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A special issue of Buildings (ISSN 2075-5309). This special issue belongs to the section "Construction Management, and Computers & Digitization".

Deadline for manuscript submissions: closed (30 March 2022) | Viewed by 57440

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Special Issue Editor

Dr. Maziar Yazdani

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School of Civil and Environmental Engineering, The University of New South Wales, Sydney, NSW 2052, Australia
Interests: scheduling; artificial neural network; optimization techniques; machine learning; production planning; disaster management; construction management; engineering optimisation; artificial intelligence; metaheuristic algorithms
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Special Issue Information

Dear Colleagues,

The frequency, magnitude, and severity of natural and human-made disasters has steadily increased with substantial immediate and long-term impacts on communities, economies, and built environments. Hundreds of thousands of fatalities and billions of dollars in economic damage highlight the importance of studies in the field of disaster risk management (DRM) to reduce the negative impacts of disasters. Although disaster risk management plans and strategies have evolved in recent years, the development of disaster risk management literature in the construction and built environment context has not been sufficiently explored.

To this end, we invite researchers from a wide range of field of research to submit their original studies to this Special Issue to address this gap. This line of research is scarce and needs to be conducted in responding to new emerging challenges such as pandemics, floods, earthquakes, and storms. The publications can include but are not limited to theoretical and applied research investigating the following topics:

Disaster recovery project management;
Project management methodology for post-disaster reconstruction;
Construction waste management in disasters;
Disaster response strategies in the built environment;
Disaster-resilient built environment;
Bridging gap between project management knowledge areas and disaster risk management (DRM) phases;
Different strategies and plan for mitigation, preparedness, response, and recovery;
Construction management in response to disasters;
Construction management and mitigation activities;
Resilience against disasters;
Mathematical and simulation modeling;
Exact and approximate optimization techniques;
Artificial intelligence in managing challenges;
Post-disaster reconstruction supply chain.

Dr. Maziar Yazdani
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Buildings is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

disaster recovery project management
project management methodology for post- disaster reconstruction
construction waste management in disasters
disaster response strategies in the built environment
disaster- resilient built environment
bridging gap between project management knowledge areas and disaster risk management (DRM) phases
different strategies and plan for mitigation, preparedness, response, and recovery
construction management in response to disasters
construction management and mitigation activities
resilience against disasters
mathematical and simulation modelling
exact and approximate optimization techniques
artificial intelligence in managing challenges
post-disaster reconstruction supply chain

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Published Papers (10 papers)

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Research

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30 pages, 4918 KiB

Open AccessArticle

Selecting an Appropriate Configuration in a Construction Project Using a Hybrid Multiple Attribute Decision Making and Failure Analysis Methods

by Ali Beiki Ashkezari, Mahsa Zokaee, Amir Aghsami, Fariborz Jolai and Maziar Yazdani

Buildings 2022, 12(5), 643; https://doi.org/10.3390/buildings12050643 - 11 May 2022

Cited by 11 | Viewed by 3434

Abstract

To successfully complete a project, selecting the most appropriate construction method and configuration is critical. There are, however, plenty of challenges associated with these complex decision-making processes. Clients require projects with the desired cost, time, and quality, so contractors should trade-off project goals through project configuration. To address this problem, in this study, an integrated FTA-DFMEA approach is proposed that implements the integrated AHP-TOPSIS method to improve construction project configuration. The proposed approach applies quality management techniques and MADM methods concurrently for the first time to improve construction project configuration considering project risks, costs and quality. At first, the Client’s requirements and market feedback are considered to identify potential failures in fulfilling project goals, and an integrated AHP-TOPSIS is used to select the most critical potential failure. Then fault tree analysis is used to indicate minimal paths. An inverse search in the operational model is performed to determine relevant tasks and identify defective project tasks based on WBS. Afterward, failure modes and effect analysis are applied to identify failure modes, and an integrated AHP-TOPSIS is used to rank failure modes and select the most critical one. Then Corrective actions are carried out for failure modes based on their priority, and project configuration is improved. This study considers construction resource suppliers with different policies, delivery lead times, warranty costs, and purchasing costs. Moreover, redundancy allocation and different configuration systems such as series and parallel are taken into account based on the arrangement and precedence of tasks. Finally, a case study of a building construction project is presented to test the viability of the proposed approach. The results indicate that the proposed approach is applicable as a time-efficient and powerful tool in the improvement of construction project configuration, which provides the optimal output by considering various criteria with respect to the client’s requirements and contractor’s obligations. Moreover, the algorithm provides various options for the contractor to improve the implementation of construction projects and better respond to challenges when fulfilling project goals. Full article

