Assessing the Use of Online Platforms in Sharing Tacit Knowledge in

Innovation Networks

Nathalya Guruge and Jyri Vilko

Department of Industrial Engineering and Management, LUT University, kauppalankatu 13, 45100 Kouvola, Finland

Keywords: Tacit Knowledge, Knowledge Sharing, Innovation Networks.

Abstract: In an increasingly digitalized society, sharing tacit knowledge has emerged as a critical activity for driving

innovation, especially within innovation networks. This paper presents a systematic literature review to assess

the role of online platforms in facilitating tacit knowledge sharing. It explores how digital tools impact the

exchange of tacit knowledge, offering a conceptual framework to understand this process. The findings

provide strategies for leveraging online platforms to foster innovation within diverse knowledge-driven

ecosystems.

1 INTRODUCTION

Tacit knowledge, which is uncodified and personal,

has become a crucial asset for innovation in the

modern knowledge society (Polanyi, 1966; Nonaka,

1994). As organizations increasingly prioritize

knowledge sharing to maintain competitive

advantages, particularly within the digital space,

understanding how tacit knowledge can be effectively

shared online is critical (Ichijo & Nonaka, 2007). This

paper ex-amines the practices and tools used in tacit

knowledge sharing, motivating and inhibiting factors

that affect tacit knowledge sharing and the outcomes

of this sharing particularly within innovation

networks, through a systematic review of literature.

2 THEORETICAL

BACKGROUND

This section explores the foundational theories of

tacit knowledge and innovation networks, setting the

stage for examining how digital platforms support

this knowledge exchange.

2.1 Tacit Knowledge

Tacit knowledge, first explored by Michael Polanyi

in 1958, refers to the inexpressible knowledge that

resides in the human subconscious, which is difficult

to articulate in written or spoken form (Polanyi,

1966). Nonaka (1994) later expanded on this concept,

asserting that the knowledge expressible in words is

only a small part of the broader body of knowledge.

Tacit knowledge, as further developed by Nonaka and

Takeuchi (1995), includes personal experiences,

beliefs, and values, and is harder to express explicitly,

but can be articulated in certain situations. In

management studies, Nonaka's definition of tacit

knowledge, emphasizing its implicit and experiential

nature, is more widely accepted.

The initial view of tacit knowledge suggested by

Polanyi sees a minor change during Nonaka’s time in

such a way that it becomes known as the part of

knowledge that is possible to be articulated and

expressed in certain situations. In management

studies these philosophical definitions of tacit

knowledge by Polanyi are not commonly used but

Nonaka’s definitions are accepted as more relevant.

Hence, tacit knowledge is the implicit knowledge

possessed by individuals including skills, insights,

intuitions, and experiences, which are often difficult

to express explicitly.

2.2 Tacit Knowledge Sharing Online

Tacit knowledge sharing is defined as the exchange

of intuitive and unarticulated knowledge that takes

the form of personal skills, know-how, experience,

and expertise in knowledge management literature.

This type of knowledge, which is intangible and

personal, occurs primarily between peers or co-

workers in a workplace and it involves direct

206

Guruge, N. and Vilko, J.

Assessing the Use of Online Platforms in Sharing Tacit Knowledge in Innovation Networks.

DOI: 10.5220/0012926000003838

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 16th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2024) - Volume 3: KMIS, pages 206-213

ISBN: 978-989-758-716-0; ISSN: 2184-3228

exchange of knowledge between employees

(Majewska and Szulczynska, 2014). However, the

importance of the need of support to foster trust and

overcome resistance to knowledge transfer is

highlighted by Majewska and Szulczynska (2014)

signalling of an establishment of a new argument

related to factors that can catalyse tacit knowledge

transfer which is addressed in this present study.

