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The purpose of this paper is to explore the challenges of transitional shelter provision for internally displaced persons (IDPs) in urban informal settlements. While there has been considerable research on postdisaster transitional shelters, less is known on shelters for IDPs in urban informal settlements.

A case study is presented based on field research at the communities in Olaria and City in São Paulo, Brazil. Collection of data included personal communication with the dwellers, surveys and interviews with representatives from Techo, one of the few organizations that provide transitional shelters for IDPs. A review of documents regarding the construction, design and users' adaptation of transitional shelter was also undertaken. Data was analyzed using thematic analysis.

The study found that Techo's program impacts positively on the nonphysical aspects of shelter, such as physical and mental health, security, household responsibilities and community participation. However, Techo's transitional shelter for IDPs in urban informal settlements and most postdisaster transitional shelters share similar problems. These programs respond to the needs of a small proportion of the affected populations with shelters of minimum quality and low durability.

This paper is limited to a single case study of the NGO Techo and further case study research is recommended to further develop and validate the study results in other urban development contexts.

This research contributes to describing and understanding the context and the provision of transitional shelters to IDPs in urban informal settlements and impacts in the community. With increasing numbers of IDPs settling in urban informal settlements in many parts of the world, this paper is valuable to policymakers, NGOs and researchers operating in this field to facilitate community development.

Project selection is a critical decision for any organization seeking to commission a large-scale construction project. Project selection is a complex multi-criteria decision-making problem with significant uncertainty and high risks. Fuzzy set theory has been used to address various aspects of project uncertainty, but with key practical limitations. This study aims to develop and apply a novel Pythagorean fuzzy sets (PFSs) approach that overcomes these key limitations.

The study is particular to complex project selection in the context of increasing interest in resilience as a key project selection criterion. Project resilience is proposed and considered in the specific situation of a large-scale construction project selection case study. The case study develops and applies a PFS approach to manage project uncertainty. The case study is presented to demonstrate how PFS is applied to a practical problem of realistic complexity. Working through the case study highlights some of the key benefits of the PFS approach for practicing project managers and decision-makers in general.

The PFSs approach proposed in this study is shown to be scalable, efficient, generalizable and practical. The results confirm that the inclusion of last aggregation and last defuzzification avoids the potentially critical information loss and relative lack of transparency. Most especially, the developed PFS is able to accommodate and manage domain expert expressions of uncertainty that are realistic and practical.

The main novelty of this study is to address project resilience in the form of multi-criteria evaluation and decision-making under PFS uncertainty. The approach is defined mathematically and presented as a six-step approach to decision-making. The PFS approach is given to allow multiple domain experts to focus more clearly on accurate expressions of their agreement and disagreement. PFS is shown to be an important new direction in practical multi-criteria decision-making methods for the project management practitioner.

Currently there is no analysis of the development of disaster risk management literature in the construction and built environment context, the changes in its research paradigms over time and the role of different key players in the advance of its current body of knowledge. This study aims to address that gap by investigating the longitudinal data of disaster risk management literature published over the past three decades.

A social network analysis approach is used in this study to show the overall development of the field and specifically the impact of research collaborations between different organisations and countries on research productivity.

The results indicate that the focus of disaster risk management research in the built environment context is heavily biased towards reactive strategies (response and recovery) over proactive strategies (mitigation and preparedness). The findings also demonstrate that collaboration between disaster risk management researchers has a significant influence on their research productivity.

The findings from this study should be of value to researchers, policymakers and academic strategists. This study for the first time shows the ability of the social networks paradigm to reveal frailties in research connections in the field of disaster risk management in construction and built environment and highlights where networking strategies are needed.

The purpose of this study is twofold: first, to identify major project management (PM) complexities in principal construction contracting; and second, to study the contribution of project management offices (PMOs) to addressing such complexities.

A two-stage research design was adopted through a structured literature review (SLR) and a qualitative survey study.

The two-stage study resulted in mapping out the contribution of 10 functional areas to 15 complexity factors that were retrieved from the literature and categorized using the TOE (technical, organizational and environmental) framework. Six outcomes including (1) facilitated processes, (2) improved decisions, (3) improved coordination, (4) enhanced alignment, (5) addressed uncertainties and (6) integrated oversight were identified that describe how PMOs can contribute to tackling complexities.

