performance of the current models to determine which ones are most effective. The data driven models developed in this study will provide confidence to the ODOT pavement management team in developing short-term and long-term pavement management strategies and realistic pavement budget estimates and resource allocation.

Benchmarks of crew cost and productivity performance for commonly used methods in the construction industry are readily accessible through industry-wide commercial estimating databases (such as RS Means). The objective of this study is to identify limitations of commercial benchmarking services and further propose a framework for benchmarking crew cost and productivity performance over several years and in different cities. The proposed framework is applied to a typical open-cut method, illustrated with data retrieved from RS Means online databases. In particular, the data structure of RS Means is explained, and the drawback of the underlying productivity benchmarking methodology is revealed. We conclude crew cost data ($/labor-hour) from RS Means can be used to trend the changes of time and location-specific crew and material costs in a reliable way, while productivity (daily or hourly production: unit/h) accounts for the industry average only, ignoring theunique variations and attributes of crews, jobs, contractors, or projects.

Site personnel or construction workers will spend most of the construction time within construction sites. If construction workers are able to move easily and quickly within the site, it helps to save time and increases productivity as well as safety. Optimizing the cost, safety, and productivity of a project often relies on the optimal planning of the construction site layout. However, site layout planning—unique for each construction project—depends on many variables, such as work areas and facility locations. To optimize workplace usage and minimize construction conflicts, participants on a project must consider the constraints that each construction project entails. Currently, the concept of an optimized construction site layout has no clear definition, so practitioners do not have specified guidelines or policies that govern the construction site layout. Therefore, the purpose of this paper is to assess current practices for site layout planning and highlight the need for a rule-based approach to evaluating construction site layouts. The results presented in this paper can provide construction firms with a better understanding of why a rule-based system is important in site layout planning.

According to the 2013 Report Card for America's Infrastructure, prepared by American Society of Civil Engineers (ASCE), the drinking water and wastewater infrastructure received grade of D. The American Water Works Association (AWWA) estimated that it would cost about $1 trillion to replace every drinking water pipe in United States. Further, it would cost about $298 billion over the next 20 years to fix the nation's wastewater and stormwater systems. Owners, engineers, and contractors are using alternative project delivery (APD) methods, for example, construction management-at-risk (CMAR), design-build (DB), construction manager/general contractor to build water and wastewater projects to save time and costs, as well as to improve the quality of the projects. In this study, a survey was designed to assess the satisfaction levels of policy makers, project staffs, and utility managers regarding various benefits related to APD methods. The surveys were emailed to 455 owners using APD methods in their water and wastewater projects. The study results showed that, on average, owners and project staffs were satisfied with most of the issues related to these delivery methods. Particularly, study results elaborate on the differences in satisfaction levels between respondents involved in CMAR and DB projects.

The past decade has witnessed a surge in the application of formal probabilistic risk assessment on cost, schedule, or both in major capital projects. Depending on the level of detailed information required the sophistication of risk assessment approach ranges from simply considering some important variables to fully integrated cost/schedule risk models. The most common modeling approach is to model cost components as random variables and calculate total cost distribution. For projects or portfolios spanning several years, the effect of cost escalation on budget is profound. Because of this, the variability of the escalation factor should be considered in the conduct of the risk assessment. This paper provides a mathematical framework for modeling of cost uncertainty in a portfolio of large infrastructure projects with a multiyear duration. This framework considers the randomness of cost and escalation factor at the project level. Relevant equations are presented that consider various degrees of probabilistic modeling from basic to complex. The paper can be used for understanding major drivers of uncertainty in portfolio budget and to evaluate the effect of escalation variability on project costs. The concepts and the suggested approach are explained using a numerical example.

Hazard recognition and communication is critical for preventing injuries on construction projects. Across the industry, employers encourage workers to conduct regular prejob safety meetings and hazard analyses to identify, communicate, and mitigate site-based hazards. Although such programs promote safety, potential benefits often are lost because of inefficient communication channels, differences in language proficiency, and poor safety culture. In this study, we use social network analysis (SNA) to explore the relationship between patterns of worker interaction and situational hazard awareness on active projects in the United States. Specifically, we gathered hazard recognition and communication level data from 18 active construction crews involved in diverse projects and trades through field observations, measured and modeled safety interaction among crew members using social network analysis, and related network characteristics with situational awareness capability of the crews. The results of the study provide strong evidence suggesting that well-connected crews with higher network density outperform poorly connected crews in identifying and communicating hazards. As a result, it is necessary that safety practitioners not only implement traditional program elements but also promote efficient and frequent interaction among workers of all trades.

Highway construction and maintenance crews are often forced to work adjacent to high volumes of traffic and in many cases fast-flowing traffic. This exposure is hazardous and evident from the high number of work zone crashes that occur in the United States. Current work zone traffic control measures used to improve motorist and worker safety include positive protection measures, such as concrete and steel barriers, as well traditional measures, such as variable message signs, flaggers, cones, flares, and law enforcement presence at worksites. For short-term maintenance operations of duration less than one work shift, the implementation of positive protection measures is not feasible, and work crews need to work with minimum protection from errant vehicles that might cross into the work zone. A recent advancement in work zone safety includes the use of a mobile barrier system (MBS) that can be transported to a work zone and provides positive protection to maintenance crews, with minimum effort and in a very short time. The Oregon Department of Transportation (ODOT) recently purchased such a barrier and, with the limited independent literature available as to the effectiveness of its use in work zones, contracted with researchers at Oregon State University to evaluate the MBS. The research team investigated the barrier during five case studies that were representative of ODOT maintenance activities for various performance metrics, such as time of setup, limitations/enhancements to work operations, worker safety and safety perception, worker productivity, and motorist safety perception. The same performance metrics also were investigated in similar maintenance operations without the MBS present. The results show that the MBS provides enhanced protection to the workers by reducing and eliminating hazards and providing a positive barrier between the work area and passing traffic. The barrier facilitates work operations by enhancing worksites with additional lighting, noise protection, power capabilities, and storage compartments. Additional training is needed for the work crews so that they can fully seize the true potential of the barrier for efficiency.

Evidence suggests that sleep deprivation negatively affects behavior, wellbeing, and work performance. Although several researchers debated the relationships between sleep deprivation and work performance, research that clearly determines the relationship between construction workers' sleep deprivation and safety performance has yet to be performed. To contribute to the analysis of this relationship, the researchers designed and administered a survey at three construction sites in Seattle, WA. The survey collected information about workers' schedule, sleeping habits, and issues. The study concluded that most of the workers slept between five and six hours before a working day and, therefore, could become the candidates to experience sleep deprivation related issues. Further, respondents were asked to rank the effect of sleep deprivation on the occurrence of 10 types of near misses. Three types of near misses relating to the operation of forklifts, scissor lifts, trucks, or carts; the lack or improper use of personal protective equipment; and the use of ladders were recognized as most likely to occur because of sleep deprivation. Thus, this study warrants that sleep deprivation might cause safety concerns for particular construction activities and that trade-specific investigation is necessary to understand clearly the relationship between sleep deprivation and safety.

Highway preservation projects commonly are conducted at night and often require construction workers to work in close proximity to ongoing traffic. This situation creates considerable safety risk for both the workers and passing motorists. It is widely accepted that work zone safety is highly related to vehicle speed, and a lower speed will make the work zone safer. Additionally, vehicle speed and speed variability in work zones is inextricably connected to the work zone design and the selected traffic control devices. Therefore, the type and layout of traffic control devices used in a work zone are important criteria when addressing work zone safety. To provide guidance on how to enhance work zone safetyeffectively and efficiently, a research study was conducted to investigate selected traffic control devices within highway preservation project work zones. The researchers implemented multiple traffic control devices on two case study projects and evaluated their effect on vehicle speed, construction productivity, cost, and motorist and worker safety. Interviews were conducted onsite to collect worker's opinions toward traffic control devices implemented each night. Speed data were gathered to evaluate the effectiveness of traffic control devices. A police officer parked onsite was found toreduce traffic speeds effectively and also was highly recommended by interviewees. The research findings also suggest using a combination of temporary reduced speed limit signs, radar speed monitoring display, and PCMS signs on both trailers and rollers.

