The OCAI model questionnaire applied to the respondents has been simulated into SPSS according to the regression analysis, the results being presented below. This approach aims algorithm of Likert scale conversion (1–7) and converted every number to scale 100 on every OCAI dimension. The OCAI model for negentropic organization taken into consideration use the algorithm formula calculus:
$${NOC}_{\alpha }=\sum _{r=1}^{R}(\frac{\sum _{i=1}^{6}\frac{{\beta }_{ij}}{\sum {\beta }_{ij}}x100\%}{i})/R$$
1
where,
NOC\(\alpha\) – negentropic organizational culture profile
\(\alpha\) – number of the organizational culture (1–4)
r – number of respondents for each of the organizational culture of the OCAI model
R – number of respondents for all the questions of the OCAI model
βij – score into 100 on each OCAI dimension
i – the six dimensions of the questionnaire
j – the four types of cultures (group culture / family / clan / human relationsoriented culture, adhoc culture / in development / innovation / open system, hierarchical culture / internal process / based on rules, rational / market culture / based on objectives)
Existing group / family / clan / human relations oriented culture (A)
Based on the correlative analysis indicating a directly linear and statistically significant proportional relationship between the existing group culture scores and seniority (r = 0.104; p = 0.292), position (r = 0.114; p = 0.274), age (r = 0.145; p = 0.222) and study level (r = 0.155; p = 0.207) the independent variables were introduced in a multiple linear regression model.
Model OCAI 1A, which contains all four variables has an explanatory capacity of 7.3% of the experimental distribution of group culture scores (R square = 0.073) and increases the explanatory capacity to 7.3% (R square change = 0.073) but statistically insignificant p (F change) = 0.743 (failure to reach the threshold of statistical significance can be attributed to the small number of subjects). Model OCAI 2A, obtained by removing the variable studies level, has an explanatory capacity of 7.1% (R square = 0.071) and the reduction of the explanatory capacity of 0.2% (R square change = 0.002). Not statistically significant for p (F change) = 0.820. Model OCAI 3A, obtained by removing the variables level of education and seniority has an explanatory capacity of 4.9% (R square = 0.049) and the reduction of explanatory capacity of 2.2% (R square change = 0.022). Not statistically significant for p (F change) = 0.445. Model OCAI 4A, obtained by removing the variables level of education, seniority and job position has an explanatory capacity of 2.1% (R square = 0.021) and the reduction of explanatory capacity of 2.8% (R square change = 0.028). Not statistically significant for p (F change) = 0.379. Based on the regression equation determined for the OCAI model 1, the highest explanation of the variation of the score obtained for the existing group culture R2 = 0.073 (7.3%) is obtained.
In this case, the null hypothesis is that the respective regression coefficients are equal to 0 while the alternative hypothesis is that they are different from 0. The test result is displayed in the columns of the regression analysis in the form of a test whose values (t = Coefficient B / standard error B) expresses the significance of the difference between the respective coefficients and 0. For all four models, coefficients have statistically insignificant values (Sig. is greater than 0.05). This aspect allows to admit the conclusion that all four coefficients are not significantly different from 0 and therefore the predictor variables are not important enough for the appreciation of the criterion variable. The lack of statistical significance for the F test can be attributed to the small number of subjects.
Regression equation:
Model OCAI 1A. Existing group culture score = 120.705 + 16.77 * seniority + 13.21 *
job position − 25.8 * age + 7.99 * education level (2)
Model OCAI 2A. Existing group culture score = 140 + 16.14 * seniority + 16.21 *
job position − 28.89 * age (3)
Model OCAI 3A. Existing group culture score = 171.190 + 15.33 * job position – 24.82 * age (4)
Model OCAI 4A. Existing group culture score = 196.757–18 * age (5)
It is observed that the R2 changes for the models obtained by eliminating the independent variables are statistically insignificant (Sig. F change).
The conclusion would be that for the Existing group / family / clan / human relations oriented culture, a linear regression model cannot be determined based on the input factors. There are no individual correlation relationships between certain factors and group culture.
Existing adhoc culture / in development / innovation / open system (B)
Based on the correlative analysis indicating a directly linear and statistically significant proportional relationship between existing adhoc culture scores and seniority (r = 0.012; p = 0.474), position (r = 0.222; p = 0.121), age (r = 0.077; p = 0.343) and study level (r = 0.042; p = 0.413) independent variables were introduced in a multiple linear regression model.
