Abstract
Knowledge has become a key factor to success in social environments and virtual communities. Also, human resources are a critical part of the creation and dissemination of the knowledge-based resources in virtual communities. Comprehensive understanding of virtual community dynamics can aid us to address critical organizational and information systems issues. Furthermore, virtual communities have gained high acceptance for people to learn and share knowledge. However, the detailed review and deep discussion in this filed are very rare. Therefore, this paper reviews and discusses the recently introduced mechanisms in this field as well as providing a deep analysis of their applied domains. This survey will help to a conceptual understanding of nature and the position of KS in virtual communities. Moreover, the drawbacks and benefits of the reviewed mechanisms in three categories such as social factors, motivation factors, and medical factors have been discussed and the main challenges of these mechanisms are highlighted for developing more efficient KS in virtual communities in the future. The obtained results indicated that helps the creativity and the success of the organizations, saving time and cost, reducing medical errors and also optimizing the learning effect. Trust is also the greatest prerequisite for KS.
Introduction
Today, in many organizations and social communities, people play a critical role in continuing competitiveness [1]. With the growth of information technology and the prevalence of the Internet, the ways through which people communicate and obtain information are more and more diverse [2–5]. Therefore, recently, managers have recognized Knowledge Sharing (KS) as a serious enabler for people to create value and offer a competitive advantage in a rapidly changing environment [6–8]. Knowledge is not ‘processing of information’ but it is a coordination of actions [9, 10]. Hence, KS is considered to be a vital means through which human resources make positive contributions to knowledge application and innovation among individual teams [11], ultimately leading to the sustainable development of the organization [12, 13].
On the other hand, one of the technological developments that changed the pattern of communication and traditional marketing is social media [14, 15]. One of the important social media that can be utilized by companies for reaching this purpose is the virtual community [16, 17]. A virtual community is a kind of online structure that enables Internet users to communicate and collaborate. In a Web 2.0 environment (forums, social networks, blogs, and communities), there are different ways to bring persons together through networks, allowing individuals to share their knowledge and personal skills, and to obtain knowledge from others [18, 19]. Members of virtual communities interact through the Internet and engage in communication, information exchange, and KS activities [20–22]. Online virtual communities broaden the scope of traditional communities and enhance the interaction efficiency of online communication [23]. An advantage of virtual communities is the ability to let innovative ways of creating and sharing organizational knowledge [23–25]. So, virtual communities are viewed as an informal tool to improve KS across time and location [26].
KS is the process of moving knowledge from one people to another [27]. Also, virtual communities are expected to serve the desires of their users for communication, information, and KS. However, the detailed review and deep discussion in this filed are very rare. Therefore, this paper reviews and discusses the recently introduced mechanisms in this field as well as providing a deep analysis of their applied mechanisms. A systematic literature review (SLR) as a popular method to classify and construct all related studies about particular research, subject zone, or important phenomenon [28] is used in this paper. It helps to limit regular errors, lessen chance effects, and increase the validity [29]. This survey will help to a deep understanding of nature and the importance of KS in virtual communities. Moreover, the drawbacks and benefits of the reviewed mechanisms have been discussed and the main challenges of these mechanisms have been highlighted for developing more efficient KS in Virtual communities in the future. Briefly, the goals of this paper are: Providing valuable information about the role of KS in virtual communities; Describing how SLR can be conducted in this field; Providing an outline of the current challenges in a range of problem domains related to in virtual communities; Exploring the future challenges for the KS in virtual communities; Outlining the significant scopes where future research can develop the use of KS techniques;
This paper explains the following issues: Some related works are discussed in Section 2. Section 3 discusses the research background. The research methodology is presented in Section 4. In Section 5, the reviewing of selected papers is presented. Discussion, open issues, and future trends are provided in Section 6. Eventually, Section 7 concludes the paper.
Related work
Some review papers about KS and other related domains are discussed in this section to highlight our motivation for writing this paper. Also, we examined a number of review articles that have been prepared in relation to our subject matter to highlight our motivation for writing this paper and to show some of their weaknesses.
Razzaque, et al. [30] have investigated the KS for medical decision-making in an e-health virtual community. Traditional and up-to-date theoretical, experiential, and case study-based literature review has been done to support these inter-relationships between two main theoretical constructs: KS quality and medical decision-making quality. The result showed that KS quality has the potential to facilitate a positive impacting role in medical decision-making quality. The study adds value to the large body of intellectual knowledge by improving the conception of medical decision-making quality to improve healthcare quality. The paper has introduced a new avenue upon which healthcare quality can be improved by improving medical errors, from the perspective of medical decision-making quality and KS quality on in Web 2.0 e-health social media platform. However, the weaknesses of this study are: The paper is not a systematical survey. The paper selection process is unclear. Future works have not been satisfactorily explained. There is no comparison between the articles.
