How is Social Media perceived as a platform for transferring Tacit Knowledge between Coworkers

How is Social Media perceived as a platform for transferring

Tacit Knowledge between Coworkers

Master Thesis

Volkan Önnisan

S3518930

21.06.2018

University of Groningen

Master of Science Business Administration

Organizational and Management Control

Supervisor: Dr. Sakshi Girdhar

Co-assessor: Dr. Kristina Linke

2

Abstract

Researchers and organizations are increasingly recognizing the importance of Social Media applications in the workplace. According to recent reports, the majority of managers believe that Social Media plays an essential role within their organizations. The high adoption rate of Social Media in organizations supports this notion. The introduction of these tools enables new opportunities in the workplace in terms of knowledge transfer between coworkers. However, limited research leading to controversial results in this field caused tension between scholars which magnifies the need for additional research to arrive at a more accurate and broader insight on how Social Media affects knowledge transfer between coworkers in the workplace. Therefore, this paper answers the call for more research and literature regarding this topic and shall focus on the transfer of tacit knowledge which is more challenging and valuable compared to explicit knowledge. To this end, a case study was conducted to explore and to investigate the significant elements surrounding this pressing issue. This paper aims to contribute to our continuing understanding of Social Media channels and their perceived contribution to the tacit knowledge transfer in the workplace. As will be discussed and shown hereunder, the findings of this study partly support current literature and also disagrees with it and reveals new insights which were not examined thus far.

Keywords

Social Media, Knowledge Transfer Model, Tacit Knowledge, Knowledge Transfer, Software Engineers.

Acknowledgements

3

Table of Content

4.1 Significance of Social Media ... 17

4.2 Organizational Level ... 19

4.3 Facilitating Level ... 21

4.4 Individual Level ... 28

5. Discussion and Conclusion... 30

4

List of Tables and Figures

5

1. Introduction

The rise of Web 2.0 has been leading to an unprecedented impact in the environment of organizations. Where the antecessor Web 1.0 was predominantly a “read-only” technology the new Web 2.0 offers more interaction and participation through blogs, wikis, social software etc. (Sturm, 2010). Social Media is commonly based on mobile and web-based technologies which creates highly interactive platforms enabling individuals and communities to share, co-create, discuss, and modify user generated content (Kietzmann et al, 2011). The Social Media Networks adoption rate in organizations is 80% according to recent reports (Overby, 2012). In addition, 86% of the managers believe that Social Media Networks play an essential role within their organizations (Kiron et al, 2012). The rapid advances of Web 2.0 technologies and their adoption in companies influenced the social perspective within organizations. Consequently, some scholars have started doing research in this field to illuminate the proper use of Social Media in the workplace (Faci et al, 2017). Despite the hype regarding Social Media, however, still some organizations have doubts about the real benefits of these applications. Therefore, some resistance has shown in adopting Web 2.0 applications at the workplace (El-Sayed and Westrup, 2011). This can be argued with the increasing misuse cases and occurring security threats regarding Social Media applications like Facebook and Twitter. Thus, these are important issues which dictate the skepticism in terms of Social Media use at the workplace (Faci et al, 2017). Further investigations in this field are important but this is beyond the scope of this paper. However, some scholars also revealed that the introduction of Social Media at the workplace can be beneficial as well. For instance, it supports interpersonal communication and collaboration (Kane, 2014). Furthermore, it also enables to post, edit, and sort text and files linked to themselves or others whenever they want. The awareness of ambient communication occurring among coworkers and the increased visibility of the communication within employees can be an important antecedent for knowledge transfer (Leonardi, 2015). Consequently, it can be assumed that organizations struggle with the introduction of Social Media for work purposes. Even if, it seems beneficial in terms of communication and knowledge

transfer.

6

crucial to keep the knowledge within the organization and ensure the transfer between employees. Social Media is new and a more interactive type of technology allowing a variety of new behaviors that were not previously possible, e.g. authoring, reviewability, editability, association, experimentation, etc. These new behaviors have implications for the knowledge process (Wagner et al, 2014). However, the transfer of knowledge can be influenced by social elements like interpersonal trust, knowledge sharing self-efficacy, community identity, and social awareness (Tseng and Kuo, 2010). In this connection, these enumerated interpersonal and personal elements can significantly influence the interpersonal relationship between coworkers, that on the other hand, can be essential to preserve, share, learn, create, and utilize knowledge (Wasko and Faraj, 2000; Koch, 2002). Nevertheless, it is unknown whether all these elements are relevant in term of tacit knowledge transfer through Social Media. Previous research in the field of knowledge transfer influenced by social elements revealed that communication is essential in facilitating transfer of information. Consequently, it allows that tacit knowledge being made explicit (Hedlund, 1994). For this reason, it can be concluded that communication illustrates the foundation for the tacit knowledge transfer between coworkers and that any improvement in this element leads to an enhancement in the tacit knowledge transfer process. Moreover, further research in the field of network learning revealed that relationship between the knowledge exchanging coworkers is essential to make knowledge explicit. In this connection, some scholars argue that interpersonal ties (Tseng and Kuo, 2010; Haythornthwaite and de Laat, 2010) and trust (Hsu and Chang, 2014; Quigley et al, 2007; Rajagopal et al, 2012) positively influence exchange activities between the members within the network. In view of the foregoing, this study will investigate these elements which are influenced by the personal attitude and characteristic in the setting of Social Media and its use for tacit knowledge transfer. Another research in the field of knowledge share through Social Media revealed that codifiability is a crucial element and that explicit knowledge which is codified is more likely to be shared (Zander and Kogut, 1995; Nonaka, 1994; Hedlund, 1994). In this connection, elements related to the characteristic of tacit knowledge and opportunities offered by Social Media will be investigated regarding their significance as well. These elements on different levels influence the knowledge transfer process. This study will investigate the significance and effects of these above-mentioned different elements from different levels focusing on tacit knowledge transfer through Social Media which was not investigated so far. In addition, this qualitative research will show whether prior findings conducted in different settings can be applied to this particular setting. Social Media is a quite new research field that requires more attention. This will enable to reveal how Social Media is perceived in terms of tacit knowledge transfer between coworkers.

