Printer Friendly

A REVIEW OF FACTORS AFFECTING THE SHARING OF KNOWLEDGE IN SOCIAL MEDIA.

Byline: Yahya Hakami Sakirin Tam Abdelsalam H. Busalim and Abdul Razak Che Husin

ABSTRACT: The success of knowledge management depends on how the knowledge is shared. Media such as Social Network Blogs Wikis and Podcast Forums have emerged as innovative online tools that affect knowledge sharing. As a result many researchers have endeavored to define factors that affect knowledge sharing (KS) in social media. However none of these efforts have either identified or categorized these factors in a comprehensive manner. Rather different researchers focused on specific factors within different contextual milieus. Hence this paper presents as systematic literature review in an attempt to identify all factors that affect the sharing of knowledge in social media and to provide a systematic categorization. We identified 120 papers from recognized online databases such as ISI Sciencedirect IEEE Explore ABSCOhost Compendex and the CAM digital library that provided data on KS in social media and selected 15 of these for a detailed study.

The major outcome of this study was the categorization of factors affecting KS in social media to include: include technological organizational - environmental and individual-personal factors.

Introduction

Over the last decade knowledge management (KM) has been a primary focus of attention for strategic capital groups interested in the innovative development and maintenance of competitive advantages [1]. These groups view knowledge sharing (KS) as an essential component of KM. KS is defined as the process by which members of an organization

acquire knowledge. Growing numbers of professionals have started web blogs and use social media as a tool to share their ideas. Hence it has become increasingly important to explore novel approaches that encourage individuals to contribute their personal knowledge and assist community members to share their expertise [2]. Increasingly organizations and educational institutions are implementing virtual learning communities that promote KS. However the goal is not achieved simply by grouping people together

and telling them that the sharing of your knowledge will help you learn better [3].

Social media have also become increasingly popular and their numbers and interactions grow daily. This online environment is host to a large range of activities that include the exchange of photos video media ideas commentary

and even the building of personal and career networks. Safko and Brake [4] defined social media as activities practices and behaviors among communities of people who gather online to share information knowledge and opinion

using conversational media.

This paper is structured to examine this phenomenon as follows: Section 2 presents the theoretical background of KS and social media. Section 3 describes our methodology. Section 4 presents our results and discussion. Section 6 concludes our discussion. Section 7 highlights our findings

and recommendations. This paper primarily questions the following items: (i) What is the role of social media in KS (ii) What are the main factors that affect KS in social media (iii) How do we categorize these factors

2. THEORITICAL BACKGROUND

1 Knowledge

Knowledge is information that has been validated through tests of proof [5] and which ultimately emerges as a strategically significant resource as an essential component of an organizations property; frequently referred to as one of the most important assets any firm may possess. Hence knowledge has been described as the foundation of a firms

competitive advantage and a key driver of the firms value [6789]. This advantage is generally established by an organizations ability to create and share knowledge thus resulting in greater social and intellectual capital [10119].

Social capital theory has also been studied as a base for analyzing the collaboration of online interactions [12]. Online knowledge collaboration occurs when either the Internet or the Intranet are used as a vehicle for the exchange

of knowledge [13]. The value of knowledge is two-fold in that (i) once created it can be used repeatedly by other individuals in the organization; and that (ii) knowledge once

shared stimulates the creation of new knowledge [1415]. Furthermore although there is no standard definition of Knowledge each attempt brings a similar essence so that what constitutes knowledge for one person may generate data for another and what counts as data for some people at any given time might later generate new knowledge for others [16].

2 Knowledge Sharing

KS is defined as the process by which members of an organization acquire knowledge whether unambiguous or implicit and which subsists within that organization with a marked emphasis on the importance of arranging a field of focus for relevant interaction [17]. In 2007 Kim [18] suggested a systems network that may effectively help knowledge sharing whereas Cross et al explained that any base for KS cannot simply be implemented through systems or a constitution but rather through the social interactions of participants [19]. KS has therefore become of crucial concern as a process whereby sources given by one party and received by another actually have added value [20]. Although based on the knowledge source knowledge

received cannot be identical as the process of interpretation is subjective and is restructured according to the receiver's bank of knowledge and interpretation [21].

KS is a behavior that occurs when an individual disseminates acquired knowledge to other members within an organization [22]. Prior research highlighted various

factors that affect an individuals willingness to share knowledge such as costs and benefits incentive systems extrinsic and intrinsic motivation organizational climate and management championship [2324252627]. Therefore we can reasonably assume that an individual's KS behavior is guided by personal characteristics and their ambient environment.

KS research also focuses on underlying behaviors governing communications and the interactions of participants who generate specific domains of knowledge that specifically enable participants to perform common functions and build relationships with other members in social media [23.27]. These efforts help academics for example to gain insights on how to enhance and stimulate KS in social media. Hence factors that inhibit or foster KS between individuals and groups depend on integrating the interrelationships of the social network's overall perspective which in turn attributes characteristic behavioral patterns to the social context within which the participants are embedded [18].

3 Social Media

A Origin and Definitions of Social Media

The term 'social media' has been discussed since Web 1.0 and Web 2.0 were released early in 2000 [28] and as a specific concept was initiated by Tim and John (Web 2.0) [2930]. It is therefore a relatively new topic that may be difficult to define. Tim and John published a Web 2.0 article

in 2005 entitled What is Web 2.0 that described design patterns and business models for the next generation of software [31]. This article may be considered the first such

paper on Web 2.0 as later cited by many researchers such as Gilchrist Levy and Lietsala and Sirkkunen [303233].

