THE IMPACT OF CORPORATE CULTURE VARIABLES ON KNOWLEDGE SHARING IN THE FIELD OF LEGAL SERVICES IN THE REPUBLIC OF KAZAKHSTAN

ВЛИЯНИЕ ПЕРЕМЕННЫХ КОРПОРАТИВНОЙ КУЛЬТУРЫ НА ОБМЕН ЗНАНИЯМИ В ОБЛАСТИ ОКАЗАНИЯ ЮРИДИЧЕСКИХ УСЛУГ В РЕСПУБЛИКЕ КАЗАХСТАН

Дайрабаева Гульзира Муратхановна

докторант бизнес-школы Казахстанско-Британского Университета,

Казахстан, г. Алматы

 

THE IMPACT OF CORPORATE CULTURE VARIABLES ON KNOWLEDGE SHARING IN THE FIELD OF LEGAL SERVICES IN THE REPUBLIC OF KAZAKHSTAN

Gulzira Dairabayeva

Doctoral student of the business school of the Kazakh-British University,

Kazakhstan, Almaty

 

АННОТАЦИЯ

В статье делается сравнительный анализ влияния разных факторов  на процесс обмена знаниями, в котором элементы корпоративной культуры обрели преобладающее значение.

Цель исследования: выявить элементы корпоративной культуры  или элементы технического характера имеют большее влияние на процесс обмена знаниями в области оказания юридических услуг в Республике Казахстан?

Методология исследования: метод системного анализа,способ анонимного анкетирования, проведенный в фокус группе, состоящей из юридических консультантов и среди нотариусов, общее количество которых составило 425 человек.

Результаты исследования: автор выявил переменные, имеющие низкое, среднее и высокое влияние на обмен знаниями и опытом. При этом переменными, имеющими высокое влияние, оказались факторы корпоративной культуры. По результатам исследования руководству организации были даны  рекомендации: для совершенствования процесса обмена знаниями нужно повышать работу с факторами корпоративной культуры.

Оригинальность и вклад автора(авторов): Это  исследование, в результате которого выявлено преобладание переменных как удовлетворенность работой, уровень коммуникационной среды, уровень поддержки коллег в рабочем коллективе, которые являются элементами корпоративной культуры, над переменными как внедрение информационных технологий, стаж, опыт, в процессе обмена знаниями в сфере оказания юридических услуг.

ABSTRACT

This article presents a comparative analysis examining the influence of various factors on the process of knowledge sharing, with a specific focus on the significance of corporate culture elements.

Research Objective: The objective of this study is to identify the key elements of corporate culture or technical aspects that have a greater impact on the knowledge sharing process within the realm of legal services in the Republic of Kazakhstan.

Research Methodology: The research employs a systemic analysis approach and utilizes an anonymous questionnaire administered to a focus group comprising legal consultants and notaries, with a total participant count of 425 individuals.

Research Findings: The author identified variables that have low, moderate, and high impact on knowledge and experience exchange. Notably, the variables with high impact were found to be related to corporate culture factors. Based on the research results, recommendations were provided to the organization's management, suggesting that improving knowledge sharing processes necessitates focusing on enhancing corporate culture factors.

Originality and Contribution of the Author(s): This study reveals the predominance of variables such as job satisfaction, communication environment, and colleague support within the work collective, which are elements of corporate culture, over variables like the implementation of information technologies, tenure, and experience in the knowledge sharing process in the field of legal services.

 

Ключевые слова: корпоративная культура, зависимые и независимые переменные, знание, система управления знаниями, обмен знаниями, сфера оказания юридическихуслуг.

Keywords: corporate culture, dependent and independent variables, knowledge, knowledge management system, knowledge sharing, legal services sector.

 

Introduction

Literature Review

Numerous authors have dedicated their works to the study of corporate culture, including D. Meister, E. Schein, T. Kotter, J. Heskett, E. Jacques, K. Cameron and R. Quinn, A.N. Krylov, O.N. Shinkarenko, and T.O. Solomandina.