Chen and Hew [31] have investigated the KS in virtual distributed environments. They have reviewed some empirical research that classifies the main theories and factors used to explain online KS. The results suggested that incentive items could be classified into three main categories: organizational, and personal, social factors. Further, this research focused on several main differences among past research studies, such as the notion of perceived compatibility and trust to provide potential directions for future research. Discrepancies that exist in the behavior and intention of KS are also discussed. However, there is no mention of any model or tactic for knowledge optimization in virtual communities. The weaknesses of this study are: The paper selection process is unclear. The paper is not a systematical survey. Few studies have been studied.
Liang and Liu [32] have examined a series of content analyses to classify the current trends and provided a new scientific visualization method through knowledge domain mapping to explore the position and direction of KS in virtual communities by CiteSpace software. The findings showed that the most significant developments and progress in KS in virtual communities have occurred primarily in China, Taiwan, USA, and Malaysia. Also, they have shown that the existing research in the field of KS in virtual communities focused primarily on business, engineering, economics, and computer science. Finally, five hot topics related to KS in virtual communities were also disclosed (virtual communities, trust, behavior, management, and network). However, this study suffers from some weaknesses such as: The paper is not a systematical survey. Future works have not been satisfactorily explained. Few studies have been reviewed.
Zhang [33] has investigated 180 kinds of literature on KS in virtual communities which 2002 to 2017. CiteSpace technology based on Java platform is used to change the visualization analysis of the development trajectory, and summarize the research distribution, intellectual base, and evolution trail of how KS in virtual communities has been applied. Results showed that the quantitative development of literature on KS in virtual communities has experienced three stages, and China, USA, South Korea have led the research of this area. In addition, the evolution path has gone through two stages. The research also provides the research trajectories and future research directions. However, this study has some weaknesses such as: The limitations of CiteSpace software may cause to ignore some important papers. The paper is not a systematical survey. The paper selection process is unclear. The comparing among articles has not been provided.
Lai, et al. [18] have examined a meta-analysis of KS in virtual communities from several well-known databases, published between 2002 and 2016. The selected articles extensively discussed critical factors affecting KS by members of virtual communities. Intrinsic and extrinsic motivations, social-capital factors and knowledge-sharing outcomes have been considered. Membership types were used as a moderating variable. The relevant analysis has been conducted by means of comprehensive meta-analysis software. Results showed that membership types play an important role as they moderate or restrain relationships based on certain knowledge-sharing variables. The weaknesses of this study are: The paper is not a systematical survey. The study is limited to years 2002–2016.
Based on the analysis of the reviewed articles, we have found that various issues in this field are improving quality, facilitating the decision-making, enhancing the competitive advantage, facilitating the KS and reducing the error. However, the greatest challenge in the development of a virtual community is the provision of knowledge and the willingness of individual KS with other members. Some review research has been done in the domain of KS and virtual communities. However, a few reviews considered these topics together. Also, KS benefits and disadvantage in virtual communities have not been discussed well. In addition, while systematic reviews are very important for performing a sound review, these surveys did not present a complete SLR-based review in this field with an analysis of their taxonomy and future challenges. To better understand the main features of the reviewed surveys, Table 1 provides a brief examination of the discussed review articles about KS in virtual communities and related domains. As we can see, many articles do not provide logical classification, articles comparison, and their analysis in detail. Therefore, in the rest of this paper, we try to solve the mentioned issues and provide an up-to-date analytical review paper in this domain.
Comparison of discussed articles about the role of KS in virtual communities
Comparison of discussed articles about the role of KS in virtual communities
Virtual communities are informal environments without any formal agreements, existing only in the minds of the members, who have shared interests or benefits [34]. Therefore, the major challenge in creating a virtual community is developing member willingness to share knowledge with others [35]. Virtual communities are not limited by location and time, and participants can share common interests that encourage regular interaction [36]. In this section, the related articles to the KS in virtual communities have been divided into three major categories (social factors, motivation factors, and medical factors) according to Fig. 1, that we will explain each of them in following.
Categorization of KS mechanisms in virtual communities.
