Journal of Construction Engineering and Management

Payment default is a common complaint from contractors in the construction industry. Many regulative measures have been adopted in different jurisdictions to address such payment problems. Current research primarily takes an interpretative approach for conducting semantic analysis of these measures, reporting their applications, and comparing their implementation outcomes. This paper presents a comprehensive theoretical understanding of these issues, their sources/roots, and related measurements, and addresses them through gametric models. Working elements of regulative measures are demarcated as punishment of opportunistic payers, remedies for unpaid payees, and costs to parties in referring to remedies and realizing justice. Empirical evidence from an international literature review of protection measures and experiences of addressing payment arrears and from a survey in mainland China is provided to support the models. This framework is useful to researchers and professionals in complementing the current descriptive approach in investigating and understanding regulative measures that address payment problems. This understanding is also useful for lawmakers to accompany the current path-dependent approach in introducing and amending payment protection legislation, i.e., referring to similar measures in other jurisdictions where a mutual legislative origin is shared.

Activity production rates drive the development and accuracy of linear schedules. The nature of linear projects dictates an assortment of variables that affect each activity’s production rate. The purpose of this research was to expand the capabilities of linear scheduling to account for variance in production rates when and where the variance occurs and to enhance the visual capabilities of linear scheduling. This new linear scheduling model, a linear scheduling model with varying production rates (${\mathrm{LSM}}_{\mathrm{VPR}}$), has two objectives. The first is to outline a framework to apply changes in production rates when and where they occur along the horizontal alignment of the project. The second objective is to illustrate the difficulty or ease of construction through the time-location chart. This research showed that the changes in production rates because of time and location can be modeled for use in predicting future construction projects. Using the concept of working windows, ${\mathrm{LSM}}_{\mathrm{VPR}}$ allows the scheduler to develop schedule durations on the basis of minimal project information. The model also allows the scheduler to analyze the impact of various routes or start dates for construction and the corresponding impact on the schedule. The graphical format allows the construction team to visualize the obstacles in the project when and where they occur by using a new feature called the activity performance index (API). This index is used to shade the linear scheduling chart by time and location with the variation in color indicating the variance in predicted production rate from the desired production rate.

Schedule delay is a common construction dispute. For analyzing schedule delays, a previous study had proposed an academic analysis method, the “isolated collapsed but-for” (ICBF) method. However, because many construction projects involve numerous complex activities, the procedure of using the ICBF method for schedule delay analysis is time-consuming. Therefore, this study used Microsoft Visual Basic for Applications (VBA) language and spreadsheet techniques to develop an Excel-based program for rapid delay analysis rather than manual calculation. A case study confirmed that the program automatically produces analytical results with only common delay documents (as-planned and as-built schedules and identified delay events). Compared with previous studies, schedule analysts can obtain analysis results quickly and correctly. Research results provide not only a convenient tool for schedule delay analysis but also a guide to computerize various academic delay analysis methods in the future.

The costs of construction injuries can have a substantial impact on the financial success of construction organizations and increase the overall costs of construction up to 15%. Following the Occupational Safety and Health Act of 1970, construction firms began to implement a variety of management techniques to reduce the frequency of injuries. Although these strategies decrease the cost of injuries, they consume time and other significant resources. Thus, it is imperative for construction organizations to objectively evaluate the cost-benefit of investments in injury prevention through formal and robust processes. This paper presents a risk-based framework that can be used to evaluate the incremental return on investment of a series of investments in highly effective injury prevention strategies. The framework was developed using foundational risk quantification and analysis techniques and is illustrated using a hypothetical case study that is based on archival data published by United States government agencies. The conclusion of this study is that the optimal investment strategy can be identified through a formal analysis and that optimization depends on the frequency and cost of injuries, the sequence in which the specific injury prevention techniques are implemented, the risk mitigated by each strategy, and the organization’s attitude toward acceptable risk.

Bridges are principal and vital transportation structures. If risk management is not considered in bridge construction projects, objectives cannot be delivered on time, on budget, or with suitable quality results. Risk data set sizes and experts’ judgments are not usually sufficient for analyzing significant risks in bridge construction projects; moreover, the statistical distributions for risk parameter estimates are usually unknown. Standard parametric statistical techniques cannot provide appropriate solutions for cases with small data sets or unknown distributions. This paper proposes a new hybrid approach by using a nonparametric resampling technique and interval computations for risk analysis, in particular, for bridge construction projects. Bootstrap techniques produce more accurate inferences for comparing parametric techniques and are an alternative when the underlying parametric assumptions are not considered. Increasingly, because of the complexity and uncertainty in decision making at bridge projects, it is easier or more natural to provide interval values for parts or all of decision-making judgments. Furthermore, the goal of reducing standard deviations for both risk probability and risk impact compared with the conventional approach is another conclusion of this paper. The proposed approach is applied to a case in Iran to show the validity of the approach.

This paper proposes a fuzzy preference relations consensus (FPRC) approach that helps owners and contractors reach consensus on their responsibilities and reduce conflicts in shared tasks. A fuzzy similarity consensus (FSC) model was developed to aggregate experts’ opinions on roles and responsibilities in the owner managing contractor (OMC) project delivery system. The FSC model categorized 324 generic OMC tasks into three responsibility task lists: owner, contractor, and shared. In a consensus-reaching process, the FPRC approach is applied to shared tasks, where expert opinions on responsibility conflict are expressed, to achieve an aggregated responsibility decision for each task. Experts compare the three responsibility alternatives in pairs by using linguistic preferences, defined on a fuzzy preference scale, to select a preferred responsibility alternative for each of the conflicting tasks. A computed linguistic consensus degree guides the experts on their level of consensus in every round of the process. The quality of experts is defined with a fuzzy expert system–determined importance weight factor for each expert. The FPRC approach is relevant to the construction industry, as it incorporates consistency in decision making by allowing experts to measure and reach an adequate level of consensus linguistically when deciding on responsibilities. The proposed approach provides a method of reducing conflicts in the assignment of task responsibility between the owner and its contractors as early as the project initiation phase; thus, the project teams can concentrate on the work to be done rather than deal with responsibility conflicts during project execution.

As construction projects get larger and more complex, it has become clear that no single entity can have complete knowledge of or the abilities to handle all matters. Therefore, collaborative practices among heterogeneous individuals, which are temporarily congregated to perform a project, are required to accomplish common project objectives. On the basis of this premise, this paper introduces an agent-based simulation of the evolution of collaboration within interorganizational networks of construction project teams from game theory and social network perspectives. The simulation confirmed that the fewer individuals are familiar with others in the network, and thereby aware of networks they are involved in, the more time it takes for networks to reach stable states. It was also found that the tendency of cohesion increased as the effort to form relationships with outside partners rose. Furthermore, the results indicated that the more effort needed to form relationships with those from other organizations, the less efficient the networks were. The model of organizational processes developed in this study explicitly incorporated a representation of individual decision makers and their interactions from both active and dynamic standpoints. This model represents a contribution to enhancing the understanding of the affect of organizational aspects on project management and to facilitating the development of tools for investigating organizations in construction.