But 'Social Media' has no clear definition and many researchers apply different implications. Safko and Brake [4] defined it as activities practices and behaviors among communities of people who gather online to share information knowledge and opinions using conversational media. Other researchers define the term according to categories such as blogs Wiki sites and Social Networks

[3435]. Bowley [36] defined social media as collaborative online applications and technologies which enable and encourage participation conversation openness creation and socialization amongst a community of users. Despite several definitions the common aspect is 'participants who produce content'.

The term Web 2.0 and Social Media have been used with reference to each other [37383935] despite their differences. Social media is principally based on social networking according to different user-base practices [33]; whereas Web 2.0 refers to the use of an application by organizational members [38].

B Characteristics of Social Media

There are many social media characteristics but researchers tend to focus on the leading five leading that are related to KS. These features make social media a greater vehicle for KS because they enhance visibility and effectively promote knowledge creation and distribution by enabling participants to develop relationships and trust and thus share their knowledge [40]. They are itemized as follows:

User content generation is a major characteristic [36 41] that allows users to create edit comment annotate evaluate and distribute contents. The actual co-creation of content has become a key feature of social media [42].

Peer to peer communication has become globally interactive in real time formats such as chatting video/telephone conferencing etc [36 4337] and since communication is important for KS [44] social media provide effective channels for this purpose.

Networking allows users to create virtual communities that enable people with similar interests to collectively interact online to share their experience and knowledge develop relationships and freely discuss daily issues [45 42 37].

Multimedia orientation allows users to store and share content in various forms which include text image audio video etc. [46 47]. Users may easily share tag and comment on multimedia files in social media. Currently millions of users with multimedia contents share countless videos and photos on websites such as YouTube Flicker Facebook Twitter etc. [40].

User friendly designs with few constraints [37] that are simple dynamic attractive and enjoyable where users easily publish and customize multimedia [48 41 49].

C Categories of Social Media

Social media has been divided into many categories. According to Mayfield [37] they comprise social networks blogs wiki pages podcast forums content communities and micro-blogging (short updates posted by users). Others include RSS feeds message boards and 'tagging' [30 50]. The following table lists the most common social media categories.

Table 1. Social Media Categories

(Sources: Mayfield 2008; Otala and PAlysti 2008; Razmerita et al. 2009)[37 5152]

Categories###Key Functions###Examples

###To bring together users

###with similar interests.

Social###Facebook

###To###support###user

Networking###LinkedIn

###communication###and

###networking.

###To provide a platform for

###an online diary and

###Blogspot.com

Blogs###comments.

###Blog.com

###To support storytelling and

###knowledge sharing.

###To collect and edit

Wikis###knowledge in one place.###Wikipedia

###To enable collaboration

###and knowledge sharing.

###To share content among

###members with similar

Content###interests.###Youtube

Communities###To###support###content SlideShare

###management###and

###knowledge sharing.

###To categorize and manage

Tagging###Delicious

###content.

3. METHODOLOGY

In this section we describe the methodology of our systematic review based on guidelines from Kitchenham [53]. We also discuss research questions results from our planning and conducting phases and any threat to validity.

Systematic reviews were first presented by Kitchenham in 2004 and have since gained increasing popularity. The goal of a systematic review is: ==. . . to identify evaluate and interpret all available research relevant to a particular research question or topic area or phenomenon of interest. Individual studies contributing to a systematic review are called primary studies; a systematic review is a form of secondary study [54].

The researchers identified our objectives as follows: (a) to identify and select primary subject studies; (b) to extract data from the studies; (c) to synthesize the collected data. The last step entailed a discussion where the researchers wrote and evaluated their reports and drew conclusions as a result of steps a and b.

The next step was to identify appropriate research questions as we needed to classify our results based on a defined area of focus. We also needed to consider systems criteria to assess research quality and potential contributions based on the types of research contributions and evaluations. These questions are listed in Section 3.1 (below).

Another part of our review protocol required the selection of databases search terms types of studies and classification protocols for the collation and reporting of our results. We chose the following databases for our search: ISI Web of Knowledge; Compendex; IEEE Xplore digital libraries. We also used the ACM digital library to validate the completeness of our research selections. We employed the following search string with keywords title and abstract to locate results in the databases cited above: "Knowledge Sharing and Social Media". This broad term was chosen in order to discover the most relevant results. Our intention was then to use additional or fewer words depending on the number of hits which then proved unnecessary as the number of hits was typical for large systematic reviews.

To select relevant primary studies from the entire set of initially identified studies exclusions were made by a single researcher. However to minimize bias in the review protocol a second observer was included in each step to classify studies. Control studies were selected randomly. Results from primary and control sampling were then compared and in cases of significant difference issues were

addressed. Results from these steps are discussed in Section D.

A Research Questions We posited the following specific questions:

RQ1: What is the role of social media in knowledge sharing

RQ2 Focus: What main factors affect KS in social media

RQ3: How do we categorize these main factors

We answered these questions by conducting a systematic literature review as described in the protocol cited above. Methods and results of this review are discussed in the following sections.

B Sources of Information

To obtain the widest set of papers possible we searched the most popular and relevant literature databases used by investigators in the field. They are:

1. ISI Web of knowledge

2. ACM digital library

3. IEEE Xplore (IEEE)

4. Compendex

5. ABSCOhost

6. Sciencedirect

These databases cover the majority of journal and conference papers published in the field of KS. Technical reports and other documents lacking peer review assessments were excluded due to the large number of results obtained. After performing these exclusions we manually removed and/or resolved overlaps and duplicate papers.

C Study Selection

We developed exclusion/inclusion criteria for the selection process. Initial hits were filtered and excluded in several steps as explained below.

Exclusion criteria based on title:

The paper discusses different factors affecting KS on social media than software.

Short papers under five pages were excluded.

Exclusion criteria based on abstract:

If the term 'robust' was used without explanation as to how or why the study was robust the paper was excluded.

