PROBING FACTORS AFFECTING KNOWLEDGE SHARING BEHAVIOR OF PAKISTANI BLOGGERS

EJISDC (2011) 45, 6, 1-14

The Electronic Journal on Information Systems in Developing Countries http://www.ejisdc.org

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PROBING FACTORS AFFECTING KNOWLEDGE SHARING BEHAVIOR OF PAKISTANI BLOGGERS

Abida Abi. Ellahi

[email protected]

Rabia Mushtaq

[email protected] International Islamic University

Islamabad Pakistan

ABSTRACT The objective of this study is to identify those factors that affect the knowledge sharing behavior of individuals in the context of blogs of Pakistan. A research model has been developed, which consists of six construct derived from three well known theories namely Innovation Diffusion Theory, Social Capital theory and Theory of Reasoned Action. This theoretical model was tested empirically by conducting web based survey. Questionnaire was used as an instrument for data collection from 120 bloggers. Partial Least Square technique was employed to test the model. Four out of five hypotheses were confirmed. This study confirmed that relative advantage, attitude and social interaction ties have significant influence on intention to share knowledge and intention to share knowledge is a predictor of actual knowledge behavior. This study has several implications for professional and academic institutions. Key Words: Blogs, Intention, Complexity, Relative advantage, Theory of Reasoned Actions, Social Capital Theory, Innovation Diffusion Theory. 1. INTRODUCTION Organizations acknowledge that knowledge is a valuable intangible asset for generating competitive advantage (Miller & Shamsie, 1996). Knowledge sharing is a key to success for any organization. It is the behavior of propagating the value able knowledge to other members of an organization as well as to whole community which can get benefit through it. All learning organizations get help of knowledge management for sharing of knowledge. It creates linkages among employees, customers and suppliers through sharing of information (Weathersby, 1999).

A lot of factors affect knowledge sharing behavior of individuals (Ryu et al., 2003; Cabrera & Cabrera, 2002). Importance of human behavioral factors cannot be ignored for the spreading of knowledge (Bollinger & Smith, 2001).In human behavior first factor for sharing of knowledge is individual attitude towards knowledge sharing. Individual attitude towards sharing of knowledge is too much important. Attitudes are related with feelings of individuals. Sometime individuals are not willing to share the knowledge due to feelings of insecurity. They feel fear from the loss of superiority and knowledge ownership after sharing their distinctive ideas with others (Hislop, 2003; Yang, 2008). This unwillingness to share knowledge is natural human affinity (Davenport & Prusak, 1998). It means that transferring individuals’ knowledge into valuable organizational knowledge is not a simple phenomenon and contains many challenges (Ryu et al., 2003). Therefore, it is vital to recognize those factors that promote or limit knowledge sharing behavior.

Blogs, wiki and podcasts are continuously growing and popular information technology applications. The difference between these are that blogs are text-based log someone writes and updates, sort of like a web journal, whereas wiki is a web site anyone can edit, add to, and update, like Wikipedia and podcast are an online audio or video broadcast people can subscribe to or watch on a web site (usually hosted from a blog). According to Merriam-Webster dictionary (2010) blog “a short for Weblog is a Web site that contains an

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online journal with reflections, comments and often hyperlinks provided by the writer.” Most of businesses have started using blogs as a medium to prop up their products and services. Individuals use blogs as the source of getting relevant information and use it as a platform for sharing knowledge (Mohita, 2010). Blogs are renamed as social software which can be employed for social networking as well as sharing of different information. Bloggers can use blogs for collecting ideas and for revealing in-progress activities or works (Avram, 2006). These blogs can be used as tool for creating, organizing and sharing knowledge as well as developing personal knowledge management skills (Pettenati et al., 2007).

