Detecting defects in UK new-build housing: a learning perspective

House builders play a key role in controlling the quality of new homes in the UK. The UK house building sector is, however, currently facing pressures to expand supply as well as conform to tougher low carbon planning and Building Regulation requirements; primarily in the areas of sustainability. There is growing evidence that the pressure the UK house building industry is currently under may be eroding build quality and causing an increase in defects. It is found that the prevailing defect literature is limited to the causes, pathology and statistical analysis of defects (and failures). The literature does not extend to examine how house builders individually and collectively, in practice, collect and learn from defects experience in order to reduce the prevalence of defects in future homes. The theoretical lens for the research is organisational learning. This paper contributes to our understanding of organisational learning in construction through a synthesis of current literature. Further, a suitable organisational learning model is adopted. The paper concludes by reporting the research design of an ongoing collaborative action research project with the National House Building Council (NHBC), focused on developing a better understanding of house builders’ localised defects analysis procedures and learning processes.

Developing temporary manufacturing facilities for residential building: a case of the modern flying factory

The building industry is often berated for its short comings in meeting up with the demand for the provision of new housing. Addressing the need for new housing stock is a challenge that has led to debates among professional bodies, the construction sector, housing industry and government. The introduction of new manufacturing technologies is often offered as a solution, but the challenges of increasing the amount of off-site construction in residential building are well known and well-rehearsed. The modern flying factory (MFF) is a concept that involves the manufacture of specific components or modules in temporary off- or near- site locations using relatively simple and quick to set up and dismantle technologies and processes. The aim is to produce short batches and hence achieve some of the benefits of off-site manufacture on a much smaller scale than in dedicated factory environments. A case study of a modern flying factory being set up to produce pre-assembled utility cupboards for a large residential development in London is presented, involving participant observation and informal interviews with key actors on the design and operationalising of the process. The case reveals that although there are costs, efficiency and health and safety benefits to using MFF approaches, there are also challenges to overcome over the time required to set up and establish the process for relatively short runs, and in evaluating whether the MFF or traditional site based production is most effective for particular aspects of projects.

A comparison of greenhouse gas emissions in the residential sector of major Canadian cities

One of the most significant sources of greenhouse gas (GHG) emissions in Canada is the buildings sector, with over 30% of national energy end-use occurring in buildings. Energy use must be addressed to reduce emissions from the buildings sector, as nearly 70% of all Canada’s energy used in the residential sector comes from fossil sources. An analysis of GHG emissions from the existing residential building stock for the year 2010 has been conducted for six Canadian cities with different climates and development histories: Vancouver, Edmonton, Winnipeg, Toronto, Montreal, and Halifax. Variation across these cities is seen in their 2010 GHG emissions, due to climate, characteristics of the building stock, and energy conversion technologies, with Halifax having the highest per capita emissions at 5.55 tCO2e/capita and Montreal having the lowest at 0.32 tCO2e/capita. The importance of the provincial electricity grid’s carbon intensity is emphasized, along with era of construction, occupancy, floor area, and climate. Approaches to achieving deep emissions reductions include innovative retrofit financing and city level residential energy conservation by-laws; each region should seek location-appropriate measures to reduce energy demand within its residential housing stock, as well as associated GHG emissions.

Housing provision in 21st century Europe

European housing markets exhibited considerable volatility so far in the 21st century while affordability worsened for many. Boom-bust has had greater housing impacts than any specific housing policy, which illustrates the difficulty in policy terms of seeing housing in isolation and the central significance of interlinked relationships between housing, the economy and financial markets. Europe historically invented a powerful set of interventionist tools to alter housing circumstances but, as the overview of rental markets here indicates, today they have mixed success. Examples of what to avoid in policy are at least as common as exemplars.