If the paper had a completely different focus other than knowledge sharing. If this was not detected when screening the title it was subsequently done when reviewing the abstract. Some articles described robustness as the proposed method or component of a developmental process rather than KS. Usually such cases were detected and excluded when screening title and abstracts. A common example was that of robust watermarks within KS that appeared often but were beyond the scope of our study although the word 'robust' was in the field of retrieved papers.

Exclusion criteria based on the full text were the same as criteria for abstract screening. In some cases the product was claimed as robust but the focus on KS was absent on screening the abstract.

These cases were handled at the full text level and studies were only included if a vigorous approach was presented; if that was not the case on our review of the complete text the paper was excluded.

D Data Extraction and Synthesis

As mentioned in Section 3.3 papers not related to knowledge

sharing based on the title were excluded. A total of 120 studies were however included. Any study mentioning KS in a significant manner was included after initial screening. After each of the six data bases was completed papers that passed filtering as cited above were moved into a final database. A cumulative number of unique results after repeated searches of the final database indicated a high number of duplicates from the database

5 RESULT

A Factors Affecting KS in Social Media

Our literature review revealed a wide range of factors

affecting KS that can be typified in three categories: technology organizational-environmental and individual- personal factors [5556575859]

History

The old way of doing things presents difficulties when using social media for KS. Users are now more familiar and comfortable with tools such as email instant messaging and existing IT technology using blogs social networks and wikis [6061]. The old way of accessing and retrieving information was cumbersome. Moreover Sotirios and Alya

researched the Determinants of KS using Web 2.0 Technologies and found that organizations focus more on promoting current tolls than social media technology.

Organizational Management Support Organizational and management support play important roles that sustain employee use of social media for purposes of KS. Organizations support KS by promoting its usefulness as important tool for social media exchange. They provide training and reward staff members as active users [6061]. This is consistent with Cabrera et al [56] who mentioned that managers often identify the importance of KS and promote its use by their staff.

Collective Cognitive Responsibility Collective cognitive responsibility refers to efforts made by all members to secure group success rather than individual achievement alone [62]. Each member becomes responsible to transfer his/her knowledge within the organizational milieu in order to facilitate current knowledge dissemination especially with respect to organizational affairs in order to become up-to-date and well informed [63]. Appointed educational staff members often conduct conferences and workshops to emphasize the importance of collective cognitive responsibility [64].

Enjoyment of Helping Others

The gratification that comes when helping others learn is another factor that affects KS [25]. This factor is consistent with the theory of altruism and many knowledge contributors gain pleasure by sharing [9]. Furthermore such

enjoyment leans towards growth [6566]. However the effect of this satisfaction is contingent on other factors such as motivation reciprocity and a sound organizational support system.

Reciprocity

Reciprocity is also an important factor in KS [23 67 68 69 70 27] with regard to perceptions of fair exchange and mutual knowledge sharing behavior [67]. This influence extends to the degree that each individual perceives improved relationships with others within the KS milieu and process [23]. Wasko and Faraj [27] clearly indicated that reciprocity in social media has a pronounced positive influence on the success of KS activities.

Information Privacy

Westin defined information privacy as the claim of individuals groups or institutions to determine for themselves when how and to what extent their information is communicated to others. This refers to controlled or restricted access to personal information in cyberspace [71] and is a critical factor for people participating in social media. People

can and do face unexpected admonitions or even dismissal from their positions due to inappropriate behavior as a result [72]. Hence data privacy bears a critical impact on KS in online social media.

Subjective Norm

The willingness of users to share knowledge is markedly enhanced when they discover that the sharing is useful for others. Moreover they then make greater efforts especially when they perceive that people come to expect their contributions [73 74 75]. This is referred to as a social norm: i.e. "the degree to which the user perceives that other participants approve of his or her contributions to the blog".

Social Networking Sharing Culture

A Social Networking Sharing Culture involves definite characteristics such as fairness identification and openness. These aspects significantly influence subjective norms and intentions toward the sharing of knowledge. When individuals in social media Groups find they are treated equally and as part of the group and are encouraged to share their knowledge they are more likely to do so [73 76]. The latter's research supported these observations and most especially the perception of fairness as significant factors in KS for Wikipedians.

Sense of Self-Work

Based on sound results it has been suggested that when a Facebook Group's members perceived that their own values helped others to learn they found sharing knowledge enjoyable because it improved their perception of self-worth [73].

Altruism and Reputation

Altruism refers to a person's willingness to increase other peoples welfare by helping them without expecting or waiting for any return benefit. Hsu and Lin [75] found that Altruism directly affected users attitudes toward sharing knowledge in blogs. Furthermore the degree to which a KS

contributor believed their participation would enhance their personal reputation was yet another notable factor affecting KS [77].

Motivation

Extrinsic motivation satisfies indirect or instrumental human needs; money for example is a prime motivator in this regard. Adequate financial rewards provide satisfaction that may remain independent of other direct outcomes of an individual's contribution to the collective's effort. Extrinsic motivation may also be satisfied by social rewards [78].

Experience Sharing

Practical experience is also considered an essential quality for KS through the sharing of personal knowledge using methods such as storytelling or offering observations as an experienced participant in focused discussions. This component vigorously transfers knowledge throughout social media [79 80 81].

Outcome Expectations

Outcome expectations refer to an individual's belief that the accomplishment of a certain sharing task leads to anticipated outcomes. In this study community-related outcome expectations refer to a knowledge contributor's assessment of the likely consequences that his/her KS behavior will produce within a virtual community. On the other hand personal outcome expectations refer to probable consequences that may individually rebound on their own person from his/her KS behavior. According to Social Cognitive Theory individuals are more likely to engage in behaviors from which they expect favorable consequences. Several studies in KS research provided support for this thesis. One of these found that performance-related outcome expectations had a significant effect on computer use [82]. Another found that outcome expectations were significantly related to the end user's organizational commitment [83].

