Design for safety (DfS) is an important mechanism for addressing accidents in construction. In the main, DfS studies have largely focussed on various regions of the world other than sub-Saharan Africa (SSA). Through a questionnaire survey, this study investigated the DfS awareness and practice amongst architects in the Ghanaian construction sector. Data analysis revealed that there is a low engagement in DfS practice despite a high level of awareness of DfS amongst architects. There is a high interest in DfS training juxtaposed against a low engagement in DfS training. DfS practice is not associated with: awareness of the concept of DfS; engagement in DfS professional development training; receipt of DfS education; membership of professional body; years of experience in role; and the company size. Concerted efforts by industry stakeholders, including clients, educational institutions and design professional bodies would be required to encourage the application of DfS amongst architects and other design professionals within the Ghanaian construction environment. Furthermore, more studies on DfS within the SSA context are required in order to profile DfS awareness and practice amongst design practitioners and other industry stakeholders within the region.

Purpose Against the backdrop of the contribution of design to the occurrence of occupational injuries and illnesses in construction, design for occupational safety and health (DfOSH) is increasingly becoming prominent in the construction sector. To ensure that design interventions are safe for construction workers to build and maintain, design firms need to have the appropriate organisational capability in respect of DfOSH. However, empirical insight regarding the attributes that constitute DfOSH organisational capability is lacking. The purpose of this paper, which trailblases the subject of DfOSH organisational capability in construction, is to address two key questions: what organisational attributes determine DfOSH capability? What is the relative priority of the capability attributes? Design/methodology/approach The study employed three iterations of expert focus group discussion and a subsequent three-round Delphi technique accompanied by the application of voting analytic hierarchy process. Findings The study revealed 18 capability attributes nested within six categories, namely: competence (the competence of organisation’s design staff); strategy (the consideration of DfOSH in organisation’s vision as well as the top management commitment); corporate experience (organisation’s experience in implementing DfOSH on projects); systems (systems, processes and procedures required for implementing DfOSH); infrastructure (physical, and information and communication technology resources); and collaboration (inter- and intra-organisational collaboration to implement DfOSH on projects). Whilst these categories and their nested attributes carry varying weights of importance, collectively, the competence-related attributes are the most important, followed by strategy. Originality/value The findings should enable design firms and other key industry stakeholders (such as the clients who appoint them) to understand designers’ DfOSH capability better. Additionally, design firms should be able to prioritise efforts/investment to enhance their DfOSH capability.

The findings are thus symptomatic of the prevalence of influential DfS implementation barriers within the construction sector. Industry stakeholders should seek to raise the profile of DfS practice within the sector. Furthermore, similar empirical studies in the construction sector of other developing countries would be useful in shedding light on the status of DfS in these countries.

Purpose: Decisions made during the design stage of construction works can significantly reduce the risk of occurrence of occupational accidents, injuries and illnesses. Moreover it has been established that design is one of the major contributors of accidents and injuries. Design for safety (DfS) studies within construction have highlighted factors affecting the implementation of DfS, amongst which are: designer attitude; DfS knowledge/awareness and education; availability of DfS tools including guidance; client's influence and motivation; and legislation. The main objective of this study is to carry out an in-depth literature review of DfS studies within construction to explore the extent to which existing DfS research have looked at the above listed DfS implementation factors. Design/methodology/approach: A review of 164 journal articles related to design for safety in construction (published from 1990 to 2017) within built environment, engineering and multi-disciplinary safety journals was undertaken. Findings: The findings indicate that around 60% of the journal articles reviewed address designer knowledge/awareness and education issues; about 27% looked at DfS implementation tools to assist designers to undertake DfS; about 23% studied client influence/motivation; about 16% studied designers attitudes towards DfS implementation; and approximately 16% looked at the role of legislation in DfS implementation. The literature points that client influence/motivation and legislation are very influential DfS implementation factors despite a limited number of studies in these areas. Originality/value: Overall, the findings provide an indication of areas of DfS implementation, particularly client influence/motivation and legislation, where more research would be needed to promote DfS in construction in order to help mitigate the occurrence of accidents and injuries.

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In this paper, we provide a new upper bound for the α-domination number. This result generalises the well-known Caro-Roditty bound for the domination number of a graph. The same probabilistic construction is used to generalise another well-known upper bound for the classical domination in graphs. We also prove similar upper bounds for the α-rate domination number, which combines the concepts of α-domination and k-tuple domination.

More and more households are purchasing electric vehicles (EVs), and this will continue as we move towards a low carbon future. There are various projections as to the rate of EV uptake, but all predict an increase over the next ten years. Charging these EVs will produce one of the biggest loads on the low voltage network. To manage the network, we must not only take into account the number of EVs taken up, but where on the network they are charging, and at what time. To simulate the impact on the network from high, medium and low EV uptake (as outlined by the UK government), we present an agent-based model. We initialise the model to assign an EV to a household based on either random distribution or social influences-that is, a neighbour of an EV owner is more likely to also purchase an EV. Additionally, we examine the effect of peak behaviour on the network when charging is at daytime , night-time, or a mix of both. The model is implemented on a neighbourhood in southeast England using smart meter data (half hourly electricity readings) and real life charging patterns from an EV trial. Our results indicate that social influence can increase the peak demand on a local level (street or feeder), meaning that medium EV uptake can create higher peak demand than currently expected.