The Model OCAI 1B, which contains all four variables, has an explanatory capacity of 5.5% of the experimental distribution of the existing adhoc culture scores (R square = 0.055) and increases the explanatory capacity to 5.5% (R square change = 0.055), but statistically insignificant p (F change) = 0.834. Model OCAI 2B, obtained by removing the age variable, has an explanatory capacity of 5.4% (R square = 0.054) and a reduction of the explanatory capacity of 0.1% (R square change = 0.001) and without statistical significance for p (F Change) = 0.902. Model OCAI 3B, obtained by removing the seniority and age has an explanatory capacity of 5.3% (R square = 0.053) and the reduction of explanatory capacity of 0.1% (R square change = 0.001). Not statistically significant for p (F change) = 0.885. Model OCAI 4B, obtained by removing the variables seniority, age and level of education has an explanatory capacity of 4.9% (R square = 0.049) and the reduction of explanatory capacity of 0.5% (R square change = 0.005). Not statistically significant for p (F change) = 0.719. Based on the regression equation determined for the model OCAI 1B, the highest explanation of the variation of the score obtained for the existing adhoc culture R2 = 0.055 (5.5%) is obtained.
The lack of statistical significance obtained from the ANOVA analysis for all models indicates that the observed data does not allow the identification of valid models. The four variables taken together do not explain statistically significant variation in existing ad hoc culture scores. In the regression analysis, for all four models the coefficients have statistically insignificant values (Sig. Is greater than 0.05) which leads to the conclusion that all four coefficients are not significantly different from 0 and therefore the predictor variables are not important for estimating the variable criterion.
Regression equation:
Model OCAI 1B. Adhoc culture existent score = 99.833–1.5 * seniority + 13.29 *
job position − 2.06 * age – 7.57 * education level (6)
Model OCAI 2B. Adhoc culture existent score = 96.314 + 13.25 * job position – 2.31 *
seniority − 7.26 * education level (7)
Model OCAI 3B. Adhoc culture existent score = 91.283 + 12.36 * job position – 5.91 *
education level (8)
Model OCAI 4B. Adhoc culture existent score = 82.576 + 10.64 * job position (9)
The lack of significance was also present in the R2 changes for the models obtained by eliminating the independent variables.
In conclusion, for the Existing adhoc / developing / innovation / open system culture, a linear regression model cannot be determined based on the input factors. There are no individual correlation relationships between certain factors and adhoc culture.
Existing hierarchical culture / internal process / based on rules (C)
Based on the correlative analysis indicating a directly linear and statistically significant proportional relationship between the scores of the existing hierarchical culture and seniority (r = 0.043; p = 0.410), position (r = 0.345; p = 0.031), age (r = 0.120; p = 0.265) and study level (r = 0.139; p = 0.232) independent variables were introduced in a multiple linear regression model.
Model OCAI 1C contains all four variables and has an explanatory capacity of 26.3% of the experimental distribution of existing hierarchical culture scores (R square = 0.263) and increases the explanatory capacity to 26.3% (R square change = 0.263) but insignificant from a statistical point of view, p (F change) = 0.095. Model OCAI 2C, obtained by removing the age variable, has an explanatory capacity of 26.3% (R square = 0.263) and a reduction of the explanatory capacity of 0% (R square change = 0.000) and without statistical significance for p (F change) = 0.966. Model OCAI 3C, obtained by removing the variables age and seniority has an explanatory capacity of 23.3% (R square = 0.233) and the reduction of the explanatory capacity by 3% (R square change = 0.030). Not statistically significant for p (F change) = 0.312. Based on the determined regression equation, for models OCAI 1C and 2C the highest explanations of the variation score obtained for the existing hierarchical culture R2 = 0.263 (26.3%) were obtained.