7

useful for the knowledge transferring process. Particularly, with the focus on tacit knowledge which is more challenging to transfer because of aforementioned issues. In addition, most of the scholars in prior research considered tacit and explicit knowledge more as substitutes and therefore, did not distinguish between these two knowledges explicitly (Wu et al, 2015; Virtanen, 2013; Jasimuddin et al, 2005). However, these two types of knowledge show different characteristics, and should therefore, be considered individually. Thus, this research will mainly focus on the impact of Social Media on tacit knowledge transfer. Furthermore, prior research about tacit knowledge transfer through digital technologies was mainly focused on Information Technology systems based on Web 1.0, the antecessor of Web 2.0 and Social Media (Hislop, 2002; Spender and Mahoney, 2000; Johannessen et al, 2001; Desouza, 2003a). Therefore, this research will mainly focus on Social Media as transmitter. Altogether, the objective of this research will be to reveal the elements influencing the knowledge transfer between coworkers through Social Media.

Consequently, with this research the following question will be answered:

How is Social Media perceived as a platform for transferring tacit knowledge between coworkers?

In summary, this study contributes to the field of effective tacit knowledge management in many ways and offers managers a broad insight in this certain area. Knowledge is being seen as a crucial resource regarding market value and is primary source of Ricardian rents (Machlup, 1980; Grant, 1996). Especially, tacit knowledge plays a central role in achieving sustained competitive advantage over competitors (Nonaka, 2007). Tacit knowledge is seen as one of the most critical resources in an organization (Sobol and Lei, 1994). With the help of this study, managers can obtain insights about elements influencing the tacit knowledge transfer between coworkers through Social Media. This can help to keep the tacit knowledge within the organization and manage their transfer.

Accordingly, the top management and upper management, who are influencing the implementation and use of Social Media at the workplace, need to know about the advantages and disadvantages of Social Media platforms. Knowing what kind of elements play a significant role and how they influence the tacit knowledge transfer between coworkers can assist to create a general framework to increase the efficient use of Social Media tools at the workplace. Researchers in the field of Social Media or knowledge transfer have to know, how certain elements influence its proper use and whether Social Media is an efficient tool for transferring tacit knowledge between coworkers. These new insights can provide new approach for future research.

8

2. Literature Review

There is a great ongoing debate between scholars whether Social Media can influence the share of knowledge. On the one hand, some scholars argue that sharing tacit knowledge through Social Media channels is too limited with many obstacles which makes it even impossible to complete the transfer process successfully (Johannessen et al, 2001; Hislop, 2002; Haldin-Herrgard, 2000). On the other hand, there are also some scholars who argue that Social Media can be seen as an enrichment for sharing tacit knowledge, even if it is not able to achieve the same level like face to face communication which is seen as the best method to transfer tacit knowledge (Selamat and Choudrie, 2004; Falconer, 2006; Hildrum, 2009).

Figure 1: Knowledge Transfer Model. Based on: Yang and Maxwell, 2011.

9

these elements are quite complex and each element have the ability to influence the others (Yang and Maxwell, 2011).

The Knowledge Transfer Model consists of three layers. The first layer includes the elements organizational structure and organizational culture which have a broad impact on all the activities of an organization (Yang and Maxwell, 2011). As a result, the first layer is named organizational level because these two listed elements can be directly influenced by the organization itself. Consequently, these two elements are located in the outer layer because they have influence on the elements located in the inner layers, illustrated by the arrows. Hence, the first layer of the Knowledge Transfer Model creates the basic condition for the knowledge share between coworkers through Social Media. Through implementing a supporting organizational structure and establishing an appropriate organizational culture, organizations can create a basis for efficient use of Social Media in terms of knowledge transfer. Therefore, it can be concluded that the elements in the first layer can create the foundation for the communication and collaboration between coworkers.

In this connection prior research revealed that, communication is one of the key elements in terms of sharing knowledge. Increased communication supports to build relationship between two people and it helps to establish trust (Angehrn et al, 2009; Boeije et al, 2009). Therefore, some scholars argue that Social Media contributes to the communication between coworkers and is an efficient tool for knowledge sharing accordingly (Gordeyeva, 2010; Haythornthwaite and Laat, 2010). According to other research, the communication between coworkers through Social Media can be influenced by the culture andstructure of the organization. If the organization does not enable free communication between coworkers through Social Media, this can hinder the knowledge sharing process. The environmental setting within the organization is crucial. Therefore, according to prior research in this field, companies should create an atmosphere which enables and supports participation and collaboration between coworkers to create a knowledge community where they can share their own views and ideas (Yu et al, 2010; Levy, 2009; Boeije et al, 2009). Hence, the organizational structure is crucial in terms of creating an appropriate basis for knowledge transfer between coworkers. Formalization is defined as formal rules, guidelines and procedures, and regulations of an organization (Hall and Tolbert, 2004). According to prior research, formal systems with strict hierarchy are less effective compared to systems which are more informal in facilitating the transfer of knowledge. Informal rules can lead to greater flexibility and openness which increases the interaction and communication between coworkers (Jarvenpaa and Staples, 2000; Kim and Lee, 2006).

10

the company plays an essential role though, if the organizational culture does not support knowledge sharing, it does not matter what kind of channel is used (Vuori and Okkonen, 2012; Ipe, 2003). Consequently, creating an organizational culture which establishes an ambient atmosphere can support the interaction and knowledge transfer between coworkers through Social Media channels positively. It can then be concluded that introducing Social Media tools in an organization without creating a base for that, through adjusting the organizational structure and establishing an appropriate culture to enable free communication, can lead to inefficient results.

The second layer of the model includes elements which are in between the organizational and individual level and therefore embodies a facilitating role within the model. The second layer is named facilitating level because these elements can be categorized as elements which are the results of organizational structure and organizational culture or are influenced by them. As illustrated in the model, these elements can be influenced by organizational structure and organizational culture. Furthermore, these elements can influence the personal attitudes and beliefs of each individual (Yang and Maxwell, 2011). For instance, organizational culture can influence trust between coworkers. If the organization manages to establish an organizational culture which creates a strong team spirit among coworkers, this can increase the cooperative feeling and build trust between coworkers. On the other hand, this increased trust can influence the element personal attitude in the third layer and enable employees to engage more with other coworkers regarding knowledge transfer.

11

not widely spread like nowadays. The introduction of Social Media changed every day lives enormously (Hinton and Larissa, 2013; Burn and Martinsons, 1997).

