ORIGINAL SCIENTIFIC PAPER
RECEIVED: NOVEMBER 2018
REVISED: DECEMBER 2018
ACCEPTED: DECEMBER 2018
DOI: 10.2478/ngoe-2019-0004
UDK: 001.101:005.5
JEL: J24, C38
Citation: Rozman, M., Shmeleva, Z., & Tominc, P. (2019). Knowledge Management Components and Their Impact on Work Engagement of Employees. Nase gospodarstvo/Our Economy, 65(1), 40-56. DOI: 10.2478/ ngoe-2019-0004
Knowledge Management Components and Their Impact on Work Engagement of Employees
Maja Rozman
University of Maribor, Faculty of Economics and Business, Slovenia maja.rozman1@um.si
Zhanna Shmeleva
Krasnoyarsk State Agrarian University, Department of Foreign Languages at the Center of International Links and Business, Russia shmelevazhanna@mail.ru
Polona Tominc
University of Maribor, Faculty of Economics and Business, Slovenia polona.tominc@um.si
Abstract
In Light of globalization and modern business, companies are typically exposed to challenges caused by unpredictable and complex competitive environments. The business environment, with global trends and stringent competition in the world market, now faces significant changes that companies should introduce into their current business operations. Among them, the human resource management of knowledge employees has become extremely important. The main aim of this article is to establish the impact of components of knowledge management on work engagement of employees in Slovenian companies. In the empirical part of the research, a sample of 112 Slovenian companies was obtained. Senior managers of companies and their employees were surveyed, using the questionnaire developed based on existing measurement scales. The results will help us to better understand the importance of knowledge management in Slovenian companies and its importance as a business strategy that must be fully integrated within all of the employees' related processes of the company.
Keywords: knowledge management, knowledge management components, employees
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. 40-56
Introduction
Knowledge is an important issue for business organisations. Knowledge management is defined by Tan (2000) as "The process of systematically and actively managing and leveraging the stores of knowledge in an organization." According to Armstrong (2014), knowledge management is concerned with storing and sharing the wisdom, understanding, and expertise accumulated in an enterprise about its processes, techniques, and operations. It treats knowledge as a key resource. Knowledge management is about the management and motivation of
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Knowledge Management Components and Their Impact on Work Engagement of Employees
knowledge workers who create knowledge and will be key for business success. Yeh et al. (2006) summarize that employees are the core for creating organizational knowledge; therefore, it is crucial to manage employees to create and share that knowledge. A key element for an enterprise to be successful in pushing knowledge management is the process to encourage people to communicate and share their knowledge with others. Therefore, organizations should view employees as their most important knowledge resource; further, the concept of knowledge management should be integrated into employee management policies because it is crucial for an employee to be willing and enthusiastically motivated to participate and engage in the obtaining and sharing of knowledge. Good working conditions increase employees' willingness to participate in the creation and sharing of knowledge. Also, the educational training of all employees is another key factor for knowledge management.
Knowledge management is a discipline that promotes an integrated approach to identifying, capturing, evaluating, retrieving, and sharing all of an enterprise's information assets. In a company, it is essential to ensure good working conditions, if that company wishes to maintain an agile, productive, and innovative working environment (Gao et al., 2008). Albrecht (2012) argues that, to motivate and engage employees, organizations should create open, supportive, and fair organizational and team culture and ensure that jobs are clearly aligned with organizational goals and have the appropriate levels of autonomy, support, and career development opportunities.
In a knowledge-based economy, it is extremely important to properly manage employees who have a major impact on the future of the organization, namely, knowledge employees. Managing these employees in such a manner as to win their full engagement in work is a true challenge for the organization where they work and for their superiors. Engaged knowledge employees derive more pleasure from their work, have a sense of realization of their potential, feel that they are doing something important for themselves and the environment, realize their ideas and professional ambitions, go beyond the routine procedures and undertake challenges (Figurska, 2015).
Figurska (2015) summarized that determinants of knowledge employees' engagement are, in order of importance: senior management's interest in employees' well-being, challenging work, decision-making authority, evidence that the company is focused on customers, career advancement opportunities, the company's reputation as a good employer, a collaborative work environment where people work well in teams, resources to get the job done, input on decision making, and a clear vision from senior management about future success.
The main objective of this article is to establish the impact of components of knowledge management on work engagement of knowledge employees. We formulated the following research question: Do components of knowledge management have a statistically significant impact on work engagement of knowledge employees?
In this article, a review of the literature is first presented. Then, we present a description of methodology and results. At the end, we present a discussion of the findings.
Literature Review Knowledge Management
Knowledge management can be defined as the achievement of the organisation's goals by making the factor knowledge productive. This is done primarily by facilitating and motivating people to tap into and develop their capacities (their core competencies) and to stimulate their attitude to intrapreneurship. Besides this, knowledge management includes the entirety of systems with which the information within an organisation can be managed and opened up (Beijerse, 2000). According to Ringel-Bickelmaier and Ringel (2010), knowledge management involves activities related to the capture, use, and sharing of knowledge by the organization. Yeh et al. (2006) stress that knowledge management has a significant influence on business success; further, knowledge management will help a company to maintain its competitive advantage.
Appropriate Approaches of Knowledge Management
Under new work conditions, to create value, every organization has to seek, generate, distribute, and apply knowledge, a function that, instead of being driven by capital, emerges from an environment in which the human spirit is enthused. Only those knowledge companies that develop a work environment that motivates their employees to engage in a behavior consistent with this goal will succeed. These companies will be able to recognize and solve contemporary problems and bring solutions to the marketplace sooner than their competitors who fail to develop such an environment (Amar, 2004). Organizations that desire to use knowledge in their products, processes, and services have to know how to engage the human mind in their operations. From this perspective, adequate working conditions for employees are important (Yeh et al., 2006; Amar, 2004).