Social Interaction Ties

Tsai and Ghoshal [84] remarked that social interaction ties (network ties) were channels through which information and resource flowed. Granovetter [85] described 'network tie' strength as a combination of time emotional intensity and intimacy (mutual confiding) that met with reciprocal services that characterized the bond. In this study social interaction (network) ties represent the 'strength of relationship as measured by the amount of time spent communicating and frequency of communication between members of virtual communities

Trust

Trust has been viewed as a set of specific beliefs that primarily deal with integrity benevolence and the ability of engaged parties in the management of literature [86 87]. Trust has been recognized as an important antecedent of a group's KS performance [88]; its intellectual capital exchange [89]; creation of organizational value ([84]; online transactions [90 87 91]; and KS in virtual communities [92].

Reciprocity Norm

In this study the reciprocity norm refers to mutual knowledge exchanges that are perceived as fair by the parties. According to Lin and Huang [93] reciprocity implies actions that are contingent upon receiving rewarding responses from others. Furthermore these exchanges tend to cease when the expected reactions are not forthcoming."

Identification

Identification refers to one's conception of self in terms of the defining features of a self-inclusive social category [94] which in this case is the virtual community. Nahapiet and Ghoshal [89] noted that identification is the process whereby individuals see themselves as one with another person or group of people (p. 256). In this study identification refers to an individual's sense of belonging-to along with positive feelings-for a virtual community; similar to emotional identification as proposed by Ellemers et al [95]. Emotional identification fosters loyalty and citizenship behaviors in a group setting [96 86] and is useful in explaining an individual's willingness to maintain a committed relationship with virtual communities [94 97].

Shared Language

The 'shared language' characteristic goes beyond the language that is shared to include acronyms subtleties and underlying assumptions that are the staples of day-to-day interactions [98]. Shared codes and language facilitate the common understanding of collective goals and the protocols

of virtual community behavior [84]. Nahapiet and Ghoshal [89] went further to state that a shared language influences conditions for the combination and exchange of intellectual capital in several ways. First a shared language facilitates a community's ability to access other people and their information. Second a shared language provides a common conceptual apparatus that allows people to evaluate the likely benefits from an exchange and shared knowledge collaboration. Finally a shared language supports knowledge overlap. Hence these factors combine to enhance the capability of different parties to synthesize the knowledge gained through social exchange.

Shared Vision

Virtual communities are groups of people that are brought together by common interests and goals. Tsai and Ghoshal [84] noted that a shared vision embodies the collective goals and aspirations of the members of an organization (p. 467). A shared vision is therefore viewed as a bonding mechanism that helps different parts of an organization to integrate or to combine resources [84]. Organization members who share a vision will be more likely to become partners in the exchange of resources [84].

Tables 2 3 and 4 lists factors that affect KS in social media according to our classification: technology organizational- environmental and individual-personal factors [55 56 57 58 59].

Table 2. Individual / Personal Factors Affecting KS in Social Media

Factors###Description###Sourced

Enjoyment###Knowledge###Kankanhalli et al.

in helping###contributor who###2005

others###gains through###Wasko and Faraj

###altruism###2000

###Ba 2001

###Constant et al. 1994

Reciprocity###Fair exchange of###Bock et al 2005

###mutual knowledge###Chiu et al 2006

###behavior###Davenport and Prusak

###2000

###Huber 2001

###Lin 2007

###Wasko and

###Faraj2005

###Chiu Hsu 2006

###Davenport Prusak

###1994

###Thibaut1959

Trust###Expectation that###Sotirious and Alya

###members will###2009

###follow a generally###Johanna 2010

###accepted set of###Abrams et al. 2003

###values norms and###Alawi Marzooqi and###Id

###principles###Mohammed 2007

###Ardichvili et al.

###2003

###Cheng Yeh and Tu

###2008

###Lai and Lee 2007

###Lin et al. 2009

###Paroutis and Al

###Saleh 2009

###Chiu Hsu 2006

###Blau 1964

###Ridings and Gefen

###2002

###Nonaka1994

###Hsu et al. 2007

###Sangmi et al. 2011

###Parameswaran and

###Whinston 2007

###Nicolaou and

###McLight 2006

###Peng and Chou

###2009

Outcome###Individuals share###Sotirious and Alya

expectation###knowledge within###2009

Media

###virtual communities###Johanna 2010

###with expectations of###McAfee 2006b

###enriching their###Hsu et al. 2007

###knowledge while###Cabrera and Cabrera

###seeking support and###2002

###making friends###Oliver and Kandadi

###2006

###Antikainen et al.

###2010

###Ardichvili et al.

###2003

###Hara and Hew 2007

###Jeppesen and

###Frederiksen 2006

###Lin 2007

###Paroutis and Al

###Saleh 2009

###Rolland and

###Kaminska 2008

###Tohidinia and

###Mosakhani 2010

###Bandura 1997

###Compeau and

###Higgins 1995

###Lave and Wenger

###1991

###Chiu and Hsu 2006

###Bock 2002

###Butler 2002

###Kolekofski 2003

###Lesser 2000

Self-Efficacy###A person's###Bandura 1986

###perception of their###Constant et al. 1994

###ability and skills###Bock and Kim 2002

Identification###Process whereby###Chiu Hsu 2006

###individuals see###Bergami 200

###themselves as one###Meyer 2002

###with another person###Ellemers 1999

###or group of people

Subjective###Degree to which###Pi et al. 2013)

Norm###users perceive that###Chow and Chan 2008

###others approve of###Hsu and Lin 2008

###his/her participation###Chen and Chen 2009

###in the social media###Hwang and Kim 2007

###for the purpose of

###sharing knowledge

Altruism and###Degree to which a###Hsu and Lin 2008

Reputation###person is willing to###Okyere and Nor

###increase the welfare###2011

###of other people

Experience###A way of sharing###Haldin-Herrgard

Sharing###personal experience###2000

###using different###Panahi et al. 2012

###methods###Dampney et al.