As blogs are a facilitating medium for quick communication of ideas, sharing of knowledge and dispersions of information to a wide number of readers. Thus, it is not logical for companies to ignore such potential channel. By keeping this view, many companies such as Google and Microsoft etc use blogs as knowledge and information sharing tool both internally and externally (Hsu & Lin, 2008). It is assumed that bloggers voluntarily publish their knowledge in blogs (Karimi & Poo, 2009); however it is not uncommon that bloggers are also affected by certain internal and external factors that limit or encourage them to share knowledge in blogs. There are a large number of researches on knowledge management phenomena but few have studied knowledge sharing and among those few studies, limited studies have investigated knowledge sharing factors in context of blogs.

Present study investigates the influence of certain factors on online knowledge sharing via blogs. These factors have different theoretical basis. The objective of this study is to identify those factors that encourage or obstruct the knowledge sharing behaviors of individuals in context of blogs. This study extracted factors from three different theories namely Innovation Diffusion Theory, Social Capital Theory and Theory of Reasoned Action. Two research questions of this research are:

1. What are the factors that support or obstruct knowledge sharing behaviors of users

in blogs? 2. Is intention to share knowledge shapes the actual behavior of knowledge sharing

in context of blogs or not? The scheme of study is as follow. First, on the basis of theoretical framework,

hypotheses are developed and a theoretical model is derived. Second, hypotheses as well as model as a whole is tested to give answer about above certain questions, which are described in the third section of this paper. Finally, conclusion, implication of studies, limitations and future research direction are discussed that draw conclusion on the basis of those results. 2. THEORETICAL BACKGROUND AND HYPOTHESES The propagation of network access has given smoothness to the progress of virtual communities. Virtual communities’ access is not limited to only one community. Individuals’ participation in professional virtual communities is increasing for getting knowledge to solve various problems. All the organizations have recognized that knowledge is an essential for getting competitive advantage (Teo et al., 2003; Hof, Browder, 1997). Thus, without valuable knowledge, virtual communities’ value will be diminished. Virtual communities are playing vital role in society due to their rapid access to valuable knowledge. Community members share the knowledge to get known how about the different sectors of society (Chiu et al., 2006). Different factors influence to virtual communities. These factors facilitate the knowledge sharing among the community members. Following factors can be considered as main source for actual knowledge sharing. These factors come under the umbrella of different theories but they support the environment of virtual communities knowledge sharing.

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2.1 Attitudinal Factors Impact on Actual Knowledge Sharing Fishbein and Ajzen (1975) gave the best attitudinal theory, which is the theory of reasoned action. Specifically, it focuses on the link between attitude and intention, and between intention and actual behavior. A major contribution of the theory of reasoned action is the specificity of attitudes and intentions to match with actual behavior (Bobbitt & Dabholkar, 2001). Most research in the area of technology has focused on the antecedents of technology adoption. What is the rate of adaptation of technology by individuals? With how much intensity people actual adopt it and use it? (Gatignon & Robertson, 1985).Attitude is always an antecedent of adaptation (Bobbitt& Dabholkar, 2001). For sharing of knowledge, employees need a positive attitude to behave in certain direction. Usually individuals don’t give importance for sharing of knowledge (O’Dell & Grayson, 1998). People don’t share due to feelings of insecurity. As insecurity is related with employees’ feelings, may be they considered that by sharing the knowledge they will lose their opportunities or they have no such caliber to share the knowledge. Thus, these different factors may impede the intention towards sharing of knowledge (Szulanski, 1996). Sometimes individuals are not willing to share their knowledge when they have no good feelings from learning experiences (Cameron, 2002). Chatzoglou (2009) highlights that there is the requirement of creating a climate that would help individuals to develop a more favorable attitude toward knowledge sharing with their true intention.

TRA also conceives that behavioral intention is best predictor of actual behavior. Behavioral intention can be measured an individual’s potency of intention to carry out a certain behavior ((Ajzen, 1991). Behavioral intention contains motivational aspects affecting a particular behavior and it is a person’s intention to perform or not perform a certain behavior. Consequently, intention to share knowledge in blogs is predictor of actual knowledge sharing (Kuo & Young, 2008) Thus, it can be hypothesized that Hypothesis 1: Intention to knowledge sharing has a positive effect on actual knowledge sharing. Hypothesis 2: Attitude toward knowledge sharing will be positively related to actual knowledge sharing.

