MAPPING KNOWLEDGE MANAGEMENT RESEARCH: A BIBLIOMETRIC OVERVIEW

. In recent years, knowledge management (KM) has consistently attained considerably growing research attention. Consequently, several literature reviews have been performed addressing different topic areas of KM. This paper seeks to present a comprehensive bibliometric and network analysis on KM to understand its development from the perspective of academic communities. Subsequently, it seeks to identify the structure of associations between prior and current themes, predict emerging trends and offer a longitudinal perspective on KM research. This study used web of science database and the initial sample was trimmed down by considering only the articles contributing to KM literature, and further 8,721 KM papers published in the last 30 years were systematically evaluated. The descriptive statistics and science mapping methods employing co-citation analysis were performed with VOSviewer software. In the descriptive analysis, we have analysed publication trends over time, geographical localization of the contributing institutions, journals, most prolific authors, top-performing institutions and most cited articles. Science mapping analysis is based on co-word analysis and co-citations analysis, namely articles’ co-citations and authors’ co-citations. The main findings of this paper will help researchers and academicians to develop knowledge in a specific sub-field by analysing the research outcomes of the papers included in the body of literature.


Introduction
Over the past 20 years, research on knowledge management (KM) has witnessed considerable attention throughout the world and is well at the end of its third decade of investigation. The KM is becoming a strategic factor for all industries to survive in today's dynamic global business competition Kaklauskas & Kanapeckiene, 2005).
The concept of knowledge has been analysed in literature from different perspectives concerning what is knowledge (Lin & Ha, 2015), where it is embedded (Buenstorf & Costa, 2018;Lönnqvist, 2017;Miklosik et al., 2019), and how it can be classified (Polanyi, 1958;Nonaka, 1994;Holsapple, 2005). Starting from these conceptualizations, the interesting recent trends have been appeared such as impact of knowledge risk management on performance (Durst et al., 2019), market knowledge sourcing determinants (Endres et al., 2020), heterogeneous knowledge ties (Maghssudipour et al., 2020), role of international joint venture in managing and exploiting knowledge (Zhang et al., 2018), KM and green innovation (Abbas & Sağsan, 2019). These trends have given unique conceptualization in the KM domain dealing with efficient and effective KM processes, as well as systematic strategies pertaining to knowledge creation, processing, sharing, and execution (Raudeliūnienė et al., 2018).
Besides, in the past, a number of reviews on the topic of KM have been published in recent years. Few of them have investigated the KM in specific subject areas , while others have shed light on several aspects: major trends and challenges in KM (Asrar & Anwar, 2016), key KM approaches (Alexandru et al., 2019), processes for exploration and exploitation of knowledge (Centobelli et al., 2019), KM in strategic alliance (Tsai, 2016), KM and firm performance (Inkinen, 2016;Sulistio & Dianawati, 2020), corporate culture and KM (Buckova, 2017), KM and sustainability (López-Torres et al., 2019), KM in SMEs and startups (Castagna et al., 2020) and KM performance measurement (Asiaei & Bontis, 2019;Cardoni et al., 2020). These reviews have identified few research areas and research questions in the literature to be analysed for further research.
Despite the growing interest in KM and the number of review papers already published, there is a scarcity of contributions analysing how the whole KM academic research has evolved over the time. Thus, the aim of this paper is to answer the following research questions: 1) what are the key topics covered widely in literature? 2) which papers contributed more to the KM field? 3) what is co-words structure in the literature? 4) what is the social structure based on the authors' co-authorship? and 5) what is the co-citation based structure of articles and authors?
The remain of the paper is organised as follows: Section 1 presents the research methodology used in this paper. Section 2 and Section 3 discuss the results of the performance analysis and science mapping, respectively. Finally, we draw our conclusions and future research directions in Section 5.