This research documents and assesses the development of a construction safety training module featuring BIM-enabled 3D visualization narrated in both English and Spanish to test if such information can enhance safety training for construction management students and construction workers. A pilot (English version) of the module was administered to construction management students and generally their responses were positive. Spanish and English versions of the modules were then administered to professional mason laborers onsite in Denver, CO. This paper highlights the technical challenges and the lessons learned through the development of training module, particularly for use and research on actual construction sites. Findings support and highlight future opportunities to develop more advanced, custom (project specific) bilingual safety training modules.

Changing from day to day, the construction jobsite is in a constant state of flux. This constant change presents challenges for safety managers who must be able to foresee, as much as possible, hazardous conditions before they cause injuries or fatalities on the jobsite. Advances in information and sensing technology show promise in protecting workers from harm. However, they rely on data collection methods, which may not be fast enough to allow managers to act on the information they receive. This paper evaluates the potential applications that unmanned aerial systems (UAS) have for enhancing safety on construction jobsites by providing real-time visual access to jobsite environments. The type of UAS considered in this study is a quadcopter-type system that can be piloted remotely using a smart phone, tablet device, or computer. The evaluation of the system consisted of a heuristic evaluation, as well as a user participation analysis, to determine the features of an ideal UAS for safety-related tasks on construction sites. The results of the heuristic evaluation revealed some of the user interface challenges of the UAS interface considering safety related tasks. The user participation evaluation involved a simulated task in the controlled environment of the lab of determining worker compliance with the use of required personal protective equipment. This experimental approach revealed that using the UAS with a large-size interface on a tablet device would provide an accurate view of a jobsite that would be useful for safety-related tasks. Recommendations for the required features of an ideal UAS for construction safety applications include autonomous navigation, vocal interaction, high-resolution cameras, and collaborative user-interface environment, among others. The ultimate goal of this effort is to have jobsites free of the hazards that affect the most precious resource of the construction industry, its workers.

In 2012, the government of Colombia enacted Law 1508, providing new regulations for public-private partnerships (PPPs), and initiated a new generation of road concessions. Under this framework, control instruments are based on operational performance indicators, and revenues for the private party become available only when the infrastructure becomes fully functional and complies with service metrics. Risks associated with operation phases are now significant in contrast with conventional risk analyses that prioritize the construction phase. Although the construction period is shorter than the operation period of PPP projects, very little analysis is available for operational risks. This study proposes a qualitative research and case study methodology, with the comparison of road concession cases in Spain and Chile with Colombia, and the analysis of contractual documents and performance reports as a source of operational performance requirements, risk allocation, and activation events. Nonconventional factors are identified, such as third-party influence and user behavior, opposite motivations in demand management between toll income and maintenance requirements, negative incentives in availability payments, split incentives in the public-private relationship, and ambiguous definition in force majeure events and insurance coverage. Recommendations are proposed for further risk assessment and allocation.

Concrete formwork is a common type of temporary structure used on construction projects. Because of difficulties in considering actual construction site implications during formwork design, assessments of formwork integrity often are made in the field by site personnel based on subjective visual inspection. Further, the construction and placement of concrete formwork continues to be a high-risk activity, especially in regard to fall injuries and fatalities. This paper presents a research study in which work and material flow for the typical formwork construction process are mapped and the risks associated with each stage of the process are characterized to investigate the effects of construction site conditions and operations on concrete formwork. Development of the process and identification of the risks were based on interviews of construction site personnel involved in formwork construction and on jobsite observations of formwork construction activities. Throughout its life cycle, formwork is exposed to repeated loadings from concrete pressure, worker activities, and environmental conditions. The mapped work flow provides new information that can be used for the design and construction of formwork to improve construction worker safety and production, and study the reliability of formwork with respect to repeated operational and environmental loading.

A great amount of research has focused on improving project risk management processes. However, because of the uncertainty and variableness within building projects, past research has not been able to identify the frequency and timing of risk effects clearly during projects. Further project risk mapping is necessary to understand the characteristics of when risks occur. Understanding risk encounters on different project types can improve predictability of when risks occur during project schedules. This research captures risk management data from 229 design-bid-build building projects over a seven-year period. The projects encountered 1229 risks during the construction phase that had the potential to delay the schedule or increase the cost of the project. An analysis of the risks encountered was able to identify the quantity of risks identified accordingly to the originally planned schedule. The analysis provides a histogram that improves the ability to identify the timing and frequency of project risks during building projects. A discussion on the observations found in the research is presented. The objective of this paper is to determine if the project type has influence on the frequency and timing of the risks.

An important challenge for construction practitioners and researchers is to develop production systems that are highly productive and safe. Toward this aim, this study investigated the work practices of field supervisors who consistently achieve very high levels of productivity and safety. In the context of this research, such supervisors are called high-reliability (HR) supervisors. Indepth field studies documented the work practices of HR supervisors in three trades: residential framing, masonry, and concrete. The HR foremen used several strategies that prevented errors and variability, while at the same time increased the speed of production. An unexpected finding was that there were significant differences with regard to the control of hazards and exposures. The HR supervisors were able to prevent accidents even under conditions of significant exposures to hazards. The findings provide empirical evidence that the production practices that prevent errors and variability not only improve production but also prevent accidents.

A novel decision support approach based on fuzzy Bayesian networks (FBN) is developed for safety risk analysis in this paper with detailed step-by-step procedures, including risk mechanism analysis, FBN model establishment, fuzzification and defuzzification, and fuzzy Bayesian inference. A conceptual causal framework is proposed to investigate the causal relationships between tunnel-induced pipeline damage and its influential variables on a basis of failure mechanism analysis. The probability inference model is then built by combining the conceptual causal framework with FBN to implement fuzzy Bayesian inference. The approach proposed in this paper is capable of calculating the probability distribution of potential safety risks and identifying the most likely potential causes of accidents under both prior knowledge and given evidence circumstances. A case concerning the safety analysis of the underground buried pipelines adjacent to the construction of Wuhan Yangtze River Tunnel is presented. The results demonstrate the feasibility of the proposed FBN approach and its application potential. The proposed approach can be used as a decision tool to provide support for safety assurance and management in tunnel construction, and thus increase the likelihood of a successful project in a complex project environment.

Safety climate is one of the indicators of safety performance of a construction project. It is a "snapshot" of the safety culture of any organization, and it is dynamic in nature. It reflects the employees' perceptions and attitudes toward the existing safety condition at the construction sites. The important constructs for the safety climate are determined through literature review. The constructs are assumed to influence the behavior of workers at the projects. The aim of this study is to develop a model to predict the safety climate on a construction project using an artificial neural network (ANN). The constructs are used as inputs, and safety climate of a project is used as output for the ANN algorithm. For the study, 200 responses were collected through a questionnaire survey across the country. A three-layer feed forward back propagation neural network (10-18-1) has been found suitable for the analysis. It has been trained, validated, and tested during the model development. The developed model is found to be predicting the safe climate of a construction project reasonably well. Commitment, supervisory environment, personnel appreciation, and competence could be proposed as effective and positive constructs of safety climate based on the results of the study. The model should prove to be helpful to clients and contractors to develop positive safety climates and thereby manage safety of workers effectively at construction projects.

