Journal of Construction Engineering and Management

Public–private partnerships (PPP) are contracts with a long-lasting period, huge relationship-specific investment, and great uncertainties. In many PPP projects, it is difficult or even impossible to write a complete contract that specifies all contingencies, so a renegotiation-allowed contract could be better than a renegotiation-proof one. Under a renegotiation-allowed PPP agreement, renegotiations can significantly influence the interests of both the private party and the government, so they have to evaluate the benefit and cost of renegotiations ex ante and consider them in the tender price. This study considers renegotiations as real options that are embodied to provide flexibilities for PPP contracts, and develops a model to capture the value of renegotiation based on real option theory. The model is proposed in three steps, including modeling underlying risk, bargaining renegotiation payoffs, and determining real option value. An illustration case is presented to demonstrate the applicability of the model. The case study shows that if a renegotiation-allowed contract is used, then (1) contractor-led renegotiation is very likely to occur, especially at the early stage of concession while government-led renegotiation is less likely to occur, and if any, it should occur at the middle stage of concession; (2) one party could use opportunistic renegotiation to hold the other party up and ask for excessive compensation, so renegotiations must be regulated; and (3) renegotiation in a PPP project may have a huge real option value, and the higher the uncertainty, the higher the renegotiation value.

Mobile light detection and ranging (LiDAR) is currently one of the most used instruments in road inspections to collect geometric and radiometric data. Different strips of the same area are common and bring problems in data registration related to the inaccuracies of global navigation satellite systems. This paper shows a methodology for automatic and robust data registration. It is based on segmentation of highly reflective data (i.e., road signs) and avoids the use of control points manually marked, typically used in the traditional techniques. The data set must be acquired under favorable climatological conditions. Root-mean-square errors in registration show values around 2 cm, while if the high-reflectivity segmentation is not used values higher than 8 cm are obtained.

State departments of transportation (DOTs) have been trying to identify alternative and innovative sources of revenue and cost savings. One potential solution to funding issues that has gained recent attention is value extraction from highway rights-of-way (ROW). In this paper, first, the state-of-the-practice of value extraction projects in highway ROWs is established. Next, detailed analysis is conducted regarding three high-priority value extraction projects chosen by the Florida DOT including solar photovoltaic, light emitting diode (LED) lighting, and agricultural uses. The feasibility screening tools introduced in this paper integrate all of the research findings from the literature review, survey of state DOTs, and case studies of select projects and programs. The screening tools provide in a tabular form a thorough list of various technical and financial criteria that play an important role in choosing and implementing the related value extraction projects. The information provided for the individual value extraction project types can be used as a platform to successfully design and manage those projects in the highway ROW.

Decisions made prior to construction impact the safety of construction workers. Past research has shown that there is a link between design decisions and fatalities. Prevention through Design (PtD) is a concept that attempts to identify and mitigate hazards early in the design process with the goal of eliminating the risks of injury to workers and/or damage to facilities during construction. PtD is a required practice in some countries, primarily because of legislation. In the United States, however, PtD is not well known by design professionals and there is opposition to its practice. The objective of this paper is to present the results of a Delphi study, in which the Delphi panel was tasked to identify: (1) the construction industry group with the most influence to generate interest in PtD in the United States, (2) the method with which that interest can be achieved, and (3) the industry group that should be targeted with that method. The Delphi panel came to a consensus that owners have the greatest influence to generate interest, and they should be the group to be targeted using the business case method.

This study applies a fuzzy consensus scheme integrated with a multicriteria decision making method and fuzzy set theory to mitigate groupthink and disagreements among members of a building envelope design team. This fuzzy consensus scheme consists of freezing conditions and a standardized procedure to govern group decision making. The study employs a case study as a research design to test effectiveness of the fuzzy consensus scheme in mitigating groupthink and disagreements among the building design team members. In the case study, the design team is engaged and then tasked to apply the fuzzy consensus scheme when assessing different building envelope designs of a representative building project. A semi-structured interview is conducted to collect perspectives of the design team members regarding the effectiveness of the fuzzy consensus scheme applied in the case study in relation to their previous experience in similar actual projects. Results from the case study suggest that the fuzzy consensus scheme is useful in promoting group cohesiveness and generation of a variety of decision solutions. The scheme also assists the team members to express their opinions, listen to each other voices, and seek the optimal solutions that everyone in the team agrees with. These as a whole help mitigate both groupthink and disagreements among the team members. The main contributions of this study lie in the achievement of more effective group decision making and agreed design solutions. Future studies can incorporate the fuzzy consensus scheme into decision support tools to promote integration among project team members in several project development phases.

