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Proceeding of 1st International Conference on Human Capital and Knowledge Management

KM - 1

Abstract – Prior literature has shown that the concept

of knowledge management (KM) has been applied in

public organisations in both developed and developing

countries. Prior studies share three themes: the use of

KM in organisations, KM implementation and, KM

issues and challenges. Opportunities seem to exist for

future research on knowledge management and

innovation in public organisations as this area remains

under-researched.

Keywords – knowledge management, public

organisation, innovation.

I. INTRODUCTION

Nowadays, knowledge is treated as an asset in

organisations. This entails that knowledge needs to be

managed effectively. The processes that deal with

“development, storage, retrieval, and dissemination of

information and expertise within an organisation to

support its business performance” have been referred to as

knowledge management” [21]. In managing knowledge,

organisations ought to first be aware of knowledge

characteristics. Tacit and explicit knowledge are two

types of knowledge characteristics that exist. Tacit

knowledge represents knowledge that people possess. It

has a personal quality that makes it hard to formalise and

communicate [32]. Individuals’ experiences and skills

characterise tacit knowledge. Explicit knowledge, on the

other hand, represents knowledge that can be codified in a

tangible form [33]. Explicit knowledge is transmittable in

formal and systematic language. Explicit knowledge

manifests in material form. Books and manuals are

identified as explicit knowledge [34; 46]. Explicit and

tacit knowledge are regarded as essential for the success

of any organisation [33; 31].

Perhaps, the early phase of knowledge management

(KM) practice started to be recognised in organisations in

1975 [27]. Knowledge then was the central focus. Further,

organisations at that time, did not rely on information

technology (IT) in their administration. The Information

Age sees the pervasive use of IT to manage knowledge.

The literature shows that over the years, the trends for

research in KM have been on:

1) Knowledge Creation – Knowledge is created through

the processes of conversion. The conversion creates

knowledge from tacit to explicit knowledge and vice

versa.

2) Knowledge Capture – this refers to the progress of

retrieving tacit knowledge before storage of

knowledge. Example of this is the discussion among

members. [42].

3) Knowledge Store – The storage of knowledge in

electronic databases, expert systems, and documented

of tacit knowledge [43].

4) Knowledge Sharing – the act of sharing knowledge

in organisations. Sharing is through individuals to

groups or groups to individuals via discussions,

forums, directly or through a virtual network [7].

5) Knowledge Dissemination – The process of

spreading the knowledge using technology, tools and

techniques as a mediator [42].

6) Knowledge Management System – (KMS) – Is a

collection of process of knowledge creation,

knowledge store, knowledge transfer/sharing and

application of it in organisations [24].

This trend has been coined as knowledge management

system (KMS) by Alavi [24] while some scholars defined

it as KM process. [13; 37; 38].

The paper aims at identifying KM topics that have

been previously researched on in public organisations.

The paper reviews the literature published between the

year 2000 and 2012 on knowledge management in public

organisations in developed and developing countries. The

outcome of this endeavour is envisaged to facilitate

investigations on an under-researched area in future.

II. LITERATURE REVIEW

In this section, we present prior literature that have

focused on KM in public organisations. Our emphasis is

on developed and developing countries.

The literature on KM in developed countries suggests

that KM has been investigated in Canada, United States of

America (USA), United Kingdom (UK), Netherlands and

Australia. On the other hand, India, Pakistan, Malaysia

and China have been the focus of researchers on KM in

developing countries.

Below we outline the observations on KM in public

organisations:

Unit of analysis – The unit of analysis for studies on KM

in public organisation in developed and developing

countries have used organisation [30; 47] and individual

[1].

Theme – The themes have been on the use of KM [16],

KM implementation [8] and, KM issues and challenges

A LITERATURE SURVEY ON KNOWLEDGE MANAGEMENT AND

PUBLIC ORGANISATIONS

H. M. Adnan*1, N. Mohamed

1

1International Business School, Universiti Teknologi Malaysia, Kuala Lumpur, Malaysia

(*[email protected])


KM - 2

[15; 39]. Use of KM refers to the application of a KM

model or framework in organisions as a method for

specific tasks such as knowledge sharing in organisations

[17]. KM implementation denotes taking actions using

KM in organisations as a solution to resolve specific

problems in an organisation [38; 22].

Typical KM issues and challenges have been cited as the

barriers and difficulties that arose in organisations while

applying or practicing KM in organisations [10]. The

barriers and difficulties hinder the organisations to apply

KM successfully [29]. For instance,there is no awareness

of KM in public organisation and the lack of IT

infrastructrure to implement it [10; 26; 42]. In addition,

the policy of centralisation in public organisation has been

cited as hindering public organisation’s full

implementation of KM [12].

Factors influencing success of KM – it has been cited

that among factors influencing success of KM in public

organisation are organisational culture [19], readiness of

organisations to implement it [38], then the willingness to

apply it across the organisations [42] in order to improve

organisational performance. There appears to be a lack of

focus on innovation and KM in public organisation even

though innovation impacts on organisational performance

[24].

Prior literature on KM trend in public organisation

shows that there is the need for a combination of KM

trends to enhance organisational performance [10;11;36].

Organisations that focus on a specific trend, for example,

knowledge sharing in Malaysia is just for the purpose of

meeting administrative requirement only. This suggests,

that the purpose of knowledge sharing is not to enhance

the organisational performance [42]. The need of KM

[13;37;38] as a strategy seem vital for organisational

performance.

A. KM and Public Organisation in Developed

Countries

This sections identifies prior research on KM and

public organisations in developed countries. Evidence

exist for Canadian Federal Government in Canada,

Federal Government in United States (US) and Singapore

National Library.

In Canada, KM in public organisations is better

known as Inukshuk KM model that comprises five

elements, technology, leadership, culture, measurement,

and process. Technology is a tool to collect, share and

create new information among group members.

Leadership focuses on the task of a leader to guide,

encourage and direct group members take actions in

achieving organisational missions and goals. Culture is

about developing beliefs that would encourage knowledge

sharing and creation in organisations. Measurement is an

element to determine whether KM had achieved its goals

and mission in organisations. Process refers to conversion

of knowledge, from tacit to explicit and conversely.This is

recognised as a vital guideline when planning and

implementing KM in public organisations [17].

In the US, KM is used to solve leadership issues by

training the leaders to strengthen and enhance their

leadership skills.The successful leaders continue the

knowledge sharing and knowledge creation culture to be

sustained over the time in United States (US)[20].

Moreover, in Singapore, KM is a mediator for

knowledge sharing and knowledge creation among the

staffs in the National Library. KM is about knowledge

sharing culture among staff starting from the bottom level

to the top level, toward achieving the National Library

mission and goal [45].

KM was evident in tourism sector in Australia

through a KM based framework for disaster management.

The framework includes recommendations about the

various types of knowledge and information needed and

the specifics of the information system architecture for

disaster planning prevention [28].

A study on KM implementation in Greece public

library shows that KM was successfully used as a model

for taxonomy by using the ontology to retrieve the

accurate data from their digital library database [38].The

implementation of KM in Denmark, focused on

knowledge sharing in a public organisation to resolve the

problem of losing the knowledge and skills of

professional staff when they retired. Beside knowledge

sharing, knowledge capture and store is another concernt

toward saving the public organisation from depletion of

knowledge [22].

A study in Australia revealed that the challenge of

KM in centred around policy development between public

organisations and stakeholders. Transparency issue in

establishing successful partnerships arises while

transferring the knowledge between public organisations

and stakeholders. This challenge and issue need strategic

point to capture knowledge about stakeholders, by

highlighting how stakeholders interact with policy

development processes [39].

In Toronto, a study of knowledge sharing and

knowledge conversion across the school face a critical

challenge when schools in different districts lack

information technology infrastructure [16]. Cong and

Pandya [10] claimed that there are several challenges and

issues when public organisations in US implemented KM.

For example, issues covered awareness, readiness to adopt

KM and dire need for a generic KM framework in order

to implement KM successfully in public organisations.

Another issue of knowledge sharing in health sector

shows the challenges on readiness of the organisation to

adopt or to practice knowledge sharing [44].This study

shows that the innovative culture, a capacity to learn from

failure and good information quality are strong predictors

of successful knowledge sharing. Besides, the issue and

challenge in implementing KM in public organisation are

technology, leadership and culture [6].


KM - 3

B. KM and Public Organisations in Developing

Countries

Research on KM and public organisations in revolve

around the use of KM in organisations, KM

implementation and KM issues and challenges.

In Taiwan, KM in central government was used as a

mediator to transfer and share tacit knowledge among

organisations by building the culture of sharing and

organisations try to learn from expertise [17].

A study in India by Chawla [8] on KM

implementation in public organisations using KMAT tool

(Knowledge Management Assessment Tool) shows that

public organisations are behind private organisations in

KM implementation. Another study in Indian government

shows that KM implementation successfully enhances

knowledge sharing strategy through adding information

technology in creating a virtual organisation for

knowledge sharing strategy purposes. As a consequence,

KM improved organisational and managerial style as well

meets the purpose of KM implementation to enhance the

service offerings [18]. Moreover in a public university

India [2], the study shows that implementing KM give

benefits in converting the traditional teaching university

into a learning university through the application of

knowledge sharing and knowledge creation strategy.

In another study, Saudi Arabian public schools

(primary and secondary school) show that KM used to

enhance e-learning faced with cultural and technical

challenges. The Saudi government authorities were

reluctant to use the Internet technology in learning, avoid

undesirable content in regard to religion, culture and

society [29].

More recently, Syed [42] studied the status of KM

implementation in the Ministry of Entrepreneur

Development of Malaysia.The study aimed at gaining

insights into whether the ministry had implemented KM

in their organisation. The study indicates that KM as a

practice could be the most influential strategy in

managing knowledge in public organisations in Malaysia.

In another Malaysia scenario, the issue on KM in public

organisations is about the readiness of organisations to

adopt and implement knowledge management practice

[40].

