Factors Influencing Social Knowledge Management in Social Society: A Systematic Literature Review

Factors Influencing Social Knowledge Management in Social Society: A Systematic Literature Review

Volume 5, Issue 3, Page No 198-206, 2020

Author’s Name: Erick Fernando1,a), Meyliana1, Achmad Nizar Hidayanto2, Harjanto Prabowo3

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1School of Information Systems, Information Systems Department, Bina Nusantara University, 11480, Indonesia
2Faculty of Computer Science, Universitas Indonesia, 16424, Indonesia
3BINUS Graduate Program – Doctor of Computer Science, Computer Science Department, Bina Nusantara University, 11480, Indonesia

a)Author to whom correspondence should be addressed. E-mail: erick.fernando001@binus.ac.id

Adv. Sci. Technol. Eng. Syst. J. 5(3), 198-206 (2020); a  DOI: 10.25046/aj050326

Keywords: Social society, Knowledge Management, Social Knowledge Management, Systematic literature review

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Knowledge is important now for the development of social society; it is necessary for knowledge management. Knowledge management (KM) aims to support the creation, transfer, and application of knowledge in social societies. This fact illustrates that in the management of social knowledge, the role of social communities is very important and is influenced by factors in the process. With this, this study will look for theories and factors that influence KM social interactions that occur in social societies. The method used is a systematic literature review. The results of this study found theories and factors that influence KM in social societies.

Received: 15 April 2020, Accepted: 21 April 2020, Published Online: 19 May 2020

1. Introduction

In the development of organizations and social societies, the need for knowledge becomes the most important [1][2][3]. The need is seen in transactions of knowledge through social ties and organizations that will provide developments within the organization or social community. The importance of acquiring knowledge and combinations as a source of value creation and competitive advantage [1]. Thus knowledge needs to be better managed [4][5]. Knowledge management (KM) aims to support the creation, transfer, and application of knowledge in organizations and social communities [3][6]. Social knowledge management is a management based on KM that involves social relationships [7]. This KM In management, there are two main aspects: one that refers to the management of general and other knowledge, which is particularly included in its social character.

A social character can be seen in social network relationships and knowledge management, to explain how it is acquired, transferred, exchanged, and generating knowledge [5] about the basic social processes and learning of the organization; Knowledge science and technology management, which aims to promote research and development and use of ICT; A holistic knowledge management model, including models not seen in previous models and integrating new subdisciplines [7][8].

Knowledge management that occurs in the social community influenced interaction relationships that occur therein. The interaction that occurs will have the factors that affect an individual to interact. With this in the study wanted to find these factors. This study was conducted by systematic review literature. Therefore, this study tries to define “Theory dan factor influencing social knowledge management of social society?”. This research will focus on looking for factors that influence social character within each social networking relationship for knowledge management. Where knowledge management begins making, transferring, making, and producing the knowledge gained in social society.

2. Theoretical foundations

2.1.  Knowledge Management

KM is a collection of tools, techniques, and strategies to maintain, analyze, organize, enhance, and share insights and experiences that justify the belief that knowledge is an asset to enhance the capacity of the organization to be able to work more effectively[1][9].

The existence knows knowledge management of Tacit Knowledge and Explicit Knowledge[10], [11]. Tacit Knowledge means the science or experience one gets through a daily activity in doing a field of work. Tacit knowledge will simply disappear if the person concerned does not share his / her knowledge with others (transfer knowledge) or is not well documented in hard/soft copy[11]. Explicit Knowledge is more to how the science is well documented, so it can be stored ideally and does not just disappear[11]. Knowledge management model, Nonaka, and Takeuchi are renowned for their SECI (Socialization, Externalization, Combination, and Internalization) methods [11].

2.2.  Social Community

The community is a small or large social unit that has similarities that are described as norms, religions, values, or identities. This community is located in a specific geographic region or in cyberspace through a platform. Sometimes the community can be defined as a social bond. It is just as important as their identities, practices, and roles in social institutions such as family, home, work, government, community, or humanity [12].

2.3.  Social Knowledge Management

Social Knowledge Management is production management and dissemination of knowledge, research, and socially promoted epistemological models of the class[13]. Knowledge development in society involves the participation of social actors themselves and Trans Discipline (which is not equivalent to interdisciplinarity). The knowledge formed in this environment is the responsibility of the social individual to disseminate that has been facilitated in the exercise of critical thinking (social accessibility of knowledge) and has adequate social outreach for community development [13].

3. Methodology

This study uses a systematic literature review (SLR) approach. SLR is used to identify, evaluate, and interpret all relevant research from research questions, phenomena, and topic areas [14]. SLR is carried out with several processes, including search process, inclusion criteria and exclusion, data extraction, and analysis of findings to answer research questions.