Research methodology
In this paper, we employed the WoS database a digital platform globally acknowledged among scholars for its quality standards (Mulet-Forteza et al., 2019) that makes it one of the most used tools for searching and analysing both publications and journals among other databases like Scopus. Many researchers dealing with bibliometric analysis papers adopt WoS since it allows downloading properly all the relevant bibliometric information needed for this approach and performs much better than other databases in the accuracy (Wang & Waltman, 2016). Furthermore, researchers emphasized that deploying multiple different databases arise the issue of data homogenization which negatively impacts results (Mariani & Borghi, 2019). We further intend to perform co-citation analysis considering the cited references inside the same papers collected from WoS. This approach enables to recognize the additional pertinent literature, even from other databases, that may be overlooked during standard approaches of literature search (Trujillo & Long, 2018).
The following keywords were used during December 2019 to retrieve the papers: ("knowledge manag*" OR "knowledge creat*" OR "knowledge stor*" OR "knowledge shar*" OR "knowledge transf*" OR "knowledge appl*" OR "knowledge diffus*" OR "knowledge acqui*" OR "knowledge integrat*" OR "knowledge utili*" OR "knowledge us*" OR "knowledge combinat*" OR "knowledge assimilat*" OR "knowledge adopt*" OR "knowledge exploit*" OR "knowledge explor*"). The use of these keywords makes it possible to select papers dealing with the main knowledge management processes analysed in the body of literature (i.e., knowledge acquisition, knowledge creation, knowledge storage, knowledge sharing, knowledge transfer, knowledge diffusion, knowledge application, knowledge integration, knowledge utilization, knowledge use, knowledge combination, knowledge assimilation, knowledge adoption, knowledge exploitation, and knowledge exploration). We only considered papers published in English language and restricted the literature search between the time period of 1990 and 2019. Further, we excluded the conference proceedings, editorial notes, book chapters, book reviews, and extended abstracts. Subsequently, we trimmed down the initial sample by eliminating the irrelevant articles which do not significantly contribute to KM literature. A validation criterion regards the integration of contributions that were not found through the research string and/or comprised in the selected academic database but were cited in the literature on KM. Therefore, this criterion validates the choice of the search string and academic database. Finally, 8,721 papers were retrieved which include reviews and full papers written in English language and published until 2019. Finally, sample papers were analysed using two bibliometric procedures: performance analysis and science mapping. Figure 1 shows that research on KM increases over the years. Despite the growth between 1990 and 1999 was very slow, the scientific literature on KM in peer-reviewed journals increased significantly after 1999. It passed from 619 articles published until 1999 to 4,422 articles published between 2000 and 2014. More recently the growth was even more significant with 3,680 papers published only in the last five years. This aspect confirms that the research on KM has attained growing research attention in recent times.

Performance analysis results
The statistics confirm that 2,353 journals have contributed total of 8,721 articles published on KM. For the journal ranking, in case of equal publications by two or more journals, the number of citations is considered for ranking. Table 1 show that the 25 most contributing journals have published a total of 1,930 articles representing about 22.13% of all identified articles. Therefore, the contribution of the remaining 2,328 journals is about 77.87%. Notably, "Journal of Knowledge Management" emerges as the journal with the highest number of published articles on KM (409), followed by "Knowledge Management Research & Practice" and "Expert Systems with Applications" with 190 and 154 articles published, respectively.
The analysis of journals with highest number of citations reveals that the top 25 journals are cited 107,696 times. "Journal of Knowledge Management" is also the journal with the highest number of citations received (9,667). "Strategic Management Journal" and "MIS Quarterly" journals are not in the list of top 25 contributing journals, but they appear in the second and third place in the top 25 journals rank considering the number of citations received with 9,418 and 7,581 citations received, respectively (Table 1). These two journals represent the 24.76% of the total citations of the 25 most contributing journals. Similarly, "Knowledge Management Research & Practice" is the second top contributing journal but not appeared in the top 25 list of most cited journals. If we compare the average citations per paper of "Strategic Management Journal" and "MIS Quarterly" with "Journal of Knowledge Management" and "Expert System with Applications" which are two leading journals (also appeared in the top-cited journal list) based on the number of papers published over the time, a large difference will be found. Table 2 reports journals' metrics for the top 25 contributing journals. These journals cover eight subject areas. According to Buckley and Carter (1999), KM is a crossroad research topic focusing on different subjects even if, in line with the nature of the KM topic, "Business, Management and Accounting" and "Computer Science" emerged as the subject areas most frequently encountered. Therefore, indeed, Table 2 reports publications belonging to different subject areas, a wide range of journals, published in different countries under different publishers. For that reason, Neves and Da Silva (2016) suggest categorizing papers by the journal to support both researchers and practitioners in identifying who publish such topics in a particular domain. Among 25 journals, nine journals belong to "Elsevier", four to "Emerald", two to "Springer", two to "Taylor & Francis". Remaining seven journals belong to "Inderscience", "World Scientific", "Association of Professional Managers in South Africa", "Sage", "MDPI" "Wiley", "Technische", "Technischen", and "Idea Group", respectively. Meanwhile, eleven journals belong to the "United Kingdom", six to "Netherlands", four to "United States", one to "Germany", one to "South Africa", one to "Switzerland", and one to "Austria".   (206, and 162, respectively). Besides, the "Research Policy" and "Information & Management" emerged as leading SJR scorers with 3.41 and 1.72, respectively. "Research Policy" and "Knowledge-Based Systems" appeared as high impact factor journals with 5.42 and 5.10 impact factor values, respectively (Table 2).