According to some scholars Social Media can lead to increased visibility between coworkers. This allows employees to identify and monitor the contribution of each employee, leading to a reduction of inactivity in the work environment and encourage coworkers to share knowledge more actively (Liden et al, 2004). Increased visibility enables coworkers to develop metaknowledge about who knows what and who knows whom. This metaknowledge can be seen as an important antecedent to increase collaboration and knowledge transfer (Choi et al, 2010). In this connection, Social media enables to create a more accurate metaknowledge compared with traditional mechanisms, which would likely slower in this process.

Furthermore, some scholars focused on the research of interpersonal relationship elements and their influence on knowledge transfer. In this connection, they argue that coworkers are more willing to share knowledge with other people if they have an acceptable relationship to their counterpart. Therefore, they argue that knowledge transfer activities are influenced by social relationships. Those relationships decide about the dimension of the transferring activities (Lin and Lo, 2015; Staples and Webster, 2008; Haythornthwaite and de Laat, 2010). Especially, the element trust regarding the quality and reliability in terms of the provided knowledge are an important element. In addition, trustworthiness of the counterpart also has a positive influence to the process of knowledge sharing (Wasko et al, 2009; Huang et al, 2011).

According to prior research, another interpersonal relationship element mentioned in a limited number of papers is the element sympathy. Sympathy facilitates the externalization of tacit knowledge (Sigala and Chalkiti, 2007). In addition, it influences the willingness of sharing knowledge among themselves (Matzler et al, 2008). However, less research was conducted in the past in this connection. Therefore, it is not appropriate to make a conclusion regarding the relationship between sympathy and the knowledge transfer engagement between coworkers.

In conclusion, some research brought evidence on the effects of above-mentioned two interpersonal relationship elements trust and sympathy on the knowledge transfer. These findings are consistent with prior findings of Dyer and Noboeka (2000) and Todo et al (2016) who argued that strong ties are essential for two entities to enter into a knowledge transferring environment. However, another research conducted to find the effect of ties and knowledge transfer concluded that weak ties can also contribute to the transfer of knowledge (Minguela-Rata et al, 2012). Thus, it is important to mention that interpersonal relationship elements are controversially discussed among scholars.

12

which can occur if the coworker’s belief that sharing their valuable knowledge with their coworkers will not result in any benefit for them. Moreover, other individuals see reciprocity as an important element which facilitates the engagement into the knowledge transferring process. These kind of personal attitudes and characteristics affect the cost/benefit equation of each individual differently (Ardichvill et al, 2003; Bock et al, 2005). The arrows in the Model indicates the direction of influence between the layers. Consequently, the outer layers influence the inner layers directly and affect the knowledge transfer significantly. The innermost layer that represents the successful knowledge transfer between coworkers is influenced directly or indirectly by all other three outer layers according to the figure. For this reason, all the demonstrated elements in the Knowledge Transfer Model should significantly influence the tacit knowledge transfer between coworkers. The Knowledge Transfer Model is an accurate model to analyze each individual element more effectively and understand the process of tacit knowledge transfer via Social Media more accurately.

In this regard to the third layer of the Knowledge Transfer Model, scholars revealed some challenges which could hinder the transfer of tacit knowledge. One of these elements can be the fear of losing knowledge power through sharing the valuable know-how. Tacit knowledge is unique and valuable and therefore, it can increase the power of coworkers, which they probably don’t want to share with their coworkers (Gray, 2001; Amidi et al, 2015; Pee and Lee, 2015). These kind of power games can negatively influence the willingness of sharing valuable tacit knowledge with the coworkers. On the other hand, individual attitudes also affect the transfer process. Employees’ motivation in sharing knowledge is an important aspect for an effective knowledge transfer. Another element is the reciprocity in knowledge sharing. Individuals expect that the communication is not just one way, both sides should engage in the process to increase the motivation for participating in the knowledge transfer. The general attitude in terms of knowledge sharing is positive and useful and can increase the value of the shared information. (Vuori and Okkonen, 2012; Ipe, 2003). According to these prior researches, it can be concluded that elements related to interpersonal relationships can significantly influence the knowledge transferring engagement. In addition, contributing tacit knowledge can lead to the perception of giving up benefits of possessing this knowledge. The perceived lack of personal benefits which can occur if the perceived costs of sharing tacit knowledge outweighs the benefits can also lead to closeness of employees in terms of sharing knowledge with their coworkers (Gray, 2001; Amidi et al, 2015; Pee and Lee, 2015). Accordingly, it can be concluded that personal characteristics and attitudes can significantly influence the knowledge transfer process.

13

14

3. Research Methodology

3.1 Research Design

The goal of this research is to contribute to the understanding of the influence of the different elements regarding the knowledge share through Social Media platforms. For this reason, the underlying question will be “how” Social Media can affect this process. The impact of Social Media on the transfer of tacit knowledge was not researched so far. Scholars were focused mainly on knowledge transfer in general, while ignoring the different characteristics of tacit and explicit knowledge or conducted research in a different context. Accordingly, this research will be the first to focus mainly on tacit knowledge transfer in the context of Social Media setting. In this context, to understand the human activity embedded in the real world in this specific context, the chosen research method in this paper will be a qualitative case study (Gillham, 2000). That is why a single case study in an office setting will be conducted to answer the above-mentioned specific research question. This kind of setting was not addressed in prior research so far. To investigate this situation where just a little is known so far will open the door for more formal research in the future (Gillham, 2000). Therefore, this research is about creating new knowledge in the field of Social Media and tacit knowledge.

Because the topic is about tacit knowledge transfer through Social Media platforms, the Software industry was selected. Software Engineers are usually known for code production of various demands. However, code production is just a small part of the scope of work. Other typical activities are maintaining systems, identifying needed upgrades, integrating and testing, capture detailed requirements, etc. (Story, 1989). Due to the enormousness of the field, individuals usually cannot possess all the required knowledge to complete a programming project successfully. Therefore, peer experience and learning from each other are essential to be successful and to prevent becoming obsolete in this business. Consequently, Software Engineers are suitable test subjects for this research because software engineering is a highly knowledge-intensive domain, where the keys for success are related to the knowledge and experience of a person in various software development fields (Desouza, 2003b). High interaction with coworkers and high involvement of knowledge transfer (tacit and explicit) in their daily work, make this occupational group an ideal candidate for this research.