Corporate culture refers to the fundamental assumptions that individuals share regarding the values, beliefs, norms, symbols, language rituals, and myths of an organization. It provides people with a foundation for their work and guiding principles for their actions. The successful implementation of a knowledge management system in an organization can only be achieved when the culture is aligned with the system, allowing knowledge to be transferred to employees at any given time [1]. Corporate culture represents a specific, implicitly explicit collective knowledge shaped by a particular value-meaning model, determining the socio-economic quality of the corporation's activities [5]. "Corporate culture is a complex set of assumptions invented, discovered, or developed by a group to cope with problems of external adaptation and internal integration. It must function for a sufficient period, establish its independence, and therefore be transmitted to new members of the organization as the correct mindset and attitude towards these problems" [7].  

Managers of companies need to be able to utilize organizational culture tools to improve the socio-psychological climate within the team, enhance motivation for work, facilitate training and development of personnel, and increase employee job satisfaction. By influencing these factors, they can achieve improved individual, departmental, and overall organizational productivity [3].

According to T.B. Ivanova and E.A. Zhuravleva, the satisfaction with work directly affects the performance of an enterprise. "Job satisfaction is an indicator of an individual's personal attitude towards their work and group members" [4].

T.O. Solomandina has developed a model of organizational culture as a cultural field or socio-economic space [6]. She identifies four sectors within this space, each of which is analyzed based on three parameters.

Sector 1: Loyalty

1. Job satisfaction

2. Alignment of personal goals and values with the company

3. Satisfaction with leadership style

Sector 2: Social Microclimate

4. Positive perception of colleagues (as partners)

5. Low level of conflicts within the team

6. Recognizing the importance of mutual assistance and support

Sector 3: Training and Communication

7. Satisfaction with career development programs

8. Satisfaction with the frequency of corporate events

9. Satisfaction with the existing training system

Sector 4: Motivation

10. Satisfaction with working conditions

11. Satisfaction with moral incentives

12. Satisfaction with financial incentives [6].

Results of the Study

Analysis of Factors Influencing the Level of Knowledge and Experience Exchange in Legal Organizations

To identify the key determinants that drive legal professionals' willingness to exchange valuable knowledge and experience with colleagues, a questionnaire was developed. A total of 425 employees were surveyed using computer-based questionnaires. After processing the collected data and preparing it for statistical analysis, a logistic regression model was constructed. Let's take a closer look at the process of questionnaire development and the subsequent analysis of the obtained data.

 Questionnaire Development and Determination of Dependent and Independent Variables

To identify the factors influencing the level of knowledge sharing, scientific literature in the fields of corporate governance and psychology was analyzed. Based on the findings of previous research in this area, the main factors influencing the inclination for knowledge sharing within a work collective were identified. Using these factors, a questionnaire was developed for quantitative measurement of the propensity for knowledge sharing. A seven-point Likert scale was chosen to assess each factor in the questionnaire, as it is important to accurately capture respondents' reactions without burdening them with a large number of response options.

The dependent variable in the study is the inclination to exchange knowledge with colleagues, while the independent factors consist of respondents' personal and organizational characteristics, each comprising three sets of factors. All the questions were shuffled and presented to respondents in a random order during the survey.

To ensure a more accurate assessment, each factor includes five questions. Direct questions assessing satisfaction levels or the corporate environment carry the risk of respondents inflating their ratings. Therefore, questions directly related to the factors were implicitly framed, meaning that the factors were evaluated based on objective characteristics of the respondents. The dependent variable was assessed with a single question, as it reflects a more objective measure. Let's consider the questions used to evaluate the dependent variable and independent factors. Respondents rated the extent to which each statement corresponded to their own views on a seven-point Likert scale, where 1 indicates no correspondence at all and 7 indicates complete correspondence.

Dependent variable (knowledge sharing): "I openly and actively exchange experiences and knowledge with colleagues."

Personal factors:

• Block 1: Job satisfaction level:

o        Question 1: "I always go to work with a positive attitude."

o        Question 2: "My current job is close to ideal."

o        Question 3: "I always look forward to returning to work after vacation."

o        Question 4: "I would recommend others to work in my company."

o        Question 5: "I feel enthusiastic about my company and my work tasks."

• Block 2: Income satisfaction level:

o          Question 6: "My salary (including bonuses and special allowances) currently fully meets my expectations."

o          Question 7: "My income is higher than that of my close circle."

o          Question 8: "I can afford to make expensive purchases frequently (e.g., regularly upgrading my phone or laptop)."

o          Question 9: "I don't need to borrow money."

o          Question 10: "I have a goal to increase my income in the next six months."