Similar to other qualitative studies, this study has some limitations in terms of the replicability of results. Regarding the exploratory nature of this study to explain the contribution of PMO to complexity, further quantitative surveys can be conducted using a larger sample to statistically examine the significance of proposed relations between capabilities and complexity factors.

This study provides an understanding of the contribution of PMOs to tackling ever-increasing complexities embedded in construction contracting. The authors suggest requirements to be considered by professionals toward overcoming such complexities.

Although prior studies have separately investigated PMO functions and PM complexities, this study explores the link between these two spheres to discuss one important application of PMO in this context.

In disaster risk reduction (DRR), it is important to realise stakeholders’ approaches against disasters in the built environment. The purpose of this paper is to explore why stakeholders take proactive and/or reactive approaches in DRR.

Using a review of existent literature, this work scrutinises disaster theories and their applications in the built environment to develop a theoretical framework for perceiving stakeholders’ proactive and/or reactive approaches in DRR.

Stakeholders’ organisational attributes – power, legitimacy and urgency – and decision-making paradigms – value maximisation and intuitive reasoning – are fundamental factors affecting stakeholders’ approaches against disasters. Power and legitimacy of stakeholders result in a proactive approach if stakeholders consider value maximisation paradigm in their decision-making process. Powerful and legitimate stakeholders may take reactive approaches because of intuitive reasoning paradigm. Stakeholders may shift from a reactive to proactive approach and vice versa based on the combination of urgency attribute and decision-making paradigms.

It is essential to consider the classification of respective stakeholders in applying the idea of this paper. Furthermore, this paper does not attempt to validate the proposed theoretical framework empirically, but it combines stakeholder and decision-making theories by which this could be undertaken.

Little attention has been paid to systematic theorising in managing stakeholders’ approaches against disasters. Furthermore, many researchers have focused on similar underlying theories and heuristics in the context of DRR. Thus, this paper introduces a theoretical framework to examine stakeholders’ proactive and/or reactive approaches in the built environment, by synthesising stakeholder and decision-making theories.

The purpose of this paper is to investigate the literature on resilience factors applied to post-disaster reconstruction projects and to develop a guiding framework to assist in their strategic selection and application.

A systematic review was undertaken on the literature’s account in four major bibliographic databases to elicit resilience factors contributing to improving post-disaster reconstruction projects' robustness. Through summative content analysis and open-coding of research outputs over the past decade, the factors identified informed the development of a conceptual framework that can significantly impact the built environment’s resilience development process.

The review found 24 resilience factors open-coded into five criteria groups: governance, innovations, reconstruction approaches, resource management and stakeholder expectations. While these factors have influenced reconstruction projects, the recently increased participation of clients and end-users in construction management accentuates their strategic selection and applications.

The research focused on English language articles; therefore, any claim to a comprehensive resilience factors listing can be amiss. The framework provides a platform for developing clear measurement indicators for allocating project resources and determining resilience deficiencies.

Results confirm the designs and assessment of a resilient built environment extends beyond the traditional structural characteristics, but includes the ability of the integrated network of buildings and infrastructure to support the continuous delivery of the community’s social and economic services in normal and post-disaster settings.

The review is very specific as it attempts to develop a novel conceptual framework for guiding developers and practitioners in the application of resiliency to post-disaster reconstruction projects.

Reducing wear of undercarriage track propulsion systems used in heavy construction equipment decreases the maintenance costs and increases the equipment's life. Therefore, understanding key factors that affect the wear rate is critical. This study is an attempt to predict undercarriage wear.

This research analyzes a sample of track-type dozers in the eastern half of North Carolina (NC), USA. Sand percentage in the soil, precipitation level, temperature, machine model, machine weight, elevation above sea level and work type code are considered as factors influencing the wear rate. Data are comprised of 353 machines. Machine model and work code data are categorical. Sand percentage, elevation, machine weight, average temperature and average precipitation are continuous. ANOVA is used to test the hypothesis.

The study found that only sand percentage has a significant impact on the wear rate. Consequently, a regression model is developed.

The regression model can be used to predict undercarriage wear and bushing life in soils with different sand percentages. This is demonstrated using a hypothetical scenario for a construction company.

This work is useful in managing maintenance intervals of undercarriage tracks and in bidding construction jobs while predicting machine operating expense for each specific job site soil makeup.

