Journal of Knowledge ManagementDeterminants of knowledge sharing in a public sector organizationAngela Titi Amayah

Article information:To cite this document:Angela Titi Amayah, (2013),"Determinants of knowledge sharing in a public sector organization", Journal of Knowledge Management, Vol.17 Iss 3 pp. 454 - 471Permanent link to this document:http://dx.doi.org/10.1108/JKM-11-2012-0369

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Determinants of knowledge sharing in apublic sector organization

Angela Titi Amayah

Abstract

Purpose – The purpose of this paper is to investigate the factors that affect knowledge sharing in a

public sector organization.

Design/methodology/approach – The paper is based on quantitative research. The data were

gathered through questionnaires and analyzed using multiple regression.

Findings – Community-related considerations, normative considerations and personal benefits were

three motivators found to have a unique contribution to the variance in knowledge sharing. The following

enablers had a significant main effect on knowledge sharing: social interaction, rewards, and

organizational support. Two barriers, degree of courage and degree of empathy, which measured

organizational climate, were found to have a significant main effect on knowledge sharing. The

interaction of normative consideration with social interaction, personal benefit with organizationalsupport, and normative considerations with degree of courage, had a moderating effect on the

relationship between motivating factors and knowledge sharing.

Research limitations/implications – The study was conducted in a single public sector organization,

which limits the generalizability of the findings to other settings. Another limitation is that attitudes toward

knowledge sharing, and knowledge-sharing behaviors, vary across cultures. Finally, self-reported data

are subject to response bias.

Practical implications – Identifying factors that influence knowledge sharing could help practitioners

create a knowledge-sharing culture that is needed to support knowledge sharing and knowledgemanagement within public sector organizations.

Originality/value – This empirical study will contribute to the theoretical knowledge on knowledge

sharing in the public sector, which has been neglected in knowledge-sharing research.

Keywords Public sector organizations, Knowledge management, Knowledge sharing,Motivational factors, Enablers, Barriers

Paper type Research paper

Introduction

In the knowledge-based economy, knowledge sharing is increasingly viewed as critical to

organizational effectiveness (Quigley et al., 2007). It is argued that knowledge sharing

among employees significantly impacts the performance of both public and private sector

organizations (Silvi and Cuganesan, 2006). As a result, knowledge sharing has gained

importance in organizations seeking to gain a competitive edge (Felin and Hesterly, 2007).

However, knowledge sharing is challenging in organizations for two reasons. First,

employees’ tacit knowledge, by its very nature, is difficult to transfer. Second, knowledge

sharing is typically voluntary (Lin et al., 2008). Organizations can manage knowledge

resources more effectively only if employees are willing to share their knowledge with

colleagues. To facilitate knowledge sharing among public employees and across agencies,

it is essential to understand the factors influencing employees’ willingness to share

knowledge. Accordingly, there is a significant amount of research on factors that may

influence knowledge sharing in organizations. However, most research on knowledge

sharing has been conducted in private sector organizations (e.g. Hara and Hew, 2007; Land

PAGE 454 j JOURNAL OF KNOWLEDGE MANAGEMENT j VOL. 17 NO. 3 2013, pp. 454-471, Q Emerald Group Publishing Limited, ISSN 1367-3270 DOI 10.1108/JKM-11-2012-0369

Angela Titi Amayah is

based at SUNY Empire

State College, Rochester,

New York, USA.

Received 30 November 2012Revised 6 February 201314 March 201329 March 2013Accepted 4 April 2013

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et al., 2009; Li et al., 2010) or among students (e.g. Kwok and Gao, 2005). Few studies focus

on knowledge sharing in the public sector (Sandhu et al., 2011; Yusof et al., 2012).

This article makes two key contributions. First, there is little research on knowledge sharing in

public sector organizations. In the past 20 years, significant changes have occurred in the

public sector, moving from a traditional, bureaucratic approach to a more managerial one

(Sandhu et al., 2011). Today, public organizations are also known as knowledge-based

organizations (Willem and Buelens, 2007). Thus, knowledge is as critical a resource to public

sector organizations as it is to private sector firms (Siong et al., 2011; Willem and Buelens,

2007). Public organizations too have to contend with greater competition for resources and

competition from alternative services (Luen and Al-Hawamdeh, 2001). Additionally,

improving knowledge sharing processes would help ensure employees benefit as much

as possible from senior employees’ knowledge and experience before they retire. Second,

this study extends the literature on the factors that affect informal knowledge sharing. The

study not only examines factors that encourage knowledge sharing, but also those that

negatively influence employees’ willingness to share knowledge in a public sector

organization.

The next section is a summary of previous research on knowledge sharing and the factors

that influence individuals’ willingness to share, with specific emphasis on the public sector.

Next, the methodology is discussed, including the population and data analysis. Multiple

regression was used to analyze the data, generating a model showing the influence of

several factors on knowledge sharing. The findings and discussion sections report on this

analysis. Finally, the paper offers conclusions and recommendations for practice and further

research.

Previous research

Knowledge sharing

Knowledge and information are not clearly distinguished in the literature. According to

Nonaka (1994), information, defined as ‘‘a flow of messages’’ (p. 15), differs from

knowledge, an organized flow of information. However, the terms ‘‘knowledge’’ and

‘‘information’’ are most often considered to be interchangeable in the literature. Bartol and

Srivastava (2002) and Wang and Noe (2010) suggest that there is little practical value in

distinguishing between knowledge and information in knowledge sharing research.

Therefore, in this study knowledge is understood as ‘‘information processed by

individuals including ideas, facts, expertise, and judgments relevant for individual, team,

and organizational performance’’ (Wang and Noe, 2010, p. 117). Knowledge sharing refers

to the provision of task information and know-how to help others and to collaborate with

others to solve problems, develop new ideas, or implement policies or procedures (Wang

and Noe, 2010, p. 117).

While knowledge is shared through face-to-face interactions, it can also be shared through

such channels as telephones or e-mail (Truran, 1998). According to Von Krogh et al. (2000),

knowledge is shared informally even in highly structured organizations. Employees often

share knowledge unconsciously through informal interactions (Swap et al., 2001; Taminiau

et al., 2009). This implies that knowledge can be shared without the specific intention to do

so. Examples of knowledge sharing include conversations over a cup of coffee and other

exchanges with the purpose of helping colleagues get something done better and in a more

efficient manner.

‘‘ Effective knowledge sharing is challenging becauseemployees cannot be compelled to do it. ’’

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Knowledge sharing in public sector organizations

Prior study of knowledge sharing has placed emphasis on similarities and differences

between private and public sector organizations, and factors that affect knowledge sharing.

Liebowitz and Chen (2003), for instance, found that it is more difficult to share knowledge in

public sector organizations because most people associate knowledge with power, and

their promotion opportunities. Other studies have focused on some of the factors that affect

knowledge sharing in the public sector. For instance, Seba et al. (2012) found that

organizational structure, leadership, time allocation, and trust could be barriers to

knowledge sharing in the Dubai police force. In a study of 50 private sector organizations,

Lin (2007) found that motivational factors such as reciprocal benefits, knowledge

self-efficacy, and enjoyment in helping others significantly affect employee knowledge

sharing attitudes and intentions. Most knowledge sharing studies, however, are conducted

in private sector organizations. Thus, there is a growing interest for further research on

knowledge sharing in the public sector.