3.1.  Search process

The first systematic literature review (SLR) process was carried out by searching for relevant articles and find with research in a reliable, reputable, and up-to-date journal database. The database includes:

  1. ACM Digital Library (dl.acm.org)
  2. IEEE Xplore Digital Library (http:/ieeexplore.ieee.org)
  3. JStor (www.jstor.com)
  4. Science Direct (sciencedirect.com)
  5. Emerald Insight (emeraldinsight.com)
  6. Springer Link (link.springer.com)
  7. Taylor and Francis (tandfonline.com)

Search process in this research using the Boolean operator. This search can filter search data better, so search gets priority data. the Boolean operators used are AND and OR. the composition used by keyword is as follows:

  1. (‘Social’ AND ‘knowledge ‘AND ‘Management’) OR (‘Theory’)
  2. (‘Knowledge’ AND ‘Management’ OR’ Social’)
  3. (‘Knowledge’ AND ‘Management’ OR’ Social Theory’)
  4. (‘Knowledge’ AND ‘Management’ OR’ Social Society’)

3.2.  Inclusion and exclusion criteria

The search inclusion process has three criteria, namely (1) Founded Study is the process of finding documents based on keywords, (2) Candidate Study is the process of selecting documents based on titles and abstracts that are relevant to the research objectives, (3) Selected Study is the process of filtering documents by reading carefully consider all that is used to answer research questions.

The exclusion criteria process has provisions including determining the time of publication of a paper used so that in this study using a time period before 2001, a complete article identity structure (title, author, journal name, etc.), ensuring the article used is not duplicate and The built SLR can answer the questions in the research consistently.

3.3.  Data extraction

The literature search process began in November 2017 by finding 278 article documents from the database, and the search criteria that have been determined are founded studies. The second process found 152 article documents from the screening process of relevant documents based on titles and abstracts as candidate studies. the final process found 39 article documents which through the process of careful reading of the contents of the document as candidate studies and used to answer research questions

Table 1. Number studies in selected sources

Source founded Studies Candidate studies Selected studies
Emerald 60 45 3
IEEE 40 16 6
Jstor 30 17 3
ACM 25 10 3
Science Direct 35 15 5
Taylor and Francis 48 31 9
springer 40 18 10
278 152 39

4. Results and discussions

4.1.  Demographic and trend characteristics
4.1.1.    Publishing outlets

From the search process, there is a great deal of research in various conferences and journals. This study found among others: journal Knowledge Management Research & Practice (#5), Hawaii International Conference on System Sciences (#2), International Journal of Information Management (#2), Total Quality Management & Business Excellence (#2), and the other amounted to 1. The total number of 39 from conference and journal, can be seen in the following table 2

Table 2. Source of publications

Journal/ conference Journal/conference name # %
Journal Knowledge Management Research & Practice 5 12.82
conference 2011 44th Hawaii International Conference on System Sciences 2 5.13
Journal International Journal of Information Management 2 5.13
Journal Total Quality Management & Business Excellence 2 5.13
conference 2010 International Conference on E-Product E-Service and E-Entertainment, ICEEE2010 1 2.56
conference 2014 IEEE Workshop on Advanced Research and Technology in Industry Applications (WARTIA) 1 2.56
conference Adaptation and Value Creating Collaborative Networks: 12th IFIP WG 5.5 Working Conference on Virtual Enterprises, PRO-VE 2011 1 2.56
Journal Advances in Intelligent and Soft Computing 1 2.56
Journal Computational and Mathematical Organization Theory 1 2.56
Journal Development in Practice 1 2.56
Journal Healthcare Knowledge Management SE – 8 1 2.56
Journal Housing, Care and Support 1 2.56
conference IFIP Advances in Information and Communication Technology 1 2.56
Journal Information & Management 1 2.56
Journal Information Processing and Management 1 2.56
conference International Conference on Context-Aware Systems and Applications 1 2.56
conference International Conference on Knowledge Management in Organizations 1 2.56
conference International Symposium IUKM 2013 1 2.56
Journal Journal of Business Ethics 1 2.56
Journal Journal of Information Technology 1 2.56
Journal Journal of Integrated Care 1 2.56
Journal Journal of International Business Studies 1 2.56
Journal Journal of Knowledge Management 1 2.56
conference Procedia Computer Science 1 2.56
conference Proceeding OSDOC ’13 Proceedings of the Workshop on Open Source and Design of Communication 1 2.56
conference Proceedings of the 2010 International Conference on Information Technology and Scientific Management 1 2.56
conference Proceedings of the 2012 iConference on – iConference ’12 1 2.56
conference Proceedings of the 41st Annual Hawaii International Conference on System Sciences (HICSS 2008) 1 2.56
conference Proceedings of The 3rd Multidisciplinary International Social Networks Conference on Social Informatics 1 2.56
Journal Public Performance and Management Review 1 2.56
Journal Technology Analysis and Strategic Management 1 2.56
Journal The Academy of Management Journal 1 2.56
Total source publication 39

4.1.2.  Most productive institutions

The most productive institution is a National Central University, National Central University, Ewha Woman’s University with two paper each. An others institution each have one paper. Detail data can be seen in table 3 which in total there are 53 institutions.

