Abstract

As a representative service industry, the hotel industry has a complex water-use structure and high water consumption. It is of great significance to investigate the mechanisms determining hotel water-use behavior for demand analysis, as this would make it possible to enhance water-use efficiency and enact targeted water-saving measures. Using Spearman’s hierarchical correlation coefficient, the multi-layer perceptron (MLP) neural network model, and the structural equation model (SEM), in this study, we explored the mechanism determining hotel consumers’ water-use behavior from different dimensions and constructed a typical water-use behavior model based on the MLP-SEM model. In terms of individual water-use behavior, the results showed that individual characteristics, water-conservation awareness, and consumption behavior possessed significant differences regarding their influence on and correlation with various water-use behaviors. The most relevant factors influencing each behavior, namely washing up, hand washing, and drinking, were daily stay in the hotel, education, and income. Gender had the greatest impact on bathing and toilet-flushing water-use behaviors. The importance of daily stay in the hotel was 0.181, which meant that this was the most significant factor influencing the direct water-use behavior of hotel guests. The following factors were identified: hotel type, income, age, and gender. Typical individual characteristics had a significant impact on main water-use behaviors, whereas typical consumption behaviors had no effect. These results can provide a foundation for relevant research in other industries and serve as a basis for a prediction model of water consumption in hotels based on water-use behavior. Furthermore, they provide a basis for the delicate management of water-use behavior in hotels, making it possible to effectively guide the public to consciously adopt water-saving habits, thus improving water efficiency, which could alleviate the shortage of water resources in the long-term.

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