Abstract
Given that knowledge is one of the most important human resource values, the manner of its acquisition, transfer and development within an organisation is crucial. It should come as no surprise that given the link between knowledge acquisition and development in most spheres, several individuals wish to restrict their knowledge to themselves, as it gives them value in the labour market. Yet, if we inculcate knowledge sharing habits among individuals at an early age, so that they not only impart but also acquire knowledge through knowledge transfer, information acquisition can become a mutually beneficial process for both providers and acquirers. In this study, we conducted a survey among university students in Hungary to investigate how open they are about sharing their knowledge with each other and what they expect from their peers in exchange for the information they have. Data analyses showed that students' willingness to transfer knowledge and their expectations in return for the knowledge transferred are greatly influenced by their mutual relationships, but the strength of these relationships impact the rewards they expect for knowledge transfer.
1 Introduction
Knowledge management is currently one of the most popular areas of research. The concept is very diverse and includes the rational management of knowledge, the exchange of experiences and the management of human resources with knowledge. Bencsik et al. (2018) suggested that knowledge management also considers how knowledge and experience can be best utilised, and that such a strategy must be in line with corporate objectives. Knowledge management encompasses several functions, including knowledge acquisition and sharing. Organisations that can effectively transfer knowledge from one unit to another experience several positive effects. Among other things, they will be more productive and more likely to survive than those that do not have an elaborate knowledge transfer system. However, successful knowledge transfer is not easy (Argote et al. 2000).
It should be stated that the terms ‘knowledge transfer’ and ‘knowledge sharing’ are not always differentiated in the literature (Liyanage et al. 2009). However, as we wish to differentiate between them, it would be useful to use the term ‘knowledge sharing’ when the exchange of knowledge is between and among individuals; but it usually does not have a clear a priori objective (Paulin – Suneson 2011) Therefore, ‘knowledge transfer’ should be used when the focus is on groups, departments and organizations and when knowledge is viewed as an object.
Abjanbekov and Padilla (2004) assumed that knowledge transfer could serve as a catalyst for organisations' goal achievement, and one of their sources of knowledge transfer might be higher education institutions. One of the fundamental tasks of these institutions is the transfer of knowledge, primarily between lecturers and students. However, after graduation, students leaving education institutions need to know for themselves how to successfully acquire and transfer knowledge. Thus, the present study deals with how students relate to knowledge transfer among themselves during their studies, how they socialise in order to be open to knowledge transfer in a workplace, the factors that influence who they share information with and the information that they share. We formulated the aim of the research and the research question, tried to examine the value ascribed to knowledge transfer by students, and sought to identify the expectations connected with it. Furthermore, the study also analysed whether students expect something in exchange for knowledge transfer and which factors influence these expectations. We conducted this study involving 552 students in higher education institutions in Hungary, in 2021. The results are highly instructive not only for universities but also for employer organisations. We concluded that students' expectations related to receiving credit for their knowledge are significantly influenced by their mutual relationships. Financial expectations increase with distance in relationships. A stronger friendship is predicted to lead to a more affectionate and pleasant relationship. The research paper starts with a summary of the literature review; research methods and results follow; and the discussion and conclusion sections have been placed at the end.
2 Literature review: reflections on knowledge transfer and its practice in education
While examining ‘knowledge’, it should be noted that there is a hierarchy moving upward from data to information to knowledge (Albers – Brewer 2003). According to Dretske (1981), data consists of raw numbers and facts, information is processed data, and knowledge is authenticated information. Above these levels lies expertise: specialized, deep knowledge and understanding of a certain field that is far above the average (Bender – Fish 2000). From another perspective, knowledge is a mixture of framed experiences, values, contextual information and expert insight (Davenport – Prusak 1998).
Alavi and Leidner (2001) observed that knowledge may be viewed from several perspectives: it may be a state of mind, an object, a process, the condition of having access to information, or a capability. Liyange et al.'s (2009) study concurred with this.
We believe that knowledge behaves differently, and so it should be managed differently. In this study, knowledge management was considered to be focused on knowledge flows and the process of sharing and distributing knowledge. Therefore, the process perspective was adopted. Since this study viewed knowledge as a process, it focused on the flow of knowledge, that is, how knowledge is created, shared and distributed.
Knowledge sharing occurs when people exchange their knowledge in a two-way process (Truch et al. 2002). The term ‘knowledge transfer’, however, is used when there is active communication of knowledge and an active consultation with others to acquire it (van der Hoof et al. 2004). The method selected for successful knowledge transfer depends on both the source and the receiver (Nonaka – Takeuchi 1995). In this study, various methods, sources and receivers have been observed, in order to present a model of how university students transfer their knowledge and share it with their peers. The questionnaire used to conduct the survey focused on the connection between the provider and the receiver; it was supposed that the stronger the connection, the more effective the transfer is.