Tacit knowledge sharing is viewed as tacit-to-

tacit conversations (Socialization) and as tacit-to-

explicit conversations (Internalization) according to

the knowledge creation theory of Nonaka and

Takeuchi (1995) (Marwick, 2001; Sarkiunaite and

Kriksciuniene, 2005; Lopez-Nicolas and Soto-

Acosta, 2005). This is because of the interactive and

dynamic relationship between tacit and explicit

knowledge (Panahi et al., 2015). The scholars

explained this further using the spiral model of

knowledge management and stated that Nonaka and

Takeuchi’s theory on knowledge creation which

adopts a spiral movement indicates it is unavoidable

to externalize and internalize tacit knowledge when

communicating. With the introduction of web

initiatives, arguments on new tools that can drive

sharing tacit knowledge through interactive and

collaborative technologies was discussed (Panahi et

al., 2012). ICT has been one of the main enablers of

knowledge sharing activities (Panahi et al., 2016).

Building on this, online platforms, particularly those

leveraging Web 2.0 technologies, have enabled more

dynamic and interactive forms of knowledge sharing.

2.3 Innovation Networks

Innovation builds upon previous discoveries and

inventions, much like Newton's famous analogy of

"standing on the shoulders of giants."(Acemoglu et

al., 2016). A consistent and reliable network of

innovators facilitates the ongoing accumulation of

technological and scientific advancements leading to

economic growth and transformation. This is well

explained through Neo-Schumpeterian economics

that places technological innovation at the core of

economic advancement. According to the theory

accumulation of knowledge and technological

advancement is fueled by research and development

funding, intellectual property protection (Law),

Support for entrepreneurship and policymaking

(Government intervention). Hence, this is an

innovation system (Beije and Groenewegen, 1992)

and in modern literature known as ‘Innovation

Networks’. The term refers to the actors in an

innovation system and their relationships.

Difficulties in knowledge creation and learning

significantly impact the overall results and

achievements of a network of collaborating

organizations (Lampela, 2009). One practical

solution put forward by Lampela (2009) to overcome

the challenges in innovation networks is

implementing virtual innovation teams. Sharing

knowledge within virtual teams can be complicated

since it is unlike face-to-face communication.

Knowledge, especially tacit knowledge, is sensitive

information that is embedded in a person’s sub

conscious mind. The sharing of sensitive information

in innovation networks necessitates a high degree of

trust. Simultaneously, the operational processes

demand speed and flexibility, despite facing

uncertainty, complexity, and ambiguity in the

available information and operating environment

(Lampela, 2009). Hence, it is worth assessing the

factors that enable and moderate virtual tacit

knowledge sharing in innovation networks.

3 METHODOLOGY

This study utilizes a systematic literature review

approach, analysing peer-reviewed journal articles

and conference papers published between 2003 and

2023. The review spans various academic databases,

including Scopus and Web of Science, and focuses on

studies that explore the use of online platforms in tacit

knowledge sharing.

Main research question:

What is the use of online platforms in sharing tacit

knowledge in innovation networks?

This question is split into five questions to in a way

that they cover the wide span of the above research

question.

1. What are the practices used to share tacit

knowledge online?

2. What are the tools used to share tacit

knowledge online?

3. Which factors enhance tacit knowledge

sharing online?

4. Which factors inhibit tacit knowledge sharing

online?

Assessing the Use of Online Platforms in Sharing Tacit Knowledge in Innovation Networks

207

5. What are the possible outcomes of tacit

knowledge sharing online?

Once formulating the research questions, a

comprehensive search strategy was developed to find

articles and conference papers. The strategy includes

which scientific databases are used, the search terms

and inclusion exclusion criteria of data. This review

spans academic databases such as Scopus, Web of

Science and Ebsco. The descriptor contained

synonyms and related terms from each category of

key words to ensure the comprehensive coverage of

the topic. These words were either present in the Title

of the article which was optional and were present in

both the abstract and the key words section. This

bibliographic search was conducted from June 2023

to July 2024. The search was refined and repeated

several times until the optimum results were yielded.

The search for relevant literature was restricted to

peer-reviewed journal articles and conference papers

published in English between 2003 and 2023.

Textbook chapters were not included, and while the

search was limited to English language publications,

there were no restrictions based on geographic

location. The initial search yielded 80 articles, and

after filtering, 24 journal articles were selected for

review.