Knowledge Management (KM) is a vital asset in defining the success and survival of an organization in today’s competitive markets [37–39]. Human is one of the important foundations in KM [40]. Human and technology must collaborate to facilitate KM process [41]. Therefore, The impact of social factors on KS is one of the key issues in this domain [42]. Social factors refer to an individual’s contract with the groups’ culture and specific interpersonal links with others. Individuals with dissimilar cultures may react in broadly different ways to the same stimulus situation; these variances are because of differences of subjective norms [43, 44]. On the other hand, from a social perspective, social influences are the most relevant factor in virtual community activities [45]. The social factors include the number of members in the community, social capital, trustworthiness, social usefulness, and the amount of reciprocity [46]. Trust in a virtual community is the action of believing that the other participants of the virtual community have provided accurate information [47]. Social capital is essential in creating greater economic capital for the company via customer loyalty [48]. Finally, social usefulness in a virtual community includes dome factors such as respect, recognition, and approval that a member of the virtual community receives from other community members [47, 49].
Motivation factors
Managers should cautiously consider incentive factors in IT-based systems since incentives potentially affect KS [50, 51]. Motivation is resulting from individual expectations of promising outcomes; it impels the contribution of an individual in certain behaviors [52, 53]. The researchers showed that motivational factors (intrinsic and extrinsic motivations) can either promote or impede KS in numerous contexts [54, 55]. Intrinsic motivation (i.e. challenge and enjoyment, reputation) remains an important construct, reflecting the natural human propensity to learn and assimilate [56]. However, extrinsic motivation (i.e. perceived usefulness, reward) is claimed to differ considerably in its relative autonomy and therefore can either reflect external control or true self-regulation [52]. Extrinsic motivation and intrinsic motivators are both crucial in explaining KS. On the other hand, in the virtual community, individuals are the main subjects, who are the implementers of KS [57]. For example, rewards can be an important motivator for KS in a virtual community.
Medical factors
Virtual communities play a significant role in business, society, healthcare, and education. KS in healthcare services refers to the transferability of knowledge between the key producers of a service [58]. The Internet offers users the chance to seek help, gather information, and find support when faced with important decisions regarding their health [59]. Effective KM enables health organizations to develop health knowledge. Health professionals and researchers to enhance the quality of healthcare services by improving health practitioners’ knowledge use virtual communities. They use web 2.0 environments to share their knowledge and experiences as well as asking for online information [60]. Online communities are forms of interaction that facilitate consumers’ online search and exchange of information that might result in an improvement of their health knowledge [61]. As a consequence, healthcare consumers prefer to turn to peer-to-peer communication by building online communities, participate and give online support and discuss, online, their health issues [62].
Research methodology
Assuming the huge number and frequent updates of healthcare, it is hard to study the related articles for evidence-based practice studies [63–65]. To adopt this practice, experts must seek evidence of research [66, 67]. The SLR is a concept for identifying, assessing, and interpreting all available researches related to a specific research query or topic area [68–70]. In this section, the SLR is presented to growth the understanding of KS in Virtual communities. This research aims at addressing the following research questions: RQ1: What is the importance of virtual communities in KS? RQ2: Why KS is used in virtual communities? RQ3: Which potential locations are in the usage of virtual communities for executing KS practices? RQ4: What are the taxonomies of research applications? RQ5: What are the benefits and drawbacks of KS systems in virtual communities?
Article selection process
The article selection has been fulfilled in three steps, include: Stage 1: Automated search Stage 2: Paper selection Stage 3: Publication and relevant analysis
In step 1, we used various search engines (Table 2) to discover relevant articles based on keywords including (knowledge sharing virtual communities) or (KS virtual communities) and (knowledge sharing online community). So, 374 articles are found from journals, conferences, and books. Figure 2 shows the classification of the articles in each publisher. Finally, Fig. 3 shows the distribution of the articles over time and journals. The published articles are highest in 2011 and by IEEE.
Electronic databases used in SLR.
Electronic databases used in SLR.
Percentage of published articles based on database sources.
Distribution of published articles by year of publication.
Step 2 sets some criteria to assure that the qualified publications are selected. The editorial notes, reports, working papers, and non-English papers are excluded [71–73]. Finally, the detailed analysis is done through 80 articles.