Table 3 Source of publications

Institutions # papers   %
National Central University, 2 3.64
Hebei University of technology Tianjin 2 3.64
Ewha Womans University 2 3.64
Vrije Universiteit Amsterdam 1 1.82
University of Zagreb 1 1.82
University of Westminster, 1 1.82
University of Twente, 1 1.82
University of Turkey, 1 1.82
University of Toronto 1 1.82
University of Science and Technology 1 1.82
University Of Salford 1 1.82
University of Melbourne 1 1.82
University of Manchester 1 1.82
University of Las Palmas de Gran Canaria 1 1.82
University of Groningen 1 1.82
University of Caxias do Sul 1 1.82
University of Auckland 1 1.82
Universiti Teknologi Malaysia 1 1.82
Universiti Teknologi Malaysia 1 1.82
universitas liverpool 1 1.82
Tilburg University, 1 1.82
The Hong Kong Polytechnic University 1 1.82
Technical University of Bari, 1 1.82
Royal Tropical Institute, 1 1.82
Renmin University of China, 1 1.82
North Carolina State University , 1 1.82
National University of Singapore, 1 1.82
National Taiwan Ocean University 1 1.82
National Sun Yat-sen University, 1 1.82
National Quemoy University, 1 1.82
National Kaohsiung First University of Science of Technology 1 1.82
Nanyang Technological University, 1 1.82
Jiangsu University of Science and Technology 1 1.82
Jiangsu University of Science and Technology 1 1.82
Instituto Universitario de Lisboa 1 1.82
Hong Kong Baptist University 1 1.82
FCET Staffordshire University, 1 1.82
Dalian University of Technology Dalian 1 1.82
City University of Hong Kong 1 1.82
Center for Innovation Research, 1 1.82
Bei Hang University, 1 1.82
Autonomous University of Baja California 1 1.82
Arizona State University 1 1.82
Åbo Akademi University 1 1.82
 University of Siegen 1 1.82
 The University of Sydney Business School 1 1.82
 National Chiao Tung University 1 1.82
 National Central University, 1 1.82
 Harrisburg University of Science and Technology 1 1.82
 Gazi University 1 1.82
 Australian National University (ANU) 1 1.82
 Al Ghurair University, 1 1.82
 Peking University, 1 1.82
Total institution : 53 institutions 56

4.2.  Authors’ academic backgrounds

The academic background author that can be seen in table 3 consists of 18 backgrounds of 91 authors that match the research.

Table 4. Discipline of authors

Department # %
Department of Information Systems 14 12.74
Information Management 13 11.83
Business Administration 11 10.01
Industry 10 9.1
Management 9 8.19
Economics and Management 9 8.19
Architecture and Urban Studies 4 3.64
Department of Informatics 3 2.73
Chemical Sciences and Engineering 3 2.73
Center for Sustainable Innovation 3 2.73
Technology and Management 2 1.82
Shipping and Transportation Management 2 1.82
Business and Finance 2 1.82
Business and Economics 2 1.82
Science and Technology 1 0.91
Development Policy Management 1 0.91
Department of Management and Marketing 1 0.91
Computing Drive 1 0.91
Total 91

4.3.  Background of authors

The author’s background consists of 81 academic and 32 from the industry. Those who do related research on knowledge management.

Table 5. Background of authors

Background author # %
Academic 81 90.9
industry 10 9.1
Total 91

4.4.  University affiliation according to country

University affiliation of the 68 countries, China has 16 authors with six institutions, Taiwan has 13 authors with six institutions, the USA has nine authors with five institutions, Netherland has eight authors with five institutions, the UK has seven authors with four institutions, and detail data can see in table six. it is a country that contributes in the development research in knowledge management.