(This article belongs to the Special Issue Construction Management and Disaster Risk Management)

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15 pages, 1053 KiB

Open AccessArticle

Influence of Organisational Culture on Total Quality Management Implementation in the Australian Construction Industry

by Carla Coelho, Mohammad Mojtahedi, Kamyar Kabirifar and Maziar Yazdani

Buildings 2022, 12(4), 496; https://doi.org/10.3390/buildings12040496 - 16 Apr 2022

Cited by 15 | Viewed by 7022

Abstract

This study explores the relationship between organisational culture and total quality management (TQM) implementation in Australia, with the purpose of identifying the particular culture that dominants the Australian construction industry, and distinguishing which cultures determine the successful implementation of TQM. Although the application of the competing values framework (CVF) for evaluating organisational culture (OC) in the construction industry has been studied by some scholars, research into OC and its impact on TQM procedures in connection to the CVF in project-based industries such as construction has received less attention. Thus, this research intends to determine the relationship between OC and TQM regarding the CVF in the Australian construction industry. The research methodology used the validated organisational culture assessment instrument (OCAI) CVF to frame OC, and TQM practices identified from the literature review. An online questionnaire was distributed through Qualtrics, whereby 42 valid responses representing various construction organisations in Australia were analysed through IBM SPSS Statistics 26 through endorsing k-means cluster analysis, and analysis of variance. The findings support that Australian construction organisations are dominated by the market and external focused cultures according to the CVF of organisational classification. Furthermore, the findings acknowledge that organisations that are dominated by hierarchical cultural characterises could provide an unfavourable environment for the successful implementation of TQM. Whilst an organisation that obtains a mix of cultures, specifically with the adhocracy and market cultures dominating could provide a favourable environment for the successful implementation of TQM. Full article

(This article belongs to the Special Issue Construction Management and Disaster Risk Management)

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28 pages, 4194 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Post-Disaster Temporary Shelters Distribution after a Large-Scale Disaster: An Integrated Model

by Zahra Gharib, Reza Tavakkoli-Moghaddam, Ali Bozorgi-Amiri and Maziar Yazdani

Buildings 2022, 12(4), 414; https://doi.org/10.3390/buildings12040414 - 29 Mar 2022

Cited by 21 | Viewed by 5260

Abstract

This paper develops an integrated model for the distribution of post-disaster temporary shelters after a large-scale disaster. The proposed model clusters impacted areas using an Adaptive Neuro-Fuzzy Inference System (ANFIS) method and then prioritizes the points of clusters by affecting factors on the route reliability using a permanent matrix. The model’s objectives are to minimize the maximum service time, maximize the route reliability and minimize the unmet demand. In the case of ground relief, the possibility of a breakdown in the vehicle is considered. Due to the disaster’s uncertain nature, the demands of impacted areas are considered in the form of fuzzy numbers, and then the equivalent crisp counterpart of the non-deterministic is made by Jimenez’s method. Since the developed model is multi-objective, the Non-dominated Sorting Genetic Algorithm (NSGA-II) and Multi-Objective Firefly Algorithm (MOFA) are applied to find efficient solutions. The results confirm higher accuracy and lower computational time of the proposed MOFA. The findings of this study can contribute to the growing body of knowledge about disaster management strategies and have implications for critical decision-makers involved in post-disaster response projects. Furthermore, this study provides valuable information for national decision-makers in countries with limited experience with disasters and where the destructive consequences of disasters on the built environment are increasing. Full article

(This article belongs to the Special Issue Construction Management and Disaster Risk Management)

