# Identifying Energy-Use Behavior and Energy-Use Profiles of Hotel Guests
## 7 Conclusions  
The main goal of this study was to identify the energy-use profiles of hotel guests (i.e., energy-use survey participants in this study) to reduce hotel guests' energy consumption in hotel buildings. To achieve this, an integrated energy-use framework was developed and implemented in six stages: (1) integrating four energy-related behavior models of Motivation-Opportunity-Ability (MOA), Norm Activation Model (NAM), Theory of Planned Behavior (TPB), and Pro-environmental Behavior (PEB) to design the integrated energy-use framework of this study as presented in Figure 1; (2) developing eleven hypotheses and their relevant measures to investigate the relationship among the energy-related behavior models (i.e., MOA, NAM, TPB, and PEB) and hotel guests' energy-use behavior (i.e., MOA levels) as presented in Tables 1-3; (3) conducting an energy-use survey in Qualtrics and distributing the energy-use survey in Prolific (see Appendix A) to analyze the impact of each identified measure on hotel guests' energy-use profiles in hotel buildings; (4) performing energy behavior data analysis using Exploratory Factor Analysis (EFA) in SPSS software to analyze the energy-use survey questions and answers to determine the Motivation, Opportunity, and Ability (MOA) levels for each hotel guest in hotel buildings; (5) analyzing the energy behavior data using K-means clustering algorithm in RapidMiner software to determine energy-use behavior of hotel guests for each of the three MOA levels in hotel buildings; (6) analyzing the energy behavior data using the energy-use profile matrix shown in Figure 7 to identify energy-use profiles of hotel guests in hotel buildings. The results from the energy behavior data analysis for the energy-use behavior of hotel guests' Motivation level indicated that 50% of the hotel guests have Low to Medium-Low energy-use behavior and 21% have High energy-use behavior. This means that only 21% of the hotel guests (i.e., energy-use survey participants in this study) are highly motivated toward saving energy during their stay in hotel buildings. Additionally, the energy-use behavior of hotel guests' Opportunity level illustrated that 51% of the hotel guests have Low to Medium-Low energy-use behavior and 19% have High energy-use behavior. This indicates that only 19% of the hotel guests feel that they have the complete accessibility and controllability to hotel room energy systems (e.g., lighting, HVAC, appliances, and electronics) in hotel buildings to save energy consumption. Further, the energy-use behavior of hotel guests' Ability level determined that 53% of the hotel guests have Low or Medium-Low energy-use behavior and 27% have High energy-use behavior. This illustrates that \begin{table}
\begin{tabular}{c c} \hline \hline
**Energy-Use Profile** & **Incentives** \\ \hline Prone to Change & - \\ \hline Indifferent to Change & Free Soft Drink, Hotel Room Upgrade, Free VIP Parking, Free Roll-up Bed \\ \hline Resistant to Change & Meal Coupon for in Hotel Use, Discounts for Future Stays, Free Soft Drink Coupon, Travel Point on Hotel Reward Card \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Assigning proposed incentives to the hotel guests based on their energy-use profiles. about 27% of the hotel guests have perceived knowledge or energy-use knowledge to reduce their energy consumption in hotel buildings. On the other hand, the results from the energy behavior data analysis also illustrated that 85% of the hotel guests have Resistant to Change and Indifferent to Change energy-use profiles and only 15% of the hotel guests have Prone to Change energy-use profile. This shows that about 85% of the hotel guests have dark and moderate energy consumption behavior and only 15% of the only 15% of the hotel guests have good energy consumption behavior.