Table 6. University affiliation according to country

  Country # authors % authors # institutions % institutions
China 16 17.58 6 12.77
Taiwan 13 14.29 6 12.77
USA 9 9.89 5 10.64
Netherlands 8 8.79 5 10.64
UK 7 7.69 4 8.51
Hongkong 5 5.49 3 6.38
Italy 4 4.40 1 2.13
Korea Selatan 4 4.40 1 2.13
Australia 3 3.30 2 4.26
Portugal 3 3.30 1 2.13
Brazil 3 3.30 1 2.13
Finland 2 2.20 2 4.26
Singapore 2 2.20 2 4.26
Spain 2 2.20 1 2.13
Turkey 2 2.20 1 2.13
Malaysia 2 2.20 1 2.13
New Zealand 2 2.20 1 2.13
United Arab Emirates 1 1.10 1 2.13
Australia 1 1.10 1 2.13
México 1 1.10 1 2.13
Croatia 1 1.10 1 2.13
Total country: 21 countries 91 47

4.5.  Most prolific authors

From the analyst’s point of view, there are 90 authors with 39 papers. The author who actively found the author on KM in social society is Marleen Huysman (# 2). Another writer averages one article. It can be seen clearly in Table 7 below.

Table 7. most prolific authors

Author # %
Marleen Huysman 2 2.25
Albert A. Cannella Jr 1 1.12
Gang Qu 1 1.12
Rolando Vargas Vallejos 1 1.12
Amanda Edwards 1 1.12
Andrew Long 1 1.12
Annette Boaz 1 1.12
Anne-wil Hazing 1 1.12
AydÄntan Belgin 1 1.12
Bosen Li 1 1.12
CarlaC.J.M. Milla 1 1.12
Carlos J. Costa 1 1.12
Caterina De Lucia 1 1.12
Chen Yen Yao 1 1.12
Chen Yijia 1 1.12
Cheng Yang Lai 1 1.12
Chia Fen Chung 1 1.12
Chin-Chung Tsai 1 1.12
Chongju Choi 1 1.12
Chun-Wei Choo 1 1.12
David Sundaram 1 1.12
Dino Borri 1 1.12
Fan Yi-Wen 1 1.12
G.Widen 1 1.12
Goksel Aykut 1 1.12
Guido Sechi 1 1.12
He Wei 1 1.12
Hsing Kuo Wang 1 1.12
Hsiu-Fen Lin 1 1.12
Janaina Macke 1 1.12
Javier Osorio 1 1.12
Jay Liebowitz 1 1.12
Jin Hui 1 1.12
Jingjing Han 1 1.12
Jin-Xing Hao 1 1.12
Jo van Engelen 1 1.12
Jordan Lewis-Pryde 1 1.12
Jui Pattnayak 1 1.12
Julia Nieves 1 1.12
Jung Feng Tseng 1 1.12
Kadgia Faccin 1 1.12
Kang Kai 1 1.12
Kelly Lyons 1 1.12
Kwok-Kee Wei 1 1.12
Lesley Gray 1 1.12
Li Wang 1 1.12
Lorna Uden 1 1.12
Lv Jingyin 1 1.12
M. Ann McFadyen 1 1.12
Manuela Aparicio 1 1.12
Margaret Sheng 1 1.12
Mark W.McElroy 1 1.12
Markus Schatten 1 1.12
Matti Mantymaki 1 1.12
Mohamed Khalifa 1 1.12
Niels Noorderhaven 1 1.12
Nuno Sousa 1 1.12
Ping Chuan Chen 1 1.12
Qian Qian 1 1.12
Rafael Pimienta-romo 1 1.12
Rendi Hartono 1 1.12
Rene J.Jorna 1 1.12
Reyes Juarez-ramirez 1 1.12
Richard David Evans 1 1.12
Richard Heeks 1 1.12
Riemer kai 1 1.12
Rose Alinda Alias 1 1.12
Sabyasachi 1 1.12
Sarah Cummings 1 1.12
Shih-Wei Chou 1 1.12
Shiu Wan Hung 1 1.12
Steven Chuang 1 1.12
Tzu Fong Liao 1 1.12
Valeria Sadovykh 1 1.12
Viesturs Celmins 1 1.12
Viesturs Celmins 1 1.12
Violeta Ocegueda-miramontes 1 1.12
Volker Wulf 1 1.12
Wu Cheng-Chieh 1 1.12
Xiao Ying Dong 1 1.12
Yan Yu 1 1.12
Yen-Chiang Fang 1 1.12
Yu Fang Yen 1 1.12
Yu-Chieh Chang 1 1.12
Yujin Choi 1 1.12
Yung Ming Li 1 1.12
Zainal Wardah Abidin 1 1.12
Zhang Jie 1 1.12
Total 89

4.6.  Mapping to Theories, Factors, and Paper

The comprehensive review process classifies the factors that are mostly done in knowledge management in social societies. This factor classification mapping is based on the theory, factors, and authors of the articles used in this study. The following results are shown in Table 8