Cement as one of the major components of construction activities, releases a tremendous amount of carbon dioxide (CO₂) into the atmosphere, resulting in adverse environmental impacts and high energy consumption. Increasing demand for CO₂ consumption has urged construction companies and decision-makers to consider ecological efficiency affected by CO₂ consumption. Therefore, this paper aims to develop a method capable of analyzing and assessing the eco-efficiency determining factor in Iran’s 22 local cement companies over 2015–2019.

This research uses two well-known artificial intelligence approaches, namely, optimization data envelopment analysis (DEA) and machine learning algorithms at the first and second steps, respectively, to fulfill the research aim. Meanwhile, to find the superior model, the CCR model, BBC model and additive DEA models to measure the efficiency of decision processes are used. A proportional decreasing or increasing of inputs/outputs is the main concern in measuring efficiency which neglect slacks, and hence, is a critical limitation of radial models. Thus, the additive model by considering desirable and undesirable outputs, as a well-known DEA non-proportional and non-radial model, is used to solve the problem. Additive models measure efficiency via slack variables. Considering both input-oriented and output-oriented is one of the main advantages of the additive model.

After applying the proposed model, the Malmquist productivity index is computed to evaluate the productivity of companies over 2015–2019. Although DEA is an appreciated method for evaluating, it fails to extract unknown information. Thus, machine learning algorithms play an important role in this step. Association rules are used to extract hidden rules and to introduce the three strongest rules. Finally, three data mining classification algorithms in three different tools have been applied to introduce the superior algorithm and tool. A new converting two-stage to single-stage model is proposed to obtain the eco-efficiency of the whole system. This model is proposed to fix the efficiency of a two-stage process and prevent the dependency on various weights. Converting undesirable outputs and desirable inputs to final desirable inputs in a single-stage model to minimize inputs, as well as turning desirable outputs to final desirable outputs in the single-stage model to maximize outputs to have a positive effect on the efficiency of the whole process.

The performance of the proposed approach provides us with a chance to recognize pattern recognition of the whole, combining DEA and data mining techniques during the selected period (five years from 2015 to 2019). Meanwhile, the cement industry is one of the foremost manufacturers of naturally harmful material using an undesirable by-product; specific stress is given to that pollution control investment or undesirable output while evaluating energy use efficiency. The significant concentration of the study is to respond to five preliminary questions.

This study aims to examine the reuse of plastic and fly ash (FA) to improve the soil and achieve sustainable development goals.

Sand from the Anzali port was reinforced with Geopet (GP) and stabilized with FA plus 3% sodium hydroxide. The GP was placed in FA-stabilized soil and the California bearing ratio (CBR), and unconfined compressive strength (UCS) tests were performed on samples at the optimum moisture content.

The results showed that the improvement in the optimum CBR was 174.9%. The UCS increased 15.25% and 48.65% in soil reinforced with three layers of GP plus 15% FA over those containing 10% and 5% FA, respectively. Additionally, the current analysis used response surface methodology (RSM) to investigate the impact of FA percentage, GP layers and their interaction on CBR. The results highlight the efficacy of the used RSM model, as evidenced by the significantly low p-value (<0.0001).

This demonstrates the suitability and effectiveness of RSM for evaluating CBR in this scientific study.

The purpose of this study is to present a new failure mode and effects analysis (FMEA) approach based on fuzzy multi-criteria decision-making (MCDM) methods and multi-objective programming model for risk assessment in the planning phase of the oil and gas construction projects (OGCP) in Iran.

This research contains multiple steps. First, 19 major potential health and safety executive (HSE) risks in OGCP were classified into six categories with the Delphi method. These factors were distinguished by the review of project documentation, checklist analysis and consulting with experts. Then, using the fuzzy SWARA method, the authors calculated the weights of major HSE risks. Subsequently, FMEA and PROMETHEE approaches were used to identify the priority of main risk factors. Eventually, a binary multi-objective linear programming approach was developed to select the risk response strategies, and an augmented e-constraint method (AECM) was used.

Regarding the project triple well-known constraints of time, cost and quality, which organizations usually confront, the HSE risks of OGCP were identified and prioritized. Also, the appropriate risk response strategies were also suggested to the managers to be adopted regarding the situations.

The present research points at the HSE risks’ assessment integrating the fuzzy FMEA, step-wise weight assessment ratio analysis and PROMETHEE techniques with the AECM. Further to the authors’ knowledge, the quantitative assessment of the HSE risks of OGCP has not been done using the combination of the fuzzy FMEA, MCDM and AECMs.