Factor analysis and reliability testing are two important statistical procedures used to analyze data, especially in the fields of social sciences, psychology, and marketing. Using factor analysis, researchers can identify underlying relationships between variables and categorize them into factors. Reliability analysis ensures that the scales used in the study maintain consistency across items. Both analyses are crucial for developing valid and reliable measurement instruments in research. The following step-by-step can help you.

1-Material For Tutoring

1.1. Conceptual Framework:
The existing literature review and research scholars have integrated the conceptual framework for this study.

1.2. Questionnaire Design and Measurement Scales:

Table 2. Questionnaire Design and Measurement Scales

Research Constructs	Items	Authors
Environmental Knowledge [ENK]	4	Kim and Stepchenkova (2020)
Environmental Awareness [ENA]	9	Wu et al. (2024)
Pro-Ecological Attitudes [PEA]	5	Uriely et al. (2007)
Environmentally Responsible Behavior [ERB]	12 (3 sub-dimensions)	Cheng et al. (2019) Davis et. (2009)
Total	31

Note: All 27 items were rated by a-5 Point Likert scale (i.e., 1= Strongly Disagree, 2= Disagree, 3= Neither Agree nor Disagree, 4=Agree, 5= Strongly Agree. Questionnaire items refer to Appendix.

1.3. SPSS Data:
You can download SPSS Data from this link. Download. If you have any problem with this download document. You can contact us to get it.

1.4. Step by Step: Factor Analysis and Reliability Test.
You can download step by step of factor analysis and reliability test below.
– Ensure your data is appropriate for factor analysis. This typically requires a large sample size and variables that are measured at the interval or ratio level.
– Check for missing values and outliers, as they can affect the results.

2. Sample Sizes and Rule of Thumbs:
2.1. Sample sizes:
– Aim for at least 3 items (Topliss et al., 1979) and 5-10 observations per variable (Peduzzi et al., 1996; Nasser et al., 2001). The consensus is that at least three indicators per latent variable are desirable for optimal ratio of indicators (Lee et al., 2013). Thus, per research variable should consist of 3, 5, 10, and 25 indicators for social science research.
– A minimum of 100 observations is often recommended for stable solutions. Sample sizes of 100 are often adequate (Reise et al., 2000)
2.2. The Rule of Thumbs:
Table 1 displays the general guidelines for factor analysis and reliability tests in SPSS.

Table 1. The Rule of Thumbs

Descriptions	Factor Analysis	Reliability Test
1. Factor Loading (FL)	> 0.60 or 0.70
2. KMO	$$\geq0.50$$
3. Eigenvalue	> 1.0
4. Cumulative %	> 60%
5. Item-total-Correlation		$$\geq0.50$$
6. Cronbach’s Alpha		> 0.60 or 0.70
Source: Hair et al., (2019).

3-Appendix: Questionnaire, Framework, and Step by Step.

4-Outputs of SPSS [Excel File]

5-SPSS-Tutoring: Factor Analysis and Reliability Test

6-References

1-Hair Jr, J., Black, W., Babin, B., & Anderson, R. (2019). Multivariate data analysis: A global perspective. Prentice Hall and Pearson.
2-Cheng, T.-M., Wu, H. C., Wang, J. T.-M., & Wu, M.-R. (2019). Community Participation as a mediating factor on residents’ attitudes towards sustainable tourism development and their personal environmentally responsible behaviour. Current Issues in Tourism, 22(14), 1764-1782. https://doi.org/10.1080/13683500.2017.1405383
3-Kim, M.-S., & Stepchenkova, S. (2020). Altruistic values and environmental knowledge as triggers of pro-environmental behavior among tourists. Current Issues in Tourism, 23(13), 1575-1580. https://doi.org/10.1080/13683500.2019.1628188
4-Lee, L. Y., Veasna, S., & Wu, W. Y. (2013). The effects of social support and transformational leadership on expatriate adjustment and performance: The moderating roles of socialization experience and cultural intelligence. Career Development International, 18(4), 377-415. https://doi.org/10.1108/CDI-06-2012-0062
5-Nasser, F., & Wisenbaker, J. (2001). Modeling the Observation-to-Variable Ratio Necessary for Determining the Number of Factors by the Standard Error Scree Procedure Using Logistic Regression. Educational and Psychological Measurement, 61(3), 387-403. https://doi.org/10.1177/00131640121971275
6-Peduzzi, P., Concato, J., Kemper, E., Holford, T. R., & Feinstein, A. R. (1996). A simulation study of the number of events per variable in logistic regression analysis. Journal of Clinical Epidemiology, 49(12), 1373-1379. https://doi.org/https://doi.org/10.1016/S0895-4356(96)00236-3
7-Reise, S. P., Waller, N. G., & Comrey, A. L. (2000). Factor analysis and scale revision. Psychological Assessment, 12(3), 287-297. https://doi.org/10.1037/1040-3590.12.3.287
8-Topliss, J. G., & Edwards, R. P. (1979). Chance factors in studies of quantitative structure-activity relationships. J Med Chem, 22(10), 1238-1244. https://doi.org/10.1021/jm00196a017
9-Wu, J., Ahmad, S. F., Ali, Y. A., Al-Razgan, M., Awwad, E. M., & Ayassrah, A. Y. B. A. (2024). Investigating the role of green behavior and perceived benefits in shaping green car buying behavior with environmental awareness as a moderator. Heliyon, 10(9).
10-Uriely, N., Reichel, A., & Shani, A. (2007). Ecological orientation of tourists: An empirical investigation. Tourism and Hospitality Research, 7(3/4), 161-175.http://www.jstor.org/stable/23745432
9-Davis, J. L., Green, J. D., & Reed, A. (2009). Interdependence with the environment: Commitment, interconnectedness, and environmental behavior. Journal of Environmental Psychology, 29(2), 173-180.