III. DISCUSSION AND CONCLUSION

From the literature, it shows that the study on KM

and public organisations regardless of countries share

three common themes: the use of KM in organisations

[15], KM implementation [8] and KM issues and

challenges [15; 39]. Table 1 shows the summary of prior

studies as a whole.

TABLE 1 KM AND PUBLIC ORGANISATION PRIOR RESEARCH THEMES

Countries

Use

of

KM

Issu

es

&

ch

all

en

ges

Imp

lem

enta

tio

n

To

tal

by c

ou

ntr

y

Developed countries

Canada 1 1 2

US 1 3 1 4

Australia 1 1 1

Singapore 1 1

Total by theme 4 5 1 -

Developing countries

India 3 3

China 1 1

Malaysia 1 1 1 2

Total by theme 2 1 4 -

6 6 5

The table shows that almost all themes were given almost

equal emphasis. In developed countries, the use of KM

and issues and challenges were placed as more important.

In developing countries however, KM implementation is a

more important by majority.

This may suggest that public organisations in

developed countries appear to show a keen interest in a

framework and resolving issues and challenges that may

have an impact on use of KM. This may in turn be used as

lessons learnt for other public organisations especially in

developing countries. On the other hand, public

organisations in developing countries main interest is on

KM implementation. This suggests that KM

implementation may be perceived as a silver bullet for

specific internal issues.

Future research opportunities seem to exist on

innovation and KM for public organisations. One possible

area for exploration is the implementation climate for

KM. If KM is viewed as innovation, the climate may refer

to KM implementation climate and innovation climate

[35].

This paper has surveyed the literature and finds

opportunities exist for KM researches in public

organisations. More exploration is required to advance

understanding in KM and public organisations in

developing countries like Malaysia.

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Abstract - The purpose of this paper is to identify the

barriers of KM implementation in an organisation.

Based on the preliminary literature review, KM

barriers such as lack of senior management leadership

and commitment, poor technological infrastructure,

poor organization structure, rigid culture and no

motivation and no reward, poor KM measurement

was identified. However, no empirical study was

conducted in Malaysia to this point of time. Therefore,

this paper recommended to carry out an empirical

study in Malaysia to validate the KM barriers

identified by the researchers in other countries.

Keywords – Knowledge Management, Knowledge

Management Implementation and Knowledge

Management Barriers

I. INTRODUCTION

knowledge is a source of wealth [1]. In his opinion,

productivity level would have increased when the workers

apply knowledge to tasks they are familiar with, and the

term innovation is used when the workers apply

knowledge to tasks that are new and different. Therefor

many organizations strived to implement KM campaigns

recently with the intention to develop their knowledge

capacity in order to obtain their distinct competitive

advantage as many companies are competing vigorously

with each other. However, research has shown that not

many KM projects were successful implemented [2].

Indeed, more than 8% of KM projects are failed [3] and

this indicates that successful implementation of KM is not

as straight forward as most the companies think.

Therefore, this paper aims to identify the main barriers of

KM implementation in Malaysia since no empirical study

was conducted in Malaysia

II. METHODOLOGY

The literature review focuses on the knowledge

management papers in international refereed journals

using the literature databases of Emerald, ProQuest

Direct, Sciencedirect and Wiley Interscience. The articles

are selected based on the keywords “knowledge

management implementation” or “knowledge

management strategy” or where the articles’ title includes

one of these compound terms and later the articles are

chosen based on the selected research theme, namely

“barriers for knowledge management implementation”.

From this preliminary literature review, barriers for KM

implementation are identified as one of the recent

research themes that worth further studies since no

empirical study papers in Malaysian context were found

in the literature search process.

III. LITERATURE REVIEW

Many KM researchers and practitioners have

identified barriers of KM implementation, such as lack of

senior management leadership and commitment [4], poor

technological infrastructure [5], poor organization

structure [6], rigid culture [2] and no motivation and no

reward [6; 7], poor KM measurement [8; 9] are reviewed

in the following sections:

A. Lack of Senior Management Leadership and

Commitment

Senior management is playing a very important role

in KM implementation. Low commitment from senior

management and poor leadership will slow down the

process of the KM practices in an organization. In

addition, a knowledge sharing culture in an organization

that is badly role-modeled by those top executives in the

organizations hierarchy can impede KM implementation

in an organization. High commitment and support from

senior management will lead to well-behaved and

responsible employees. If top management is unreliable or

does not follow up on activities, employees will not care

about those activities too [4]. Therefore, top management

is the most critical for a successful KM implementation,

particularly in knowledge creation and sharing.

B. Poor Technological Infrastructure

Poor technological infrastructure is one of the barriers

of KM. Information technology provides platform to

KM, the role of IT is to help organization to do

knowledge preservation and knowledge sharing. For

example, ERP, CRM, KMS and etc. are used as an enable

for KM implementation. However, information

technological solutions normally require a budget. This

can easily become a huge constraint in implementation of

KM. Even if free software is available, there is often lack

of hardware, lack of bandwidth and lack of IT literacy

Barriers for Successful Knowledge Management Implementation: A Preliminary

Literature Review and Research Agenda

A. H. H. Ng*1, M. W. Yip

2, S. Din

3, N. A. Bakar

4

1International Business School, Universiti Teknologi Malaysia, Kuala Lumpur, Malaysia

2Faculty of Engineering and Built Environment, Tunku Abdul Rahman University College, Kuala Lumpur, Malaysia 3Razak School of Engineering and Advanced Technology, Universiti Teknologi Malaysia, Kuala Lumpur, Malaysia

4Malaysia-Japan International Institute of Technology, Universiti Teknologi Malaysia, Kuala Lumpur, Malaysia



KM - 7

when it comes to handling the software, thus making costs

gain even higher than comparable ‘pay’-software [7].

C Poor Organizational Structure

Organizational structure includes division of staff,

departmentalization and distribution of authority which is

necessary to support the decision process of the

organizations. Organization structure such as bureaucratic

structure blocks the flow of knowledge; therefore it is a

barrier of KM implementation [6]. Bureaucracy is

characterized by highly routine operating tasks achieved

through specialization, very formalized and rigid rules

and regulations, tasks that are grouped into functional

departments, centralized authority, narrow spans of

control and decision-making that follows chains of

command and lack of flexibility. Because of rigidity and

less flexibility, hence the employee are not empowered

enough to handle the decision-making process. Authority

and responsibility are restricted, so employees may well

reduce their level of commitment of KM implementation.

D. Rigid Culture

Culture is known as the sum of shared philosophies,

assumptions, values, expectations and social norms that

influences behaviors throughout the organizations [10].

the majority of success of KM in their experiences of

knowledge sharing is closely related to culture [2].

Furthermore, he also says that in order to be successfully

obtain and transfer knowledge, constituents of

organizational culture also identify the extent of its

success. Rigid culture will block the creativity and

innovation of the employee. Lack of open culture will

limit the efficiency of KM.

E. No Motivation and No Reward for Employees

KM goals cannot be reached unless the organization

integrates the concept of motivation and rewards to their

employees [6; 7]. This is because motivation acts an

important factor which brings employees satisfaction. In

the increasingly competitive business environment of

recent years, motivating employees has been concerned

by many managers in order to increase the level of

energy, commitment and creativity of employees.

Motivation has been used as a tool to put employees into

action, increase employees’ level of efficiency and build a

positive relationship between managers and employees.

Without motivation, this will discourage employees to

create, share and use knowledge as they do not have the

willingness to work for the organizations. Thus, it has

become one of the barriers of successful implementation

of KM.

F. Poor KM Measurement

The last barrier for KM implementation is about the

measurement of the impact or benefits of KM. Many

organisations that are implementing KM do not know

how to measure the impact of KM [8]. Therefore, KM

measurement is crucial to success of KM implementation

[9].

IV. DISCUSSION

Based on the preliminary literature review on the

barriers for KM strategies, basically the barriers derive

from both soft elements (practices) and hard elements

(technology). The barriers derive from hard elements, for

instant poor technological infrastructure technology [5].

Indeed, adoption of IT technology can enable an

organization to become more productive, efficient,

effective and agile in KM implementation and be superior

to other firms in the market-place [11]. However most

examples of barriers derive from soft elements are

leadership and commitment [4] poor organization

structure [6], rigid culture [2] and no motivation and no

reward [6; 7], poor KM measurement [8; 9]. According to

Mathiyalakan [12], it is possible for small businesses with

limited resources to initiate the smaller scale of KM

implementation program by using appropriate soft

elements and then use an evolutionary path to migrate to

the use of hard elements (technological infrastructure)

which required more investment.

V. CONCLUSION

From the above literature review and discussion, this

paper has identified the some KM barriers such as lack of

senior management leadership and commitment, poor

technological infrastructure, poor organization structure,

rigid culture, no motivation and no reward and also poor

KM measurement. However, there are no empirical

studies were conducted in Malaysia to date. Therefore,

this paper recommended to carry out an empirical study to

validate all the KM barriers (as mentioned above) in

Malaysia context using the focus group. The KM

practitioners from various industries in Malaysia will be

invited to participate in the the focus group.

ACKNOWLEDGMENT

This research was financially supported by the Razak

School Research Grant (Vot No. 4b036) from Razak

School of Engineering and Advanced Technology,

Universiti Teknologi Malaysia and Ministry of Higher

Education.

REFERENCES

[1] P.F. Drucker, Innovation and Entrepreneurship. Oxford:

Butterworth Heinemann, 1985.

[2] C. BenMoussa, “Barriers to knowledge management: a

theoretical framework and a review of industrial cases”.

World Academy of Science, Engineering and Technology,

vol. 30, pp. 901-912, 2009.


KM - 8

[3] C, Lucier, J. Torsiliera, “Why knowledge programs fail”.

Strategy and Business, pp.14-28. 4th quarter 1997.

