Analysis and modelling of social housing repair and maintenance costs: A UK case study. (15th July 2022)

• Record Type: Journal Article
• Authors: Fulcher, Matthew; Edwards, David John; Lai, Joseph H.K.; Thwala, Wellington Didibhuku; Hayhow, Sue
• Is Part Of: Journal of building engineering. Volume 52(2022)
• Publication Date: 2022-07-15
• Subjects: UK Social housing -- Repairs and maintenance -- Asset management -- Cost -- Cross comparative analysis -- Statistical analysis -- Linear regression; Building -- Periodicals; 690.05
• DOI: 10.1016/j.jobe.2022.104389
• Languages: English
• ISSNs: 2352-7102

Abstract

Abstract: Effective use of resources for maintaining social housing has long been a common goal of public bodies across the world. However, maintenance cost data is quintessentially sensitive and thus difficult to obtain, rendering the dearth of empirical maintenance cost studies on social housing. This research investigates the complexities of repair and maintenance (R&M) associated with social housing and specifically, develops benchmark indicators for such works. The ambition being to provide a knowledge sharing analysis of costs expended that allows a social housing provider to learn from past works undertaken with a view to optimising future practice. A mixed philosophical approach is adopted that combines elements of both pragmatism and interpretivism. A case study and participant action researcher (PAR) strategy is adopted where the lead researcher is employed within a repairs and maintenance (R&M) department of a UK Housing Association. Longitudinal quantitative R&M cost data is analysed using summary statistical, regression analysis and performance statistics (to measure predictive accuracy). Focus groups are held with housing practitioners and the cross-sectional qualitative discourse is analysed using content analysis to explain emergent patterns and trends accrued form the quantitative analysis conducted. This research identified that R&M works for a UK Housing Association follow a non-parametric distribution that is heavily positively skewed. Housing Associations without sufficient planned investment will see more sporadic distributions leading to less cost certainty. Furthermore, linear regression analysis provides an accurate fit of the cumulative R&M spend with very little deviation between actual and predicted R&M costs; hence, accurate forecasting is possible for Housing Associations. Finally, the sub-categorisation of works packages has indicated that certain work packages expend greater funds (often considered as being outlier costs) than others but linear regression models did not fit all sub-categorisations accurately. This research presents a unique insight into R&M costs incurred on social housing by a UK Housing Association to provide a vignette of contemporary practice and costs incurred. The work proves useful to housing associations, contractors and policy makers who seek to optimally balance cost and service delivered for residents. Highlights: A case study analysis and modelling of social housing repair and maintenance costs is presented. Real life maintenance cost data for social housing is analysed using regression analysis and performance statistics. Qualitative focus groups are also used to further explain the cost data analysed. The paper presents a rare and unique insight into usually confidential cost data.