To meet the large demands for infrastructure and public facilities in the rapid urbanization process, the Chinese government has issued a series of regulations for promoting private investments and participations. Among different applications of private investment, build-transfer (BT) method was widely explored for not-for-profit infrastructure and public facilities. First, private investors finance and build infrastructure and public facilities, indirectly promoting urban area and housing market development. Later, the government acquires land usage fees (LUF) from real estate developers and pays the private investor back using LUF. This BT plus LUF delivery method is an innovative way to solve the dilemma between "development" and "fund shortage" in China. However, the risks, such as long construction period, high investment, and obstacles in land acquisition, make it difficult to implement. This paper attempts to illustrate the mechanism and risk management of this delivery method. An ecological small town located in central China was used as a case study. Based on literature review and characteristics analysis of the case, a list of initial risk factors was proposed. A questionnaire survey was then conducted, and based on that, 28 risk factors were allocated between the government and the private investor, and ranked according to their significance scores. Further, control measurements for the top four government-responsible risk factors were discussed. The results create a systematic risk management framework including risk identification, risk evaluation, and risk response, which can provide a reference for risk management for foreign or domestic investors in China.

The optimum financial resourcing of health and safety (H&S) is marginalized by competitive tendering, which does not ensure an equitable basis for estimating and bidding because generally, there are no detailed items included for H&S in contract documents such as Bills of Quantities. Anecdotal evidence and previous research indicates that a possible solution is the inclusion of an H&S section in the preliminaries section of such Bills of Quantities. The paper reports on a followup study conducted among general contractors. Findings include the two widely used forms of standard conditions of contract make limited reference to or mention H&S; a preliminaries item predominates in terms of the manner that contract documents have facilitated/made financial provision for H&S; competitive tendering without reference to H&S marginalizes H&S; a provisional sum should be provided for H&S in the preliminaries; and contractors generally do not determine the percentage H&S constitutes of tender and project cost. Conclusions include, inter alia, that H&S is marginalized by procurement practices, standard conditions of contract, and the lack of a structured approach to the facilitating of financial provision for H&S. Recommendations include, inter alia, that a detailed H&S section should be included in the preliminaries section of Bills of Quantities.

Among the Washington State Department of Transportation's (WSDOT) capital assets, Transportation Equipment Fund (TEF) shops provide a crucial service by ensuring proper care and maintenance of most of the state vehicles and equipment. Therefore, any reduction of TEF shop facilities capabilities could jeopardize not only WSDOT vehicles and equipment maintenance but also WSDOT's ability to fulfill its core mission. Given the importance of TEF shops, this exploratory case study analyzes the building system failures that have occurred or are likely to occur in these facilities, and utilizes discrete-event simulation to investigate how WSDOT operations can be affected by these events. In particular, by creating a model capable of simulating the service operations performed in the TEF shops, this study quantifies the consequences of failures on the shop activities and road users. The aim of this paper is to describe the development and validation of the discrete-event simulation model and its associated data gathering efforts. Further building systems failure analysis and impact assessment are within the scope of another publication.

Facility information is created and continually developed over the life cycle of a project influencing the current and future conditions of some aspect of the facility. Typically, the information handed over to the owners is in the form of paper-based or digital documents that include the requirements as specified in the contract. Databases such as a Building Information Model (BIM), have enabled the easy accumulation and preservation of data from various phases and sources in the projects life cycle, which are delivered to the owner, sometimes as a single information model. In an ideal situation, it is expected that the availability of the digital data will enable the facility management (FM) team to retrieve any information they require at any moment, increasing their daily productivity. It is now possible to access real-time information from the model and the facilities database on hand-held devices. Although the aspect of reducing time to increase efficiency has been addressed in previous research, knowledge about the semantics and structure of the information required during the execution of a work order also is essential and needs to be addressed. To understand this information requirement, the authors began the process by studying the information networks of existing healthcare facilities. The literature review and subsequent discussions with healthcare facility owners, operators, and managers established the need and motivation for the development of an information management framework. This paper discusses the preliminary review of literature, development of a research method based on grounded theory (GT), and the design of a data collection tool.

Inadequate information interoperability in facility management (FM) activities costs time and money being wasted for searching for the needed information from many different data sources. An integrated Building Information Model (BIM), depicting as-is conditions, has a high potential to minimize such wastes. However, facility managers still face the challenge of generating as-is building information models for existing facilities. A main problem with current approaches for generating as-is BIMs is that they mainly focus on capturing and providing geometric information. Many other types of information are missing, such as equipment warranty and technical parameters. The research described in this paper targets the generation of accurate and semantically rich as-is BIMs by leveraging heterogeneous existing information sources, such as drawings and operation and maintenance manuals. This approach was investigated through detailed case studies done in two old academic buildings. Existing information obtained from documents has been compared to industry foundation classes (IFC), COBie, and the data generated from a BIM authoring system. The comparative analysis results reveal several information gaps among different sources.

The objective of this study was to establish a relationship between facility energy management and asset valuation in federal facilities. The current operating pool of federal government facilities of varying size and location were considered in this study to determine this relationship. The overall value of a building asset was considered and evaluated in the context of the building's energy performance over time. One major conclusion was that facilities that had better energy management have higher "tier" ratings than those buildings that had little to no energy management. The findings of this study would be useful for facility/building managers and asset managers.

Research shows that noise is detrimental to developing children from many perspectives, cognitive, social, behavioral, and psychological; yet noise levels in classrooms are far from recommended standards. Studies suggest that the problem of poor acoustics exists for many reasons, including lack of acoustics education for architects and engineers, and lack of perception of the problem and its solution on the part of the professionals involved. Furthermore, these features often are discarded during value engineering or simply removed from the project to meet a predetermined budget. The issue is how we bridge the gap between research results, acoustics standards, and real practice of classroom design and construction. The problem of classroom acoustics involves multiple criteria, decision makers, stakeholders, and alternatives. Therefore, it is a valid problem for applying the theories and principles of multicriteria decision making (MCDM). Consequently, the hypothesis of this study is that a robust structured decision-making framework to facilitate choice of optimal classroom acoustics can be developed. This decision making framework is expected to facilitate decision-makers implementing new standards and policies, as well as provide professionals who are involved with school design and construction with decision rules for making informed choice about classroom acoustics within a specific decision context rather than being guided only by cost-effectiveness.

With the facility management industry increasingly adopting Building Information Modeling (BIM) technologies, there is a need to investigate where this industry stands in its application. Moreover, studies on efficient and cost-effective solutions to integrate BIM and mobile augmented reality (MAR) present an environment where facility managers can experience an intuitive natural interaction with their mobile interfaces to access their required information efficiently. The industry's view on this new approach of accessing information from BIM models also should be investigated and its feedback should be considered for future phases of this avenue of research. This paper explores not only how BIM can be beneficial to facility management practitioners but also how its integration with MAR and making the data accessible through handheld mobile devices can enhance current facility management practices. An online survey was conducted to assess professional facility managers' characteristics, technology use and working environment, as well as the current status of BIM application in their practices. An online video scenario also has been used to illustrate to facility managers how a BIM-MAR integrated environment can provide them with mobile access to their required information. Facility managers' feedback on usability, applicability, and challenges of such environment has been investigated through a followup survey. With this study, industry practitioners, as well as academic researchers, will be able to understand the current status of BIM and mobile computing application in facility management along with the benefits and challenges of implementing these technologies in an augmented reality environment.

Until now, the process of obtaining spatial information for facilities management (FM) has been laborious and tedious, even with the use of computer-aided facility management tools. The proposed research utilizes BIM-based workflow to capture object attributes such that the building data created in a BIM model may be brought seamlessly into a facilities management system rather than recreated. The proposed system not only imports geometry of walls, doors, windows, columns, and so on, but also retrieves attribute data associated with these objects. Therefore, queries can be executed to obtain needed information, generate graphic or data-based reports, and identify interesting trends in facilities operations and maintenance for appropriate management. Because the proposed approach is object-based, the system will calculate automatically or display the area of each space, and add additional information about each space, such as occupant information, capacity, type, equipment, and so on. Open BIM standards are used to retrieve or store information in a BIM model as that will facilitate the exchange of information among different FM systems. A prototype of the proposed system was developed in collaboration with the University of North Carolina at Charlotte (UNCC) FM department. The prototype was tested for its applicability and flexibility for the UNCC FM operations and maintenance management.

