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The regular occurrence of natural disasters elevates the need for an effective method to measure organizational preparedness in responding to the adverse impact of disasters. In this context, this paper presents a new decision support model to assess organizational disaster preparedness using both subjective and objective disaster preparedness criteria in a multi-criteria decision-making context.

The statistical variance method is integrated with the proximity value index (PVI) technique to determine priority scores in order to rank organizational disaster readiness.

The results of applying the integrated model developed herein enable decision-makers to make informed decisions for assigning priority ranking of organizational disaster preparedness in a simpler and more efficient way.

Human resource is the most impacting criterion affecting hospital preparedness in undertaking action to cure disaster victims.

This paper offers an exemplar of a simple and efficient decision-making process considering the subjectivity associated with decision-making as well as the objectivity of data used for determining the priority ranking of organizational disaster preparedness.

Integrating statistical variance method with the PVI technique is novel and it has not been presented in previous studies. In fact, this study is the first to integrate both methods for selecting the priority ranking of organizational disaster preparedness.

The overall objective of this study is envisaged to provide decision makers with actionable insights and access to multi-risk maps for the most in-danger stave churches (SCs) among the existing 28 churches at high spatial resolution to better understand, reduce and mitigate single- and multi-risk. In addition, the present contribution aims to provide decision makers with some information to face the exacerbation of the risk caused by the expected climate change.

Material and data collection started with the consultation of the available literature related to: (1) SCs' conservation status, (2) available methodologies suitable in multi-hazard approach and (3) vulnerability leading indicators to consider when dealing with the impact of natural hazards specifically on immovable cultural heritage.

The paper contributes to a better understanding of place-based vulnerability with local mapping dimension also considering future threats posed by climate change. The results highlight the danger at which the SCs of Røldal, in case of floods, and of Ringebu, Torpo and Øye, in case of landslide, may face and stress the urgency of increasing awareness and preparedness on these potential hazards.

The contribution for the first time aims to homogeneously collect and report all together existing spread information on architectural features, conservation status and geographical attributes for the whole group of SCs by accompanying this information with as much as possible complete 2D sections collection from existing drawings and novel 3D drawn sketches created for this contribution. Then the paper contributes to a better understanding of place-based vulnerability with local mapping dimension also considering future threats posed by climate change. Then it highlights the danger of floods and landslides at which the 28 SCs are subjected. Finally it reports how these risks will change under the ongoing impact of climate change.

This paper covers the development of a novel defect model for concrete highway bridges. The proposed defect model is intended to facilitate the identification of bridge’s condition information (i.e. defects), improve the efficiency and accuracy of bridge inspections by supporting practitioners and even machines with digitalised expert knowledge, and ultimately automate the process.

The research design consists of three major phases so as to (1) categorise common defect with regard to physical entities (i.e. bridge element), (2) establish internal relationships among those defects and (3) relate defects to their properties and potential causes. A mixed-method research approach, which includes a comprehensive literature review, focus groups and case studies, was employed to develop and validate the proposed defect model.

The data collected through the literature and focus groups were analysed and knowledge were extracted to form the novel defect model. The defect model was then validated and further calibrated through case study. Inspection reports of nearly 300 bridges in China were collected and analysed. The study uncovered the relationships between defects and a variety of inspection-related elements and represented in the form of an accessible, digitalised and user-friendly knowledge model.

The contribution of this paper is the development of a defect model that can assist inexperienced practitioners and even machines in the near future to conduct inspection tasks. For one, the proposed defect model can standardise the data collection process of bridge inspection, including the identification of defects and documentation of their vital properties, paving the path for the automation in subsequent stages (e.g. condition evaluation). For another, by retrieving rich experience and expert knowledge which have long been reserved and inherited in the industrial sector, the inspection efficiency and accuracy can be considerably improved.

Despite striving for resilience and a sustainable urban future, European cities face a multitude of crisis caused by both natural and human-induced risks. This paper asks two key questions: How have cities experienced and managed crises situations they encountered? and What are the plans and actions for embedding sustainability at a local level within a clear decision-making structure? Hence, it aims to examine urban resilience in the context of urban crisis and the associated health concerns that took place because of crisis situations, while identifying sustainable urban development initiatives and strategies that were conceived and implemented beyond crisis.

An evidence-based analytical approach is undertaken following two lines of inquiry. The first is case-based and identifies 11 cities that have experienced crisis situations and a further 10 cities that have instigated urban resilience strategies. The second is theme-based and engages with identifying strategies relevant to sustainable urban development at city and project levels. The outcomes of the two lines of inquiry are verified by mapping the lessons learned from the analysis to recent international guidance and a further co-visioning workshop with 6 experts.