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To identify factors that determine the level of knowledge employees' engagement, it is worthwhile to get to know their expectations toward the organizations they work in, the nature of the job itself, the superiors, and co-workers. To be highly engaged and effective, a knowledge employee (Figurska, 2015):
•	needs to be treated not as a component of the system but as an individual who has his/her own needs, values, opinions, feelings, problems;
•	needs to be informed about activities and plans of the company as well as threats and opportunities affecting its functioning, which gives him/her a wider context of the work;
•	needs to receive feedback on issues related to his work, thanks to which he knows how his work is evaluated, which of his competences should be developed, etc.;
•	expects that his/her professional achievements will be appreciated by managers;
•	expects tolerance for making mistakes because mistakes are inextricably connected with human creativity and innovativeness;
•	needs to be provided with adequate technical and organizational working conditions that enable him/her to devote the time and effort to activities that generate added value to the organization;
•	needs to be provided with the opportunities of professional development because the desire to satisfy this need is a strong motivator for taking (or not) specific activities;
•	needs to be engaged in the process of management, so he/she will influence decisions and actions taken in the organization by what this person feels valued and appreciated;
•	needs to be independent in making decisions regarding tasks and duties and in performing his/her job;
•	needs to be respected as an employee and as a person, so he/she feels comfortable at work;
•	expects that work performed by him/her corresponds to the knowledge and skills by which one's potential can be fully exploited;
•	needs to be provided with professional challenges at work, so he/she does not fall into a routine;
•	expects the lack of excessive bureaucracy, which will help to make his/her professional life much easier and enables one to focus on activities that are important to this him/her as well as bring added value to the organization;
•	expects to be treated as a trustworthy person with respect to both him/her as a man or a woman and his/ her professional competence, who does not need to be under strict control;
•	needs an appropriate working atmosphere, thanks to which the organization becomes a place where he/
she wants to go, of which he/she says with pride, and for which he/she wants to do more than just what is necessary;
•	expects a high level of competence from the superior, which means that this superior's knowledge, skills, attitudes, and behaviors let employees perceive him/her as a reliable/ responsible/trustworthy, etc. person; and
•	expects consistency between his/her remuneration and contribution to the work, i.e., expects financial appreciation.
According to Armstrong (2011), the goal of the organization is to develop its employees. The next step is the identification of employees within the organization, i.e., their development and promotion. Outside the organization, attracting employees is implemented, followed by the selection, employment, and retaining of employees. Employees must be given the ability to learn and develop in new roles and the opportunity to develop their talents. In general, this means creating a pleasant working environment, dealing with employees honestly, recognising their value and enabling them to develop. The goal is that employees are engaged both to the work and to the organization, which leads to employees' engagement.
Work Engagement of Employees
The most important result of a high level of engagement is an improvement in the welfare, i.e., engagement influences the growth of employees' life satisfaction, more frequent feeling of positive emotions, and heightening self-esteem and sense of meaning. Furthermore, engaged employees enjoy better physical and mental health, e.g., they have a reduced risk of cardiovascular disease, rarely suffer from headaches or problems with the gastric system, and half as often suffer from depression (Figurska, 2015). According to Bakker (2011), engaged employees are physically, cognitively, and emotionally connected with their work roles. They feel full of energy, are dedicated to reach their work-related goals, and are often fully immersed in their work. Hughes and Rog (2008) assert that those organizations that are implementing main practices of knowledge management can appreciate a positive impact on the level of their employees' engagement.
Based on literature review, we formulated a multidimensional model of components of knowledge management (Figure 1).
Based on theoretical bases and formulated multidimensional model of approaches of knowledge management, we formulated the following hypothesis:
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Knowledge Management Components and Their Impact on Work Engagement of Employees
Figure 1. Research Model
KNOWLEDGE MANAGEMENT COMPONENTS: /th component; /=1,2.....9:
1. Appropriate employee selection 2. Appropriate employee work competencies 3. Role of mentor 4. Motivation 5. Employee leadership 6. Suitable communication 7. Appropriate organizational climate
8.	Friendly working environment
9.	Investment in human capital
Work engagement of employees
H1: A significant impact of zth knowledge management component on work engagement of employees can be identified: z = 1, 2,..., 9.
Methodology
Data and Sample
A survey among Slovenian medium - and large-sized companies was conducted to examine the impact of components of talent management on the work engagement of employees, with the sample size of 112 companies (in each company a senior manager filled the questionnaire). In the structure of employers who participated in the survey, 30.4% were females and 69.6% were males. Regarding the achieved education level of employers who participated in the research, 50.6% of respondents finished a high professional or university education, 31.3% of the respondents have a master's degree or doctorate, 14.5% of the respondents finished college, and the smallest percentage presents respondents who finished vocational training or high school (3.6%). In the survey, large companies participated with 51.9%, and medium-sized companies comprised 48.1%. The structure of employees who participated in the survey show that 43.8% were females and 56.2% were males. The sample comprised 40.2% of employees aged from 18 to 49 years and 59.8% employees aged over 50 years.
Research Instrument
The questionnaire includes 10 items (with 100 statements) of a closed type related to constructs of approaches of talent
management in the research model, represented by Figure 1, and two items (13 statements) related to the demographic characteristics of the respondents. The five-level Likert-type scale was applied, where respondents assessed their agreement/disagreement (1 = completely disagree; 2 = do not agree; 3 = partially agree; = agree; 5 = completely agree).
Implementation of components of knowledge management were measured with various constructs, as presented in Figure 1: Appropriate employee selection, appropriate employee work competencies, the role of mentor, employee leadership, suitable communication, appropriate organizational climate, motivation, friendly working environment, and investment in human capital. Statements (nine statements in our questionnaire) for the construct appropriate employee selection and appropriate employee work competencies (22 statements in our questionnaire) were formed by International Institute of Directors and Managers (2018) and author Maloney (2018). Statements for the construct the role of mentor (six statements in our questionnaire) were formed by authors Klasen in Clutterbuck (2003). Statements for the construct employee leadership (11 statements in our questionnaire) were formed by authors Cheung and Wong (2011), Jaiswal and Dhar (2017). Statements for the construct the suitable communication (11 statements in our questionnaire) were formed by Clutterbuck (2002); statements for the construct organizational climate (eight statements in our questionnaire) were formed by Schaufeli (2016) and Albrecht et al. (2018); statements for the construct motivation (nine statements in our questionnaire) were formed by Amar (2004), Islam and Ismail (2008); statements for the construct friendly working environment (10 statements in our questionnaire) were formed by Kalliath and Kalliath (2012), George and Zakkariya (2015), Bolin et al. (2008); statements for the construct investing in human capital (six statements in our questionnaire) were formed by
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Coulson-Thomas (2012), Felício et al. (2014), Vidotto et al. (2017). Statements for the construct work engagement of knowledge employees (16 statements in our questionnaire) were formed by Schaufeli and Bakker (2004) - Utrecht work engagement scale.