The lack of statistical significance obtained following the ANOVA analysis for the first model indicates that the observed data does not allow the identification of valid models. The four variables taken together do not explain statistically significant variation in the scores of the existing hierarchical culture. For models OCAI 2C and 3C, statistical significance was obtained, which indicates that the observed data allow us to identify valid models. The three variables taken together (education level, age and position) explain statistically significant variation in the scores of the existing hierarchical culture. In the regression analysis, the first two models have coefficients with statistically insignificant values (Sig. is greater than 0.05) aspect that allows to conclude that all four coefficients are not significantly different from 0 and therefore the predictor variables are not representative for estimating the variable criterion. The model OCAI 3C approaches statistical significance (p = 0.000, p = 0.011 and p = 0.055) and therefore the predictor variables (job position and level of education) are important enough to evaluate the variable criterion.
Regression equation:
Model OCAI 1C. Existing hierarchical culture score = 174.715–0.5 * seniority + 33.52 *
job position – 15.64 * age – 41.23 * education level (10)
Model OCAI 2C. Existing hierarchical culture score = 173.534 + 33.5 * job position – 15.72 *
age − 41.12 * education level (11)
Model OCAI 3C. Existing hierarchical culture score = 139.242 + 27.4 * job position – 31.95 *
education level (12)
The lack of significance was also present in the R2 changes for the models obtained by eliminating the independent variables.
Existing rational / market / goalbased culture (D)
Based on the correlative analysis indicating a directly linear and statistically significant proportional relationship between the existing rational culture scores and seniority (r = 0.105; p = 0.291), position (r = 0.379; p = 0.019), age (r = 0.025; p = 0.447) and study level (r = 0.080; p = 0.338) independent variables were introduced in a multiple linear regression model.
Model OCAI 1D, which contains all four variables has an explanatory capacity of 22.3% of the experimental distribution of existing rational culture scores (R square = 0.223) and increases the explanatory capacity to 22.3% (R square change = 0.223) and statistically insignificant p (F change) = 0.161. The model OCAI 2D, obtained by removing the seniority variable, has an explanatory capacity of 21% (R square = 0.210) and a reduction of the explanatory capacity of 1.3% (R square change = 0.013) and without statistical significance for p (F change) = 0.526. Model OCAI 3D, obtained by removing the variables seniority and level of education has an explanatory capacity of 16.7% (R square = 0.167) and the reduction of explanatory capacity of 4.4% (R square change = 0.044). Not statistically significant for p (F change) = 0.242. Model OCAI 4D, obtained by removing the variables seniority, level of education and age has an explanatory capacity of 14.4% (R square = 0.144) and the reduction of explanatory capacity of 2.3% (R square change = 0.023). Not statistically significant for p (F change) = 0.397. Based on the regression equation determined for model 1, the greatest explanation of the variation of the score obtained for the existing rational culture R2 = 0.223 (22.3%) is obtained.
The lack of statistical significance obtained from the ANOVA analysis for the first three models indicates that the observed data does not allow the identification of valid models. The four variables taken together do not explain statistically significant variation in the scores of the existing hierarchical culture. For model OCAI 4D, statistical significance was obtained, which indicates that the observed data allow us to identify a valid model. The job position variable explains statistically significant variation in the scores of the existing rational culture.
In the regression analysis, the first three OCAI models have coefficients with statistically insignificant values (Sig. is greater than 0.05) which would allow the conclusion that all four coefficients are not significantly different from 0 and therefore the predictor variables are not important for estimating criterion variable. The model OCAI 4 has statistical significance (p = 0.000 and p = 0.039) and therefore the predictor variable (job position) is important for estimating the variable criterion.
Regression equation:
Model OCAI 1D. Existing rational culture score = 202.746–14.77 * seniority – 60.02 *
job position + 43.5 * age + 40.81 * education level (13)
Model OCAI 2D. Existing rational culture score = 167.974–60.38 * job position + 41.03 *
age + 43.9 * education level (14)
Model OCAI 3D. Existing rational culture score = 256.220–43.71 * job position + 23.17 *
age (15)
Model OCAI 4D. Existing rational culture score = 286.836–38.66 * job position (16)
The lack of significance was also present in the R2 changes for the models obtained by eliminating the independent variables.
Preferred group / family / clan / human relations oriented culture (E)
Based on the correlative analysis indicating a directly linear and statistically significant proportional relationship between the scores of the preferred group culture and seniority (r = 0.287; p = 0.062), position (r = 0.305; p = 0.050), age (r = 0.160; p = 0.199) and study level (r = 0.220; p = 0.122) the independent variables were introduced in a multiple linear regression model.