In search of conference papers, the same search

strategy was applied which resulted in 18 papers from

16 conferences. They were subjected to researcher

triangulation and 11 papers were considered suitable

to study the research questions. To ensure the quality

of studies conferences with a h-Index ranking were

selected. H-index was introduced by Jorge E. Hirsch

in 2005 to measure a researcher’s scientific

productivity and impact based on the number of

publications and citations (Hirsch, 2005; Meho and

Yang, 2007). This metric, now widely adopted in

academia, considers an H-Index of 30 or above as a

benchmark for selecting conferences in this study.

Once applying the H-Index seven articles were

initially chosen for full-text assessment. However,

two additional conference papers were included due

to their relevance to the research objectives and

quality: the Wireless Telecommunications

Symposium paper, a good H-Index of 20, and

"Potentials of social media for tacit knowledge

sharing amongst physicians: Preliminary findings"

(Panahi et al., 2012), which was deemed

exceptionally useful despite not meeting the strict

criteria. This resulted in a total of eight conference

papers being selected for review. Hence, a total of 30

journal articles and conference papers were analysed

in this review.

Figure 1: Research Design.

4 DATA ANALYSIS

This study employed both content and thematic

analysis to analyse data from 30 articles, using NVivo

and Microsoft Excel for qualitative data analysis.

Content analysis, following Gaur and Kumar (2018),

quantified specific elements within the data, while

thematic analysis, adhering to Braun and Clarke's

(2017,2022) guidelines, identified broader themes

and patterns. Data from the articles were recorded in

an Excel sheet with key columns such as author, DOI,

and findings, which were analysed to identify

descriptive and thematic results. A coding framework

was developed based on Gaur and Kumar’s (2018)

categories, focusing on practices, tools, factors

enhancing or inhibiting tacit knowledge sharing, and

outcomes. Iterative adjustments were made to

account for emergent themes that did not fit the initial

categories.

5 ANALYSIS

The line graph depicts the selected number of journal

articles, conference papers published each year and

the total number of data used in this review. The

highest number of articles has been published in

2019, and there are no conference papers this year.

This total drastically decreases in the following year,

KMIS 2024 - 16th International Conference on Knowledge Management and Information Systems

208

the year when the covid-19 pandemic started

spreading outside of China. The lowest number of

journal articles and conference papers were seen in

2015 with zero data from the year. There are 8 years

in which only one article or conference paper was

found. The overall trend is an increase which

indicated promising future for research interests in

tacit knowledge sharing online.

Figure 2: Number of journal articles and conference papers

according to the year published.

Of the 30 articles analysed, 22 mentioned practices

or/and tools used in TKSO. In the present context

practices are the processes and interactions that

facilitate TKSO. Hence, explaining how a tool, or an

online platform enables individual to share expertise

in online environments. The identified practices are;

Structuring information (Kogl and Gilbert, 2019),

Virtual communities (Chi-cheng et al., 2022), Virtual

learning activities (Haag and Duan, 2012; Hildrum,

2009), case analyses and sharing of experiences

(Deng et al., 2023) broadcasting information to wider

audiences, faster dissemination, personalized feeds,

staying up-to-date, documenting experiences, and

improved retrievability (Panahi et al., 2016).

Tools in the present research context are specific

technologies and platforms that assist the execution

of the practices. Such tools identified in the reviewed

studies are; Web 2.0 technologies (E-ling and

Xiaoxia, 2019; Jarrahi et al., 2019; Fang and Gong,

2012; Panahi et al., 2012), Social media platforms

(Panahi et al., 2016; Panahi et al., 2016 Mladenovoic

and Krajina, 2020; Liana et al., 2014; Amidi et al.,

2018; Amidi et al.,2017; Mislan et al.,2016), Online

community forums (Rachaneewan, 2011; Yuan et al.,

2016; Ku, 2014), Social networking applications

(SNAs) (Diptee and Diptee, 2013),Videos, Text,

interactive elements (drag and drop exercises (Hon et

al., 2008; Mislan et al.,2016), IoT, Digital twins,

Siemens tecnomatrix ( Guerra-Zubiage et al., 2021).

16 studies presented factors affecting tacit

knowledge sharing online. These factors either

belonged to motivating factors or hindering factors.