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26 pages, 22771 KiB

Open AccessArticle

Prioritizing Post-Disaster Reconstruction Projects Using an Integrated Multi-Criteria Decision-Making Approach: A Case Study

by Zahra Mohammadnazari, Mobina Mousapour Mamoudan, Mohammad Alipour-Vaezi, Amir Aghsami, Fariborz Jolai and Maziar Yazdani

Buildings 2022, 12(2), 136; https://doi.org/10.3390/buildings12020136 - 27 Jan 2022

Cited by 34 | Viewed by 5506

Abstract

As the destructive impacts of both human-made and natural disasters on societies and built environments are predicted to increase in the future, innovative disaster management strategies to cope with emergency conditions are becoming more crucial. After a disaster, selecting the most critical post-disaster reconstruction projects among available projects is a challenging decision due to resource constraints. There is strong evidence that the success of many post-disaster reconstruction projects is compromised by inappropriate decisions when choosing the most critical projects. Therefore, this study presents an integrated approach based on four multi-criteria decision-making (MCDM) techniques, namely, TOPSIS, ELECTRE III, VIKOR, and PROMETHEE, to aid decision makers in prioritizing post-disaster projects. Furthermore, an aggregation approach (linear assignment) is used to generate the final ranking vector since various methods may provide different outcomes. In the first stage, 21 criteria were determined based on sustainability. To validate the performance of the proposed approach, the obtained results were compared to the results of an artificial neural network (ANN) algorithm, which was applied to predict the projects’ success rates. A case study was used to assess the application of the proposed model. The obtained results show that in the selected case, the most critical criteria in post-disaster project selection are quality, robustness, and customer satisfaction. The findings of this study can contribute to the growing body of knowledge about disaster management strategies and have implications for key stakeholders involved in post-disaster reconstruction projects. Furthermore, this study provides valuable information for national decision makers in countries that have limited experience with disasters and where the destructive consequences of disasters on the built environment are increasing. Full article

(This article belongs to the Special Issue Construction Management and Disaster Risk Management)

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25 pages, 4958 KiB

Open AccessEditor’s ChoiceArticle

Off-Site Construction Three-Echelon Supply Chain Management with Stochastic Constraints: A Modelling Approach

by Samira Al-Sadat Salari, Hediye Mahmoudi, Amir Aghsami, Fariborz Jolai, Soroush Jolai and Maziar Yazdani

Buildings 2022, 12(2), 119; https://doi.org/10.3390/buildings12020119 - 25 Jan 2022

Cited by 33 | Viewed by 5836

Abstract

Off-site construction is becoming more popular as more companies recognise the benefits of shifting the construction process away from the construction site and into a controlled manufacturing environment. However, challenges associated with the component supply chain have not been fully addressed. As a result, this study proposes a model for three-echelon supply chain supply management in off-site construction with stochastic constraints. In this paper, multiple off-site factories produce various types of components and ship them to supplier warehouses to meet the needs of the construction sites. Each construction site is directly served by a supplier warehouse. The service level for each supplier warehouse is assumed to be different based on regional conditions. Because of the unpredictable nature of construction projects, demand at each construction site is stochastic, so each supplier warehouse should stock a certain number of components. The inventory control policy is reviewed regularly and is in (R, s, S) form. Two objectives are considered: minimising total cost while achieving the desired delivery time for construction sites due to their demands and balancing driver workloads during the routeing stage. A grasshopper optimisation algorithm (GOA) and an exact method are used to solve this NP-hard problem. The findings of this study contribute new theoretical and practical insights to a growing body of knowledge about supply chain management strategies in off-site construction and have implications for project planners and suppliers, policymakers, and managers, particularly in companies where an unplanned supply chain exacerbates project delays and overrun costs. Full article

(This article belongs to the Special Issue Construction Management and Disaster Risk Management)

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17 pages, 4514 KiB

Open AccessArticle

Thermal Comfort Performances of Temporary Shelters Using Experimental and Computational Assessments

by Alex Yong Kwang Tan and Chi-Keong Tan

Buildings 2021, 11(12), 655; https://doi.org/10.3390/buildings11120655 - 17 Dec 2021

