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The purpose of this paper is to develop a structural relationship model to study the relationship between causes and effects of poor communication and information exchange in construction projects using Smart-PLS.

The first method of this research is to identify the causes and effects factors of poor communication in construction projects from the extant of literature. The data used to develop the model was collected using a questionnaire survey, which targeted construction practitioners in the Malaysian construction industry. A five-point Likert type scale was used to rate the significance of the factors. The factors were classified under their relevant construct/group using exploratory factor analysis. A hypothetical model was developed and then transformed into Smart-PLS in which the hypothetical model suggested that each group of the cause factors has a direct impact on the effect groups. The hypothesis was tested using t-values and p-values. The model was assessed for its inner and outer components and achieved the threshold criterion. Further, the model was verified by engaging 14 construction experts to verify its applicability in the construction project setting.

The study developed a structural equation model to clarify the relationships between causes and effects of poor communication in construction projects. The model explained the degree of relationships among causes and effects of poor communication in construction projects.

The published academic and non-academic literature introduced many studies on the issue of communication including the definitions, importance, barriers to effective communication and means of poor communication. However, these studies ended up only on the general issue of communication lacking an in-depth investigation of the causes and effects of poor communication in the construction industry. The study implemented advanced structural modeling to study the causes and effects. The questionnaire, the data and concluding results fill the identified research gap of this study. The addressed issue is also of interest because communication is considered one of the main knowledge areas in construction management.

Sources highlight that insufficient skills of site supervisors considerably influence the progress of many construction projects in numerous countries. This study intends to identify the crucial supervisory competencies that influence the effectiveness of building project operations in the context of developing countries.

The crucial construction site supervisory competencies were qualitatively identified through a comprehensive literature survey and a series of expert interviews with the use of thematic analysis approaches. A questionnaire survey was then carried out among 154 building project firms to quantify the impacts of the competencies on the effectiveness of project tasks with the use of the relative importance index approach. Additionally, industry-consultative meetings were held using problem-focused communication strategies to scrutinise the necessary actions.

Overall, 22 cognitive elements and 24 skills/abilities of supervisors were determined as being critical according to their impact values, where the site supervisors cognitive domains in construction planning and construction materials were determined as the top-ranking competencies in the list, with their manual skills/abilities in labour management and labour performance evaluation. Accordingly, a group of key competency outcomes were produced for the considerations in developing new site supervisory training components. Relevant statistical analysis results and the industry consultative outcomes substantiated the validity and dependability of the overall results.

Although the study's focus was to site supervision procedures used in Sri Lankan building construction projects, the overall findings/outcomes might be put to the test in related situations in other emerging industries in other countries.

The study has constructed a base that shows how the significant site supervisory competencies influence the effectiveness of building construction operations, contributing to making a big difference in the methods of reskilling/upskilling in the industry associated with construction labour, supervision, efficiency management and productivity enhancement.

Quality in the construction industry is an important issue yet ignored during the initial stages of the life cycle of a project, that is, the design and construction stage. The contribution of stakeholders, especially the architects is generally suspended though it has huge significance in terms of cost and time related to quality. This research endeavors to examine the issues related to the design and construction stages of the project from architects' purview, to understand the relative importance of these issues in the Indian construction industry.

The study of qualitative data conducted formed a basis for online quantitative data collection that was further analyzed with the help of cross-tabulation and multiple correspondence analysis methods.

The study concludes that the budget of a project is a corresponding factor related to quality concern for architects. The study also established that the quality issues corresponding to high budgets are closely related to the construction stage and are identified as preparation of checklist, and bidding process of hiring the contractor on the lowest bid.

The study is limited to analyzing the perspective of architects; however, other stakeholders of the construction industry may represent a different opinion.

This research emphasizes the importance of the client's role, and need for integration and coordination among stakeholders in the construction industry for effective quality control and management.

The research presents an exhaustive literature review on quality issues and its importance with respect to cost implications, standard practices, sustainability and the life cycle of the project.

This paper covers the development of a multidimensional contract administration performance model (CAPM) for construction projects. The proposed CAPM is intended to be used by the industry stakeholders to measure the construction contract administration (CCA) performance and identify the strengths and weaknesses of the CCA system for running or completed projects.

