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Construction projects are prone to accidents and injuries, necessitating a focus on implementing safety programs. However, the implementation of such programs is influenced by various factors. Developing countries often have poor safety performance in their building sectors, with limited research in this area. This study aimed to identify essential safety program activities (SPAs) specific to the building sector. Through a literature review and survey, 25 SPAs were identified and validated via a pilot survey involving building sector experts. A questionnaire survey was conducted with 105 participants from the construction industry and academia. They were then categorized into four interconnected measurements using Exploratory Factor Analysis (EFA): Safety Program Management and Development (SPMD), Safety Culture Development (SCD), Safety Risk and Hazard Management (SRHM), and Safety Leadership, Responsibility, and Commitment (SLRC). The impact of safety implementation (SI) on overall project success (OPS) was analyzed using Partial Least Square- Structural Equation Modelling (PLS-SEM). Subsequently, Synthetic Fuzzy Evaluation (SFE) was employed to determine the criticality and importance of each SPA grouping for construction projects. The PLS-SEM analysis indicates that SI has a moderate impact on OPS, with an R2 value of 45.4%. Moreover, the findings of the SFE highlight that the SLRC group is the most significant in enhancing the safety implementation of the construction industry.

Sustainability principles should be incorporated into all decision-making stages for residential construction projects to ensure maximum revenue while maintaining essential residential building services. This study identifies and analyzes the critical success factors (CSFs) necessary for implementing agile project management (APM) in residential construction projects. Data were collected from 120 professionals in the Nigerian construction industry through questionnaire surveys to understand the implementation of APM. The CSFs were obtained from previous research and analyzed within the specific context of the Nigerian construction industry through questionnaire surveys. The CSFs were grouped into two main categories using exploratory factor analysis: dynamic project optimization and agile project foundations. The model for the CSFs was developed using partial least squares structural equation modeling. The study found that the dynamic project optimization element had the most significant impact on the model, highlighting its importance as a key CSF in APM implementation. These results support the adoption of APM within Nigeria’s construction industry as stakeholders and professionals seek effective strategies to reduce costs and improve sustainability.

This study examines how certain artificial intelligence (AI) drivers affect the industry's adoption of this technology in the construction industry. The research methods comprised a comprehensive analysis of previous studies to pinpoint the primary factors influencing AI adoption in the construction industry. Data collection was carried out through a well-structured survey involving relevant stakeholders in the building construction sector. The three main constructs of technological devices, advancement, and knowledge were found from the set of drivers with the technique of exploratory factor analysis. The deployment of AI in construction has the potential to improve health and safety and expedite project completion, as this research has evaluated. To figure out how these factors relate to the adoption of AI in the construction industry, partial least squares structural equation modeling was used. The study's conclusions showed that the influence of AI installation in the construction industry is reasonably significant thanks to the technology, advancement, and knowledge, contributing around 15 % of the effects that have been directly witnessed. The practical implications of AI for policy makers, engineers, and construction stakeholders are extensive and provide valuable insights for customized strategies aimed at using AI's potential to improve projects, promote sustainability, and elevate health and safety standards.

The wireless use of radio frequency waves for data acquisition and transfer is known as Radio Frequency Identification (RFID). RFID-based systems have been applied in various fields, including building construction and maintenance. This study aims to evaluate the RFID tools for realizing the sustainability of construction projects. The literature was reviewed to obtain secondary data, complemented by a quantitative method involving the administration of a questionnaire to 107 experts in Nigeria using a random sampling method. It was followed by data analysis using the Exploratory Factor Analysis (EFA) approach. Finally, the structural equation modeling-artificial neural network model was applied to prioritize the major constructs. The EFA results demonstrated that RFID deployment areas may be divided into two main categories: hardware and system. The results affirmed the effectiveness of the system tools for RFID implementation in the building industry. Additionally, the hybrid model revealed that system and hardware predictors rank first and second in the RFID implementation areas. The outcomes of this study are important to understanding tools and methodologies related to the fuzziness of RFID for prospective workforces. Furthermore, it is envisaged that the identified RFID tools would enhance the sustainability of building projects. This study lays the foundation for the enhancement of decision-making in building projects. Although these studies have been confined to Nigeria, the findings apply to other developing countries, especially those with similar construction processes and operations.