The Knowledge Transfer Model will be used to interpret and analyze the tacit knowledge transfer process. This particular model demonstrates the different elements which influence the knowledge transfer process on three different levels.

3.2 Data Collection

15

data. The study participants were Software Engineers. As mentioned above, this business field is a highly-knowledge intense industry, where knowledge transfer is a key element for success (Desouza, 2003b). The participants were selected through the following three pre-defined criteria. Participants having minimum three years of work experience, using Social Media on regular basis, and are available for the study. These criteria should ensure that the selected participants have enough experience to share information about tacit knowledge share through Social Media in a work environment.

Semi-structured interviews were conducted to gather the participants’ experiences and perspectives regarding the tacit knowledge share via Social Media platforms. Therefore, a series of open-ended questions were asked to the participants in a face-to-face setting. Before each interview, a brief explanation was given regarding tacit and explicit knowledge. Additionally, it was mentioned that all the questions are based on tacit knowledge transfer to ensure accuracy of the answers. Likewise, a small introduction regarding Social Media applications were provided to ensure that participants focus on the correct platforms, when they respond to the asked questions. The length of the interviews were approximately 45 minutes. The interviews were conducted in Germany and German speaking part of Switzerland. The name of each interviewee was not mentioned to remain anonymity. Seven employees were interviewed in total, which were considered as adequate to collect sufficient empirical results. An overview of the interviewees is provided in Table 1. Even if three interviewees’ position differs from the position of Software Engineers, the interviewees ensured that, the majority of their work task is based on programming. Some of the questions asked were about what kind of Social Media platforms they use for professional intentions, what kind of obstacles they encounter when using these platforms, what motivates or demotivates them to share knowledge, and what kind of elements influence the knowledge transfer through Social Media. All these collected data helped to provide a broad insight about this specific issue.

Interviewee Position Work experience Length of interview

Interviewee 1 Software Engineer 4 years 45 min

Interviewee 2 Software Engineer 5 years 31 min

Interviewee 3 Software Engineer 4 years 44 min

Interviewee 4 Data Scientist 4 years 40 min

Interviewee 5 IT Consultant 4 years 42 min

Interviewee 6 SAP Consultant 3 years 47 min

Interviewee 7 Software Engineer 12 years 57 min

16

3.3 Data Analysis

17

4. Analysis

4.1 Significance of Social Media

Nowadays, Social Media is an indispensable part of daily work of Software Engineers. Working on projects together with other coworkers is a well-established part of their daily task. Therefore, collaboration between coworkers is crucial to finish the ongoing projects at hand successfully. Referring to this, all seven interviewees confirmed that Social Media improves collaboration between coworkers as one of them explained:

“Social Media platforms helps you to save some time and effort, it is good to have communication channels like these which improves the collaboration and enables you to share things with coworkers”.

Additionally, four Software Engineers mentioned that they require a broad repertoire of different kind of knowledge. The other three interviewees did not mention anything related to this issue. Accordingly, transferring knowledge between coworkers is essential to be able to finish your current task, as one Software Engineer stated:

“In my field (Data Science, Software Engineering) there are so many different tasks, one employee cannot know everything. Therefore, you strongly need to transfer the needed knowledge with your coworkers, and in this connection Social Media tools are good alternatives”.

Therefore, the data also revealed that communication is crucial in the field of Software Engineers. In this connection, Social Media is an effective tool to communicate with each other and overcome distances according to all seven interviewees. It helps to keep in touch with your coworkers.

“In my business field, communication with coworkers is extremely important. Nowadays you or your coworkers are doing home office very frequently. Therefore, Social Media allows us to keep in touch and ask for knowledge without calling the colleague every time. You can simply text your colleague and simply get the required knowledge, it enables fast transfer”.

In addition, three interviewees also mentioned that it also enables fast-communication compared to alternative channels like Emails. The other four interviewees did not mention anything related to this issue. In this connection, one Software Engineer expressed:

18

These findings support the prior findings of Gordeyeva (2010) and Haythornthwaite and Laat (2010) that Social Media positively contributes to the communication between coworkers. Especially, the opportunity to communicate collectively with your coworkers through Social Media channels enables Software Engineers to communicate with many coworkers at the same time which improves the team spirit and communication between Coworkers. This effect was mentioned by three interviewees the other four interviewees did not mention anything related to this issue. Referring to this, a Software Engineer expressed:

“One of the biggest advantage is that you can communicate not just with one or two coworkers at the same time which is usually the case if you use Emails, no it allows you to communicate with your entire division. This can also help to increase the team spirit”.

Two Software Engineers mentioned that this opportunity of communicating with a group of coworkers enhances the transfer of the required knowledge. It allows employees to request the required knowledge to a huge group of employees at the same time.

“You can have group of experts where everyone can answer the question about this specific

area. […] Social Media platforms can help you to ask a question to a huge group of experts […]. So more than just one coworker is able to answer your question at the end”.

The data also revealed that Social Media helps employees with communication problems to express themselves much more efficiently and openly and therefore, helps to overcome this kind of deficits. This was mentioned by one Software Engineer.

“Social Media has a huge potential in my industry, because usually information engineers are

not communicatively strong, and therefore, have problems to communicate face to face with someone, because they are very shy or getting afraid. Which is very often the case. In this regard, Social Media platforms helps to overcome this obstacle, because it allows the coworkers to avoid direct communication and helps them to communicate more openly”.

In addition, it is also very beneficial for people who has speech impediment which was also mentioned by one Software Engineer with the following explanation:

19

Media platforms because it enables him to communication more fluently with overcoming his speech impediment, […]”.

Consequently, Social Media is an indispensable part of a Software Engineers daily work. It improves collaboration and communication between Coworkers and enables to communicated with a group of employees which positively influences the team spirit.

However, the data also revealed a negative aspect of Social Media that is the distraction from the work. Referring to this, four Software Engineers mentioned and supported this disadvantage. The other three interviewees did not mention anything related to this issue. Referring to this an interviewee stated:

“A huge disadvantage of Social Media, in my opinion, is that you get distracted from your work and accordingly lose the focus. Social Media can mislead to transferring unnecessary information between coworkers caused through Small talk which has no positive effect on your work”.

