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


Autoria(s): Hopkin, Tony; Lu, Shu-Ling; Phil, Rogers; Sexton, Martin
Data(s)

2016

Resumo

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.

Formato

text

Identificador

http://centaur.reading.ac.uk/64080/1/Hopkin%20et%20al%202016%20CME.pdf

Hopkin, T., Lu, S.-L. <http://centaur.reading.ac.uk/view/creators/90003776.html>, Phil, R. and Sexton, M. <http://centaur.reading.ac.uk/view/creators/90001121.html> (2016) Detecting defects in the UK new-build housing sector: a learning perspective. Construction Management and Economics, 34 (1). pp. 35-45. ISSN 0144-6193 doi: 10.1080/01446193.2016.1162316 <http://dx.doi.org/10.1080/01446193.2016.1162316>

Idioma(s)

en

Publicador

Taylor & Francis

Relação

http://centaur.reading.ac.uk/64080/

creatorInternal Lu, Shu-Ling

creatorInternal Sexton, Martin

10.1080/01446193.2016.1162316

Tipo

Article

PeerReviewed