• Block 3: Career satisfaction level:

o          Question 11: "Over the past year, I have achieved my professional advancement goals."

o          Question 12: "In my current position, I have developed a significant number of new skills."

o          Question 13: "My colleagues and management are attentive to my professional and personal development."

o          Question 14: "Currently, my professional life is close to what I have dreamed of."

o          Question 15: "If given the opportunity, I would completely change the way I have built my professional career."

Organizational factors:

• Block 4: Communication environment level:

o        Question 16: "At work, we frequently discuss current tasks and methods of solving them."

o        Question 17: "Management regularly provides me with useful feedback."

o        Question 18: "The work team appreciates my contribution to the job."

o        Question 19: "I often suggest improvements in my work and put in extra effort when tackling a new task."

o        Question 20: "I and my colleagues make an effort to meet more often in informal settings."

• Block 5: Level of implementation of information technologies in the organization:

o        Question 21: "At work, we often use social networks and messaging apps."

o        Question 22: "The level of technical competence among the management is quite high."

o        Question 23: "I actively use technical tools and gadgets in my work."

o        Question 24: "My organization has established a corporate information environment (shared workspace, chats, etc.)."

o        Question 25: "The team and management are interested in developing skills in computer programs and the Internet."

• Block 6: Level of support from colleagues in the work team:

o          Question 26: "Assisting colleagues brings me pleasure."

o          Question 27: "My team always helps me."

o          Question 28: "The management strives to promote mutual support within the organization."

o          Question 29: "I try to help my colleagues, even if they don't directly ask me to."

o          Question 30: "I feel a sense of unity with my team."

In addition to this, respondents provided data on their gender, age, work experience, and psychological type (introvert or extrovert). During the survey, 425 responses were collected, and those with identical answers were removed. As a result, the analyzed sample consisted of 418 observations.

Primary data analysis and preparation of variables for logistic regression model building

Let's examine the distribution of respondent characteristics. Among the surveyed respondents, the majority are women and extroverts (Table 1).

Table 1.

Frequency table for gender, psychological type, age, and total work experience variables.

 

When analyzing the distribution of the target question, it can be concluded that there is a significant right skewness in all the responses (Figure 1). The majority of respondents indicated that they actively share knowledge with their colleagues.

 

Figure 1. Distribution of responses for the target question

 

Bar charts representing the distribution of responses for each question are presented in the appendix. Indices were calculated for each factor by taking the arithmetic mean of the five questions in each block. It should be noted that the questions "I have a goal to increase my income in the next six months" and "If given the opportunity, I would completely change my professional career" exhibit a decreasing level of satisfaction as the score increases. Therefore, these questions were reversed during data preparation, meaning they could be formulated as "I do not have a goal to increase my income in the next six months" and "I would not change anything in my professional career."

The obtained means exhibit a right-skewed distribution (Figures 2-7).

 

Figure 2. Distribution of means for Block 1

 

Figure 3. Distribution of means for Block 2

 

Figure 4. Distribution of means for Block 3

 

Figure 5. Distribution of means for Block 4

 

Figure 6. Distribution of means for Block 5

 

Figure 7. Distribution of means for Block 6

 

Descriptive statistics for the means are presented in Table 2. The descriptive statistics provide the mean values for each variable along with the standard deviation (SD), as well as the median and the first and third quartiles (Q1 and Q3) in square brackets.

Table 2.

Descriptive Statistics for Indices (Factors).