Cited by 3 | Viewed by 3359

Abstract

This paper examines the thermal comfort of temporary shelters under Taiwan’s subtropical summer conditions. The temperature within the tent was higher compared to the standard configuration of the temporary shelter, but its relative humidity was lower. During the time period 09:30 to 14:30, temperatures at the center of the tent at positions 0.10 m, 1.10 m and 1.70 m above ground were 3.1 °C, 5.5 °C and 6.0 °C higher, respectively, than the average ambient temperature of 36.3 °C. However, temperatures for the standard configuration at similar central positions of 0.10 m, 1.10 m and 1.70 m above ground were 1.2 °C, 0.5 °C and 0.7 °C lower, respectively, than the same average ambient. In the afternoon, the standard configuration (PMV of 3.14 and PPD of 100) performed better than the tent (PMV of 5.03 and PPD of 100), although neither achieved thermal comfort. Various experimental configurations showed that double layers of roof lowered temperatures, but the thermal comfort (PMV of 3.32 and PPD of 100) remained unchanged. Various computational configurations showed that closing the door and one window and installing a mechanical fan of average speed 2.75 m/s lowered the temperature and increased the air speed to achieve thermal comfort with PMV and PPD values of 1.49 and 50, respectively. Full article

(This article belongs to the Special Issue Construction Management and Disaster Risk Management)

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19 pages, 1348 KiB

Open AccessArticle

Comprehensive Success Evaluation Framework for Socio-Natural Disaster Recovery Projects

by Homa Bahmani and Wei Zhang

Buildings 2021, 11(12), 647; https://doi.org/10.3390/buildings11120647 - 14 Dec 2021

Cited by 7 | Viewed by 3303

Abstract

There is an ample amount of studies attempting to evaluate the success of recovery projects. However, they mostly focused on unilateral success indicators and ignored the continual lifespan and various stakeholders. This study has focused on addressing these obstacles by proposing a comprehensive success evaluation framework for recovery projects following socio-natural disasters through identifying the success dimensions and their effectual parameters. Triangulation of the results of quantitative and qualitative methods and the logic of qualitative comparative analysis were used to answer the research questions. System thinking and the concept of resiliency and sustainability, known as key performance indicators, structured the success measurements. The effectual elements on the success, critical success factors, were grouped according to the continuous life-cycle of these projects. Finally, the framework for success evaluation of socio-natural disaster recovery projects illustrates interactions among the deducted critical success factors and key performance indicators. The proposed framework may serve as more efficient guidelines to set and follow the recovery goals, comprehensively considering a wide range of stakeholders and long-term recovery. The results of this study can be subject to further research by using different methods to enhance the comprehensivity of the framework. The authors will conduct further research to verify the suggested framework by implementing case studies. Full article

(This article belongs to the Special Issue Construction Management and Disaster Risk Management)

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Review

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17 pages, 1331 KiB

Open AccessReview

Resilience in Infrastructure Systems: A Comprehensive Review

by Wenque Liu, Ming Shan, Sheng Zhang, Xianbo Zhao and Zhao Zhai

Buildings 2022, 12(6), 759; https://doi.org/10.3390/buildings12060759 - 2 Jun 2022

Cited by 16 | Viewed by 10727

Abstract

When encountering crisis events, systems, organizations, and people must react and handle these unpredictable events. Under these circumstances, important social functions and infrastructures must be restored or adapted as quickly as possible. This capacity refers to resilience. Although considerable research has been conducted on the resilience of infrastructure systems over the past years, a critical review of these studies remains lacking. Therefore, this study aims to bridge the knowledge gap by presenting a comprehensive review of infrastructure research conducted in the past decade, namely, from 2011 to 2021. On the basis of a systematic search, this study identified 222 journal articles investigating infrastructure resilience. A review of the identified papers revealed five research streams in the area of infrastructure resilience (IR), namely, the assessment of infrastructure resilience, improvement of infrastructure resilience, conceptualizing infrastructure resilience from various perspectives, factors influencing infrastructure resilience, and the prediction of infrastructure resilience. This study also presented some directions that future research can pursue. These directions include analyzing factors influencing infrastructure resilience based on simulation, assessing the resilience of green infrastructure, improving the resilience of interdependent infrastructure, and predicting the resilience of infrastructure based on empirical research. Full article

