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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.

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.

Informed by the resource-based view of the firm, dynamic capabilities theory and contingency theory, this study examines the impact of Industry 4.0 (IR4.0) technologies adoption on firm performance (FP) while accounting for the mediating role of innovation ambidexterity (IA) and moderating roles of contextual and methodological factors that drive the performance gains of the phenomenon.

A random-effect model in comprehensive meta-analysis (CMA) is used to synthesize 113 studies in 115 independent samples with 192,188 observations.

This analysis demonstrates that IR4.0 digital technologies are directly related to financial and non-financial performance, disclosing that the performance effect on non-financial is the largest. Moreover, there is a complementary partial mediation role of the impacts of IR4.0 on FP by IA. Furthermore, this focal relationship is moderated by boundary-spanning conditions: contextual factors – firm size, business type, economic development, industry sector and methodological factors – proxy of FP, sample size and study type.

The results imply that IR4.0 produces financial and non-financial benefits by enabling firms to develop dynamic capabilities like innovation ambidexterity, which informs managers and practitioners that unless IR4.0 technologies and IA strategies are combined together to generate superior FP, IR4.0, in and of itself, would produce a less positive impact on FP than the combined impact of IR4.0 and IA. Therefore, managers should focus on converting IR4.0 resources to dynamic capabilities like IA by leveraging open innovation strategies or building IR4.0-based coordination mechanisms by creating cross-unit business synergies.

To the best of the authors' knowledge, per the literature review, this is the first meta-analysis structural equation modeling study on the interplay between IR4.0, innovation ambidexterity and firm performance.

The construction industry is shifting towards becoming more circular by reducing waste, reusing building materials and embracing regenerative solutions for energy generation and biodiversity conservation. Thus, construction professionals must perform diversified services to achieve a circular built environment (CBE). Implementing resource planning and waste management in CBE has already posed challenges to the quantity surveying profession; thus, quantity surveyors (QSs) should be equipped with new roles and competencies to tackle challenges in achieving a CBE. Hence, this study aimed to investigate the functions and competencies of QSs at the design and building material sourcing stages in achieving a CBE according to 3R principles.

The research apprehended a qualitative approach, including two expert interview rounds adhering to the Delphi technique with 14 and 11 experts per each round. Manual content analysis was incorporated to analyse the collected data.

The research findings revealed the important roles and competencies of QSs in achieving a CBE. In addition, essential functions and competencies were categorised according to the 3R principles (reduce, reuse, recycle) to successfully implement CBE during the Design and Building Material Sourcing stages. According to the 3R principles of CBE, cost control, cost planning, feasibility studies, measurement and quantification, risk management, value engineering and innovations and technologies were well-received by most interviewees as essential roles of QSs during the Design and Building Material Sourcing stages. Further, basic/mandatory competencies (personal, interpersonal, professional practice and business skills), economic analysis, BIM management, cost management and risk management are highly regarded by experts for QS as important competencies to achieve CBE.

With new construction trends, QSs must enhance their conventional roles and competencies and search for new skills and competencies. Those skills and competencies could be linked to the CE concept, either directly or indirectly. Since QS holds a prominent place in sustainable construction in CBE, adapting to changes in the construction industry such as CBE is timely for QSs. Further, there is a shortage of literature regarding QSs' roles and competencies in achieving a CBE; thus, this study will contribute by identifying new avenues for QSs in achieving a CBE in the practice and the research.

Understanding the technical and socioeconomic dimensions to resilience is core to making a business case for property-level flood risk adaptation. The study investigates the socioeconomic factors that impact the technical dimensions to property-level flood risk adaptation, and whether there is a typology of households adopting similar adaptation measures in Port Harcourt.

Exploratory and inferential statistical analysis of data collated from 407 questionnaires was carried out. Using chi-square analysis, significant bivariate associations were sought between the level of uptake of different categories of property level adaptation and the socioeconomic characteristics of households. A two-step cluster analysis was used to explore discernible patterns of households implementing similar adaptation measures. Logistic regression analysis was further used to evaluate the extent to which socioeconomic parameters impact residents' willingness to undertake adaptation measures given the option of relocation.

The chi-square analysis highlighted a lack of significant association between some socioeconomic parameters and the uptake of individual adaptation measures. The regression analysis however showed that the socioeconomic parameters exert varying degrees of influence on the residents' willingness to undertake adaptation measures. Two homogeneous groups of residents with similar socioeconomic characteristics were identified via the cluster analysis but did not translate into strongly discernible adaptation differences/patterns.

The study shows that although socioeconomic parameters to some extent underlie the technical dimensions to flood resilience, there is no distinctive typology of households in Port Harcourt adopting a similar combination of measures.

The study offers insights into understanding property-level flood risk adaptation responses within the context of the developing world.