Public sector organizations differ from private organizations in a number of ways (Milner,

2000). First, organizational goals in public organizations are typically more difficult to

measure and more conflicting than in private organizations, and they are affected differently

by political influences (Pandey and Wright, 2006). Second, public organizations can be very

different from one another, based on ownership of the organization, funding, and control

(Willem and Buelens, 2007). Other differences include fragmented authority and less

incentive for efficiency (Heffron, 1989).

Factors affecting knowledge sharing

Effective knowledge sharing is challenging because employees cannot be compelled to do

it. Therefore it is important to understand the factors that affect employees’ willingness to

share. Several models presenting factors that affect knowledge sharing have been tested in

a variety of organizational settings. Some of the variables investigated were analyzed at the

individual level, while others examined variables at the team or community level. For

instance, Kim and Lee (2006) examined the impact of organizational structure,

organizational culture, and information technology on employee knowledge sharing

capabilities. Riege (2005) suggested three-dozen barriers to knowledge sharing, including

individual barriers such as formal power and age and gender differences, potential

organizational barriers, and potential technology barriers. Ardichvili (2008) proposed that

the following factors affect individuals’ willingness to share knowledge:

B motivation factors (personal benefits, community-related considerations, and normative

considerations);

B barriers (interpersonal, procedural, technological, cultural); and

B enablers (supportive corporate culture, trust, tools).

Few of those factors have been tested empirically. Furthermore, the empirical research

suggests a lack of consensus on the key determinants of knowledge sharing.

Research design

This article draws on Ardichvili’s (2008) proposed model to identify some determinants of

knowledge sharing among employees in public sector organizations. Ardichvili (2008)

suggested that motivational factors, enablers, and barriers influence knowledge sharing.

‘‘ A shared vision should therefore influence the quantity ofknowledge shared. ’’

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Motivational factors

Motivation is a necessary prerequisite for knowledge sharing (e.g. Ardichvili, 2008; Zboralski

et al., 2006). Because knowledge resides within individuals, knowledge cannot be shared

effectively if individuals are not motivated to share it. Therefore, it is important to gain a better

understanding of the factors that motivate knowledge sharing. Three categories of

motivating factors have an impact on an individual’s willingness to share knowledge with

other employees: personal benefits, community-related considerations, and normative

considerations.

Individuals may be motivated to share knowledge with others because they expect

knowledge sharing to be advantageous to them (Hall, 2001). Personal benefits from

knowledge sharing identified in the literature include:

B status and career advancement;

B a better professional reputation;

B emotional benefits; and

B intellectual benefits.

Another motivator, community-related considerations, refers to the moral obligation that

individuals feel to advance or benefit others in their network. Ardichvili’s (2008) framework

identified three community-related considerations that may influence one’s motivation to

share knowledge:

1. sharing knowledge to establish ties with people one collaborates with;

2. sharing knowledge as a means to build a stronger community; and

3. sharing knowledge to strengthen one’s position in a community.

Normative considerations, which refer to organizational norms to which employees are

expected to adhere, take into account values and cultural norms that may lead an individual

to share his or her knowledge. Values affect goals, attitudes, and behaviors. Individuals who

have common values and a shared vision are likely to share knowledge (Alavi et al., 2006;

Chiu et al., 2006). A shared vision should therefore influence the quantity of knowledge

shared. The following research question is proposed:

RQ1. What is the relative and unique contribution of motivational factors (personal

benefits, community-related considerations, and normative considerations) on

explaining the variance in knowledge sharing in a public sector organization?

Enablers

Besides the three aforementioned categories of motivational factors, willingness to share

knowledge can be further encouraged by a number of enablers. Enablers of knowledge

sharing include organizational culture, social capital, and trust. Once an individual is

motivated to participate in knowledge sharing activities, enablers facilitate the actual

provision of information.

Several studies have identified a link between organizational climate and knowledge sharing

(e.g. Janz and Prasarnphanich, 2003). Organizational climate determines values, beliefs,

and work systems that encourage or hinder both learning and knowledge sharing (Janz and

Prasarnphanich, 2003). If the organizational climate is not conducive to knowledge sharing,

then individuals will not be willing to engage in such behaviors. A climate of sharing will

‘‘ Organizational support also had a moderating effect ofpersonal benefits on knowledge sharing. ’’

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influence employees’ attitudes toward knowledge sharing (Zboralski et al., 2004, Yang,

2007). An open and caring climate is also important to knowledge management, as it

encourages interaction among individuals, which facilitates knowledge sharing (Alavi et al.,

2006; Janz and Prasarnphanich, 2003). Organizational climate may also act as barrier to

knowledge sharing.

Another factor that enables knowledge sharing is trust. For tacit knowledge to be transferred

successfully there must be trust and mutual understanding (e.g. Ardichvili, 2008; Ardichvili

et al., 2003). In their study of factors that influence knowledge sharing, Ardichvili et al. (2003)

found that participants will be more inclined to use the knowledge made available if they

trust it to be a reliable and objective source of information. Thus, trust leads to greater

openness between individuals (Garavan et al., 2007), encourages sharing of knowledge

and willingness to collaborate with others (Liao, 2006; Sharratt and Usoro, 2003).

Two dimensions of social capital relevant to knowledge sharing are structural capital and

social interaction. The structural dimension of social capital manifests itself in several ways,

including through the norm of reciprocity. Reciprocity refers to the sharing of knowledge that

is mutual and that both parties perceive as fair (Chiu et al., 2006). While Chiu et al. (2006)

identified a positive relationship between norm of reciprocity and knowledge sharing,

McLure Wasko and Faraj (2005) found a negative relationship between the two. Social

interaction was found to influence significantly the extent to which knowledge sharing

happens (Chiu et al., 2006; Inkpen and Tsang, 2005; Nahapiet and Ghoshal, 1998). This is

because social interaction enables individuals to increase the depth, breadth, and efficiency

of the knowledge they share with one another. Thus, social capital may be considered a

contributing factor to one’s willingness to share knowledge. The following research question

is proposed:

RQ2. What is the relative and unique contribution of enablers (organizational climate,

trust, social capital) on explaining the variance in knowledge sharing in a public

sector organization?

Barriers

In spite of their motivation to share knowledge and enabling factors facilitating such

exchange, employees might also be faced with organizational barriers preventing the

diffusion of knowledge. Barriers that may prevent employees from sharing knowledge with

colleagues include organizational climate and organizational structure. When barriers can

be removed and knowledge sharing promoted, employees can more effectively disseminate

and manage their knowledge.