Author influence
The results show that there are 19,175 authors publishing 8,721 papers on KM. Table 3 reports the 20 most prolific authors (in terms of number of articles published), the number of citations received, the number of papers they published, their H-index and affiliation. Results show that Akhavan Peyman from Malek Ashtar University of Technology, Tehran (Iran) is the most prolific author and published 16 articles followed by Kianto Aino from Lappeenrannan Teknillinen Yliopisto, Lappeenranta (Finland) with 14 articles. In the third place among the top contributing authors, Georg Von Krogh from the ETH Zürich University (Switzerland) is also the dominant cited author with 1,486 citations and the highest average citations per article (123.83). Figure 2 indicates the origin of the institutions who contributed most in the advancement of the KM research. Notably, in case of equal number of articles by two or more countries, the number of citations is considered for ranking. It can be concluded that United States, United Kingdom and China based institutions are the major contributors. Most importantly, Asian institutions' contribution is quite less, only few Northeast Asian countries (China, Taiwan, and South Korea) have significantly contributed to the KM research. In detail, considering the top 5 contributing countries, United States of America published in total 1,832 articles, United Kingdom 992, China 866, Taiwan 619, and Canada 447 articles. Besides, African countries have not published (e.g., Chad, Congo, and Eritrea) or published less than 10 papers (e.g., Botswana, Cameroon, Gabon, Namibia, Somalia, Sudan, and Zimbabwe). The limited use of information and communication technology, as well as the digital divide between the different countries, may be a reason behind such difference of contribution between African, American, and European countries. Table 4 reports the organization's ranking based on the number of citations received by articles divided by the number of articles published. The University of Illinois published 39 articles and these articles have been cited 3,155 times, and thus obtained the highest value of citations per article (80.89), followed by the National University of Singapore who published 46 articles cited 2,817 times (61.23 average citations per article). This implies that these universities are the most impact-full universities in the KM filed. Among the 25 top institutions (in terms of average citations per paper), six are from Taiwan, three from Canada and UK, two from Singapore, Hong Kong, Malaysia, China and Iran and one from South Korea and United States. This distribution is almost in line with the distribution of the most prolific authors (Table 3).