In step 3, to verify the relevance of the article, they are reviewed in detail. The subject, publication year, and rank of the journal are the key issues to decide the including or excluding of the articles. After applying these filters, the related articles are selected, which are published by 9 famous publishers. So, 57 articles are excluded. Finally, 23 articles have remained, which are divided into four sections where certainly about the KS in virtual communities, explained the proposed technique clearly, and improved some of the related parameters.
A summary of the applied process to categorize the articles is illustrated in Table 3 and Fig. 4. The searching process led to the identification of 23 relevant articles for deeper analysis (18 papers in Section 5 and 5 papers in Section 2). Moreover, Table 4 shows the classified papers.
Detail of selected articles in each stage
An overview of the used process to identify the articles.
Classified analyzed papers in 2 and 5 sections
This section divides the selected articles into three divisions, including social factors, motivational factors, medical factors.
Social factors
Though knowledge is a significant factor in organizations, only in recent years it has been considered the critical source of organizations’ long-term existence. KM has become embedded in organizations’ strategy, regardless of their size, geographical position, and sector of activity. Consequently, one of the important duties in KM is KS. Hence, discovering the factors that can facilitate KS is very necessary [89]. One of these factors is the virtual community which plays a major role in implementing and facilitating the sharing of knowledge. In this section, we examine the social factors that affect the sharing of knowledge in the virtual community.
Chiu, et al. [74] have studied the integration of social cognitive and social capital theories to build a model for investigating the motivations behind people’s KS in virtual communities. They have investigated the influence of individuals’ KS in virtual communities. They have shown that community-related outcome expectations could engender KS in virtual communities. The results of the study helped in classifying the motivation underlying individuals’ KS in professional virtual communities. The paper caused understanding the complex process is easy. But, the study suffers from several limitations, the research findings are not generalizable to the whole, only one aspect of KS is examined, the presented data are cross-sectional, and the results may have been impacted by self-selection bias.
Yao, et al. [83] have provided a new model for investigating the relationships among social capital, KS, team learning and e-loyalty in virtual communities. A survey of 222 virtual community participants was conducted to collect data. The results showed that social capital is positively related to their team learning and KS in the community, while team learning is positively related to KS. Particularly, social capital and KS are both positively related to members’ e-loyalty. Although the study highlights some of the factors affecting KS, however, the proposed model considers only some factors and does not mention culture as an important factor.
Also, Li [2] has identified the KS role on the Internet. He has proposed a model based on social exchange theory in which can share willingness, altruism, trust, and reciprocity to have an impact on people’s KS in virtual communities using structural equation modeling methods. The results have shown that members’ altruism could not predict KS. He also has found that members’ sharing willingness is the most important factor in the virtual community compared with trust, reciprocity, and altruism. The study helped recognize people’s incentive about KS; however, it also has some weaknesses. The survey data was collected in a limited area (Non-generalizability). The other limitation is that group analysis is not complete.
Furthermore, Chang, et al. [84] have proposed a theoretical model to examine the effects of trust, commitment, and self-efficacy on KS in the virtual communities. Data were gathered from 150 members of a technical virtual community. The results have revealed that trust and KS self-efficacy impact KS intention at two points of measurement, while commitment significantly affects KS intention at the second point of measurement. The relationship between trust and KS intention reduces over time, whereas the link between commitment and KS intention increases. The paper contributes to the works on virtual communities by examining the change in the effects of the predictors of intention over time. Although the results of this study provide several interesting and useful results, it has some limitations. Using limited members in a virtual community may limit the generalizability of the findings to other types of virtual communities. In addition, the results may also suffer from self-selection bias.
Deng and Guo [81] have explored the antecedents that influence people’s KS in virtual communities. A questionnaire was used to collect data. The ultimate sample included 96 individuals. Then they used the hierarchical linear modeling method to study the data. The results have shown that community member’s attachment could be a strong indicator of his/her KS intention. However, this effect can be contingent on individual centrality and community member variations. The advantage of the study is an adopted network perspective to build the research model. In addition, KS can be seen as a channel to attain status and centrality in a community. Finally, the paper emphasizes the dynamic characteristic of members in virtual communities and proves the moderation effect of community member variations. However, the sample is a little bit limited. Also, they have used subjective measures of individual centrality. The study also has the disadvantages of a cross-sectional design.