Furthermore, knowledge transfer and exchange refer to the interactive communication of knowledge between the transmitters and users of information (Kiefer et al. 2005) The aim of knowledge sharing is to determine how acquired knowledge may be transferred.
Several conditions need to be met for the success of knowledge transfer, one being the openness of both the knowledge provider and the recipient. An important consequence of knowledge transfer is that it results in a certain degree of change in the attitude and behaviour of the players involved in the process and initiates innovative ideas they may not have considered before the exchange. However, it is normal for the knowledge recipient to not use the acquired knowledge. Such a situation may be attributed to several reasons: mistrust, lack of time or opportunity, pride or stubbornness, or a firm resistance to change, to name a few (Bencsik 2013).
Moreover, knowledge transfer can lead to a process of learning, as the sharers will only be able to explain something well if they fully understand it themselves (Wasko – Faraj 2000). The transfer of knowledge can be affected by several factors, such as the corporate environment, company habits and national culture (Stone – Tsai 2003), or OVID-19, during which the safest way to convey knowledge was online (Kéri 2021). It can also be induced by several procedures, which might be technology-based or non-technology-based (Narteh 2008). The choice and success of various methods may vary depending on the type of knowledge being transferred or the size of the classroom as well (Kovács et al. 2022). A flipped classroom could also be considered as a kind of knowledge transfer, wherein the role of the teacher could be regarded as that of an instructor and not as the source of the knowledge. However, even in this situation, most students gain their information about the given topic at the university (Udvari – Vizi 2023).
In order to improve knowledge transfer, it is important to identify the barriers and facilitators of knowledge transfer. De Wit-de Vries et al. (2019) identified the chief barriers as knowledge differences and discrepancies in goals, resulting from diverse institutional cultures. These barriers result in ambiguity, problems with knowledge absorption and difficulties with the application of knowledge, whereas trust, communication, use of intermediaries and experience were found to facilitators of knowledge transfer that helped overcome the identified barriers. According to the basic model of the circle of concern, wherein philosophers observed that family and close friends are more important to humans than strangers (Whiting et al. 2018), the strength of the connection between the sender and the recipient is also considered a determinant. In order to identify a technology that could effectively support knowledge management and knowledge transfer, Garavelli et al. (2002) analysed two main cognitive processes: codification and interpretation. He argued that, in order to define the properties of knowledge technology (KT), it is necessary to analyse the cognitive context wherein knowledge transfer takes place. He then proposed a cognitive approach to the analysis of knowledge transfer, in order to define the properties of KT.
Cooperation among organisations and knowledge transfer between universities and businesses have already been incorporated into recent business trends. Knowledge sharing can be a key source of competitive advantage, but shared knowledge can also be used in competition (Loebecke et al. 1999). There is no single universal set of methods for increasing the effectiveness of knowledge transfer, because cultural differences influence the way knowledge is shared. Such differences might occur in the case of businesses as well as universities (Wang – Noe 2010). Moreover the ‘publish or perish’ culture of the universities (Király – Kovats 2022) supports the creation and sharing of knowledge but makes it more difficult to find relevant research studies and results.
One of the main tasks of higher education institutions, apart from promoting economic development (Kotosz – Lukovics 2017) and knowledge creation, is the transfer of knowledge. Although this can be achieved through education, industrial relations also play a significant role in this regard. In his study, Benedek Nagy (2012) presented the wide range of relationships among universities and the problems that arise during the transfer of knowledge within the university sector. However, in recent decades, significant changes have been made in the management of interactions between universities and industries. Knowledge transfer has become a strategic issue. However, identifying clear management models for interactions and knowledge transfer processes between universities and industries is not an easy task (Geuna – Muscio 2009).
As mentioned above, one of the missions of universities is the provision of education, that is, the transfer of knowledge, and they have several goals to meet in this regard. In contemporary society, the key issues in teaching and learning involve knowing how to select, organise and use information, in order to solve problems, handle new situations and continue learning (UNESCO 2005). Imparting these skills is particularly critical for European universities and is currently recognised as vital in the context of the European Higher Education Area (EHEA). Information literacy forms the foundation for lifelong learning. It is common to all disciplines, to all learning environments and to all levels of education. It enables learners to master content and extend their investigations, become more self-directed and assume greater control over their own learning (Molina – Sales 2008).
However, according to Hewitt-Dundas (2012), universities' approach to knowledge transfer is determined by institutional and organisational resources, particularly ethics and the quality of research, rather than by the ability to transfer knowledge through a technology transfer office or department. Strategic priorities related to knowledge transfer are reflected in universities' activities, in terms of the dominance of each knowledge transfer channel, the geographical locations of university partners and business relationships.
