Discriminant validity |
Fornell-Larcker criterion |
Values of the square roots of average variance extracted (AVE) must be higher than the values of the correlations of the constructs. |
Fornell and Larcker (1981)Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 18(3), 1–15. https://doi.org/10.1177/002224378101800313 https://doi.org/10.1177/0022243781018003...
and Ringle et al. (2014)Ringle, C. M., Silva, D. da, & Bido, D. de S. (2014). Modelagem de equações estruturais com utilização do SmartPLS. REMark-Revista Brasileira de Marketing, 13(2), 56–73. https://doi.org/10.5585/remark.v13i2.2717 https://doi.org/10.5585/remark.v13i2.271...
|
Normality test |
Collinearity statistic (variance inflation factor – VIF) |
VIF < 5.00 |
Hair et al. (2009)Hair, J. F., Jr., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2009). Análise multivariada de dados. (9. ed.). Bookman.
|
Goodness of fit indicators of the structural model |
Average variance extracted (AVE) |
AVE > 0.50 |
Henseler et al. (2009)Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. In R.R. Sinkovics, & P. N. Ghauri (ed.) New Challenges to International Marketing (Advances in International Marketing, (20)), Emerald Group Publishing Limited, Bingley. 277–319. https://doi.org/10.1108/S1474-7979(2009)0000020014 https://doi.org/10.1108/S1474-7979(2009)...
, Hair et al. (2014)Hair, J. F., Jr., Sarstedt, M., Hopkins, L., & Kuppelwieser, V. G. (2014). Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research. European Business Review, 26(2), 106–121. https://doi.org/10.1108/EBR-10-2013-0128 https://doi.org/10.1108/EBR-10-2013-0128...
, and Ringle et al. (2014)Ringle, C. M., Silva, D. da, & Bido, D. de S. (2014). Modelagem de equações estruturais com utilização do SmartPLS. REMark-Revista Brasileira de Marketing, 13(2), 56–73. https://doi.org/10.5585/remark.v13i2.2717 https://doi.org/10.5585/remark.v13i2.271...
|
Composite reliability (CR) |
CR > 0.70 |
Henseler et al. (2009)Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. In R.R. Sinkovics, & P. N. Ghauri (ed.) New Challenges to International Marketing (Advances in International Marketing, (20)), Emerald Group Publishing Limited, Bingley. 277–319. https://doi.org/10.1108/S1474-7979(2009)0000020014 https://doi.org/10.1108/S1474-7979(2009)...
, Hair et al. (2014)Hair, J. F., Jr., Sarstedt, M., Hopkins, L., & Kuppelwieser, V. G. (2014). Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research. European Business Review, 26(2), 106–121. https://doi.org/10.1108/EBR-10-2013-0128 https://doi.org/10.1108/EBR-10-2013-0128...
, and Ringle et al. (2014)Ringle, C. M., Silva, D. da, & Bido, D. de S. (2014). Modelagem de equações estruturais com utilização do SmartPLS. REMark-Revista Brasileira de Marketing, 13(2), 56–73. https://doi.org/10.5585/remark.v13i2.2717 https://doi.org/10.5585/remark.v13i2.271...
|
R square (R2) |
Values greater than zero R2 > 0.00 |
Cronbach’s alpha (CA) |
CA > 0.70 |
Predictive relevance |
Predictive relevance (Q²) |
Values greater than zero Q2 > 0.00 |
Effect size |
Effect size (f²) |
Values of 0.02, 0.15, and 0.35 are considered small, medium, and large, respectively. |
Standardized coefficients |
Student’s t test (significance of investigated relations) |
t > 1.96
p < 0.05
|
Path coefficients |
Values (positive or negative) in a range between −1 and +1. |