Moreover, Rodman and Trespalacios [79] have investigated the KS and potential virtual communities of practice in the U.S. coast guard’s afloat community. The study employed determined sampling to conduct six interviews of afloat members with diverse degrees of afloat experience. The interviews were used to explain the KS role in afloat community, including the degree to which afloat members are willing to exchange knowledge and how trust, reciprocity, and disposition towards online learning have an impact on this exchange. Interviews were digitally recorded and manually transcribed. In the research, a trust includes some elements, such as integrity, benevolence, and perceptions of professional competence. The study revealed that the afloat community possesses interest for virtual community’s development, but the mechanisms to enhance trust should be further explored. Despite the benefits mentioned above, the results of this study cannot be generalized to the entire community.
User anonymity is central to study social networks. Hence, Mojdeh, et al. [88] have examined the contextual roles of anonymity and community on individual drivers of KS attitude in social networking sites. By means of social capital theory as a theoretical backbone, they have proposed and empirically validated a relational model through a survey of 329 users of Facebook, LinkedIn, and CNET. By analyzing the data with the PLS method, they have found strong explanatory power of the proposed research model. The results have shown the positive impacts that various social factors (reputation, enjoy helping others, social capital, and commitment) can have on KS attitudes in social networking sites. Additionally, they have demonstrated the influence of contextual factors on these social factors, which, in turn, encourages KS. However, this study suffers from some weaknesses. They have used self-reported measures for the dependent variable and social antecedents. Although analyses have shown that common method variance was not an issue in the investigation, it could be more accurate to measure the dependent variable through the actual behavior of participants. Also, the obtained data are cross-sectional. Finally, this study focuses on social networking sites as one type of online communities. Aggregators (e.g., Digg, Reddit) and publications (e.g., Wikipedia) represent other types of websites that offer social collaboration artifacts. The generalizability of the current investigation is limited to online social networks.
The development of virtual communities is due to that most organizations do not possess all the required knowledge within their formal boundaries, hence, Need external knowledge resources. So, KS among participants has become critical for attracting and holding members of virtual communities. We found that access to valuable knowledge, trust, social communication, enhancing reputation, online learning, achieving a sense of self-worth and enjoyment are motivations of individuals’ for KS in virtual communities. Trust is widely accepted as an important enabler of KS processes in virtual communities. If managers can understand these social factors better, they will be better prepared to pursue the opportunities and benefits opened up by KM. Table 5 compares the important factors in the discussed social factors.
A side-by-side comparison of the important criteria social factors KS in virtual communities.
A side-by-side comparison of the important criteria social factors KS in virtual communities.
In recent years, we have witnessed a significant growth of virtual communities where users contribute content in various forms. Content sharing from members is critical to the viability of these virtual communities. It is therefore important to understand what motivation to share content with others. The effect of motivational factors on KS has been extensively investigated in many virtual communities. In this section, we review the motivational factors that are effective in KS in virtual communities, and it is also important for us to know if the intrinsic motive is further influenced by the KS or external motivation.
Wei, et al. [80] have provided a new model for studying the impact of national culture on KS motivation in virtual teams based on the social influence theory and the theory of reasoned action. The purpose is to deepen the theoretical understanding of the factors that rise or lessen employees’ tendencies to engage in KS. The paper offered a KS motivation model to enrich the theoretical foundation of understanding the whole mechanism, which makes positive KS. The paper has enriched the theoretical foundation of understanding the whole mechanism, which makes KS intention. However, the focus of the study was on culture and the motivation to share knowledge.
Chen, et al. [35] have investigated understanding KS motivation, incentive mechanisms, and satisfaction in virtual communities. They have focused on the websites of the traditional Chinese version of Wikipedia and Yahoo. By means of survey data from 169 community members, they have investigated the conditions under which motivation, incentive mechanisms, and satisfaction affect KS. They have designed a survey as an empirical measurement tool. They also have employed Pearson’s chi-square and t-test to test hypothesizes. The results have shown that the incentive mechanism is a significant predictor of a virtual community member’s motivation to get knowledge. While this study provides valuable information about the KS in virtual environments, however, it focuses only on one area and does not measure many factors.
Also, Martins [85] has examined the motivations for KS in virtual social networks. The aim is to produce a significant theoretical review, bring related insights from many contexts, and suggest a model for assessing the main motivations for KS in virtual social networks. It has systematized in five main dimensions: structural, cognitive, and relational capital reasons, personal motivations, and monetary reasons. The results have revealed that the process of KS in virtual networks seems to be a consequence of a combination of community and self-oriented motivations that differ slightly based on different goals and contexts of these online communities, where monetary reasons seem to be secondary. However, the proposed model has not been evaluated in a real environment.