Model OCAI 1E, which contains all four variables has an explanatory capacity of 22.8% of the experimental distribution of the scores of the preferred group culture (R square = 0.228) and increases the explanatory capacity to 22.8% (R square change = 0.228) but statistically insignificant p (F change) = 0.152. Model OCAI 2E, obtained by removing the study level variable, has an explanatory capacity of 22.1% (R square = 0.221) and a reduction of the explanatory capacity of 0.6% (R square change = 0.006) and without statistical significance for p (F change) = 0.652. Model OCAI 3E, obtained by removing the variables level of education and age has an explanatory capacity of 17.5% (R square = 0.175) and the reduction of the explanatory capacity of 4.6% (R square change = 0.046). Not statistically significant for p (F change) = 0.227. Model OCAI 4E, obtained by removing the variables level of education, age and seniority has an explanatory capacity of 9.3% (R square = 0.093) and the reduction of explanatory capacity of 8.2% (R square change = 0.082). Not statistically significant for p (F change) = 0.113. Based on the regression equation determined for models OCAI 1E and 2E, the highest explanations of the variation of the score obtained for the preferred group culture R2 = 0.221 (22.1%) were obtained.
The lack of statistical significance obtained from the ANOVA analysis for the four models indicates that the observed data does not allow the identification of valid models. The four variables (level of education, seniority, job position and age) taken together do not explain statistically significant variation in the scores of the preferred group culture. In the regression analysis, for all four models, the coefficients have statistically insignificant values (Sig. is greater than 0.05) and consequently, all four coefficients are not significantly different from 0 and therefore the predictor variables are not important enough to determine the variable criterion.
Regression equation:
Model OCAI 1E. Preferred group culture score = 140.744 + 10.26 * seniority – 14.4 *
job position + 12.89 * age + 5.47 * education level (17)
Model OCAI 2E. Preferred group culture score = 152.570 + 9.79 * seniority – 12.35 *
job position + 10.77 * age (18)
Model OCAI 3E. Preferred group culture score = 162.612 + 11.64 * seniority – 10 *
job position (19)
Model OCAI 4E. Preferred group culture score = 189–10 * job position (20)
The lack of significance was also present in the R2 changes for the models obtained by eliminating the independent variables.
Preferred adhoc culture / in development / innovation / open system (F)
Based on the correlative analysis indicating a directly linear and statistically significant proportional relationship between the scores of the preferred adhoc culture and seniority (r = 0.002; p = 0.496), job position (r = 0.206; p = 0.137), age (r = 0.092; p = 0.315) and study level (r = 0.108; p = 0.285) independent variables were introduced in a multiple linear regression model.
The Model OCAI 1F, which contains all four variables, has an explanatory capacity of 10.6% of the experimental distribution of the preferred adhoc culture scores (R square = 0.106) and increases the explanatory capacity to 10.6% (R square change = 0.106) but statistically insignificant p (F change) = 0.572. Model OCAI 2F, obtained by removing the age variable, has an explanatory capacity of 10.5% (R square = 0.105) and a reduction of the explanatory capacity of 0.2% (R square change = 0.002) and without statistical significance for p (F change) = 0.833. Model OCAI 3F, obtained by removing the variables age and seniority has an explanatory capacity of 9.5% (R square = 0.095) and a reduction of the explanatory capacity of 0.9% (R square change = 0.009). Not statistically significant for p (F change) = 0.611. Model OCAI 4F, obtained by removing the variables seniority, age and level of education has an explanatory capacity of 4.3% (R square = 0.043) and the reduction of explanatory capacity of 5.3% (R square change = 0.053). Not statistically significant for p (F change) = 0.239. Based on the regression equation determined for the Model OCAI 1F, the highest explanation of the variation of the score obtained for the preferred adhoc culture R2 = 0.106 (10.6%) is obtained.
The lack of statistical significance obtained from the ANOVA analysis for the four models indicates that the observed data does not allow the identification of valid models. The four variables (level of education, seniority, job position and age) taken together do not explain statistically significant variation in the preferred adhoc culture scores. In the regression analysis, for all four models the coefficients have statistically insignificant values (Sig. Is greater than 0.05) and therefore all four coefficients are not significantly different from 0 and therefore the predictor variables are not considerable for estimating the variable criterion.