Since the effects of external conditions, such as limited resource supplies and poor working environments in damaged regions, are critical to facility restoration projects after a catastrophic disaster, a lack of understanding regarding restoration conditions may lead to unexpected delays and additional project costs. The fact that various elements of postdisaster restoration conditions interact with each other and vary with a facility’s surrounding damage and recovery situations over time makes many stakeholders’ comprehension even more challenging. To support immediate and appropriate facility restoration planning under changing project conditions, this study developed a hybrid system dynamics (SD)–discrete event simulation (DES) framework. In this hybrid restoration simulation, SD allows for a comprehensive understanding of the dynamic features of various restoration conditions, while DES enables an in-depth examination of facility restoration operations according to external condition changes. By allowing two simulations to seamlessly interact together, this study provides key insights into postdisaster restoration, including how complex and critical restoration conditions change over time depending on facility types and subregions, and to what extent these conditions adversely impact a project’s performance and uncertainty throughout lengthy project durations, especially when restoration work scope and processes vary with damage patterns. A test tool for analyzing the effectiveness of managerial policies is also provided by showing experimental results. For instance, a project initiation, postponed to avoid unfavorable restoration conditions, can be delayed to reduce the project’s uncertainty by alleviating possible increases in wasted time and cost of running an unproductive site. Therefore, the major contribution of this research to the body of knowledge in construction engineering resides in the capacity for the developed hybrid model to make facility restoration planning and execution deal with project uncertainties caused by chaotic and disrupting external conditions. As such, unexpected delays and additional costs common for postdisaster recovery can be alleviated.

Improving project performance has always been emphasized in construction projects. When project objectives contradict, the project manager must apply mitigating or conflict resolution strategies to remove or minimize the level of contradiction in order to enhance project performance. A typical example is conflict between cost and schedule, where cost tends to increase when the schedule is crashed (sped up). Although some of the current project control systems attempt to diagnose the root cause of performance deviations and suggest corrective action, none is designed to resolve conflicts in a systematic and innovative manner to improve the project performance. The purpose of this paper is to present a systematic and structured approach to guide project managers to propose corrective action plans that lead to minimal conflict and ultimately to better project performance. Resolving contradictions can generate effective corrective action plans that would enhance project performance. Conflicts among competing project performance indices such as cost, schedule, safety, and quality are obvious in any project. This innovative approach uses the theory of inventive problem solving (TRIZ) to develop a framework for a conflict resolution strategy called techniques for resolving project performance contradictions (TRAC), or the techniques for resolving performance contradictions. TRAC provides an algorithmic approach for solving performance contradictions in order to optimize the overall project performance. TRAC is a user-oriented methodology and presents a new model for performance problem solving to assist project managers in their corrective action exercise. TRAC methodology is demonstrated in two case studies that indicate the workability of this model and its usefulness in resolving performance contradictions in contraction projects.

An effective theory-based intervention strategy is developed to improve worker adoption of a ventilated dust-control tool that reduces dust exposure by 95%. The Prevention through Design Adoption Readiness Model (PtD ARM) was employed to develop educational materials, hands-on training, and worksite cues-to-action. Educational materials were targeted to improve worker knowledge of the health risks associated with construction dusts. Hands-on training was developed with the objective of improving worker self-efficacy regarding the new equipment. Additionally cues-to-action were given to the workers. These cues were hard-hat stickers and $t$-shirts with reminder slogans. In a pretest/posttest experimental design with control group ($n=40$), questionnaire data were analyzed using independent $t$-tests of the gain-scores, and significant changes ($p<0.05$) were seen in worker self-efficacy, trust-in-technology, and overall readiness to adopt the tool. Theory-based intervention strategies were found to be effective in improving worker willingness to use ventilated tools. The most impactful intervention methods include training regarding risks to worker health, hands-on training with ventilated tools, and cues-to-action reminders to use the tools.

Although the construction industry is a major component of the U.S. economy, it has been suffering from declining productivity for decades. The human element, project managers (PMs) in particular, are key in solving these persisting problems. Measurement of a PM’s overall performance is important to identify training needs and enables executives to better match competent PMs with the appropriate projects. This paper provides the construction industry with a generic mathematical formulation to reliably weigh different PM competencies. The developed data-driven mathematical model reflects the relative importance that industry practitioners place on different PM competencies while distinguishing exceptional PMs from average ones. This developed model is applied to a data set of 124 PM assessments filled by 62 PM supervisors so that each PM supervisor selected and rated an exceptional PM and an average PM. The results presented in the paper suggest that PMs should focus on developing their cognitive side, rather than settling only for possessing adequate knowledge and experience, managerial skills, and leadership capabilities. Also, these quantitative results illustrate that having business and financial acumens, disciplinary understanding of all the phases of construction projects and their interrelationships, continuous monitoring of similar construction projects, and consistent awareness of the available information technologies are among the most distinguishing competencies between exceptional and average PMs. Such results can assist the construction industry in directing its efforts toward accurately identified leverage development areas through pinpointing actual training and educational needs. Additionally, this paper compares the results of the developed data-driven mathematical model to an existing expert evaluation, presenting a key step in revealing and, in turn, reducing experts’ subjectivity.