Although extensive research has been conducted to explain the high accident rates in the Indian construction industry, studies focusing on the contributions of the prevailing safety climate as an enabler of such incidences remain sparse. Safety climate plays a crucial role in shaping workers’ safety behaviors. Therefore, eliciting the perspectives of construction workers concerning safety climate dimensions that are critical for engendering improved safety behavior will provide valuable insights into the dimensions required to sustain the desired safety performance levels on construction sites. This study adopted a sequential mixed-methods research design. Purposively selected respondents and interviewees were surveyed and interviewed at various intervals. The study established that safety climate dimensions, such as effective leadership, effective communication, consultation, training, resources, incentives, and recognition, are critical in improving safety behavior among construction workers. The results of this study have significant implications for practice and knowledge, as they provide an approach for assessing the impact of different safety climate dimensions on the safety behavior of construction workers in India. Understanding these dimensions will lead to a framework for managing these challenges and improving construction safety performance. The study reported in this paper remains one of the few studies seeking to explore the impact of safety-climate dimensions on worker safety behavior in the construction industry.

In the global push for carbon neutrality and the emergence of net-zero carbon buildings (NZCBs), the lack of substantial progress in achieving NZCB goals due to unaddressed barriers is a pressing issue. While there are ongoing initiatives for NZCB, a crucial research gap exists in the thorough examination of specific barriers and their interconnected complexities, impeding progress in the NZCB agenda. This study aims to fill this gap by identifying and investigating the barriers negating the implementation of Prefabricated NZCBs through a systematic literature review and analyzing their relationships using Interpretative structural modeling (ISM) analysis. Additionally, the study aims to provide a strategic roadmap to overcome the barriers that impede the successful implementation of prefabricated NZCBs. The findings reveal that the regulatory barriers, including regulations, policies, and implementation efforts, emerge as the most significant, followed closely by uncertainties related to long-term financial returns and payback periods. The study concludes that the acceleration of NZCB goals depends on addressing these identified barriers and underscores the imperative for collaboration among government bodies, supply and demand sectors, and end users. Policymakers are urged to integrate these findings into their guidelines for promoting NZCB. The implications of this research are substantial, offering a path forward that prioritizes regulatory obstacles and addresses the most crucial barriers, ultimately propelling the NZCB agenda and contributing to a more sustainable and environmentally friendly future.

The increasing use of road traffic for land transportation has resulted in numerous road accidents and casualties, including those involving oil and gas tanker vehicles. Despite this, little empirical research has been conducted on the factors influencing tanker drivers' performance. This study aims to address this knowledge gap, particularly in the energy transportation industry, by examining the driving performance factors that affect tanker drivers and incorporating risk assessment measures. The model variables were identified from the literature and used to develop a survey questionnaire for the study. A total of 307 surveys were collected from Malaysian oil and gas tanker drivers, and the driving performance factors were contextually adjusted using the Exploratory Factor Analysis (EFA) approach. The driving performance model was developed using partial least squares structural equation modeling (PLS-SEM). The EFA results categorized driving performance into two constructs: 1) drivers' reaction time with β = 0.320 and 2) attention and vigilance with β value = 0.749. The proposed model provided full insight into how drivers’ reaction time, attention, and vigilance impact drivers' performance in this sector, which can help identify potential risks and prevent accidents. The findings are significant in understanding the factors that affect oil and gas drivers' performance and can aid in enhancing oil and gas transportation management by including effective risk assessment measures to prevent fatal crashes.

The use of modular construction (MC) is well-established in developed countries and is known to promote sustainability. However, MC is not widely utilised in developing countries. To address this issue, a study was conducted to identify enablers that can increase the adoption of MC in developing countries, specifically for residential projects. A survey was conducted to determine the relative value of 21 enablers that boost the adoption of MC. The data collected was analysed using Exploratory Factor Analysis (EFA), which classified the enablers into four main components: Optimization, Planning and Management, Preparation, and Promotion and Improvement. Then, Fuzzy Synthetic Evaluation (FSE) was employed to rank these four components, where it was found that “Optimization” is the top performing component while “ Promotion and Improvement ” is the least performing component. The study's results provide a roadmap for the Egyptian construction industry to adopt MC, which can improve the construction sector, particularly in residential construction. Additionally, the findings of this research help fill a gap in knowledge about the enablers that can enhance the use of MC in developing countries.