Citation analysis
The citations received by a paper indicates its impact and serves as quality indicator. Therefore, the highly cited papers demonstrate the greater contribution towards literature than less cited papers (Jiang et al., 2014). Citation analysis plays a crucial role in three main areas: 1) in investigating the relativeness of papers, institutions, and countries; 2) in serving as a metric of journal ranking; and 3) in exploring the intellectual formation of the domain. Table 5 reports the 25 papers with highest number of citations in WoS. "A dynamic theory of organizational knowledge creation" published in 1994 by Ikujiro Nonaka appeared as the most cited paper. This has been cited 6,453 times since 1994 (until 2019), and also has highest citations per year (258.12). "Knowledge management and knowledge management system: conceptual foundation and research issues" published in 2001 by Alavi M. and Leidner D. E. is the second most cited paper with 3,500 citations since 1996, and also has the second highest per year citations (194.44). Hence, these papers have given significant contributions to theory development in KM field. The total number of citations received by each country indicates the impact of each country in the research domain. In Table 6 we summarize the top twenty cited countries. The United States of America emerges as the most cited country with 94,679 citations, followed by United Kingdom with 24,876 citations. As discussed in section 3.2, these two countries are also the highest contributors in terms of number of papers published.

Science mapping
Science mapping is an approach based on the use of techniques aimed to build bibliometric maps that describe how specific disciplines and scientific domains are conceptually and intellectually related. Among the most commonly used techniques there are co-citation analysis and the keywords' co-occurrence. We used VOSviewer software to conduct network analyses for the following reasons: (1) it is an easy-to-use tool, (2) it allows to visualize large networks and present clearly the results, (3) it incorporates three types of visualizations: network visualization, overlay visualization, and density visualization, (4) it offers distance-based visualization in which the nodes' distance infers their relatedness (van Eck & Waltman, 2014), and (5) it helps in visualizing the outputs through various bibliometric metrics (Merigó et al., 2018).

Co-word analysis
Co-word analysis is a content analysis method that captures scientific maps of a field using the document's keywords. This aims to identify words with high frequencies to extract the concept and co-occurrence relationship behind. We identified 19,489 unique keywords. With such large number, it is difficult to get a clear map of the most important keywords. According to Chai and Xiao (2012), only the most frequent keywords offer a deep understanding of key topics, and therefore, keywords should be limited. Thus, we use a threshold of at least 5 as a minimum co-occurrence frequency. As a result, 1,796 unique keywords meet this threshold and were used for the analysis. Figure 3 represents a density view map of keywords. Three main colours can be easily figured out: green, yellow and warm red. Green reflects lower density keywords, yellow reflects medium density keywords, and warmer red reflects the highest density keywords representing the hot themes. As the distance increases from the centre of gravity, the colour automatically changes, demonstrating that they are far from hot themes and the integrated clusters will be changed to non-integrated ones. Results of the analysis reveal four well-separated subfields in KM research: "knowledge management" (middle left), "performance" (middle right), "innovation" (lower middle) and "knowledge sharing" (upper middle) ( Figure 3). Meanwhile, "knowledge management", "performance", "innovation", "knowledge sharing", "management", "knowledge transfer", "model", "firm" and "impact", and "absorptive-capacity" emerge as main keywords with 2,032, 1,465, 1,244, 1,109, 1,085, 760, 719, 582, 581, and 553 occurrence frequency, respectively.