Statistical Analysis
Within the empirical part. In the first step, we use factor analysis to reduce a large set of measured variables into a smaller set of factors. We wanted to establish if the use of factor analysis is justified on the basis of the Kaiser-Meyer-Olkin measure of sampling adequacy (KMO > 0.5) (Kaiser, 1974) and Bartlett's test of sphericity. For communalities, the 0.4 threshold was used (Costello & Osborne, 2005). We also checked the reliability of measurement scales within the scope of inner consistency with Cronbach's alpha coefficient (Cronbach, 1951, 297-334). We also employed the factor rotation, whose purpose is to improve factors interpretability and achieve a more even distribution of variance according to factors. We used the rectangular rotation with the characteristic that the rotated factors are independent from each other. The rectangular rotation varimax maximises the variance of weight squares in every factor and, with that, simplifies the structure by columns (Manly, 2005). We saved the derived factor scores and, with that, created new variables (factors).
Based on the gained new variables (factors), we performed regression analyses to test the impact of zth multidimensional construct (knowledge management component) on employees' engagement. Within the regression analyses, the correlation coefficient, coefficient of determination, F-test, and t-test were used.
Results
In the first part, the results of factor analysis for each component of knowledge management are presented.
Appropriate Employee Selection
Table 2 presents the results of factor analysis for the construct appropriate employee selection. Value of Kaiser-Meyer-Olkin measure of sampling adequacy (KMO = 0.780) and results of Bartlett's test of sphericity (p < 0.001) suggested the use of factor analysis.
The values of all communalities for construct appropriate employee selection are higher than 0.60; therefore, we have not eliminated any variable. We obtained a two-factor solution; both factors together explain 83.82% of variability, namely, first factor 60.31%, second factor 23.51% (Table 2).
We named the two factors for construct appropriate employee selection according to the variables that were included into each factor and thus represented it, namely,
•	Factor 1: The candidate's past experiences, achievements, and knowledge;
•	Factor 2: Employee selection.
Factor weights indicate the importance of each individual variable in a factor, i.e., the higher the weight, the more important the variable for the factor is. In our case, the most important role in the candidate's past experiences, achievements, and knowledge (factor 1) is the past candidate training and education. In employee selection (factor 2), the
Table 2. Results of Factor Analysis for the Construct Appropriate Employee Selection
		Factor Loadings
Statement	Communalities	
		1 2
We employ exclusively persons with high potential	0.887	0.882	0.331
We employ exclusively persons with high work efficiency	0.860	0.904	0.208
We employ persons who are capable of quality work	0.609	0.764	-0.157
We employ persons with work experience	0.765	-0.051	0.873
Candidate's achievements are important	0.925	0.241	0.931
Candidate's competencies are important	0.779	0.883	0.018
Candidate's past training and education play an important role	0.924	0.204	0.939
Candidate's ability to think creatively is important	0.945	0.779	0.582
Candidate's ability to connect/network with others is important	0.851	0.799	0.462
Kaiser-Meyer-Olkin measure: 0.780			
Cumulative percentage of explained variance for first factor: 60.315 % Cumulative percentage of explained variance for second factor: 23.507 %			
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most important variable is "We employ people exclusively with high work efficiency."
The value of Cronbach's alpha for appropriate employee selection is exemplary in the case of both factors together (0.913) and with factor 1 (0.931) and with factor 2 (0.925).
Appropriate Employee Work Competencies
Table 3 presents the results of factor analysis for the construct appropriate employee work competencies. Value of Kaiser-Meyer-Olkin measure of sampling adequacy (KMO = 0.605), and results of Bartlett's test of sphericity (p < 0.001) suggested the use of factor analysis.
Again, the values of all communalities for construct appropriate employee work competencies are higher than 0.50. We obtained a two-factor solution; both factors together explain the 81.31% of variability, namely, first factor 63.07%, second factor 18.24% (Table 3).
Because no particular distribution of variables across the two factors was present, we use the general names for factors:
•	Factor 1: appropriate employee work competencies 1;
•	Factor 2: appropriate employee work competencies 2.
In our case, the most important role in the appropriate employee work competencies 1 (factor 1) has the variable "Employees must have a positive attitude towards change." In appropriate employee work competencies 2 (factor 2), the
Table 3. Results of Factor Analysis for the Construct Appropriate Employee Work Competencies
		Factor loadings
Statement	Communalities	
		1 2
An employee must have a positive attitude to changes	0.893	0.041	0.944
An employee must have managerial skills	0.716	0.802	-0.270
An employee must be able to assume responsibilities and risks	0.679	0.605	0.559
An employee must be able to solve various problems	0.838	0.593	0.697
An employee must be able to make decisions	0.863	0.893	0.256
An employee must be able to use a systematic and analytical approach in the company	0.871	0.648	0.672
An employee must be able to make good decisions even under pressure	0.899	0.905	0.285
An employee must be able to judge the consequences of his decisions	0.868	-0.007	0.932
An employee must be able to use good experiences from the past	0.780	0.883	-0.017
An employee must be able to see a problem comprehensively	0.882	0.778	0.526
Employee innovation and creativity are important	0.885	0.860	0.381
An employee must encourage and use an honest way of communication	0.790	0.532	0.712
An employee must provide accurate and consistent information and instructions	0.587	0.085	0.761
An employee must encourage and motivate other colleagues	0.778	0.870	-0.145
An employee must delegate wisely and effectively	0.900	0.816	0.484
An employee must maintain a good, fun working environment with appropriate work challenges	0.753	0.832	0.247
An employee must be able to develop cooperation at all levels of the company	0.874	0.762	0.541
An employee must be able to solve conflicts in the company	0.910	0.587	0.752
An employee must be able to provide feedback and constructive criticism	0.770	0.859	0.181
An employee must be able to establish informal relationships to achieve goals	0.719	0.781	0.331
An employee must be a good negotiator	0.749	0.850	0.165
An employee must be flexible	0.886	-0.020	0.941
Kaiser-Meyer-Olkin measure: 0.605
Cumulative percentage of explained variance for first factor: 63.071% Cumulative percentage of explained variance for second factor: 18.240%
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most important variable is "An employee must be able to make good decisions even under pressure."