[4] N. Hermann, “Barriers for an Efficient Management of

Knowledge: Experiences From a Southern African”. Open

Journal of Knowledge Management, no. 3, pp. 29- 41,

2011.

[5] T. Baquero, and W. Schulte, “An exploration of knowledge

management practices in Colombia”. The Journal of

Information and Knowledge Management Systems, vol. 37,

no.3, pp. 368-386, 2007.

[6] M. D. Singh, R. Kant, “Knowledge management barriers:

an interpretive structural modeling approach”.

International Journal of Management Science and

Engineering Managament. vol 3, no. 2, pp. 141-150, 2008.

[7] S. Syed-Ikhsan, F. Rowland, ‘‘Knowledge management in

public organizations: 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, 2004.

[8] J. E. McCann, J. H. Syke, “Strategically integrating

knowledge management initiatives”. Journal of Knowledge

Management, vol.8, no.1, pp 47-63, 2004.

[9] S. Moffett, R. McAdam, S. Parkinson, “An empirical

analysis of knowledge management applications”. Journal

of Knowledge Management, 7(3): pp 6 – 26, 2003.

[10] APQC, Knowledge Management: Executive Summary:

Consortium Benchmarking Study Best-Practice Report.

Houston, TX: American Productivity and Quality Center.,

1999.

[11] P. Evangelista, E. Esposito, V. Lauro, M. Raffa, “The

adoption of knowledge management systems in small

firms”, Electronic Journal of Knowledge Management, vol.

8 no. 1, pp. 33-42, 2010.

[12] S. Mathiyalakan, “The use of hard and soft technologies for

knowledge management in small businesses” in Emerging

Trends and Challenges in Information Technology

Management- Volume 1 and Volume 2, M. Khosrow-Pour,

Ed. Hershey, PA: Idea Group Inc., pp. 916-917, 2006.


KM - 9

Abstract - The main objectives of this research are to (i)

explore the relationship between types of knowledge and

academics’ knowledge sharing behaviour, (ii) examine the

relationship between knowledge sharing behaviour and its

predictors based on the Theory of Planned Behaviour, and

(iii) identify the factors motivating and hindering academics’

knowledge sharing behaviour. Adopting Ajzen’s Amended

Theory of Planned Behaviour, this research used the

quantitative research approach employing an online survey

using questionnaire to collect data from academics in ten

public universities. Data were analyzed using SPSS and

PLS-SEM. The analysis process involved assessment of the

measurement model to evaluate the items reliability and

validity, and assessment of the structural model to evaluate

its validity, path coefficients, and test the hypotheses. The

results revealed a high level of knowledge sharing practice.

Furthermore, the results showed that academics’ knowledge

sharing behaviour is significantly influenced by explicit

knowledge, tacit knowledge, and intention. Intention itself is

significantly influenced by attitude, subjective norms, self-

efficacy, but not influenced by controllability. Also, attitude

is significantly and positively influenced by trust and

reputation as motivators of knowledge sharing behaviour.

Whereas, controllability is significantly and negatively

influenced by lack of time and poor communication as

barriers of knowledge sharing behaviour. Keywords - academics, knowledge sharing behaviour, Theory

of Planned Behavior, UAE, universities.

I. INTRODUCTION

Knowledge sharing is a process of exchanging and

transferring existing knowledge and ideas among people

in order to create new knowledge and ideas to help

organizations achieve their objectives. It helps in

achieving continuous organizational growth, maintaining

competitiveness and profitability, promoting individuals’

learning and innovation, enhancing their performance,

skills and competencies, and transferring knowledge

among individuals which insures sustaining knowledge

within an organization.

Universities are knowledge-intensive environments

responsible for creating, managing, and disseminating

knowledge in society. They grow and prosper from the

knowledge of their academics [1]. Accordingly to ensure

success, achieve their goals [2], and have constant

performance improvements, universities should promote

knowledge sharing among their academics. In the

academic environment, the role of knowledge sharing is

quite significant to achieve maximum results for higher

education institutions [3] considering the important role of

academics in education, research, and scholarly work.

Recognizing the importance of knowledge sharing in both

education and research is creating a demand for applying

it in academic institutions.

The United Arab Emirates (UAE) has experienced

significant local and foreign investments in various fields

such as construction, infrastructure, telecommunications,

media, information technology, hospitality and tourism as

well as education. The government has also announced a

strategy in 2010 to invest in its human capital and

establish a knowledge-based society with a knowledge-

based economy [4]. Thus, it has allocated more than 1/3

of its budget to education and research [4].

Therefore if UAE is to play its aspired role in creating

knowledge and establishing a knowledge-based society in

the region, the government has to promote a culture of

knowledge sharing [5] particularly within academic

institutions given their importance in knowledge creation.

In light of that, this research intends to study academics’

knowledge sharing behaviour and identify the factors

influencing it in UAE universities. This research is the

first to address knowledge sharing in higher education

sector in UAE considering the importance of knowledge

sharing in achieving universities’ aims.

II. THEORETICAL FRAMEWORK

The theory of planned behaviour [6] states that

human behaviour is guided by three kinds of salient

beliefs: behavioural beliefs about the likely consequences

or attributes of the behaviour, normative beliefs about the

normative expectations of other people, and control

beliefs about the presence of factors that may facilitate or

hinder performance of the behaviour [7]. In their

respective aggregates, behavioural beliefs produce a

favorable or unfavorable attitude toward the behaviour;

normative beliefs result in perceived social pressure or

subjective norms; and control beliefs give rise to

perceived behavioural control, the perceived ease or

difficulty of performing the behaviour [7]. In

combination, attitude, subjective norms, and perceived

behavioural control lead to the formation of a behavioural

intention. However, due to the conceptual and

methodological ambiguities concerning the concept of

perceived behavioural control, Ajzen [7] stated that

perceived behavioural control should be viewed as a

“unitary, higher-order concept that consists of two

interrelated components” (Kraft et al., 2005: 480-481). He

thus deconstructed perceived behavioural control into two

constructs: self-efficacy and controllability [7].

FACTORS INFLUENCING ACADEMICS’ KNOWLEDGE SHARING

BEHAVIOUR IN UNITED ARAB EMIRATES PUBLIC UNIVERSITIES

H. A. Skaik*1, R. Othman

1

1Department of Library & Information Science, International Islamic University Malaysia, Kuala Lumpur, Malaysia



KM - 10

According to Ajzen [8], the more favorable the

attitude and subjective norm, and the greater the self-

efficacy and controllability, the stronger the intention to

carry out the behaviour. Thus, intention is assumed as the

immediate antecedent of behaviour. Having a sufficient

degree of actual control over the behaviour, people are

expected to perform the behaviour when the opportunity

arises. Each of the theory elements of intention, attitude,

subjective norms, self-efficacy, and controllability is

counted as an aspect of the actual behaviour [9].

III. LITERATURE REVIEW

A throught review of the literature has led the authors

to a number of factors that influence knowledge sharing

behaviour. Among these factors are the two types of

knowledge. Some researchers have found that both

explicit and tacit knowledge play important roles in

enhancing knowledge sharing among individuals [10, 11].

Reychav and Weisberg [12] indicate that there is a

positive relationship between either explicit or tacit

knowledge and knowledge sharing behaviour.

The literature also identifies a number of individual

factors that influence knowledge sharing behaviour. Such

factors may either be motivating or hindering ones. Trust

and reputation are important individual motivators of

knowledge sharing [13]. Trust is a medium to share

knowledge smoothly. Tan el al. [14] believe that trust

determines the success of knowledge sharing. Reputation

positively influenes an individual to share knowledge.

Hung et al. [15] emphasize that professional reputation

enhances people to share their knowledge with others.

On the other hand, lack of time and poor

communication are some of the most significant barriers

identified [14]. Haas and Hansen [16] state that

individuals’ willingness to share knowledge is affected by

the amount of time allocated to perform their

responsibilities for which knowledge sharing can be

useful. Poor communication is seen as a major barrier in

the process of knowledge sharing since individuals’

ability to share knowledge depends largely on their

communication skills [17]. Based on the theoretical

framework and the literature review above, Fig. 1 shows

the conceptual framework of the current research.

Figure 1: Research Model

IV. METHODOLOGY

A cross-sectional web-based survey was used as a

method to collect data from the academics working in the

targeted public universities in UAE. The instrument

employed for this purpose was the questionnaire that was

sent to the academics through universities internal

circulation system and email inviting them to participate

in the survey. Using the simple random sampling

technique, the sample consisted of 321 academics

working in different faculties in UAE public universities.

The measurement items used in the questionnaire

were developed and validated based upon Ajzen’s theory

of planned behaviour, and other instruments validated in

previous researches conducted on knowledge sharing

behaviour. All items were measured using five-point

Likert-scale. The questionnaire was provided in both

English and Arabic, which are the official languages of

teaching in the universities.

Data analysis was conducted using partial least square

path modeling technique. By using SmartPLS 2.0

software [18], PLS-SEM was applied to assess the

measurement model and structural model, and to test the

research hypotheses. The assessment of the measurement

model involved assessment of indicator reliability,

internal consistency reliability, convergent validity, and

discriminant validity at indicator and construct levels

[19]. The assessment of the structural model involved

assessment of the coefficient of determination, path

coefficient, effect size, and predictive relevance [19].

V. RESULTS

A. Assessment of the Measurement Model

The purpose of assessing the measurement model is

to evaluate its validity and reliability. It is conducted

through the following tests: Indicator reliability by

measuring the factor loading of each of the manifest

variables, which should be above 0.4 [20], internal

consistency reliability by measuring composite reliability

and Cronbach’s alpha which should be 0.7 [20],

convergent validity by measuring the AVE, which should

be more than 0.5 [21], and discriminant validity by using

Fornell-Larcker’s [21] criterion where the square root of

Knowledg

e Sharing

Self

Efficacy

Controllability

Intention

Subjectiv

e

Attitude

Poor

communication

Reputatio

n

Trust

Lack of

Explicit Knowledg

e

Tacit

Knowledge


KM - 11

the AVE for each construct exceeds the correlations

between the construct and all other constructs [22].