2.2 Innovation Diffusion Theory There can be different sources of getting actual knowledge. Now question is why only virtual communities should be the source of sharing. For answering this question, innovation diffusion theory can be used who support to the use of virtual communities. This theory addresses the rate of adoption for innovations by the member of society. The relative speed with which members of a social system adopt an innovation depends on the different factors (Rogers, 1962). Some characteristics of innovation facilitate to the use of new object. These characteristics are categorized into five sub characteristics which are relative advantage (improvement of innovation over the previous method), compatibility (extent of comfort level given by that innovation in individual life), complexity (extent of difficulty level), trialability (experimental ease for early adopters) and observability (visibility level of innovation) (Rogers 1962).Two sub characteristics of innovation are address in this study as they are more relevant. They are relative advantage and complexity. 2.2.1 Complexity. Complexity occurs when an innovation is difficult to understand or use then individuals in all possibility will have inadequate knowledge, skill, and experience to use it. Thus, in these circumstances adoption rate will be slow down (Robertson, 1971; Rogers, 1995; Gatignon & Robertson, 1985). When the individuals have learning behavior

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then they will try to use new thing and share it with others after learning it (Wilton & Pessemier, 1981). Intention is a very accurate variable for predicting behavior. When the individuals have intention to learn something new and feel easy to use it then they will actual enhance the sharing of their knowledge (Ajzen et al., 1985). 2.2.2 Relative advantage. Relative advantage is the degree to which an innovation is superior from previous change or not (Rogers, 1995). Target group must consider to new improvement better and truly advantageous from societal economic and technological perspective (Chakravarty & Dubinsky, 2005). When the use of virtual communities is intended advantageous then actual knowledge sharing will take place. On the basis of above mentioned facts, it can be hypothesized: Hypothesis 3: Perception of complexity of particular technology use for knowledge sharing will be positively related to actual knowledge sharing. Hypothesis 4: Perceived relative advantage of particular technology use for knowledge sharing will be positively related to actual knowledge sharing. 2.2.3 Social Interaction Ties Social Capital Theory belief is to make strong social relationships among people to enhance their productivity and get other advantages (Coleman, 1988). Social capital consists of three distinct dimensions: structural dimension refers to the overall pattern of connections between stakeholders, relational dimension refers to the kind of personal relationships people have developed with each other through a history of interactions and cognitive dimension refers to those resources providing shared representation, interpretations, and systems of shared meanings among the concerned parties (Nahapiet & Ghoshal, 1998).

Virtual organizations are different from normal organizational structure. In virtual organizations or in virtual communities; individuals are connected through online communication. Social capital developed in virtual communities is strong support to encourage individuals to facilitate complex knowledge sharing process, and then share valuable knowledge among stakeholders (Nahapiet & Ghoshal, 1998).

Well educated and knowledge individuals are asset for every community. They become the source of competitive advantage for firms. Especially for knowledge sharing, intensive firm bond of these intellectuals is necessary. When the social ties among them become strong, they will be able to share the knowledge on actual basis (Alvesson, 2000).

People who prefer to use virtual communities are not only getting information but they also try to create link with one another. Social capital theory explains this issue what is the reason of knowledge sharing among communities. Knowledge sharing is actually a behavior which is exhibit by the member of society (Alavi & Leidner, 2001). Majority of the people interact with one another to resolve their problems and share their expertise. Trough frequent interaction of people a strong social relation between them is appeared in the form of social ties. These social ties will enhance the relationship of trust, beliefs and respect with member of communities along with sharing of useful knowledge (Semin & Smith, 2002). Nahapiet and Ghoshal (1998) argued that social network ties influence both access to parties of community to exchange and share the actual and valuable knowledge. Therefore, hypotheses will be built on this pattern: Hypothesis 5: Social interaction ties have a positive effect on intention to share knowledge.