The climate in which individuals work has an impact on knowledge sharing (Zarraga and

Bonache, 2003). For instance, in organizations where individual competition is emphasized,

employees will not be likely to share knowledge with others at work (e.g. Schepers and van

den Berg, 2007; Willem and Scarbrough, 2006). The construct of organizational climate has

numerous dimensions. To investigate organizational climate as barriers to knowledge

sharing, Zarraga and Bonache (2003) used two dimensions:

1. degree of active empathy and lenience in judgment; and

2. degree of courage.

Active empathy and lenience in judgment is defined as ‘‘offering judgments and opinions of

the actions or ideas, but with clemency’’ (Zarraga and Bonache, 2003, p. 1231). Degree of

courage refers to individuals’ freedom to express their opinion without fear. Lack of empathy

and lack of courage to express oneself can act as a barrier to knowledge sharing.

According to Kim and Lee (2006), few studies have investigated how organizational

structure impacts knowledge sharing in public and private sector organizations. Sharratt

and Usoro (2003), found that ‘‘organizations with a centralized, bureaucratic management

style can stifle the creation of new knowledge, whereas a flexible decentralized

organizational structure encourages knowledge-sharing, particularly of knowledge that is

more tacit in nature’’ (p. 189). Similarly, Tsai (2002) found that centralization could reduce

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individuals’ interest in sharing knowledge with other units within an organization. Conversely,

knowledge sharing will increase among organizational units when formalization is low in the

organization structure (Lin, 2008). Thus, organizational structure may have an impact on

knowledge sharing. This leads to the following exploratory research question:

RQ3. What is the relative and unique contribution of barriers (organizational climate and

organizational structure) on explaining the variance in knowledge sharing in a

public sector organization?

In their review of the literature on knowledge sharing in public organizations, Yang and

Maxwell (2012) identified a number of questions that are yet to be investigated in empirical

research. This includes whether certain factors are more important than others in the

framework of intra-organizational information sharing. Yang and Maxwell (2012) also

suggested that enablers, motivators, and barriers can affect each other. According to

Heppner et al. (2008), ‘‘examining [. . .] moderating effects among variables are two

common research strategies for understanding more complex relationships among

variables’’ (pp. 250-1). For instance, trust may have a moderating effect on workplace

behaviors (Dirks and Ferrin, 2001). Additionally, organizational climate can have a

moderating effect on knowledge sharing (e.g. van den Hooff and de Ridder, 2004), and the

level of social capital may influence the relationship between one’s willingness to share

knowledge and knowledge sharing behaviors (Cabrera and Cabrera, 2005). Therefore, it is

proposed in the current study that enablers may moderate the relationship between

motivators and knowledge sharing. Previous research showed that organizational climate (Li

et al., 2010) and organizational structure (Du et al., 2007; Yang and Maxwell, 2012)

influenced knowledge sharing behavior. Based on prior research, the moderating effect

barriers may have on knowledge sharing will also be investigated. However, because of the

weak evidence of the effect of intrinsic factors such as degree of empathy (McLure Wasko

and Faraj, 2005), the moderating role of the degree of empathy will not be investigated. The

following research question ensues:

RQ4. What is the moderating effect of enablers and barriers on the relationship between

motivators and knowledge sharing in a public sector community of practice?

Figure 1 summarizes the relationships between motivators, enablers, barriers, and

knowledge sharing.

Figure 1 The research model

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Method

This article proposes a model of the factors that affect knowledge sharing in a public sector

organization. A questionnaire was used to collect data from the employees.

Questionnaire design

Questionnaires are an efficient way to collect data as they allow an opportunity to generate a

larger sample of respondents and can be used for statistical analysis (Snow and Thomas,

1994). A 72-item questionnaire with a seven-point Likert type scale was used to collect data

(1 ¼ “strongly disagree’’; 7 ¼ “strongly agree’’). Determinants of knowledge sharing in the

proposed model include the following constructs:

B motivators (personal benefits, community-related considerations, and normative

considerations);

B enablers (organizational culture, trust, and social capital); and

B barriers (organizational climate, and organizational structure).

All constructs were measured using multiple items. The variables tested in this study are

defined in Table I.

Table I Source of measurement items

Constructs Source Definition

Knowledge sharing activities Kim and Lee (2006) Task information and know-how to help others and tocollaborate with others to solve problems, develop new ideas,or implement policies or procedures

Community-related considerations Chiu et al. (2006) ‘‘A knowledge contributor’s judgment of likely consequencesthat his or her knowledge sharing behavior will produce’’ (p.1876) to a community

Personal benefits Chiu et al. (2006) ‘‘Knowledge contributor’s judgment of likely consequencesthat his or her knowledge sharing behavior will produce to himor herself’’ (p. 1876)

Normative considerations Levin et al. (2002) Shared values and vision, and norms

Rewards Janz and Prasarnphanich (2003) ‘‘A measure of how well the organization recognizesemployee performance with rewards’’ (p. 360).

Organizational support Janz and Prasarnphanich (2003) ‘‘Support is a measure of the organization’s interest in thewelfare of the employee’’ (p. 360)

Trust Chiu et al. (2006) ‘‘A set of specific beliefs dealing primarily with the integrity,benevolence, and ability of another party’’ (p. 1877)

Social interaction Chiu et al. (2006) ‘‘Social interaction ties represent the strength of therelationships, and the amount of time spent, andcommunication frequency among members of virtualcommunities’’ (pp. 1876-7)

Reciprocity Chiu et al. (2006) ‘‘Actions that are contingent on rewarding reactions fromothers and that cease when these expected reactions are notforthcoming’’ (p. 1877)

Degree of courage Zarraga and Bonache (2003) An individual’s ability to express his or her opinions withoutfear

Degree of empathy Zarraga and Bonache (2003) Feeling of freedom in individuals, leading to share knowledgeand experiences with others

Centralization Kim and Lee (2006) ‘‘Degree to which power and authority are concentrated at theorganization’s higher levels’’ (p. 373)

Formalization Kim and Lee (2006) ‘‘The degree to which are manifest in written documentsregarding procedures, job descriptions, regulations, andpolicy manuals’’ (p. 374)

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Measurement items were adapted from the literature, with minor modifications to ensure

contextual consistency. Each variable was investigated using previously validated

subscales. Cronbach’s a reliability estimates for the variables can be found in Table II.

The questionnaire consisted of two parts. In the first part, items addressed factors

influencing one’s willingness to share knowledge. Questionnaire items pertaining to personal

benefits asked the participants’ agreement or disagreement with statements such as

‘‘Sharing my knowledge will help me to make friends with coworkers’’ or ‘‘Sharing my

knowledge will strengthen the tie between coworkers in my department and me’’. The

second part gathered demographics information about the respondents, such as age, years

of employment at the public institution, gender, and job title. Negative items were included to

check for consistency of response. The instrument was piloted with individuals from the

research population.

Data collection procedures

The questionnaires were e-mailed to 1,738 civil service employees at a mid-size public

academic institution in the Midwest. They represent a large number of job groups, from

professional to service/maintenance, which makes them representative of the workforce in

other public organizations. Participants were sent one e-mail reminder, ten days after the first

request. The majority of the respondents (314) completed the survey after the first e-mail

request. The remaining 147 questionnaires were received after the follow up e-mail. Of the

1,738 individuals who were e-mailed the questionnaire, 461 returned completed

questionnaires, resulting in a 26.5 percent response rate. However, 22 returned

questionnaires were only half complete and, therefore, were discarded leaving 439

questionnaires to be analyzed. As a result, the response rate for usable questionnaires was

reduced to 25.3 percent.