Construction industry professionals admire the evolution of digital data-acquisition technologies in monitoring processes due to efficient and efficacious outcomes. However, due to a lack of theoretical insight towards the effective application of these technologies, hesitation has been observed for its adoption, which added a challenge to attaining the Industry 4.0 spirit. This study aims to improve a theoretical, statistically validated model, underlining the operational factors that enhance the performance of the digitized monitoring process. The study has followed the structural equation modeling (SEM) approach on identified 36 factors, which were colligated under four categories for developing the technological-based model. The attained model defines effective technological-based factors for implementing automated monitoring under ‘tracking & sensing’, ‘site video’, ‘3D scanner’, and ‘site images’. The significance of this model is a provision of a theoretical base to researchers and construction industry professionals in digitized progress monitoring technological operations and technical aspects towards enriched outcomes.

Driving heavy vehicles with dangerous cargo involves various work environments that can significantly impact road safety. This research aims to study the impact of oil and gas tanker drivers’ work environment on driving performance to identify and address any issues that may affect their ability to carry out their jobs effectively. To achieve this, a quantitative approach was employed using a questionnaire survey adapted from the literature review. The data collected from a sample of drivers of oil- and gas-heavy vehicles were analyzed using structural equation modelling. The study’s findings reveal a significant association between the drivers’ work environment and driving performance, represented by a path coefficient of β = 0.237. These results highlight the substantial contribution of the work environment to driving performance, with an effect of 63%. Consequently, the study emphasizes the importance of considering the work environment as a potential factor when assessing and enhancing tanker drivers’ driving abilities during oil and gas transportation.

Existing literature has shown that Virtual Reality (VR) is widely utilized in advanced economies to enhance sustainable construction practices. However, its adoption in developing economies remains limited. To this end, this study aims at exploring the potential benefits of implementing VR technology in a developing country. The study collected information on the beneficial aspects of VR from previous research and conducted questionnaire surveys to gather relevant insights from construction project experts in Nigeria. The collected data were analyzed using the Measurement of Alternatives and Ranking According to the Compromise Solution (MARCOS) method and Exploratory Factor Analysis (EFA). The MARCOS method revealed that the key potential benefits of VR include improved communication and collaboration, enhanced project performance, risk identification, digitalization, and safety planning. Furthermore, the study conducted an in-depth investigation of the beneficial areas of VR using EFA, which identified six component groups: pre-contract stage planning, post-contract stage planning, quality control and sustainability, design flexibility and reputation, resource management, and risk management and digitalization. The study provides a comprehensive discussion of the advantages of implementing virtual building methods in developing countries.

Poor safety performance is a serious problem in the construction industry. Safety program implementation has always been one of the most successful actions to reduce construction accidents. This research aims to identify barriers to the implementation of safety programs in the construction industry. It begins with identifying barriers to the implementation of safety programs from the literature review. Further barriers were identified from semi-structured interviews conducted with experts in the construction industry in Iraq. The exploratory factor analysis (EFA) technique was used to evaluate data collected from the survey, reduce the number of factors and establish relationships between variables. Based on the analysis, the 12 barriers were grouped into four dimensions: non-conductive work climate, poor governance, poor safety awareness, and unsupportive industry norms. Partial Least Square Structural Equation Model (PLS-SEM) was conducted to validate the EFA results through assessing the relationships between constructed and items. It is recommended that a system of governance at the national level is developed to take these barriers down and improve safety performance in the construction industry.

