Key performance indicators (KPI) for the sustainability of building energy efficiency retrofit (BEER) in hotel buildings in China

Building energy efficiency retrofit (BEER) not only provides excellent opportunities to reduce overall energy consumption of buildings in a city but also encourages environmental protection, the rational use of resources, and occupants' healthcare, which all contribute towards the sustainability of existing buildings. However, there is a lack of effective performance indicators to measure the sustainability of BEER projects. The aim of this paper is to formulate a list of key performance indicators (KPI) for the sustainability assessment of BEER in hotel buildings.

First, a literature review and in‐depth interviews with industry experts and academic researchers were conducted, which filtered the performance indicators for assessing sustainability. Second, a questionnaire survey was conducted to collect data from various groups of experts to analyze the significance of the selected performance indicators. Finally, a model based on fuzzy set theory was designed to identify the key performance indicators (KPIs) for the sustainability of BEER.

Eight KPIs were identified based on fuzzy set theory in this study. They are: quality performance, hotel energy management, cost performance, project profitability, energy consumption and resources saving, health and safety, stakeholder satisfaction, and innovation and improvement.

The KPIs of sustainability of BEER identified for hotel buildings in China in this study can be useful reference for other similar research. However, with the different requirements for building types and building ownerships, the KPIs of sustainability of BEER for different buildings may be variable. The findings in this study may not be directly relevant to other types of building.

Key performance indicators for the sustainability assessment of BEER in hotel buildings in China are identified and analyzed in this study. The KPIs can help decision‐makers to identify an optimal solution between alternatives, which presents the maximum sustainability performance.