The respondents’ profiles can be found in Table III. The majority of civil service employees

were over 46 years old (65 percent), females (73.8 percent), and held a Bachelor’s degree

(45.6 percent). Most respondents reported having been employed by the institution for over

21 years (27.1 percent), followed by relatively recent hires – less than five years (22.8

percent).

To determine whether there was non-response error, early respondents were compared to

late respondents on two key variables – i.e. knowledge sharing and trust (Table IV) – using

an independent t-test (Lindner et al., 2001). Early respondents were those individuals who

completed the questionnaire within the deadline after receiving the first e-mail. Individuals

who responded to the subsequent e-mail were labeled late responders. The independent

sample t-test analysis indicated that there was no statistically significant difference between

the mean of the later respondents and that of early respondents on the subscale knowledge

Table II Cronbach’s a reliability estimates

Factors Constructs Source Cronbach’s a

Knowledge sharing Knowledge sharing activities Kim and Lee (2006) 0.89

Motivators Community related considerations Chiu et al. (2006) 0.91Personal benefits Chiu et al. (2006) 0.91Normative considerations Levin et al. (2002) 0.82

Enablers Rewards Janz and Prasarnphanich (2003) 0.75Organizational support Janz and Prasarnphanich (2003) 0.61Trust Chiu et al. (2006) 0.89Social interaction Chiu et al. (2006) 0.90Reciprocity Chiu et al. (2006) 0.88

Barriers Degree of courage Zarraga and Bonache (2003) 0.75Degree of empathy Zarraga and Bonache (2003) 0.75Centralization Kim and Lee (2006) 0.85Formalization Kim and Lee (2006) 0.75

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sharing activities (KSA), tð437Þ ¼ 20:465, p ¼ 0:642 (two-tailed). The results are

comparable for trust, the other variable selected for this analysis.

Data analysis

The model shown in Figure 1 was analyzed using regression. According to McNabb (2004),

although inferential statistics should only be used when data are collected from a sample,

inferential statistics may still be used to analyze population data. Therefore, inferential

statistical methods were used to answer the research questions. RQ1-RQ3 sought to identify

Table IV Comparison of later and early respondents for non-response error

Levene’s test forequality ofvariances t-test for equality of meansF Sig. t df Sig. (two-tailed) Mean difference SE difference

KSAEqual variances assumed 0.494 0.482 20.465 437 0.642 20.113 0.244Equal variance not assumed 20.465 430.273 0.642 20.113 0.244

TrustEqual variances assumed 2.904 0.089 0.663 437 0.508 0.362 0.546Equal variance not assumed 0.663 429.201 0.508 0.362 0.546

Table III Profiles of respondents

Demographic characteristics Number of responses Percentage

GenderMale 109 24.8Female 324 73.8No response 6 1.4

Age18-25 11 2.526-35 49 11.236-45 89 20.346-55 178 40.556 and up 109 24.8No response 3 0.7

Education levelLess than high school 1 0.2High school 15 3.4Some college 144 32.8Bachelor’s degree 200 45.6Master’s degree 72 16.4Doctorate 5 1.1No response 2 0.5

Work experienceLess than five years 100 27.116-20 years 60 13.7Over 21 years 119 27.1No response 160 36.4

Job titlesClerks 46 10.48Office managers 39 8.88Accountants 36 8.20Office support specialists 24 5.47Office administrators 24 5.47No response 75 17.08Others 195 44.42

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the relative contribution of three categories of independent variables (motivators, enablers,

and barriers) in explaining the variance in knowledge sharing. RQ4 investigated the

moderating effect of enablers and barriers on the relationship between motivators and

knowledge sharing. A stepwise regression analysis was performed to investigate RQ1-RQ3.

The moderating effect of enablers and barriers on motivational factors was analyzed using

multiple regression.

Results

All motivators, community-related considerations (b ¼ 0:328, p , 0:001), normative

considerations (b ¼ 0:967, p , 0:001), and personal benefits (b ¼ 20:312, p , 0:01),

significantly contributed to the variance in knowledge sharing (adjusted R 2 ¼ 0:425). All

three motivating factors could explain up to 42.5 percent of the total variance in knowledge

sharing. The best predictor of knowledge sharing was community-related considerations,

which alone explained 39 percent of the variance in knowledge sharing (adjusted

R 2 ¼ 0:396). Personal benefits’ negative b value suggests that willingness to share

knowledge decreases as personal benefits increase.

Three enabling factors – i.e. social interaction (b ¼ 0:585, p , 0:001), rewards

(b ¼ 20:090, p , 0:05), and organizational support (b ¼ 20:563, p , 0:01), had a

significant main effect on the variance in knowledge sharing. Reciprocity was included in

the model although it did not have a significant main effect on knowledge sharing

(b ¼ 20:008, p . 0:05). These three enablers together could explain 1.3 percent of the total

variance in knowledge sharing (DR 2 ¼ 0:058). Surprisingly, the variable ‘‘trust’’ was

excluded from the model. Both dimensions of organizational climate, rewards and

organizational support, were negatively related to knowledge sharing. Degree of empathy

(b ¼ 0:345, p , 0:001), and degree of courage (b ¼ 0:337, p , 0:05) significantly

contributed to the variance in knowledge sharing. Those two barriers together could

explain 7 percent of the total variance in knowledge sharing (DR 2 ¼ 0:073). The

organizational structure variables, centralization and formalization, were not included in

the model.

The interaction term ‘‘normative considerations £ social interaction’’ (b ¼ 20:869,

p , 0:001) was significant in predicting one’s willingness to engage in knowledge sharing

activities. Similarly, the interaction terms ‘‘personal benefits £ organizational support’’

(b ¼ 0:839, p , 0:01), and ‘‘normative considerations £ degree of courage’’ (b ¼ 20:487,

p , 0:05), had a significant moderating effect on the relationship between motivators and

knowledge sharing activities. The results of the regression analysis can be found in Table V.

A model generated by the stepwise regression analysis, which was statistically significant

(p ¼ 0:036), explained 58 percent of the variance in knowledge sharing (adjusted

R 2 ¼ 0:583). This suggests that the variables included in the model are good at predicting

knowledge sharing activities (Figure 2).

Discussion

This research has proposed a model of the factors that affect knowledge sharing in a public

sector organization. Contrary to what was expected, personal benefits were negatively

related to knowledge sharing. Personal benefits’ negative b value suggests that willingness

to share knowledge decreases as personal benefits increase. This finding is not consistent

with most of the knowledge sharing literature (e.g. Ardichvili, 2008; Chiu et al., 2006; McLure

Wasko and Faraj, 2005). A possible explanation for this result could be that in some cases

the cost of sharing knowledge might outweigh the personal benefits. For instance,

individuals willing to share knowledge would lose their unique value to organizations that

value expertise but not mentoring or assisting others (Bock et al., 2005). Thus, the lack of

sufficient personal outcome could constitute a barrier to knowledge sharing. This finding

also indicates that department managers at this public institution should promote a culture

that encourages civil service employees to share their knowledge with others in their units or

departments.