Hung, et al. [82] have provided a fuller understanding of the formation of behavioral intention in professional virtual communities by decomposing the psychological formation of KS intention and concentrating on factors deemed likely to influence the KS intention of posters and lurkers. The online survey of 177 posters and 246 lurkers from 3 professional virtual communities. Interpersonal trust and peer influence strongly affected the subjective norm of KS in both groups, with posters emphasizing interpersonal trust and lurkers emphasizing peer influence. Finally, knowledge self-efficacy and resource availability enhanced the perceived behavioral control of KS. This study suffers from some shortcomings such as the obtained results cannot be generalized to the whole society, and in addition, the reliability of the research is poor. Finally, the results of the research have not been implemented in the real environment. However, it has many benefits, such as this study helps that effectively implement community activities and make a usable interface where practitioners, particularly community developers and moderators could understand which variables affect the formation of lurkers’ behavioral intention.
Assegaff and Kurniabudi [86] have investigated how the elements of extrinsic and intrinsic motivation contribute to people intending to perform KS in virtual communities. They have conducted a survey in a formal virtual community of practices members in one Indonesian company. 204 respondents participated in this study. Data was analyzed using SEM with Smart PLS software. The study founded that both of those motivations (intrinsic and extrinsic) positively influence the behavior of people in KS in formal virtual communities. Also, they showed found that people are more consent on organizational reward, reciprocity, reputation and enjoy helping in sharing their knowledge. However, there are several limitations of the study. The sample was selected from two 204 employees in just one organization in Indonesia banking institution. The model should be tested further using a different sample from another type of institution and also from different countries, since cultural difference among organizations and countries may lead to different belief and behavior of the people.
Finally, Maharani and Hendriyani [16] have examined the factors that motivate KS within the online community. They have used the theory of individual motivation and social capital theory because KS in the online community is a social process that involves personal interaction among members, the perspective of individual psychology and sociology will be able to explain more about this behavior. Motivation is divided into two, namely intrinsic motivation (enjoyment in helping others) and extrinsic motivation (rewards and reputation), while social capital consists of structural capital (social interaction), relational capital (identification, trust, reciprocity), and cognitive capital (shared language and shared vision). The results have found that enjoyment in helping others, reputation, social interaction, trust, reciprocity, and shared language influence KS, but the study finds interesting findings where rewards, identification, and shared vision do not affect KS. The results of the study helped identify the motivations underlying the KS of individuals in the online community.
According to the analysis of the above articles, many researchers have focused on satisfaction, reward, and reputation. Although culture and trust have an effective role in sharing knowledge in a virtual society, the researchers’ focus on these areas has been low. However, many frameworks are not measured in a real environment. Table 6 compares the important factors in the discussed motivational factors studies.
A side-by-side comparison of the important criteria motivational factors in KS virtual community
A side-by-side comparison of the important criteria motivational factors in KS virtual community
Health plays a deep role in our daily life. Peoples obtain health information from many sources that represent diverse viewpoints, and this information informs their health decisions. Currently, individuals are increasingly participating in virtual health communities to meet their needs for health-related information [78]. In this section, we examine the important health factors that affect the KS in the virtual community.
Zhang, et al. [75] have developed and evaluated a theoretical model that describes the intention to continue KS in a virtual community by focusing on the perceived level of psychological safety and its selected antecedents. They have found that psychological safety had an important effect on the degree of intention to continue KS, and that trust had both a direct and indirect effect on the degree of intention to continue KS through its impact on psychological safety. Thus, they have demonstrated the importance of psychological safety as a factor in determining the level of intention to continue KS in virtual communities. The study has some limitations. They have measured intention to KS rather than their actual sharing behavior. Also, the results of the research cannot be generalized to the whole society. However, the study highlighted the role of psychological safety and trust in influencing KS in virtual communities.
Alali and Salim [76] have explored the predictive influence of independent variables, which support KS, through the satisfaction of the health virtual communities members. They have developed and confirmed a multidimensional model of virtual communities success to support KS in the healthcare sector. The proposed model can be employed to assess and measure the KS behavior of virtual communities. The results have shown that members were satisfied with health virtual communities due to the quality of KS, the system, and service, and perceived the usefulness of health virtual communities. Additionally, they have found that perceived ease of use did not have a significant influence on a user’s satisfaction. Precisely, the higher the members’ satisfaction, the better is the KS, which implies that satisfaction is a surrogate measurement for KS in virtual communities. However, the study is limited to the health of virtual communities in the Middle East.