Spatial housing economics: a survey

This introduction to the Virtual Special Issue surveys the development of spatial housing economics from its roots in neo-classical theory, through more recent developments in social interactions modelling, and touching on the role of institutions, path dependence and economic history. The survey also points to some of the more promising future directions for the subject that are beginning to appear in the literature. The survey covers elements hedonic models, spatial econometrics, neighbourhood models, housing market areas, housing supply, models of segregation, migration, housing tenure, sub-national house price modelling including the so-called ripple effect, and agent-based models. Possible future directions are set in the context of a selection of recent papers that have appeared in Urban Studies. Nevertheless, there are still important gaps in the literature that merit further attention, arising at least partly from emerging policy problems. These include more research on housing and biodiversity, the relationship between housing and civil unrest, the effects of changing age distributions - notably housing for the elderly - and the impact of different international institutional structures. Methodologically, developments in Big Data provide an exciting framework for future work.

Reducing defects through organizational learning within a Housing Association environment

Housing Associations (HAs) contribute circa 20% of the UK’s housing supply. HAs are however under increasing pressure as a result of funding cuts and rent reductions. Due to the increased pressure, a number of processes are currently being reviewed by HAs, especially how they manage and learn from defects. Learning from defects is considered a useful approach to achieving defect reduction within the UK housebuilding industry. This paper contributes to our understanding of how HAs learn from defects by undertaking an initial round table discussion with key HA stakeholders as part of an ongoing collaborative research project with the National House Building Council (NHBC) to better understand how house builders and HAs learn from defects to reduce their prevalence. The initial discussion shows that defect information runs through a number of groups, both internal and external of a HA during both the defects management process and organizational learning (OL) process. Furthermore, HAs are reliant on capturing and recording defect data as the foundation for the OL process. During the OL process defect data analysis is the primary enabler to recognizing a need for a change to organizational routines. When a need for change has been recognized, new options are typically pursued to design out defects via updates to a HAs Employer’s Requirements. Proposed solutions are selected by a review board and committed to organizational routine. After implementing a change, both structured and unstructured feedback is sought to establish the change’s success. The findings from the HA discussion demonstrates that OL can achieve defect reduction within the house building sector in the UK. The paper concludes by outlining a potential ‘learning from defects model’ for the housebuilding industry as well as describing future work.

Detecting defects in the UK new-build housing sector: a learning perspective

Rapid growth in the production of new homes in the UK is putting build quality under pressure as evidenced by an increase in the number of defects. Housing associations (HAs) contribute approximately 20% of the UK’s new housing supply. HAs are currently experiencing central government funding cuts and rental revenue reductions. As part of HAs’ quest to ramp up supply despite tight budget conditions, they are reviewing how they learn from defects. Learning from defects is argued as a means of reducing the persistent defect problem within the UK housebuilding industry, yet how HAs learn from defects is under-researched. The aim of this research is to better understand how HAs, in practice, learn from past defects to reduce the prevalence of defects in future new homes. The theoretical lens for this research is organizational learning. The results drawn from 12 HA case studies indicate that effective organizational learning has the potential to reduce defects within the housing sector. The results further identify that HAs are restricting their learning to focus primarily on reducing defects through product and system adaptations. Focusing on product and system adaptations alone suppresses HAs’ abilities to reduce defects in the future.

Are mortgage lenders guilty of the housing bubble? A UK perspective

Existing theoretical models of house prices and credit rely on continuous rationality of consumers, an assumption that has been frequently questioned in recent years. Meanwhile, empirical investigations of the relationship between prices and credit are often based on national-level data, which is then tested for structural breaks and asymmetric responses, usually with subsamples. Earlier author argues that local markets are structurally different from one another and so the coefficients of any estimated housing market model should vary from region to region. We investigate differences in the price–credit relationship for 12 regions of the UK. Markov-switching is introduced to capture asymmetric market behaviours and turning points. Results show that credit abundance had a large impact on house prices in Greater London and nearby regions alongside a strong positive feedback effect from past house price movements. This impact is even larger in Greater London and the South East of England when house prices are falling, which are the only instances where the credit effect is more prominent than the positive feedback effect. A strong positive feedback effect from past lending activity is also present in the loan dynamics. Furthermore, bubble probabilities extracted using a discrete Kalman filter neatly capture market turning points.