Regression equation:
Model OCAI 1F. Preferred adhoc culture score = 127.575 + 3.11 * seniority – 23.64 *
job position + 9.4 * age + 31.42 * education level (21)
Model OCAI 2F. Preferred adhoc culture score = 134.893–23.57 * job position + 9.92 *
age + 30.77 * education level (22)
Model OCAI 3F. Preferred adhoc culture score = 156.516–19.72 * job position + 24.98
* education level (23)
Model OCAI 4F. Preferred adhoc culture score = 193.303–12.46 * job position (24)
The lack of significance was also present in the R2 changes for the models obtained by eliminating the independent variables.
Preferred hierarchical culture / internal process / based on rules (G)
Based on the correlative analysis indicating a directly linear and statistically significant proportional relationship between the preferred hierarchical culture scores and seniority (r = 0.052; p = 0.393), position (r = 0.403; p = 0.014), age (r = 0.190; p = 0.157) and study level (r = 0.037; p = 0.422) independent variables were introduced in a multiple linear regression model.
The model OCAI 1G, which contains all four variables, has an explanatory capacity of 23% of the experimental distribution of the scores of the preferred hierarchical culture (R square = 0.230) and increases the explanatory capacity to 23% (R square change = 0.230) but statistically insignificant p (F change) = 0.147. The Model OCAI 2G, obtained by removing the age variable, has an explanatory capacity of 23% (R square = 0.230) and a reduction of the explanatory capacity of 0% (R square change = 0.000) and without statistical significance for p (F change) = 0.974. Model OCAI 3G, obtained by removing the variables age and seniority has an explanatory capacity of 22.6% (R square = 0.226) and the reduction of explanatory capacity of 0.4% (R square change = 0.004). Not statistically significant for p (F change) = 0.715. Model OCAI 4G, obtained by removing the variables seniority, age and level of education has an explanatory capacity of 16.2% (R square = 0.162) and the reduction of explanatory capacity of 6.4% (R square change = 0.064). Not statistically significant for p (F change) = 0.146.
Based on the regression equation determined for models 1G and 2G, the highest explanations of the variation of the score obtained for the preferred group culture R2 = 0.230 (23%) were obtained.
The lack of statistical significance obtained from the ANOVA analysis for the first three models indicates that the observed data does not allow the identification of valid models. The four variables (level of education, seniority and age) taken together do not explain statistically significant variation in the scores of the preferred hierarchical culture. For model 4G (p = 0.027), statistical significance was obtained which indicates that it is a valid linear regression model. The job position variable significantly explains the variation of the scores of the preferred hierarchical culture. In the regression analysis, for the first three models, coefficients have statistically insignificant values (Sig. is greater than 0.05) aspect that allows the conclusion that the first three coefficients are not significantly different from 0 and therefore the predictor variables (seniority, age and level of education) are not considerable for evaluating the criterion variable. For model four, the coefficient has statistically significant value (p = 0.027) and thus this coefficient is significantly different from 0 and therefore the predictor variable job position is important for estimating the variable criterion.
Regression equation:
Model OCAI 1G. Preferred hierarchical culture score = 134.743 + 0.37 * seniority + 25.96 *
job position – 4.98 * age – 23.31 * education level (25)
Model OCAI 2G. Preferred hierarchical culture score = 135.533 + 25.97 * job position – 4.92 *
age – 23.38 * education level (26)
Model OCAI 3G. Preferred hierarchical culture score = 124.803 + 24.06 * job position − 20.5 *
education level (27)
Model OCAI 4G. Preferred hierarchical culture score = 94.606 + 18.09 * job position (28)
The lack of significance was also present in the R2 changes for the models obtained by eliminating the independent variables.
Preferred rational / market / goalbased culture (H)
Based on the correlative analysis indicating a directly linear and statistically significant proportional relationship between the scores of the preferred rational culture and seniority (r = 0.345; p = 0.031), position (r = 0.127; p = 0.252), age (r = 0.247; p = 0.100) and study level (r = 0.069; p = 0.358) independent variables were introduced in a multiple linear regression model.
