Negentropy: a sustainable culture of educational leadership. An OCAI model analysis

doi:10.21203/rs.3.rs-2487757/v1

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Negentropy: a sustainable culture of educational leadership. An OCAI model analysis

https://doi.org/10.21203/rs.3.rs-2487757/v1

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Purpose: This study aims to analyze the impact of socio-economic negentropy on a management organization's culture. The study aims to check the level of entropy within an organization and propose solutions for negentropy development. The excellent organization represents the ordering of positive entropy into negative entropy.

Design/methodology/approach: The theoretical part of the paper presents the importance of the negentropy paradigm in developing the management organization's culture. The empirical study is based on samples from a university with information about different management organization cultures. The data are analyzed by means of regression analysis applied to the Organizational Culture Assessment Instrument (OCAI). The organizational culture improves management organization through socio-economic negentropy.

Findings: Four types of organizational cultures were determined for socio-economic negentropy applied to management organizations: group/family/clan/human relations, ad-hoc/in development/ innovation/open system, hierarchical/internal process/rules-based, rational/market/goal-based. The model has theoretical limitations, being applied to a few respondents. Practical implications refer to the improvement of management organization cultures through using negentropy. Possible social impact concerns a superior work organization and increased productivity. The assumed hypotheses show that the variables' level of education, seniority, age, and job position generate valid statistical models for the existing/preferred cultures from the OCAI model.

Originality: Organizations with coherent management efficiently organize their activities through an entropic management organization model. Present within an organization (as an open system), negentropy opposes disintegration, disorder, and entropy.

culture organization

management systems

negentropy/entropy

OCAI analysis

organizational management

The paper proposes a model for cultural sustainable leadership in an organization through more organized management (Iqbal and Piwowar-Sulej 2023). The hypotheses assumed highlighted that aspects of organizational culture such as age, nature of the position held, seniority in the organization, and others are factors with a very strong non-tropic potential along with drastic measures related to staff numbers and their remuneration. Organizations can creatively use the resources at their disposal internally or externally to generate solutions for survival or progress (double negative entropy). (Alvim 2020)

Naturally, systems move in the direction of increasing entropy (Attard 2002). Some open systems generate entropy that is exported out of the system. This aspect leads to the growth of one’s own organization, with the cost of increasing the disorder in the environment. Such systems are present in an appreciable number in the biological environment that by developing such a mechanism manage to maintain or even increase their degree of organization by transmitting in the environment (so to other systems) excess entropy. Management systems can be subjected to the same entropic dissipation structure as systems that exhibit dynamic self-organization. Open systems generate entropy but it is a dissipating entropy, or exported out of the system. Such behavior is common in living organisms that take energy and matter from the environment in the form of light and food and then give it in the form of waste products that have a higher entropy than initially received. (Scarlat & Mitruț 2012, p. 120)

As Alfred Lotka (1925) stated, each species can be seen as a different type of transformer for capturing and using available energy. Each transformer or organism is equipped with a series of devices that it uses to take energy from its surroundings. With all these known variables, entropy export does not explain why and how self-organization takes place.

For closed socio-economic systems, the law of increasing entropy has the same effect as in the case of physical systems. However, the action of this law is not universal, socio-economic systems and processes are not always in equilibrium or in a state close to equilibrium (Mykhailovska 2014).

In a certain context, the management process is an entropically neutral process. It takes over information, low entropy, and turns it into high entropy or into a result that materializes in maintaining or preserving institutional functioning. Within some organizations, this process seems to be more economical based on the information from the hierarchy and thus ensures the functionality of that organization without too much effort to transform information into managerial quality (Ali and Kashif 2020). In other organizations, the effort to transform low entropy into high entropy is vital, and the survival of that organization depends on that transformation. (Carr-Chellman 2019)

This entropic process seems to depend more on human effort than on natural entropies within the universe or on all the non-living structures present in the general functioning environment of the earth. Therefore, entropy seems to depend on the activity of humans in an overwhelming proportion and in some cases, its negative effects can be transformed into positive effects or at least can be sorted. This transformation of low entropy into high entropy is not a pointless endeavor. It can be the purpose of living and transforming, it can be the source of satisfaction or pleasure, it can transform the personality, mobilize strong and lasting efforts from the people involved, ennoble and increase the comfort of living, give meaning to life and the very reason for existing. Basically, that kind of organizational entropy is fought by consuming personal entropy. In other words, one of the best ways to prevent (eliminate) entropy from one’s own system is to consume the potential to combat entropy from another system. Thus, double effects are obtained from the sustained effort to combat entropy in one’s own system of life (Georgescu-Roegen 1976). Therefore, personal entropy is consumed for organizational entropy. But in the economic dimension, there are things that have economic value and no price.