According to the Hartford Institute, there are about 350,000 churches in the United States. Churches generally operate fewer hours per week than commercial or industrial facilities. Congregations generally are small with a median size of 75 and annual church budgets of $90,000. About 90% of all American congregations are 350 or less, but 50% of all church participants attend churches with more than 350 attendees. In light of recent increases in energy costs, many churches in the United States consume significant portions of their operating budgets for lighting, heating, and cooling. Graduate students in the Master of Construction Management program at Western Carolina University in North Carolina performed energy audits of churches during the spring semester of 2013. Eighteen churches were audited. Average energy bills amounted to nearly $20,000 per year per church. Recurring energy wasting issues were noted and categorized. A list of common, low-cost energy conserving strategies was formulated based on the recurring themes of the audits performed. Inefficient incandescent lighting still was used in 12 of the churches surveyed. Weather stripping and caulking issues were noted in nine churches. Motion sensors for lighting control were recommended for nine churches. Programmable thermostats were recommended for 10 churches.

Although knowledge is a vital resource for construction companies, most organizations do not take full advantage of their knowledge resources. In many cases, knowledge management is a game of extremes; either managers take a hands-off approach and employees fail to initiate connections that would otherwise be useful, or they embrace a spirit of collaboration that saturates employees with relationships and information flows that are redundant, time intensive, and distracting. To better understand what drives effectiveness in knowledge sharing networks, this study examines the relationship between structural and relational factors and the perceived usefulness of knowledge sharing connections. Results indicate that there is no association between usefulness and communication frequency, media richness, or geographic and disciplinary boundary spanning. These results and their implications are discussed in depth.

The modular construction industry has made significant advances in the last two decades that qualifies it as a more efficient, greener, and affordable alternative for delivering building projects. Modular construction depends on moving portions of the project work to offsite manufacturing locations where the building is manufactured in modules, transported to the site, and erected in the designed configuration. Currently, modular construction is a sizable industry that encompasses its own stakeholders, customers, vendors, and supply chains. However, there is no comprehensive understanding of the structure and growth dynamics of this industry that is necessary for predicting its future performance trends. Accordingly, this paper presents a comprehensive description of the modular construction industry structure and a preliminary analysis of previous growth trends and dynamics. Different aspects of the industry are described in terms of its main stakeholders, supply chain interactions, logistical requirements, and economical attributes of manufactured modular buildings. The industry growth dynamics and trends are analyzed by examining available historical performance data of the modular construction industry that have been collected by the Modular Building Institute since 1994. The findings of this analysis should prove useful in developing future advanced models to help in designing efficient policies and measures to support the growth of the modular building industry.

Often cited as a major barrier to the seamless exchange of data and information among project team members evolving in the architecture, engineering, and construction (AEC) industry, technological interoperability has been the focus of many ongoing research efforts within the AEC field. In other knowledge fields, such as information systems (IS) and military research, the interoperability construct has evolved beyond the purely technological domain to encompass multiple dimensions. Within the AEC industry, these dimensions of interoperability have yet to take root. This paper introduces a conceptual framework that develops the interoperability construct across multiple dimensions. The framework defines emerging collaborative project delivery systems within the AEC industry by relating the technological, organization and procedural dimensions and situating them within the contextual dimension. The framework is underpinned by an information processing systems approach to project delivery in the AEC industry. Based on a two-part systematic literature review, a rigorous and structured process aimed at answering a very specific and targeted question within a given field, this paper presents the conceptual framework and discusses the various dimensions of interoperability. The paper concludes by presenting opportunities for future research through gaps identified in the literature. It is believed that by adopting this broader view of the interoperability construct in the AEC industry, the deployment of seamless collaborative project delivery systems and emerging technologies and processes, such as Building Information Modeling (BIM) will be better informed and structured and thus more effective and efficient.

Design and construction projects incorporate stakeholders from many different organizations, often with conflicting goals, overlapping responsibilities and differing areas of expertise. With an increasing interest in improving the integration and collaboration on construction projects, there is a need for empirical research to understand the contributions of project team interactions to project-level performance. The purpose of this paper is to explore the correlations among several indicators of the collaborative team environment and traditional measures of project success. With the assistance of an industry advisory board, a survey questionnaire was developed to collect detailed information for recently completed building projects in the United States. The questionnaire was distributed via mailing lists, conferences, and industry contacts to reach a diverse set of respondents. Using this large data set of 124 projects, bivariate Spearman rho correlation coefficients are calculated and reported. Significant correlations suggest the role of on-time communication in reducing construction cost growth, higher team chemistry in reducing overall schedule growth, and larger administrative burdens in increasing construction cost growth and final unit cost. Multicollinearity among the measures of team environment suggests the presence of latent variables and the need for future multivariate analyses.

The architectural, engineering and construction (AEC) industry currently lacks streamlined corrective measures to improve communication within cross-functional teams and optimize project outcomes. Previous research in this area offers lean construction methodologies, Building Information Modeling (BIM) techniques, and integrated project delivery (IPD) principles. However, communication aspects within project teams and their effect on project outcomes are to be examined further. Using a well-accepted taxonomy of team processes, this paper explores the communication aspects among AEC team members in an IPD case. Process maps developed based on project team meeting minutes guided this study in identifying the episodes in study case leading to positive or negative cost outcomes. Because of the intrinsic characteristics of IPD projects, the authors were able to rule out some key concepts of team integration, such as collaborative decision making, respect, trust, early involvement of participants and open communication, and focus on information exchange dynamics among participants in the case study. Results suggest that influence in decision making, integrated communication, and timing for key decisions are among the major factors that lead progress during project delivery to optimize project cost.

Today, state highway agencies (SHA) invest a large amount of money in collecting, storing and managing various types of data ranging from roadway inventory to pavement condition data during the life cycle of highway projects. Despite this huge investment, the use of data in satisfying users' need to extract information and knowledge and support decisions has become questionable. This paper presents a conceptual highway data quality report card (HDQ_RC) that can indicate the level of data quality by identifying decision makers' requirements through the application of a quality function deployment (QFD). The report card utilizes 10 data quality dimensions identified from review of literature and interviews with department of transportation (DOT) managers to analyze the data needs of pavement management decision makers' at a project level. A multi-attribute approach is utilized to analyze the level of data quality with respect to active utilization. The output of this paper may be used as a tool to evaluate the status of various highway project data by linking decision makers' requirements with data quality dimensions. This type of report card also will help justify the return on investment on the continuous and growing data collection efforts.

The construction industry is one of the most information-dependent industries where effective communication greatly affects the successful delivery of a project. Whereas the best way to communicate is to involve project participants in all activities throughout the duration of project, lack of collaboration in projects' early stages could result in a great deal of waste in the design, rework in construction, and delay or even failure to achieve initial goals. Although a considerable amount of research expanded the existing knowledge toward effective construction communication, studies show that there are still difficulties in controlling the spread of information during many projects. The objective of the presented research is to develop strategies for resolving early-stage communication problems by focusing on team structure and information diffusion in construction projects. To address those issues, a team structure optimization framework through social network analysis (SNA) is proposed. This paper first introduces SNA as a tool for understanding the spread of information in construction projects. A model then is developed to simulate project participants' interaction and analyze potential communication problems. An illustrative example finally is presented to demonstrate how to optimize team structure for balancing communication in a construction project.