“The Oops Game” explores the question, how much should be invested in planning? The simulation offers the opportunity to reduce the risk of an “Oops” by collecting more information or to go ahead and make the choice with the information at hand. There are two extreme strategies. Nothing is invested in planning in the so-called Guts-ball approach, but this increases the likelihood that an “Oops” will occur and thus increases the cost to complete the project. The second strategy is to invest in planning before attempting to build. This will increase the cost of planning upfront, but may reduce the risk and cost of an “Oops” in building. In reality, the cost and value of planning depends on the complexity level of the project, the amount of uncertainty that we need to deal with it, and the cost of an “Oops.” We used computer simulation to show how the value of planning is sensitive to those factors. The results showed that the project with the reliable planning strategy had a 35% higher productivity and a cost-benefit ratio of $13:1$. The contribution to the body of knowledge of “The Oops Game” lies in providing a simple and effective means to show the value of planning to construction practitioners and students. The findings from this research fill in the gap of knowledge in quantifying the value of plan under different circumstance for construction projects.

Traditional risk-assessment methods typically evaluate accident probability, exposure frequency or duration, and consequence severity, respectively, and finally determine a quantitative risk score or a qualitative risk level. The assessment process is prospective and subjective. Changing and complex construction situations impede their practical and efficient application. To assess safety risk with regard to changing site conditions in an objective and efficient way, this study proposes a quantitative model for hazard exposure assessment based on real-time location data of construction workforce and equipment, collected by a location-based proximity warning system. In contrast with traditional risk-assessment methods, the model proposed in this study combines accident probability and hazard exposure duration into a single quantitative concept—hazard exposure amount. This concept takes into account the space factor as well as the time factor of construction activities. For ease of understanding, a hazard is analogized as a radiation source and the hazard exposure is then referred to as the radiation quantity received. The longer duration and closer proximity in which a person is exposed to a radiation (hazard), the more radiation the person receives (the higher risk to which the person is exposed). A trial study is described in which a proximity warning system was developed and used to demonstrate and test the model’s capability of hazard exposure assessment. This shows that the system can provide safety officers with an ongoing and immediate means of comparing safety risk trends from worker, hazard, and project perspectives.

Ensuring that all resources required to complete a task (materials, equipment, etc.) are available is essential to create a reliable workflow. Yet, in customized house building, clients’ design information (e.g., design drawings containing clients’ desired changes) is a key input that is often missing. This can affect the performance of the task in which such input is first needed and all subsequent ones. In spite of that, this theme has received limited attention by the literature. It is not yet clear how to manage customization strategies to minimize disruptions in production or how to quantify the workflow variations created by distinct strategies. This paper addresses this gap by proposing a set of guidelines to manage customization strategies (i.e., clients’ information flow and scope of customization) to support a reliable workflow. A visual indicator is also proposed and applied in two projects (completed in 2011 and 2014) with distinct customization strategies. The results suggest that workflow variations (due to customization) were lower in the latter project. The changes in the strategy that led to the improvements measured are discussed. This research contributes to the existing body of knowledge by (1) presenting guidelines to manage clients’ information flow in customized projects; (2) proposing a visual indicator to measure and compare workflow variations created by different customization strategies; (3) suggesting tactics that can be incorporated in full-customization strategies to reduce workflow variations; and (4) critically examining the mass customization theoretical background and its role in addressing construction problems.

There have been limited studies that have examined the relationship between quality and safety performance. In addressing this issue, this paper examines a project-lifecycle safety, quality, and environment (SQE) strategy, which was supported by a behavioral and accountability initiative, and its effect on reducing the number of safety incidents in an AU$375 million program alliance that delivered 129 water infrastructure projects over a 5-year period. While the SQE program proved to be effective, the alliance also recognized that rework had become an issue and thus developed a rework prevention program as part of their continuous improvement process. Thus, this paper describes the nature of these programs and provides statistical analysis to demonstrate their combined effectiveness in reducing safety incidents. It is suggested that the alliance’s approach and experiences in simultaneously addressing quality and safety provide learning opportunities for those organizations that are seeking to ameliorate the performance of the projects that they are charged with delivering.