The following tables (table 1 and 2) depict each factor

identified along with the relevant references.

Table 1: Factors motivating tacit knowledge sharing online.

Motivating factors

References

Closeness of the

network

(Chi-Cheng et al.,2022; Cao et

al.,2012; Mislan et al., 2016)

Frequency of

interaction

(Cao et al.,2012; Chi-Cheng et

al.,2022; Tee and Karney,2010;

Diptee and Diptee,2013)

Stability of member

interaction

(Cao et al.,2012; Chi-Cheng et

al.,2022; Ku, 2014; Großer et

al.,2018; Panahi et al., 2016)

Intrinsic motivations

(enjoyment & self-

efficacy)

(Wang et al.,2022; Mislan et al.,

2016; Hildrum, 2009; Amidi et

al.,2017)

Personal traits

(Yuan et al., 2016; Diptee and

Diptee,2013)

Trust in the informant

(Diptee and Diptee,2013; Großer

et al.,2018; Panahi et al., 2016)

Communication style

(Diptee and Diptee,2013; Großer

et al.,2018)

Appropriate

technology use

(Großer et al.,2018; Amidi et

al.,2017; E.-Ling and Xiaoxia,

2019)

Factors that act as barriers to online tacit

knowledge sharing have not been studied by many

researchers hence the few refences.

Table 2: Factors hindering tacit knowledge sharing online.

Hindering factors

References

Lack of communication

(Metin, 2019)

Conflicting perspectives

(Metin, 2019; Jarrahi et al.,

2019)

Misaligned priorities

(Metin, 2019)

Lack of trust

(Cao et al.,2012; Mislan et al.,

2016)

Virtual rewards

(Wang et al.,2022)

Value dissimilarity

(Jarrahi et al., 2019)

Economic factors

(Deng et al.,2023)

Network reciprocity

(Deng et al.,2023)

Regarding the outcomes of Tacit knowledge

sharing online (TKSO), nine studies directly or

indirectly discussed the impact of TKSO. These

outcomes were concentrating on Organizational (2

Studies), Interpersonal (2 Studies), Both individual

and Organizational (1 study), and Individual (3

studies). The sector with the most outcomes is the

healthcare sector.

Assessing the Use of Online Platforms in Sharing Tacit Knowledge in Innovation Networks

209

6 FINDINGS

The systematic review of 30 articles reveals a diverse

landscape of tools and practices employed for TKSO.

22 of such articles addressed tools or practices used

in different contexts. Hence, this paper identifies

practices used for TKSO as; information structing,

memberships in virtual communities, virtual learning

activities, virtual case discussions, and the use of

social media features such as broadcasting and

personalized feeds. These practices collectively

enhance the accessibility and co-creation of tacit

knowledge among innovation networks.

The tools identified in this study largely falls into

two categories; 1. communicating and collaborating

tools, 2. Social media platforms. Skype, slack, e-

learning platforms, blogs, and wikis fall under

communicating and collaborating tools while Twitter,

Facebook and LinkedIn can be categorized under

social media platforms. However, both these

categories of tools enable real-time interaction,

collaborative content creation and knowledge

disseminations among innovation networks.

Real-time communication, collaborative features,

and personalization/ filtering capabilities within these

tools are essential for effective TKSO in innovation

networks. They promote engagement, facilitate

interaction, and help individuals find relevant up to

date information. In addition to the established tools

that are discussed above, this review identified

emerging technologies such as digital twins and IoT

being explored to capture tacit knowledge transfer

between humans and collaborative robots (Guerra-

Zubiage et al.,2021) highlighting the evolving

landscape of TKSO.

Out of 30 revied studies, 16 identified factors

influencing tacit knowledge sharing (TKSO),

categorized as moderating or inhibiting. The four key

moderating factors are network characteristics,

intrinsic motivation, trust, and communication

technology. Strong relationships and frequent

interactions within a network promote effective

TKSO, with trust in the knowledge provider—based

on benevolence, competence, and integrity—being

crucial. Organizations should encourage trust through

transparent communication and recognition of

expertise. Additionally, clear communication and

appropriate technology, such as real-time

communication tools, are vital for successful

knowledge exchange, with the choice of technology

and communication style being tailored to specific

contexts for optimal results.

