Study of hotel energy performance using data envelopment analysis

As hotel energy consumption is affected by many technical, operational and managerial factors, it is often not possible to use the traditional benchmarking methods such as energy utilization index (EUI) in a meaningful way. This research applies data envelopment analysis (DEA) for assessing hotel energy performance in Hong Kong. A simple and basic DEA model, known as the input-oriented Charnes-Cooper-Rhodes (CCR-i) model under constant returns to scale (CRS), was developed for the evaluation of energy consumption of a sample hotel. The model was set up using a linear programming methodology to transform multiple input variables (electricity use, Towngas use, water use, outdoor temperature and relative humidity) into multiple output variables (numbers of room nights, room guests, and food & beverage covers). It is found that the DEA model can identify the relative efficiencies of different decision making units (DMU) (which are the hotel food & beverage outlets). DEA can accommodate a multiplicity of inputs and outputs; it also takes into consideration returns to scale in calculating efficiency, allowing for the concept of increasing or decreasing efficiency based on size and output levels. A drawback of this technique is that model specification and inclusion/exclusion of variables can affect the results.