(This article belongs to the Special Issue Construction Management and Disaster Risk Management)

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19 pages, 1043 KiB

Open AccessReview

A Conceptual Framework for Implementing Lean Construction in Infrastructure Recovery Projects

by Mahyar Habibi Rad, Mohammad Mojtahedi, Michael J. Ostwald and Suzanne Wilkinson

Buildings 2022, 12(3), 272; https://doi.org/10.3390/buildings12030272 - 25 Feb 2022

Cited by 15 | Viewed by 5746

Abstract

Natural hazards can have substantial destructive impacts on the built environment. Providing effective services in disaster areas is heavily reliant on maintaining or replacing infrastructure; thus, post-disaster reconstruction of infrastructure has attracted growing attention. Due to the complex and dynamic nature of infrastructure recovery projects, contractor companies engaged in this work have typically experienced poor performance. Furthermore, from a commercial perspective, the post-disaster reconstruction environment is characterized by fierce competition and market uncertainty, challenging the organizational resilience of companies undertaking this work. One approach for improving contractor performance is the implementation of lean construction, but the literature lacks consensus on its capability to affect organizational resilience. To respond to this problem, a conceptual framework applicable for lean implementation in infrastructure, which explicitly addresses organizational resilience, is required for recovery projects. In parallel, contributing components to effective implementation of lean-recovery and supportive theories for justifying the conceptual framework must be identified. Consequently, this paper proposes a conceptual framework to implement lean practices for the enhancement of organizational resilience. The framework is developed using a systematic research method, wherein 110 research documents were discovered initially, and following processing, 18 relevant documents were identified and analyzed. Through this process, contingency and Transformation-Flow-Value (TFV) theories were identified as an appropriate foundation for a framework to implement lean construction in infrastructure recovery projects. Full article

(This article belongs to the Special Issue Construction Management and Disaster Risk Management)

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Other

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23 pages, 4181 KiB

Open AccessPerspective

An AI/ML-Based Strategy for Disaster Response and Evacuation of Victims in Aged Care Facilities in the Hawkesbury-Nepean Valley: A Perspective

by Hafiz Suliman Munawar, Mohammad Mojtahedi, Ahmed W. A. Hammad, Michael J. Ostwald and S. Travis Waller

Buildings 2022, 12(1), 80; https://doi.org/10.3390/buildings12010080 - 14 Jan 2022

Cited by 17 | Viewed by 4508

Abstract

The Hawkesbury-Nepean Valley, Australia’s longest coastal catchment, is spanned by a river system of more than 470 km, that runs from Goulburn to Broken Bay, covering a total area of over 2.2 million hectares. This region has remained prone to flood events, with considerable mortalities, economic impacts and infrastructural losses occurring quite regularly. The topography, naturally variable climatic conditions and the ‘bathtub’ effect in the region are responsible for the frequent flood events. In response, the Government at the national/federal, state and local level has focused on the design of efficient flood risk management strategies with appropriate evacuation plans for vulnerable communities from hospitals, schools, childcare and aged care facilities during a flood event. Despite these overarching plans, specialized response and evacuation plans for aged care facilities are critical to reducing the loss incurred by flood events in the region. This is the focus of this present paper, which reviews the history of flood events and responses to them, before examining the utilization of artificial intelligence (AI) techniques during flood events to overcome the flood risks. An early flood warning system, based on AI/Machine Learning (ML) strategy is being suggested for a timely decision, enhanced disaster prediction, assessment and response necessary to overcome the flood risks associated with aged care facilities within the Hawkesbury-Nepean region. A framework entailing AI/ML methods for identifying the safest route to the destination using UAV and path planning has been proposed for timely disaster response and evacuation of the residents of aged care facilities. Full article

(This article belongs to the Special Issue Construction Management and Disaster Risk Management)

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