In contemporary construction environments, employees and managers alike are faced with numerous pressures to carry out work to meet corporate expectations of performance. Continuous change and adaptation in organizational structures, practices, and technologies are conducive to successful management and execution of construction projects. Construction projects tend to measure how well they perform against a set of predefined performance indicators. These performance indicators are based on the ability of construction projects to attain necessary sets of "competencies" that enable successful execution of work. This paper identifies and classifies the different competencies and performance indicators that are used in construction projects and proposes a framework and methodology to identify and measure them. Appropriate measurement scales for the different competencies and performance indicators are developed, and a survey structure is proposed to collect data on the competencies and performance indicators from experts in the construction domain. A data aggregation method is introduced to combine experts' evaluation of construction projects' competencies and performance indicators. Last, the paper discusses future work pertaining to the development of a cascade fuzzy neural network that can predict different performance indicators for construction projects based on the identified competencies.

The Ghanaian public sector procurement is experiencing a paradigm shift from a clerical role to a more strategic function targeting optimum achievement of value for money. For this to be fully realized, the skills of the workforce must be developed to meet contemporary expectations. Underperformance and misapplication of the public sector procurement function has been linked to a shortage of an adequately skilled workforce. This study was designed to ascertain the nature and level of professional development required to enhance competencies of the workforce for successful delivery of the procurement function. The study employed questionnaires and interviews in a mixed methodology to collect data from the procurement management workforce within the Ghanaian Road Subsector. The findings of the study suggest weaknesses in key skill areas required of modern procurement practice, which inhibit the achievement of maximum value for money. Up-skilling is recommended through appropriate training and continuous professional development with focus on the key areas identified.

The government patronizes and awards public sector construction projects to large construction companies in South Africa based on the premise that they are technically and financially capable of executing the projects. In spite of this assumption and important contributions made by the construction organizations in delivering high-profile construction projects, many clients report poor performance of contactors on public projects. This paper, therefore, investigates the competitive strategies being used by large construction companies, their financial performance, and whether their knowledge of the business environment help in obtaining beneficial strategic fit and fiscal performance. This study intends to use the synthesis of industrial organization, contingency, and resource-based theories in developing measures of environmental factors and competitive strategies used by construction companies. Parametric and nonparametric statistics are used in analyzing quantitative and qualitative data obtained from the questionnaire survey. It emerged that corruption and lack of transparency was perceived as the key exogenous environmental factors influencing the strategies adopted by construction companies, while manpower problems associated with trade unions was perceived as the key endogenous environmental factor. The results also indicate that the differenting competitive strategies of achieving high quality and time (which are correlated negatively to financial performance) were viewed by the respondents as the best strategies to adopt. This research contributes to the discourse on competitive strategies in the construction industry and best practices.

Practitioners in the construction industry acquire much tacit knowledge at the workplace. Tacit knowledge involves much contextual information that is difficult to codify and share, so that it normally remains in the minds of individuals. Sharing context-rich tacit knowledge requires active interaction between knowledge-holders and knowledge-seekers. Thus, sharing tacit knowledge at the workplace is highly dependent on organizational ecology. The objective of this study is to investigate and evaluate the maturity of organizational ecology for sharing tacit knowledge in the construction industry. To this end, this study has surveyed industry practitioners. This paper presents a preliminary result of the survey with respect to five areas of issue concerning tacit knowledge sharing—perception, personal awareness, organizational readiness, current practices, and obstacles.

Increasingly competitive business environments and restrictive financial conditions have led owner organizations in the architecture, engineering, and construction industry to implement alternative project delivery methods. Whereas the goal of alternative project delivery methods (APDMs) is to increase project delivery performance, the organizational challenges that are encountered during the implementation and adaptation of these tools often are overlooked, particularly in reference to employee resistance to change. This research utilizes an action research approach to gather empirical data on the behavioral elements of resistance to change within large public and private architecture, engineering, and construction (AEC) owners across North America. Observational data was collected for levels of change readiness and types of resistive behavior exhibited by key employees at multiple phases of the project delivery life cycle. Key findings included a statistically significant, directly proportional relationship between employee training levels and their readiness for change. Additional findings identified the most commonly encountered type of resistance to be employee tendencies to revert back to traditional project delivery practices during implementation of new APDMs. Based on these findings, the authors conclude that AEC owners should emphasize formal, change-related training programs when implementing new project delivery processes within their organizations. Future research is recommended to investigate the effect of other organizational characteristics and change-implementation strategies on employee resistance to change.

The use of different theoretical frameworks and models of construction innovations is based on the particular characteristics of the construction work, including the types and modes of innovations, the "players" involved in the projects, and other influences. Recently, some new models have adopted new perspectives and approaches, such as socio-psychological perspectives, sociology of technology approaches, and actor-network theory. Some models were tested empirically with specific technological and nontechnological innovations in architectural and engineering design firms. The goal of this study is to explore how sustainable innovations in the building sector can be understood through diffusion of innovation theories. To do so, previously proposed frameworks and models are reviewed critically; then, empirical studies are synthesized to find inconsistencies in the literature. As a result, this study clarifies the commonalities and dissimilarities of the suggested models of construction innovation and discusses how different models supplement each other and can be combined. Attention to the process of adopting sustainable construction innovations reveals common challenges of sustainability, as well as leverage points where stakeholders can intervene in the building sector for sustainability. In the end, through the proposed theoretical framework, future research that can facilitate the adoption of sustainable innovation is suggested.

New technologies are increasingly offered by vendors in the construction industry. Several studies in the literature have examined information technology adoption at the individual level and how administrative and process innovations are diffused through the industry. However, vendors' diffusion strategies for tools, plant, and equipment from an organizational perspective have received very little attention. This paper explores the different patterns of strategies that vendor organizations use to influence their customers in the decision process, understanding that the customer is not usually an individual in the organization but a much larger group of people, many of whom will not come into direct contact with the vendor's staff. Vendors offer solutions to construction companies and support the decision makers by providing relevant information. It would be very helpful to recognize whether there are patterns in vendors' diffusion strategies. Identifying the patterns and the basis of these patterns, such as particular technology types, would help customers predict the vendors' role in technology adoption at an organizational level rather than at an individual level. Data about the activities and means of product presentation of vendors at a technology exhibition provided the basis for classification, analysis and pattern recognition. The identified patterns subsequently were validated using data from a second exhibition. The finding of the fuzzy analysis resulted in clustering the vendors into five classes according to three groups of technologies, each with unique characteristics of behavior. The presented classification pattern contributes to understanding the supportive strategies used by vendors to influence the decisions of potential users.

In recent years, the international construction market has witnessed the growing eminence of construction professional services (CPS) while the traditional contracting sector remains strong. Today, it is not uncommon to see a design firm taking over the work of a traditional main contractor, or vice versa, of overseeing the delivery of a project. Much has been said about the nexus between the two business sectors in the international market, but little has been done to articulate it using empirical evidence. This study examines the nexus between contracting and CPS businesses by offering and testing lead-lag effects between the two in the international market. A longitudinal panel data composed of 23 top international contractors and CPS firms from the Engineering News-Record's top lists over the past 12 years was adopted. Surprisingly, it is found that CPS business does not have a significant positive causal effect on contracting, and vice versa. CPS and contracting subsidiaries in the same company do not necessarily form a consortium to undertake the same project; rather, they often collaborate with other CPS or contracting counterparts to undertake projects. The research provides fresh insights to the diversification strategies adopted by international contracting and CPS firms.

As the opportunities for international construction projects continue to grow, there is also a need for better understanding of uncertainties and risks that international contractors face in different business environments. Those opportunities are a double-edged sword, because the international contractors may end up with catastrophic failures unless the multitude of risks are not analyzed carefully and mitigated appropriately. This study uses the institutional theory as an analytic lens to investigate the risks of international construction projects. This study identified and classified institutional risks and noninstitutional risks with which international contractors are confronted when they venture into international construction markets. Level of risk occurrences, their effects on the project cost and schedule, and characteristics of the firms' strategic responses to those risks are investigated using the survey data of 139 international projects. The data analysis results using the analysis of variance (ANOVA) show that there are significant differences in the average magnitude of risks and their effects on the cost increase and schedule delay by risk categories (macro, micro, and noninstitutional risks) and the host country's institutional efficiency. In addition, preresponse methods used by the contractors to mitigate risks are also different by the risk and country type. The findings of this study are expected to contribute to establishing effective strategic risk response plans for international projects.

