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The purpose of this study is to investigate the factors affecting the cost of concrete component prefabrication using the moderating role of organizational readiness, compatibility and competitive pressure.

The information collected in this study was obtained from 188 questionnaires filled out online by civil engineers active in the Iranian construction industry. Data analysis was performed by partial least squares structural equation modeling.

The results reveal that perceived risk has the greatest impact on cost of using precast concrete components (PCC). Furthermore, the organizational readiness, competitive pressure and compatibility variables have moderating role in the relationship between perceived risk and perceived usefulness. The results can help policymakers and managers to apply the appropriate perspective and strategy to promote this method by illustrating the factors affecting the cost of using PCC in the building construction.

Using the variables of perceived risk, perceived usefulness, and perceived ease of use to predict factors affecting the cost of using PCC is considered as an innovation in this research. In addition to identifying the most important factors affecting the cost of PCC prefabrication in the construction industry, this research tries to identify the impact of environmental factors on the model by examining the moderating role of organizational readiness, competitive pressure and compatibility.

The average lifetime of a building in Iran is only one-quarter of the reported global average lifespan. A major reason why buildings in Iran have shorter service life is attributed to the inappropriate selection of the facility repair and maintenance (R&M) methods. Hence, selecting the appropriate R&M methods is critical in upholding or even extending the lifespan of the building. The purpose of this paper is to determine the main criteria for selecting the suitable R&M methods of commercial real estate (CRE) in Iran as a major challenge encountered by the Iranian construction industry.

The total number of identified criteria (related to the selection of the suitable R&M methods) is 16, which is divided into five clusters (referred as main criteria in this study): human resources; flexibility and technical capability; safety and risk; cost of maintenance; and facilities and technology. To analyze the identified criteria, the expert opinions were collected through both face-to-face interviews and distribution of Delphi survey questionnaires. A total of 12 industrial experts in the construction industry were invited to participate in a Delphi survey to solicit their perceptions and opinions on the identified criteria in this research.

The findings indicated that, among the five main criteria, the cost of maintenance is the most important criteria for selecting appropriate R&M methods of CRE in Iran. In addition, the criterion of facilities and technology was recognized as the least important among the main criteria.

The research, significantly, justified the configuration of non-compliance with the practice and its deliverables and developed a diagnostic study on the grounds of failure in the Iranian construction industry regarding the issues which are threatening the expected and desirable outcomes. The research achievements and suggested effective recommendations can serve as a useful policy and consultative instrument for the relevant stakeholders in the construction industry engaged in building R&M work.

As a little research has been conducted to understand the factors influencing users’ intentions to adopt blockchain-based telemedicine (BBT), it is important to investigate BBT acceptance as incorporation of blockchain technology can solve telemedicine-related issues. Accordingly, this study aims to investigate the factors influencing behavioral intentions (BI) to adopt BBT.

An integrated model comprising the constructs taken from technology–organization–environment framework, technology acceptance model, unified theory of acceptance and use of technology and theory of planned behavior based on their relevance to the context and the objectives of the study has been used for this research. A quantitative approach has been used to test the hypotheses, for which the data was collected from 324 respondents through a self-administered questionnaire. Partial least squares structural equation modeling has been used to test the hypotheses.

The results of the study show that relative advantage, perceived usefulness, trust and perceived ease of use have a significant impact on BI to adopt BBT, whereas regulatory support, subjective norms and facilitating conditions do not have any significant impact on the same.

As the concept of BCT in Pakistan is at its nascent stage and literature regarding this technology’s adoption is also limited, researchers and scholars can apply it to several other fields in Pakistan. For example, this study can be extended to explore the factors influencing blockchain adoption in areas such as education, logistics, transportation, finances and management. This research only considers the direct effects of constructs on BI to adopt BBT and does not consider any mediation and moderations constructs. Future researchers can also study the influence of mediation and moderation constructs on BI to adopt BCT.

Although studies on the acceptance of telemedicine exist, there is a gap concerning the acceptance of BBT, which the current study helps to bridge. From a practical standpoint, the current study makes a highly valuable contribution toward understanding acceptance factors for BBT projects, leading to help policymakers devise policies to promote telemedicine.

This paper studies the critical factors from the perspectives of technological quality, personal compatibility and organisational commitment using the technological adoption framework (TAF). The proposed TAF studies the critical factors that influence the intention to use building information modelling (BIM) taking into consideration of the “Perceived Ease of Use (PEU)” and “Perceive Usefulness (PU).”

The proposed study is a quantitative research study using the TAF model and the statistical analysis using “Partial Least Squares-Structural Equation Modelling (PLS-SEM).” The questionnaires are developed based on the literature review study and disseminated to the stakeholders in the Malaysian construction industry, including consultants, contractors, and clients. The data collected are analysed using PLS-SEM to identify the correlation between the critical factors influencing BIM adoption and the moderation influence of the PEU and PU towards the “Intention to Use (IU)” BIM.

The data collected from 185 construction industry stakeholders in Malaysia was utilised to develop the structural equation model. The measurement model was analysed in terms of composite reliability, discriminant validity, and collinearity issues. Subsequently, the SEM is analysed, and the findings on the hypothesis on the correlation between the critical factors and the intention to use BIM are examined. The study also examines the mediation effects of the PEU and PU towards the BIM adoption in the Malaysian construction industry.

This research conceptual framework, TAF, is derived from the integration of the existing underpinning theories of the technological adoption model and the technology–organisation–environment framework. This new TAF can be used for the study of new technology adoption. This cross-sectional research study is in line with the “Construction 4.0 Strategic Plan” in Malaysia to establish the current BIM adoption scenario and formulate the framework to promote incentives to promote BIM adoption.