Sewer pipeline failures pose significant threats to the environment and public health. To tackle these repercussions, many deterioration models have been developed to predict the conditions of sewer pipes, most of which are based on CCTV inspection reports. However, these reports are prone to errors due to their subjective nature and human involvement. More importantly, there are insufficient data to develop prudent deterioration models. To address these shortcomings, this paper aims to develop a CCTV-based deterioration model for sewer pipes using Artificial Intelligence (AI). The AI-based model relies on the integration of an unsupervised, multilinear regression technique and Weibull analysis. Findings derived from the Weibull deterioration curve indicate that the useful service life for concrete and vitrified clay pipes are 79 years and 48 years, respectively. The regression models show that the R2 value for vitrified clay sewer pipes, concrete sewer pipes, and ductile iron sewer pipes are 71.18%, 71.47%, and 81.51%, respectively, and 73.69% for concrete stormwater pipes. To illustrate the impact of various factors on sewer pipes, sensitivity analyses under different scenarios are conducted. These analyses indicate that pipe diameter has a significant influence on sewer pipe deterioration, with little impact on stormwater pipes. These findings would guide decision makers in identifying critical pipes and taking necessary precautionary measures. Further, this provides a sound basis for prioritizing maintenance actions, which would pave the way for designing sustainable urban drainage systems for cities.

To reap the most advantages while maintaining the functioning of residential building projects, sustainability concepts should be included at all stages of the construction decision-making process. This research identified and investigated the barriers to the employment of cyber technology in residential construction projects in order to ensure their long-term viability. Prior research identified cyber technology barriers, which were then contextually explored using a questionnaire survey in the Nigerian construction business. An exploratory factor analysis (EFA) revealed that cyber technology hurdles may be classified into five constructs: knowledge, government, culture, project nature, and regulations. The barriers model was also built using partial least square structural equation modelling (PLS-SEM). According to the findings, project-related constraints were key impediments to the implementation of cyber technology. The findings of this study might serve as a guide for decision-makers in Nigeria’s construction industry looking to decrease costs and boost sustainability via the use of cyber technology.

Successful concepts are adopted throughout the phases of the building lifecycle to provide maximum comfort and benefits to occupiers without compromising the function of such a project. Although there is limited information on building information modeling (BIM) execution in developing countries, BIM drivers have received significant attention from different researchers, but with a limited investigation into the influence of BIM barriers on such building projects. Our goal with this research is to identify and remove any challenges that may stand in the way of using BIM in developing country construction projects. To this end, a comprehensive literature search uncovered impediments to BIM implementation. To assess the relative importance of the numerous challenges to BIM mentioned in the literature, a survey questionnaire was distributed to a sample of specialists in the construction industry. Exploratory factor analysis (EFA) was used to classify these challenges, and partial least square structural equation modeling (PLS-SEM) was created to bring attention to the most pressing ones in the context of BIM adoption. The results of this research will inform policymakers in underdeveloped nations interested in adopting BIM on the pitfalls they should avoid.

The fourth industrial revolution (4IR) era also known as digital age is central to the advancement of the construction industry as the industry is currently facing a myriad of challenges, including poor productivity and project failure. Therefore, there is an urgent need for industry to adopt 4IR innovations to increase the building business’s performance. The study explored the relationship between the critical barriers to 4IR innovations to foster sustainable development. The study embraced a numerical exploration approach which employed a questionnaire to obtain information from building industry experts. The questionnaire data were used to classify the 4IR barriers into policy and structure, readiness, and acquisition, using Exploratory Factor Analysis (EFA). Likewise, a predictive model was developed using Structural Equation Modelling-Partial Least Square (SEM-PLS). It explained the relationship between the barrier categories and the barriers to 4IR innovation adoption for sustainable development. The results showed that policy and structure were critical components of 4IR adoption that the stakeholders of the construction industry must pay close attention to. The study also provided valuable areas for future research to enhance 4IR innovation adoption for sustainable development.

