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While it may be in the interest of construction firms to expand either gradually or rapidly their workload over time, the need to maintain a stable volume of work is still crucial for long‐term survival. While it is obviously useful for the industry to try to resolve the specific quality problems identified, the need to attain a stable and minimal level of workload will remain a high priority for all construction firms. This is because without a stable workload, survival will be at stake, let alone expansion and provision of good quality services and products. Sets out to test two hypotheses. First, poor quality standards in the construction industry are primarily structural problems tied to the demand for construction. Second, because cyclical fluctuations are inherent in the construction industry, poor quality standards in construction are also likely to be perpetual problems.

It is widely believed that the construction industry is more volatile than other sectors of the economy. Accurate predictions of the level of aggregate demand for construction are of vital importance to all sectors of this industry (e.g. developers, builders and consultants). Empirical studies have shown that accuracy performance varies according to the type of forecasting technique and the variable to be forecast. Hence, there is a need to gain useful insights into how different techniques perform, in terms of accuracy, in the prediction of demand for construction. In Singapore, the residential sector has often been regarded as one of the most important owing to its large percentage share in the total value of construction contracts awarded per year. In view of this, there is an increasing need to objectively identify a forecasting technique which can produce accurate demand forecasts for this vital sector of the economy. The three techniques examined in the present study are the univariate Box‐Jenkins approach, the multiple loglinear regression and artificial neural networks. A comparison of the accuracy of the demand models developed shows that the artificial neural network model performs best overall. The univariate Box‐Jenkins model is the next best, while the multiple loglinear regression model is the least accurate. Relative measures of forecasting accuracy dealing with percentage errors are used to compare the forecasting accuracy of the three different techniques.

The purpose of this paper is to empirically investigate the effects of a major disaster on the management of human resources in the construction sector. It sets out to identify the construction skills challenges and the factors that affected skills availability following the 2010/2011 earthquakes in Christchurch. It is hoped that this study will provide insights for on-going reconstruction and future disaster response with respect to the problem of skills shortages.

A triangulation method was adopted. The quantitative method, namely, a questionnaire survey, was employed to provide a baseline description. Field observations and interviews were used as a follow-up to ascertain issues and potential shortages over time. Three focus groups in the form of research workshops were convened to gain further insight into the feedback and to investigate the validity and applicability of the research findings.

The earthquakes in Christchurch had compounded the pre-existing skills shortages in the country due to heightened demand from reconstruction. Skills shortages primarily existed in seismic assessment and design for land and structures, certain trades, project management and site supervision. The limited technical capability available nationally, shortage of temporary accommodation to house additional workers, time needed for trainees to become skilled workers, lack of information about reconstruction workloads and lack of operational capacity within construction organisations, were critical constraints to the resourcing of disaster recovery projects.

The research findings contribute to the debate on skills issues in construction. The study provides evidence that contributes to an improved understanding of the industry’s skills vulnerability and emerging issues that would likely exist after a major disaster in a resource-limited country such as New Zealand.

From this research, decision makers and construction organisations can gain a clear direction for improving the construction capacity and capability for on-going reconstruction. Factors that affected the post-earthquake skills availability can be considered by decision makers and construction organisations in their workforce planning for future disaster events. The recommendations will assist them in addressing skills shortages for on-going reconstruction.

Although the study is country-specific, the findings show the nature and scale of skills challenges the construction industry is likely to face following a major disaster, and the potential issues that may compound skills shortages. It provides lessons for other disaster-prone countries where the resource pool is small and a large number of additional workers are needed to undertake reconstruction.

A statutory board is one of the three forms of public enterprise in Singapore which are involved directly or indirectly in economic development. Tan Chwee Huat has defined a statutory board as “an autonomous government agency set up by special legislation to perform specific functions (Tan, 1974, p. 102).” Similarly, Lee Boon Hiok has referred to statutory boards as “a catchall phrase for the statutory bodies which have been established by an Act of Parliament,” which specifies their rationale as well as their rights and powers (Lee, 1975, pp. 38–39).

The purpose of this paper is to investigate whether a few leading Hong Kong construction firms are also efficient contractors. Theoretically, market leaders can exploit the virtue of economy of scale, learning curve and cost leadership to consolidate their competitiveness. However, if market share is key success factor for firms to become and stay competitive, smaller contractors will be further marginalized if the construction market continues to shrink as Hong Kong's economy approaches maturity. Hence the research question is: Have a few leading contractors been taking advantage of their market size to be efficient in Hong Kong?

Based on the Data Envelopment Analysis Assurance Region (DEA_AR) model, the efficiency scores of 17 major Hong Kong contractors are compiled over the last ten years. DEA is a non‐parametric approach to examine the relative efficiency among different firms, in terms of output/input ratios. Unlike traditional I‐O analysis which relies on a static table of coefficients, DEA does not require any priori and usually subjective weights for inputs or outputs.