Co-citation analysis
Co-citation analysis was introduced by Small (1973) and, since then, it has gained great popularity in the bibliometric research. This evaluates the degree of correlation between papers or authors. Papers/authors are co-cited if they appear together in the reference list of other papers. Most often co-cited papers/authors represent similar research topics/interests that were mostly discussed in the literature.
The last cluster includes blue nodes and has been named as "Barriers, motivations, and stages of knowledge sharing". Meanwhile, Cluster 1 (red cluster) includes papers related to knowledge sharing and knowledge sharing networks. Szulanski (2000) proposed a model that discusses the knowledge transfer stages and difficulties that firms face at different stages of the knowledge transfer process. Yli-renko et al. (2001) confirmed the mediating role of knowledge acquisition between social capital and the exploitation of knowledge. Hansen (2002) introduced the knowledge networks concept to explain effective knowledge sharing in multiunit companies. Powell et al. (1996) defined inter-organizational collaboration as a network of learning. Gupta and Govindarajan (2000b) analyzed the process of knowledge transfer, whereas Inkpen and Tsang (2005) evaluated how networks' social capital dimensions impact knowledge transfer. Likewise, Levin and Cross (2004) proposed and tested a framework for knowledge transfer. Lane and Lubatkin (1998) studied the role of a partner's knowledge and research networks in the inter-organizational learning context, whereas Mowery et al. (1996) emphasized on the inter-firm knowledge sharing among strategic business partners. Nevertheless, the way how knowledge is shared depends upon the competence of the multinational organizations in transferring knowledge to other firms (Kogut & Zander, 1993), and the positive effect of interaction between absorptive capacity and network position on a firm's performance has utmost importance (Tsai, 2001). In the same vein, network range and the strength of network ties impact the knowledge transfer process . Furthermore, few researchers emphasized that firms should extend their dynamic learning capability beyond their knowledge creation networks to attain unique competitive edge (Dyer & Nobeoka, 2000). On the other hand, research also claimed that not all business partners are equally important for knowledge creation and transfer (Hamel, 1991). Also, the firms need to put more effort into identifying knowledge than in understanding how to create, retain and share knowledge (Argote et al., 2003). Kogut and Zander (1992) provided an overview of the relationship between the firm's knowledge, combinative capabilities, and the replication of technology.
Cluster 2 (green cluster) includes papers dealing with knowledge creation, organizational capabilities, innovation, and KM. Researchers have further established the relationships between different factors of KM (Lee & Choi, 2003). Nonaka (1994) emphasized that organizational knowledge creation is a wide-spread and dynamic concept whose effectiveness depends upon the balance between explicit and tacit knowledge. Meanwhile, few researchers reported explicit, tacit, individual and group knowledge as four sources of organizational knowledge creation (Cook & Brown, 1999;Brown & Duguid, 2001). Other researchers claimed organization culture and identity, routines, policies and systems, documents, and employees (Grant, 1996) cognitive and behavioral dimensions as multiple ways of knowledge creation (Huber, 1991). Similarly, a knowledge creation model is proposed including three components: SECI process, Ba (the shared context for knowledge creation), and knowledge assets (Nonaka et al., 2000). The organizations can obtain and share knowledge considering other means, comprising, declarative, causal, relational, and conditional (Zack, 1999). A disproportionate emphasis either on exploitation or exploration can hamper the business performance (March, 1991). Besides, Nonaka (1991) discussed the notion of "tacit" knowledge as well as valuable and subjective information that are difficult to create and share. Davenport and Prusak (1998) underlined the cultural and behavioral concerns and effective ways to incorporate information technology for KM. Evidence is also available that supports a positive link between information technology and organizational KM (Alavi & Leidner, 2001). Gold et al. (2001) reported the perspectives of effective KM under organizational capabilities. The literature further supported the relationships between work, learning, and innovation (Brown & Duguid, 1991), and established the association between different factors of KM (Lee & Choi, 2003).
Cluster 3 (blue cluster) includes paper dealing with barriers, motivations, and stages of knowledge sharing. Osterloh and Frey (2000) and Lin (2007a) explained the effect of different types of extrinsic and intrinsic motivations related to explicit and tacit knowledge sharing intentions. Similarly, extrinsic motivators, social-psychological drivers and organizational climate influence individuals' knowledge sharing intentions (Bock et al., 2005). However, the employees share their knowledge in the case when they consider that it will enhance their professional goodwill (Wasko & Faraj, 2005) as individual and organizational factors signifi-cantly affect the willingness of the employees to collect and share knowledge and fosters the innovative capacity of firms (Lin, 2007b). On the other hand, Hsu et al. (2007) proposed a social cognitive theory-based framework that comprises knowledge exchange self-efficacy and outcome. Meanwhile, the research concluded that external knowledge sharing is more strongly related to performance in the case where workgroups are more structurally diverse (Cummings, 2004). Van den Hooff and van Weenen (2004) emphasized that to differentiate the different knowledge exchange processes, the levels of commitment and knowledge exchange, and modes of computer-mediated communication have immense importance to explain the relationship between commitment, knowledge exchange, and computer-mediated communication use. However, resource availability impacts electronic knowledge repositories usage for knowledge search mainly during the low task tacitness is low (Kankanhalli et al., 2005). Ipe (2003) highlighted the interconnection between the type of knowledge, sharing intention, sharing opportunities, and the work culture.

