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Mental health problems are a grave concern in construction. Although the distinction between high job demands and low job resources, as reflected in the Job Demands-Resources (JD–R) model, has been used to examine the extent to which psychosocial hazards influence mental health for construction practitioners, limited research has reflected on the nature of these psychosocial hazards by exploring experiences of site-based construction practitioners.

This study adopted a phenomenological approach to examine people’ experiences and thoughts of the complex phenomena of psychosocial hazards and mental health in construction. In total, 33 semi-structured interviews were undertaken with site-based construction practitioners in Australia to unveil construction-focused psychosocial hazards and their effects on mental health. The data were analysed via content analysis, employing an interpretation-focused coding strategy to code text and an individual-based sorting strategy to cluster codes.

Eighteen psychosocial hazards were identified based on the JD–R model. Six of these represented a new contribution, describing salient characteristics inherent to the construction context (i.e. safety concerns, exposure to traumatic events, job insecurity, task interdependency, client demand and contract pressure). Of particular importance, a number of interrelationships among psychosocial hazards emerged.

The significance of this qualitative research lies in elucidating psychosocial hazards and their complex interrelatedness in the context of the mental health of construction practitioners, enriching the understanding of this central health and safety issue in the high-risk setting of construction work. The findings contribute to addressing mental health issues in the Australian construction industry by identifying higher order control measures, thereby creating a mentally healthy workplace.

The purpose of this paper is to investigate how a deep learning approach can impact the construction industry.

The objectives of this paper were to investigate: the awareness of people dealing with sustainability in their daily working environment; how much training and information construction industry workers have had in the topic of sustainability; and if a deep learning approach to sustainability teaching can make an impact on everyday practise in the industry. With these objectives, following a literature review, a questionnaire survey has been applied to 133 office and site‐based construction workers. In total, 50 office‐based workers and 50 site‐based workers participated.

The findings reveal that deep learning can be a possible opportunity and that the Government and the construction industry should explore it when training their staff. Although there are agencies which specifically deal with green issues, they are not widely embraced and workers currently just use them as a way to meet criteria and not to fully grasp the concept and incorporate it into their everyday practice. If deep learning can be embraced it can lead to a continuous improvement in green practice.

With the UK government recently setting new targets for sustainability, it is important that the construction industry takes actions to reduce its carbon footprint. The construction industry needs to improve its ability to train and teach its staff about the importance of green issues and environmentally‐friendly practices. This paper presents the results of research which may contribute to meeting the government targets and can be useful for practitioners and researchers.

Conventional methods of project duration control primarily rely on comparing contracts programs with actual progress. Detailed barcharts are often produced and progress is measured and recorded for monitoring by site based practitioners. Head office managers that are responsible for a group or groups of contracts running simultaneously depend on the reports generated on site for their control mechanism. There are many drawbacks in relying solely on site based reports, including concerns about accuracy, misrepresentation of facts, competence of site based staff, time taken to interpret these reports, etc. This paper develops and proposes the use of a new system that can be used as an additional tool whereby significant discrepancies in projects' progress performance can be highlighted. The system is based on stochastic models developed to simulate the cost commitment curves of traditional construction projects. The paper describes how the system is developed and how it can be used. The system has been developed as part of a pilot study to validate its usefulness in principle. Hence the factors used to distinguish projects characteristics were only based on broad terms. It is hoped that an improved model would be developed when more variables are considered and incorporated.

Young construction project management practitioners (CPMPs) have unique, complex, and notable occupational mental health problems. However, there were few studies about the intervention for occupational mental health of CPMPs, and traditional intervention modes often failed to achieve significant effects. Therefore, this study aims to propose a new and effective intervention method.

Job crafting intervention was used to design an intervention experiment. A total of 72 CPMPs participated in a 10-week randomized controlled trial in China. Descriptive statistics and repeated measures analysis of variance were used to verify the effectiveness of job crafting intervention (JCI) on job crafting behaviors, job burnout, and work engagement with consideration of the impact of time.

Results showed that the intervention increased social resources, thus effectively reducing job burnout and promoting work engagement. Time also had a significant impact on cynicism, dedication, and social resources.