The purpose of the managerial process can be subsumed in a vast process of negative entropy. The management process aims to reduce organizational entropy, increase efficiency, effectiveness and quality of production, contribute to increasing consumer’s satisfaction, employees and shareholders, in order to ensure a competitive advantage (Brătianu 2007, p. 13) or to ensure elegance in chaos equivalent to order in chaos (Sprott 2010). Of course, several studies have shown that organizational culture has strong effects on issues such as employee retention, job satisfaction and organizational commitment. (Heracleous 2003; Sokolova 2019)

Current activities aim to reduce an entropic generalization through what we do or when we tend to organize a system which, in this case is an overlap with negentropy through various activities “… we impose order and reduce the entropy associated with the structure we organize. The organization has developed as a necessity to increase the efficiency and quality of work. According to the law of generalized entropy, systems naturally tend to evolve into increasingly disorganized states, each new state being characterized by a larger entropy than the previous state. At the limit, the state of chaos is reached, when the entropy becomes maximum.” (Brătianu 2007, p. 63). Therefore, the organizational process generates structural and functional order, decreases entropy and increases work efficiency. Or, the organization is maintained by extracting the order from the environment (Schrödinger 1980; Achieng 2020).

In a special context, it can also discuss the entropy of a single process within organizational management. That singular process can bring the contribution within the general structure or can disrupt (delay) the organizational process and thus bring it closer to the entropic part. Consequently, we can also include the choice of personalized entropy of processes within organizational management and thus can reduce the entropy of a process by structuring and ordering it (Brătianu 2007, p. 64), through procedures that transfer chaotic behavior into a structured environment or anti-entropic environment. In this case we can also discuss the double or even triple entropy. First, we can talk about general entropy or a state of unorganized things and which requires various procedures to be organized. Then, after their organization, the new situation is subjected to a new entropic tendency, the job position-organization entropy or the entropy that appears with the establishment of an organization or structure and which in the absence of this organization, could not act. And as a third aspect, we can discuss the entropy of procedures. And the procedures themselves can be subjected to the entropic process by the fact that they are not adapted and without real content for the entropic context in which they must act. (Trinn 2018; Avsar Erumit et al. 2022)

Negentropy is somehow closely related to the attempt to regulate a system and in other cases, to a deregulation of it. However, this aspect is valid, or it can only be attested to a certain point. It seems to be an indirect (negative) mechanism to control entropy. (Lichtenstein 2020)

The research was conducted within a single higher education institution in Bucharest in the form of an institutional case study. Total population of employees, as per Hyperion University (2018–2020) is 248 and total population of teaching people is 180. Total population of managing professors from Hyperion University in Bucharest is in number of 30. The people involved are part of the hierarchical structures of the institution: rector (president), president of the senate, vice-rectors, deans, vice-deans, heads of department, economic director, director of human resources or other people in key positions or with administrative responsibility within the institution.

To assess the OCAI model, data was collected through specific questionnaire. Validity and reliability of the model was verified through ANOVA (analysis of variance) in accordance with OCAI model, according to regression approach.

For the regression analysis, two hypotheses were formulated:

Hypothesis 1

It is assumed that the variables level of education, seniority, age and job position generate statistical models valid for existing cultures from the OCAI model.

Hypothesis 2

It is assumed that the variables level of education, seniority, age and job position generate valid statistical models for the preferred crops from the OCAI model.

OCAI, a model based on a questionnaire with six dimensions, is completed by employees, where each dimension is composed of four types of cultures (group / family / clan / human relations oriented culture, ad-hoc culture / in development / innovation / open system, hierarchical culture / internal process / based on rules, rational / market / goal-based culture). For each domain, 100 points are divided between the four alternatives in proportion to the extent of which each alternative is perceived as present or desired. The six areas are as follows: dominant features, organizational leadership, employee management, organizational link, strategic orientation. success criteria.

The introduction of the variables in the model under analysis was of the backward type, step by step regression with retrograde selection. The first step of this method was to calculate a regression equation in which the predictor variables are included. Then, for each predictor variable, a significance test is performed, identified with the letter “F” for the overall evaluation of the correlations of each predictor. Subsequently, the values of F are compared with a predetermined limit value and the variables that do not exceed this threshold are removed from the equation. As the variables are eliminated, the new equation and a new value for the F test for the remaining variables are calculated. This new calculation is followed by a possible elimination of a variable. This process continues until only significant variables remain in the equation.