During the Covid-19 period, when human beings are socially isolated, telework is a viable solution to safeguard employees' health. Because many employees have never experienced such a working system and organizations have not planned for it before the pandemic, imposing employees to telework has adversely affected their productivity and efficiency. This study aims to identify factors affecting individuals' tendency toward teleworking during the pandemic, which can lead to practical solutions for the post-pandemic era.

Through the use of technology acceptance models, a conceptual model was designed. Data used to assess the model were cross-sectional and derived from 229 questionnaires filled out by employees in Tehran. The AMOS24 software processed the corresponding structural equation model.

The results from the cross-sectional data indicated that attitude toward telework and perceived behavioral control over the system were significantly correlated directly with the intention to telework, while perceived usefulness and perceived ease of use of telework were correlated indirectly. Therefore, the integrated model predicts behavioral intentions better than single models performed separately.

Psychological and mental health research describing adoption intentions of telework, particularly those focusing on employees, is still lacking. To the best of the authors' knowledge, this is the first study in this regard that has used a conceptual model derived from two technology acceptance models during the Covid-19 outbreak. An era in which the extent of the pandemic has forced employees to experience such working systems and thus the importance and practicality of teleworking have been more evident to nearly every individual.

The purpose of this article is to analyze the state-of-the art in a systematic way, identifying the main research groups and their related topics. The types of studies found are fundamental for understanding the application of artificial neural networks (ANNs) in cemented soils and the potential for using the technique, as well as the feasibility of extrapolation to new geotechnical or civil and environmental engineering segments.

This work is characterized as being bibliometric and systematic research of an exploratory perspective of state-of-the-art. It also persuades the qualitative and quantitative data analysis of cemented soil improvement, biocemented or microbially induced calcite precipitation (MICP) soil improvement by prediction/modeling by ANN. This study sought to compile and study the state of the art of the topic which possibilities to have a critical view about the theme. To do so, two main databases were analyzed: Scopus and Web of Science. Systematic review techniques, as well as bibliometric indicators, were implemented.

This paper connected the network between the achievements of the researches and illustrated the main application of ANNs in soil improvement prediction, specifically on cemented-based soils and biocemented soils (e.g. MICP technique). Also, as a bibliometric and systematic review, this work could achieve the key points in the absence of researches involving soil-ANN, and it provided the understanding of the lack of exploratory studies to be approached in the near future.

Because of the research topic the article suggested other applications of ANNs in geotechnical engineering, such as other tests not related to geomechanical resistance such as unconfined compression test test and triaxial test.

This article systematically and critically presents some interesting points in the direction of future research, such as the non-approach to the use of ANNs in biocementation processes, such as MICP.

Regarding the social environment, the paper brings approaches on methods that somehow mitigate the computational use, or elements necessary for geotechnical improvement of the soil, thereby optimizing the same consequently.

Neural networks have been studied for a long time in engineering, but the current computational power has increased the implementation for several engineering applications. Besides that, soil cementation is a widespread technique and its prediction modes often require high computational strength, such parameters can be mitigated with the use of ANNs, because artificial intelligence seeks learning from the implementation of the data set, reducing computational cost and increasing accuracy.

The oil and gas construction projects are affected negatively by the drop in oil price in recent years. Thus, most engineering, procurement and construction (EPC) companies are opting to optimize the project mainly to mitigate the source of risks in construction to achieve the project expectation. Risk factors cause a threat to the project objectives regarding time, cost and quality. It is additionally a vital component in deviating from the client's expectation of productivity, safety and standards. This research aims to investigate the causes of risk in the oil and gas construction projects in Yemen.

A comprehensive literature review from various sources including books, conference proceedings, the Internet project management journals and oil and gas industry journals was conducted to achieve the objectives of this study. This initial work was predicated strictly on a literature review and the judgments of experts to develop the risk factor framework for the oil and gas construction projects in Yemen.

The authors found a few studies related to risk factors in oil and gas construction projects and shared a similar view about general construction projects. However, only a fraction of the factors accepted have included the variances of other studies on a regional basis or specific countries, such as the Yemen situation, due to the differences between the general construction industry and oil and gas industry. Moreover, the factors of these attributes were still accepted due to their applicability to the oil and gas industry, and no significant variances existed between countries. Research has indicated that 51 critical factors cause risks in the oil and gas construction projects in Yemen. Such risk factors can be divided into two major groups: (1) internal risk factors, including seven critical sources of risks, namely client, contractor, consultant, feasibility study and design, tendering and contract, resources and material supply and project management; and (2) external risk factors, including six sources of critical risk factors, namely national economic, political risk, local people, environment and safety, security risk and force-majeure-related risk factors. A risk factor framework was developed to identify the critical risk factors in the oil and gas construction projects in Yemen.

This research was limited to the oil and gas construction projects.

Practically, this study highlights the risk factors that cause a negative effect on the success of oil and gas construction projects in Yemen. The identification of these factors is the first step in the risk management process to develop strategic responses for risks and enhance the chances of project success.

The identification of risks factors that cause the failure of construction projects helps develop response strategies for these risks, thereby increasing the chances of project success reflected in the oil and gas sector, which is a main tributary of the national economy in developing countries.

This research is the pioneer for future investigations into this vital economic sector. Given the lack of resources and studies in the field of construction projects for the Yemeni oil and gas sector, the Yemeni government, oil companies and researchers in this field are expected to benefit from the results of this study. The critical risk factors specific to the oil and gas construction projects in Yemen should be further investigated with focus only on Yemen and its oil and gas industry players.