The value of Cronbach's alpha for appropriate employee work competencies is exemplary in the case of both factors together (0.968) and with factor 1 (0.971) and with factor 2 (0.947).
The Role of Mentor
Table 4 presents the results of factor analysis for the construct the role of mentor. Value of Kaiser-Meyer-Olkin measure of sampling adequacy (KMO = 0.708) and the results of Bart-lett's test of sphericity (p < 0.001) again suggest the use of factor analysis.
The values of all communalities for the construct role of mentor are higher than 0.60. Total variance explained is 79.86%. All factor loadings for construct the role of mentor are higher than 0.80. In our case, the most important role of mentor is "The mentor helps to set up an employee development plan for the company" (Table 4). The value of Cronbach's alpha of the factor the role of mentor is 0.949; therefore, the reliability of the measurement of the role of mentor is exemplary.
Employee Leadership
Table 5 presents the results of factor analysis for the construct employee leadership. Value of Kaiser-Meyer-Olkin
Table 4. Results of Factor Analysis for the Construct Role of Mentor
Statement	Communalities	Factor Loadings
A mentor assists in evaluation of new candidates for employment	0.646	0.804
A mentor decides on employment of a new candidate	0.775	0.880
A mentor introduces a candidate to a new workplace	0.712	0.844
A mentor participates in the promotion of the employee	0.909	0.953
A mentor helps to set up an employee development plan in the company	0.913	0.956
A mentor orders the tasks that the employees perform in the framework of their work tasks	0.837	0.915
Kaiser-Meyer-Olkin measure: 0.708		
Cumulative percentage of explained variance: 79.857%
Table 5. Results of Factor Analysis for the Construct Employee Leadership
		Factor Loadings
Statement	Communalities	
		1 2
In the company, we are concerned with good relationships	0.915	0.535	0.793
In the company, we are concerned with the prevalence of respect and trust	0.842	0.069	0.915
In the company, we monitor the performance of employees	0.633	0.573	0.552
We pay attention to employees at the individual level	0.797	0.799	0.399
In the company, we ensure that every employee is adequately qualified or educated	0.852	0.744	0.546
In the company, we care for employee satisfaction	0.858	0.574	0.727
In the company, we care for adequate motivation of employees	0.898	0.794	0.517
In the company, we care for the well-being and health of employees	0.726	0.316	0.792
In the company, we are concerned with keeping employees with the highest potential	0.873	0.934	0.028
In the company, we are committed to continual improvements	0.926	0.550	0.790
We seek an opportunity to improve the way of working and cooperation between employees	0.925	0.803	0.528
Kaiser-Meyer-Olkin measure: 0.740
Cumulative percentage of explained variance for first factor: 73.775% Cumulative percentage of explained variance for second factor: 10.270%
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measure of sampling adequacy (KMO = 0.740) and results of Bartlett's test of sphericity (p < 0.001) suggested the use of factor analysis.
The values of all communalities for construct employee leadership are higher than 0.60; therefore, we have not eliminated any variable. The two factors obtained explain 84.04% of variability, namely, first factor 73.77%, second factor 10.27% (Table 5).
Similar to the previous construct, no particular distribution of variables across the two factors was present; therefore, we used the general names for factors:
•	Factor 1: Employee leadership 1;
•	Factor 2: Employee leadership 2.
In our case, the most important role in the employee leadership 1 (factor 1) has variable "The company takes care of keeping employees with the highest potential." In employee leadership 2 (factor 2), the most important variable is "In the company, we are concerned with the prevalence of respect and trust."
The value of Cronbach's alpha for employee leadership is exemplary in the case of both factors together (0.947) and with factor 1 (0.935) and with factor 2 (0.942).
Suitable Communication
Table 6 presents the results of factor analysis for the construct suitable communication. The value of Kaiser-Meyer-Olkin measure of sampling adequacy (KMO = 0.611) and results of Bartlett's test of sphericity (p < 0.001) suggested the use of factor analysis.
The values of all communalities for construct suitable communication are higher than 0.60. In this case the three factors solution was formed: three factors together explain 88.50% of variability, namely, first factor 64.83%, second factor 12.17%, third factor 11.50% (Table 6).
We named all three factors for construct suitable communication according to the variables that were included in each factor and represent it, namely:
•	Factor 1: Communication with employees in the company;
•	Factor 2: Possibilities of communication in the company;
•	Factor 3: Information about work implementation.
In our case, the most important role in the communication with employees in the company (factor 1) has the variable "We organise periodic meetings." In possibilities of communication in the company (factor 2), the most important variable is "In the company, we emphasise internal communication." In information about work implementation
Table 6. Results of Factor Analysis for the Construct Suitable Communication
Statement			Factor Loadings	
	Communalities	1	2	3
In the company, we emphasise internal communication	0.973	0.197	0.959	0.125
We offer a possibility of contacting by e-mail and by phone	0.662	0.316	0.644	0.383
We organise periodic meetings	0.877 1	0.895	0.134	0.241
Employees have precise information about the company's goals	0.946	0.209	0.792	0.525
Employees have precise information about the roles in the company	0.983	0.264	0.260	0.920
Employees have detailed information necessary for understanding the work task	0.972	0.244	0.235	0.925
Employees receive reports on their work, achieved results and problems at work	0.850	0.749	0.038	0.536
Exchange of information and opinions prevails in the company	0.751	0.765	0.318	0.255
We regularly organise meetings where employees exchange their ideas, solutions	0.917	0.851	0.416	0.142
We regularly resolve possible conflicts that have arisen	0.904	0.587	0.743	0.082
We try to obtain feedback on employee satisfaction	0.899 1	0.826	0.430	0.177
Kaiser-Meyer-Olkin measure: 0.611				
Cumulative percentage of explained variance for first factor: 64.829%				
Cumulative percentage of explained variance for second factor: 12.169%				
Cumulative percentage of explained variance for third factor: 11.498%				
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(factor 3), the most important variable is "Employees have detailed information necessary for understanding the work task."