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Fig 1: Proposed Theoretical Model with Hypotheses

3. METHOD The purpose of this study was to understand the user's attitudes and behavioral pattern towards knowledge sharing in context of blogs. Individuals who frequently use blogs were focus group of this study. Web based survey design was selected for this research. As survey increases the generalizability of the results because researchers cannot direct the state of respondents (Yalcinkaya, 2007); therefore it was chosen for this study. 3.1 Instrument Development Questionnaire was used as an instrument for data collection. This questionnaire was confirmed with the previous researches (e.g. Lin, 2007; Kuo & Young, 2008). In Pakistan, English is the official language of correspondence as well as medium of instruction. Therefore, in the questionnaires all the questions were written in English language. In Pakistan usually, researchers used questionnaires in English (Raja & Johns, 2010). Self-report questionnaire was used for the measure. All variables were rated on 5 point Likert scale. Responses were ranged from 1 depicts “strongly disagree”, 5 “strongly agree”. Questionnaire comprises of two parts. Part first was introductory section which contained information about bloggers’ skills, frequency of use and purpose of using blogs. Part two consisted of questions to measure theoretical constructs. 3.2 Sample Pakistani Bloggers were the target population of this study. In this research individual user of blogs was unit of analysis. Purposive sampling technique was the sampling frame used in this research. This purposive sampling presents the advantages of choosing sample according to specific characteristics and situations (Ellahi & Manarvi, 2010). Simple random sampling technique was used to choose sample from purposive sampling frame. The logic of purposive sampling method was to include those subjects who actually use blogs for knowledge sharing

Intention to shareknowledge

Actual KnowledgeSharing

Attitude towards learning

Social interaction ties

Relative Advantage

Perceived Complexity

Innovation diffusion theory Dimensions

Social Capital Theory Dimension

H1H2

H5

H4

H3Theory of Planned Behavior Dimensions

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by having understanding of blogs. The original sample size for this study was 200 but only 120 out of 200 favorable responses were obtained. Researchers have supported1 this sample size.

The web based questionnaires survey was distributed among the participants because bloggers were accessed through internet and along with it web-surveys were relatively fast, in-expensive and efficient method for data collection (Snow & Thomas, 2007). Similarly response rate of web-based questionnaires is considerably higher (Kiernan et al., 2005) rather than in paper-based surveys. The participants were assured that their responses would not be revealed other than academic research purpose. After carrying out process of collecting data, two statistical software - SPSS 17 and Smart-PLS - were used to conduct the empirical analyses. 4. RESULTS 4.1 Background Information The background information about bloggers’ skill, frequency of using blogs and purpose of using blogs is given in Table1. According to frequency results majority of (45.8+45%) respondents use blogs for knowledge collection and knowledge distribution. Only 9.2% use blogs just time killing. Similarly majority of (77.5%) respondents use blogs daily. The statistics presented in Table 2 also show that 65% of respondents considered themselves as having excellent level of skill for operating blogs. Only 6% have poor level of skill and 35% have good level of skill. Table 1. Blog Use of Respondents

Category Options Frequency Percentage To collect knowledge 55 45.8 To distribute Knowledge