In addition, Social Media can also hamper communication leading to an ambiguous communication between coworkers. Four Software Engineers confirmed this view, three interviewees had no opinion regarding this issue. The following statement supports the ambiguous communication which can occur:

“Ambiguity is very often the case. It happens very frequently, that you try to transfer your knowledge to a coworker but he misunderstands it. The coworker automatically gathers wrong knowledge and thinks that it is correct. This is the case because you don’t get any direct feedback through Social Media platforms”.

According to the data many Software Engineers mentioned ambiguity as a huge problem of Social Media in terms of communication between coworkers, which even affects the knowledge transfer process negatively.

Altogether, it can be concluded that Social Media is a significant component of the workday of Software Engineers nowadays, with many advantages and some disadvantages.

4.2 Organizational Level

20

knowledge transfer process according to prior findings and which is part of the organizational structure. However, the findings are quite controversial without any clear evidence whether hierarchical position positively or negatively influences the knowledge transfer process. On the one hand, three Software Engineers confirmed that it is not relevant as the following statement illustrates:

“Hierarchical position doesn’t play a role regarding how I engage with a person. However, I would say that it could depend on how the organization is organized and how employees act with each other. In my current organization it is not the case. Actually, I can contact everyone through Social Media platforms unimportant whether he/she is my boss or not”.

On the other hand, however, three interviewees also supported the view, that hierarchy is a significant element which influences the knowledge transfer process significantly. The remaining one interviewee had no opinion regarding this issue. The following statement supported the significance of this element:

“Hierarchical position plays a huge role for me. I think twice, before I contact my supervisor through Social Media channels. Usually I go to his office first and ask him how his workload is. However, with the supporters, who are below my position in the hierarchy, I don’t think twice and simply contact them immediately, if I need something”.

According to these quotes, it can be concluded that there is no clear evidence, whether hierarchical position and organizational structure, which plays a significant role in the knowledge transfer process or not which contradicts with prior findings. Hierarchical position can be categorized in the first layer of the Knowledge Transfer Model named organizational level, because organizational structure determines how strict or loose the hierarchical system is within the organization.

Previous research disclosed that ambient atmosphere can help coworkers to become more comfortable with the tools and helps to increase the information exchange and interaction between coworkers (Blasco-Arcas et al, 2013). Therefore, the organizational culture of a company plays an essential role in this regard. If the organizational culture does not support knowledge sharing so it does not matter what kind of channel is used (Vuori and Okkonen, 2012; Ipe, 2003). The empirical results confirm the importance of organizational culture regarding tacit knowledge transfer which was supported by four interviewees. The remaining three interviewees had no opinion regarding this issue. According to this, one Software Engineer stated:

21

or structures in this case. Enforcement and consequences are the wrong way especially in terms of knowledge transfer. Nobody want to be forced to share his valuable knowledge with his coworkers. Consequently, it is essential that the organization establishes an organizational culture which creates an ambient atmosphere within the organization, that enhances the interaction between coworkers and supports tacit knowledge transfer”.

The results of the interview analysis confirm the significance and importance of organizational culture for the tacit knowledge transfer between coworkers. Thus, it is essential to create an ambient atmosphere within the organization to support tacit knowledge transfer through Social Media. Enforcement and consequences are the wrong way to stimulate the employees.

Consequently, it can be concluded that the results support the prior research that organizational structure and organizational culture have a broad impact on all the activities of an organization (Yang and Maxwell, 2011). However, there is no clear evidence about whether organizational structure significantly influences the tacit knowledge transfer process or not. Unlike organizational structure, the data revealed clearer evidence for the significance of organizational culture. The data also supports the relationship between the organizational level and the facilitating level in the Knowledge Transfer Model. As the statement aforementioned, organizational culture can enhance the interaction between coworkers which on the other hand, leads to increased visibility regarding who knows what and who knows whom which is categorized on the facilitating level of the Knowledge Transfer Model. Hence it can be concluded that, the empirical data partly supports the organizational level of the Knowledge Transfer Model.

4.3 Facilitating Level

Codifiability of tacit knowledge is a significant and crucial element for knowledge transfer (Zander and Kogut, 1995; Nonaka, 1994; Hedlund, 1994). According to prior research, codifiability through Social Media channels is difficult, some scholars argue that capturing and coding tacit knowledge through Social Media is challenging and therefore, difficult to transfer through these kind of platforms (Hislop, 2002; Spender and Mahoney, 2000; Johannessen et al, 2001). The analyzed results of the interviews partly confirmed these previous results. Five Software Engineers confirmed the difficulty of codifying tacit knowledge through Social Media. The other two remaining interviewees did not mention anything related to this issue. One supporting statement was:

22

However, the analysis of the interview revealed complexity as facilitating element whether tacit knowledge can be codified successfully or not through Social Media. In this regard, six Software Engineers confirmed this statement the remaining one interviewee had no opinion regarding this issue. The following explanation supports this view:

“I think it is more complex to codify tacit knowledge through Social Media channels. […] It is not that easy, if you try to document your tacit knowledge. For small, not that complex tacit knowledge it can definitely help. However, increased complexity leads you to change the format of communication”.

The data also revealed another element which influences the codifiability of tacit knowledge negatively. The element time was mentioned frequently as a negative aspect in terms of codifying tacit knowledge. Referring to this, four Software Engineers supported this view the remaining three interviewees did not mention anything related to this issue. A Software Engineer explained as follows:

“It involves huge effort to write down the knowledge and to express it in words. […] It is a very time-consuming process”.

These findings partly confirmed previous findings, that it is difficult to codify tacit knowledge through Social Media channels because it also revealed, that codifiability depends on the complexity of the transferred tacit knowledge. According to the results, tacit knowledge which is not that complex can be codified and transferred through Social Media without any obstacles which contradict with the above-mentioned prior findings.

Scholars argue that face to face communication is the most efficient way of codifying tacit knowledge (Haldin-Herrgard, 2000; Falconer, 2006; Panahi et al, 2016). The interview data also confirms this view supported by all seven Software Engineers. In this connection, an interviewee stated:

“Face to face communication is definitely the best way to codify and transfer tacit knowledge”. Another Software Engineer supported this view with the following statement “I personally think that face to face communication is the best method to transfer tacit knowledge, because when you transfer tacit knowledge through face to face communication so you see the facial expression of your counterpart. It shows you whether your explanation was sufficient or not”.

23

“I personally experienced, that coworkers communicate very open with each other, on the same level like face to face communication. Therefore, they are able to share the same knowledge like which they can share through face to face communication”.