A university's role is to develop the skill of knowledge sharing among students, in order to more effectively collect and utilise their knowledge later, thereby leading to lower costs, faster development of products and projects as also increased revenues (Mesmer-Magnus – DeChurch 2009).
In Hungary, considering EU's Lisbon strategy, the knowledge triangle of education, research and innovation is regarded as one of the basic conditions of competitiveness. The properly chosen and effective transfer of knowledge constitutes the fundamental criterion for competitiveness. Though Hungary's transition to the Bologna Process began years ago, the processes of implementing new relationships within a competitive industry and new organizational structures challenge Hungarian universities. Competitive training requires interactive training programmes, one of whose pillars is that students should be provided with practical knowledge by universities (Zéman 2019). Today, modern universities are introducing training courses where practitioners share their experiences with students. In such institutions, graduate career tracking is crucial for collaboration with industry (Kálmán 2021).
In Hungary, in accordance with modernisation goals, the fragmentation of the vocational training structure has decreased and the proportion of participants in dual training has increased. Geographically, universities are located mainly in the larger cities, primarily in the capital. In the domain of globalised higher education, only those higher education institutions that can adapt to varying challenges at the management level remain effective and competitive (Deli-Gray et al. 2010). According to Harsányi and Vince (2012), both the number of higher education institutions and the number of students per million people in Hungary lags behind that of the neighbouring and developed European countries. As a result, the share of graduates is lower than the EU average. It was also pointed out that upon analysing the relationship between higher education spending and economic growth, it may be concluded that countries spending more on education grow faster (Harsányi – Vincze 2012).
This short literary review makes it clear that the role of higher education in knowledge transfer is unquestionable. At the same time, the question of the extent to which this transfer covers knowledge sharing among students and how a particular institutional culture supports students being open to sharing information among themselves arises. Therefore, this study investigates these questions and examines the factors influencing these processes in the context of higher education.
3 Research methodology and results
This study examined students' willingness to share knowledge in higher education institutions in Hungary in 2021. The researchers did not address the universities directly. They connected with the respondents through learning platforms popular among university students, in order to invite them to participate in the study and involve additional students from their respective classes. Respondents had to anonymously and voluntarily complete a questionnaire published on the Internet. The researchers created their own questionnaire, without using questionnaires from previous studies. They formulated their questions following a literature review along the lines of the model and hypotheses they had already developed. Prior to the study, a pilot questionnaire survey was conducted with 10 students to test the interpretability of the questions (in 2021). Since the respondents had no problems with the interpretation of the questions, the researchers sent out the questionnaire unchanged. Respondents had to answer 27 questions. Since the questionnaires were completed on social media platforms, the respondents' willingness to participate in the study could not be measured. Out of the 27 questions, 26 questions were closed-ended and one was open-ended. The researchers used nominal and metric variables. Before the questionnaire was administered, a trial process was conducted, wherein three respondents filled out the questionnaire. Thus, it was ensured that there were no incomprehensible questions, and the researchers administered the questionnaire to the respondents in the same form.
The questions can be divided into several groups. The structure of the questionnaire is shown in Table 1.
Questionnaire structure
| Question Group 1 Respondent-Specific Questions | Question Group 2 Cooperation | Question Group 3 Reciprocity in Each Situation | Question Group 4 Knowledge Transfer Problems |
| Respondent's gender; age; place of residence; study discipline; current year of study; reasons for choice of respondent's university | Cooperation among institutional members; sharing information in various situations (with friends, acquaintances, strangers); who the respondent is open to share information with; informal knowledge sharing in universities | The method of reciprocity for specific information in various situations; expectations in each situation | Problems that arise in the transfer of knowledge among university students |
Source: authors.
The study included a total of 552 respondents, and all questionnaires were evaluated. The researchers were unable to use a representative sample in their research. According to KSH data for 2021, the number of students in higher education was 287,900. Based on the sample size calculator (Calculator.net 2023), 384 or more students would be needed in a survey, in order to have a 95% confidence level for the true value to be within ±5% of the measured/surveyed value. Therefore, a sample of 552 was considered acceptable. The evaluation methods used included single and multivariate data analysis methods, such as frequency studies, average analyses, ANOVA, cross-table, correlation and factor analysis.
During the study, the researchers were guided by several goals. These included:
How can respondents cooperate with the members of the university during their education?
Which factors does the sharing of information among students depend upon (gender, age, relationship between students)?
What do students expect from each other in return for information?
Which methods of reciprocity exist?
Which problems might arise during institutional knowledge transfer?
The questions raised in this study were presented through the target structure shown in Fig. 1.