This study aims to assess the barriers impeding cloud computing (CC) applicability in sustainable construction. A total of 11 barriers in the use of CC were identified for the literature review. A questionnaire survey was used to collect the data from construction stakeholders. In total, 101 valid responses were obtained and analyzed using mean ranking, normalized value (NV), overlapping analysis, Kruskal–Wallis H test, exploratory factor analysis (EFA), and fuzzy synthetic evaluation (FSE). The EFA extracted four interrelated components: social, economic, expertise, and connectivity. These components were exported for mathematical analyzing using the FSE technique. As a result, the FSE indicated that connectivity is the highest-impacted component, while the overall impact level of barriers is inclined to high regarding CC applicability in sustainable construction. This is due to other components having an average to high impact level. In this regard, the findings reflect the actual current status of developing countries in using CC in sustainable construction. These research findings will allow construction stakeholders to take proactive steps toward increasing the use of CC in their current and future sustainable construction. Decision-makers could also make accurate decisions that are well-informed in managing CC barriers. This paper provides stakeholders, researchers, and decision-makers with a list of CC barriers that hinder developing countries.

A significant issue in the construction sector is poor safety performance. Construction sites are hazardous and prone to crashes, with several risks that can lead to accidents, injuries, or even the deaths of site workers or passing road users. Numerous studies have addressed this topic but there aren’t many studies in Saudi Arabia that are comparable. The purpose of this research is to determine which obstacles are standing in the way of the construction industry’s adoption of health and Safety Program. Starting with literature research, obstacles to the implementation of safety initiatives are noted. An analysis method known as the Partial Least Square Structural Equation Model (PLS-SEM) was utilized to look into additional barriers. It is recommended that a national governance structure be established in order to overcome these barriers and improve safety performance in the construction industry. Decision-makers would move decisively to establish and enhance safety practices in light of the proposed model’s outcomes. By identifying, assessing, and reducing the primary obstacles to safety program implementation, the study’s findings help Saudi Arabia improve safety practices for building projects.

Building constraints hinder building operations from meeting a project’s time, budget, and quality objectives. For a construction project to provide satisfying results, it is essential to recognize and address such constraints early on. Unfortunately, research on the causes of building constraints and their implications for building management has been limited. Therefore, there is a pressing need to study the sources of constraints and how they impact project results. Consequently, this study addresses this gap by examining the hurdles confronting Egypt’s general building construction projects. Building constraints were identified from previous studies, which were then contextually investigated using a survey questionnaire within the Egyptian construction sector. The exploratory factor analysis (EFA) findings indicated that the constraint factors could be divided into six constructs: environment, stakeholders, regulations, policies, management, and traditional beliefs and ownership. Partial least square structural equation modeling was also utilized to create a constraint factor model. The findings demonstrated that environmental restrictions were significant obstacles to the effective execution of a project. The results of this research can assist decision makers in Egypt’s building sector in cutting costs and improving sustainability by easing the effects of limiting variables.

The sustainable building concept must be implemented throughout the project lifecycle to achieve the highest proceeds without lowering the standard. Although implementing green walls in emerging nations is partial, such studies have concentrated on drivers for implementing green walls. Conversely, there is less proof to comprehensively study the impact of implementing green walls’ overall sustainable success (OSS) concerning the lifecycle of projects. This research focuses on the green wall adoption barriers in construction projects in third-world nations. It assesses the effect of addressing green wall (GW) adoption obstacles on OSS throughout the project lifespan. Therefore, a broader review of the literature is needed for conceptual model development. Structural equation modelling and partial least square (SEM-PLS) have been developed employing a survey evaluation tool (i.e., questionnaire). Information was derived from one hundred and five building professionals in Nigeria. The model output revealed that eradicating GWs barriers had a slight to intermediate influence on OSS during the construction scheme’s lifespan. These results offer the foundation for policymaking in third-world nations regarding successful project completion through evading barriers to green wall adoption. Similarly, green walls implementation will enhance the building project’s success.

To maximize the benefits without sacrificing the functionality of projects, sustainability concepts should be used across all stages of the decision-making process when creating residential buildings. The primary sustainable aims may be improved with BIM activities. However, in the building sector of underdeveloped nations, BIM activities use informal methods. By examining the connection between overcoming BIM implementation challenges and the overall sustainable success (OSS) in building projects, this research seeks to establish a model for BIM implementation. Following the BIM hurdles identified in earlier research, 86 building stakeholders in the Egyptian building sector were given questionnaires. The structure of the obstacles was established and confirmed using partial least-squares structural equation modeling (PLS-SEM), and the connections between the OSS and overcoming BIM deployment were investigated. The adoption of BIM contributed 40.7% to the project’s long-term sustainability, according to the data, which demonstrated a strong link. The findings of this research will serve as a roadmap for decision-makers who want to use BIM in developing nations’ building sectors to save costs and increase sustainability.