The value of Cronbach's alpha for suitable communication is exemplary in the case of all factors together (0.936) and with factor 1 (0.937), factor 2 (0.877), and with factor 3 (0.993).
Appropriate Organizational Climate
Table 7 presents the results of factor analysis for the construct appropriate organizational climate. Value of Kaiser-Meyer-Olkin measure of sampling adequacy (KMO = 0.692), and results of Bartlett's test of sphericity (p < 0.001) suggested the use of factor analysis.
The values of all communalities for construct appropriate organizational climate are higher than 0.60. Two factors obtained explain 86.83% of variability, namely, first factor 70.72%, second factor 16.11% (Table 7).
Again, no particular distribution of variables across the two factors was present; therefore, we used the general names for factors:
•	Factor 1: Organizational climate in the company 1;
•	Factor 2: Organizational climate in the company 2.
In our case, the most important role in the organizational climate in company 1 (factor 1) has the variable, "In the company, autonomy is important." In the organizational climate in company 2 (factor 2), the most important variable is "In the company, the employee satisfaction is important."
Table 7. Results of Factor Analysis for the Construct Appropriate Organizational Climate
Factor Loadings
Statement	Communalities	1	2
In the company, interactions with people are important	0.929	0.886	0.379
In the company, the employee satisfaction is important	0.959	0.118	0.972
In the company, loyalty is important	0.965	0.911	0.367
In the company, the employee well-being is important	0.866	0.805	0.467
In the company, cooperation with employees is important	0.807	0.383	0.812
In the company, solidarity is important	0.600	0.304	0.713
In the company, the awareness of people or employees is important	0.959	0.913	0.355
In the company, autonomy is important	0.861	0.927	0.047
Kaiser-Meyer-Olkin measure: 0.692
Cumulative percentage of explained variance for first factor: 70.719% Cumulative percentage of explained variance for second factor: 16.111%
Table 8. Results of Factor Analysis for the Construct Motivation
Statement	Communalities	Factor Loadings
In the company, we emphasise the motivation of employees	0.845	0.919
We strive to ensure that each employee is especially motivated in the performance of his work (individual approach to the employee)	0.884	0.940
We provide our employees appropriate pay for success	0.718	0.847
An employee receives a praise or recognition for achieving successful results	0.794	0.891
We enable our employees to attend education, training	0.897	0.947
Employees have the possibility of career development	0.802	0.896
We provide flexible working hours to our employees	0.727	0.853
We provide autonomy at work to our employees	0.649	0.806
In the company, good relationships prevail	0.609	0.781
Kaiser-Meyer-Olkin measure: 0.604		
Cumulative percentage of explained variance: 76.959%		
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The value of Cronbach's alpha for appropriate organizational climate is exemplary in the case of both factors together (0.907) and with factor 1 (0.970) and with factor 2 (0.841).
Motivation
Table 8 presents the results of factor analysis for the construct motivation. Value of Kaiser-Meyer-Olkin measure of sampling adequacy (KMO = 0.604), and the results of Bartlett's test of sphericity (p < 0.001) suggest the use of factor analysis.
The values of all communalities for construct motivation are higher than 0.60. Total variance explained is 76.96 %. All factor loadings for construct motivation are higher than 0.70. In our case, the most important role in the motivation
has the variable "We enable our employees to attend education, training." (Table 8). The value of Cronbach's alpha of the factor motivation is 0.957; therefore, the reliability of the measurement of motivation is exemplary.
Friendly Working Environment
Table 9 presents the results of factor analysis for the construct friendly working environment. Value of Kaiser-Meyer-Olkin measure of sampling adequacy (KMO = 0.723) and the results of Bartlett's test of sphericity (p < 0.001) suggest the use of factor analysis.
The values of the communalities for the variables in the construct of friendly working environment are higher than 0.40. Total variance explained is 73.96%. All factor loadings for
Table 9. Results of Factor Analysis for the Construct Friendly Working Environment
Statement	Communalities	Factor Loadings
We provide employees the possibility of flexible working hours	0.612	0.782
We provide employees a balance between work and private life	0.606	0.779
We care for creating a pleasant company culture and climate	0.763	0.874
We offer our employees the possibility to participate in teams	0.904	0.951
In the company, we emphasise the intergenerational synergy	0.896	0.947
We organise events for socialising of employees	0.783	0.885
In the company, we care for a friendly working environment	0.758	0.871
We care for the well-being of our employees	0.818	0.904
We offer various programs for well-being and coping with stress	0.414	0.643
We are focused on solving individual problems of employees at the workplace	0.842	0.918
Kaiser-Meyer-Olkin measure: 0.723		
Cumulative percentage of explained variance: 73.965%
Table 10. Results of Factor Analysis for the Construct Investment in Human Capital
Statement	Communalities	Factor Loadings
We enable our employees to develop innovations and encourage them in innovative thinking	0.856	0.925
We encourage employees to achieve successful business results	0.932	0.966
We encourage employees to solve problems efficiently	0.961	0.980
The training of employees is focused on the development of specific competencies and skills, in line with the needs of the company	0.953	0.976
We enable our employees to regularly attend education, training	0.913	0.956
We offer employees the opportunity to further develop their careers	0.755	0.869
We promote a healthy lifestyle for our employees	0.697	0.835
Kaiser-Meyer-Olkin measure: 0.810		
Cumulative percentage of explained variance: 86.691%		
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construct friendly working environment are higher than 0.60. In our case, the most important role in the friendly working environment has the variable "We offer our employees the possibility to participate in teams." (Table 9). The value of Cronbach's alpha of the factor friendly working environment is 0.948; therefore, the reliability of the measurement of friendly working environment is exemplary.
Investment in Human Capital
Table 10 presents the results of factor analysis for the construct investment in human capital. Value of Kaiser-Meyer-Olkin measure of sampling adequacy (KMO = 0.810) and the results of Bartlett's test of sphericity (p < 0.001) suggest the use of factor analysis.