The research target system
Source: authors.
Citation: Society and Economy 2023; 10.1556/204.2023.00022
The research target system
Source: authors.
Citation: Society and Economy 2023; 10.1556/204.2023.00022
The research target system
Source: authors.
Citation: Society and Economy 2023; 10.1556/204.2023.00022
In Fig. 1, the goals for each area under study are presented. The arrows symbolise direct relationships, while the dotted lines symbolise supposedly indirect relationships between units. Part of the study analyses the kinds of possibilities for knowledge transfer that appear among students during education and the factors that affect this cooperation system. Thus, among other things, the strength of the relationship between gender, grade, age and students as factors was analysed and the factors which lead students to successfully transfer knowledge were examined. In addition, the research also covered the difficulties encountered in the transfer of knowledge. In addition to the factors already under consideration, the process may be influenced by the varying expectations that both the provider and the receiver of the information impose on each other, as well as the value of the given knowledge. Finally, the existing methods of reciprocity and the kind of compensation expected by the provider in exchange for the given information were investigated.
Based on the above, this study arrived at the following hypotheses:
H1
The knowledge transfer of the students participating in the research is greatly influenced by the value of the given knowledge material, the relationship between the students who are sharing and acquiring knowledge and the extent to which the given institution supports the knowledge transfer.
H2
Students have expectations of their peers in exchange for knowledge, but these expectations differ, depending upon the relationship between the participants in the knowledge transfer and the extent to which the given institution supports knowledge transfer.
The characteristics of the study sample are presented in Table 2.
Specification of the sample (N = 552)
| Specification | Frequency (Main) | |
| Gender | Male | 251 |
| Female | 301 | |
| Fields of Study | Health Science | 19 |
| Natural Science | 24 | |
| Technical Science | 46 | |
| Economics | 411 | |
| Humanities | 18 | |
| Art Science | 3 | |
| Law | 7 | |
| Pedagogical Science | 8 | |
| Military Science | 1 | |
| Missing answer | 15 | |
| Student's Current Year of Study | First year | 179 |
| Second year | 104 | |
| Third year | 113 | |
| Fourth year | 55 | |
| Fifth year | 12 | |
| Other (for example PhD, postgraduate and so on) | 89 | |
Source: authors.
Participants volunteered to participate in the study. The researchers informed them that the data were for research purposes only. The researchers also obtained approval from their university ethics committee.
The average age of the respondents was 17–24 years. The respondents were limited to Hungarian students. As shown in Table 2, BSc and MSc students were included in the sample and all grades were covered.
The researchers started by asking what had influenced students' choice of university. This was indirectly interesting information for the researchers in terms of knowledge exchange. If students study on their own free will and not under external pressure, it is possible that they would have a more positive attitude towards the university. Testing this hypothesis will be the aim of a later study. Among the respondents, 40.9% decided to start their higher education at their favoured institute. In the case of 31.1% of the respondents, a valuable degree was the determining factor in their choice of university. A further 8.3% gave importance to being able to work while studying at a higher education institution, 5% were attracted by the institution's reputation and 7.3% had sufficient admission results for their chosen university.
Based on gender, there was no significant difference between the respondents (chi-squared: 10,718; df: 8; sign: 0.218; P > 0.05). The highest proportion of both females (42.8%) and males (39.3%) decided independently where they would go after high school. As such, 66% were satisfied with their decision and 2% were not, whereas 32% were not able to decide whether they had made the right decision. In this respect, students across varied disciplines had significantly different opinions (F: 4,547; df: 4; sign: 0.001; P < 0.05). The most satisfied were the liberal arts students (average: 4.04) and students of pedagogical sciences (average: 4.13), while the students of natural sciences (mean: 3.46) were the least satisfied with their choice. In terms of gender, the responses on this issue did not differ (t: −1.509; df: 550; sign: 0.066; P > 0.05). However, on average, females seemed more satisfied (mean: 4.05) than males (mean: 3.95).
The analyses also showed that there was no correlation between age and decision satisfaction in the given sample (Pearson correlation: 0.2; sign: 0.635; P > 0.05), that is, respondents' age did not affect their satisfaction about their choice of the university during their studies.
Respondents had to evaluate their own educational institution to assess their university's place and role in knowledge transfer. A total of 79% of the respondents believed that knowledge sharing plays an important role in the organisation's strategy. However, 4% did not feel this way, while 17% thought that it both exists and does not exist. Further, 77% agreed that there was active knowledge transfer in their university, 4.2% disagreed, and 18.1% said that it was active but not always.