Several factors inhibiting tacit knowledge sharing

(TKSO) were identified, including lack of trust and

poor communication, which are interconnected

barriers in virtual platforms. Building trust through

open communication and clear expectations is

crucial. Differences in values or negative attitudes

within innovation networks also hinder knowledge

sharing. Additionally, virtual rewards, if poorly

designed, can demotivate TKSO. Economic

disparities between regions influence knowledge

flow, with wealthier regions typically sharing more

knowledge with less successful ones. Lastly, network

reciprocity where knowledge is shared only when

something valuable is received can limit the

willingness to share tacit knowledge.

The findings highlight the complexity of tacit

knowledge sharing (TKSO), influenced by both

individual and contextual factors. Positive influences

include network characteristics and intrinsic

motivation, while the effects of external rewards and

social dynamics are more nuanced. TKSO is crucial

for innovation networks, promoting trust,

collaboration, and the sharing of expertise to drive

growth. The outcomes of TKSO extend beyond the

act of sharing, producing tangible benefits such as

increased knowledge and skills, and intangible ones

such as enhanced collaboration and innovation.

Nine studies, primarily focused on healthcare,

examined TKSO outcomes at individual and

organizational levels. Panahi et al. (2016) and

Muhammed Kashif et al. (2019) found that sharing

medical knowledge through social media enhances

both professional and personal development. At the

individual level, TKSO improves skills, motivation,

and innovation capabilities. Hildrum (2009) and Tee

and Karney (2010) emphasized that TKSO fosters

learning and problem-solving skills. Organizational-

level outcomes, as noted by Buunk et al. (2018) and

Panahi et al. (2016), include improved problem-

solving and innovation, showing TKSO as a catalyst

for individual and organizational growth and

innovation.

7 CONCLUSION

This systematic review highlights the crucial role of

online platforms in facilitating tacit knowledge

sharing (TKSO) within innovation networks. It

identifies a range of tools, from social media to

emerging technologies like digital twins, which

promote TKSO. Both individual-level and

organizational-level benefits, such as professional

development, innovation, and problem-solving, are

noted. However, TKSO's effectiveness is influenced

KMIS 2024 - 16th International Conference on Knowledge Management and Information Systems

210

by factors like network characteristics, motivation,

trust, and appropriate technology use.

The review offers insights for fostering a

knowledge-sharing culture by emphasizing trust,

collaboration, and the selection of suitable tools. A

conceptual framework is developed to illustrate the

interplay between individual characteristics

(moderating factors) and contextual factors (enabling

factors) in the TKSO process. The framework

underscores the recurring nature of knowledge

sharing and provides a foundation for future research

and practice.

Figure 3: Conceptual framework for TKSO in innovation

networks.

Overall, this review highlights the multifaceted

impact of TKSO, extending beyond the mere

exchange of information. By understanding these

outcomes, organizations can develop strategies to

leverage online platforms and create environments

that encourage and reward the sharing of tacit

knowledge, ultimately driving individual growth and

organizational success.

REFERENCES

Acemoglu, D., Akcigit, U., Kerr, W. R. (2016). Networks

and the Macroeconomy: An Empirical Exploration.

NBER Macroeconomics Annual, 30, 273-335. DOI:

10.1086/685961.

Amidi, A., Jabar, M., Jusoh, Y.Y. and Abdullah, R. (2017).

Appropriation of social media for fostering effective

tacit knowledge sharing: developing conceptual model.

Journal of Physics: Conference Series, [online] 892,

p.012012. doi: https://doi.org/10.1088/1742-6596/892/

1/012012.

Amidi, S., Yusmadi Yah Jusoh, Mar Yah Said, Jabar, M.A.

and Abdullah, R. (2018). Application of Social Media

Among Medical Practitioner for Sharing Tacit

Knowledge: A Pilot Study. [online] doi:

https://doi.org/10.1007/978-981-10-8276-4_32.

Beije, P. R. & Groenewegen, J. (1992). A Network

Analysis of Markets. Journal of economic issues.