Although tremendous focus in management research is placed on new construction technologies, the social and human factors through which these technologies are implemented often are neglected. An increasing trend in construction management research is seen in soft management aspects, such as trust. This basically developed from the fact that construction projects involve individuals and their beliefs. Construction projects are based on collaboration among contracting parties to accomplish project goals. Thus, it is crucial to build teams quickly and establish good communications among team members. Trust has been determined by many studies as an excellent determinant to successful projects and crucial to building integrated project teams. The aim of this paper is to present a literature review of research on trust in construction, identify knowledge gaps, and suggest recommendations for future research. More than 50 peer-reviewed publications were reviewed through which six main lines of research were identified. Research in trust in construction seems to focus primarily on four main areas: trust types, factors affecting trust development, trust effect on project success, and relational contracting. Yet there still exists knowledge gap in areas of nonrelational agreements, North American construction markets; and project cost, risk, and contracts' relations to trust.

With the spectacular rise of the Chinese and Indian economies the accompanying growth in these two countries' construction sectors justifies more understanding. There is, however, a lot of unknowns about the two countries' construction sectors from a comparative perspective. This study attempted to identify and compare the comparative/competitive advantages of the two fast-growing economies in construction in pursuit of policy and management implications, which can benefit not only the two countries but also other developing countries. In this regard, a comparative advantage framework and Porter's Diamond Framework were applied to analyze the relative advantages of the Chinese and Indian construction sectors. The comparative analyses showed that China appears better endowed in labor with high productivity. Government intervention was identified as benefiting Chinese firms with support for the development of human resources. China also benefits from superior access to a wide range of inputs, including equipment, construction materials, and technology. The existence of large corporate champions provides scale of economy and contributes to the advantage of the construction sector of China. In contrast, India benefits from the increased competitive rivalry thanks to its more hands-off government policies that focus primarily on providing a good business environment with a favorable tax system, market entry policies, laws and regulations, and code/standard systems. The differences identified provide policy implications to the decision makers of the two countries in further developing their construction sectors.

As the architecture, engineering and construction industry globalizes, design and planning work increasingly is executed in geographically distributed and culturally diverse global virtual project networks (GVPNs). Within a GVPN, boundaries exist that can interfere with collaboration effectiveness and work processes. To increase effectiveness of GVPNs, we need to develop a better understanding of how to span boundaries. Although previous research has examined strategies for spanning individual boundaries, we lack an understanding of how multiple, layered boundaries can be spanned simultaneously. For instance, when knowledge domain boundaries correspond to cultural boundaries, are cultural boundary spanners able to support network interactions effectively? Our research examines a case where cultural, technological, and knowledge domain boundaries simultaneously exist to identify effective interacting strategies that minimize the effect of the boundaries on project execution time. Based on a social network analysis, our results indicate that cultural boundary spanners may not be effective when simultaneously spanning knowledge domain and technological boundaries. Our research contributes a preliminary exploration of layered boundaries and layered boundary spanning in GVPNs and provides project decision makers with insight into effective GVPN team composition and interacting strategies that can lead to more efficient project outcomes.

While the United States experienced a sharp decline in residential real estate prices in several regions over the past few years, the Middle East experienced a significant escalation in residential housing costs over the same period. This escalation has led to several social and economic problems, including public dissatisfaction with government policies. The housing cost escalation could be attributed to a number of factors, including the rise of oil prices that typically leads to sharp hikes in inflation rates. The main objective of this research is to identify the factors that led to housing cost escalation, rank them according to their significance, and investigate the best strategies to address them in the short- and long-term. The study focuses on Riyadh city as a case study to apply the proposed methodology, which includes identifying possible factors from the literature, conducting surveys, and interviews; soliciting evaluation as to the effect of these factors; and conducting quantitative statistical analysis to compare the effects of the factors. The most effecting factors are identified to facilitate further investigation of their effects and propose strategies to address these effects. This should prove useful to other cities experiencing similar trends, as it presents a systematic replicable approach to identify the cause and effect of housing cost escalation.

One of the most compelling reasons to examine the globalization of the engineering and construction industry relates to the business opportunities it brings; yet global collaboration also creates distinctive challenges, especially in the early stages, that firms must overcome. Overcoming these collaboration challenges in a virtual environment may require different approaches for global virtual project networks (GVPNs) as compared to domestic virtual project networks (DVPNs) to achieve performance objectives. In this paper, we examine facilitation, a boundary spanning collaboration technique that may have unique requirements in GVPNs. We observed two DVPNs and two GVPNs working in a virtual workspace called the CyberGRID and studied the interactions among network members to examine whether significant differences exist in the utilization of facilitation in the initial stages of collaboration. We found that facilitators were utilized more frequently in GVPNs. This finding has important implications for the efficient functioning of the increasingly common global project networks in the construction industry that utilize virtual collaboration techniques.

Limited research has been carried out on artificial-intelligence-based deterioration modeling for coastal structures. An asset inventory database (AID) for Alexandria's Eastern Harbor coastal assets was developed. Established visual inspection and condition rating procedures were followed to obtain a current structural condition index (SI) and a structural condition matrix (SCM) for each structure, considering a single inspection point. SIs and SCMs are classified into severity ranges. Taking the age of structure into account, transition probabilities between each of the deterioration severity ranges were calculated using backward analysis. Such probabilities then were utilized to formulate the structure's Markov- Chain (MC) transition probability matrix, enabling the prediction of future deterioration in case of a no-action policy. Furthermore, an artificial neural network (ANN) model was constructed using the same backward analysis concept. Comparing the MC and the ANN deterioration forecasts up to year 2050 for the same structures, the results showed very close deterioration trends with an error margin ranging between 5% and 12%. It was concluded that the stochastic MC-based deterioration modeling was more accurate in simulating the deterioration of structures between their year of construction and present. The deterministic ANN model showed promising capability of deterioration prediction depending on the quality of the structure's design data, historical records, and environmental conditions.

Building energy assessment models support design decisions, which should be made only if stakeholders are confident that the decision taken will result in a preferred outcome. Despite this fundamental notion, the assessment of confidence in decisions is not included in current energy assessment tools. Uncertainties in model inputs and in the appropriateness of the models used leads to uncertainty in model outputs and therefore to a reduction of confidence in the decisions supported by those outputs. In early design stages, there is great uncertainty about how a design might evolve, which leads to large uncertainties in predicted outcomes, rendering the appropriateness of performance prediction to the decision questionable at this phase unless these uncertainties are quantified and used in performance predictions. Here we propose a quantification of these uncertainties and preliminarily examine their effect on confidence in design decisions using a case study.

Buildings are responsible for 40% of the national annual energy consumption, 72% of electricity consumption, 13% of water consumption, 39% of all carbon footprint, and 30% of the total waste output in the United States. These negative environmental and economic effects have motivated many owners to explore various sustainability measures in their buildings, including energy efficient devices (such as LED and fluorescent lighting, HVAC systems, ground-source heat pumps, hand dryers, vending machines, refrigerators, and water heaters); renewable energy equipment (such as solar panels and wind turbines); and water saving plumbing fixtures (such as efficient faucets, urinals, and toilets). These sustainability measures can improve building performance in terms of energy efficiency, water conservation, waste reduction, and longer life cycle. Despite higher initial costs, in most cases, these sustainability measures can pay back these costs because of their lower energy and water consumption. Because of the large combination of options and the payback period, decision makers often are faced with the challenges of which option to select because of limited budgets. This paper presents an optimization model that is designed to identify an optimal selection of building sustainability measures that are capable of minimizing the annual operational costs of the building while complying with a limited upgrade budget. The optimization model analyzes the replacement of building fixtures and equipment with more energy- and water-efficient alternatives to reduce building operational costs. The optimization analysis accounts for the initial replacement cost, maintenance cost, operational costs, energy and water savings, discount rate, payback period, and functional performance. An application example of a public building is used to illustrate the capabilities of the developed optimization model and verify its results.