Virtual health communities are becoming valuable platforms for patients to communicate and find support. Yan, et al. [77] have provided benefits vs. cost KS model for Online healthcare communities. The benefits are mainly based on Maslow’s hierarchy of needs, and the cost includes cognitive and execution costs. They used this benefit vs. cost model to examine how Online health communities members KS. The Data was collected from users of two well-known Online health communities in China and the structural equation model was using for analyzed. They founded that three factors positively impact the KS: members’ perceived social support, a sense of self-worth, and reputation enhancement. Execution and cognitive cost have a negative impact on KS. The study of online health communities revealed that benefits promote the KS and costs prohibit it.
The Improve Care Now (ICN) exchange is an online KS platform that lets healthcare employees, clinicians, patients, and their families to classify like-minded people and share quality improvement tools and educational information. In this context, Gupta, et al. [87] have developed an interactive social network analysis tool to explore activity patterns on an online health KS platform. They have focused on three key KS activities: repin, comment, and download. They have modeled each set of activities as a directed social network. In order to successfully and efficiently explore meaningful patterns in these social networks, they have developed an interactive analysis tool through the system usability scale with textual feedback. They also have developed a highly usable and interactive social network analysis tool that can be used to support future studies of online health KS activities. The results have validated the high usability of the tool and indicated a few areas of improvement.
Finally, Zhang, et al. [78] have proposed the new models for KS motivations in online health communities. They have examined both the extrinsic (reputation and reciprocity) and intrinsic (knowledge self-efficacy, altruism, and empathy) motivations of health professionals and usual users. The data was collected from 443 members of three famous online health communities in China. They have found that reciprocity and altruism positively affect the KS intention of health professionals and usual users. Furthermore, reputation and knowledge self-efficacy have a greater effect on the KS intentions of health professionals than usual users; whereas reciprocity, altruism, and empathy have a greater influence on the KS intentions of usual users than health professionals. However, the study has some limitations, such as the sample size is not large, and the researchers relied on self-reported user surveys for data collection. Also, given that online health communities in China may differ from those of other cultures, the model should be evaluated further in other countries.
According to the presented results in Table 7, researchers in this field have focused on a sense of self-worth, reputation, empathy, reciprocity. However, as we have seen, in this series of articles, the implementation of programs in the real environment has been underestimated. Thus, the virtual health community is increasingly accepted as a means to access health knowledge. Health sector utilizes informatics to provide its services through KS during participatory behavior between members of a healthcare virtual community [30].
A side-by-side comparison of the important criteria medical factors KS in a virtual community
A side-by-side comparison of the important criteria medical factors KS in a virtual community
In this Section, 18 selected articles are analyzed. The focus of researchers in the selected papers is mainly on reputation, trust, reciprocity, satisfaction, and motivation. Based on these results, we conclude that internal factors such as satisfaction and reputation are more effective than external factors, such as rewards in sharing knowledge in virtual communities. More importantly, distrust relative to each other in virtual communities can prevent the sharing of knowledge among members, so adopting strategies and creating a culture, in this case, can help build trust among users. However, in most studies, the sample size was limited, which causes the results cannot be generalized. Also, Table 8 shows differences, advantages, and disadvantages of the reviewed mechanisms. In addition, we compared the achievements of the three groups of the selected papers in Table 9. The results show that the greatest benefit of virtual community in KS is facilitating KS, saving time and cost, increasing knowledge of members, and reducing medical errors. Future research should do a lot of research on other benefits of virtual community in KS to make the users more aware of the benefits of this technology and implement the culture of using KS systems in organizations.
Comparison of the KS mechanisms in a virtual community
Comparison of the KS mechanisms in a virtual community
A side-by-side comparison of the important criteria KS in a virtual community
Our study collected and reviewed many relevant papers and classified them. According to the performed SLR about the role KS mechanism in the virtual community until 2018, we showed the number of published articles have very high in 2011. Furthermore, IEEE and IGI have published 9% and 5% of the articles among 374 selected articles, respectively. The articles are divided into three main categories that 7 of them are social factors, 6 of them are motivational factors, and 5 of them are medical factors.
