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The two stages approach has the advantage of estimating a more parsimonious model, since there is no need to represent LOCs (Hair, Sarstedt, Ringle & Gudergan, 2018 Sarstedt, Hair, Cheah, Becker & Ringle, 2019), besides being more adequate when the researcher's interest lies only on the relationships stating in the HOC (Becker, Klein & Wetzels, 2012 Sarstedt, Hair, Cheah, Becker & Ringle, 2019), which is the case of this model. In the second stage Figure 1b), the latent variable scores obtained in the first stage were used as indicators for the HOC construct. In the first stage (Figure 1a), the latent variable scores of LOCs were obtained in a model that did not consider the HOC. Model's parameters were estimated by the two stages approach (Becker, Klein & Wetzels, 2012 Hair, Sarstedt, Ringle & Gudergan, 2018 Sarstedt, Hair, Cheah, Becker & Ringle, 2019). The LOCs constructs are reflexive, while the HOC construct is formative and it mediates completely the influence of the LOCs in the intention of consuming organic products construct. Due to the conceptualization and operationalization of the hierarchical model, this research model is classified as a model of hierarchical latent variables of a reflexive-formative type (Chin, 1998 Becker, Klein & Wetzels, 2012 Sarstedt, Hair, Cheah, Becker & Ringle, 2019). In this case, relations between the HOC and the LOCs do not portray dependence, but hierarchy (Becker, Klein & Wetzels, 2012 Sarstedt, Hair, Cheah, Becker & Ringle, 2019), since the HOC does not exist without the LOCs. Also, this model presents one hierarchical latent variable, where environment awareness is a second-order construct (high order constructs-HOCs) constituted by first-order constructs (low order constructs-LOCs) (Hair, Sarstedt, Ringle & Gudergan, 2018).

According to suggestions from Hair, Hult, Ringle and Sarstedt (2017), it was opted for the use of partial least squares-structural equation modeling (PLS-SEM) in order to identify degrees of prediction and explanation of presented constructs.

The empirical research was developed through a quantitative methodology, with the use of multivariate data analysis.