The results identify efficient contractors, among which the three leading ones (China State Construction, Shui On Construction and Yau Lee Holdings) have captured the majority of housing construction contract values. Nevertheless, only China State Construction has ranked consistently as most efficient over time. The efficiency scores of Shui On Construction have decreased successively from 2002 to 2009, and it has been the least efficient contractor from 2006 to 2009. Yau Lee Holdings has a V‐curve of efficiency scores.

This study represents the first attempt to adopt a DEA_AR model to evaluate construction contractors' efficiency, which reduces the number of zeroes and the variation in weights for estimation and enhances the adequacy for individual contractor's efficiency scores, compared to other types of DEA models such as the CCR model and the BCC model.

COVID-19 was officially declared as a worldwide pandemic by the World Health Organisation on 11th March 2020, before the UK was put into lockdown on the 23rd March 2020. Organisations had to reconsider their policies and procedures to allow their businesses to continue. This paper aims to focus on the effects of COVID-19 that the UK construction sector has had to undertake to enable businesses while employees had to adhere to COVID-19 lockdown rules. In addition, how the sector can positively continue once normality has returned within the industry. In doing so, this paper understands the historical issues within the construction sector and has had an effect during COVID-19.

A qualitative research methodology approach was taken to help obtain live information. In total, 19 semi-structured interviews from 15 organisations related to the construction sector were conducted to collect data. This information was evaluated using thematic analysis to arrive at the results, inferences and recommendations to the sector.

This research has revealed that companies have had to adopt a three-stage process to overcome a new dimensional challenge of COVID-19. These include: 1. Making quick decisions during the first stage of the pandemic. 2. Producing new policies and procedures to restart businesses enabling staff to return to the workplace safely. 3. Implementing methods to future-proof organisations against any potential pandemics. To help organisations future-proof their business five C’s are recommended.

This paper provides a rich insight into the understanding and awareness of the effects of COVID-19 and the changes that the construction sector has had to undertake to adhere to the lockdown rules while remaining productive. This research contributes towards informing policymakers on some of the lessons learned during the management of the COVID-19 pandemic from a construction sector perspective.

The construction industry is a crucial industry for national development worldwide. Because the construction industry is tied to national and international economic activities, the COVID-19 outbreak has limited construction projects. Therefore, this study investigates the most influential factors regarding COVID-19 and their effects on the construction industry.

The potential impacts of COVID-19 on the construction industry were identified through a realistic literature review and interviews with professionals. A questionnaire was distributed via e-mail to architects, civil engineers and contractors who play vital roles during the construction processes. The data were analysed using SPSS 22 and LISREL 8.7 software to quantify the most influential pandemic-related factors faced by the construction industry.

Ten influential pandemic factors affecting the construction industry in Turkey were identified. Among them, “increased costs and price escalations due to shortage of raw materials and supply chain disruption” and “challenges with payment and cash flows” were determined as the most influential pandemic factors.

This research aims to advance comprehension of pandemic impacts and contributes an incipient assessment framework based on 10 determined pandemic factors. Therefore, contractors, architects and civil engineers may analyse their weaknesses and organise precise priorities so that their firms may remain competitive, thus minimising the adverse impact of COVID-19 and possible forthcoming waves.

Few studies have identified the effect of pandemics on the construction industry qualitatively, forcing management to make projections to the current situation. Moreover, no study has provided insights into the influential factors of pandemics using quantitative methods. Therefore, this study comprehensively and quantitatively determines the relevant COVID-19 pandemic factors using exploratory factor analysis (EFA) and utilises confirmatory factor analysis (CFA) and structural equation modelling to present a structural model of how pandemic factors affect the Turkish construction industry.

A mixed philosophies epistemological design with inductive reasoning was adopted to develop new theoretical insights into the phenomena under investigation. First, interpretivism was employed to contextualise the prevailing body of knowledge and source questions (and prompts) to be posed to practitioners. Second, a case study strategy (augmented by participant action research) was adopted to measure construction industry professionals' perceptions of the clerk of work's role and their impact upon both quality and safety of construction.

This research conducts a case study investigation of affordable and/or social home construction and examine industry's perception of the clerk of works (CoW) and their powers and responsibilities within existing legislation to impact quality of construction.

The findings illustrate that while the clerk of work's role positively impacts quality and safety of construction, it is hindered by cost and time constraints that are often prioritised. An analogy to “yield points” in materials science is then adapted to develop new theory to conceptualise the pivotal position that the CoW has in upholding quality construction. The research concludes with pragmatic recommendations (such as industry centric codes of practice) to mitigate quality and safety issues arising and signpost future academic research in this area.

UK construction has been criticised for prioritising costs and profits vis-à-vis quality and safety issues, as exemplified by the Grenfell fire. This study demonstrates the need for reinstatement of the CoW role in mitigating residential housing quality decline.