[Online] 26 (1), 87–114. DOI: 10.1080/00213624.

1992.11505263.

Braun, V. & Clarke, V. (2022). Thematic analysis: a

practical guide. SAGE Publications, London.

Buunk, I., Smith, C.F. and Hall, H. (2018). Tacit knowledge

sharing in online environments: Locating ‘Ba’ within a

platform for public sector professionals. Journal of

Librarianship and Information Science, [online] 51(4),

pp.1134–1145. doi: https://doi.org/10.1177/

0961000618769982.

Cao, W., Xu, L., Liang, L. and Chaudhry, S.S. (2012). The

impact of team task and job engagement on the transfer

of tacit knowledge in e-business virtual teams.

Information Technology and Management, [online]

13(4), pp.333–340. doi: https://doi.org/10.1007/s1

0799-012-0129-6

Clarke, V. & Braun, V. (2017). Thematic analysis. The

journal of positive psychology. [Online] 12 (3), 297–298.

Deng, Z., Deng, Z., Liu, S. and Evans, R. (2023). Knowledge

transfer between physicians from different geographical

regions in China’s online health communities.

Information Technology & Management. [online] doi:

https://doi.org/10.1007/s10799-023-00400-3.

Diptee, D. and Diptee, J. (2013). Tacit knowledge

acquisition in virtual teams. 2013 Wireless

Telecommunications Symposium (WTS). [online] doi:

https://doi.org/10.1109/wts.2013.6 566228

Duan, Y. and Haag, M. (2011). Understanding personal

knowledge development in online learning

environments: an instrument for measuring

externalization, combination, and internalization.

Electronic Journal of Knowledge Management.

[online] Available at: https://search.ebscohost.com/

=ehost-live

Fang, J. and Gong, L. (2011). Web2.0 Environment of

Personal Knowledge Management Applications.

Lecture notes in electrical engineering, [online]

pp.1639–1646. doi: https://doi.org/10.1007/978-94-

007-1839-5_177

Gaur, A. and Kumar, M. (2018). A systematic approach to

conducting review studies: An assessment of content

analysis in 25 years of IB research. Journal of World

Business, 53(2), pp.280-289.

Großer, B., Kepplinger, S., Vogel, C. and Baumöl, U.

(2018). Knowledge Processes in Virtual Teams - Tacit

Knowledge. [online] 20th International Conference on

Enterprise Information Systems. doi: https://doi.org/10.

5220/0006674602470254

Guerra-Zubiaga, D.A., Navid Nasajpour-Esfahani, Phan,

N.Q., Gupta, S. and Block, L. (2021). Tacit Knowledge

Assessing the Use of Online Platforms in Sharing Tacit Knowledge in Innovation Networks

211

Capture Using Digital Tools in a Human-Robot

Interaction: A Case Study. Volume 2B: Advanced

Manufacturing. [online] doi: https://doi.org/10.1115/

imece2021-66084.

Haag, M. & Duan, Y. (2012). Understanding Personal

Knowledge Development in Online Learning

Environments: An Instrument for Measuring

Externalization, Combination, and Internalization. The

Electronic Journal of Knowledge Management, 10(1),

pp. 39-47.

Hildrum, J. M. (2009). Sharing Tacit Knowledge Online:

A Case Study of e-Learning in Cisco’s Network of

System Integrator Partner Firms. Industry &

Innovation, [online] 16(2), pp.197–218. doi:

https://doi.org/10.1080/13662710902764360.

Hirsch, J. E., 2005. An index to quantify an individual's

scientific research output. Proceedings of the National

Academy of Sciences, 102(46), pp.16569-16572.

Huang, C.-Y., Gamage, B., Bryce, E.A., LoChang, J.,

Yassi, A., Maultsaid, D. and Yu, S. (2008). Personal

protective equipment in health care: Can online

infection control courses transfer knowledge and

improve proper selection and use? American Journal of

Infection Control, [online] 36(10), pp. e33–e37. doi:

https://doi.org/10.1016/j.ajic.2008.07.007

Hsiao, E-Ling. and Huang, X. (2019). Strategies to Support

Personal Knowledge Management Using a Wiki Site in

Online Courses. The Journal of Educators Online,

[online] 86 16(1). doi: https://doi.org/10.9743/

jeo.2019.16.1.5

Jarrahi, M. H., Philips, G., Sutherland, W., Sawyer, S. and

Erickson, I. (2019). Personalization of knowledge,

personal knowledge ecology, and digital nomadism.

