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The purpose of this paper is to consider the significance of the sources of cost of construction plant theft identified in previous studies and derive rates which can enhance proper estimation of the cost of plant theft to the construction industry. The direct and indirect costs of plant theft include replacement cost (new‐for‐old/depreciated), emergency cost, hire replacement cost, productivity loss, increased labour cost, loss of goodwill, administration cost, increased insurance premium and social cost.

The cost‐contribution of these various sources was studied, using a structured questionnaire which was administered to building contractors in the UK construction industry, to measure their opinions of the frequency and severity of the contribution of the sources to the cost of construction plant theft. The questionnaires were administered to 220 companies and 51 of them were fully completed, representing 23.1 per cent of the original sample. The responses were analysed using descriptive and inferential statistics to derive the probabilities of sources contributing to the cost of plant theft.

The results of the analysis show that the rates of contribution to the cost of plant theft varies significantly between the sources, with “loss of output” and “increased insurance premium” ranking as the top‐two costs of plant theft in the UK construction industry. The rates derived in this study can be used by contractors to reasonably estimate the cost of plant theft, especially when there is need to justify the adoption of measures that can mitigate plant theft.

This study generated rates of contribution by factors which contribute to the overall cost of theft of construction plant in the UK. These rates can provide a more reliable estimate of the cost of plant theft than current estimations which vary significantly.

Unlike common evaluation procedures where students are only used to gather information without being involved in the utilisation of the information, the procedure applied in this study involved students in the process of implementing the gathered information in the improvement of learning and the development of a student-centred learning resource. This study aims to improve learning by involving students in the improvement process through appreciative inquiry (AI) and give students a different teaching method.

In this study, AI was used to identify the best of an existing learning resource; co-envisioning the possibilities that can improve the learning resource and co-constructing the possibilities along with the students that will benefit from the improved learning resource.

Through the five phases of AI, students generated ideas for improving the learning resource and the ideas were implemented in creating an improved learning resource. The improved learning resource was evaluated by other students that did not participate in creating the improved learning resource. Majority of the students said the improved learning resource was more impactful on their learning, better than the original learning resource.

AI has hitherto been mostly focussed on other aspects of teaching and learning than aspects that require subject knowledge such as the development of teaching and learning resources. Hence, in this study, students were engaged as co-creators in developing a student-centred self-learning study manual.

The purpose of this paper is to discuss an integrated decision analysis framework for the investment justification of implementing alternative information and communication technology (ICT)-based logistics systems in the construction industry so as to enhance the decision-making process in selecting the best alternative.

An integrated framework is proposed that is composed of a set of interrelated evaluation and analysis techniques that allow the identification and quantification of costs, benefits and risks involved in implementing ICT systems to mitigate problems that hinder the efficient operation of construction logistics. Such techniques include decision trees and multi-attribute decision-making under uncertainty that can be applied to the logistics planning of any new build construction project.

The probabilities of providing benefits vary among the alternatives, and the probabilities will replace the uncertainties surrounding the impacts of the alternative ICT systems in addressing the identified construction logistics problems with chance events so as to estimate the expected cost of each alternative with respect to each selection attribute.

This paper shows that it is almost certain that the analysed alternative ICT system will provide benefit because its probability of benefit is almost equal to 1.

The framework captures the existing problems of logistics in construction process, potential solution that can address the problems through the implementation of ICT systems and the decision-making process in the selection of appropriate ICT solution. The output of the framework will help to make knowledge-based decision in selecting the best ICT system for addressing construction logistics problems.

During the last decade, the practice of sustainability has been gradually adopted in the UK construction industry, with the increasing interest in the discourse of sustainable development. This paper therefore aims to investigate the role and ability of sustainable development-based requirements – top management commitment, government regulations and construction stakeholder pressures – as potential determinants of adoption of proactive environmentally sustainable practices, with a view of promoting sustainable innovation in the UK construction industry.

The research approach selected for this research comprised of a questionnaire survey of the UK construction industry practitioners – architects and designers, structural engineers, construction managers and quantity surveyors – with the aid of an Adobe Livecycle Designer. Purposive sampling techniques using maximum variation strategy were adopted for selecting the target survey respondents. The Predictive Analysis Software (PASW) Statistics 17.0 (formerly SPSS statistics) was employed to analyse information from the survey.

Empirical results indicate a positive effect of government regulations, top management commitment and construction stakeholder pressures on sustainable construction practices. Government regulation was found to be the most important determinants of sustainable practices. In addition, top management commitment appears to be linked with government regulation as the defining factor increasing managers sustainability awareness, helping sustainable practices to be effectively implemented and appealing to firms.

The research results provide useful information in understanding the determinant factors of sustainable construction innovation and are particularly essential in aiding better decision-making in implementing sustainable practices, thereby facilitating the sustainability of the construction sector.