The values of the communalities for the variables in the construct of investment in human capital are higher than 0.60. Total variance explained is 86.69%. All factor loadings for construct investment in human capital are higher than 0.80. In our case, the most important role in the investment in human capital has variable "We encourage employees to solve problems efficiently." (Table 10). The value of Cronbach's alpha of the factor investment in human capital is 0.971, therefore the reliability of the measurement of investment in human capital is exemplary.
Work Engagement of Employees
Table 11 presents the results of factor analysis for the construct work engagement of employees. Value of Kaiser-Meyer-Olkin measure of sampling adequacy (KMO = 0.810) and the results of Bartlett's test of sphericity (p < 0.001) suggest the use of factor analysis.
The values of the communalities for the variables in the construct of work engagement of knowledge employees are higher than 0.70. Total variance explained is 89.70%. All factor loadings for construct work engagement of knowledge employees are higher than 0.80. In our case, the most important role in the work engagement of knowledge employees has the variable "I am enthusiastic about my job." (Table 11). The value of Cronbach's alpha of the factor work engagement of employees is 0.992; therefore, the reliability of the measurement of work engagement of knowledge employees is exemplary.
In the second part of analysis, regression models were tested, with the purpose to test the impact of the ith component of knowledge management on the work engagement of knowledge employees, i = 1,2,...,9.
After saving factors' scores as new variables, we performed a regression analysis to test the hypotheses; for the ith
Table 11. Results of Factor Analysis for the Construct Work Engagement of Employees
Statement	Communalities	Factor loadings
At my work, I feel bursting with energy	0.882	0.939
I find the work that I do full of meaning and purpose	0.864	0.930
Time flies when I'm working	0.873	0.934
At my job, I feel strong and vigorous	0.933	0.966
I am enthusiastic about my job	0.987	0.993
When I am working, I forget everything else around me	0.964	0.982
My job inspires me	0.977	0.989
When I get up in the morning, I feel like going to work	0.896	0.947
I feel happy when I am working intensely	0.846	0.920
I am proud on the work that I do	0.812	0.901
I am immersed in my work	0.891	0.944
I can continue working for very long periods at a time	0.873	0.934
I get carried away when I'm working	0.954	0.977
At my job, I am very resilient, mentally	0.889	0.943
It is difficult to detach myself from my job	0.768	0.876
At my work I always persevere, even when things do not go well	0.943	0.971
Kaiser-Meyer-Olkin measure: 0.810		
Cumulative percentage of explained variance: 89.702%		
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Knowledge Management Components and Their Impact on Work Engagement of Employees
component of knowledge management, the separate regression model was formed. In the continuation, we present the results of testing the set of Hypotheses H1: A significant impact of ith knowledge management component on work engagement of knowledge employees can be identified; i = 1, 2,..., 9.
Table 12 shows regression analysis results. Model 1
The value of the multiple correlation coefficient between dependent variable (work engagement of employees) and independent variables (Factor 1: The candidate's past experiences, achievements, and knowledge and Factor 2: Employee selection) is R = 0.847, which indicates a strong connection between the variables. The value of the adjusted determination coefficient is 0.715. The adjusted determination coefficient explains that 71.5% of the variance of the dependent variable (work engagement of knowledge employees) is explained with the variance of the independent variables (Factor 1: The candidate's past experiences, achievements, and knowledge and Factor 2: Employee selection). We have established the reliability of the derived regression function with the F-test: F = 315.448, p < 0.001. The results of the regression (Table 12) indicated that the regression coefficient of appropriate employee selection - factor 1: The candidate's past experiences, achievements, and knowledge was 0.792 (P = 0.792) and was significantly different from 0 (p < 0.001). The regression coefficient of appropriate employee selection - Factor 2: Employee selection was 0.300 (P = 0.300) and was significantly different from 0 (p < 0.001).
Model 2
The value of the multiple correlation coefficient between dependent variable (work engagement of employees) and independent variables (Factor 1: Appropriate employee work competencies 1 and Factor 2: Appropriate employee work competencies 2) is R = 0.862, which indicates a strong connection between the variables. The value of the adjusted determination coefficient is 0.741. The adjusted determination coefficient explains that 74.1% of the variance of the dependent variable (work engagement of knowledge employees) is explained with the variance of the independent variables (Factor 1: Appropriate employee work competencies 1 and Factor 2: Appropriate employee work competencies 2). We have established the reliability of the derived regression function with the F-test: F = 360.130, p < 0.001. The results of the regression (Table 12) indicated that the regression coefficient of appropriate employee work competencies -Factor 1: Appropriate employee work competencies 1 was
0.729 (P = 0.729) and was significantly different from 0 (p < 0.001). The regression coefficient of appropriate employee work competencies - Factor 2: Appropriate employee work competencies 2 was 0.459 (P = 0.459) and was significantly different from 0 (p < 0.001).
Model 3
The value of correlation coefficient between the dependent variable (work engagement of employees) and independent variable (the role of mentor) is R = 0.668, which indicates there is a moderate connection between the variables. The value of determination coefficient is 0.447. The determination coefficient explains that 44.7% of the variance of the dependent variable (work engagement of knowledge employees) is explained with the variance of the independent variable (the role of mentor). We have established the reliability of the derived regression function with the F-test: F = 201.725, p < 0.001. The results of the regression (Table 12) indicate that the regression coefficient of the role of mentor is 0.668 (P = 0.668) and is significantly different from 0 (p < 0.001).
Model 4
The value of the multiple correlation coefficient between dependent variable (work engagement of employees) and independent variables (Factor 1: Employee leadership 1 and Factor 2: Employee leadership 2) is R = 0.858, which indicates a strong connection between the variables. The value of the adjusted determination coefficient is 0.733. The adjusted determination coefficient explains that 73.3% of the variance of the dependent variable (work engagement of knowledge employees) is explained with the variance of the independent variables (Factor 1: Employee leadership 1 and Factor 2: Employee leadership 2). We have established the reliability of the derived regression function with the F-test: F = 345.970, p < 0.001. The results of the regression (Table 12) indicate that the regression coefficient of employee leadership - Factor 1: Employee leadership 1 is 0.717 (P = 0.717) and was significantly different from 0 (p < 0.001). The regression coefficient of Employee leadership - Factor 2: Employee leadership 2 is 0.471 (P = 0.471) and is significantly different from 0 (p < 0.001).