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Reciprocity was not statistically significant in predicting the variance of knowledge sharing.

Although not consistent with most of the literature, this result supports Huang et al.’s (2008)

finding. According to Huang et al. (2008), an anticipated reciprocal relationship does not

significantly influence one’s willingness to share knowledge. In their study, knowledge was

shared to make work more effective, not because individuals expected the same in return.

The results from the regression analysis indicated a statistically significant negative

relationship between knowledge sharing and both dimensions of organizational climate,

i.e. rewards and organizational support. This finding is consistent with prior research. Bock

and Kim (2002) found that expected rewards were negatively related to knowledge sharing.

Rewards’ negative b value might be explained by the fact that rewards can strain the

relationship between those who win and those who do not, or that rewards weaken intrinsic

motivation (Kohn, 1993). Organizational support’s negative b value is inconsistent with the

literature, suggesting that the relationship between organizational support and knowledge

sharing may be contingent on other factors, such as commitment to the organization (King

and Marks, 2008).

Trust was not a significant predictor of one’s willingness to share knowledge. Additionally,

trust did not have a significant interaction effect on the relationship between knowledge

sharing and the three motivators included in the study, i.e. community related

considerations, normative considerations and personal benefits. This finding is surprising

because trust is generally associated with willingness to share knowledge (e.g. Ardichvili,

2008; Huang et al., 2008). Others have, to a certain extent, contradicted this view. For

instance, Chiu et al. (2006) found that trust did not have a significant impact on the quantity

of knowledge shared. According to Chiem (2001), most public sector employees tend to

believe that knowledge sharing leads to loss of power, resulting in their unwillingness to

share knowledge with coworkers. Additionally, if the knowledge shared is not seen as

sensitive or otherwise important, trust might not be needed for one to be willing to share it.

None of the measures of organizational structure, formalization and centralization, had a

significant effect on knowledge sharing. This particular finding may be explained by the fact

that not all public organizations are bureaucratic (Boyne, 2002). However, the findings could

differ in other types of public sector organization.

Table V Determinants of knowledge sharing

Regression modelVariables b R Adjusted R 2 Sig. F change

Main effectsMotivational factorsCommunity related considerations 0.328***Normative considerations (NC) 0.967***Personal benefits (PB) 20.312**

Block 1 0.655 0.425 0.028EnablersSocial interaction (SOCI) 0.585***Reciprocity 20.008Rewards 20.090*Support (SUP) 20.563**

Block 2 0.701 0.483 0.001BarriersDegree of empathy 0.345***Degree of courage 0.337*

Block 3 0.752 0.556 0.016

Interaction effectsNC £ SOCI 20.869***PB £ SUP 0.839**NC £ COUR 20.487*Block 4 0.771 0.583 0.036

Notes: *p , 0:05; **p , 0:01; ***p , 0:001

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The interaction effect of social interaction and degree of courage on normative consideration

was significant, suggesting that social interaction and degree of courage moderated the

effects of norm considerations on knowledge sharing. The findings indicate that as the

interaction term normative consideration £ social interaction increases, the effects of norm

considerations on knowledge sharing decline. Thus, the more employees in this organization

interact with each other, the less they feel compelled to adhere to group norms. This finding

is counterintuitive. According to Knight Lapinski and Rimal (2005) ‘‘special circumstances

exist, however, when collective action is detrimental to individual well-being’’ (p. 128). Thus,

in instances where employees’ values and goals are not congruent with those of colleagues,

the behavior would not be aligned with group norms. Similarly, the interaction term norm

considerations £ degree of courage can decrease the influence of norms when individuals

do. This result could be interpreted to mean that norms in the respondents’ work

environments discouraged open and frank exchanges among coworkers.

Organizational support also had a moderating effect of personal benefits on knowledge

sharing. The positive beta coefficient of the product terms (PB £ SUP) indicates that as the

amount of support increased, so did the effect of personal benefit on knowledge sharing.

Personal benefits from knowledge sharing include the positive feelings one experiences

from feeling useful. This result suggests that such positive feelings increase in a supportive

culture. Managers in public sector organizations should recognize the importance of an

encouraging and supportive culture that could weaken barriers in their environment that

value personal technical expertise (Snowden, 2000, p. 143).

Figure 2 Results of the regression analysis

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The bureaucratic nature of many government organizations, where knowledge does not

easily flow to other departments or agencies, is not conducive to knowledge sharing and

comprehensive knowledge management initiatives. Identifying factors that influence

knowledge sharing could help practitioners create a knowledge sharing culture that is

needed to support knowledge sharing and knowledge management within public sector

organizations. Managers in public sector organizations could encourage the development

of communities of practice to support knowledge sharing. Tacit knowledge is acquired by

interacting with others, and can only be shared between individuals in the same place or in

different locations if a social network exists (Yang and Chen, 2008). One way for knowledge

management practitioners to overcome this difficulty is through the use of human networks

such as communities of practice. Human networks are a key medium for sharing knowledge.

According to Snowden (1998), individuals and communities can gain greater access to

explicit knowledge and increase knowledge sharing through the creation of communities of

practice.

A comparison of the factors investigated in private and public sector organizations in recent

knowledge sharing literature suggests that the private or public nature of the organizations

may not have a significant influence on these factors, or the differences between the two are

not as pronounced as often thought (Tables VI and VII). Indeed, some of the factors

investigated so far seem to have similar effect on knowledge sharing, whether the studies

were conducted in private or public sector organizations. This implies that successful

Table VI Factors influencing knowledge sharing in private sector organizations

Chenand

Hung(2010)

Linet al.

(2008)

Linet al.

(2009)

Chowand

Chan(2008)

KimandLee

(2006)Lin

(2007)

McClureMcLure

Wasko andFaraj

(2005)

Yuet al.

(2010)

Qianet al.

(2007)

Al-Alawiet al.

(2007)

Lam andLambermont-Ford

(2010)

Trust £ £ £ £ £

Knowledgenetworks £

Social networks £ £ £

Reward £ £

Technologyinfrastructure £ £

Knowledge sharingself-efficacy £ £ £ £ £

Perceived relativeadvantage £ £

Fairness £

Identification £

Openness £

Enjoyment in helpingothers £ £ £

Sharing/organizationculture £ £ £

Learning orientationOpen leadershipclimateSubjective norms £

ManagementsupportReciprocal benefits £ £

Motivation £

Shared goals £

ReciprocationReputation £

Vision and goals £

Leadership £

Communication £ £

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knowledge management practices used in the private sector can also be applied in the

public sector. Further research is needed to ascertain the extent of the differences between

both types of organizations, and how they affect knowledge sharing practices in these

organizations.