The results of analyzing the measurement model

demonstrated reliable and valid measurement model as

displayed in Tables I and II below. All factors loaded

above the recommended value of 0.7 demonstrating

satisfactory indicator reliability. The constructs composite

reliability and Cronbach’s alpha values exceeded the

recommended value of 0.7 indicating satisfactory internal

consistency reliability. The constructs AVE exceeded the

recommended value of 0.5 demonstrating adequate

convergent validity. The square root of the constructs

AVE values exceeded the correlations between the

constructs and all indicators loaded higher on their own

constructs indicating satisfactory discriminant validity.

TABLE I

Internal Consistency

Construct Composite

Reliability

Cronbach’s

Alpha

Knowledge Sharing Behaviour 0.9056 0.8612

Explicit Knowledge 0.9159 0.8914 Tacit Knowledge 0.9034 0.8686

Intention 0.9461 0.9288

Attitude 0.9475 0.9307 Subjective Norms 0.9082 0.8658

Self-Efficacy 0.9548 0.9409

Controllability 0.9499 0.9311 Trust 0.9560 0.9462

Reputation 0.9598 0.9478

Lack of Time 0.9078 0.8660 Poor Communication 0.8369 0.7380

TABLE II

Convergent and Discriminant Validity

Construct AVE √AVE


Explicit Knowledge 0.6459 0.804

Tacit Knowledge 0.6519 0.807 Intention 0.7785 0.882

Attitude 0.7832 0.885

Subjective Norms 0.7122 0.844 Self-Efficacy 0.8089 0.899

Controllability 0.8261 0.909

Trust 0.7568 0.870 Reputation 0.8270 0.909

Lack of Time 0.7113 0.843

Poor Communication 0.6371 0.798

B. Assessment of the Structural Model

The purpose of assessing the structural model is to

evaluate its validity and test the hypotheses. This is

achieved through the following tests: The coefficient of

determination (R²) by measuring the amount of explained

variance of each latent variable, path coefficient by

measuring the path estimates and t-statistics, effect size

(f²) by measuring the relative impact of a particular

exogenous latent variable on an endogenous latent

variable by means of changes in the R² of the latent

variable, and pedictive relevance (Q²) by measuring how

well observed values are reconstructed by the model and

its parameter estimates [19].

As seen in Tables III and IV below, the results of

analyzing the structural model demonstrated an adequate

and valid model. The R2 values for knowledge sharing

behaviour and intention were large demonstrating strong

explanatory power. Meanwhile the R2 value for attitude

was moderate demonstrating modest explanatory power,

and the R2

value for controllability was small.

The effect size values were within the recommended

values of 0.02, 0.15, and 0.35. The values ranged from

0.002 to 0.219 demonstrating small and medium effect

sizes of the independent variables. The predictive

relevance values of the dependent variables were above

the recommended value zero indicating an adequate

predictive relevance of the model.

TABLE III

Coefficient of Determination and Predictive Relevance

Construct R2 Q²


Intention 0.4705 0.3643 Attitude 0.2427 0.1830

Controllability 0.0625 0.0441

TABLE IV

Effect Size

Path f² Effect

Size

Explicit knowledge Knowledge sharing

behaviour

0.044 Small

Tacit knowledge Knowledge sharing

behaviour

0.035 Small

Intention Knowledge sharing behaviour 0.063 Small

Attitude Intention 0.219 Moderate

Subjective Norms Intention 0.079 Small

Self-efficacy Intention 0.049 Small Controllability Intention 0.002 Small

Trust Attitude 0.120 Small

Reputation Attitude 0.067 Small Lack of Time Controllability 0.015 Small

Poor Communication Controllability 0.023 Small

C. Hypotheses Testing

Based on the path coefficients assessment, the

hypotheses were tested. 10 hypotheses were supported

providing empirical support for the conceptualized

research model. Table V shows the results of the

hypotheses testing with path coefficients and t-statistics.

The path coefficients demonstrated significant levels that

exceeded the recommended β value of 0.1 at t-statistics

values of 1.96 and 2.59.

TABLE V

Hypotheses Testing

Hypothesis β T-

statistics

Result

H1 Explicit knowledge

Knowledge sharing behaviour

0.241 3.773** Supported

H2 Tacit knowledge 0.217 2.895** Supported


KM - 12

Knowledge sharing behaviour

H3 Intention Knowledge

sharing behaviour

0.253 4.221** Supported

H4 Attitude Intention 0.410 7.811** Supported

H5 Subjective Norms Intention

0.232 4.145** Supported

H6 Self-efficacy Intention 0.217 3.600** Supported

H7 Controllability Intention -0.010 0.342 Not Supported

H8 Trust Attitude 0.333 6.271** Supported

H9 Reputation Attitude 0.248 4.426** Supported H10 Lack of Time

Controllability

-0.128 2.130* Supported

H11 Poor Communication Controllability

-0.164 2.783** Supported

* Significance at t value ≥1.96 with p ≤ 0.05, **Significance at t value ≥ 2.59 with p ≤ 0.01

VI. DISCUSSION

The results revealed that academics’ knowledge

sharing behaviour is significantly influenced by explicit

knowledge, tacit knowledge, and their intention to share

knowledge, which is in consistent with previous studies.

Collectively, explicit knowledge, tacit knowledge, and

intention to share knowledge explained 37% of the

variance in knowledge sharing behaviour. Moreover, the

results showed that academics’ intention is significantly

influenced by attitude towards knowledge sharing,

subjective norms, and self-efficacy. This result is in

accordance with the theiry of planned behaviour.

Collectively, attitude towards knowledge sharing,

subjective norms, and self-efficacy explained 47% of the

variance in intention. Finally, contrary to the theory, the

results found that controllability does not have any

influence on academics’ intention.

In addition, and in consistent with prior findings the

results proved that attitude towards knowledge sharing is

significantly and positively influenced by trust and

reputation as motivators of knowledge sharing behaviour.

Trust and reputation explained about 24% of the variance

in attitude towards knowledge sharing. Also, the results

showed that controllability is significantly and negatively

influenced by lack of time and poor communication as

barriers of knowledge sharing behaviour. Lack of time

and poor communication explained 6% only of the

variance in controllability.

VII. CONCLUSION

The findings of this research contribute to previous

researches that have explained the complicated nature of

knowledge sharing behaviour with particular emphasis on

knowledge sharing in UAE in higher education.

Indicating the importance and various benefits of

knowledge sharing for both organizations and individuals

is the key to the success of organizations as well as

individuals. The necessity of exploring knowledge sharing

in higher education particularly is reinforced by the

significant role of universities in creating and distributing

knowledge, and by the major role of academics as

valuable resources of creating, exchanging, and

disseminating knowledge, where knowledge sharing can

help them in their scholarly and research works.

REFERENCES

[1] P. Singer and J.E. Hurley, “The Importance of Knowledge

Management Today,” ALA-APA Library Worklife Home,

vol. 2, no. 6, pp.1-3, 2005.

[2] A. Sharma, “Enabling knowledge management of

organizational memory for groups through shared topic

maps,” Master dissertation, Iowa State University, USA,

2010.

[3] F. Babalhaveji and Z.J. Kermani, “Knowledge sharing

behaviour influences: A case of library and information

science faculties in Iran,” Malaysian Journal of Library and

Information Science, vol. 16, no.1, pp. 1-14. 2011.

[4] N. b. M. Al-Nahyan, “Executive Focus: Government

commitment and investment in education, research

initiatives, and improving the quality of education”

available at

http://www.theprospectgroup.com/executivefocus/profile/h-

h-sheikh-nahyan-bin-mubarak-al-nahyan-minister-of-

higher-education-and-scientific-research-uae-2/8578/, 2012.

[5] K. Alrawi and K.H. Jaber, “Virtual classrooms and the

flexibility of e-learning in the Gulf universities,” Journal of

knowledge Management Practice, vol. 8, no. 3, 2007.

[6] I. Ajzen, “From intentions to actions: A theory of planned

behavior,” in Action control: From cognition to behavior, J.

Kuhl and J. Beckman, Eds. Berlin: Springer-Verlag, 1985,

pp. 11-39.

[7] I. Ajzen, “Perceived behavioral control, self-efficacy, locus

of control, and the theory of planned behavior,” Journal of

Applied Social Psychology, vol. 32, no. 4, pp. 665-683,

2002.

[8] I. Ajzen, “Constructing a theory of planned behaviour

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211, 1991.

[10] S. Sohail and S. Daud “Knowledge sharing in higher

education institutions: Perspectives from Malaysia,” The

Journal of Information and Knowledge Management

Systems, vol. 39, no. 2, pp. 125-142, 2009

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sharing among academic staff: A case study of business

schools in Klang Valley, Malaysia,” JASA, vol. 2, pp. 23-

28, 2007.

[12] I. Reychav, and J. Weisberg, “Bridging intention and

behavior of knowledge sharing,” Journal of Knowledge

Management, vol. 14, no. 2, pp. 285-300, 2010.

[13] I. Seba, J. Rowley and S. Lambert, “Factors affecting

attitudes and intentions towards knowledge sharing in the

Dubai police force,” International Journal of Information

Management, vol. 1120, pp. 1-9, 2012.

[14] N.L. Tan, Y.H. Lye, T.H. Ng and Y.S. Lim, “Motivational

factors in influencing knowledge sharing among banks in

Malaysia,” International Research Journal of Finance and

Economics, no. 44, pp. 191-201, 2010.

[15] S.Y. Hung, H.M. Lai and Y.C. Chou, “The determinants of

knowledge sharing intention in professional virtual

communities: An integrative model,” in Proc. PACIS 2010.