In an effort to achieve large-scale energy savings, governments have been developing energy conservation policies that target large numbers or stocks of commercial buildings. Although actions performed by occupants and facility managers significantly affect building energy performance, current policies overlook the importance of human actions and the potential energy savings from a more efficient operations of buildings. This slow policy adoption is attributed mainly to the absence of energy modeling tools and frameworks that evaluate nontechnological drivers of energy use and quantify energy savings for large stocks of buildings to support policy-making efforts. Such an evaluation is, in fact, essential to help policy makers set specific energy conservation targets, highlight the need for operation-focused policy tools, and justify corresponding investment costs. Therefore, this study proposes a systematic approach to quantifying the energy savings potential because of improved operations of any stock of commercial buildings. The proposed framework is general and combines energy modeling, existing studies on human actions in buildings, and surveying methods. The framework's capabilities are illustrated in a case study performed on medium-sized office buildings in the United States. Results indicate a potential 18% reduction in the current energy use levels of these buildings through realistic changes in the operation pattern of different building systems.

The effect of construction detailing on energy efficiency of buildings has received a lot of attention on the component level but not enough on the whole building level. Inadequate construction detailing and workmanship lead to deterioration of façade properties. Their occurrence and effects cannot be determined in a deterministic way. It is, therefore, relevant to quantify, in a probabilistic sense, the role of construction detailing and workmanship on overall building energy performance. This paper focuses on two typical construction concerns, namely, thermal bridge and air leakage. We set up a method to quantify the typical variability of infiltration and thermal bridge workmanship effects, and introduce a detailed case study to examine the effect of construction practice on building space heating and cooling demands. The relative importance of construction detailing and workmanship in achieving energy-efficient buildings is discussed.

Accurate quantification of energy cost savings associated with retrofitting poor building envelopes can minimize the financial risk of insulation retrofit investments. However, reliable estimation of the expected monetary savings through improving thermal efficiency is not a trivial task. To overcome this, we present a new infrared thermography-based method together with cost estimation process that evaluates the cost-benefit of insulation retrofit alternatives. Our method relies on collections of thermal and digital images acquired during building diagnostics. These images are used to develop energy performance augmented reality (EPAR) models that jointly represent actual and expected building thermal performance in 3D. By exploring the performance gaps in the EPAR models, potential thermal defects are detected automatically. Then, based on a point-based measurement of the actual R-values of the detected areas along with the degree-days statistics, the amount of energy loss and the expected energy saving cost by retrofitting the detected problems are estimated. Finally, we compare the expected energy saving cost with the cost of retrofitting the detected problems. Our results from several experiments conducted on two existing buildings hold the promise for a reliable diagnostic method that can help minimize the risk of retrofit investments for homeowners.

A lack of standards that define the energy auditing process and the energy modeling methods for the retrofit building sector has resulted in variable outcomes. One cause of the variability is the limited time industry members have to devote to energy model development coupled with the lack of understanding of which input parameters are the most effective in terms of energy use projections. For the research, a case study is presented regarding a retrofitted building, which was not performing as the energy model created during the retrofit design had projected, and possible reasons for the discrepency are identified. LEED documentation, the retrofit design drawings, and the energy model report were used to recreate an eQuest model that aligned with the original eQuest model used for the retrofit design process. A sensitivity analysis was performed to determine the effect-specific energy modeling input parameters (identified through the case study) had on the energy analysis outputs. The intent of the research was to confirm that energy modeling input parameters have varying effects on energy use projections. With a clearer understanding of the varying effects input parameters have on energy use projections, industry members can begin to sense where they should allocate time when developing an energy model.

Approximately 30% of energy use in Canada is consumed in buildings. The largest component of this energy consumption in multifamily residential buildings is space heating. One of the primary functions of building enclosure is reducing space-heating energy. Although heat flow cannot be completely prevented, it can be controlled to reduce energy consumption, create a sustainable environment, and implement indoor human comfort. However, this can be achieved by constructing a thermally resistant building enclosure. This study aims at developing and evaluating some innovative potential energy-efficient wall systems for mid-rise, wood- frame buildings in terms of their thermal and structural performances. Regarding the thermal resistance performance, four wall systems were developed, installed in a full-scale testing house, and examined on a long-term period along with a baseline wall system. The selection of the wall systems was based on specific considerations: current practice, preliminary structural analysis, prefabricability, and expected energy efficiency. Several sensors were installed at each wall system: heat flux, thermocouple and humidity sensors. The results from the thermal analysis and the structural tests provide useful directions toward future development of energy-efficient wall systems.

Taking into account the increasing complexity and scale of construction projects recently, interface management (IM) has been emerging as an important aspect of project management practices. It is believed that effective IM improves alignment and reduces conflicts among project stakeholders by increasing visibility on roles, responsibilities and deliverables, particularly in large projects. The recent improvements in the communications and information management technologies make it possible for the global mega-project, such as oil-sand, off-shore facilities, to employ IM as a part of their project management process. Mega-projects generally are defined to be more than $1 billion; however, projects with lower cost but high organizational and interface complexity are also good candidates for IM adoption. Although there is a high demand for IM, it has not been well-defined yet, which limits its full adoption. As part of a research program to identify and establish the definitions and best practices of IM, sponsored by the Construction Industry Institute (CII), the authors investigated the current state of IM in 37 projects. These projects, including owners and contractors working within different construction sectors, are surveyed according to their general characteristics (e.g., cost, project types, etc.) and IM adoption. Furthermore, the research team analyzed the IM adoption with respect to several interface risk and complexity factors within these projects. The expected contributions of the research will be a comprehensive study of the current state of IM in construction mega-projects, identifying the factors that may lead to implementing IM in projects, and providing the definitions and preliminary principles for establishing effective IM.

Extensive research and published material exists addressing owner, contractor, and supplier relationships and contracting methods. Also, there exist a variety of capital project delivery systems in construction industry, which all aim at delivering projects to project owners with desired quality and within expected cost and schedule. These project delivery systems are predefined systems and processes each defined to address some of the many problems that keep owners of projects from achieving their desired results. Previous literature, however, indicates that the outcomes of applying these delivery processes are still disappointing to owners and not promising to a major part of the construction industry. The major objectives of this Construction Industry Institute (CII)-funded research were to identify an innovative approach to project delivery, challenge the industry and its customers to create conditions for ideal project delivery paradigm, and provide suggestions on how to approximate the ideal in imperfect conditions. The research objectives were attempted through a combination of qualitative and quantitative research methods. A comprehensive review of existing literature in the field and creative thinking workshops were steps in the research to achieve the vision to the new ideal project delivery system and to develop the hypothesis. The hypothesis was then tested and validated through statistical analyses and case-study research. We concluded that superior project performance can be achieved by breaking existing paradigms and implementing organizational integration, alignment of interests, and management-by-means through new project delivery systems.

Effective collection and dissemination of project information including procedures and guidelines that help increase the likelihood of construction management success is vital to organizations. Inside the construction industry these pieces of project information are referred to as "best practices." In a global economy, it is crucial to have successful practices standardized and accessible across organizations when needed. Best practices can help improve project performance, yet these practices are not implemented universally in the industry, because of the following: Not all practices are applicable to every project or organization; knowledge is lost in organizational turnover (which leads to inconsistent collection and implementation of best practices); andthere is a lack of standardized processes for best practice management in an organization. This study, sponsored by the National Academy of Construction, the Construction Industry Institute and Arizona State University, used structured interviews and a Delphi study to examine the best practice management process further, common pitfalls, and the efficacy of an open repository of best practices repository. This paper presents the authors' findings to date, specifically exploring the term "best practice," its definition, elements that hinder implementation, and the potential value of an open online repository for such practices in the AEC industry.