Conclusions and implications

This research proposed a model of some factors affecting an individual’s knowledge sharing in

the context of a public sector organization. A model generated by the stepwise regression

analysis, which was statistically significant (p ¼ 0:036), explained 58 percent of the variance in

knowledge sharing (adjusted R 2 ¼ 0:583). Community-related considerations were found to

be the strongest predictor to knowledge sharing in the organization of interest. Therefore,

public sector managers will need to pay particular attention to programs and activities they can

design to develop a sense of community among co-workers. Further research could establish

whether other factors such as diversity contribute to the variance in knowledge sharing.

Public sector organizations seeking to encourage or facilitate knowledge management

among their employees could encourage the formation of communities of practice. Studies

like this one can be used to create strategies to develop and sustain knowledge sharing

among employees. Although encouraging knowledge sharing might not translate into actual

use of that knowledge, public organizations can create appropriate conditions for

knowledge sharing to occur if they know which factors to influence. Prior studies have

established a link between employee engagement and lower turnover and improved

employee performance. Further research could investigate the extent to which communities

of practice can be used not only to aid with knowledge management, but also to encourage

employee engagement.

There are three limitations to the research findings. First, there are many organizational forms

operating within the public sector (Wettenhall, 2003; Willem and Buelens, 2007). Since this

study was conducted in a single public higher education institution and data were collected

frommostly lower level employees, the findings cannot be generalized to other public sector

workers. As a result, factors that influence people’s willingness to share knowledge and the

recommendations from this study may vary in different contexts. Alternatively, extending this

study using a larger sample with more balanced representation, and possibly across

different public sector organizations, will give some indication of the relevance of these

findings to other public sector workers. Second, attitudes toward knowledge sharing, and

knowledge sharing behaviors vary across national cultures. Additionally, there are a number

Table VII Factors influencing knowledge sharing in public sector organizations

Friesl et al.(2011)

Willem and Buelens(2007)

Sandhu et al.(2011)

Seba et al.(2012)

Syed-Ikhsan and Rowland(2004)

Kim and Lee(2006)

Trust £ £

Knowledge networks £

Reward £

IT systems £ £ £

Organizational structure £ £

Formalization £

Organizational context £

Social identification £

Lateral coordination £

Power games £

Organization design £

Recognition £

Time £ £

Interaction £

Interpersonal skills £

Leadership £

Sharing culture £

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of subcultures within a national culture (Michailova and Hutchings, 2006). This may limit the

applicability of the findings to other countries or regions. Third, the study used self-reporting

data gathered via questionnaires. Self-reporting data may create a response bias, which

may also limit the relevance of this study’s findings to other public sector employees.

References

Al-Alawi, A.I., Al-Marzooqi, N.Y. and Mohammed, Y.F. (2007), ‘‘Organizational culture and knowledge

sharing: critical success factors’’, Journal of Knowledge Management, Vol. 11 No. 2, pp. 22-42.

Alavi, M., Kayworth, T.R. and Leidner, D.E. (2006), ‘‘An empirical examination of the influence of

organizational culture on knowledge’’, Journal of Management Information Systems, Vol. 22 No. 3,

pp. 191-224.

Ardichvili, A. (2008), ‘‘Learning and knowledge sharing in virtual communities of practice: motivators,

barriers, and enablers’’, Advances in Developing Human Resources, Vol. 10 No. 4, pp. 541-554.

Ardichvili, A., Page, V. and Wentling, T. (2003), ‘‘Motivation and barriers to participation in online

knowledge-sharing communities of practice’’, Journal of Knowledge Management, Vol. 7 No. 1, pp. 64-77.

Bartol, K.M. and Srivastava, A. (2002), ‘‘Encouraging knowledge sharing: the role of organizational

reward systems’’, Journal of Leadership and Organizational Studies, Vol. 9 No. 1, pp. 64-76.

Bock, G. and Kim, Y. (2002), ‘‘Breaking the myths of rewards: an exploratory study of attitudes about

knowledge sharing’’, Information Resources Management Journal, Vol. 15 No. 2, pp. 14-21.

Bock, G.W., Zmud, R.W., Kim, Y.G. and Lee, J.N. (2005), ‘‘Knowledge sharing: examining the roles of

extrinsic motivators, social-psychological forces, and organizational climate’’, MIS Quarterly, Vol. 29

No. 1, pp. 87-111.

Boyne, G.A. (2002), ‘‘Public and private management: what’s the difference?’’, Journal of Management

Studies, Vol. 39 No. 1, pp. 97-122.

Cabrera, E. and Cabrera, A. (2005), ‘‘Fostering knowledge sharing through people management

practices’’, International Journal of Human Resource Management, Vol. 16 No. 5, pp. 720-735.

Chen, C.J. and Hung, S.W. (2010), ‘‘To give or to receive? Factors influencing members’ knowledge

sharing and community promotion in professional virtual communities’’, Information & Management,

Vol. 47 No. 4, pp. 226-236.

Chiem, P.X. (2001), ‘‘In the public interest: government employees also need incentives to share what

they know’’, Knowledge Management Magazine, August.

Chiu, C.M., Hsu, M.H. and Wang, E.T.G. (2006), ‘‘Understanding knowledge sharing in virtual

communities: an integration of social capital and social cognitive theories’’, Decision Support Systems,

Vol. 42 No. 3, pp. 1872-1888.

Chow, W.S. and Chan, L.S. (2008), ‘‘Social network, social trust and shared goals in organizational

knowledge sharing’’, Information & Management, Vol. 45 No. 7, pp. 458-465.

Dirks, K.T. and Ferrin, D.L. (2001), ‘‘The role of trust in organizational settings’’, Organization Science,

Vol. 12 No. 4, pp. 450-467.

Du, R., Ai, S. and Ren, Y. (2007), ‘‘Relationship between knowledge sharing and performance: a survey

in Xi’an, China’’, Expert Systems with Applications, Vol. 32 No. 1, pp. 38-46.

Felin, T. and Hesterly, W.S. (2007), ‘‘The knowledge-based view, nested heterogeneity, and new value

creation: philosophical considerations on the locus of knowledge’’, Academy of Management Review,

Vol. 32 No. 1, pp. 195-218.

Friesl, M., Sackmann, S.A. and Kremser, S. (2011), ‘‘Knowledge sharing in new organizational entities:

the impact of hierarchy, organizational context, micro-politics and suspicion’’, Cross Cultural

Management: An International Journal, Vol. 18 No. 1, pp. 71-86.

Garavan, T.N., Carbery, R. and Murphy, E. (2007), ‘‘Managing intentionally created communities of

practice for knowledge sourcing across organizational boundaries: insights on the role of the CoP

manager’’, The Learning Organization: The International Journal of Knowledge and Organizational

Learning Management, Vol. 14 No. 1, pp. 34-49.

PAGE 468 j JOURNAL OF KNOWLEDGE MANAGEMENTj VOL. 17 NO. 3 2013

Dow

nloa

ded

by S

EG

i Int

erna

tiona

l Bhd

At 1

9:15

17

Janu

ary

2015

(PT

)

Hall, H. (2001), ‘‘Social exchange for knowledge exchange’’, paper presented at the International

Conference on Managing Knowledge, University of Leicester, Leicester.