However, the data also highlighted that Social Media cannot be equivalent to face to face communication and, therefore not able to codify tacit knowledge appropriate. This was supported by three interviewees. The remaining two interviewees had no clear opinion regarding this issue. According to this, one of the Software Engineers stated:

“It is extreme difficult to transfer tacit knowledge correct. Transferring knowledge through writing it down, didn’t work that well, compared to transferring it through speaking format. For instance, if someone requires a knowledge regarding a technical issue which he/she didn’t know very well, then it is more difficult for me to transfer the required knowledge correct because it will be useless for him. Then the coworker is not able to use this knowledge or I transfer him the wrong knowledge”.

Further two interviewees mentioned that face to face communication has some characteristics which Social Media cannot replace.

“Through a face to face discussion a know-how can develop further, which works more effective through direct communication. Because it can lead to open discussions automatically. Social Media is a good alternative but not a solution. Social Media is not able to abolish face to face communication”.

Another two interviewees mentioned the missing feedback, if you use Social Media tools, which can influence the codify process of the knowledge.

“I personally think that face to face communication is the better method to transfer tacit knowledge, because when you transfer tacit knowledge through face to face communication so you see the facial expression of your counterpart. It shows you whether your explanation was sufficient or not. Accordingly, you can reformulate your sentence and try to explain it better. You can talk more about the details or try to keep it simpler. Face to face is always better to transfer tacit knowledge”.

24

Codifiability can be categorized into the second layer of the Knowledge Transfer Model. The empirical results revealed following sub facilitating elements complexity, time consuming, and face to face communication regarding codifiability. According to the results, these sub-elements differently influence the codifiability of tacit knowledge through Social Media channels. The data also confirmed that codifiability is an element which significantly influences the transfer of tacit knowledge between coworkers. According to the Knowledge Transfer Model this element can be influenced by organizational structure and organizational culture. For instance, organizational culture can influence the codifiability of tacit knowledge. For instance, it can determine how tacit knowledge can be requested or transferred between coworkers according to the existing communication culture within the organization. In addition, codifiability can influence the personal attitude of an employee as illustrated in the Knowledge Transfer Model. For instance, increased difficulty in terms of codifiability of knowledge can change the attitude of an employee and decrease his willingness to share their knowledge through these kinds of platforms. Consequently, the elements of codifiability are part of the second layer in the Knowledge Transfer Model, that can significantly influence the tacit knowledge transfer between coworkers. It can be influenced by the elements of the first layer and can influence the elements in the third layer.

Previous research also revealed that knowledge transfer activities are influenced by social relationships and these relationships decide about the dimension of the knowledge transferring activities (Lin and Lo, 2015; Staples and Webster, 2008; Haythornthwaite and de Laat, 2010). Especially, trust is a significant element according to researchers. For instance, trustworthiness of the counterpart has a positive influence on the knowledge transfer process (Wasko et al, 2009; Huang et al, 2011). However, the interview data of this study demonstrates controversial results. Four interviewees supported this argument as one of them mentioned:

“Trust is a crucial element for me. If I didn’t trust a person so I am less willing to share my knowledge with this person. For instance, if a coworker transfers your knowledge to other coworkers and demonstrates it as his own knowledge, then it disturbs me enormously. This kind of behavior has a negative impact on the knowledge transfer process. Therefore, you should trust the people to be ready to transfer your valuable knowledge”.

Interestingly, three Software Engineers also expressed that trust does not influence the transfer process significantly. A Software Engineer stated referring to this:

25

For this reason, there is no clear evidence about how trust influences the knowledge transfer between coworkers and how significant it is for the tacit knowledge transfer. However, the data also revealed that Social Media can be a helpful tool to build and strengthen trust between coworkers. This argument found support from five interviewees the other two interviewees had no clear opinion regarding this issue. One supporting statement was:

“Communicating through Social Media channels, especially, when you do some small talk which is not related to your job, can increase the trust between coworkers. Especially if this communication happens frequently”.

Consequently, frequent communication and information about your counterpart which you can get through Social Media channels can be helpful to build trust between coworkers. In the Knowledge Transfer Model, the element trust is located in the second layer on the facilitating level. That means that trust can be influenced by the elements from the organizational level and can influence the elements on the individual level. However, because of the controversial results there is no clear evidence whether trust is a significant element or not in terms of tacit knowledge transfer between coworkers.

The interview data revealed sympathy as a significant element which influences the engagement in knowledge transfer. In this regard, four interviewees mentioned and supported this view. The remaining three interviewees did not mention anything related to this issue. For instance, the following explanation supports this finding.

“Sympathy is an important element for me, even more than trust. Because if you don’t feel any sympathy for a coworker so you are less willing to engage with him into a knowledge transferring process. Only if I don’t have another choice, then I would contact that person. If I feel sympathy for a person so I will ask him immediately for that specific knowledge, but if it is not the case, so I will try to get the knowledge somehow by myself before I contact him”.

This finding supports prior research conducted by Matzler et al (2008) that sympathy influences the willingness of sharing knowledge with your counterpart. Thus, it can be concluded that sympathy is a significant interpersonal element, which decides about, whether a coworker is willing to share his valuable knowledge or not. Consequently, the empirical result confirms that it can be classified as a significant element on the facilitating level in the Knowledge Transfer Model which influences the personal attitude of an employee in terms of sharing tacit knowledge, as illustrated in the model.

26

who knows whom, which is seen as an important antecedent to increase collaboration and knowledge transfer between coworkers (Liden et al, 2004; Choi et al, 2010). The analyzed interview data supports these prior findings supported by five Software Engineers, two interviewees had no opinion regarding this issue. One of them explained in this regard:

“Social Media tools definitely helps to increase visibility between coworkers. For example, when an employee posts something about a specific field of software development on Social Media platforms, you automatically see this post and automatically keep it in mind that this person posted something about this and this. So later if you work in this specific field, for example with a specific software code, which you don’t understand because of lacking knowledge, then it automatically pops up in your mind that this one employee posted something about that, so he/she could possess the required knowledge. Consequently, interaction through Social Media helps to increase visibility between coworkers”.

