## 4 Model Estimation and Results  
Starting from the conceptualized model of rational behavior theory described in the previous chapter, the following six proxy variables were considered success factors regarding the implementation of the model (Table 1): the strategic vision of the companies involved in ecological projects [54], the degree of regulation on green procurement [55], the level of competences [56], the integrated operational management [57], social responsibility [58], and the degree of innovation in the organic production process [59]. The independent variables described in Table 1 will be the latent variables of the model, while the reflexive dependent variable is \"the degree of competition\". This is described in Table 2 and is determined by three proxy variables: \"The number of competitors on the green procurement market\", \"the price offered for the green procurement versus the reference price on the market\", and \"the degree of concentration on the green procurement market\" [60]. Figure 2: Structural model that incorporates the results of rational behavior in modeling the impact of green procurement on competition. The questionnaires based on which the quantitative analysis was carried out, were addressed to both the management of the companies that built ecological projects, following the participation in the public procurement procedures, starting with the beginning of May 2019 and completed at the end of June of this year. The distribution of the respondents in the sample, depending on the function they hold within the selected company, is the following: Staff (22), Management (118), and Total (140). As it could be seen from the table above, the sample consisted of 140 managers and exectives from companies that are involved in environmental projects won through public procurement procedures, which have been interviewed directly, the questionnaire containing 30 questions. For the data collection, the simple random sampling method was used, between 1 May 2019-30 June 2019, using a questionnaire with both closed and open questions. The main problem in collecting the data was the reluctance of the respondents to complete the questionnaires. The main objectives pursued in carrying out the study were: determining the degree of regulation in the field of green procurement; identification of respondents' level of knowledge regarding green procurement, based on age, gender, educational level, and respondents' interests; evaluating the competences of the employees and evaluating the strategic vision, social responsibility, integrated operational management and the degree of innovation in the organic production process. Before starting the actual analysis of the model, the degree of significance of the variables of the conceptual model will be tested. For this, the Cronbach's Alpha and Dillon-Golsteins' \(\varrho\) coefficients will be calculated and interpreted [61]. Table 3 shows the values of these indicators. From Table 4 it can be observed that the VIF (variance inflection factor) values of the latent variables are lower than 5. According to [62], it results that there are no problems of collinearity between the independent variables in the model. It can also be observed that the values of the [PERSON]'s Alpha and Dillon-Golsteins' \(\varrho\) coefficients of the six independent variables have values greater than 0.7. Thus, we can conclude that the independent variables in the model are significant. The econometric analysis was performed using the PLS-SEM method. It consists of the analysis of two sub-models, respectively the measurement model \"outer model\" and the structural model \"inner model\". The PLS-SEM method was chosen for data analysis in the detriment of other similar methods, such as covariance-based structural equation modeling (CB-SEM), because it is less sensitive to asymmetric distributions, small samples, or the presence of multicollinearity, but, at the same time, it is even more robust [63; 64].