The students mentioned the following aspects as the most important problems connected to knowledge transfer. According to 30.3% of students, they did not ask questions for fear of revealing their ignorance, 16.3% of students said they lacked motivation, 14.3% felt that there was not enough time for effective knowledge sharing to take place, and 9.3% believed that they do not receive the knowledge expected by the market during their education. Many saw the instructors as the root cause of the problem, with 5% saying that teachers could not share their knowledge usefully and 3.4% saying that there was a lack of motivation on the part of the instructors.
Among other things, the research looked at whether the students in the study shared information with each other. On a five-point Likert scale, students had to indicate how much they agreed; one was not at all, while five was completely. The researchers analysed three situations; the respondents had to evaluate the same statements for each situation: (1) they were in a friendly relationship with the person they were sharing information with; (2) they were acquaintances but not friends; and (3) they were neither friends nor acquaintances and could be considered strangers to each other.
Table 3 shows the extent to which students are willing to share information with each other in a given relationship. In the case of friends, it is typical that information facilitating operational learning, such as enrolment, exam application, subject admission or the knowledge that is perceived to be useful by the instructor, is shared. In case of these students, they would also prefer to study in a group and pass on the knowledge they think is valuable, even their own notes.
How much would you share information with your fellow student if you are friends, if you are familiar, if you are strangers? (mean and standard deviation)
| Statements – Information Sharing | Friend | Acquaintance | Stranger | |||
| Mean | SD | Mean | SD | Mean | SD | |
| If you know the exam questions in advance, you share them. | 3.93 | 1.27 | 3.36 | 1.284 | 2.52 | 1.354 |
| You share your elaborate answers. | 4.09 | 1.09 | 3.44 | 1.176 | 2.57 | 1.314 |
| You help during the written exam. | 3.28 | 1.388 | 2.77 | 1.337 | 2.17 | 1.299 |
| You write the essay instead of someone else. | 1.94 | 1.224 | 1.76 | 1.138 | 1.57 | 0.991 |
| You share the information you receive from the instructor, which you consider useful. | 4.43 | 0.857 | 3.93 | 1.03 | 3.28 | 1.303 |
| In the case of group work, you take on the most difficult tasks. | 3.49 | 1.047 | 3.21 | 1.147 | 2.72 | 1.206 |
| You support self-education. | 4.13 | 0.948 | 3.92 | 1.011 | 3.42 | 1.253 |
| You support group learning. | 3.85 | 1.09 | 3.47 | 1.18 | 2.99 | 1.312 |
| You are happy to participate in a team. | 3.79 | 1.118 | 3.47 | 1.119 | 3 | 1.281 |
| Enrolment information is shared as soon as you find out. | 4.12 | 1.045 | 3.58 | 1.187 | 3.12 | 1.344 |
| You share exam application times as soon as you find out. | 4.16 | 1.021 | 3.61 | 1.171 | 3.08 | 1.338 |
| You share the subject admission information as soon as you find out. | 4.18 | 1.043 | 3.62 | 1.165 | 3.08 | 1.339 |
Source: author.
In the case of acquaintances, this feature is a little more nuanced. The willingness to share information that helps operational learning is no longer so strong, and the role of self-education is also amplified compared to that of group learning. The sharing of valuable information with these students is not so common and motivation is weakened, especially in the field of exam questions and the transfer of notes; the students no longer really want to share important information with each other if they are simply acquaintances.
In the case of strangers, this willingness is even weaker; due to several factors, the frequency of the disagreement scale values is higher. The least strong knowledge transfer is in the case of curricular knowledge and teamwork. The role of self-education is strong, and support for each other in the framework of group learning is also very weak.
During further analysis, the researchers compressed the variables into factors for each of the three relationship systems separately. In case of friendships, the results of the analysis were as follows: KMO Barlett: ∼0.787; chi-squared: 3232.609; df: 66. Post varimax rotation, the explained proportion was 63.501%. In case of acquaintances, the results were as follows: KMO Barlett: ∼0.836; chi-squared: 3781.196; df: 66. Following varimax rotation, the explained ratio was 67.335%. In case of strangers, the results were as follows: KMO Barlett: ∼0.880; chi-squared: 5246.186; df: 66. Post varimax rotation, the explained ratio was 74.149%.
The component matrix, the names of the factors and the Cronbach alpha values are presented in Table 4.
