## 5 Results and Discussion  
### Demographic Analysis  
The absolute values of skewness coefficients of each measurement item of each variable in the sample are all less than 2, which means that the scale data is close to the normal distribution, so the sample passes the normality test. This study uses an independent-sample \(t\)-test and one-way analysis of variance to analyze the differences in residents' energy-saving behavior and attribution style in terms of demographic characteristics. The results are shown in Table 1.  
Table 1 shows that efficiency investment and energy-saving behaviors have significant differences in educational level and habit adjustment. Energy-conservation behaviors have significant differences in marital status, and attribution styles have significant differences in age, educational level, and marital status. Specifically, gender had no significant effect on any of the three (HAB, EIB, and attribution style). However, the comparison of average values shows that the implementation level of HAB among women is higher than that of men, which indicates that women are more likely to focus on saving energy daily and choosing an energy-efficient lifestyle. Some scholars [16; 50] also believed that women paid more attention to daily energy-saving, mainly considering the differences in social roles and lifestyles between men and women. Energy-saving behaviors show an \"inverted U-shaped\" trend with increasing age. Residents aged 46 to 59 have the highest level of \begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & **Demographic Variables** & **Proportion** & **HAB** & **EIB** & **Attribution Style** \\ \hline \multirow{3}{*}{Gender} & Male & 48.56\% & 3.567 & 3.772 & 0.860 \\  & Female & 51.44\% & 3.662 & 3.778 & 0.780 \\  & F & & 0.357 & 0.611 & 1.832 \\ \hline \multirow{3}{*}{Age} & 18–25 years old & 16.91\% & 3.502 & 3.758 & 0.420 \\  & 26–35 years old & 20.49\% & 3.629 & 3.722 & 0.340 \\  & 36–45 years old & 38.68\% & 3.635 & 3.810 & 1.090 \\  & 46–59 years old & 22.25\% & 3.662 & 3.775 & 1.090 \\  & Over 60 years old & 1.67\% & 3.575 & 3.775 & 1.100 \\  & F & & 1.143 & 0.436 & 7.753 *** \\ \hline \multirow{3}{*}{Education} & High school or below & 12.12\% & 3.610 & 3.627 & 1.180 \\  & Technical secondary school & & 24.80\% & 3.673 & 3.702 & 0.870 \\  & or college degree & 47.29\% & 3.622 & 3.829 & 0.830 \\  & Postgraduate degree & & 15.79\% & 3.517 & 3.835 & 0.450 \\  & (Master or doctoral degree) & & 1.282 & 3.074 * & 3.246 * \\ \hline \multirow{3}{*}{Marital status} & Unmarried & 23.05\% & 3.493 & 3.684 & 0.250 \\  & Married & 73.84\% & 3.659 & 3.804 & 0.970 \\  & Divorced & 3.11\% & 3.558 & 3.791 & 1.470 \\  & F & & 4.050 * & 2.035 & 13.902 *** \\ \hline \hline \end{tabular} Note: *** \(p<\) 0.001; * \(p<\) 0.05. HAB indicates habits adjustment energy-saving behavior and EIB indicates efficiency investment energy-saving behavior.  
\end{table} 
Table 1: Demographic analysis of energy-saving behaviors and attribution style. HAB, and residents aged 36 to 45 have the highest level of EIB. Existing studies have not reached a unified conclusion on the impact of education level on energy-saving behavior. In this study, energy-saving behavior is divided into HAB and EIB, and it is found that residents' education level significantly affects their efficiency investment and energy-saving behavior. Education level significantly affects residents' EIB (F = 3.074, \(p\) < 0.05). The higher the education level, the higher the implementation level of EIB. As for HAB, residents with technical secondary school or college degrees scored the highest, while residents with postgraduate degrees scored the lowest. For attribution style, it shows completely significant age differences (F = 7.753, \(p\) < 0.001) and marital status (F = 13.902, \(p\) < 0.001) and differs significantly in education (F = 3.246, \(p\) < 0.05). As can be seen from the results in Table 1, compared with women, men's attribution style is more positive.