###2007

Table 3. Organizational Factors Affecting KS in Social Media Table 4. Technology Factors Affecting KS in Social Media

Factors###Description###Sourced

History###Old way of doing###Sotirious and Alya

###things###2009

###Johanna 2010

###Richard 1980

###McAfee 2006c

Organizatio###Promoting training###Sotirious and Alya

nal and###and rewarding staff###2009

managemen###for their knowledge###Johanna 2010

t support###sharing efforts###Cabrera et al. 2006

###McAfee 2006a

###Ardichvili et al. 2003

###Jeppesen

###Frederiksen 2006

###Lai and Lee 2007

###Lin 2007

###Paroutis and Al Saleh

###2009

###Zboralski 2009

###Tohidinia###and

###Mosakhani 2010

Collective###Collective efforts of###Chun and Mei 2009

Cognitive###group members to###Scardamalia 2002

Responsibil###succeed in###MacAndrew et al.

ity###knowledge sharing###2004

Shared###Addresses###Chiu and Hsu 2006

language###acronyms###Nahapiet 1998

###subtleties and###Tsai 2002

###assumptions that are

###the staples of day-

###to-day interactions

Shared###Embodies collective###Chiu Hsu 2006

Vision###goals and###Cohen 2001

###aspirations of the###Tsai 1998

###members of a social

###media community

Extrinsic###External motivation###Jeon et al. 2011

Motivation###that encourages

###knowledge sharing

Table 4. Technology Factors Affecting KS in Social Media

Factors###Description

###Sourced

Information###Controlled or###Chai et al. 2006

###restricted access###Snyder et al. 2006

Privacy###to personal data###Awad and Krishnan

###in cyberspace###2006

###Chellappa and Sin 2005

###McKnight###and

###Chervancy 2002

Social Ties###Social networks###Collins 2001

###personal contacts###Nahapiet and Ghoshal

###membership and###1998

###social class###Tsai and Ghoshal 1998

###Larson 1992

###He et al. 2009

###Chiu and Hsu 2006

###Tsai 2002

###Nahapiet###and

###Ghoshal1998

DISCUSSION

There are many factors affecting KS in social media that can be classed in three categories: technology individual-personal and organization-environmental factors. Most factors affecting KS in social media are related to nine aspects that are directly related to the individual: enjoyment when helping others; reciprocity; trust; outcome expectation; self-efficacy; identification; subjective norms; altruism and reputation; and the sharing of experience. The second tier of factors concerns five aspects of organizational and environmental milieus: organization and management support; collective cognitive responsibility; shared language; shared vision; and extrinsic motivation. Technology factors comprise the third tier and are perceived as having the lowest impact on KS in social media. These involve two aspects: information privacy and social ties.

Again if we look into the details of each category we see that the individual-personal factors that bear the most significant influences on KS in social media are outcome expectation and trust as both have been cited by many investigators. In this study twenty-two papers cited outcome expectation and nineteen papers cited trust.

In addition organizational and management support were marked as having the most noteworthy influence on KS in social media as stated by eleven researchers. Other factors such collective cognitive responsibility shared language and shared vision were indicated as the next most important group affecting KS in social media. As stated earlier technology factors came in third place with 'social ties' ranked as the most important factor followed by information privacy (eight papers cited social ties and five cited information privacy).

CONCLUSION

Knowledge management is a process that helps achieve organizational goals by capturing using and sharing knowledge. The sharing of knowledge has a large affect on the knowledge management process. Although much research combined efforts to define different factors that affect KS in social media we found no papers that categorized these factors. Therefore this paper provides a systematic literature review and initial categorization of the known factors that affect KS in social media. These categories are Individual-Personal Organizational and Technology with outcome expectation trust organizational support and management support and social ties leading each category respectively. We conclude therefore that the cited factors decidedly determine the success or failure of KS in social media.

REFERENCES

[1] Chua A. Y. "The dark side of successful knowledge management initiatives" Journal of Knowledge Management Vol.13 pp.3240(2009)

[2] Yu T.K. Lu L.C. and Liu T.F. "Exploring factors that influence KS behavior via weblogs"Computers in Human Behavior Vol.26 pp.3241(2010)

[3] Chen I. Y. and Chen N.S. "Examining the Factors Influencing Participants' KSBehavior in Virtual Learning Communities" Educational Technology and Society Vol.12 pp.134148(2009)

[4] Safko L. and Brake D. K. "Social Media Bible. Tactics Tools and Strategies for Business Success" New Jersey: John Wiley and Sons(2009)

[5] J. P. Liebeskind A. L. Oliver L. Zucker and M. Brewer "Social networks learning and flexibility: Sourcing scientific knowledge in new biotechnology firms" Organization science Vol.7 pp. 428-443 (1996)

[6] Bock G.-W. Zmud R.W. Kim Y.G. and Lee J.N. "Behavioral intention formation in knowledge sharing: Examining the roles of extrinsic motivators social- psychological forces and organizational climate" MIS

Quarterly Vol.29 No.1 pp.87111(2005)

[7] A. H. Gold A. Malhotra and A. H. Segars "Knowledge management: an organizational capabilities perspective" J. of

Management Information Systems Vol. 18 pp. 185-

214(2001)

[8] R. M. Grant "Toward a knowledge-based theory of the firm"

Strategic management journal Vol. 17 pp. 109-122(1996).