We have identified the most important factors affecting the sharing of knowledge in the virtual community and categorized them. These factors include satisfaction, motivation, usefulness, ease of use, social capital, member’s attachment, e-loyalty, culture, online learning, willingness, self-efficacy, commitment, psychological safety, altruism, reciprocity, justice, social support, reward, reputation, enjoy helping others, social interaction, identification, shared vision. In addition, the most important challenge for sharing knowledge in a virtual society is trust. Accordingly, the virtual community’s managers can promote trusting relationships by encouraging a shared vision through experiences. On the other hand, individuals like to gives their knowledge to others, when others also share their own knowledge. Therefore, individuals behave based on rational self-interest. Hence, research findings engender numerous implications for KS and virtual community literature.
We found that the social interaction ties and identification increased individuals’ quantity of KS. KS help to better development of social interaction ties, mutual trust, knowledge quality, identification, and shared vision. When the impact of community-related outcome expectation is taken into account, researchers are more concerned about the successful functioning, survival, and growth of the virtual communities than the benefits that will make to themselves [74]. Therefore, virtual communities’ managers can foster an active environment for social interactions for users, develop strategies that encourage the interaction and the strength of the relationships among members. In addition, they can encourage reciprocity by means of extrinsic motivators such as rewards for KS. We also found that individuals with better health status and higher education levels are more willing to share knowledge because they have felt more confident and experienced in helping others solve health problems. Virtual health community has a advantages such as 24-hour availability of information and the support from people beyond the limitations of geographic proximity, reduced perceived risk, as well as its cost savings, customizable information to meet one’s needs, lack of embarrassment, and access to diverse support networks and information [90]. So, virtual community managers should work to increase people’ psychological safety if they want to promote members’ participation in the virtual community. Therefore, virtual community managers can hold periodic offline meetings, establish a more convenient communication channel, and increase mutual trust between users to improve social interaction.
We found that the various focuses of KS in virtual communities in terms of research contents, application areas and research methods are constantly evolving [32]. The biggest challenge in fostering a virtual community is the willingness to KS with other members. Thus, virtual community administrators should focus more on individual career development needs, use incentives such as reputable rewards and answer ratings, which can enhance the self-efficacy of professionals to build their own reputations. It is also showed that many research investigated an individual’s self-perceived intention to share knowledge. Therefore, for determining the actual knowledge, sharing activity is a challenge for future works. Finally, research on possible factors that could sustain online KS over a prolonged time period is rare. Future studies should examine that factors and sustaining longitudinal KS.
Conclusion
A virtual community is considered as one of the important research directions for many purposes in KS. Hence, in this paper, we have surveyed the past and the state of the art articles KS mechanisms in the virtual community’s domains systematically. In addition, we comprehensively reviewed the KS mechanisms in virtual communities, that, what topics investigated, and the results were collected. This paper addresses the challenges of these methods to develop more efficient KS in virtual communities in the future. In the end, some interesting lines for future researches are provided. According to the studies, we categorized KS mechanisms in virtual communities into three classifications: Social factors; Motivational factors; Medical factors.
These mechanisms are comprehensively reviewed and compared, and the results were collected. The results showed that many organizations have launched virtual communities to promote KS among their employees. Because it helps to enhance the creativity, increase the success of the organizations, facilitates KS between users, and optimize the learning effect. Also, KS in virtual communities needs to earn the trust and satisfaction of users.
The findings of this paper make the following contributions. This study advances our understanding of KS by providing significant attention on a special type of virtual communities, which have been scarcely investigated in prior studies. The study provides insights from key academics and research institutions, focusing on core topics, and state of the research field. In addition, for practitioners, the results of this research report will enable practitioners to benefit more from the core research or core research results, and help them to follow appropriate procedures and select the appropriate advisory body for their application. Organizational researchers can use the results of this study to understand the role of employees in virtual community environments and related knowledge-sharing situations, and to gain a better understanding of the dynamics of knowledge generation and sharing. The findings provided a knowledge map for conducting relevant academic research, and we provide suggestions that are more specific to virtual community administrators.
This article suffers from several limitations. Only limited publications such as Google Scholar, Emerald, ABI/Inform Global ProQuest, Science Direct, and Springer link, Web of Science, IEEE journals were included in literature analysis and synthesis. The net effect of this is that this study excluded any KS in virtual communities research published in journals outside the above publications and so the findings may not be comprehensive and representative. Also, the focus of the current study was exclusively on the main body of literature of KS in virtual communities while it was ignored a large part of studies that have conducted over different areas such as virtual networks, learning environment, supply chain and etc. Thus, it could be worth considering these studies conducted over different areas by future studies. Lastly, non-English publications were excluded from this study. We believe research regarding the application of KS techniques in virtual communities have also been discussed and published in other languages.