Subsequently, the correlation (overall) between the criterion and the predictor must be evaluated and the main problem is reduced to the significant correlations existing between the predictor variables correlated with the criterion variable. 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 taken together do not explain significantly, from a statistical point of view, the variation in existing group culture scores.

At the same time, the significance of the individual regression coefficients must be analyzed to see if they have a possible relationship between the predictor variables and the criterion variable.

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:

$${NOC}_{\alpha }=\sum _{r=1}^{R}(\frac{\sum _{i=1}^{6}\frac{{\beta }_{ij}}{\sum {\beta }_{ij}}x100\%}{i})/R$$

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

β_ij – 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 relations-oriented culture, ad-hoc 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 ad-hoc culture / in development / innovation / open system (B)

Based on the correlative analysis indicating a directly linear and statistically significant proportional relationship between existing ad-hoc 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 ad-hoc 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 ad-hoc 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. Ad-hoc culture existent score = 99.833–1.5 * seniority + 13.29 *

job position − 2.06 * age – 7.57 * education level (6)

Model OCAI 2B. Ad-hoc culture existent score = 96.314 + 13.25 * job position – 2.31 *

seniority − 7.26 * education level (7)

Model OCAI 3B. Ad-hoc culture existent score = 91.283 + 12.36 * job position – 5.91 *

education level (8)

Model OCAI 4B. Ad-hoc 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 ad-hoc / 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 ad-hoc 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 / goal-based 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 ad-hoc 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 ad-hoc 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 ad-hoc 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 ad-hoc 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 ad-hoc 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 ad-hoc culture score = 127.575 + 3.11 * seniority – 23.64 *

job position + 9.4 * age + 31.42 * education level (21)

Model OCAI 2F. Preferred ad-hoc culture score = 134.893–23.57 * job position + 9.92 *

age + 30.77 * education level (22)

Model OCAI 3F. Preferred ad-hoc culture score = 156.516–19.72 * job position + 24.98

* education level (23)

Model OCAI 4F. Preferred ad-hoc 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 / goal-based 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 ad-hoc 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 / goal-based 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 / goal-based 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.

Experimentally, the confirmed hypotheses allow to draw some conclusions about the organizational culture based on questioning people in the hierarchy of the institution: the first hypothesis showed that the male gender is better prepared to approach the Existing ad-hoc culture / in development / innovation / open system and the group with seniority up to ten years it is more open to the Existing rational / market / goal-based culture (the group with the completed doctorate has the same openness) and towards the Preferred rational / market / goal-based culture; both assumed hypotheses highlighted that aspects of organizational culture such as age, the nature of the position held and seniority in the organization are factors with a very strong non-tropic potential along with drastic measures related to staff numbers and their remuneration. Keeping the vision for maintaining the organizational status quo was highlighted as the key factor in maintaining the organization as such.

Theoretically, there are some issues to formulate based on experimental part of the paper. The authors view, according to the theory and experimental lines of the paper, is in accordance with negentropy that can be understood as an organizational ability to: survive; regenerate or recover; to prevent disparity; to understand in a proper amount of time, the situations that could lead to the mentioned aspects. Some non-entropies (negentropies) may be based on only one of the aspects mentioned, in response / reaction to external factors and may have different intensities. The balance of the social macro-system supposes a legitimacy that includes negentropy as an area of resistance or counteraction.

Entropic growth is activated with the emergence of an organization. This aspect is somehow uncontrollable, suspecting that connected to the development of an organization, a certain amount of entropy is born. By contrast, the non-appearance of that organization would mean a lack of entropy in that direction. Thus, we can take a simplistic logical approach: the birth of an organization means the appearance of a quantity of entropy. The emergence of a regulation results in an increased possibility that the entropy will be higher (conditioned by the application of that regulation). Organizational management through negentropy resolve the problem of entropic growth.

The study concludes that negentropy is not just a continuous ascent curve. In many cases, negentropy is survival, especially in work intensive organizations, as universities. Thus, in any organization, the production of negative entropy must exceed the production of positive entropy. Specific for universities, the organizational culture formed by the local feeling of pleasant environment, with the entropies of certain sub-departments controlled by the main departments and not based on assuming the responsibilities (especially academic ones), leads ultimately to the survival of the organization. In this sense, the entropy must not be exported to departments or non-entropic specializations.

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No competing interests reported.

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Negentropy: a sustainable culture of educational leadership. An OCAI model analysis

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