Hara, N. and Hew, K.F. (2007), ‘‘Knowledge-sharing in an online community of healthcare

professionals’’, Information Technology & People, Vol. 20 No. 3, pp. 235-261.

Heffron, F. (1989), Organization Theory and Public Organizations, Prentice Hall, New York, NY.

Heppner, P.P., Kivlighan, D.M. Jr and Wampold, B.E. (2008), Research Design in Counseling, 3rd ed.,

Brooks Cole, Belmont, CA.

Huang, Q., Davison, R.M. and Gu, J. (2008), ‘‘Impact of personal and cultural factors on knowledge

sharing in China’’, Asia Pacific Journal of Management, Vol. 25, pp. 451-471.

Inkpen, A.C. and Tsang, E.W.K. (2005), ‘‘Social capital, networks, and knowledge transfer’’, Academy of

Management Review, Vol. 30 No. 1, pp. 146-165.

Janz, B. and Prasarnphanich, P. (2003), ‘‘Understanding the antecedents of effective knowledge

management: the importance of a knowledge-centered culture’’, Decision Sciences, Vol. 34 No. 2,

pp. 351-384.

Kim, S. and Lee, H. (2006), ‘‘The impact of organizational context and information technology on

employee knowledge-sharing capabilities’’, Public Administration Review, Vol. 66 No. 3, pp. 370-385.

King, W.R. and Marks, P.V. Jr (2008), ‘‘Motivating knowledge sharing through a knowledgemanagement

system’’, Omega, Vol. 36 No. 1, pp. 131-146.

Knight Lapinski, M. and Rimal, R.N. (2005), ‘‘An explication of social norms’’, Communication Theory,

Vol. 15 No. 2, pp. 127-147.

Kohn, A. (1993), ‘‘Why incentive plans cannot work’’, Harvard Business Review, September/October,

pp. 54-63.

Kwok, S.H. and Gao, S. (2005), ‘‘Attitude towards knowledge-sharing behavior’’, Journal of Computer

Information Systems, Vol. 46 No. 2, pp. 45-51.

Lam, A. and Lambermont-Ford, J.P. (2010), ‘‘Knowledge sharing in organisational contexts: a

motivation-based perspective’’, Journal of Knowledge Management, Vol. 14 No. 1, pp. 51-66.

Land, S.M., Draper, D.C., Ma, Z., Hsieh, H.W., Smith, B.K. and Jordan, R. (2009), ‘‘An investigation of

knowledge building activities in an online community of practice at Subaru of America’’, Performance

Improvement Quarterly, Vol. 22 No. 3, pp. 23-36.

Levin, D., Lesser, E., Cross, R. and Abrams, L. (2002), ‘‘Trust and knowledge sharing: a critical

combination’’, white paper, IBM Institute for Knowledge-based Organizations, Cambridge, MA.

Li, Z., Zhu, T. and Luo, F. (2010), ‘‘A study on the influence of organizational climate on

knowledge-sharing behavior in IT enterprises’’, Journal of Computers, Vol. 5 No. 4, pp. 508-515.

Liao, L.F. (2006), ‘‘A learning organization perspective on knowledge-sharing behavior and firm

innovation’’, Human Systems Management, Vol. 25 No. 4, pp. 227-236.

Liebowitz, J. and Chen, Y. (2003), ‘‘Knowledge-sharing proficiencies: the key to knowledge

management’’, in Holsapple, C.W. (Ed.), Handbook on Knowledge Management 1: Knowledge

Matters, Springer-Verlag, Berlin, pp. 409-424.

Lin, H.F. (2007), ‘‘Effects of extrinsic and intrinsic motivations on employee intentions to share

knowledge’’, Journal of Information Science, Vol. 33 No. 2, pp. 135-149.

Lin, H.F., Lee, H.S. and Wang, D.W. (2008), ‘‘Evaluation of factors influencing knowledge sharing based

on a fuzzy AHP approach’’, Journal of Information Science, Vol. 35 No. 1, pp. 25-44.

Lin, M.J.J., Hung, S.W. and Chen, C.J. (2009), ‘‘Fostering the determinants of knowledge sharing in

professional virtual communities’’, Computers in Human Behavior, Vol. 25 No. 4, pp. 929-939.

Lin, W.B. (2008), ‘‘The effect of knowledge sharing model’’, Expert Systems with Applications, Vol. 34

No. 2, pp. 1508-1521.

Lindner, J.R., Murphy, T.H. and Briers, G.E. (2001), ‘‘The handling of non-response errors in social

science survey’’, Journal of Agricultural Education, Vol. 42 No. 4, pp. 43-53.

VOL. 17 NO. 3 2013 j JOURNAL OF KNOWLEDGE MANAGEMENTj PAGE 469

Dow

nloa

ded

by S

EG

i Int

erna

tiona

l Bhd

At 1

9:15

17

Janu

ary

2015

(PT

)

Luen, T.W. and Al-Hawamdeh, S. (2001), ‘‘Knowledge management in the public sector: principles and

practices in police work’’, Journal of Information Science, Vol. 27 No. 5, pp. 311-318.

McLure Wasko, M. and Faraj, S. (2005), ‘‘Why should I share? Examining social capital and knowledge

contribution in electronic communities of practice’’, MIS Quarterly, Vol. 29 No. 1, pp. 35-57.

McNabb, D.E. (2004), Research Methods for Political Science: Quantitative and Qualitative Methods,

M.E. Sharpe, Armonk, NY.

Michailova, S. and Hutchings, K. (2006), ‘‘National cultural influences on knowledge sharing:

a comparison of China and Russia’’, Journal of Management Studies, Vol. 43 No. 3, pp. 383-405.

Milner, E. (2000), Managing Information and Knowledge in the Public Sector, Routledge, London.

Nahapiet, J. and Ghoshal, S. (1998), ‘‘Social capital, intellectual capital, and the organizational

advantage’’, Academy of Management Review, Vol. 23 No. 2, pp. 242-266.

Nonaka, I. (1994), ‘‘A dynamic theory of organizational knowledge creation’’, Organization Science,

Vol. 5, pp. 14-37.

Pandey, S.K. and Wright, B.E. (2006), ‘‘Connecting the dots in public management: political

environment, organizational goal ambiguity, and the public manager’s role ambiguity’’, Journal of Public

Administration Research & Theory, Vol. 16 No. 4, pp. 511-532.

Qian, H., Davison, R.M. and Gu, J. (2008), ‘‘Impact of personal and cultural factors on knowledge

sharing in China’’, Asia Pacific Journal of Management, Vol. 25 No. 3, pp. 451-471.

Quigley, N.R., Tesluk, P.E. and Bartol, K.M. (2007), ‘‘Amultilevel investigation of themotivational mechanisms

underlying knowledge sharing and performance’’, Organization Science, Vol. 18 No. 1, pp. 71-88.