Component matrix
| Items | Component | |||
| Friend | Acquaintance | Stranger | ||
| Operational Information Transfer | You share subject admission information as soon as you find out. | 0.904 | 0.885 | 0.894 |
| You share exam application times as soon as you find out. | 0.892 | 0.902 | 0.889 | |
| Information about enrolment is shared as soon as you find out. | 0.813 | 0.869 | 0.868 | |
| You share the information you receive from the instructor that you find useful. | 0.598 | 0.631 | 0.667 | |
| Cronbach Alpha | 0.881 | 0.905 | 0.938 | |
| Knowledge Transfer of Exam Materials | You help with the written exam. | 0.853 | 0.841 | 0.825 |
| If you find out about the exam questions in advance, you share them. | 0.813 | 0.781 | 0.733 | |
| You share your elaborate answers. | 0.660 | 0.657 | 0.671 | |
| You write the essay instead of someone else. | 0.566 | 0.644 | 0.751 | |
| Cronbach Alpha | 0.735 | 0.765 | 0.820 | |
| Group Learning | You support group learning. | 0.821 | 0.811 | 0.820 |
| You are happy to participate in a team. | 0.817 | 0.797 | 0.829 | |
| In the case of group work, you take on the most difficult tasks. | 0.573 | 0.669 | 0.692 | |
| You support self-education. | 0.503 | 0.631 | 0.702 | |
| Cronbach Alpha | 0.723 | 0.777 | 0.842 | |
Source: authors.
Links between the willingness for knowledge transfer in organisations and its factors (P = 0.05)
| Factors | Active Knowledge Transfer | Rewarded Knowledge Transfer | ||||
| F | Sig. | Most Typical | F | Sig. | Most Typical | |
| Transfer of operational information to friends | 18.646 | 0.000 | There is active knowledge transfer. | 5.435 | 0.005 | There is an active reward. |
| Knowledge transfer of exam material in the case of friends | 1.591 | 0.205 | 0.404 | 0.668 | ||
| Group learning in the case of friends | 4.124 | 0.017 | There is active knowledge transfer. | 7.944 | 0.000 | There is an active reward. |
| Transfer of operational information to acquaintances | 6.202 | 0.002 | There is average knowledge transfer. | 2.957 | 0.053 | |
| Knowledge transfer of exam materials in the case of acquaintances | 2.975 | 0.052 | 12.634 | 0.000 | There is an active reward. | |
| Group learning in the case of acquaintances | 6.749 | 0.001 | There is average knowledge transfer. | 0.250 | 0.779 | |
| Transfer of operational information to strangers | 3.926 | 0.020 | There is active knowledge transfer. | 2.100 | 0.123 | |
| Group learning in the case of strangers | 1.655 | 0.192 | 8.954 | 0.000 | There is an active reward. | |
| Knowledge transfer of exam materials in the case of strangers | 8.808 | 0.000 | There is average knowledge transfer. | 0.028 | 0.973 | |
Source: authors.
In case of all three relationship systems, the researchers created three factors (Table 5). Based on their components, these factors were given the following names: (1) the transmission of operational information, (2) the transfer of knowledge of exam materials and (3) group learning. This study analysed whether there was a difference among the various levels of familiarity, if there was an active transfer of knowledge in the university, or if knowledge sharing was rewarded. Table 4 shows where there is a connection and where there is no correlation among the variables. In cases where there was a significant difference, the researchers indicated the most characteristic case while examining that factor.
The data show that active organisational knowledge transfer and reward have an impact on the way students are willing to share their knowledge with their peers at different levels of familiarity. Active organisational knowledge transfer is strongly present in the case of friends, both in terms of operational knowledge transfer and group learning. Familiarity plays a role in the transfer of operational information. The reward is less visible, but its effect is characteristic of several factors, such as group learning.
Overall, based on the above results, the willingness of students to transfer knowledge is greatly influenced by the relationship they have with each other. The stronger the relationship level, the more typical it is for knowledge to be transferred, even valuable knowledge. On the other hand, knowledge sharing is also influenced by how strong and active the knowledge transfer its reward is in the given educational institution. Considering these results, the first hypothesis was accepted.
The research also focused on what students expected in exchange for their shared knowledge. As in the case of knowledge transfer, the researchers examined what students asked in return for their knowledge at different levels of relationships, that is, in the case of friends, acquaintances and strangers. There were several options to choose from. Table 6 shows the frequency of responses according to each connection level.
What do you expect in exchange for knowledge? (Number, %)
| Possibilities | Friend | Acquaintance | Stranger | |||
| N | % | N | % | N | % | |
| Cash benefit | 12 | 1.3 | 17 | 2.1 | 51 | 6.7 |
| Knowledge | 266 | 28.2 | 278 | 34.2 | 237 | 21.3 |
| Exam support | 102 | 10.8 | 90 | 11.1 | 64 | 8.5 |
| Good friendship | 248 | 26.3 | 127 | 15.6 | 70 | 9.3 |
| Other | 24 | 2.5 | 32 | 3.9 | 29 | 3.8 |
| Responsibility improvement | 91 | 9.7 | 88 | 10.8 | 67 | 8.9 |
| Learning opportunity | 188 | 20.0 | 174 | 21.4 | 232 | 30.7 |
| Anything | 11 | 1.2 | 7 | 0.9 | 6 | 0.8 |
Source: authors.