The evidence-based analysis reveals key lessons which were classified under two primary types of findings: (a) lessons learned for a future urban resilience resulting from the 1st line of Inquiry (case-based) and (b) lessons learned for a future sustainable urban development resulting from the 2nd line of inquiry (theme-based). The verified lessons provide four areas that can be utilised as key priorities for future urban resilience and sustainable urban development including (a) Governance, effective communication, and decision making for city resilience and urban sustainability; (b) the social dimension of resilience and participatory practices for sustainable urban development; (c) from implicit strategies for health to positive impact on health; and (d) diversification of initiatives and localisation of sustainable development endeavours.

There is always limitation on what a bibliometrics analysis can offer in terms of the nature of evidence and the type of knowledge generated from the investigation. This limitation manifests in the fact that the analysis engages with the body of knowledge but not based on engaging physically or socially with the contexts within which the cases took place or through empirical investigations including systematic observations, focused interviews, and attitude surveys. While the study does not generate empirical findings, the rigour of the bibliometrics analysis offers a credible and reliable evidence on how cities experienced and managed crises situations and their current plans and priority actions for embedding and localising sustainable development measures.

This research conveys significant implications for policy, practice, and action in that it crystalises the view that understanding urban resilience and sustainability, at the city or urban level, requires coupling the two. The findings offer a solid foundation for a more contextualised, evidence-based examination of urban resilience and sustainability during and beyond crisis. Highlighting urban and health challenges that emerged from experienced crisis situations, how these were managed and developing an understanding of sustainable urban development and local resilience strategies elucidate insights that can be adopted and acted upon by city councils and built environment practitioners.

The analysis provides comprehensive insights into urban resilience and sustainable urban development at both city and continental Europe scales in the form of key lessons that represent the first step towards developing rudiments for building a better urban future. Little is known about resilience and sustainability at these scales. The originality of this work lies in the breadth and depth for capturing an inclusive understanding of urban resilience and sustainable urban development based on systematic inquiry and scrutinising the body of knowledge emerged over the past 2 decades.

The purpose of this paper is to elicit the expectations for resilient post-disaster rebuilds from Caribbean project end-users. In anticipation of future climatological, meteorological, hydrological or geophysical disasters disaster, key stakeholders can articulate and incorporate strategies for resilience development, thus leading to improved end-users’ satisfaction and confidence.

This paper engages the results of a systematic literature review that identified 24 empirical resilience factors for post-disaster reconstruction projects. These factors informed a semi-structured questionnaire to elicit the perspectives of Caribbean end-users on a seven-point Likert scale. The quantitative analysis of both factor ranking and principal component analysis was performed to identify correlations and provides further interpretations on the desires of the end-users for resilient rebuilds.

The results presented in this paper highlight the collective perspectives on the Caribbean end-users on what they perceived to be aiding more resilient reconstruction projects. They identified reconstruction designs mindful of future hazards, policies that aid climate change mitigation, active assessment of key structures, readily available funding sources and ensuring stakeholder’s unbiased interest as the top-most empirical factors. Factor analysis suggested collaborations with inclusive training and multi-stakeholder engagement, critical infrastructure indexing and effective governance as the critical resilience development factors.

To the best of the authors’ knowledge, this paper is first of its kind to explore the perspective of the Caribbean people regarding disaster reconstruction projects. It addresses developmental avenues for measurement indicators towards resilience monitoring and improvement. Additionally, the perspectives can provide construction industry professionals with tools for improved operational resilience objective-setting guidance, for Caribbean construction.

The unitized curtain wall system (UCWS), one of the prefabricated technologies, is increasingly attracting attention in the Hong Kong construction industry. However, this innovative technology still lacks on-site implementation in high-rise residential buildings. To promote its development, this study aims at identifying the influential factors of UCWS adoption in Hong Kong's high-rise residential buildings from a multi-stakeholder perspective.

Factors were first selected through an in-depth literature review and a semi-structured interview. Then the factors were validated through a questionnaire survey using Cronbach's Alpha Reliability Test. Next, the factors were ranked regarding their importance using mean-score ranking and standard deviation. Meanwhile, different stakeholders were clustered using an experimental factor analysis (EFA) model to find the shared preferences (namely common factors).

The result shows that reduction of construction time (B1) and insufficient site storage area (C1) are the most important factors. The six stakeholder groups were clustered into two segments. B1 and improved quality control are the shared interests. While C1 and the need of specification change are the common concerns.

There are two major breakthroughs in this study. First is the novelty of research objects. UCWS, particularly its application preference in high-rise residential buildings, has rarely been studied, yet it is urgently required. Second is the novel research perspective. The influential factors were studied from a multi-stakeholder perspective. Not only the significant factors for six specific stakeholders but also the shared preference for stakeholder groups was identified. The findings contribute to promoting UCWS more targeted, efficient and comprehensive, as well as demonstrating the collaborative possibilities of multi-stakeholders.

The present study assesses the commercial bank profit efficiency and its relationship to banking sector competition in a rapidly growing emerging economy, India from 2009 to 2019 using stochastic frontier analysis (SFA).