The research design follows a sequential mixed methodology of qualitative and quantitative data collection and analysis. In the first phase, contract administration indicators were collected from relevant literature. In the second phase, an online questionnaire was prepared, and data were collected and analyzed using the crisp value of fuzzy membership function, and structural equation modeling (SEM). The fuzzy set was chosen for this study due to the presence of uncertainty and fuzziness associated with the importance of several key indicators affecting the CCA performance. Finally, SEM was used to test and analyze interrelationships among constructs of CCA performance.

The data collected from 336 construction professionals worldwide through an online survey was utilized to develop the fuzzy structural equation model. The goodness-of-fit and reliability tests validated the model. The study concluded a significant correlation between CCA performance, CCA operational indicators, and the process groups.

The contribution of this paper to the existing knowledge is the development of a fuzzy structural equation model that serves as a measurement tool for the contract administration performance. This is the first quantitative structural equation model to capture contract administration performance. The model consists of 93 Construction Contract Administration(CCA) performance indicators categorized into 11 project management process groups namely: project governance and start-up; team management; communication and relationship management; quality and acceptance management; performance monitoring and reporting management; document and record management; financial management; changes and control management; claims and dispute resolution management; contract risk management and contract closeout management.

The conventional project delivery (CPD) approach has been reported in the literature as the most widely used project delivery method in the construction industry globally compared to other delivery methods. However, researchers and practitioners have argued that the approach, specifically during the production of design documentation under the CPD, lacks certain capabilities that ensure quality and enhance project delivery. Therefore, this study aims to use the Ghanaian construction industry to identify the capabilities required of the CPD in practice, particularly during the production of design documentation.

The study design follows a pragmatist philosophy and uses mixed methods based on a deductive approach. Data collection involved a questionnaire survey, followed by semi-structured interviews. Quantitative data analysis used descriptive and inferential statistics, whereas qualitative data analysis used content analysis with the assistance of IBM SPSS and QSR Nvivo 12 Pro.

Findings indicate that there should be incentives for producing good design documentation quality; mandatory coordination of design documentation; improving collaboration among designers; and allowing contractors to make input during the design stage.

The results indicate the need for the identified capabilities to be introduced in the CPD approach to improve design documentation quality.

This study offers a significant insight into the specific capabilities that are required of the CPD approach in practice particularly, in the production of design documentation

Sustainable/Green building materials (SBMs/GBMs) offer a wide range of benefits which cut across the economic, social and environmental dimensions of sustainability. The incorporation of these materials in construction projects in most developing countries is still low owing to some factors. This study assessed the major barriers to the incorporation of SBMs in the delivery of construction projects in developing countries, with Nigeria as a case in point.

The well-structured quantitative questionnaire was used to gather data from the key players in the construction industry, using the snowball sampling method and electronic means of questionnaire administration. Frequencies, percentile, relative importance index, Kruskal–Wallis H test, Kendall's coefficient of concordance and exploratory factor analysis were used to analyse the gathered data.

The study revealed that the major constructs of barriers to SBM adoption in construction projects are: (1) resistance and information barriers (Eigenvalues = 5.237; % of V = 23.806), (2) regulation and funding of R&D (Eigenvalues = 2.741; % of V = 12.457), (3) cost and market barriers (Eigenvalues = 2.223; % of V = 10.105), (4) government incentive and suppliers' availability (Eigenvalues = 1.728; % of V = 7.852) and (5) GB experts and labour barriers (Eigenvalues = 1.307; % of V = 5.942).

This study assessed the view of construction experts in the five states of the south-eastern geo-political zone of Nigeria, particularly as regards the barriers to the incorporation of sustainable building materials in construction projects in the region.

Site supervision features largely influence the productivity status of construction operational processes. This study aims to use a case study containing mixed methods to test the site supervisory traits in applying mathematical theories to construction operations for directing supervisory capabilities under various operational characteristics.

A total of 62 construction site supervisors were trained as part of a new apprenticeship programme. Through literature reviews and expert consultations, grading criteria were designed with various degrees of descriptions and score ratings. The supervisory attributes were evaluated under seven competency element characteristics mapped with the relevant learning domains.