Building Information Modelling (BIM) has not been sufficiently proliferated in the developing construction communities. This is owing to the lack of incorporating the key success factors (KSFs) of BIM implementation in a phase-based roadmap to support implementing BIM in practice on a step-by-step approach. With this in mind, this work aims at (1) defining the KSFs for implementing BIM within the developing economies’ socio-economic environment, (2) investigating the interrelationships among the KSFs, and (3) establishing the KSFs in a phased approach to devise a roadmap for their implementation on a step-by-step basis. First, 18 KSFs for implementing BIM have been specified by systematically investigating the pertinent literature and interviewing six well-qualified practitioners in BIM from Egypt, as a developing country. Second, from ten Egyptian BIM experts, data on the influences of the KSFs on each other have been gathered, employing a matrix format-based questionnaire. Third, the experts’ evaluations have been processed, utilizing the Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique. Proficiently, DEMATEL through its causal diagram portrayed the cause-and-effect relations map of the KSFs. Besides, it divided the KSFs into four clusters, each of which signifies a phase in the BIM implementation journey along with its corresponding priority as well as the priorities of the KSFs that it encompasses. The causal diagram indicated that phase one related KSFs of the BIM implementation journey: research and development investments, senior management support, and firm’s fiscal support contribute to the whole success of the developed BIM implementation roadmap. This study equips construction practitioners in the developing economies with a four-phased roadmap for applying the KSFs of BIM implementation journey in practice on a step-by-step basis. This contribution helps in better prioritizing their decisions and optimizing the allocation of their resources when applying BIM in their business. Hence, at a fast pace, BIM can be proliferated in those countries.

Cloud Computing has become a valuable platform for sustainability in many countries. This study evaluates the cloud computing implementation and its Critical Success Factors (CSFs) towards ensuring sustainable construction projects in Nigeria. Data were collected from previous literature, supplemented by a quantitative approach via a questionnaire survey. Data were collected from 104 construction professionals while cloud computing CSFs were examined using Relative Importance Ranking (RII) and Exploratory Factor Analysis (EFA). The results show that cloud computing’s awareness level is 96.2%, which means that the respondents are aware of cloud computing concept. Furthermore, the result shows that most of the respondents are adopting the concept. The analysis of the CSFs indicated that reliable data storage, performance as well as cost of accessibility and availability were the four most significant CSFs to cloud computing applications. Analysis of the CSFs through EFA generated four main components which include human satisfaction, organization, client’s acceptance, and industry-based. Consequently, this study contributed to existing body of knowledge by highlighting the cloud computing CSFs for achieving sustainable construction project. As such, the results could be a game-changer in the construction industry—not only in Nigeria but also in developing nations where construction projects are implemented through similar style and procedure. This study would be a benchmark for supporting decision-makers to improve data fragmentation, in which the use of data is paramount to the execution of construction works. Finally, the results of this study would be useful for enhancing sustainability and general management of construction projects through cloud computing implementation.

Value management (VM) is one of the principles adopted by stakeholders to manage issues in the building industry. This paper aims to examine VM diffusion between residential building entities in the Egyptian residential building industry. This research was confined to the Cairo and Giza regions, with enough residential building experience from clients, consultants, and contractors. A quantitative questionnaire survey was generated to find answers from those active in the residential building industry. The results show that although VM’s most widely practiced activities in the Egyptian construction industry are only information phase activities, professionals in Egyptian building projects agreed that all VM activities are important. The results also demonstrated that there is a significant positive correlation among VM phases. The results constitute activities for the adoption of VMs in Egypt. Its guidelines will dramatically enhance the implementation of VMs both in Egypt and in other developing countries where similar projects are conducted. Finally, this research strengthens the residential building industry’s present management by enhancing VM tools and elements to generate value for money.