Riege, A. (2005), ‘‘Three-dozen knowledge-sharing barriers managers must consider’’, Journal of

Knowledge Management, Vol. 9 No. 3, pp. 18-35.

Sandhu, M.S., Jain, K.K. and Ahmad, I.U.K. (2011), ‘‘Knowledge sharing among public sector

employees: evidence from Malaysia’’, International Journal of Public Sector Management, Vol. 24 No. 3,

pp. 206-226.

Schepers, P. and van den Berg, P.T. (2007), ‘‘Social factors of work-environment creativity’’, Journal of

Business and Psychology, Vol. 21 No. 3, pp. 407-428.

Seba, I., Rowley, J. and Delbridge, R. (2012), ‘‘Knowledge sharing in the Dubai police force’’, Journal of

Knowledge Management, Vol. 16 No. 1, pp. 114-128.

Sharratt, M. and Usoro, A. (2003), ‘‘Understanding knowledge-sharing in online communities of

practice’’, Electronic Journal of Knowledge Management, Vol. 1 No. 2, pp. 187-196.

Silvi, R. and Cuganesan, S. (2006), ‘‘Investigating the management of knowledge for competitive

advantage: a strategic cost management perspective’’, Journal of Intellectual Capital, Vol. 7 No. 3,

pp. 309-323.

Siong, C.C., Salleh, K., Syed Noh Syed, A. and Syed-Ikhsan, S.O.S. (2011), ‘‘KM implementation in a

public sector accounting organization: an empirical investigation’’, Journal of Knowledge Management,

Vol. 15 No. 3, pp. 497-512.

Snow, C.C. and Thomas, J.B. (1994), ‘‘Field research methods in strategic management: Contributions

to theory building and testing’’, Journal of Management Studies, Vol. 31 No. 4, pp. 457-480.

Snowden, D. (1998), ‘‘A framework for creating a sustainable knowledge management program’’,

in Cortada, J.W. andWoods, J.A. (Eds), The Knowledge Management Yearbook 1999-2000, Butterworth

Heinemann, Oxford, pp. 52-64.

Snowden, D. (2000), ‘‘Liberating knowledge’’, in Rock, S. (Ed.), Liberating Knowledge, IBM/CBI, London.

Swap, W., Leonard, D., Shields, M. and Abrams, L. (2001), ‘‘Using mentoring and storytelling to transfer

knowledge in the workplace’’, Journal of Management Information Systems, Vol. 18 No. 1, pp. 95-114.

Syed-Ikhsan, S.O.S. and Rowland, F. (2004), ‘‘Knowledge management in a public organization: a study

on the relationship between organizational elements and the performance of knowledge transfer’’,

Journal of Knowledge Management, Vol. 8 No. 2, pp. 95-111.

Taminiau, Y., Smit, W. and de Lange, A. (2009), ‘‘Innovation in management consulting firms through

informal knowledge sharing’’, Journal of Knowledge Management, Vol. 13 No. 1, pp. 42-55.

PAGE 470 j JOURNAL OF KNOWLEDGE MANAGEMENTj VOL. 17 NO. 3 2013

Dow

nloa

ded

by S

EG

i Int

erna

tiona

l Bhd

At 1

9:15

17

Janu

ary

2015

(PT

)

Truran, W.R. (1998), ‘‘Pathways for knowledge: how companies learn through people’’, Engineering

Management Journal, Vol. 10 No. 4, pp. 15-20.

Tsai, W. (2002), ‘‘Social structure of ‘coopetition’ within a multiunit organization: coordination,

competition, and intraorganizational knowledge sharing’’, Organization Science, Vol. 13 No. 2,

pp. 179-190.

van den Hooff, B. and de Ridder, J.A. (2004), ‘‘Knowledge sharing in context: the influence of

organizational commitment, communication climate and CMC use on knowledge sharing’’, Journal of

Knowledge Management, Vol. 8 No. 6, pp. 117-130.

Von Krogh, G., Ichijo, K. and Nonaka, I. (2000), Enabling Knowledge Creation, Oxford University Press,

Oxford and New York, NY.

Wang, S. and Noe, R.A. (2010), ‘‘Knowledge sharing: a review and directions for future research’’,

Human Resource Management Review, Vol. 20 No. 2, pp. 115-131.

Wettenhall, R. (2003), ‘‘Exploring types of public sector organizations: past exercises and current

issues’’, Public Organization Review, Vol. 3 No. 3, Special Issue, pp. 219-245.

Willem, A. and Buelens, M. (2007), ‘‘Knowledge sharing in public sector organizations: the effect of

organizational characteristics on interdepartmental knowledge sharing’’, Journal of Public

Administration Research and Theory, Vol. 17 No. 4, pp. 581-606.

Willem, A. and Scarbrough, H. (2006), ‘‘Social capital and political bias in knowledge sharing: an

exploratory study’’, Human Relations, Vol. 59 No. 10, pp. 1343-1370.

Yang, J.-T. (2007), ‘‘Knowledge sharing: investigating appropriate leadership roles and collaborative

culture’’, Tourism Management, Vol. 28 No. 2, pp. 530-543.

Yang, S.J.H. and Chen, I.Y.L. (2008), ‘‘A social network-based system for supporting interactive

collaboration in knowledge sharing over peer-to-peer network’’, International Journal of

Human-Computer Studies, Vol. 66 No. 1, pp. 36-50.

Yang, T.M. and Maxwell, T.A. (2012), ‘‘Information-sharing in public organizations: a literature review of

interpersonal, intra-organizational and inter-organizational success factors’’, Government Information

Quarterly, Vol. 28, pp. 164-175.

Yu, T.K., Lu, L.C. and Liu, T.F. (2010), ‘‘Exploring factors that influence knowledge sharing behavior via

weblogs’’, Computers in Human Behavior, Vol. 26 No. 1, pp. 32-41.

Yusof, Z.M., Bakhari, I., Kamsuriah, A. and Yusof, M.M. (2012), ‘‘Knowledge sharing in the public sector

in Malaysia: a proposed holistic model’’, Information Development, Vol. 28 No. 1, pp. 43-54.

Zarraga, C. and Bonache, J. (2003), ‘‘Assessing the team environment for knowledge sharing:

an empirical analysis’’, International Journal of Human Resource Management, Vol. 14 No. 7,

pp. 1227-1245.

Zboralski, K., Gemuenden, H.G. and Lettl, C. (2004), ‘‘A members’ perspective on the success of

communities of practice: preliminary empirical results’’, Proceedings of the 5th European Conference on

Organizational Knowledge, Learning and Capabilities, Innsbruck.

Zboralski, K., Salomo, S. and Gemuenden, H.G. (2006), ‘‘Organizational benefits of communities of

practice: a two-stage information processing model’’, Cybernetics and Systems: An International

Journal, Vol. 37 No. 6, pp. 533-552.

About the author

Angela Titi Amayah is an Assistant Professor of Human Resource, in the Business,Management, and Economics area of study at SUNY Empire State College. Angela TitiAmayah can be contacted at: Angela.TitiAmayah@esc.edu

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