In order to maintain a healthy learning environment, diagnosis and management of defects in the educational facility are paramount. The preliminary results of the ongoing research reported here seek to identify defects associated with educational buildings and their effects on the health of polytechnic students and staff in Nigeria. A questionnaire survey, including 34 defects based on a post-occupancy evaluation (POE) was used to establish relationships with the health of polytechnic students and staff. Two hundred (200) respondents were randomly selected based on their schools (faculty) within Lagos State Polytechnic. Descriptive and inferential statistics were used for analysis of the collected data. The results of the study indicate that defects such as plumbing and dampness problems, cobwebs and dust, are prominent in the institution. Also the relationship between building conditions (defects) and health problems was established, with the predictors of the health problems. Based on the findings, it is important for designers and managers of facilities within tertiary institutions to develop and implement design and maintenance policies targeted at minimizing the likelihood of plumbing, dampness, electrical, cobweb and dust problems in educational buildings due to the health risks induced by the defects. It is evident that effective maintenance schedules and policies should be put in place to ensure that facilities are not left to decay before replacement.

Purpose Booms and bubbles are inevitable in the real estate industry. Loss of profits, bankruptcy and economic slowdown are indicators of the adverse effects of fluctuations in property prices. Models providing a reliable forecast of property prices are vital for mitigating the effects of these variations. Hence, this study aims to investigate the use of artificial intelligence (AI) for the prediction of property price index (PPI). Design/methodology/approach Information on the variables that influence property prices was collected from reliable sources in Hong Kong. The data were fitted to an autoregressive integrated moving average (ARIMA), artificial neural network (ANN) and support vector machine (SVM) models. Subsequently, the developed models were used to generate out-of-sample predictions of property prices. Findings Based on the prediction evaluation metrics, it was revealed that the ANN model outperformed the SVM and ARIMA models. It was also found that interest rate, unemployment rate and household size are the three most significant variables that could influence the prices of properties in the study area. Practical implications The findings of this study provide useful information to stakeholders for policy formation and strategies for real estate investments and sustained growth of the property market. Originality/value The application of the SVM model in the prediction of PPI in the study area is lacking. This study evaluates its performance in relation to ANN and ARIMA.

PurposeIn recent years, there has been a tremendous increase in the number of applicants seeking placement in the undergraduate architecture programme. It is important to identify new intakes who possess the capability to succeed during the selection phase of admission at universities.Admission variable (i.e. prior academic achievement) is one of the most important criteria considered during selection process. The present study investigates the efficacy of using data mining techniques to predict academic performance of architecture student based on information contained in prior academic achievement. Design/methodology/approachThe input variables, i.e. prior academic achievement, were extracted from students' academic records. Logistic regression and support vector machine (SVM) are the data mining techniques adopted in this study. The collected data was divided into two parts. The first part was used for training the model, while the other part was used to evaluate the predictive accuracy of the developed models. FindingsThe results revealed that SVM model outperformed the logistic regression model in terms of accuracy. Taken together, it is evident that prior academic achievement are good predictors of academic performance of architecture students. Research limitationsAlthough the factors affecting academic performance of students are numerous, the present study focuses on the effect of prior academic achievement on academic performance of architecture students. Originality/valueThe developed SVM model can be used a decision-making tool for selecting new intakes into the architecture program at Nigerian universities.

Purpose Apprenticeship programmes are designed to provide young trainees with essential broad-based skills. Through apprenticeships, different sectors that are underpopulated can fill up their skills gaps. Apprenticeships are particularly useful to the construction sector which has a high ageing workforce and associated lower labour productivity. However, the completion rates of apprenticeship training programmes in the construction sector remain low in several countries across the globe. Thus, the purpose of this paper is to review the published research on apprenticeship training that is specifically focused on the construction sector, to determine the current status quo and suggest a direction for future research. Design/methodology/approach A systematic review approach was adopted. Based on a comprehensive search using SCOPUS databases, 33 relevant journal articles were identified and analysed. Findings It was found that monitoring and control is the most mentioned factor responsible for improvements in the completion rates of apprenticeship training. In contrast, the length of time required for going through the full training is the most common factor responsible for low completion rates. Three research gaps were identified, among which is the dearth of studies that has focused on apprentices training in developing countries. Research limitations/implications The gaps identified in the current knowledge on apprenticeship training would serve as a justification for future investigations. However, the scope of the review is limited to papers published in academic journals and citable through SCOPUS. Practical implications The outcomes of the study provide researchers and other relevant stakeholders with a concise report on the findings of previous studies. It also provides insight into strategies for improving the completion rates of apprenticeship training in the construction sector. Originality/value A systematic evaluation of the extant literature draws on theoretical evidence and highlights the factors that are more likely to influence the outcomes of apprentice training for craftspeople in the construction sector.

Purpose The development of corporate social responsibility (CSR) in the construction sector is slow, thereby leaving many opportunities for further development. To enable operators in the construction sector to effectively capitalise on the opportunities to promote the development of CSR in the sector, this study employs the practice viewpoint to take the stock of CSR activities in the sector. The purpose of this paper is to reveal the state of CSR practice in the construction sector. The study also draws from the development of CSR in the manufacturing, mining and banking sectors to inform the state of CSR practice in the construction sector. Design/methodology/approach This study carries out a systematic literature review of 56 journal publications that were published between the year 2000 and 2016. The deductive coding of the publications was done to identify four themes of CSR research that constitute the practice view of the state of CSR in the construction sector. Findings The implementation of CSR is the major emphasis in the state of CSR practice in the construction sector. The implementation of CSR is wrapped in the perception of operators about CSR potentials, dimensions of CSR implemented, strategies for implementation and the effects of the implemented CSR practices on performance. The sector characteristics and organisational structure are attributes for comparing the CSR practices between the construction sector and the manufacturing, mining and banking sectors. Originality/value This study provides a researchers’ view of the state of CSR in the construction sector. Additionally, the study draws from the development of CSR in the manufacturing, mining and banking sectors to inform the state of CSR practice in the construction sector.