The results demonstrate a detailed sectional view of performance ratings of supervisors under different characteristics of competency factors with the validity, reliability, applicability and generalisability assurance of the research findings using relevant statistical tests and expert evaluations.

Though the research applications were engaged directly with the construction industry in the Sri Lankan setting, other developing countries and emerging industries can also employ equivalent tactics to attain similar outcomes in their industry-based operations.

The research findings have led to producing a new guide that makes significant impacts on deciding the capability levels in construction supervisory attributes while executing problem-solving applications in construction planning and operational processes. Accordingly, the findings push to open a gate to intake advanced cognitive attributes towards addressing the industry's knowledge gap on how the problem-solving-based apprenticeship protocols need to be linked with the supervision features.

The objective of this research is to investigate the capabilities of the ChatGPT GPT-4 model, a form of artificial intelligence (AI), in comparison to human experts in the context of construction project risk management.

Employing a mixed-methods approach, the study draws a qualitative and quantitative comparison between 16 human risk management experts from Finnish construction companies and the ChatGPT AI model utilizing anonymous peer reviews. It focuses primarily on the areas of risk identification, analysis, and control.

ChatGPT has demonstrated a superior ability to generate comprehensive risk management plans, with its quantitative scores significantly surpassing the human average. Nonetheless, the AI model's strategies are found to lack practicality and specificity, areas where human expertise excels.

This study marks a significant advancement in construction project risk management research by conducting a pioneering blind-review study that assesses the capabilities of the advanced AI model, GPT-4, against those of human experts. Emphasizing the evolution from earlier GPT models, this research not only underscores the innovative application of ChatGPT-4 but also the critical role of anonymized peer evaluations in enhancing the objectivity of findings. It illuminates the synergistic potential of AI and human expertise, advocating for a collaborative model where AI serves as an augmentative tool, thereby optimizing human performance in identifying and managing risks.

Past studies highlight a wide range of labour-related problems resulting in productivity loss in the construction industry of many developing countries. This study aims to quantify the impacts of labour-related factors on the productivity of construction operations in Sri Lankan building projects based on the viewpoint of engineers and construction managers for upgrading management/organisational policies and practices.

Qualitative and quantitative approaches were used to identify the critical factors. Further, a series of industry consultative discussions were conducted through problem-based communication approaches to analyse the actions required.

A total of 21 factors were determined as critical, where skills shortage, labourers’ thinking abilities, work experience, knowledge in construction works and discipline were leading in the list. The statistical tests and the experts’ discussion outcomes ensured the validity and reliability of the study findings.

The study outcomes will contribute to finding out better ways for directing labour in the industry practices and revising organisational policies towards achieving higher productivity levels in construction operations. Though the study findings are limited to the Sri Lankan context, some findings may be tested in other developing countries in similar scenarios.

The study findings show why the identified factors are critical, how those influence construction practices and what actions need to be considered for addressing the industry’s productivity-related challenges. These can play a key role in upgrading the construction management practices and organisational policies to the near-future stages.

Risks are considered a significant obstacle to Green Building (GB) development and have recently received significant attention from both construction practitioners and academics. This study aimed to identify critical GB risks and explore the relationship between participants' characteristics and risk assessment.

Firstly, a list of GB risks was developed based on a comprehensive literature review and interviewing GB experts. After that, a survey of 207 construction professionals was then conducted to validate these GB risk factors. Finally, this research adopted the ANOVA test and hierarchical regression analysis to examine the relationship between participants' characteristics and risk assessment.

The results provided a list of GB risks classified and evaluated according to the GB project life cycle and, thus, may serve as a helpful reference for GB practitioners. Notably, the ANOVA analysis revealed that risk assessment negatively correlates with participants' GB experience, while their industry experience does not affect risk assessment. Furthermore, the hierarchical regression analysis proved that participant roles do not moderate the association between risk assessment and GB experience.

This study contributed to GB literature by implementing empirical research on GB risks in a developing country. The results implied the essential role of professionals with rich GB experience in risk management in GB projects. Furthermore, this research could help construction practitioners understand GB risks adequately and thereby have better risk-management strategies for future GB projects.