*2.3. Data Analysis*

The process of data processing and analysis is summarized in Figure 1. Subsequent steps are described in following sections, except for computing variables related to income, household type, education, and gender, which are presented in Appendix B.

**Figure 1.** Flowchart of the data processing and analysis.

## 2.3.1. Factor Analyses

For the behavior variables, principal axis factoring was used to reduce data, with the orthogonal rotation method varimax with Kaiser normalization used to produce independent factors with no multicollinearity. Kaiser-Meyer-Olkin (KMO) and Bartlett's test was used to test the adequacy of the sampling and produced a score of 0.831, which confirmed the sampling was adequate for factor analysis. Each PEB variable had a value of 0 to 4 (a value of 0 is for never and 4 is always), which were answers to how often participants engaged in 11 behaviors (Table 1). Coefficients below 0.4 were suppressed.


**Table 1.** Results of factor analysis of pro-environmental behavior variables.

Note: Extraction method: principal axis factoring. Rotation method: Varimax with Kaiser normalization.

The PEB factor analysis indicated that the 11 variables of environmentally significant behaviors could be reduced to just 3 factors related to clothing purchases (factor 1), household energy saving (factor 2), and produce purchases (factor 3). All three factors had an eigenvalue above 1.0 and the accumulated percentage of the explained variance was 59.917.

Each PEA variable had a value of 1 to 5 (value of 1 was "strongly disagree" and 5 was "strongly agree"), which were answers to how much participants agreed or disagreed with five statements (Table 2). Principal component analysis was used to reduce data. KMO and Bartlett's test produced a score of 0.850, which confirmed the sampling was adequate for factor analysis.

**Table 2.** Results of factor analysis of pro-environmental attitude variables.


The factor analysis confirmed that due to a high correlation between all variables, only one factor was needed. It had just over 62% of the explained variance and an eigenvalue of 3.1. The regression factor score was named the pro-environmental attitude (PEA factor score).