Model 5
The value of the multiple correlation coefficient between dependent variable (work engagement of employees) and independent variables (Factor 1: Communication with employees in the company, Factor 2: Possibilities of communication in the company and Factor 3: Information about
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Table 12. Regression Analysis Results
			Unstandardized Standardized Coefficients Coefficients		
Dependent variable		Independent variable	B Std. error Beta	t	Sig.
		Appropriate employee selection - Factor 1: The candidate' past experiences, achievements, and knowledge.	0.792 0.034 0.792	23.493	0.000
		Appropriate employee selection - Factor 2: Employee selection	0.300 0.034 0.300	8.888	0.000
		Model 1: R = 0.847; Adjusted R-square = 0.715; F-test: F = 315.448, p<0.001			
		Appropriate employee work competencies - Factor 1: Appropriate employee work competencies 1	0.729 0.032 0.729	22.708	0.000
		Appropriate employee work competencies - Factor 2: Appropriate employee work competencies 2	0.459 0.032 0.459	14.305	0.000
		Model 2: R = 0.862; Adjusted R-square = 0.741; F-test: F = 360.130, p<0.001			
		Role of mentor	0.668 0.047 0.668	14.203	0.000
		Model 3: r = 0.668; R-square = 0.447; F-test: F = 201.725, p<0.001			
		Employee leadership - Factor 1: Employee leadership 1	0.717 0.033 0.717	21.980	0.000
		Employee leadership - Factor 2: Employee leadership 2	0.471 0.033 0.471	14.451	0.000
		Model 4: R = 0.858; Adjusted R-square = 0.733; F-test: F = 345.970, p<0.001			
Work engagement of employees		Suitable communication -Factor 1: Communication with employees in the company	0.703 0.037 0.703	19.054	0.000
		Suitable communication -Factor 2: Possibilities of communication in the company	0.402 0.037 0.402	10.898	0.000
		Suitable communication -Factor 3: Information about work implementation	0.089 0.037 0.089	2.419	0.000
		Model 5: R = 0.814; Adjusted R-square = 0.659; F-test: F = 162.557, p<0.001			
		Appropriate organizational climate - Factor 1: Organizational climate in the company 1	0.776 0.037 0.776	21.076	0.000
		Appropriate organizational climate - Factor 2: Organizational climate in the company 2	0.244 0.037 0.244	6.637	0.000
		Model 6: R = 0.814; Adjusted R-square = 0.660; F-test: F = 244.121, p<0.001			
		Motivation	0.849 0.033 0.849	25.367	0.000
		Model 7: r = 0.849; R-square = 0.720; F-test: F = 643.472, p<0.001			
		Friendly working environment	0.824 0.036 0.824	22.988	0.000
		Model 8: r = 0.824; R-square = 0.679; F-test: F = 528.438, p<0.001			
		Investment in human capital	0.861 0.032 0.861	26.819	0.000
		Model 9: r = 0.861; R-square = 0.742; F-test: F = 719.278, p<0.001			
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work implementation) is R = 0.814, which indicates there is a strong connection between the variables. The value of the adjusted determination coefficient is 0.659. The adjusted determination coefficient explains that 65.9% of the variance of the dependent variable (work engagement of knowledge employees) is explained with the variance of the independent variables (Factor 1: Communication with employees in the company, Factor 2: Possibilities of communication in the company and Factor 3: Information about work implementation). We have established the reliability of the derived regression function with the F-test: F = 162.557, p < 0.001. The results of the regression (Table 12) indicated that the regression coefficient of suitable communication -Factor 1: Communication with employees in the company was 0.703 (P = 0.703) and was significantly different from
0	(p < 0.001). The regression coefficient of suitable communication - Factor 2: Possibilities of communication in the company was 0.402 (P = 0.402) and was significantly different from 0 (p < 0.001). The regression coefficient of Suitable communication - Factor 3: Information about work implementation was 0.089 (P = 0.089) and was significantly different from 0 (p < 0.001).
Model 6
The value of the multiple correlation coefficient between the dependent variable (work engagement of employees) and independent variables (Factor 1: organizational climate in the company 1 and Factor 2: organizational climate in the company 2) is R = 0.814, which indicates a strong connection between the variables. The value of the adjusted determination coefficient is 0.660. The adjusted determination coefficient explains that 66% of the variance of the dependent variable (work engagement of knowledge employees) is explained with the variance of the independent variables (Factor 1: organizational climate in the company
1	and Factor 2: organizational climate in the company 2). We have established the reliability of the derived regression function with the F-test: F = 244.121, p < 0.001. The results of the regression (Table 12) indicate that the regression coefficient of Factor 1: organizational climate in the company 1 is 0.776 (P = 0.776) and is significantly different from 0 (p < 0.001). The regression coefficient of Factor 2: organizational climate in company 2 was 0.244 (P = 0.244) and was significantly different from 0 (p < 0.001).
Model 7
The value of correlation coefficient between dependent variable (work engagement of employees) and independent
variable (motivation) is r = 0.849, which indicates a strong connection between the variables. The value of determination coefficient is 0.720. Determination coefficient explains that 72% of the variance of the dependent variable (work engagement of knowledge employees) is explained with the variance of the independent variable (motivation). We have established the reliability of the derived regression function with the F-test: F = 643.472, p < 0.001. The results of the regression (Table 12) indicate that the regression coefficient of motivation is 0.849 (P = 0.849) and is significantly different from 0 (p < 0.001).
Model 8
The value of correlation coefficient between dependent variable (work engagement of employees) and independent variable (friendly working environment) is r = 0.824, which indicates a strong connection between the variables. The value of determination coefficient is 0.679. The determination coefficient explains that 67.9% of the variance of the dependent variable (work engagement of knowledge employees) is explained with the variance of the independent variable (friendly working environment). We have established the reliability of the derived regression function with the F-test: F = 528.438, p < 0.001. The results of the regression (Table 12) indicate that the regression coefficient of friendly working environment is 0.824 (P = 0.824) and is significantly different from 0 (p < 0.001).