54 45 Purpose of Using Blogs

To Pass time 11 9.2 Daily 93 77.5 Weekly 23 19.2

Frequency of Use

Monthly 4 3.3 Excellent 78 65 Good 36 35

Perceived Level of Skill

Poor 6 5 Total 120 100

Reliability analysis depicts the internal consistency of scale items. It is used to ensure that scale used is producing consistent results over times. Cronbach’s alpha is widely and commonly used measure for reliability analysis. Its value range is between 0 and 12. The value closer to 1.0 confirms significant reliability of scale. Table 2 shows Cronbach’s alpha values. In light of previous researches and on basis of existing theories, six constructs were studies included: actual knowledge sharing, intention to knowledge sharing, attitude towards knowledge sharing, social interaction ties, perceived complexity and relative advantage. Each construct was indicated with sign, such as actual knowledge sharing was denoted with AKS such as AKSi, AKSii and AKSiii. 1 Bartlett et al. (2001) pointed out that if in a study, factor analysis and regression is planned then sample size should not be less than 100 observations. 2 George and Mallery (2003) provided the following rules of thumb: Cronbach alpha = “> 0.9 =Excellent, > 0.8 = Good, > 0.7 = Acceptable, > 0.6 = Questionable, > 0.5 – Poor, and < 0.5= Unacceptable”

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Table 2 .Reliability Analysis of Constructs

4.2 Results of Structure Model In order to evaluate the theoretical relationships among relevant constructs, hypotheses testing and factor analysis were conducted using Partial least squares (PLS) technique. This PLS analysis was conducted using Smart-PLS software. PLS works same like structural equation models. PLS was preferred in this study because it is best for dealing issues of small sample sizes, missing values and multicollinearity (Pirouz, 2006). Figure 2 shows the results of analysis of structure model. It includes value of R2,factor loadings and path coefficients. 4.2.1 Factor Analysis The construct validity was confirmed by computation of loading values of items on their respective constructs as shown in figure 2. The model estimation result show values of factor

Cronbach Alpha

Items Statements

Actual Knowledge sharing was measured by three item scale adopted from study of van den Hooff and de Leeuw van Weenen (2004)

AKSi When I learn new useful knowledge, I share it on blogs AKSii Knowledge sharing in blogs is considered normal

0.937

AKSiii When blogs members learn something new, they share it on blog Intention to share knowledge was measured by three item scale adopted from study of Kuo

and Young (2008) IKSi I would like to use blogs for knowledge sharing since it help me to collect and share

knowledge easily IKSii I will continuously use blogs for knowledge sharing

0.922

IKSiii I intend to share knowledge on blogs Attitude towards knowledge sharing was measured by three item scale adopted from study

of Kuo and Young (2008) AKSi Using blogs for knowledge sharing is a beneficial idea AKSii I enjoy to share knowledge on blogs

0.912

AKSiii Using blogs for knowledge sharing is valuable Social interaction ties was measured by three item scale adopted from study of Chiu, Hsu

and Wang (2006) SITi I spend a lot of time interacting with some members in blogs SITii I maintain close social relationships with some members in blogs

0.902

SITiii I have frequent communication with some members in blogs Perceived complexity was measured by three item scale adopted from study of Cobanoglu

(2006) PCi Using blogs for knowledge sharing takes up too much of time PCii When I share knowledge, I find difficult to post it in blogs

0.846

PCiii To share knowledge on blogs requires a lot of mental effort. Relative advantage was measured by three item scale adopted from study of Selamat et al.

2009) Rai Blogs facilitates the rapid sharing of knowledge RAii A blog is more than a simple place for knowledge sharing

0.907

RAiii Blogs promote interaction among members for knowledge sharing

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loadings on their respective items which were assigned to their corresponding indicator. It is clear from figure that factor loading values are in suggested range, confirming validity of constructs in model. The values of factor loadings show the strength of relation of items with their respective constructs. The items giving higher loadings that are near to 1 depict strong relation with constructs on which their loadings are computed. The highest factor loading value in this model was of AKSiii (0.95) and the lowest value was of AKSi (0.69). Thus, all factor loadings are significant and fairly high. 4.2.2 Path Analysis: Along with factor loadings, path coefficients values are also shown in figure 2. The values for path coefficients are showing hypotheses support for four out of five hypotheses. The R2