[16] M. Haas and M. T. Hansen “Different knowledge, different

benefits: Toward a productivity perspective on knowledge

http://people.umass.edu/aizen/pdf/tpb.measurement.pdf


KM - 13

sharing in organizations,” Strategic Management Journal,

vol. 28, no. 11, pp. 1133-1153, 2007.

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managers should consider,” Journal of Knowledge

Management, vol. 9, no.3, pp. 18-35, 2005.

[18] K.W. Hansmann C.M. Ringle, SmartPLS manual, institute

for operations management and organizations, Universität

Hamburg, Germany, 2004.

[19] W. W. Chin, “How to write up and report PLS analyses” in

Handbook of partial least squares: Concepts, methods and

applications in marketing and related fields, V. E. Vinzi, W.

W. Chin, J. Henseler and H. Wang, Eds. Berlin: Springer,

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[20] J.F. Hair, W.C. Black, B.J. Babin and R.E. Anderson,

Multivariate data analysis: A global perspective (7th ed.),

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KM - 14

Abstract - Total quality management (TQM)

implementation in the organizations is deeply rooted in

human resource (HR). In particular, such implementations

of TQM practices are heavily influenced by the human or

personal values of individuals. HR management worked

closely with quality management personal to motivate and

socialize these values among employees and to pursue the

quality programs and practices. However, literature lacks

in providing any directions for the quality and HR

management about the human values which are required

for the implementation of TQM. Without such knowledge

of values, it is impossible for management to shape the

implementation of TQM practices more effectively. Thus,

this research highlights the practical knowledge of

exploring and managing the human values for quality

implementation. The contribution of this research is to

propose knowledge management (KM) framework that

may assist HR and quality management to provide better

understanding of human values and their status of

implication for the implementation of TQM practices.

Besides this, it may assist the HR management to perform

the core HR functions such as selection, performance

evaluation, training and development etc that leads to the

implementation of TQM.

Keywords - Human values, TQM practices, Human

Resource (HR), Knowledge Management (KM)

I. INTRODUCTION

Implementing total quality management (TQM)

philosophy in organizations has always been a problem.

Currently organizations are focusing different approaches

based on ISO certifications and excellence awards to

approach TQM philosophy. However, it is observed that

implementation of TQM requires human and its

associated factors such as skills, attitude and personal

values as critical factor. These human or personal values

at individual level are considered as core for the effective

implementation of TQM [1,2,3,4]. The last decade shows

the scholars interest towards human values for business

organization and have emphasized these values as

potential resource for the implementation of TQM

[1,3,5,6]. Such human contents like values have been

overlooked in past few decades, but recently scholars

have emphasized on the HR content like human values

and their core functions such as selection, performance

evaluation, training and development for the

implementation of TQM [1,7].

HR management is the critical aspect for the

implementation of TQM [5,8]. HR managers generally

used different techniques to socialize these human values

among existing and new employees. Although HR

managers worked closely with quality management

managers to pursue the implementation of quality

programs and practices, but they are lacking with the

awareness and knowledge about the relevant or required

human values for the implementation of TQM practices

[7,9,10]. Without such knowledge of values in a real

situation, it is impossible for both quality and HR

management to shape the implementation of TQM

practices more effectively.

Thus, this research aimed on emphasizing on the need

of exploring and managing the human values in real

situation as hand on practice for managers for TQM

implementation. Besides this, KM framework for human

values is proposed in this paper that could assist the

management to have better understanding of human

values and their status of implication for the

implementation of TQM practices.

The paper comprises of following sections; section II

describes the importance of human values and HR

management for the implementation of TQM as literature

review, section III describes the proposed KM framework

for HR managers to implement the TQM philosophy.

Section IV comprises of discussions that followed by the

section V which describes the conclusion.

.


A. Importance of Human values and HR management for

TQM implementation:

Implementation of TQM philosophy is heavily

influenced by the human resource (HR) and considered as

critical element for its implementation [1,7,8]. It is

evident in the literature that the HR is the important and

potential resource for TQM implementation [7,10]. Last

decade is evident about the increasing interest of scholars

towards human values for business organization [1,3].

They have emphasized such values as potential resource

for the implementation of TQM. In particular,

implementation of quality is the name of “mind set” that

humans holds and motivated from their personal values

[11]. They highlighted that these values at individual level

are considered as core for the effective implementation of

TQM [2, 3]. These values are considered as unique human

Knowledge Management Framework of Human Values for Total Quality

Management Implementation

M. N. Malik*1,S. Mohd. Yusof

2

1,2 Razak School of Engineering and Technology

Universiti Teknologi Malaysia (UTM), Kuala Lumpur, Malaysia

(*[email protected], [email protected])

mailto:*[email protected]

mailto:[email protected]


KM - 15

competence that determines the quality and assist in

implementing the management practices [12,13].

Human values are the individual level characteristic

and provide guidance for behavior such as honesty,

personal growth, trust, integrity etc. They act as guideline

to think and act according to the situations that what is

right, good, or desirable [14,15]. These human values

cannot be isolated from situation. They changed

according to the situation such as individual will focus on

sincerity, respect, and consistency while in situation of

serving the customer whereas hard working, knowledge

sharing and learning is more used in generating the

quality results. Thus exploring values in real situation is

critical. Although scholars have described an assortment

of values inventories which explored out of context, as

respondents of such exploratory surveys used to rank or

rate based on given an inventory which does not reflect

the real situation. It actually emphasized respondents’

personality or preference in life that sets the result out of

context [4,16]. Therefore, identification and assessment of

human values should be identified and assessed in real

situation for implementation of TQM.

B. Importance of HR management for managing Human

values for TQM implementation:

HR management is one of the essential and core

aspect to support for design, implement and managing the

various quality implementation programs [7,8]. They

played vital role in TQM planning, assessment and

implementing process. They used different approaches to

motivate the employees. They are involved in socializing

the human values among existing employees for

implementing the quality practices. The last decade is

evident of increasing interest of scholars to accent the

closed working of HR personals with quality department

to implement the quality philosophy, but still the results

are invariant [7,10]. HR management are lacking with

awareness of and knowledge about what human values

which are required for the implementation of TQM

practices. Due to this, it is impossible for them to shape

and implement the practices of TQM effectively. Such

baseline information act as guideline, especially for HR

management while practicing basic HR functions such

selecting the new employees, training and development,

socializing values among existing employees etc.

Recently, authors [8] emphasized in his work that

importance of selection strategy as crucial for the

implementation of TQM philosophy. He argued that

selecting the right person with right values can facilitate

the TQM implementation. He relates these values with

shared organizational values. But it is also observed in

literature that scholars has emphasized these values are

personal construct that should be explored in a real

situation and cannot relate with general values [14,16].

Chandrakumara has described in his study that “…values

should not always be meshed with organization” [12].

Human values are considered as the baseline for the

modern business practices, as author argued that “…

values determine the quality and management practices”

[12]. Based on the review, it is argued that awareness and

knowledge about the relevant values which are required

for implementation of TQM are needed among the quality

and HR management. Without such knowledge of

required human values in a real situation, it is impossible

for both quality and HR management to shape the

implementation of TQM practices more effectively.

Thus, KM framework is proposed to address this issue

which is described in the next section.

III. KNOWLEDGE FRAMEWORK OF HUMAN

VALUES

Managing knowledge about human values for TQM

implementation is crucial. TQM field lacks with any

approach that can explore and manage the required human

values in a real situation for its implementation. Such

management of human values as human values KM

framework is proposed in this research that could assist

HR and quality management by providing a better

understanding of required human values and their status

of implication for the implementation of TQM practices.

This proposed framework consist of two main modules

i.e. identification and assessment of relevant human

values in a real situation for implementation of TQM

practices. This framework intends the automated system

for such identification and assessment of human values

for TQM implementation. Fig 1 shows this framework in

detail.

Fig. 1 KM framework of human values

Values identification is the first core aspect of

framework that emphasize on identifying the human

values in a real situation for the implementation of TQM

practices. Such real time identification of values needed


KM - 16

the techniques that support this notion. In order to get

such techniques, an exploratory study will be required that

evaluate the suitable techniques for identifying human

values in a real situation. These techniques later on will be

included as input for the development of identification

module of this human values KM system.

Values assessment in this framework based on the

input of values identification module. This assessment

will use scoring techniques such as 1 for low and 5 for

high. These human values will be scored accordingly to

the TQM practices. The scoring of relevant human values

will be conducted by different assessors for in each TQM

practices to avoid any biasness in the results. Such values

assessment module will assist management to get better


of implication for the implementation of TQM practices

respectively.

Implementation of TQM generally consists of certain

practices such as Leadership, quality results, customer

focuses, and information and analysis etc. This part of

framework explains the basic connection with the values

identification and assessment. In other words,

identification and assessment will be conducted certain

TQM practices respectively.

Repository represents the human values master

database that records the identified and assessed human

values. This values repository will act as baseline for

generating the results graphically. These results infer the

implication status about human values for TQM

implementation.

IV. DISCUSSION

Based on the review, it is observed that recently few

scholars have emphasized the HR functions as core

element for TQM implementation. Author [8] highlighted

the importance of selection strategy and values as base for

selecting the right person with right values and marked as

crucial for the implementation of TQM philosophy. But

he relates these values with shared organizational values,

whereas other scholars have crucially reviewed this and

argued that the values are personal construct which should

not meshed with the abstract organizational values

[12,14,16]. In this research, it is also argued that these

values are personal construct that could be explored in

real situation. Thus, to cater fall the described issue, KM

framework of human values is proposed that could assist

both quality and HR management to explore and manage

the human values in real situation as hand on practice for

TQM implementation. HR management can use such

framework while selecting the employees. This could act

as baseline that shows that what values they must look for

while recruiting or selecting the employees for certain

designation. This will also help in socializing the values

among existing employees for quality implementation.