Model 9
The value of correlation coefficient between dependent variable (work engagement of employees) and independent variable (investment in human capital) is r = 0.861, which indicates a strong connection between the variables. The value of determination coefficient is 0.742. Determination coefficient explains that 74.2% of the variance of the dependent variable (work engagement of knowledge employees) is explained with the variance of the independent variable (investment in human capital). We have established the reliability of the derived regression function with the F-test: F = 719.278, p < 0.001. The results of the regression (Table 12) indicate that the regression coefficient of investment in human capital is 0.861 (P = 0.861) and is significantly different from 0 (p < 0.001).
Based on results we confirm the set of hypotheses H1: A significant impact of ith knowledge management component on work engagement of knowledge employees can be identified; i = 1, 2,..., 9.
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Conclusion
Companies that want to survive in unpredictable and complex competitive markets should be able to quickly adapt to the new dynamics of business. This means that they must constantly invest in appropriate approaches of knowledge management and in work engagement of their employees. Knowledge employees are the greatest asset for any enterprise. One of the most important roles in a company is to ensure that employees have the right skills and competences to achieve successful business results. Based on the results, we found that appropriate approaches of knowledge management have a significant positive impact on work engagement of knowledge employees in Slovenian companies.
Moreover, our research reveals that each of the nine dimensions of the knowledge management analysed (namely, appropriate employee selection, appropriate employee work competencies, the role of mentor, motivation, employee leadership, suitable communication, appropriate organizational climate friendly working environment and investment in human capital) has a significant and positive impact on the work engagement of employees. Because the engaged employees, who will take maximum advantage of their potential, are the key factor of the competitiveness and performance of the company, it must be able to employ, identify, and, in particular, develop and retain their knowledge employees. Companies that invest in their employees and provide an appropriate working environment achieve higher productivity, better business results, and competitiveness. Companies need to put into consideration the various elements of knowledge management processes in order to enhance organization learning. It is important therefore for organizations to invest in knowledge creation, knowledge sharing, and retention as well knowledge acquisition and application. Also, companies must invest in employee motivation, in good leadership, suitable communication,
appropriate organizational climate, create a friendly working environment, and also invest in human capital of their employees. Bakker (2017) emphasises that, in a highly competitive business world, where the rate of change has been accelerating, organizations increasingly rely on the strengths and talents of their employees.
Modern organizations that want to stay competitive need engaged employees, i.e., individuals who have high levels of energy, dedication, and absorption. Engaged employees have an abundance of "resources," which they can invest in their work. They are enthusiastic about their work, immersed in their work activities, and persistent when confronted with challenges and hindrances. Moreover, research of the past decade has provided strong evidence for the notion that engagement leads to key organizational outcomes, including creativity and innovation, client satisfaction, positive financial results, and reduced sickness absenteeism.
This research is limited to the field of knowledge management. Theoretical framework and our research present the importance of components of knowledge management on work engagement of employees. The limitation of our research is also that not all important factors shaping engagement of employees were analysed; however, we focused on the components of the knowledge management, as we want to study this particular and important part of the knowledge management.
As an opportunity for future research, we see an upgrade of the measurement instrument with new constructs in the field of components of knowledge management. We suggest that the survey is carried out on the basis of a comparison of managing knowledge employees and their work engagement between different countries. Also, our further research refers to analysing different constructs with structural equation modelling (SEM).
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Authors
Maja Rozman has acquired her Master degree at the Faculty of Economics and Business in Maribor at the Department of Finance and the PhD at the Department of Management and Organization. She is also a teaching assistant at the Faculty of Economics and Business at the Department of Quantitative Economic Analyses. Her research work is focused on contemporary management problems in organisations, especially in the field of human resource management.
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Zhanna Shmeleva is an associate professor in the Department of Foreign Languages at the Center of international Links and Business, Krasnoyarsk State Agrarian University, Krasnoyarsk, Russia. Her research is focused on the methods of effective teaching in the field of foreign languages and on the social-philosophical analysis of the language as a phenomenon, which includes informative and communicative components. She has published over 150 original scientific papers, 30 textbooks, and three monographs and has participated at several scientific conferences.
Polona Tominc, PhD, is a full-time professor in the Department of Quantitative Economic Analysis at the Faculty of Economics and Business, University of Maribor. Her research is focused on statistical methods in economics and business sciences, especially in the field of entrepreneurship, gender differences, and behavioural differences between social groups in different fields of management. She has published over 60 original scientific papers, with several of them in the Scopus or WoS databases, and has participated in several scientific conferences. She is an author or co-author of monograph publications and of chapters in scientific monographs. She is a team member of DIANA international research group, aimed at researching women entrepreneurship, and a member of Global Entrepreneurship Monitor Slovenia research team. She leads the research program "Entrepreneurship for innovative Society."
Komponente managementa znanja in njihov vpliv na delovno zavzetost zaposlenih
Izvleček
V luči globalizacije in sodobnega poslovanja so podjetja izpostavljena izzivom, ki jih povzroča nepredvidljivo in kompleksno konkurenčno okolje. Poslovno okolje s svetovnimi trendi in strogo konkurenco na svetovnem trgu je povzročilo bistvene spremembe, ki jih morajo podjetja uvesti v svoje poslovanje. S tega vidika v podjetju vse bolj postaja pomemben management človeških virov in njegov vložek v znanje zaposlenih. Glavni cilj prispevka je ugotoviti vpliv komponent managementa znanja na delovno zavzetost zaposlenih v slovenskih podjetjih. V empiričnem delu raziskave je sodelovalo 112 slovenskih podjetij. Na vprašalnik, ki je temeljil na podlagi obstoječih merilnih lestvic, so odgovorili managerji in zaposleni. Rezultati raziskave pripomorejo k boljšemu razumevanju pomena managementa znanja v slovenskih podjetjih in njegov pomen v poslovni strategiji, ki mora biti v celoti vključena v vse procese, povezane z zaposlenimi v podjetju.
Ključne besede: management znanja, komponente managementa znanja, zaposleni
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