values of dependent variables model were 0.87 and 0.75, show explanatory power of model. In this regard model depicted 87% variance in intention to knowledge sharing and 75% variance in actual knowledge sharing behavior. The value range of standardized coefficients of paths was ranged from 0.16 to 0.90 as shown in figure 2. These values shows that relative advantage of blogs for knowledge sharing, attitude toward knowledge sharing and social interaction ties significantly effect intention to knowledge sharing and intention to knowledge sharing significantly effects actual knowledge sharing. However, the value of perceived complexity was showing positive relation with intention to knowledge sharing. This result was inconsistent with suggested hypothesis. 4.3 Hypotheses Testing Evaluation Hypothesis 1: Intention to knowledge sharing has a positive effect on actual knowledge sharing. The statistical results show that intention to knowledge sharing was positively related with actual knowledge sharing behavior in blogs. The highly significant path coefficient value of 0.90 (sig P<0.001) show that one unit increase in intention to knowledge sharing will increase 0.90 units in actual knowledge sharing behavior. This suggests that bloggers intention to knowledge sharing was a strong predictor of actual knowledge sharing in blogs. Thus H1 was supported. Hypothesis 2: Attitude toward knowledge sharing will be positively related to actual knowledge sharing. The path coefficient value of attitude towards knowledge sharing and intention to knowledge sharing in blogs is 0.76 (sig p<0.05). This confirms that one unit change in attitude brought 76% variation in intention to share knowledge. This confirms that attitudes of bloggers towards knowledge sharing significantly affect their intention to share knowledge in blogs. Thus H2 was also supported. Hypothesis 3: Perception of complexity of particular technology use for knowledge sharing will be positively related to actual knowledge sharing. The statistical results show that perceived complexity of blogs is positively related intention to share knowledge. However according to theoretical expectations perceived complexity negatively relates with intention to share knowledge. The bloggers who perceived that blogs were more complex to use, they were less intended to share knowledge via blogs. But a significant positive path coefficient value of 0.56 did not confirm this assumption. Thus H3 was not supported.

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Fig 2: Structural Model Results

Intention to share knowledge

R2 =0.87

Actual KnowledgeSharing R2 =0.75

Attitude towards learning

Social interaction ties

Perceived RelativeAdvantage

Complexity

Innovation diffusion theory Dimensions

Theory of Planned Behavior Dimensions

Social Capital Theory Dimension

0.90***

0.76*

0.56**

0.85***

0.67**

*P value <0.05 **P value <0.01 ***P value <0.001 (2 Tailed)

RA

i R

Aii

R

Aii

i P

Ci

PC

iii

PC

ii A

KSi

iA

KSi

i A

KS

i S

ITiii

S

ITii

SI

Ti

IKSi IKSii IKSiii AKS AKSii AKSiii

0.93

0.

88

0.79

0.

87

0.80

0.

82

0.73

0.

87

0.77

0.

78

0.69

0.

70

0.74 0.79 0.71 0.85 0.80 0.95

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Hypothesis 4: Perceived relative advantage of particular technology use for knowledge sharing will be positively related to actual knowledge sharing. The positive relation of relative advantage of blogs for knowledge sharing was confirmed by path coefficient value of 0.85 (P<0.001). It depicted that bloggers who perceived blogs offering more advantages for knowledge benefits as compare to other channels, were more intended to share knowledge via blogs. Thus H4 was also accepted. Hypothesis 5: Social interaction ties have a positive effect on intention to share knowledge. The statistical value of path coefficient for relation of social interaction ties and intention to knowledge share was 0.67. That show bloggers who had more interaction with other bloggers were more intended to share knowledge via blogs. In this way, the positive effect of social interaction ties on intention to share knowledge was confirmed. Thus H5 is supported.