It can be concluded that Social Media positively affects the knowledge transfer process. The analyzed interviews also confirmed that communication through Social Media increases the visibility between coworkers, that helps them to build metaknowledge about who knows what and who knows whom. Consequently, the increased communication and visibility positively influences the knowledge transfer between coworkers. Hence, the findings of this research support the prior research in this field and confirms the significance of this element in the tacit knowledge transfer process. The Knowledge Transfer Model confirms the influence of communication and visibility as well. As a part of the facilitating level, visibility can influence the elements on the individual level as the empirical results revealed. Increased visibility leads to a positive change of personal attitude and characteristic which positively influences the tacit knowledge transfer.

The data also revealed the element perceived loss of power which can be categorized to power games listed in the Knowledge Transfer Model. Prior research argue that tacit knowledge is unique and valuable and therefore, it can increase the power of coworkers if they possess these kinds of knowledge. Thus, the employees maybe do not want to share their valuable knowledge with their coworkers (Gray, 2001; Amidi et al, 2015; Pee and Lee, 2015). In this connection, three Software Engineers confirmed this view. One statement regarding this issue was:

27

However, the analysis of the data revealed controversial results regarding loss of power. Two interviewees disagreed on that, the remaining two interviewees had no opinion to this effect. One of the Software Engineers stated:

“In my industry knowledge is power. However, from my personal experience I can tell you that perceived loss of power doesn’t play a role regarding knowledge transfer between coworkers. Sure, there might exist some employees who see this different and I am also sure that in some areas of informatics you can gain more power if you acquire know how from your coworkers because it enables you to handle the processes more accurate. But in my field software engineering it is not the case. The reason for that is the increased teamwork in my field which requires high collaboration with other coworkers to finish a task successfully. Therefore, you have to share your valuable knowledge with your team to be successfully. Sharing tacit knowledge does not lead to loss of power, no it even helps you to increase your reputation.”

Accordingly, loss of power is a controversial element without any clear support for his significance in terms of tacit knowledge transfer between coworkers. Consequently, there is no clear support for the prior findings in this field which argued, that knowledge is used by organization members to elevate their own power (Jarvenpaa and Staples, 2001) and the more power games play a role, the less sharing of knowledge occurs (Willem and Buelens, 2007). Due to this, the significance of the element power games cannot be confirmed in the Knowledge Transfer Model.

28

influence the individual level in the Knowledge Transfer Model. Derived from the aforementioned statement, absence of sympathy can negatively influence the personal attitude in terms of tacit knowledge transfer and therefore, decrease the engagement of the coworkers among each other. Correspondently, it can be concluded that the empirical results partly support the facilitating level of the Knowledge Transfer Model.

4.4 Individual Level

The analyses of the empirical result revealed two elements which can be categorized into personal attitude which is part of the third layer named individual level of the Knowledge Transfer Model. One of these elements is personal benefits. In this connection, past research argued, that perceived lack of personal benefits which can occur if the perceived costs of sharing tacit knowledge outweighs the benefits lead to decreased willingness of employees in terms of sharing knowledge with their coworkers (Gray, 2001; Amidi et al, 2015; Pee and Lee, 2015). The interview data contradicts with these prior findings which were supported by three Software Engineers. The other four interviewees had no opinion or no clear view regarding this issue. One of the contradicting statement was:

“I don’t think that lack of personal benefits influences the transfer of tacit knowledge. Social Media enables you to gain new knowledge through participating on those platforms. The costs for participating are marginal and the benefits are enormous. Therefore, using Social Media for knowledge transfer is automatically beneficial”.

The other element disclosed by the data regarding personal attitude is competitive advantage. Competitive advantage can be classified into the third layer personal attitude because the perception regarding this element strongly depends on the attitude of each individual. Five interviewees supported this view while the other two interviewees had no opinion or no clear view regarding this issue. In this connection, one supporting argument was:

“Actually, in the reality losing competitive advantage through knowledge sharing shouldn’t be the case. Unfortunately, in the reality it is a huge issue, because if you share your knowledge with someone who is more or less your competitor to get a promotion, so he acquires my knowledge and increases his repertory. So, we both are on the same level then or maybe he is even better than me. Therefore, you sometimes reach a point where you say, no I don’t want to share my knowledge with this person because I want to get the promotion instead of him”.

29

Another interesting element, disclosed through the analysis of the empirical result, is increased pressure which is caused through the perception not to reach the expectations of other coworkers or even your supervisor. Five interviewees supported this view the other two interviewees had no opinion or no clear view regarding this issue. One of the interviewees mentioned:

“If you use this kind of platforms actively and post and share your knowledge frequently, your supervisors will recognize that. Other way around, if you didn’t post anything so your supervisors will also recognize that. This can lead to pressure to perform and also to indirect control. Increased pressure can negatively influence the knowledge transfer because the quality and the efficient transfer of knowledge will suffer under this kind of circumstances”

Increased pressure is also part of the third layer because it strongly depends on the personal characteristic of each coworker. As stated above pressure to perform can lead to inefficient knowledge transfer and hamper the process accordingly.

30

5. Discussion and Conclusion

The results of this research showed mixed support for the illustrated model derived and adjusted from the literature. Firstly, the outcomes illustrated the significance of Social Media specifically in the software development industry. It enhances the communication and collaboration between coworkers. Moreover, it positively influences the knowledge transfer which is essential in the software industry. The data also demonstrated that Software Engineers frequently works group-based on projects, which requires high collaboration, communication and knowledge transfer to be able to finish the entire project successfully. Therefore, the data supported the aspect that Software Engineers are appropriate for this research.

31

32

The empirical results are also contradicting with respect to the individual level of the Knowledge Transfer Model. The analysis revealed the significance of personal characteristic for the tacit knowledge transfer through Social Media. In this connection, the analysis disclosed pressure as a new element which was not discussed in prior research so far. It also revealed the effect that using Social Media can increase the perceived pressure which on the other hand, can negatively influence the tacit knowledge transfer process. Although, this effect was confirmed by the results, further research regarding this new element could reveal his strength. How strong it influences the tacit knowledge transfer between coworkers. However, in regard to personal attitude the analyzed result discovered two elements personal benefits and competitive advantage. Prior research regarding personal benefits argued that perceived lack of personal benefits leads to a decreased willingness in terms of sharing knowledge with their coworkers (Gray, 2001; Amidi et al, 2015; Pee and Lee, 2015). However, the interview data of this study revealed that personal benefits is not important regarding the engagement of coworkers to transfer tacit knowledge among each other. Referring to this, the result of this study revealed that costs for participating through Social Media for knowledge transfer are marginal and the benefits are enormous, therefore, personal benefits is not significant in this connection because the benefits outweighs the costs. Furthermore, the data revealed competitive advantage as a new element which was not researched so far. The analysis also supported the significance and the effect of this element. Consequently, because of contradicting findings there is no clear support for the significance of personal attitude on the tacit knowledge transfer through Social Media. In conclusion, the result partly confirms the organizational level of the Knowledge Transfer Model. It confirms the significance and the effect of personal characteristics and rejects personal attitudes. Further research is required to confirm the irrelevance of this element regarding this context.

