J. Nicholas

The state of health and safety in the UK construction industry with a focus on plant operators

Using statistics obtained from the Health and Safety Executive, compares accident rates occurring within the UK construction industry to the accident rates occurring within other industries; then assesses and discusses these. Results reveal that the construction industry is arguably the most hazardous industry and has consistently recorded a poor accident record. Off‐highway plant and equipment is a considerable contributor to the industry’s infamous record. Then assesses accidents relating to individual plant items and discusses the underlying reasons for such accidents. Part of the problem stems from poor mechanical design but in the majority of cases the operator is at fault. Training programmes and initiatives have previously attempted to address this problem but regrettably the Provision and Use of Work Equipment regulations do not enforce mandatory training and certification. Provides a potential solution to this problem through the use of psychometric test development. Hypothesizes such an approach as representing a useful technique for both improving the skills and competence of existing operatives, and aiding the selection process when hiring new operatives.

Towards standardising the assessment of flood damaged properties in the UK

Presents a conceptual model for assessing flood damage to UK domestic properties. The model originates from a critique of existing knowledge in the field and from discussions held with practitioners responsible for surveying and recommending strategies for repair of such properties. Flood damage assessment is a complex task requiring consideration of many factors. Subsequently, the model takes into account building characteristics along with the characteristics of the flood. Presently, recommendations in the literature for repairing flood damaged properties are very general in nature so “convenient” and circumspect inferences tend to be made by surveyors. In turn, professional guidance in this respect exhibits substantial variance regarding, for example, their specific recommendations for repair work. Because of this variance, it is difficult to confirm whether any repair strategy implemented is optimal, in terms of, for example, cost expended or methods used. The model presented progresses knowledge towards standardising the assessment of flood damaged UK domestic properties.

Using multivariate techniques for developing contractor classification models

Today’s growing numbers of contractor selection methodologies reflect the increasing awareness of the construction industry for improving its procurement process and performance. This paper investigates contractor classification methods that link clients’ selection aspirations and contractor performance. Multivariate techniques were used to study the intrinsic link between clients’ selection preferences, i.e. project‐specific criteria (PSC) and their respective levels of importance assigned (LIA), during tender evaluation for modelling contractor classification models in a data set of 68 case studies of UK construction projects. The logistic regression (LR) and multivariate discriminant analysis (MDA) were used. Results revealed that both techniques produced a good prediction on contractor performance and indicated that suitability of the equipment, past performance in cost and time on similar projects, contractor relationship with local authority, and contractor reputation/image are the most predominant PSC in the LR and MDA models among the 34 PSC. Suggests contractor classification models using multivariate techniques could be developed further.