Factor	Descriptive Statistics
Job satisfaction level	5,3 ± 1 5,4 [4,6; 6,4]
Income satisfaction level	3,8 ± 1 4 [3; 4,6]
Career satisfaction level	5,1 ± 1 5,2 [4,4; 6]
Communication environment level	5 ± 1 5,2 [4,2; 6]
Level of implementation of information technologies in the organization	5,5 ± 1 5,8 [5; 6,4]
Level of support from colleagues in the work team	5,4 ± 1 5,6 [4,8; 6,4]

 

Due to the right-skewed distribution of all variables, they were categorized using an optimal categorization procedure, which minimizes the entropy measure for categories. The variables were divided into several categories, distinguishing low, medium, and high inclination of respondents towards job satisfaction and workplace satisfaction. The original variables were ordinal and exhibited skewness, making linear regression inappropriate. Therefore, the target variable was divided into 2 categories as follows: respondents who answered from 1 to 4 were assigned a low inclination towards knowledge and experience sharing, while respondents who answered from 5 to 7 were assigned a high inclination. As a result, regarding the target variable, 64 respondents (15.3%) had a low inclination towards knowledge and experience sharing, and 354 respondents (84.7%) had a high inclination.

Thus, based on the available factors measured on a categorical scale, it is possible to build a logistic regression model, where the dependent variable is a binary variable reflecting respondents' inclination to share knowledge and experience. The obtained categorical factors and socio-demographic characteristics of the respondents can be considered as independent variables to assess their influence on the propensity for knowledge sharing.

Building the Logistic Regression Model

To determine the extent to which personality and organizational factors, as well as socio-demographic characteristics, influence the inclination to share knowledge with colleagues, a logistic regression model was constructed. This model expresses the dependence of the natural logarithm of the odds of an event occurrence on the combination of independent factors, which can be measured on a quantitative or categorical scale. The general formula for the logistic regression model is given as (1):

                                                            (1)

where p – represents the probability of a high inclination towards knowledge sharing, b₀, b₁, …, b_k – are the coefficients of the factors,, x₁, x₂,…,x_k – are the levels of the independent factors.

The coefficients of logistic regression indicate how the natural logarithm of the odds changes, on average, when the independent variable changes by one unit of its measurement, while keeping the other predictors constant. However, such interpretation may not be immediately clear, so it is common practice to take the exponentiation of the coefficients in the equation. In this case, the exponentiation of the coefficient shows the average change in the odds of the propensity for knowledge sharing when the independent variable changes by one unit of its measurement, while keeping the other variables constant. In this form, the model can be expressed in exponential form as (2):

                                                                      (2)

The coding of categorical variables is presented in Table 4. The dependent variable takes a value of 0 in case of low inclination of the respondent towards knowledge sharing, and 1 in case of high inclination. For the independent factors, either the first or the last categories were chosen as the reference category (denoted as 1). Preference was given to the categories with more observations.

The information value (IV) was also calculated for the factors to assess the predictive ability of the variable and select those that may have an impact on the dependent variable. The following factors had low information value: gender, age, work experience, and psychotype. The factors with medium information value were the level of information technology implementation, satisfaction with career, and satisfaction with income. The factors with high information value were the level of colleague support in the work collective, the level of communication environment in the organization, and job satisfaction of the respondents (Table 4).

Table 4.

Parameter Encoding for Logistic Regression

		Frequency	Parameter coding
Total work experience	less than 5 years	52	X1(1)
	5-10 years	100	X1(2)
	11-15 years	58	X1(3)
	16 to 20 years	66	X1(4)
	21-25 years	54	X1(5)
	26-30 years	31	X1(6)
	More than 30 years	57	X1
Age	under 30 years of age	14	X2(1)
	31-40 years old	126	X2(2)
	41-45 years old	105	X2(3)
	46-50 years old	60	X2(4)
	51-55 years old	48	X2(5)
	56-60 years old	30	X2(6)
	Older than 60 years	35	X2
Psychotype	Extravert (with an outgoing personality)	297	X8
	Introvert (with a reserved personality)	121	X8(1)
Gender	male	83	X9(1)
	female	335	X9
Level of support from colleagues in the work team:	low (up to 3.6)	42	X3(1)
	average (3.6 to 5.2)	99	X3(2)
	high (over 5.2)	277	X3
Job satisfaction level	low (up to 3.6)	26	X4(1)
	high (over 3.6)	40	X4(2)
	low (up to 3.8)	352	X4
Communication environment level	average (3.8 to 5.0)	67	X5(1)
	high (over 5.0)	112	X5(2)
	low (up to 4.6)	239	X5
Level of implementation of information technologies in the organization	high (over 4.6)	35	X6(1)
	low (up to 3.6)	383	X6
Career satisfaction level	high (over 3.6)	113	X7(1)
	low (up to 2.8)	305	X7
Income satisfaction level	average (2.8 to 4.2)	159	X10(1)
	high (over 4.2)	259	X10

 

The parameters were selected using a stepwise inclusion method based on the logarithm of likelihood of the most significant parameters. Factors such as gender, age, work experience, psychotype, level of information technology implementation, satisfaction with career, and satisfaction with income were found to be statistically insignificant. The following are the results of parameter estimates for logistic regression (Table 5). The target event for model construction was defined as having a high inclination for knowledge sharing.