33

study revealed contradicting findings because of the study context which is based on Social Media and tacit knowledge as research objectives. Finally, the research question can be answered as follows: The tacit knowledge transfer process through Social Media is complex and influenced by many elements from different areas. This study confirms the opportunity of Social Media to support this knowledge transfer process. In addition, it highlights the improvement in terms of collaboration, communication and especially tacit knowledge transfer. However, it also demonstrates the importance of further research regarding this topic.

5.1 Theoretical Implication

The results discussed in this paper underline the importance of Social Media in work environment nowadays. This research provides a broad insight about the influencing elements regarding the tacit knowledge transfer through Social Media channels. It partly confirms existing literature related to this issue, but also reveals new findings. This research highlights the significance of some elements which can influence the tacit knowledge transfer process. In addition, it also demonstrates the irrelevance of some elements that are an essential part of the Knowledge Transfer Model and therefore, raises new question marks that call for further research regarding this issue. Moreover, this study also revealed the effect of some significant elements that in addition, enables to understand how these elements influence the knowledge transfer process. Altogether, it can be concluded that this kind of platforms contains the potential to transfer tacit knowledge between coworkers. Additionally, it also stresses that further research is required to illustrate the significance of elements and their effects on the process in a more detailed way. The outcome of this research emphasized that tacit knowledge transfer through Social Media channels is a complex process, influenced by many elements on different levels.

5.2 Managerial Implication

34

of this research, it is of utmost importance that organizations establish a culture which creates an ambient atmosphere within the organization to support the tacit knowledge transfer between coworkers through Social Media platforms. In this regard, the top management and upper management support is essential to implement an adequate culture.

5.3 Conclusion

Due to controversial results of this research, it can be concluded that the research question is at least partially answered. Like the previous findings of Desouza (2003a) and Cheah and Abidi (2016), this study demonstrates that, Social Media can have a positive influence on tacit knowledge transfer even if not all elements are significant or their effects are unknown according to this study findings. Furthermore, the outcomes of this research illustrated the complexity of this question and revealed many new elements which can influence the transfer process through Social Media channels significantly. This study opens many opportunities for future research. One opportunity could be to analyze the revealed elements quantitatively with a bigger data and a more homogenous data set (i.e. cultural, country or other industry). This kind of research could help to identify which elements are statistically significant and how they are weighted compared among each other. In addition, the non-significant elements of this study could be analyzed quantitatively to underpin or reject the findings of this research. Another future research direction could be to study, how the different levels of the Knowledge Transfer Model influence each other. A quantitative study could give a broad insight about how the organizational level, facilitating level, and individual level are correlated with each other. Furthermore, it could also demonstrate how each level is weighted within the model. This kind of research would enable to understand the Knowledge Transfer Model more in detail and could identify which level and which elements accordingly are crucial regarding tacit knowledge transfer between coworkers. Another direction for a future research could be to investigate how Social Media effects the transfer of different types of tacit knowledge, because tacit knowledge can be subclassified in articulable tacit and inarticulable tacit knowledge (Panahi et al, 2016). Social Media is a quite new research subject, therefore, it requires more study to understand his opportunities and threats more accurate.

5.4 Limitations

35

36

References

Amidi, A., Jusoh, Y.Y., Abdullah, R.H., Jabar, M.A., & Khalefa, M.S. (2015). An overview on leveraging social media technology for uncovering tacit knowledge sharing in an organizational context. In: Paper presented at the 2015 9th Malaysian Software Engineering Conference (MySEC), 266-271.

Angehrn, A., Luccini, A.M., & Maxwell, K. (2009). InnoTube: a video-based connection tool supporting collaborative innovation. Interactive Learning Environments, 17 (3), 205-220. Ardichvill, A., Page, V., & Wentling, T. (2003). Motivation and barriers to participation in virtual

knowledge sharing communities or practice. Journal of Knowledge Management, 7 (1), 64-77.

Blasco-Arcas, L., Hernandez-Ortega, B., & Jimenez-Martinez, J. (2013). Adopting television as a new channel for e-commerce. The influence of interactive technologies on consumer behavior. Electron. Commerce Res., 13 (4), 457-475.

Bock, G.W., Zmud, R.W., Kim, Y.G., & Lee, J.N. (2005). Behavioral intention formation in knowledge sharing: Examining the roles of extrinsic motivators, social–psychological forces, and organizational climate. MIS Quarterly, 29 (1), 87-111.

Boeije, R., Vries, P.D., Kolfschoten, G.L., & Veen, W. (2009). Knowledge Workers and the Realm of Social Tagging. In Proceedings of the 42nd Hawaii International Conference on System

Sciences – 2009, 1-10.

Braun, V., Clarke, V. (2006). Using Thematic Analysis in Psychology. Qualitative Research in

Psychology, 3 (2), 77-101.

Brown, S., Dennis, A., Burley, D., & Arling, P. (2013). Knowledge sharing and knowledge management system avoidance: The role of knowledge type and the social network in bypassing an organizational knowledge management system. Journal Of The American

Society For Information Science & Technology, 64 (10), 2013-2023.

Burn, J., & Martinsons, M.G. (1997). Information Technology and the Challenge for Hong Kong.

Hong Kong: Hong Kong University Press.

Cavusgil, S., Calantone, R., & Zhao, Y. (2003). Tacit knowledge transfer and firm innovation capability. The Journal of Business and Industrial Marketing, 18 (1), 6-21.

Cheah, Y.N., Abidi, S.S.R. (2016). The Role of Information Technology in the Explication and Crystallization of Tacit Healthcare Knowledge. Health Informatics Journal, 7 (3-4), 158-167. Choi, S.Y., Lee, H., & Yoo, Y. (2010). The Impact of Information Technology and Transactive