The authors should promote the habit of job crafting in CPMPs. Furthermore, in order to facilitate their job crafting, the authors should increase structural and social resources for them, and the authors can also encourage them to undertake challenging demands to increase their self-efficacy and the sense of achievement.

The authors bring into light a new psychological intervention approach among CPMPs, which integrates the advantages of the guidance in traditional organized intervention methods and the proactivity in individual spontaneous job crafting. The authors verify the efficacy of the JCI among CPMPs and help propose countermeasures and suggestions to improve the occupational mental health of CPMPs.

There is a dearth of basic analysis about how the demographics of residents living in the US Department of Housing and Urban Development (HUD) subsidized properties relate to the quality of housing. This research vacuum is often filled by popular stereotypes. This study aims to address this gap by examining the relationship between the demographics of residents and inspection scores.

Two data sources are drawn from the analysis: the 2018 HUD Picture of Subsidized Households database and HUD’s 2018 REAC Public and Multi-Family Housing Inspection Scores. Linear and logistic regression analysis were conducted, and selected data were mapped using GIS software.

The analysis examines the demographics of site-based subsidized properties in relation to inspection scores. In 2018, HUD identified 31,225 traditional public housing and other site-based multi-family properties in its Picture of Subsidized Households database. Residents living in these properties are often stereotyped as a homogeneous group that is predominantly composed of single, minority women with children who are welfare dependent. Similarly, properties are often portrayed as dilapidated, high-rise projects in segregated urban communities. The results from the analysis do not support these stereotypes about HUD-subsidized multi-family properties. By contrast, the results indicate that a diverse group of households lives in HUD-subsidized multi-family properties.

There is a need for scholars, advocates and practitioners to more aggressively challenge the popular stereotypes about site-based subsidized housing. In particular, there is a need for enhanced public scholarship focused on the dissemination of evidence-based research.

This chapter presents case studies of two doctoral students in a program designed to develop leadership for social justice. Amidst criticisms that doctorate programs promote neither research nor professional expertise, the question of program relevance is addressed by asking a different question. How are urban school leaders uniquely positioned to conduct research that can transform schools? The tale of two scholar-practitioners illustrates the changes in site and district practices that result from collaborative, site-based studies. Inquiries were grounded in critical theory: by collaborating with those most affected by policy, school leaders and participants transformed inequitable practices at and beyond their schools.

An extensive search of the literature revealed a dearth of research on the demotivational factors affecting the performance and productivity level of site-based construction project managers. Following the announcement of awarding the FIFA 2022 World Cup hosting rights to the State of Qatar, the State is pledging to spend tens of Billions of Dollars on hundreds of new construction projects. Therefore, the purpose of this paper is to identify, explore, and rank the relative importance of the demotivational factors influencing the productivity of the State's construction management force.

A structured questionnaire survey comprising 38 potential demotivational factors, which were shortlisted based on relevant previous studies on the impact of motivation on construction productivity, and numerous interviews with local industry professionals, was distributed to a relatively large sample of site-resident project managers. Using the “Relative Importance Index” technique, the influence ranks of the factors explored were determined.

The results obtained reveal the following as the prominent demotivational factors influencing the productivity of construction project managers: lack of financial incentive schemes; slow decision-making process by owners; remuneration scale; delay in responding to Requests For Information (RFI); shortage of skilled labour force; shortage of materials; clarity and completeness of technical specifications; frequent changing orders during execution; drawings quality level; and rework.

It is clear, based on the outcomes, that the cultural background of individuals, and the prevalent practices within the environment in which they operate, are two critical factors in determining their motivation drivers. Hence, it is prudent to explore the dominant culture and values of the management workforce, in addition to the characteristics of the working environment, before trying to apply relevant motivational theories, or even implement new management strategies.

The results demonstrate that, within the geographical setting and cultural aspects of the sample surveyed, “tributes” and “pecuniary” may be interpreted to have the largest effect on the productivity of construction project managers.

The findings not only contribute to the overall body of knowledge related to the effect of the motivation phenomenon on the productivity of the construction operation, but can also be used to provide industry practitioners with guidance for focusing, acting upon, and controlling the significant demotivational factors affecting the efficiency of the construction project management force practicing in State.