Lerner indices, conventional and efficiency-adjusted, quantify competition. Two SFA models are employed to calculate alternative profit efficiency (inefficiency) scores: the two-step time-decay approach proposed by Battese and Coelli (1992) and the recently developed single-step pairwise difference estimator (PDE) by Belotti and Ilardi (2018). In the first step of the BC92 framework, profit inefficiency is calculated, and in the second step, Tobit and Fractional Regression Model (FRM) are utilized to evaluate profit inefficiency correlates. PDE concurrently solves the frontier and inefficiency equations using the maximum likelihood process.

The results suggest that foreign banks are less profit efficient than domestic equivalents, supporting the “home-field advantage” hypothesis in India. Further, increasing competition drives bank managers to make riskier lending and investment choices, decreasing bank profit efficiency. However, this effect varies depending on bank ownership and size.

Literature on the competition bank efficiency link is conspicuously scant, with a focus on technical and cost efficiency. Less is known regarding the influence of competition on bank profit efficiency. The article is one of the first to examine commercial bank profit efficiency and its relationship to banking sector competition. Additionally, the study work represents one of the first applications of the FRM presented by Papke and Wooldridge (1996) and the PDE provided by Belotti and Ilardi (2018).

The purpose of this article is to analyze the existing studies on the application of artificial intelligence (AI) in lean construction management (LCM). Further, this study offers a classification scheme that specifies different categories of AI tools, as applied to the field of LCM to support various principles of LCM.

This research adopts the systematic literature review (SLR) process, which consists of five consecutive steps: planning, searching, screening, extraction and synthesis and reporting. As a supplement to SLR, a bibliometric analysis is performed to examine the quantity and citation impact of the reviewed papers.

In this paper, seven key areas related to the principles of LCM for which AI tools have been used are identified. The findings of this research clarify how AI can assist in bolstering the practice of LCM. Further, this article presents directions for the future evolution of AI tools in LCM based on the current emerging trends.

This paper advances the LCM systems by offering a lens through which construction managers can better understand key concepts in the linkage of AI to LCM.

This research offers a new classification scheme that allows researchers to properly recall, identify and group various applications of AI categories in the construction industry based on various principles of LCM. In addition, this study provides a source of references for researchers in the LCM discipline, which advances knowledge and facilitates theory development in the field.

This study aims to identify the most significant barriers and the stationary barrier to modular construction (MC) implementation and promote MC widespread use. By doing so, the construction industry can leverage the benefits of MC, such as faster construction times, improved quality control, reduced waste and increased sustainability.

This study uses a Gini’s mean analysis approach to identify the stationary barriers hindering the MC adoption in residential projects. The research focuses on the Egyptian context and uses a questionnaire survey to gather data from professionals in the construction industry.

According to the survey findings, the top five significant MC barriers are inability to modify the design; contractors asking for high bidding prices (higher initial cost); scepticism, conservation and resistance of clients to innovation and change; transportation restrictions; and lack of a one-size-fits-all tool for the design. In addition, Gini’s mean of dispersion demonstrated that the stationary barrier that faces MC adoption is the apprehension that architectural creativity will suffer because of MC.

The identified obstacles could be useful for decision makers in countries that have not yet adopted MC and may aid in the planning process to manage the risks associated with MC projects. The paper stresses the significance of devising techniques to overcome these barriers and proposes several methods to tackle these challenges.

This study fills the knowledge gap by identifying the stationary barrier and emphasising the potential risks associated with MC barriers. Furthermore, it suggests several strategies for overcoming and reducing these barriers in developing countries residential projects.

This paper aims to quantitively assess the resilience of residential properties to urban flooding in Port Harcourt, Nigeria, and assess whether they vary at spatially aggregated scales relative to the level of flood exposure.

The study synthesizes theoretical constructs/indicators for quantifying property level resilience, as a basis for measuring resilience. Using a two-stage purposive/stratified randomized sampling approach, 407 questionnaires were sent out to residents of 25 flood-prone areas, to solicit information on the resilience constructs as indicated by the adaptation behaviors of individual households and their property attributes. A principal component analysis approach is used as a mechanism for weighting the indicators, based on which aggregated spatial-scale resilience indices were computed for the 25 sampled areas relative to their levels of flood exposure.

Area 11 located in the moderate flood zone has the lowest resilience index, while Area 20 located in the high flood zone has the highest resilience index. The resilience indices for the low, moderate and high flood zone show only minimal and statistically insignificant differences indicating maladaptation even with incremental levels of flood exposure.

The approach to resilience measurement exemplifies a reproducible lens through which the concept of “living with floods” can be holistically assessed at the property level while highlighting the nexus of the social and technical dimensions.

The study moves beyond theoretical conceptualization, to empirically quantify the complex concept of property-level flood resilience.