[9] M. M. Wasko and S. Faraj "Why should I share Examining social capital and knowledge contribution in electronic networks of practice" MIS quarterly pp. 35-57(2005)

[10] J. Nahapiet and S. Ghoshal "Social capital intellectual capital and the organizational advantage" Academy of management reviewVol. 23 pp. 242-266(1998)

[11] B. van den Hooff and M. Huysman "Managing knowledge sharing: Emergent and engineering approaches" Information

and Management Vol. 46 pp. 1-8(2009)

[12] K. Seonghee and J. Boryung "An analysis of faculty perceptions: Attitudes toward knowledge sharing and collaboration in an academic institution" Library and Information Science Research Vol. 30 pp. 282-290 (2008)

[13] R. Thackeray B. L. Neiger C. L. Hanson and J. F.

McKenzie "Enhancing promotional strategies within social

marketing programs: use of Web 2.0 social media" Health promotion practice Vol. 9 pp. 338-343(2008)

[14] M. Alavi and D. E. Leidner "Review: Knowledge management and knowledge management systems: Conceptual foundations and research issues" MIS quarterly pp. 107-136(2001)

[15] Petter. M. ""Education Policy Research and The Global Economy". Educational Philosophy and Theory Vol.34 No.1 p.p. 91-102 2002

[16] R. Adolphs "The social brain: neural basis of social knowledge" Annual review of psychology Vol. 60 pp. 693-

716(2008)

[17] Nonaka I. "A dynamic theory of organizational knowledge creation" Organization Science Vol.5 No.1 pp.1437(1994)

[18] S.-H. Jeon Y.-G. Kim and J. Koh "Individual social and organizational contexts for active knowledge sharing in communities of practice" Expert Systems with applications Vol. 38 pp. 12423-12431(2011)

[19] R. Cross A. Parker L. Prusak and S. P. Borgatti "Knowing what we know:: Supporting knowledge creation and sharing in social networks" Organizational dynamics Vol. 30 pp. 100-

120(2001)

[20] L. N. Marouf "Social networks and knowledge sharing in organizations: a case study" Journal of Knowledge Management Vol. 11 pp. 110-125(2007)

[21] M. Sharratt and A. Usoro "Understanding knowledge-sharing in online communities of practice" Electronic Journal on Knowledge Management Vol. 1 pp. 187-196(2003)

[22] S. Ryu S. H. Ho and I. Han "Knowledge sharing behavior of physicians in hospitals" Expert Systems with applications Vol. 25 pp. 113-122(2003)

[23] Bock.G.W. and Kim Y.G. "Breaking the myths of rewards: an exploratory study of attitudes about knowledge sharing" Information Resource Management Journal Vol.15 No. 2 (2002)

[24] Kankanhalli A Tan B Kwok-Kee W. "Contributing Knowledge to Electronic Knowledge Repositories: An Empirical Investigation" MIS Quarterly Vol.29 No.1 pp.113143 (2005)

[25] R. L. Purvis V. Sambamurthy and R. W. Zmud "The assimilation of knowledge platforms in organizations: An

empirical investigation" Organization science Vol. 12 pp.

117-135 (2001)

[26] Wasko M.M. and Faraj S. "Why should I share Examining social capital and knowledge contribution in electronic networks of practice" MIS Quarterly Vol.29 No.1 pp.35

57(2005)

[27] McCormack D. "2.0. The Resurgence of the Internet and E- Commerce Apatore Books" (2002)

[28] Funk T. "Web 2.0 and Beyond. Understanding the New Online Business Models Trends and Technologies Connecticut: Praeger" (2008).

[29] Gilchrist A. "Can Web 2.0 Be Used Effectively Inside Organizations" GAlrusler / Opinion Papers Vol.8 No.1 pp.123-139(2007)

[30] O'Reilly T. "What is Web 2.0 . Design patterns and business models for thenext generation of software" online [26.05.2013] http://oreilly.com/web2/archive/what-is-web-

20.html (2005)

[31] M. Levy "WEB 2.0 implications on knowledge management" Journal of Knowledge Management Vol. 13 pp. 120-

134(2009)

[32] Lietsala K. and Sirkkunen E. "Social Media: Introduction to the tools and processes of participatory economy" University of Tampere (2008)

[33] Anklam P. "Ten years of network"Learning Organization Vol.16 No.6 pp.415426 (2009)

[34] Ward R. "Blogs and wikis A personal journey" Business

Information Review Vol.23 No.4 pp.235240(2006).

[35] Bowley R.C."A comparative case study: Examining the organizational use of social networking sites" Master's Thesis Department of Public Relations University of Waikato Hamilton (2009).

[36] Mayfield A. "What is Social Media iCrossing". Online available [26.11.2010] http://www.icrossing.co.uk/fileadmin/uploads/eBooks/What_i s_Social_Media_iCrossing_ebook.pdf (2008)

[37] McAfee A. "Enterprise 2.0: the dawn of emergent collaboration" MIT Sloan Management Review Vol.47 No.3 pp.2128(2006).

[38] Paroutis A. and Al Saleh A. "Determinants of KS using Web 2.0 technologies" Journal of Knowledge Management Vol.13 No.4 pp.5263(2009).

[39] Anderson P. "What is Web 2.0 Ideas technologies and implications for education" Joint Information Systems Committee (JISC) Bristol (2007)

[40] Elefant C. and Black N. "Social media for lawyers: The next frontier. Chicago: American Bar Association" (2010).

[41] Lerman K. "Social information processing in news aggregation" IEEE Internet Computing Vol. 11 pp. 16-28(2007).