Table 8. Theories, Factors, and Paper

Theory Factor ID Paper
Social Capital Cognitive social capital [15],[16],[17],[18],[19],[20],[21],[22], [23],[24],[25],[26], [27],[28],[29],[8], [30],[31],[32],[33],[34],[35],[36],[37], [38]
Relational social capital
 Structural social capital
Social network-based Markov Chain (SNMC) models Semantic Similarity [39]
Profession, Reliability,
Social intimacy
Popularity,
Enterprise Social Networking Work Discussion [40]
Input Generation
Problem-solving, Social Praise
Idea Generation
Status Updates Informal
Task Management
Talk Event, Notifications
Theory of Planned Behavior (TPB) The intention, Perceived behavior toward [19]
Transactive  Memory System (TMS) Theory Credibility [18]
Specialization
Coordination
SECI model Socialization, Externalization,
Combination, and Internalization
[2]

Social Networks

 

People-related, Process-related, Technical-related, Adaptability/ Agility, Creativity, Institutional memory building, Organizational Internal Effectiveness, Intangibility, Heterogeneity, Perishability [41],[42], [43], [44]

Semantic Social Networks

 

Basic typed Semantic
Social networks and Trust annotated semantic social networks
[45]

Social Interaction

 

Employee motivation (Intrinsic motivation and Extrinsic motivation), Social interaction (Interpersonal trust, Openness in Communication, and Social reciprocity), and Knowledge Management (KM) strategy (Codification Knowledge Strategy and Personalization Knowledge Strategy) [46]

4.7.  Keyword Analysis

Keyword Analysis used in searching papers related to the study of social knowledge Management. The keyword used yields 278 papers from 7 reputable journal database sources. Among the frequently used keywords are ‘Knowledge Management Social Theory’. Article data found on other keywords that occur overlap.

Table 9Most frequently used keywords

Keyword Paper
Emerald IEEE Jstor ACM Science Direct TandF springer
Knowledge Management Social 17 10 4 8 10 15 8
Knowledge Management Social Theory 12 8 10 9 8 12 15
Knowledge ManagementSocial Society 15 15 8 5 12 14 8
Social knowledge Management Theory 16 7 8 3 5 7 9

4.8.  Mapping Theories for Factors to uses in Social Knowledge Management

  • Theory of Planned Behavior (TPB)

Ajzen explains that TRA is an individual’s attitude toward behavior positively influencing intention to participate in that behavior[19]. The main factor of planned behavior theory is the individual’s intention to perform certain behaviors. An intent is assumed to capture the motivating factors that influence the behavior of the individual. This is an indication of how hard it is for people to try, how much effort they plan to do that behavior. As a general rule, the stronger the intention to engage in the behavior, the more likely it is to perform. However, it should be clear that behavioral intentions can only express behavior only if the behavior in question is under complete control [47].

  • Transactive memory system (TMS) theory

The concept of TMS is the specific division of labor processes that relate to taking, storing, and retrieving knowledge from different environments[48]. The TMS process occurs in individual/group transactions that are aware of the need to develop unique knowledge and member expertise so that a group can rely on member knowledge. This TMS consists of three main components (1) specialization shows different members’ knowledge structures, (2) credibility shows members’ beliefs about the accuracy and reliability of other members’ knowledge, (3) coordination shows the effective and orderly storage of knowledge [18].

  • Social capital theory

Social capital is a knowledge resource that comes from social networks that people can use to make a behavior. This is illustrated through the ability to access and exchange the knowledge resources of individuals who are in the social structure. [22],[23],[24],[25], [26][49]. This makes Social capital has been recognized as an important factor for social interaction[15],[16], [17],[18], [19], [20], [21]. Interpersonal networks provide channels for the exchange of tangible and intangible resources needed. Nahapiet & Ghoshal suggest that social capital is a multifaceted concept and can be divided into three dimensions: capital structure, relationship capital, and cognitive capital.

  • SECI model

The process of socialization refers to the transfer of knowledge. The externalization process refers to documenting their knowledge so that it is possible to share it with others [1], [10], [11]. The Combination Process refers to combining knowledge with other knowledge to rearrange new knowledge [2]. Internalization Process. During the process of making new knowledge that everyone can share with each individual through further consultation, training, and assimilating this knowledge [2], [11].

  • Social Networks

Social Network Theory is a theory or study that studies how people, organizations, or groups interact with others in the network that exists in them[50], [51].In understanding this theory, it is easier when you examine individual pieces that start with the most significant element, i.e., the network, and work up to the smallest element, i.e., the actor[19]. Social networks are social structures that have a set of social actors (such as individuals or organizations), a collection of ties, and other social interactions between actors [52]. The view of the social network provides a set of methods used to analyze the structure of the entire social entity as well as theories that explain the patterns observed in this structure [45].

