Key considerations in the design of a one-stop-shop retrofit model
MetadataShow full item record
This item's downloads: 15 (view details)
McGinley, Orlaith, Moran, Paul, & Goggins, Jamie. (2020). Key considerations in the design of a One-Stop-Shop retrofit model. Paper presented at the Civil Engineering Research in Ireland (CERI) 2020, Cork, Ireland, 27-28 August.
The Irish Government’s Climate Action Plan emphasizes the need for increased retrofit activity within the built environment. As such, the plan has set targets for the completion of 500,000 energy efficient retrofits by 2030 at a rate of 50,000 per annum. Ireland’s current retrofit uptake rate is considered relatively low, at approximately 23,000 primarily shallow retrofits per annum. Thus, a significant step change is required to drive retrofit investment at a national scale, however, there are various barriers existing to such. Considering these targets, the establishment of a One-Stop-Shop (OSS) retrofit model has been identified in the Climate Action Plan as a key action. Such OSS models are emerging across Europe, with some OSS style models already introduced in Ireland. However, significant upscaling is required to deliver on the targets set. This paper provides a definition of a OSS model, highlights its benefits and how it responds to some of the barriers limiting retrofit uptake in Ireland. Secondly, this paper reviews existing literature and business models of existing European OSS models, with focus on the customer segment in these models. A brief discussion on the potential reach of such customer segments in the Irish context are presented, based on available statistics. The main finding of the paper is that there is limited published research on the characteristics and motivations of households engaging with existing OSS models and retrofitting in general in Ireland. A deeper understanding of such will be crucial to the success of the establishment of a OSS model in Ireland as a policy measure toward the achievement of the Climate Action Plan targets set.