The data in Table 6 clearly show that the more distant the relationship, the more often material expectations appear in exchange for knowledge. Thus, while 1.3% of respondents would ask friends for money in return for knowledge, this figure rises to 6.7% in the case of strangers. The most popular expectation is the barter of knowledge, which was rated as most expected by majority of the respondents, even in the case of strangers. The opportunity to learn together also offered the opportunity to transfer knowledge, which seemed attractive to the students. Strengthening of emotional attachment was essential for friends and acquaintances. The number of people at all levels of relationships who would selflessly share their knowledge without any expectation is relatively modest. So, it can be concluded that relationship systems can affect what is expected in exchange for knowledge.
The researchers also examined how active knowledge transfer in organisations and the reward for knowledge transfer affects what is expected in exchange for knowledge. The researchers analysed three exchange characteristics: monetary allowance, knowledge and good friendship. Table 7 shows, as per relationship levels, how knowledge transfer activity in organisations affects expectations. In case of significant differences, the most common features were identified.
The correlations among levels of knowledge transfer, the expectations for knowledge and the willingness of the universities to transfer knowledge (P = 0.05)
| Possibilities | Friend | Acquaintance | Stranger | |||
| Knowledge Transfer | Reward | Knowledge Transfer | Reward | Knowledge Transfer | Reward | |
| Cash benefit | Chi- squared: 12.628; sig.: 0.02. Most common when there is no knowledge transfer | No significant difference | No significant difference | Chi-squared: 7.479; sig.: 0.024. Most common when there is no monetary reward | No significant difference | No significant difference |
| Knowledge | No significant difference | No significant difference | Chi-squared: 16.382; sig.: 0.041. Most common when there is no transfer of knowledge | No significant difference | No significant difference | No significant difference |
| Good Friendship | No significant difference | No significant difference | No significant difference | No significant difference | No significant difference | No significant difference |
Source: authors.
Based on the data presented in Table 7, in the case of strangers, the knowledge transfer activities of the university are not affected by whether the transfer of knowledge is somehow rewarded within the university. The picture is already more nuanced in terms of transferring knowledge to acquaintances. In cases where there is no reward for knowledge transfer, it is more common for students to expect money from their acquaintances in exchange for their knowledge. In terms of students with friendly relationships, the institutional reward has no effect on expectations. However, where it is not typical for active knowledge transfer to operate in universities, even in terms of friends, students most often monetise their knowledge.
Overall, the relationship system has a strong impact on what students expect in return for their knowledge. The more distant the relationship, the more financial the expectation. However, in the case of a closer relationship, a more emotional and friendly relationship is built as an expected result.
Knowledge can be seen as a valuable exchange currency at all levels. The culture of knowledge transfer in higher educational institutions can affect expectations among friends and acquaintances, while the reward system in universities can mainly influence the sharing of knowledge with acquaintances. Considering theses results, the second hypothesis was accepted.
4 Discussion
Based on the results of this study, the basic model of the circle of concern was identified, as already observed by Greek philosophers (Whithing 2018). In this situation, family, as the closest relationship, was missing, but as the circle expanded, the strength of the relationship and the importance of others' knowledge or information decreased. Students were more willing to share information with friends and acquaintances than with strangers. However, the cultural differences among organisations can also have an influence on the method of sharing knowledge (Wang – Noe 2010), and this can be observed in universities as well as businesses.
Another important factor related to knowledge sharing is the motivation behind it. It could be motivated by self-interest or community interest, it could have an economic advantage, or it could have none. Moreover, knowledge transfer could behave as an instrument for public good, since the exchange mechanism could be similar in a public setting, free-loaders could appear (Wasko – Faraj 2000), and this could lead to the weakening of the expectation of monetary compensation in exchange for information. According to McLure and Faraj (2000) survey, 21.5% of online comments generated ‘tangible’ returns, such as useful information from experts, answers to specific questions, or personal gain related to their profession. Another 19.9% of comments indicated intangible returns and they found being a part of the community challenging: while helping others, they could deepen their own knowledge and develop other skills, so the overall gain was greater than the shared knowledge itself. In this study, the emotional benefits of knowledge sharing were found to be more important than the material benefits.