Co-citation analysis of authors
As co-citations of authors are concerned, there were a total of 121,322 different authors cited within the sample articles. We considered the threshold of 250 citations received by an author and only 75 met this condition (Table 8). This analysis reveals that "Nonaka and Grant" are two highly co-cited authors in the KM literature, which are further followed by "Nonaka and Davenport"; "Nonaka and Polanyi" and "Grant and Alavi". Figure 5 reports the authors' co-citation network. The analysis classified 75 researchers into 3 clusters: cluster 1 (red nodes), cluster 2 (green nodes), and cluster 3 (blue nodes). Meanwhile, the thickness of the link indicates the strength of co-citations ties.
Cluster 1 comprises researchers focusing on strategic alliances, organizational capabilities, and knowledge transfer. In this context, Robert M. Grant evaluates the coordination systems by which organizations integrate their employees' knowledge. Walter W. Powell's expertise is in inter-organizational collaborations to access and manage knowledge. Anil K. Gupta explores knowledge outflows from a subsidiary and knowledge inflows into a subsidiary and their related associations. David J. Teece analyses development of dynamic capabilities for knowledge management. Udo Zander's expertise concerns the transfer and imitation of the firm's capabilities. Linda Argote's expertise is in knowledge transfer and its mechanisms across organizations. Further, Cross Rob's expertise is in enhancing employees' capability to create and exchange knowledge in social networks. Bernard L. Simonin and David C. Mowery investigate the strategic process of knowledge transfer within strategic alliances. Ranjay Gulati focuses on social structure and strategic alliance formulation among patterns. Other researchers investigate inter-partner learning within a strategic alliance (Bruce Kogut; Gary Hamel and Andrew C. Inkpen; Peter J. Lane; Shaker A. Zahra). In addition, James G. March analyses mutual learning and knowledge sharing between members. Richard R. Nelson analyse the relationship between mutual trust, shared knowledge and information system performance.
Cluster 2 includes researchers specialized in knowledge creation and management practices. Spender John Christopher explores knowledge management processes inside and outside the organizational boundaries. Herbert A. Simon investigates the processes of acquisition Cluster 3 involves researchers investigating the factors affecting knowledge transfer and organizational performance. In this line, Chung-Jen Chen investigates the impact of human capital, organizational capital, relational capital, and knowledge sharing. Sirkka L. Jarvenpaa focuses on reporting the impact of organizational information ownership, propensity to share information, task interdependence, computer comfort, and characteristics related to computer-based information to use collaborative electronic media for knowledge creation and sharing. Meanwhile, Alexandre Ardichvili explores the role of online learning, KM and knowledge sharing in virtual communities. Cabrera Ángel studies knowledge-sharing dilemmas and determinants of individual engagement in knowledge sharing. Li-Fen Liao illustrates the influence of managers' social power and mutual trust on employees' knowledge-sharing behaviour. In this cluster, other researchers depict the impact of rewards systems, leadership (Srivastava Abhishek), and behavioural intention on knowledge sharing (Gee-Woo Bock). On the other hand, Atreyi Kankanhalli highlights the factors affecting electronic knowledge repositories usage for knowledge seeking. Further, Nicolai J. Foss illustrates the role of internal knowledge, network knowledge, and cluster knowledge on knowledge transfer, and Andrew H. Gold examines the impact of knowledge infrastructure capability and knowledge process capability on organizational performance. Jenny Darroch developed measures of KM behaviours, and implementation of the same to foster innovation and organizational performance.