5. Conclusions

Results obtained from the discussions that have been described. Described the knowledge management occurs within the social environment can be seen from the development of research conducted with several theories. Social capital theory[15][16][17] shows that 3 very strong factors can influence social relationships that occur in individuals within the social community is structural capital, cognitive capital, and relationship capital, in addition to this Theory of Planned Behavior (TPB)  illustrates that the main factor for determining the intention of individuals to perform certain behaviors is the attitude of individuals to behave positively [19] [47]. it also affects knowledge management.

After that, individual transactions described in the Transactive memory system (TMS) theory [48] have major components: specialization, credibility, coordination, so that teams can develop a shared awareness of each member’s unique knowledge and expertise[18].

Maintain relationships and transactions that occur requires a good social network. Social network theory explains by increasing interpersonal trust, informal communication, and reciprocal relationships, People-related, Process-related, Technical-related, Adaptability/agility, Creativity, Institutional memory building, Organizational internal effectiveness, Intangibility, Heterogeneity, Perishability, in turn, increasing KM maturity. The theory of social interaction affects the improvement of social networking relations. Factors are employee motivation (intrinsic motivation and extrinsic motivation), social interaction (interpersonal trust, openness in communication, and social reciprocity), and knowledge management (KM) strategy (codification knowledge strategy and personalization knowledge strategy). From the results obtained, this study illustrates these factors that affect KM in social society.

6. Implication

Based on the findings of structural capital, cognitive capital, and relationship capital on social capital theory, it becomes an essential factor to be seen in KM in social society. Thus KM can well by looking at the individual social interactions that occur. By calculating or reviewing the interaction. The implications are given in science is that social knowledge management requires developed social media today that can facilitate interactions that occur within a social community.

7. Limitation and Future research

This study has a limited database used; this is due to limited access. The number of articles to be added is mainly extracted from credible and published databases in the last five years.  Future research, researchers will perform statistical analysis of these factors on the social community to determine the influence of these factors. so, it can be seen with concrete factors that influence in KM