Hence, proposed framework could provide better


of implication for the implementation of TQM practices

in organization. In particular, it assist for the

implementation of certain TQM practices to improve and

can set quality standards. Management could get

assistance of awareness and knowledge from this

framework about not only the required values to

implement the certain TQM practices, but also while

performing basic HR functions such as selection, training

and development and performance and evaluation etc.

V. CONCLUSION

Implementation of TQM is heavily influenced by the

HR as resource. In particular, practicing human values is

an imperative aspect of structuring and formulating the

TQM practices. Quality and HR management worked

closely with each other to motivate and socialize these

values not only among existing employees but also for

while selecting or recruiting new employees [8,9,10].

They assist to pursue the quality programs and practices,

but still lacks with any framework of exploring and

managing human values for TQM implementation. In

order to address this gap, KM framework of human values

is proposed for both quality and HR management. Such

framework may assist to provide understanding of

required human values and their status of implication for

the implementation of TQM practices in organization.

Besides this, it may assist the HR management to perform

the core HR functions such as selection, performance

evaluation, training and development etc that leads to the

implementation of TQM.

By following the KM framework of human values for

the TQM implementation, an automated tool for exploring

and managing the human values in a real situation can be

developed which is one of the parts of our upcoming

research. Furthermore, the investigation of HR strategies

and their success after the implementation of the proposed

tool in the industry is another future dimensions in this

field. Such research will provide valuable insight for

scholars to cultivate the future agenda in the importance

of HR management functions for implementation of TQM

field.

ACKNOWLEDGMENT

"The authors would like to thank Universiti

Teknologi Malaysia for financial supporting as

International Doctoral Fellowship for this research"


KM - 17

REFERENCES

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human satisfaction and commitment. Total Quality

Management & Business Excellence, 23(2): p. 125-140.

[2] Ertürk A. (2012). The Role of Person-Organization Fit in

TQM: Influence of Values and Value Congruence on TQM

Orientation, Quality Management and Practices, Kim-Soon

Ng (Ed.), ISBN: 978-953-51-0550-3,InTech, .

[3] Moccia, Salvatore (2008). The Role of Personal Values in

An Advanced Perspective of Total Quality Management,

11th QMOD Conference. Quality Management and

Organizational Development Attaining Sustainability From

Organizational Excellence to SustainAble Excellence, 20–

22 August, Helsingborg, Sweden.

[4] Siltaoja, Marjo (2009). Why did the rose wither? If it is all

about values, let's discuss them. EjBO Electronic Journal

lof Business Ethics and Organizational Sutdies.

[5] Guest, D.E. (2011). Human resource management and

performance: still searching for some answers. Human

Resource Management Journal, 21(1): p. 3-13.

[6] Pfeffer, J., & Veiga, J. F., Putting People First for

Organizational Success. The Academy of Management

Executive (1993-2005), 1999. 13(2): p. 37-48.

[7] Balvir, T., (2009). Comparative study of core values of

excellence models human values. Measuring Business

Excellence, 13(4): p. 34-46.

[8] Ingelsson, P., Eriksson, M., & Lilja, J. (2012). Can selecting

the right values help TQM implementation? A case study

about organisational homogeneity at the Walt Disney

Company. Total Quality Management & Business

Excellence, 23(1), p. 1-11.

[9] Fotis, V., (, 2007). Investigating the human resources context

and content on TQM, business excellence and ISO

9001:2000. Measuring Business Excellence, 11(3): p. 21-

29.

[10] Dahlgaard, S.M.P., J.J. Dahlgaard, and R.L. Edgeman,

(1998) Core values: The precondition for business

excellence. Total Quality Management, 9(4-5): p. 51-55.

[11] Jens, J.D. and D.-P. Su Mi, (2006). Lean production, six

sigma quality, TQM and company culture. The TQM

Magazine,. 18(3): p. 263-281.

[12] Chandrakumara, P., (2011). Value of Values for Practicing

Managers and Leaders. Problems and Perspectives in

Management, 9 (2): p. 80-88.

[13] Izzo, J.B. and P. Withers, (2007). Values Shift: Recruiting,

Retaining and Engaging the Multigenerational Workforce.

FairWinds Press.

[14] Schwartz, S. H.: (2005). Basic Human Values: Their

Content and Structure Across Cultures, in A. Tamayo and J.

B. Porto (eds.), Valores e comportamento nas

organizac¸o˜es [Values and Behavior in Organizations].

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[15] Rokeach, M., (1973). The nature of human values. Free

Press.

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values: need for tools to help stakeholders and designers to

reflect and communicate. Ethics and Information

Technology, p. 1-19.


KM - 18

Abstract - The purpose of this study was to examine

technical and social factors that contribute to the KMS’s

utilization. The technical factors are information quality,

system search/retrieval level, system form and service

quality. The social factors are management support,

knowledge trust and utilization rewards. Questionnaire was

used to collect data from employees at a food processing

company. Data were analyzed using multiple regressions to

determine relationship between technical and social factors

that contribute to the KMS’s utilization. 40 questionnaires

were distributed and all of them were returned and

analyzed. The tested hypotheses showed that service quality

and management support are significant relationship with

KMS’s utilization. Finally, the study has proposed several

recommendations for further development of knowledge

management systems in Malaysia.

Keywords - Knowledge Management, Knowledge

Management System, Technical Factor, Social Factor,

Knowledge Utilization.

I. INTRODUCTION

Knowledge is also the principal factor that supports

innovation and change, and has a strategic value for

organizations. For this reason it is fundamental to manage

knowledge effectively [11]. Drucker (1999) stated that

knowledge has taken the place of capital and other assets

as the driving force in organizations, and become the most

valuable asset in this economy-based era. However, the

existence of knowledge will not help much if the

organization is unable to manage the pooled knowledge

wisely and systematically.

Knowledge management (KM) has become a

prominent strategy for enhancing and enriching the

organizational and individual performance, innovation

efforts and creativity generation [10]. Knowledge

management is a process that helps organizations identify,

select, organize, disseminate and transfer important

information and expertise that are part of the

organizational memory that typically resides within an

organization in an unstructured manner. This enables

effective and efficient problem solving, dynamic learning,

strategic planning and decision making. Knowledge

management focuses on identifying knowledge,

explicating it in a way so that it can be shared in a formal

manner and thus reusing it [12].

Knowledge Management System (KMS) is a distributed

hypermedia system for managing knowledge in

organizations, supporting creation, capture, storage and

dissemination of expertise and knowledge [14].

Knowledge management system (KMS) has been used to

facilitate organizational learning by storing organizational

knowledge and having it available to employees when

needed [1]. KMS can enhance knowledge

communications and sharing process in day-to-day

activities thus creates quality learning process in

organization.

This paper looks at technical and social factors that

influence the KMS’s utilization. Based on literature

studies, this article examines the influence of technical

and social elements which are are information quality,

system search/retrieval level, system form, service

quality, management support, knowledge trust and

utilization rewards.


Knowledge Management

Knowledge management (KM) refers to

“recognizing, generating, documenting and distributing,

and transferring between persons explicit and tacit

knowledge to increase organizational effectiveness” [20]

Its purpose is to ensure the right person gets the right

knowledge in the right place at the right time and it is also

a basis for generating new knowledge. According to the

knowledge management theory [10][21], KM is

concerned with creating the structural and organizational

conditions that support the sharing of employee’s

experience, knowledge and innovation. The theory also

reveals the essential of knowledge from individual and

organization in relation to innovation and improvement

process.

Knowledge Management System

Knowledge Management Systems (KMS) is the

system that allows the collection of processed

knowledge/information gathered from the organization’s

employees that support creation, dissemination and

utilization of knowledge/information between individuals

and groups. KMS has been used to facilitate

organizational learning by storing organizational

The Contribution of Technical and Social Factors to the Knowledge Management

Systems

Z. Zoolkefli1, N. F. Uteh

1, Z. Endot

1, N. S. Md Soh

2

1Faculty of Business Management, Universiti Teknologi MARA, Johor Bahru, Malaysia

2Academy of Contemporary Islamic Studies, Universiti Teknologi MARA, Johor Bahru, Malaysia

([email protected])


KM - 19

knowledge/information and having it available to

employees when needed [1]. The idea of KMS is to

enable the employees of the organization to have access to

the company’s knowledge of facts, sources of

information, and solutions. Having employees share their

knowledge (in brains and files) could potentially lead to

more effective problem solving and it could also lead to

ideas for new or improved products and services [14].

Technical (IS) Success Factors of KMS

Technical factors are the prominent element of this

study to identify their contribution to knowledge

management system utilization. Technical factors are

critical features of a system. [7] also included technical

factors in their study’s framework. The technical factors

are system quality, data quality and service quality. It has

been suggested that these three factors could improve

system usage and user satisfaction. In Jennex and

Olfman’s study (2002), the technical factors that have

been used are information quality and system quality.

Among these researchers, DeLone and McLean

(1992, 2002) have come out with the most popular

framework. Their study on IS success factors suggest two

factors which can affect the usage of IS and user

satisfaction namely information quality and system

quality. In 2002, the researchers have made some

modifications to the framework and added service quality

as another success factors

Social Success Factors of KMS

The social factors used in this study are related to

organizational culture. Organization culture comprises the

shared values, understandings, assumptions and goals.

Most researchers only look at those social factors that

relate to the culture within the organization itself

[25][5][24]. Schein (1992,) defined culture as the way

people do things around the location and situation and the

shared values, beliefs and practices of the people in the

organization. Dimensions of knowledge culture include

management support, vision clarity, rewards, building

contacts and trust [18][13][4][23].

Knowledge Utilization

One of the indicators to measure the deployment of

KMS is by looking at the utilization of knowledge.

Knowledge utilization is the application of knowledge to

solve daily work problems and make decision [3]. Liu

(2003) measured KMS usage by system utilization and

knowledge application. System utilization refers to the

degree to which the organization’s members apply the

system as storage, a pipeline, and/or a discussion platform

to improve individual learning in the organization’s

environment.