Discussion, implications and conclusions
This paper conducts a bibliometric overview of KM literature using the WoS database. The paper also visualizes the bibliometric networks for citations, keywords, and co-authorship patterns. There have been a good number of papers published in the KM domain over the years, many of them in the last decade. However, despite few good studies on KM have been reported in the last few years, a detailed bibliometric and network analysis to systematically and objectively recognize principal contributions, authors and growing research clusters have not been performed yet. This paper contributes to the body of knowledge by providing a comprehensive overview of KM literature in this way.
From the analysis, it can be concluded that research on KM has attained increasing attention and emerges as a popular research field. Totally 8,721 papers on KM were collected and analysed using bibliometric and network analysis. The papers over the time indicate that 6,413 papers published between 2008 and 2019 represent 73.53% of total identified papers. Meanwhile, all the most cited articles are published before 2010. This is not surprising as the field started growing. The research works published in the last 5-6 years have not had the opportunity to receive as much pull as citations have yet to accumulate.
As journals' contribution is concerned, 2,353 journals have contributed to a total of 8, The United States and United Kingdom are the most productive continents. Besides, the contribution of South Africa and Asian is quite less. The University of Illinois and National University of Singaporetook the leading position of organizations in average citations per article. Analysis proved an important approach to highlight hotspot research areas. The results confirm four hotspots, namely, knowledge management, performance, innovation, and knowledge sharing.
This study gives a noteworthy contribution to the body-of-knowledge on KM while broadening prior reviews (Kuah & Wong, 2011;Asrar & Anwar, 2016;Cerchione et al., 2020) in different ways. First, the present study applies bibliometric and network approaches to uncover the most influential articles, scholars, institutions, and countries as per the number of articles published and citations. Second, it proposes three clusters of co-cited articles namely knowledge sharing and knowledge sharing networks, knowledge creation, organizational capabilities, innovation and KM, and barriers, motivations and stages of knowledge sharing. Third, it proposed three clusters of co-cited authors such as strategic alliance, organizational capabilities and knowledge transfer, knowledge creation and management practices, and factors affecting knowledge transfer and organizational performance. Fourth, the study supports researchers to underline the most influential articles. Fifth, the findings can assist the industries and governments to identify the main research and development centres working in the field of KM for research projects. Sixth, editors organizing special and regular issues on the topic can invite leading authors and institutions. Finally, compared to prior qualitative literature reviews, the present study offers a more rigorous, updated, and detailed outline of research on KM. This study builds on and extends the previous contributions offering a broader framework for guiding scholars approaching KM from diverse perspectives and more meaningful viewpoints. The clustering of co-citations based articles will guide the scholars to identify the research gaps and further purse the research to enrich the KM literature. Scholars working on KM domain may easily recognize the researchers, research institutions and countries paying attention in the KM areas. Thus, interested scholars can perform joint research projects, share their ideas and results as well as apply for academic positions to further investigate the mentioned field.
As the managerial contribution is concerned, the present study offers opportunities to the practitioners and organizations engaged in KM. The study further provides managers with diverse outlooks that enable them to enjoy the benefits of KM in their work. The bibliometric information about the KM literature has immense value for managers as it enables them to spot the KM expertise globally. Accordingly, the research projects on KM can be developed considering this information.
Although this article significantly contributes to the field of KM, nevertheless this study is not without limitations. Few journals on the KM are not yet covered by WoS. Hence, several other major databases can be considered (e.g., Scopus, EBSCO and Google Scholar) in their future research. Second, we included only research articles and review articles; therefore, the inclusion of other types of documents may lead toward different conclusions. Thirdly, we performed the co-citation analysis using network analysis and VOSviewer software. However, other methods and software may be used, such as Gephi. Lastly, the bibliometric analysis in the present study focuses on the general themes of KM processes, and not restricted to KM up to particular topic. Therefore, in future, it would be interesting to provide the bibliometric overview of KM literature analysing the logical intersection with crucial topics affecting the industrial environment (e.g., sustainability, circular economy, and Industry 4.0).

Author contributions
Authors equally contributed to the paper.

Disclosure statement
No disclosure statements and conflicts of interest have to be declared.