  1. I. Nonaka, “The knowledge-creating company,” Harv. Bus. Rev., no. December 1991, 1991.
  2.  N. Sousa, C. J. Costa, and M. Aparicio, “IO-SECI: A Conceptual Model for Knowledge Management,” in Proceeding OSDOC ’13 Proceedings of the Workshop on Open Source and Design of Communication, 2013, pp. 9–17.
  3. N. Houari and B. H. Far, “Application of intelligent agent technology for knowledge management integration,” Proc. Third IEEE Int. Conf. Cogn. Informatics, 2004., pp. 240–249, 2004.
  4. M. Asrar-ul-Haq and S. Anwar, “A systematic review of knowledge management and knowledge sharing: Trends, issues, and challenges,” Cogent Bus. Manag., vol. 3, no. 1, pp. 1–17, 2016.
  5. M. Alavi and D. E. Leidner, “Knowledge Management and Knowledge Systems: Conceptual Foundations and Research Issue,” MIS Q., vol. 25, no. 1, pp. 107–136, 2001.
  6. M. Huysman and V. Wulf, “IT to support knowledge sharing in communities, towards a social capital analysis,” J. Inf. Technol., vol. 21, no. 1, pp. 40–51, 2006.
  7. S. G. López, J. L. S. Benítez, and J. M. A. Sánchez, “Social Knowledge Management from the Social Responsibility of the University for the Promotion of Sustainable Development,” Procedia – Soc. Behav. Sci., vol. 191, pp. 2112–2116, 2015.
  8. Y. Choi, “The Impact of Social Capital on Employees’ Knowledge-Sharing Behavior: An Empirical Analysis of U.S. Federal Agencies,” Public Perform. Manag. Rev., vol. 39, no. 2, pp. 381–405, 2016.
  9. H. Prabowo, “Information Science and Applications 2017,” Inf. Sci. Appl., vol. 424, 2017.
  10. I. Nonaka and H. Takeuchi, “A theory of organizational knowledge creation lkujiro Nonaka and Hirotaka Takeuchi Katsu hiro Umemoto,” IJTM, Spec. Publ. Unlearning Learn., vol. 11, no. 7/8, pp. 833–845, 1996.
  11.  I. Nonaka, R. Toyama, and N. Konno, “SECI, Ba and Leadership: A Unified Model of Dynamic Knowledge Creation,” Long Range Plann., vol. 33, no. 1, pp. 5–34, 2000.
  12.  R. James, “Postcolonial Development and Sustainability,” pp. 1–14, 2012.
  13. S. Rivas-Gomez et al., “MPI windows on storage for HPC applications,” in Proceedings of the 24th European MPI Users’ Group Meeting on – EuroMPI ’17, 2017, pp. 1–11.
  14. B. Kitchenham, O. P. Brereton, D. Budgen, M. Turner, J. Bailey, and S. Linkman, “Systematic literature reviews in software engineering – A systematic literature review,” Inf. Softw. Technol., vol. 51, no. 1, pp. 7–15, 2009.
  15. W. He, Q. Qiao, and K.-K. Wei, “Social relationship and its role in knowledge management systems usage,” Inf. Manag., vol. 46, no. 3, pp. 175–180, Apr. 2009.
  16. Y. Yu, J.-X. Hao, X.-Y. Dong, and M. Khalifa, “A multilevel model for effects of social capital and knowledge sharing in knowledge-intensive work teams,” Int. J. Inf. Manage., vol. 33, no. 5, pp. 780–790, Oct. 2013.
  17.  J. Pattnayak and S. Pattnaik, “Integration of Web Services with E-Learning for Knowledge Society,” Procedia Comput. Sci., vol. 92, pp. 155–160, 2016.
  18. B. Li and G. Qu, “Relationship between team social capital and knowledge transfer: The mediated effect of TMS,” 2010 Int. Conf. E-Product E-Service E-Entertainment, ICEEE2010, pp. 1–4, 2010.
  19.  S.-W. Chou and Y.-C. Chang, “An Empirical Investigation of Knowledge Creation in Electronic Networks of Practice: Social Capital and Theory of Planned Behavior (TPB),” Proc. 41st Annu. Hawaii Int. Conf. Syst. Sci. (HICSS 2008), pp. 340–340, 2008.
  20.  G. Sechi, D. Borri, C. De Lucia, and V. Celmins, “Social capital as knowledge facilitator: Evidence from Latvia,” Knowl. Manag. Res. Pract., vol. 9, no. 3, pp. 245–255, 2011.
  21. H. P. Zhang, X. G. Wei, and K. Kang, “A Study of the Effects of Social Capital on Inter-Firm Knowledge Transfer and Innovation Performance,” Proc. 2010 Int. Conf. Inf. Technol. Sci. Manag. Vols 1-2, no. 2006, pp. 819–823, 2010.
  22.  Yi-Wen Fan and Cheng-Chieh Wu, “The Role of Social Capital in Knowledge Sharing: A Meta-Analytic Review,” in 2011 44th Hawaii International Conference on System Sciences, 2011, pp. 1–10.
  23.  S. P.-M. Law and M.-K. Chang, “Social Capital and Knowledge Sharing in Online Communities: A Mediation Model,” 2012 45th Hawaii Int. Conf. Syst. Sci., pp. 3530–3539, 2012.
  24.  Wang Li and Han Jingjing, “The relationship study of social capital, knowledge management and performance in logistics enterprises based on SEM,” in 2014 IEEE Workshop on Advanced Research and Technology in Industry Applications (WARTIA), 2014, no. 1998, pp. 1249–1251.
  25.  C. Choi and C. C. J. M. Milla, “Networks ,Social Norms and Knowledge Sub-Network,” J. Bus. Ethics, vol. 90, no. 2009, pp. 565–574, 2014.
  26.  M. A. McFayden and A. A. Cannella, “Social capital and knowledge creation: Diminshing returns of the number and strenght of exchange,” Acad. Manag. J., vol. 47, no. 5, pp. 735–746, 2004.