Journal of the Association for Information Science and

Technology, [online] 70(4), pp.313–324. doi:

https://doi.org/10.1002/asi.24134

Kashif Imran, M., Fatima, T., Aslam, U. and Muhammad

Javed Iqbal, S. (2019). Exploring the Benefits of Social

Media Towards Knowledge Sharing Among Doctors.

Pakistan Journal of Psychological Research, [online]

34(2), pp.331–352. doi: https://doi.org/10.33824/

pjpr.2019.34.2.18.

Ku, E. C. S. (2012). Distributed Fascinating Knowledge

Over an Online Travel Community. International

Journal of Tourism Research, [online] 16(1), pp.33–43.

doi: https://doi.org /10.1002/jtr.1895

Kögl, S. and Silvius, G. (2019). Using Patterns to Capture

and Transfer Tacit Knowledge in Virtual Project

Teams. Semantic Scholar, [online] 7(20). doi:

https://doi.org/ 10.19255/JMPM02002

Lampela, H.: Inter organizational learning within and by

innovation networks. Lappeenranta University of

Technology. http://lutpub.lut.fi/handle/10024/45412

(2009)

Lee, C.-C., Lee, L.-C. and Kao, R.-H. (2022). How do

Enterprises promote innovation performance? A study

on the relationship between online communities and

innovation 87 performance-exploring the mediating

effect of tacit knowledge. Current Psychology. [online]

doi: https://doi.org/10.1007/s12144-022-02890-

Liu, E. and Song, M.: Innovation Networks and R&D

Allocation *. [online] Available at:

https://ernestliu.scholar.princeton.edu/sites/g/files/toru

qf4426/files/documents/paper.pdf (2024)

López-Nicolás, C. and Soto-Acosta, P., 2010. Analyzing ICT

adoption and use effects on knowledge creation: An

empirical investigation in SMEs. International Journal

of Information Management, 30(6), pp.521-528.

Marwick, A., 2001. The New Nature of History:

Knowledge, Evidence, Language. Oxford: Oxford

University Press.

Majewska, M. & Szulczyńska, U. (2014). Methods and

Practices of Tacit Knowledge Sharing Within an

Enterprise: An Empirical Investigation. Oeconomia

Copernicana. [Online] 5 (2), 35–48.

Meho, L.I. and Yang, K., 2007. Impact of data sources on

citation counts and rankings of LIS faculty: Web of

Science vs. Scopus and Google Scholar. Journal of the

American Society for Information Science and

Technology, 58(13), pp.2105-2125.

Metin, F. (2019). 'The factors influence online tacit

knowledge sharing in public organisations: A

qualitative case study from Turkey', *Gaziantep

University Journal of Social Sciences*, 18(3), pp.

1121-1142. doi: 10.21547/jss.442144.

Mislan, A., Sahibi, M.S., Jamaluddin, A., Sufi Alawi Idris,

A. and Hartina Ahmad, N. (n.d.). The arts of

Knowledge Transfer in Virtual Organization: Tacit

Knowledge. International Journal of Computer Science

and Network Security, [online] 16(4). Available at:

http://paper.ijcsns.org/07_book/201604/20160408.pdf

Mladenović, D. and Krajina, A. (2019). KNOWLEDGE

SHARING ON SOCIAL MEDIA: STATE OF THE

ART IN 2018. Journal of Business Economics and

Management, [online] 21(1), pp.44–63. doi:

https://doi.org/10.3846/jbem.2019.11407

Nonaka, I., & Takeuchi, H. (1995). The knowledge-

creating company: How Japanese companies create the

dynamics of innovation. New York: Oxford University

Press.

Nonaka, I. (1994). A Dynamic Theory of Organizational

Knowledge Creation. Organization science

(Providence, R.I.). [Online] 5 (1), 14–37. DOI:

10.1287/orsc.5.1.14.