Given that a construction site is both temporary and unique, the outcome of every construction project is dependent on having all of the proper resources delivered to the site at the appropriate time. Although construction supply chains, logistics, and materials management systems have been scrutinized in recent years, the full range of potential late deliverables has not yet been investigated. Further, the true effects of these late deliverables are much more far-reaching and less understood. This paper, part of a larger research project being developed by the Construction Industry Institute Research Team 300, describes the process followed to list and categorize common late deliverables to industrial construction sites using team knowledge, expert interviews, industry surveys, and indepth case studies, as well as a review of the existing literature on the topic. This information will serve as a starting point for an investigation into how these late deliverables affect the cost, schedule, quality, and safety performance of construction projects along with the effects on the organizations involved. The enumeration and classification of these project effects incorporating the perspectives of both owners and contractors, are also described in this paper.

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.

Construction safety performance in the past decade has stagnated to the point where only marginal improvements have occurred. Past safety performance has been driven by lagging indicators including capturing safety data only after an illness, injury, or fatality occurred. A significant improvement can be realized through effective use of leading indicators, such as near-miss data reporting, collection, and analysis. The primary objective is to identify best practices associated with a near-miss reporting program for construction companies. A near-miss reporting program was created from results of a review of literature and investigating established near-miss reporting programs of many construction companies. The created near-miss reporting program was implemented on construction projects of companies that previously failed to collect near-miss data. Project safety managers and workers were surveyed periodically throughout the duration of the construction project to capture benefits, limitations, lessons learned, and suggestions from the implemented near-miss reporting program. Results indicate near-miss data can be reported, collected, and analyzed by construction personnel. Research deliverables including near-miss reporting program guidelines, reporting flowchart, employee orientation presentation, and reporting materials can be used to implement a near-miss reporting program or enhance an existing program for construction companies.

Supplier quality surveillance (SQS) is an important process developed by Engineer-Procure-Construct (EPC) contractors to assure that products are delivered according to specifications and free of defects. In industrial projects, EPC contractors commonly design and oversee the fabrication of multiple products and large engineering components, which are classified in different levels of criticality according to the probability and consequences of failure and associated with these elements. The model discussed herein addresses the challenge of working toward zero rework in EPC projects. The authors use data obtained from an ongoing Construction Industry Institute (CII) project to build a simulation model that represents the different steps of the SQS process. Discrete event simulation is used to develop the model in the software EZstrobe. The model is developed to represent the dynamic nature of SQS, the interaction between different sub-processes (fabrication, release to site, and installation), and the effect the reliability of individual tasks has on the quality of final products delivered and installed at project sites. The results of the simulation are analyzed and a relationship is identified between the process capability (percentage of products delivered right the first time) and the inspection capability (percentage of nonconforming products identified and corrected).

This paper presents a recent initiative to revolutionize the benchmarking of capital projects. In the past 17 years, Construction Industry Institute (CII) has become a major source for the benchmarking of capital projects. Although the value of benchmarking has been recognized by CII member companies, they find it difficult to implement it because of various issues. To address these issues, CII began working with industry experts to develop a new performance assessment system. This new system, known as the 10-10 program, consists of input measures, such as planning, organizing, leading, and controlling and output measures, such as cost and capacity. This paper describes the new benchmarking theories deployed in the creation of CII's new benchmarking system. This paper explains what the new measures are and how they were chosen. The 10-10 program is substantially different from previous attempts to benchmark project performance by pairing high-value metrics with a minimum effort concerning data collection. The new system is capable of measuring absolute metrics for specific industry sectors. Importantly, users of CII's 10-10 program can assess their projects at the conclusion of each of five phases from planning through startup. As a result, project management teams will be able to take proactive actions to enhance project results. It is expected that the new system will promote enhanced performance assessment through external benchmarking.

Although the ratio of injuries and fatalities have decreased since 2009, their high rates still makes construction to be one of the top hazardous industries. OSHA and many companies that treat safety as their core value have stated repeatedly their strong desire for novel methods that speed up safety improvements. Improving the capability of hazard recognition in construction work frequently is identified as the first step toward building all other safety procedures. Without sufficient awareness and proper training on hazard recognition, even the best safety programs would not touch their desired expectations. Also, there is a need to understand better how different safety programs can maximize hazard recognition skills in workers. In response to these urgent needs, this paper explores a new training strategy for improving hazard recognition capability of construction workers. An augmented virtuality (AV) environment named SAVES (system for augmented virtuality environment safety) was developed and tested. SAVES integrates BIM with photographs of typical energy sources on a jobsite, allowing trainees to navigate and explore the built-in augmented training scenarios. This paper presents the model development and the implementation results, to validate how such an AV method can be designed to improve the capability of hazard recognition. The modeling process, analysis, and the lessons learned are discussed in detail.

Several studies have shown that the implementation of supply chain management (SCM) in the context of facilities management (FM) can resolve service delivery problems and provide significant benefit in cost savings and customer satisfaction. To utilize the benefits of SCM fully, the supply chain actors would require facilities' data, suppliers' information, and tools to share the information through a wide variety of users across the entire supply chain. Considering the wide range of spatial information used in the FM supply chain, this study develops a spatial data framework to manage data and disseminate information throughout a supply chain. The proposed framework uses Building Information Modeling (BIM) capabilities to accurately provide existing information about the inside of a building and geographic information system (GIS) to support the wide range of spatial analysis used in the logistics perspective of the supply chain. Also, semantic Web services are used to convey meaning and support the integration of information from all of these spatial, temporal, and informational dimensions. The concept of the semantic Web is applied in this study to provide semantic interoperability between BIM and GIS operations and to demonstrate the feasibility of the technology for the building and FM industries.

Increased consciousness of the environment progressively put more pressure on policy makers and urban planners to ensure sustainability of the built environment. The single biggest obstacle to devising environmentally sound urban development plans is the insufficient understanding of the urban system. The interactions between various components of urban environment as well as the large number of factors affecting its' environmental performance, makes it impossible to model today's metropolitan areas in every detail. Therefore some sort of simplification is inevitable for urban environmental modeling. However, to avoid subjective assessment of impact factors, it is necessary to define appropriate quantitative cut-off rules based on needs and available resources. This study proposes a framework for assessing the environmental effects of an urban area based on the concept of statistical "parameter variation and scenario analysis." The method is capable of considering any sector in an urban development with desired level of details and provides information about the significance of environmental effects of that sector, as well as uncertainty of the results. A case study also is provided to elaborate the capabilities of the framework.

Out-care centers are small health units with the aim to provide certain care functions in close proximity to patients. Planning for optimally locating such centers within an urban area is, however, not an easy task. This paper presents an agent-based model to support localization decision making of such out-care centers within a specific urban setting. The model accounts for patient preferences when choosing a specific out-care center, for instance, travel time, waiting time at the center, walking distance in and around the center, and service level of the center. The model also uses historical patient history data to predict the number of patients that seek treatment within a specific area. To this end, the model implements a GIS link that links patient admittance data to GIS-based postal codes. Finally, the model can simulate the out-care center market dynamics within a region. It does so by modifying the initial arrangement of out-care centers by gradually relocating them in random directions with the aim of maximizing the market share, and therefore profits, of each individual center.

Technologies of alternative energy generation for residential communities using algal material, involving the construction of bioreactors with solar cells, storage of raw materials, construction of central plants for conversion of biofuels, and delivery systems to users will have different design effects at different scales. This paper intends to define basic design and planning parameters for residential construction in accordance with the scientific knowledge and technical criteria available regarding the potential for algal biofuel production and sustainable urban living. This paper suggests a framework of GIS-based planning support system for informing processes of data representation, performance assessment, and design for the coupled algae cultivation and urban systems.