Skilled labour shortage is the shortfall of workforce in specific trades or shortage of workforce with requisite skills. The paper seeks to identify areas where there are skilled labour shortages in the building construction industry within the Central Region. A survey research approach was employed to get the study population that consisted of project managers, site engineers, site foremen and engineers working with contactors. Questionnaires were designed based on the research specific objectives and used as the main instrument for data collection. Findings from the study revealed that the shortage of skilled manpower was from painters and decorators, electricians and tile workers. Further findings showed that skilled labour shortage was caused by socio–economic conditions, external forces, job attractiveness, job characteristics, job satisfaction, industry limitations and personal factors. Employees should be encouraged to develop their trade competences and change their attitude to work, while employers should build their manpower base through training.

Building accidents and fatalities are prevalent, especially in rising nations like Ghana, despite rapid technical developments. Weak regulations, training, and change resistance typically undermine traditional safety measures. This study aimed to identify potential obstacles that prevent the implementation of artificial intelligence (AI) in construction health and safety in Ghana. A survey research approach was employed to get the study population, which consisted of 110 construction experts made up of project managers, site engineers, skilled workers, and safety officers complete the questionnaire. Data analysis included descriptive statistics, chi-square, and regression. According to varied demographic responses, AI increases design and engineering, safety and security, and human resources efficiency, decision-making, and safety. Lack of innovation culture, training, and regulation harms health and safety. Using AI promises to overcome these hurdles by minimising risks, improving worker well-being, and safe work environment. The Ghanaian industry study focus and small sample size may prejudice, as the limitations of the study. Samples must be larger and more diversified to generalise. The practical implication is that Ghanaian builders may use the study’s findings. Understanding AI’s potential and limitations helps them develop AI solutions and problem-solving methodologies. Safety, cost, and worker well-being can improve. The successful integration of AI in construction health and safety can affect society. AI can reduce workplace accidents and improve productivity, well-being, and healthcare costs. This work adds to the growing body of knowledge on AI’s building safety applications in emerging economies like Ghana. It identifies environmental restrictions and enables governments, industry leaders, and researchers to develop and implement AI solutions.

The construction industry is known for its task-related risks and hazards contributing to occupational stress and musculoskeletal disorders (MSDs). The study sought to identify the impact of MSDs among concrete mixer operators and workers in the construction industry in the Central Region of Ghana. The population for the study was made up of 28 concrete mixer operators and 187 workers. Out of the 215 questionnaires administered, 206 questionnaires were returned which represented 95.8 % of the response rate. Descriptive statistics and Relative Importance Index (RII) were used for the data analysis. Findings show that most of the workers were young males and worked for a longer period a day. Force movement, repetition, awkward bending and fixed body postures were the major factors leading to the development of MSDs and contributed to frequent absenteeism and poor performance of workers. Further findings show that back pain, waist pain and shoulder pain were the major self-reported MSD complaints. Risk assessment should be conducted on all site hazards and ergonomic tools/equipment should be introduced to reduce the impact of MSDs on workers.

Purpose: This paper aims to identify the unidimensionality and reliability of 84 factors that influence the performance of construction projects and develop a confirmatory factor analysis (CFA) model. Design/methodology/approach: The study adopted a deductive research approach and started by identifying the positive factors that influence construction project performance. This was followed by the modification of the identified factors. After that, a questionnaire was developed out of the factors for data collection. Exploratory factor analysis was used to establish the factor structure of the positive factors, and this was verified using CFA afterwards. A model fit analysis was performed to determine the goodness of fit of the hypothesised model, followed by the development of the confirmatory model. Findings: The study demonstrated substantial correlation in the data, sufficient unidimensionality and internal reliability. In addition, the estimated fit indices suggested that the postulated model adequately described the sample data. Practical implications: The paper revealed that performance can be enhanced if stakeholders identify and leverage the positive factors influencing performance. The paper suggests that project stakeholders, particularly government, project owners, consultants and construction firms, can improve project performance by critically examining economic and financial systems (EFS), regulation and policy-making systems (RPS), effective management practices (EMP) and project implementation strategies (PIS). Originality/value: The contribution of this paper to the present literature is identifying the positive factors and developing the confirmatory factor model. The model comprised 42 positive variables under four indicators: EMP, RPS, PIS and EFS.

The potential contribution of district assemblies to improving health and safety in Ghana's construction industry has not been investigated. This paper attempts to identify the local government responsibilities that could influence health and safety performance in the construction industry and to develop a confirmatory factor model based on these responsibilities. The paper adopted a positivist philosophy and a deductive methodology. A literature search was conducted to identify the local government factors that could potentially impact health and safety performance in the Ghanaian construction industry. These factors were adapted and designed into a questionnaire, and the generated questionnaires were distributed to respondents for their feedback. It was identified using the relative importance index that “the development of sanctions for violating occupational health and safety statutory obligations,” “the institution of local government occupational health and safety approval and certification for new projects,” and “the creation of occupational health and safety departments and committees that are adequately resourced to assist the Department of Factories Inspectorate” were the three most important roles that district assemblies could play as partners to improve health and safety in the construction industry. Conversely, the multivariate analysis identified the evaluation of the safety policies and risk management plans of contractors and suppliers as the most important role local government institutions could play in improving health and safety in the construction industry. The result of the study suggests that local government efforts, when given the needed attention and support, could advance health and safety in the industry. The practical implication of the study is that it identifies the roles of district assemblies that could enhance health and safety in Ghana's construction industry. All district assemblies should consider implementing these health and safety initiatives in their districts and ensuring they are regularly enforced and evaluated.