The complexity and fragmented nature and the multiple stakeholders in the construction industry often make it difficult to come up with a firm decision regarding sustainable building materials selection. The wrong choice could negatively impact the project objective and performance outcome. This study assessed the critical factor influencing the choice of sustainable building materials (SBM) selection on construction projects in the Southeast geopolitical zone of Nigeria. Data were collected using a well-structured questionnaire, non-probability (purposive and snowball) sampling techniques, and an internet-mediated survey. Data analyses were carried out using the appropriate descriptive and inferential statistical tools and exploratory factor analysis (EFA). The study revealed recycled plastic, natural clay and mud, stone, bricks and tile, cellulose, stray bales, grasses, limestone, and wood timber, are the commonly used sustainable building materials. Also, their level of awareness is high while their adoption is moderate. EFA revealed that the major clusters of determinants of the choice of green building materials are: emissions minimisation, low running cost and reusability, low thermal and energy consumption efficiency, low cost and high health and safety consideration and waste minimisation. The key factors influencing the choice of sustainable building materials selection in construction are: reducing greenhouse gas emissions from buildings, materially embodied energy cost, operating and maintenance costs, non-toxic or low toxic emissions generated by the products/materials, recyclability of the building materials, availability of the technical skills, renewable (reusable) properties, inhibiting the impact of buildings on the environment, safety and health of the occupants, and appearance and aesthetic. It is recommended that consideration be given to these factors in selecting sustainable/green building materials in the designs and specifications of construction projects.

Purpose The purpose of this paper is to establish the perception of tradespeople about project-specific constraints (PSCs) influencing construction productivity in Nigeria. Design/methodology/approach Using a qualitative descriptive survey comprising face-to-face semi-structured interviews and a purposive sampling method, views of eight groups of tradespeople and seven project managers on live construction projects in Nigeria were collected. The study used conventional content analysis with the aid of NVivo 12 pro computer software for the analysis. Findings The research evaluated the PSCs and their effect on construction productivity of tradespeople. The findings identified five key PSCs, namely: lack of promotions/reward system, unsafe/poor health condition of workers, delay in material availability, inadequate site amenities and an ageing workforce. These results support earlier research on constraints influencing labour productivity, however, the poor health condition of workers and material unavailability appear to be more unique when compared to other previous studies. Research limitations/implications The study focussed on the Federal Capital Territory Abuja and the Lagos State of Nigeria. It provides insight into the PSCs influencing the productivity of tradespeople in the Nigerian construction industry. Further research to identify the PSCs in depth, in the Eastern part of Nigeria is necessary. Practical implications The PSCs influencing tradespeople’s productivity was identified. The level of the relative impact of the PSCs is expected to guide the project team in addressing the PSCs in a method that is cost effective. Originality/value This study is original research that has underlined some areas of improvement in construction project performance.

Recent statistics reveal substantial increase in late payments cases from 18% to 27%; with over £30 billion unpaid invoices to UK contractors. Furthermore, 82% of overdue invoices are monies owed to subcontractor by tier-1 main contractors. Indeed, tier-1 contractors are deemed to be the main elephant in the room despite various contractual, government and private initiatives designed to curb late payment menace. Yet, there is little research concerning use of Alternative Payment Method (APM) to leverage tier-1 contractors paying subcontractors' invoices promptly. The aim of this study is to assess the use APM to enhance pragmatic and sustainable payment practices between tier-1 contractors and subbies. The research question is: what are the industry specific factors that influences unfair payment practices and how can alternative payment method help to leverage fair payments to subbies? The study adopted sequential exploratory design type of mixed method supported by questionnaire and structured interviews. The study population are drawn from experienced industry stakeholders including clients, contractors, designers, professionals in addition to use of computer simulation to validate proposed APM model. Initial findings reveal an optimism bias tendency of most subcontractors agreeing to lengthened and unfair payments terms induced by Tier 1 contractors. The study identified over five industry and business specific influential factors that encourages tier-1 contractors to clinch to unpropitious late payment practices. In specific terms, there are overwhelming evidences that APM has significant potential to minimize late payment in the UK construction industry if there is political, business and legislative will to implement the model.

Purpose The purpose of this paper is to investigate how on-site blockwork craft gangs’ learning impacts productivity within the production environment on-site to optimise their productivity. Design/methodology/approach The research is adopting a quantitative method with the observation of seven craft gangs’ blockwork with an average of five members in each gang, using the learning curve model application in a 17-storey tri-tower construction project in Nigeria. The linear regression method was employed in the analysis stage of this study using labour-recorded productivity time input as the dependent variables. Findings The paper provides empirical insights about the significance of on-site craft gangs’ learning. The overall blockwork craft gangs learning observed at the site level shows an average learning rate of 94.21 per cent resulting in 5.79 per cent improvement gains. Research limitations/implications Due to the nature of the study and the research question, the observations in this research study were limited to FCDA construction project in Nigeria. The limitation of this scenario is that the research results may lack generalisability. Therefore, there is the need for further study on the learning rate. Practical implications This research study includes the implications for the development of on-site blockwork craft gangs learning; the significant impact of learning rate of 94.21 per cent resulting in 5.79 per cent improvement gain can be used in the planning and to fast track the productivity of craft gangs’ construction. Originality/value This paper identified the need to improve construction productivity through craft gangs’ on-site learning with the application of the learning curve theory.

The data presented in this article is an original data on “Investigating the role of onsite learning in the optimisation of craft gang's productivity in the construction industry”. This article describes the constraints influencing craft gang's productivity and the influence of onsite learning on the blockwork craft gang's productivity. It also presented the method of data collection, using a semi-structured interview and an observation method to collect data from construction organisations. We provided statistics on the top most important constraints affecting the craft gang's productivity using 3-D Bar charts. In addition, we computed the correlation coefficients and the regression model on the influence of onsite learning on craft gang's productivity using the man-hour as the dependent variable. The relationship between blockwork inputs and cycle numbers was determined at 5% significance level. Finally, we presented data information on the application of the learning curve theory using the unit straight-line model equations and computed the learning rate of the observed craft gang's blockwork repetitive work.