Prefabricated prefinished volumetric construction (PPVC) is a game-changing construction method that transforms the fragmented site-based construction of buildings into an integrated production, integration and assembly of value-added volumetric building components. Where circumstances merit, the effective implementation of PPVC leverages significant gains in time, cost, quality, productivity and sustainability performance of construction projects. As PPVC is increasingly becoming mainstream, it is imperative to identify the critical success criteria (CSC) for measuring PPVC project success. The purpose of this study is to identify, rank and benchmark the CSC for measuring PPVC project success.

This study adopted a quantitative research design where the potential CSC for PPVC projects were evaluated. A comprehensive literature and pilot expert review identified 18 CSC for measuring PPVC project success. Based on a questionnaire survey of international PPVC experts, the 18 CSC were analyzed and prioritized using mean score analysis and weighting function.

Based on mean index assessment, the top five CSC for PPVC projects were identified as adherence to project schedules, meeting project quality specification, meeting safety requirements, client and owner satisfaction and cost savings and profitability. Further analysis grouped the 18 CSC into six principal success criteria (PSC), comprising time performance, cost performance, quality performance, environmental and safety performance, stakeholder satisfaction and supply chain performance. Based on weighted analysis of the six PSCs, quality performance, time performance and environmental and safety performance obtained the highest weights.

The research results are limited by the following limitations. First, although adequate, the sample size was relatively smaller. Second, the generalized analysis overlooked the geospatial sensitivities of the CSC.

The results constitute the first exclusive quantitative ranking and prioritization of the CSC for PPVC projects. The outputs of this study will enable practitioners to reliably and accurately evaluate the performance levels of PPVC projects. A framework of the CSC for measuring the success of PPVC projects was developed.

During a site-based certification program in a large county school district in the southeastern United States, 14 educators took 7 graduate courses on teaching emergent bilinguals. These educators made a shift in their practices and perceived a corresponding shift in their teaching efficacy. Ten years after the onset of this program, researchers returned to the site and conducted a mixed-methods study. The first purpose of this study was to explore educators’ perceptions regarding instructional practices for teaching emergent bilinguals after a decade had passed. The second purpose was to identify course features perceived by educators as having been most instrumental in fostering a long-term transformation in their teaching practices. Data were collected from a survey and interviews with the 14 educators (13 teachers and a program specialist) who had completed this certification program. Results indicated changes in their teaching methods and interactions with parents as well as heightened confidence for taking on leadership roles. Study participants identified professional learning communities, cyclical reflective activities, and action research projects as the course features that had been instrumental in transforming their practices for working with emergent bilinguals. Findings suggest that this site-based certification program was a catalyst for generating individual change that continued beyond program completion. By exploring this decade-long transformation, the current study provides implications for designing and implementing graduate certification courses that prepare in-service teachers to work effectively with emergent bilinguals.

Modular integrated construction (MiC) is a modern construction method innovating and reinventing the traditional site-based construction method. As it integrates advanced manufacturing principles and requires offsite production of volumetric building components, several factors and conditions must converge to make the MiC method suitable and efficient for building projects in each context. This paper aims to present a knowledge-based decision support system (KB-DSS) for assessing a project’s suitability for the MiC method.

The KB-DSS uses 21 significant suitability decision-making factors identified through literature review, consultation of experts and questionnaire surveys. It has a knowledge base, a DSS and a user interface. The knowledge base comprises IF-THEN production rules to compute the MiC suitability score with the efficient use of the powerful reasoning and explanation capabilities of DSS.

The tool receives the inputs of a decision-maker, computes the MiC suitability score for a given project and generates recommendations based on the score. Three real-world projects in Hong Kong are used to demonstrate the applicability of the tool for solving the MiC suitability assessment problem.

This study established the complex and competing significant conditions and factors determining the suitability of the MiC method for construction projects. It developed a unique tool combining the capabilities of expert systems and decision support system to address the complex problem of assessing the suitability of the MiC method for construction projects in a high-density metropolis.