  27.  S. Cummings, R. Heeks, and M. Huysman, “Knowledge and learning in online networks in development: A social-capital perspective,” Dev. Pract., vol. 16, no. 6, pp. 570–586, 2006.
  28. S. W. Hung, P. C. Chen, and C. F. Chung, “Gaining or losing? The social capital perspective on supply chain members’ knowledge sharing of green practices,” Technol. Anal. Strateg. Manag., vol. 26, no. 2, pp. 189–206, 2014.
  29.  J. Nieves and J. Osorio, “The role of social networks in knowledge creation,” Knowl. Manag. Res. Pract., vol. 11, no. 1, pp. 62–77, 2013.
  30. Y. F. Yen, J. F. Tseng, and H. K. Wang, “The effect of internal social capital on knowledge sharing,” Knowl. Manag. Res. Pract., vol. 13, no. 2, pp. 214–224, 2015.
  31.  A. Göksel and B. Aydıntan,“How can tacit knowledge be shared more in organizations? A multidimensional approach to the role of social capital and locus of control,” Knowl. Manag. Res. Pract., vol. 15, no. 1, pp. 34–44, 2017.
  32. A. Edwards, “What is ‘Knowledge’ in Social Care?,” Housing, Care Support, vol. 4, no. 4, pp. 2–3, Nov. 2001.
  33.  L. Grayson, A. Boaz, and A. Long, “Organising Social Care Knowledge: In Search of a ‘Fit for Purpose’ Classification,” J. Integr. Care, vol. 12, no. 1, pp. 42–48, Feb. 2004.
  34. M. W. McElroy, R. J. Jorna, and J. van Engelen, “Rethinking social capital theory: a knowledge management perspective,” J. Knowl. Manag., vol. 10, no. 5, pp. 124–136, Sep. 2006.
  35.  W. Z. Abidin, L. Uden, and R. A. Alias, “Knowledge Management in Organizations,” vol. 224, pp. 754–769, 2015.
  36. J. Hui and C. Yijia, “The research on how social capital facilitates knowledge sharing between individuals,” Adv. Intell. Soft Comput., vol. 110, pp. 261–270, 2011.
  37. R. V. Vallejos, J. MacKe, and K. Faccin, “Establishing Knowledge Management as an important factor to develop Social Capital for collaborative networks,” IFIP Adv. Inf. Commun. Technol., vol. 362 AICT, pp. 58–65, 2011.
  38.  G. Widen, “Social capital and knowledge sharing: Lessons learned,” Adapt. Value Creat. Collab. Networks 12th IFIP WG 5.5 Work. Conf. Virtual Enterp. PRO-VE 2011, vol. 362, pp. 48–57, 2011.
  39.  Y. M. Li, T. F. Liao, and C. Y. Lai, “A social recommender mechanism for improving knowledge sharing in online forums,” Inf. Process. Manag., vol. 48, no. 5, pp. 978–994, 2012.
  40.  M. Mäntymäki and K. Riemer, “Enterprise social networking: A knowledge management perspective,” Int. J. Inf. Manage., vol. 36, no. 6, pp. 1042–1052, 2016.
  41. R. Juárez-ramírez, R. Pimienta-romo, and V. Ocegueda-miramontes, “Using Social Networks for Integrating a Tacit Knowledge Repository to Support,” Int. Symp. Iuk. 2013, pp. 167–179, 2013.
  42.  J. Liebowitz, “The Hidden Power of Social Networks and Knowledge Sharing in Healthcare,” Healthc. Knowl. Manag. SE – 8, pp. 104–111, 2007.
  43.  V. Sadovykh and D. Sundaram, “Context-Aware Systems and Applications,” vol. 193, pp. 22–31, 2017.
  44. J. Lewis-Pryde and R. D. Evans, “A Social Networking Strategy for Improving Knowledge Management and Communication in the Travel Industry,” Proc. 3rd Multidiscip. Int. Soc. Networks Conf. Soc. 2016, Data Sci. 2016 – MISNC, SI, DS 2016, pp. 1–5, 2016.
  45.  M. Schatten, “Knowledge management in semantic social networks,” Comput. Math. Organ. Theory, vol. 19, no. 4, pp. 538–568, 2013.
  46.  H.-F. Lin, “The effects of employee motivation, social interaction, and knowledge management strategy on KM implementation level,” Knowl. Manag. Res. Pract., vol. 9, no. 3, pp. 263–275, 2011.
  47.  I. Ajzen, “The theory of planned behavior,” Orgnizational Behav. Hum. Decis. Process., vol. 50, pp. 179–211, 1991.
  48.  D. M. Wegner, “Summary for Policymakers,” in Climate Change 2013 – The Physical Science Basis, vol. 13, no. 3, Intergovernmental Panel on Climate Change, Ed. Cambridge: Cambridge University Press, 1995, pp. 1–30.
  49.  J. Nahapiet and S. Ghoshal, “Social Capital, Intellectual Capital, and the Organizational Advantage,” Acad. Manag. Rev., vol. 23, no. 2, p. 242, Apr. 1998.
  50.  W. Liu, A. Sidhu, A. M. Beacom, and T. W. Valente, “Social Network Theory,” Int. Encycl. Media Eff., no. September, pp. 1–12, 2017.
  51.  K. S. K. Chung and L. Crawford, “The Role of Social Networks Theory and Methodology for Project Stakeholder Management,” Procedia – Soc. Behav. Sci., vol. 226, no. October 2015, pp. 372–380, 2016.
  52.  R. A. Costa, R. Y. Oliveira, E. M. Silva, and S. R. Meira, “A.M.I.G.O.S: Knowledge Management and Social Networks,” Spec. Interes. Gr. Des. Commun. 2008, pp. 235–242, 2008.

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