[42] Matthee C. "Towards the two-way symmetrical communication model: The use of Social media to create dialogue around brands" Magister Atrium Department of Applied Media Studies Faculty of Arts Nelson Mandela Metropolitan University Port Elizabeth S. Africa (2011)

[43] Gordeyeva I. "Enterprise 2.0: theoretical foundations of social media tools influence on KSpractices in organizations" Masters Thesis Department of Business Information Technology School of Management and Governance University of Twente Enschede (2010).

[44] Sarkkinen H. "The role of social media in customer communication in business-to-business markets" Masters Thesis Department of Marketing Faculty of Economics and Business Administration University of Oulu (2009).

[45] Canali C. Garcia J.D. and Lancellotti R. "Impact of social networking services on the performance and scalability of web server infrastructures" Proceedings Seventh IEEE International Symposium on NetworkComputing and Applications Cambridge MA pp. 160-167(2008).

[46] Lindmark S. "Web 2.0: Where does Europe stand" Institute for Prospective Technological Studies (IPTS) Luxembourg (2009).

[47] Pavlicek A. "The challenges of tacit KSin a Wiki system" in

17th Interdisciplinary Information and Management

Talks(IDIMT) Jindrichuv Hradec Czech pp. 391397(2009).

[48] Zheng Y. Li L. and Zeng F. "Social media support for knowledge management" International Conference on Management and Service Science (MASS) Wuhan (2010).

[49] Caputo A. "Making the complex simple: For better business decisions. In Business Information Review" Vol.26. No.81 pp.2834(2009).

[50] Otala L. and PAlysti K. "Wikimaniaa yrityksiin. Yritys 2.0 tuottamaan" Helsinki: WSOYpro (2008).

[51] Razmerita L. Kirchner K. and Sudzina F. "Personal knowledge management. The role of Web 2.0 tools for managing knowledge at individual and organizational levels" in Online Information Review Vol.33 No.6 pp.1021

1039(2009).

[52] B. A. Kitchenham and S. Charters "Guidelines for performing systematic literature reviews in software engineering" (2007).

[53] B. Kitchenham O. Pearl Brereton D. Budgen M. Turner J.

Bailey and S. Linkman "Systematic literature reviews in software engineering A systematic literature review" Information and Software Technology Vol. 51 pp. 7-

15(2009).

[54] Ardichvili A. Maurer M. Li W. Wentling T. and Stuedemann R. ==Cultural influences on KSthrough online communities of practice Journal of Knowledge Management Vol. 10. No. 1 pp. 94-107(2006)

[55] Cabrera A. Collins W.C. and Salgado J.F. ==Determinant of individual engagement in knowledge sharing The International Journal of Human Resource Management Vol.

17. No. 2 pp. 24564(2006)

[56] Barson R. Foster G. Struck T. Ratchev S. Pawar K. Weber F. and Wunram M. ==Inter- and intra-organizational barriers to sharing knowledge in the extended supply chain e2000 Conference Proceedings University of Nottingham

Nottingham (2000).

[57] McDermott R. and ODell C. ==Overcoming culture barriers to sharing knowledge Journal of Knowledge Management Vol. 5 No. 1 pp. 76-85(2001).

[58] Riege A. ==Actions to overcome knowledge transfer barriers

in MNCs Journal of Knowledge Management. Vol. 11 No.

1 pp. 4867(2007).

[59] Sotirios P. and Alya A. A. S. "Determinants of KSusing Web 2.0 technologies" Journal of Knowledge Management Vol. 13 No. 4 pp. 5263(2009)

[60] Johanna K. W. "Social media as a form of Organizational knowledge sharing: A Case Study on Employee Participation at WArtsilA" Masters Thesis University of Helsinki (2010)

[61] Chun-an L. and Mei-chi C. (2009) "Factors Affecting Teachers' KSBehaviors and Motivation: System Functions that Work" eLAC

[62] Scardamalia M. "Collective cognitive responsibility for the advancement of knowledge" in B. Smith (ed.) Liberal education in a knowledge society. Chicago IL: Open Court pp. 6798(2002)

[63] McAndrew P. Clow D. Taylor J. and Aczel J. "The evolutionary design of a knowledge network to support knowledge management and sharing for lifelong learning" British Journal of Educational Technology Vol.35 No.6 pp.739746(2004).

[64] Ba S. "Establishing online trust through a community responsibility system" Decision Support Systems Vol.31 No.4 pp.323336(2001).

[65] Constant D. Kiesler S. and Sproull L. "Whats mine is ours or is it A study of attitudes about information sharing" Information Systems Research Vol.5 No.4 pp.400 421(1994).

[66] Chiu C.M. Hsu M. H. and Wang E.T.G. "Understanding KS in virtual communities: An integration of social capital and social cognitive theories" Decision Support Systems Vol.42 No.3 pp.18721888(2006).

[67] Davenport T.H. and Prusak L. "Working Knowledge Harvard Business School Press" Boston (1998)

[68] Huber G.P. "Transfer of knowledge in knowledge management systems: Unexplored issues and suggested studies" European Journal of Information Systems Vol.10 No.2 pp.7279 (2001).

[69] Lin H.F. "Effects of extrinsic and intrinsic motivation on employee KS intentions" Journal of Information Science Vol.33 No2 pp.135149(2007).

[70] Chai S.; Lee. J.; and Rao. H. "Managing private information safety" Papers presented at the Second Secure Knowledge Management Workshop Brooklyn NY September pp.2892 2006.