Alavi (2000) pointed that the benefits of KMS can be

achieved through knowledge utilization not system

utilization. Individuals can use knowledge for decision

making and problem solving (Alavi, 2000). This study

adopts knowledge utilization to measure KMS usage.

Knowledge utilization in this study refers to the extent to

which the organization’s members use KMS to utilize

knowledge for individual learning.

Previous Research

Hingston (2001) conducted an empirical study about

Knowledge Management initiative at Rio Tinto. Rio Tinto

is one of the world’s largest mining companies and

employed over 30,000 people worldwide, plus

contractors, and has annual gross turnover of around

US$10 billion. This article relates Rio Tinto’s experiences

in implementing this knowledge sharing web site in the

context of a pilot knowledge management programme,

and analyses the factors that have made it successful. The

researcher found that involvement of senior management

was being major driven towards usage of the website.

This indicates that management support and search and

retrieval engine can contribute to the utilization of the

website. Management support and search and retrieval

engine might be considered as the important factors

among others and should be taking into account when the

organizations decide to develop their knowledge system.

Hussain et al., (2004) conducted a study on how to

manage knowledge effectively in corporate and

organizations. He found one of special attention that

should be given to contextual dimensions of organization

was information technology such as digital documents,

intranets, expert system and so on for developing

knowledge management system. Technology plays a key

role in KM’s trend. To facilitate the environment,

intranets must be designed to support not only the

informational aspects but also include people by making

salient networks of users with similar interests and allow

them to communicate and collaborate. Thus intranet

technology can be an effective tool for managing

knowledge inside the organizations therefore enhancing

productivity and helping organizations to improve their

performance. Indirectly, this indicates that good system

search/retrieval level (intranets) and system form are

important for KMS utilization.

In other research, Goh (2004) described future

challenges for organizations to exploit the benefits of

knowledge innovations. The most interesting part that has

been discussed was about knowledge utilization

infrastructures, which closely related to information and

communication technology (ICT). According to the

researcher, the internet heralds the way for collaborative

utilization of knowledge assets. To accomplish

knowledge-utilization infrastructures for knowledge

innovations, organizations should provide adequate

support for codifying and storing knowledge, creating

knowledge maps, sharing best practices and developing

knowledge networks [1][4]. Particularly to exploit

internet, the characteristics of its knowledge-utilization

infrastructures should possess certain characteristics such

as uses a widely-supported communications standard


KM - 20

Technical Factors

System Quality

protocol, offers world-wide access, avails end-user

software, employs a high speed, broadband, digital

network and provides a quick means of publishing

information, through the World Wide Web that can be

shared globally.

III. RESEARCH MODEL AND HYPOTHESES

The purpose of this study is to test (empirically) the

influence of technical and social factors toward the usage

of knowledge management system. The research model

for this study as shown in Figure 1 is based on previous

research conducted by [3].

For the purpose of this study, the framework has

been modified and simplified. This study proposes that

technical factors i.e., information quality, system quality

and service quality and social factors i.e., consist of

management support, knowledge trust and utilization

rewards are contribute to the utilization of KMS.

Figure 1: Research Model

Research Hypotheses

Based on the problem statements and objectives of this

study, the research hypotheses for this study are:

Hypothesis (H1): Information quality positively affects

KMS utilization.

Hypothesis (H2): Search level positively affects KMS

utilization.

Hypothesis (H3): System form positively affects KMS

utilization.

Hypothesis (H4): Service quality positively affects KMS

utilization

Hypothesis (H5): Management support positively affects

KMS utilization.

Hypothesis (H6): Knowledge trust positively affects KMS

utilization.

Hypothesis (H7): Utilization rewards positively affect

KMS utilization.

IV. METHODOLOGY

Data were collected through a questionnaire from

engineer and non-engineer employees of ‘XYZ’ company

in Johor Bahru. The company has been using knowledge

management system (KMS) for more than four years. The

company employs approximately one hundred (100)

employees. The multiple regressions were utilized to

analyse the data. Descriptive statistics such as percentage

(%) also used in this study

V. RESULTS AND ANALYSIS

Forty (N=40) questionnaires were distributed to the

respondents who were engineers and non-engineers. Table

1 shows that male respondents in this study were 21

persons (52.5%) and female were 9 persons (47.5%).

Social Factors

(H1) Information

Quality

(H2) Search/retrieval

level

(H4) Service quality

(H3) System form

(H5) Management

support

(H6) Knowledge trust

(H7) Utilization

rewards

Knowledge Utilization


KM - 21

TABLE I DEMOGRAPHIC PROFILE OF RESPONDENTS

Category Percentage (%)

Gender Male Female

42 58

Age <25 26-30 31-40 >41

26 46

24

4

Work experience <1 year

1-5 years

6-10 years >11 years

28

55

12 5

Race Malays Chinese

Indians

58 27

15

KMS Use Yes

No

100.00

0

KMS Period <1 year 1-<2 years

2-<3 years

>3 years

7.5 30.0

35

27.7

Next, multiple regressions was conducted and Table II

shows the summary of the results of multiple regression.

The value of variance inflation factor is less than 10. R

value is 0.30, showing 30% variance in KMS utilization

as explained by 7 independent variables tested.

TABLE II

RESULTS OF MULTIPLE REGRESSIONS

Multiple R = 0.548

R Square = 0.300

Adjusted R2 = 0.147

Standard Error =0.62

Variable Beta t Sig.

Information Quality -0.26 -0.856 0.398

Search Level 0.47 1.839 0.075

System Form

-

0.159

-0.591

0.559

Service Quality

-

0.669

-2.452

0.020

Management Support 0.690 2.196 0.035

Knowledge Trust

-

0.338

-1.552

0.131

Utilization Rewards 0.161 0.556 0.582

Multiple regression analysis shows 2 significant factors

which influence KMS utilization, that is, service quality

(β = - 0.669, α = 0.020) and management support (β =

0.690, α = 0.035). However, the influence of others such

as information quality, search level, system form,

knowledge trust and utilization rewards toward KMS

utilization are not significant. Figure 2 shows final

research model.

Figure 2: Final Research Model

*significant at 0.05

IV. CONCLUSION

This research was carried out to identify technical and

social factors which influence knowledge management

system utilization. Based on literature review, the

researcher had developed one research model that

explained factors which influenced KMS utilization that

included 7 variables, namely information quality, system

search/retrieval level, system form, service quality,

management support, knowledge trust and utilization

rewards. From the results of multiple regression that had

been conducted, two factors were found to significantly

influence KMS utilization, that is, service quality and

management support. Service quality in this study

measured support level given by Information

Technology/System staff to end users.

From the results of this research, it is revealed that

management support also influenced the KMS utilization.

Management support was identified as the most important

KMS

Utilizatio

n

System Form

Information Quality

Search Level

Service

Quality

Management

Support

Knowledge

Trust

Utilization

Rewards

-0.260

0.470

0.161

-0.338

0.669*

-0.669*

-0.159


KM - 22

social factor to KMS utilization since it has a power to

move the organization towards KMS implementation. In

this study, management support was measured by four

measurements: clarifying the importance of KMS to

organization’s success, clarifying the objectives of KMS,

encouraging employee to use the information from KMS

and providing employee time to use the KMS. According

to Davenport and Prusak (1998), management support is

needed to endorse a KMS project, to clarify its objective

and to encourage end users and allow ample time to

utilize the system.

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Management and Knowledge Management Systems:

Conceptual Foundations and Research Issues. MIS

Quarterly. 25(1): 107-136.

[2] Alavi, M. and Leidner, D. (2000). Managing Organizational

Knowledge in R. Zmud (Ed.), Framing the Domains of IT

Management. Cincinnati, OH: Pinnaflex.

[3] Al-Busaidi, K.A. (2005). A Socio-technical Investigation of

The Determinants of Knowledge Management Systems

Usage. Claremont Graduate University, Claremont, CA:

PhD Thesis.

[4] Davenport, T.H. and Prusak, L. (1998). Working

Knowledge. Boston, MA:Harvard Business School Press.

[5] Davenport, T.H. and Prusak, L. (1998). Working

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Success Revisited. Proceedings of the 35th Hawaii

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2002. Vienna, Austria.

[7] DeLone, W. and McLean, E. (1992). Information Systems

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Biggest Challenge. California Management Review. 41(2):

45-53.

[9] Drucker, P. F. (1999). Management Challenges for 21st

century. Harper Business, New York.

[10] Edge, K. (2005). Knowledge Management as A Tool for

District-level Instructional Renewal. University Of Toronto,

Canada: PhD Thesis.

[11] Firestone, J.M. and McElroy, M.W. (2005). Doing

Knowledge Management. Learning Organization Journal.

12(2): 12-20.

[12] Gupta, A. and McDaniel, J. (2002). Creating Competitive

Advantage by Effectively Managing Knowledge: A

Framework for Knowledge Management. Journal of

Knowledge Management Practice. 3(2): 40-49.

[13] Gold, A.H. Malhotra, A. and Segars, A.H. (2001).

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Perspective. Journal of Management Information System.

18(1): 185-214

[14] Halawi, L.A. (2005). Knowledge Management Systems'

Success in Knowledge-based Organizations: An Empirical

Validation Utilizing The DeLone and McLean IS Success

[15] Model (William H. DeLone, Ephraim R. McLean). Nova

Southeastern University: PhD Thesis.

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System Sciences. 7-10 January, 2002. Vienna, Austria.

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Knowledge Management System and The Impact of Use on

Individual Learning. Claremont Graduate University,

Claremont, CA: PhD Thesis.

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S. A. (2003). Knowledge Management: Developing

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2002. Vienna, Austria.

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Hall.