Furthermore, a topographic view of organisations forms the basis for knowledge transfer and learning (Araujo 1998), as it has already been shown that the distance among individuals has an influence on the knowledge transfer among them in universities. Therefore, it is important to identify the overlapping communities within organisations: functional areas, project teams, memberships and committees. Consequently, it is essential for all types of organisations, including educational organisations, to gain a competitive advantage from specific knowledge, skills and competencies. A key role of the university is to develop the skill of knowledge sharing among students, in order to more effectively collect and utilise their knowledge later, thereby leading to lower costs, faster development of products and projects and increased revenues (Mesmer-Magnus – DeChurch 2009). All in all, an advanced level of knowledge transfer within smaller and bigger organisations could lead to a competitive and dynamic economy (Foss – Pedersen 2002).
When examining knowledge transfer, Lin (2008) noted that horizontal connections are of importance in the process, which means that the number of friends and close connections could increase universities' effectiveness in this field. Moreover, roles and identities within a group have a strong influence on attitudes and values, and could further motivate voluntary cooperation within such groups (Tyler – Blader 2001). Similar tendencies were observed in business organisations, where co-workers’ roles in knowledge transfer were more important than the organisational and supervisory support that did not show moderating effects (Homoklin et al. 2014). Likewise, stronger connections among students could also increase the effectiveness of knowledge transfer.
It is supposed that knowledge sharing can increase a businesses' effectiveness by generating solutions to exploit competitive advantage, which could also be useful for universities (Reid 2003). Moreover, a more effective sharing process could widen the knowledge base, which is essential for university students to perform better (Tsai 2001), and higher absorptive capacity could increase the possibility of successfully applying any new knowledge (Cohen – Levinthal 1990).
Moreover, it should also be considered that when organisations support knowledge transfer, it has a positive effect on organisational perceptions of innovation characteristics and interpersonal trust (Hsiu-Fen 2006) and also facilitates knowledge sharing (Kő et al. 2003).
Several studies have already touched upon the importance of knowledge transfer, which is confirmed by our research. Knowledge transfer, among other things, enables students to learn more effectively (Singporn et al. 2019). Others have pointed out that there are several factors responsible for the transfer of knowledge. It is not possible to clearly mention which incentives contribute effectively to the transfer and are also influenced by the motivation of the individual (Fenyvesi 2010). The results of Mezeiová and Bencsik (2019) show that students are primarily motivated by internal motivational factors and require non-traditional tasks.
Other researchers mentioned that by strengthening trust among individuals, the likelihood of knowledge sharing can be significantly increased (Baksa – Báder 2020). Based on our research, it may be concluded that students are often uncertain about their own knowledge, so they do not share it.
Areekkuzhiyil (2019) found that attitudes towards knowledge transfer are also influenced by gender, type of studies and type of institution, and there exist more positive relationships among postgraduate students. In our own research, we found that in the sample examined there was no significant difference in the case of gender. However, there was a difference according to the scientific field, as per the opinions expressed by respondents.
Some researchers have interpreted knowledge sharing as something that can be linked to a location and can be implemented effectively there (Stéber – Kereszty 2016). However, it should be emphasized that with the help of digitalization and the Internet, several opportunities to share information online can be utilized. Gamlath and Wilson (2022) highlight that the emergence of online learning, the widespread integration of social media, for example, are important dimensions for knowledge transfer, and also stress the need for universities to facilitate student knowledge sharing. Our study did not specifically examine this issue, but it can certainly be considered as an area requiring analysis.
In a summary study based on studies conducted in business education, it has been emphasized that knowledge transfer is a growing research topic, wherein it is still essential to identify the most effective tools for sharing knowledge (Castaneda – Cuellar 2021). In the case of accounting students, they have been shown to have a moderate to high degree of positive attitude towards knowledge sharing (Bagais et al. 2020).
The results of previous research and our own study have contributed to a deeper understanding of the importance of knowledge transfer and better practices for several stakeholders, such as academics and policy makers, lecturers and students. To this end, the examination of the efficiency of knowledge transfer between teachers and students is also of paramount importance and can serve as a basis for future research.
5 Conclusion
Based on the findings of this study, it may be concluded that knowledge transfer is important for university students, whether they are males or females, and a university environment is a good place to develop the required skills. Students mainly share public, operational information that is helpful for their studies and everyday life with their friends. The stronger the relationship with their peers, the greater the knowledge shared.
With the help of the KMO Bartlett test, three factors related to knowledge transfer were identified: operative information, exam materials and group learning. Active knowledge transfer of operational information exists among all groups of students, and rewards also play a significant role among friends and acquaintances in operational information transfer. Moreover, group work is a rewarded activity for most students, so it has a place in teaching. Often, however, the quantity and content of the curriculum cannot provide space for group work in university teaching.
The results show that operational information sharing is performed more effectively than sharing knowledge about exam materials, but the reason behind this could be the restriction of communication during exams. However, it could be a forward-thinking step to increase the sharing of exam materials among students and their groups, as it could increase the knowledge of the providers and the receivers as well.
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