The summary of supported hypotheses is given in Table 3. Table 3. Hypotheses Results Summary

Structural Path Standardized Coefficients

Hypothesis Direction

Hypothesis Testing

Intention to KS Actual KS 0.90*** + Supported

Attitude to KS Intention to KS 0.76* + Supported

Perceived Complexity Intention to KS 0.56** _ Not Supported

Relative Advantage Intention to KS 0.85*** + Supported

Social Interactions Intention to KS 0.67** + Supported

5. CONCLUSION AND IMPLICATIONS This study aimed to gain an understanding of factors effecting knowledge sharing behaviors of Pakistani bloggers in context of blogs. These factors were intention to share knowledge, actual knowledge sharing, perceived complexity, relative advantage, attitude towards knowledge sharing and social interaction ties. The results are strongly supported to all the relations except perceived complexity. Among all the variables intention to share knowledge with actual knowledge sharing behavior shows the strongest effect. Along with its strong effect of attitude towards knowledge sharing on intention to knowledge sharing also validates theory of reasoned action. The study confirms that social interaction ties, attitude towards knowledge sharing and relative advantage of blogs for knowledge sharing significantly captures their intention towards knowledge sharing. Similarly intention to knowledge sharing shapes the actual behavior for sharing of knowledge.

Opposite to expectations of study, perceived complexity did not have a strong negative effect on actual behavior of knowledge sharing. It does not mean that variable perceived complexity has no importance in this research context but it means that direct effect of complexity on intention was not supported by taking this sample but there is possibility that it might have a direct effect on actual knowledge sharing behavior. It shows that perceived complexity to blogs usage has no key role in shaping bloggers intention to share knowledge. It might be possible that bloggers in Pakistan don’t consider blogs as difficult or complex to operate. However, designing a less complex blogs is still important for

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users. Less complex blogs will lead to a belief that the blog is more useful and more enjoyable. There is also possibility of common methods bias because common method bias inflates relationships between variables measured with help of self-reports data. However, an attempt has been made to overcome this bias by using factor loadings to confirm construct validity. Conway and Lance (2010) said that to show construct validity of the measures used is one way to rule out substantial method effects. Despite of having intention to share knowledge, individuals are prevented by psychological as well as environmental (physical) factors for online sharing knowledge. This study has taken into account both types of factors in order to understand breach between intention and action.

The study contributes to literature by explaining knowledge sharing attitudes and behaviors in light of three different theories. In this way applicability of these theories was verified in this one research. Further, this study is not relevant for a particular group of professional or social group. It has taken into account almost all bloggers types beyond the boundaries of particular organization or group, thus, it was an attempt to widening the study generalisability. The results of this study can contribute to understanding of success factors of both professional and personal blogs especially in context of developing countries. It can serve as a basis for recognition of reasons of not only acceptance but also rejection decisions about direct or indirect knowledge sharing by individuals.

The knowledge sharing behavior of bloggers in context of blogs shows that blogs can serve as less costly and quickly assimilated marketing and networking tool for professional organizations in developing country. The findings provide guideline for companies using blogs as marketing channel, to gain insight into drivers of knowledge sharing. Using blogs they can target a large number of audiences worldwide beyond the boundaries of ethnicity, locality, race or religion etc. In this study the knowledge sharing aspect in blogs also draws a conclusion that these blogs have enough potential to act as valuable medium of learning and teaching in developing countries. Thus, it provides an opportunity for academic institutes as well, take an example of few universities in world like Harvard University and the University of Iowa that have taken an initiative to use blogging tools for knowledge sharing. 6. LIMITATIONS AND FUTURE DIRECTIONS The main limitations of this research are as follow: First, it has biasness’ of methods associated with survey research because study relied on single source of data gathering i.e. questionnaire. Secondly sample size was small. Thirdly, this study didn’t differentiate among bloggers on basis of their role such as comment provider, blog readers etc. Along with it, while identifying factors as antecedents of knowledge sharing in blogs, some obstacle such as time, facilitating conditions etc were not dealt. The future research models of knowledge sharing should be extended by including barriers of knowledge sharing, cultural aspects, organization citizenship behavior etc.

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Documents

PROBING FACTORS AFFECTING KNOWLEDGE SHARING BEHAVIOR OF PAKISTANI BLOGGERS