[71] Snyder J. Carpenter D. and Slauson G.J. "Myspace.com" A social networking site and social contract theory" Paper presented at the 2006 Information Systems Education Conference Dallas November 25 (2006) available: http://proc.isecon.org/2006/3333/ISECON.2006.Snyder.pdf) (2006)

[72] S.-M. Pi C.-H. Chou and H.-L. Liao "A study of Facebook Groups members knowledge sharing" Computers in Human Behavior Vol. 29 pp. 1971-1979(2013)

[73] W. S. Chow and L. S. Chan "Social network social trust and shared goals in organizational knowledge sharing" Information and Management Vol. 45 pp. 458-465(2008)

[74] C.-L. Hsu and J. C.-C. Lin "Acceptance of blog usage: The roles of technology acceptance social influence and knowledge sharing motivation" Information and Management Vol. 45 pp. 65-74(2008)

[75] H. Cho M. Chen and S. Chung "Testing an integrative theoretical model of knowledge-sharing behavior in the context of Wikipedia" Journal of the American Society for Information Science and Technology Vol. 61 pp. 1198- 1212(2010)

[76] E. Okyere-Kwakye and K. M. Nor "Individual factors and knowledge sharing" American Journal of Economics and Business Administration Vol. 3 p. 66 (2011)

[77] S.-H. Jeon Y.-G. Kim and J. Koh "Individual social and organizational contexts for active knowledge sharing in communities of practice" Expert Systems with applications Vol. 38 pp. 12423-12431(2011)

[78] T. Haldin-Herrgard "Difficulties in diffusion of tacit knowledge in organizations" Journal of Intellectual capital Vol. 1 pp. 357-365 (2000)

[79] S. Panahi J. Watson and H. Partridge "Social media and tacit knowledge sharing: developing a conceptual model" World academy of science engineering and technology pp. 1095- 1102 2012.

[80] K. Dampney P. Busch and D. Richards "The Meaning of Tacit Knowledge" Australasian Journal of Information Systems Vol.10 (2007).

[81] Compeau D.R. and Higgins C.A. "Application of social cognitive theory to training for computer skills" Information Systems Research Vol.6 No.2 pp.118143(1995).

[82] R. W. Stone and J. Henry "The Roles of Computer Self- Efficacy and Outcome Expectancy in Influencing the Computer End-User's Organizational" Advanced topics in end user computing Vol. 2 pp. 44(2003).

[83] Tsai W. and Ghoshal S. "Social capital and value creation: The role of intrafirm networks" Academy of Management Journal Vol.41 No.4 pp.464476(1998).

[84] M. Granovetter "The strength of weak ties" American journal of sociology Vol. 78 pp.l(1973).

[85] Meyer J.P. Stanley D.J. Herscovitch L. and Topolnyutsky L. "Affective continuance and normative commitment to the organization: a meta-analysis of antecedents correlates and consequences" Journal of Vocational Behavior Vol.61. No.1. pp. 2052(2002).

[86] D. Gefen E. Karahanna and D. W. Straub "Inexperience and experience with online stores: the importance of TAM and trust" Engineering Management IEEE Transactions Vol. 50 pp. 307-321(2003).

[87] K. M. Nelson and J. G. Cooprider "The Contribution of Shared Knowledge to IS Group Performance" MIS quarterly Vol. 20 (1996).

[88] Nahapiet J. and Ghoshal S. "Social capital intellectual capital and the organizational advantage" Academy of Management Review Vol.23 No.2 pp.242266(1998)

[89] K. Chang Lee S. Lee and I. W. Kang "KMPI: measuring knowledge management performance" Information and Management Vol. 42 pp. 469-482(2005)

[90] D. Gefen and D. W. Straub "Consumer trust in B2C e- commerce and the importance of social presence: experiments in e-products and e-services" Omega Vol. 32 pp. 407- 424(2004).

[91] C. M. Ridings D. Gefen and B. Arinze "Some antecedents and effects of trust in virtual communities" The Journal of Strategic Information Systems Vol. 11 pp. 271-295(2002).

[92] M.-J. J. Lin S.-W. Hung and C.-J. Chen "Fostering the determinants of knowledge sharing in professional virtual communities" Computers in Human Behavior Vol. 25 pp. 929-939(2009).

[93] R. P. Bagozzi and U. M. Dholakia "Intentional social action in virtual communities" Journal of interactive marketing Vol. 16 pp. 2-21(2002).

[94] Ellemers N. Kortekaas P. and Ouwerkerk J.W. "Self- categorization commitment to the group and group self- esteem as related but distinct aspects of social identity" European Journal of Social Psychology Vol.29 No.23 pp.371389(1999).

[95] Bergami M. and Bagozzi R.P. "Self-categorization affective commitment and group self-esteem as distinct aspects of socialidentity in the organization" British Journal of Social Psychology Vol.39 No.4 pp.555577(2000).

[96] U. M. Dholakia R. P. Bagozzi and L. K. Pearo "A social influence model of consumer participation in network-and small-group-based virtual communities" International Journal of Research in Marketing Vol. 21 pp. 241-263 (2004).

[97] Lesser E.L. "Leveraging social capital in organizations" in E.L.Lesser (ed.) Knowledge and Social Capital: Foundations and Applications Butterworth Heinemann Woburn MA.Levy M. (2007) Web 2.0 implications on knowledge management. In Journal of Knowledge Management Vol.13 No.1 pp.120134(2000).
COPYRIGHT 2014 Asianet-Pakistan
No portion of this article can be reproduced without the express written permission from the copyright holder.
Copyright 2014 Gale, Cengage Learning. All rights reserved.

Article Details
Printer friendly Cite/link Email Feedback
Publication:Science International
Article Type:Report
Date:Jun 30, 2014
Words:7698
Previous Article:ORGANIZATIONAL COMMITMENT CONSTRUCT: VALIDITY MEASURE USING SEM.
Next Article:DYNAMIC WEB-FRAME DESIGN MODEL FOR DEVELOPING WEB APPLICATIONS.
Topics:

Terms of use | Privacy policy | Copyright © 2020 Farlex, Inc. | Feedback | For webmasters