Table 5.

Results of Parameter Estimates for Logistic Regression

 

We can see that the intercept is significant, indicating that overall respondents are inclined to share knowledge regardless of personal and organizational factors. However, this inclination significantly increases when employees are satisfied with their career and there is a good communication environment and support from colleagues. We can observe that the odds of knowledge sharing decrease significantly in the case of low or moderate expression of these factors. For example, if the level of colleague support is low, it reduces the odds of knowledge and experience sharing by 94% (100% - 0.059 * 100%).

Assessment of Model Classification Quality:

By comparing the predicted values of the target variable with the actual values, the model demonstrates a good ability to identify respondents who are inclined to share knowledge with colleagues (Table 6). The model exhibits high sensitivity (0.92) and low specificity (0.76). However, by adjusting the default cutoff threshold of 0.5, a better balance between sensitivity and specificity can be achieved.

Table 6.

Comparison of Actual and Predicted Model Values

		Predicted
		A tendency to share experiences and knowledge with colleagues		percentage of correct
		low	high
A tendency to share experiences and knowledge with colleagues	low	343	11	54,7
	high	29	35	96,9
Total percentage				90,4

 

From Table 7, it can be seen that by choosing a cutoff point of 0.842, high values of both sensitivity and specificity can be achieved, which are 0.814 and 0.859, respectively.

Table 7.

Coordinates of the ROC Curve

Probability	Sensitivity	Specificity
0,0000000	1,000	0,000
0,1381526	1,000	0,328
0,2416209	0,994	0,422
0,2830447	0,992	0,438
0,3249953	0,986	0,469
0,3677056	0,975	0,547
0,4142348	0,972	0,547
0,5192244	0,969	0,547
0,6053631	0,958	0,594
0,6502995	0,958	0,609
0,7139318	0,935	0,672
0,7844986	0,910	0,719
0,8168606	0,907	0,719
0,8424955	0,814	0,859
0,8837648	0,802	0,859
0,9031483	0,797	0,859
0,9198001	0,785	0,875
0,9427742	0,655	0,938
0,9588525	0,605	0,953
0,9750846	0,599	0,969
1,0000000	0,000	1,000

 

The overall percentage of correct predictions by the model is also quite high (90.4%). An ROC analysis was conducted on the obtained model. Figure 7 presents the ROC curve.

 

Figure 7. ROC Curve of the Evaluated Model

 

The area under the ROC curve (ROCAUC) is 0.914, and the confidence interval includes fairly high values for the area under the ROC curve, indicating that the model's quality is quite high (Table 8). The Gini coefficient is calculated as 0.828.

Table 8.

Evaluation of the Area Under the ROC Curve

Result variables:	Domain	Standard error	Asymptotic significance	Asymptotic 95% confidence interval
				Lower bound	Upper bound
Predicted probability	0,914	0,020	0,000	0,875	0,953

 

Conclusions: Thus, to identify the factors influencing the level of knowledge sharing among colleagues in legal organizations, a questionnaire was developed and a survey was conducted among 425 respondents. The obtained data were processed by removing observations with identical responses. Descriptive statistics of the collected data were analyzed, and indexes reflecting the psychological and professional characteristics of the respondents were calculated, taking into account inverted questions. Subsequently, a logistic regression model was constructed, which revealed three factors influencing the inclination to exchange knowledge. These factors are:

• Level of support from colleagues in the work team.
• Level of communication environment within the organization.
• Level of job satisfaction among respondents.

The obtained model demonstrates excellent predictive ability, indicating that these factors indeed have a significant impact on the inclination to exchange knowledge. All three factors are elements of corporate culture that need to be addressed in the knowledge sharing process within the legal service sector.

 

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