Nilmanat, R. (2011). Investigating image usage and tacit

knowledge sharing in online communities.

Nonaka, I. & Teece, D. J.: Managing industrial knowledge:

creation, transfer, and utilization. London: Sage.ISBN:

0-7619-5498-8 (2001)

International Journal of Innovation and Learning, [online]

10(4), p.350. doi: https://doi.org/10.1504/

ijil.2011.043095

Panahi, S., Watson, J. and Partridge, H. (2012). Potentials

of social media for tacit knowledge sharing amongst

physicians: preliminary findings. Science &

Engineering Faculty. [online] Available at:

https://www.scopus.com/inward/record.uri?eid=2-

s2.0-84878301263&partnerID=40&md5=

c5aabe4d94691a551f8ab7d717846694.

KMIS 2024 - 16th International Conference on Knowledge Management and Information Systems

212

Panahi, S., Watson, J. and Partridge, H. (2015). Information

encountering on social media and tacit knowledge

sharing. Journal of Information Science, [online] 42(4),

pp.539–550. doi: https://doi.org/10.1177/

0165551515598883

Panahi, S., Watson, J. and Partridge, H. (2016).

Conceptualizing social media support for tacit

knowledge sharing: physicians’ perspectives and

experiences. Journal of Knowledge Management,

[online] 20(2), pp.344–363. doi: https://doi.org/10.

1108/jkm-06-2015-0229.

Polanyi, M. (1958). Personal knowledge; towards a post-

critical philosophy. University of Chicago Press,

Chicago.

Polanyi, M. (1966). The Tacit Dimension, University of

Chicago Press, London (1966).

Rachaneewan, M. (2011). Investigating image usage and

tacit knowledge sharing in online communities,"

International Journal of Innovation and Learning,

Inderscience Enterprises Ltd, vol. 10(4), pages 350-

364.

Razmerita, L., Kirchner, K. and Nabeth, T. (2014). Social

Media in Organizations: Leveraging Personal and

Collective Knowledge Processes. Journal of

Organizational Computing and Electronic Commerce,

[online] 24(1), pp.74–93. doi: https://doi.org/10.1080/

10919392.2014.866504.

Sarkiunaite, I. and Kriksciuniene, D., 2005. Impacts of

Information Technologies on Tacit Knowledge

Sharing: Empirical Approach. Informacijos Mokslai,

35, pp.69-79.

Ichij, K. & Nonaka, I. (2007). Knowledge creation and

management: new challenges for managers. Oxford:

Oxford University Press.ISBN: 9780195159622.

Tee, M. Y. and Karney, D. (2010). Sharing and cultivating

tacit knowledge in an online learning environment.

International Journal of Computer-Supported

Collaborative Learning, [online] 5(4), pp.385–413. doi:

https://doi.org/10.1007/s11412-010-9095-3.

Tidd, J., Bessant, J., & Pavitt, K.: "Managing innovation;

integrating technological, market and organizational

change, 2d ed", 2001/11//, Reference and Research

Book News, vol. 16, no. 4 (2001).

Wang, N., Yin, J., Ma, Z. and Liao, M. (2021). The

influence Practice of rewards on knowledge sharing

behaviors in virtual communities. Journal of

Knowledge Management, [online] 26(3), pp.485–505.

doi: https://doi.org/10.1108/jkm-07-2020-0530

Yuan, D., Lin, Z. and Zhuo, R. (2016). What drives

consumer knowledge sharing in online travel

communities? Personal attributes or e-service factors?

Computers in Human Behavior, [online] 63, pp.68–74.

doi: https://doi.org/10.1016/j.chb.2016.05.019

Yudhistira, D.S. and Sushandoyo, D. (2020). Does political

self-disclosure in social media hamper tacit knowledge

sharing in the workplace? VINE Journal of Information

and Knowledge Management Systems, [online] 50(3),

pp.513–530. doi: https://doi.org/10.1108/vjikms-08-

2019-0128

Assessing the Use of Online Platforms in Sharing Tacit Knowledge in Innovation Networks

213