Model OCAI 1H, which contains all four variables has an explanatory capacity of 22.3% of the experimental distribution of the preferred rational culture scores (R square = 0.223) and increases the explanatory capacity to 22.3% (R square change = 0.223) and statistically insignificant p (F change) = 0.161. Model OCAI 2H, obtained by removing the study level variable, has an explanatory capacity of 18.7% (R square = 0.187) and a reduction of the explanatory capacity of 3.6% (R square change = 0.036) and without statistical significance for p (F change) = 0.291. Model OCAI 3H, obtained by removing the variables study and job position level has an explanatory capacity of 18.7% (R square = 0.187) and the reduction of the explanatory capacity of 3.7% (R square change = 0.037). Not statistically significant for p (F change) = 0.284. Model OCAI 4H, obtained by removing the variables study and job position level has an explanatory capacity of 11.9% (R square = 0.119) and the reduction of the explanatory capacity of 3.1% (R square change = 0.031). Not statistically significant for p (F change) = 0.330. Based on the regression equation determined for model 1, the highest explanation of the variation of the score obtained for the preferred adhoc culture R2 = 0.223 (22.3%) is obtained.
The lack of statistical significance obtained from the ANOVA analysis for all models indicates that the observed data does not allow the identification of a valid model. The four variables (level of education, seniority, job position and age) taken together or separately do not explain significantly from a statistical point of view the variation of the preferred rational culture scores. In the regression analysis, for the first three models, coefficients have statistically insignificant values (Sig. is greater than 0.05) which brings us closer to the conclusion that all four coefficients are not significantly different from 0 and therefore the predictor variables are not considerable for the variables criterion. For model four, the coefficient (seniority) has a value close to statistical significance (p = 0.062) which allows us to conclude that this coefficient is quite significant for estimating the variable criterion.
Regression equation:
Model OCAI 1H. Preferred rational culture score = 196.937–13.67 * seniority + 12.09 *
job position – 17.31 * age – 13.58 * education level (29)
Model OCAI 2H. Preferred rational culture score = 167.567–12.6 * seniority + 6.99 *
job position – 12.06 * age (30)
Model OCAI 3H. Preferred rational culture score = 180.260–13.15 * seniority – 8.81 * age (31)
Model OCAI 4H. Preferred rational culture score = 167.239–14.66 * seniority (32)
The lack of significance was also present in the R2 changes for the models obtained by eliminating the independent variables.
Regarding experimental part of the paper, both hypotheses of the study were validated under negentropic desiderata.
Hypothesis 1
the variables study level, seniority, age and position generate valid statistical models for existing cultures from the OCAI model  was partially validated by:

ANOVA analysis for Existing hierarchical culture / internal process / based on rules, highlighted for models OCAI 2C and 3C statistical significances which indicates that the observed data allows us to identify valid models. The three variables taken together (education level, age and position) explain statistically significant variation in the scores of the existing hierarchical culture. In the regression analysis, model three approaches statistical significance (p = 0.000, p = 0.011 and p = 0.055) and therefore, the predictor variables (job position and level of studies) are quite important for estimating the criterion variable;

for the Existing rational / market / goalbased culture ANOVA analysis for the OCAI models obtained statistical significance which indicates that the observed data allows us to identify a valid model. The job position variable explains statistically significant variation in the scores of the existing rational culture. In the regression analysis, the same model four has statistical significance (p = 0.000 and p = 0.039) and therefore the predictor variable (job position) is important for estimating the criterion variable.
Hypothesis 2
the variables level of education, seniority, age and job position generate valid statistical models for the preferred cultures from the OCAI models  was partially validated by:

for the Preferred hierarchical culture / internal process / based on rules, preferred after ANOVA analysis for model OCAI 4G (p = 0.027) statistical significance was obtained which indicates that it is a valid linear regression model. The job position variable significantly explains the variation of the scores of the preferred hierarchical culture. In the regression analysis, model 4, the coefficient has statistically significant value (p = 0.027) which allows the conclusion that this coefficient is significantly different from 0 and therefore the predictor variable (job position) is important for estimating the criterion variable;

for the Preferred rational / market / goalbased culture in the regression analysis, for model OCAI 4H the coefficient seniority has a value close to statistical significance (p = 0.062) and therefore allows us to conclude that this coefficient is quite significant for estimating the criterion variable.