KM - 23

KEY DIMENSIONS OF KNOWLEDGE SHARING

S Ahmed*1, Akhtar

2, S Mallick

3

1Department of Business Administration, FMSR, Aligarh MuslimUniversity, Aligarh, India

2Department of Business Administration, FMSR, Aligarh MuslimUniversity, Aligarh, India

3Assistant Manager, Amfah Group, Dubai, UAE


Abstract- Knowledge is a major source of wealth for an

organisation. Organisations have two sources of

knowledge-one is document which is held in

procedures and processes while the other is tacit which

is resident in people of the organisation.

Organisations regard the management of knowledge

as a resource for sustainable competitive advantage.

While knowledge generation refers to the development

of new or tacit and/ or explicit knowledge from data

and information or from the synthesis of prior

knowledge; knowledge sharing refers to the transfer of

knowledge to other individuals. Sharing of knowledge

is critical for the organisation to grow and prosper.

Though knowledge sharing is viewed as the most

essential process, how far an organisation is able to

leverage and harness it depends upon the willingness

of individuals to share. This objective of the paper is to

identify variables for knowledge sharing prevalent in

organisations and assess the variation of knowledge

sharing dimensions with respect to organisational

variables. Key words- Knowledge, Knowledge Sharing, tacit

knowledge, dimensions of knowledge sharing

I.INTRODUCTION

Knowledge is the primary source of wealth in any

organisation [1],[2],[3],[4] while Knowledge Management

is a strategic and systematic approach to capitalise on

what an organisation knows. Organisations regard the

management of knowledge as a strategic resource for

sustainable competitive advantage. [5],[6]. Today

organisations, to effectively leverage its knowledge, are

highly dependent upon the employees and their

willingness to generate, share and use knowledge.

In the present times, an organisation’s attention has

shifted to people-to-people process for knowledge

sharing.

Since the focus is on people, managers stress that

individuals must share what they know. However,

Davenport [7] argues that sharing knowledge is often

unnatural. People in organisations are not willing to share

knowledge as they think that their knowledge is

proprietary information, and valuable. There is

unwillingness also because they have assimilated

knowledge through years of experience, study and

research; and therefore would not like to divulge it in days

and more so in hours to others.

The purpose of this research is to develop an

understanding of factors that support knowledge sharing.

These factors have been defined as key dimensions of

knowledge sharing.

Objectives of Study

The objectives of the study are:

1. To study parameters or dimensions of knowledge

sharing prevalent in organisations.

2. To assess the variation of knowledge sharing

dimensions with respect to natire of organisation.

II. DIMENSIONS OF KNOWLEDGE

SHARING

The study identified nine dimensions for knowledge

sharing. The nine dimensions were: adaptability,

appreciation, developing employee, encourage innovation,

respect for employee, role model, superior attitude,

transparency and positive feedback.

Adaptability: Adaptability is the ability and flexibility in

handling change or be changed to fit the circumstances

that enables mastering the process of changing a routine.

A proactive knowledge sharing process enables an

organisation to increase quality, productivity and cost

effectiveness and also to introduce new products, services

and routines [8].

Appreciation: An organisation can show its appreciation

by introducing a reward systems. These systems are

comprehensive, consistent, and triangulate particularly on

those aspects of the business that are tied to competitive

success and corporate values. [9]

Developing Employee: Developing of employee is

providing coaching and mentoring the employees for the

success in their careers as well as the organisational goals.

Managers facilitate the subordinate’s career advancement,

mailto:*[email protected]


KM - 24

and the subordinate reciprocates by being helpful, co-

operative and loyal to the organisation. [10],[11],[12]

Encourage Innovation: Encouragement of innovation is a

must to maintain the existing competencies and meet the

competitive advantage. An innovative knowledge sharing

environment should be created. During this process,

employees gain new knowledge and insights through co-

ordination and co-operation of all team members. [13].

An effective knowledge sharing environment accelerates

all the employees for continuous learning through the

experience of self and others. This type of effective

integration of knowledge sharing efforts develops trust in

the organisation. [14],[15]

Respect for Employee: Encouragement and respect for

employees are a basic expectation of any employee in an

organisation. This brings within an employee a certain

level of willingness to share knowledge and expertise,

which otherwise is a resource kept tightly held in their

minds. [16],[17],[18]

Role Model: An effective role model helps his colleagues

to learn positive behaviours, traits, skills and knowledge,

which enhance their efficiency. Role model develops

enthusiasm as well as continuous learning that enable an

effective knowledge sharing environment. [19]

Superior Attitude: Superior attitude goes a long way in

determining whether employees come forward to share

their experience and knowledge. Open communication,

flexible work environment, and easy approachability of

top management to all the employees defines superiors’

attitude to the organisation and motivates all the

employees to share the knowledge which further

contributes to competitive advantage to the organisation.

[20]

Transparency: Transparency refers to accessibility of

data, information and knowledge to all levels of

employees in the organisation. Companies are practicing

360 degree transparency to achieve competitive advantage

through knowledge management. [21]

Positive Feedback: Positive feedback helps bring about

organisational effectiveness in the form of more satisfied

employees and more involved employees.

Positive Feedback: The relationship positive feedback has

on the behaviour of employees have been examined in a

number of research studies. [22]. Positive feedback

results in more satisfied employees and more involved

employees. [23], [24]. Similar findings were also found in

other studies that measured positive feedback behaviour

of employees through knowledge sharing efforts.

[25],[26]

III. RESEARCH METHODOLOGY

An exploratory study (qualitative study) was undertaken

to identify dimensions for knowledge sharing.

Respondents comprised of executives working in the

industry and academicians from management institutes

falling into four age groups (25-35 years of age, 35-45

years of age, 45-55 years of age and 55 and above years

of age) who have been in service for five or more years.

This comprised of male as well as females. (Refer Table-

1-4) Convenience sampling was used.

IV.DEVELOPMENT OF RESEARCH SCALE

The study was conducted in two phases. In the first phase,

a questionnaire was designed and developed to identify

parameters that could encourage knowledge sharing. It

initially consisted of 52 different items. Content validity

was undertaken. The questionnaire was reviewed by ten

executives who were selected randomly and their

suggestion incorporated. Finally a questionnaire of 33

statements was arrived at.

In the second phase, the questionnaire was administered

to 152 respondents. The study also measured the strength

of each statement using a five point Likert Scale where 5

indicated the highest score (representing strongly agree)

and 1 indicated lowest rank (representing strongly

disagree).

V. STATISTICS TOOLS APPLIED

The statistical tools used were independent sample-t test.

Also the mean values were calculated for each dimension

to identify where the values were high and the reasons

thereof.

Hypothesis:

The hypotheses formulated were:

Ho1: There is no significant variation of Adaptability viz

a viz nature of organisation.

Ho2: There is no significant variation of Appreciation viz


Ho3: There is no significant variation of Developing viz a

viz nature of organisation.

Ho4: There is no significant variation of Encourage

Innovation viz a viz nature of organisation.

Ho5: There is no significant variation of Respect for

Employee viz a viz nature of organisation.

Ho6: There is no significant variation of Role Model viz


Ho7: There is no significant variation of Superior Attitude

viz a viz nature of organisation.

Ho8: There is no significant variation of Transparency

viz a viz nature of organisation.


KM - 25

Ho9: There is no significant variation of Positive

Feedback viz a viz nature of organisation.

Analysis:

Knowledge sharing dimension was analysed with respect

to nature of organisation:

On the basis of t test, it was concluded that there is no

significant variation of adaptability with respect to nature

of organisation. (Refer Table-5). It was observed that the

mean score obtained in the corporate sector was higher

(3.2944) as compared to academic institutions wherein the

mean value obtained was only 3.1517. (Refer Table-6)

On the basis of t, the researcher noted that there is a

significant variation with respect to the nature of

organisation. The mean value was found to be very high

among corporate (3.5040). In academic institutes it was

observed to be 3.2360 only.(Refer Table-6)

On the basis of t tests, a conclusion was reached that there

existed no significant variation of this dimension with the

type of organisation. This was further supported by the

mean value obtained which was 3.2688 for the corporate

and only 3.1461 for the academic institutes .(Refer Table-

5 &6)

A significant variation was noted with respect to the type

of organisation surveyed. The mean value in this

dimension also was very high for the academic institute

(which was 3.4242) and for the corporate were 3.1492.

This hypothesis was accepted and this was further

supported by the average mean values which was 3.6734

for corporate. It was only 3.3848 for the academic

institutes.

On the basis of t test, a conclusion was reached that there

existed no significant variation with respect to role model.

The mean scores obtained was high in the corporate for

both these dimensions; for the corporate sector it was

observed to be 3.6734 with regard to the dimension

respect for employees while for the academic institutes it

was only 3.3848; and the mean values for role model

were 3.1237 and 3.0824 for corporate and academic

institutes respectively.

No difference was noted with respect to the attitude that

superiors have towards the subordinates Corporate

displayed a more positive attitude towards juniors as

compared to academics (the mean values being 3.4731 for

corporate and 3.3221 for academics).

The study revealed that there existed no variation in

transparency with respect to organisational variables. The

mean score obtained was high for the corporate (3.4355)

while it was only 3.2191 for academic institutes.

On the basis of t test, a significant variation was noted in

transparency with respect to nature of organisation and it

was noted that the mean value was very high (3.3708) for

the corporate while it was only 3.3226 for academic

institutes.

The study further revealed that the mean values obtained

was high for most dimensions in the corporate sector

while it was high in academic institutes only in case of

two dimensions, they being encourage innovation and

positive feedback.

VI.DISCUSSION

For the purpose of this research study, knowledge sharing

framework has been tested with nine distinct variables.

The study reveals that there is no significant variation of

the dimension adaptability, developing employee, role

model, superior attitude, transparency, and positive

feedback with respect to nature of organisation. This

reveals that whether it is academic institutions or business

organisations, both ensure that they welcome change and

in process allow sharing of knowledge to take place.

Organisations and academic institutes both are willing to

coach and mentor employees for the betterment of career

prospects and this is facilitate through the process of

knowledge sharing. They take care to chalk out career

opportunities for employees and thus encourage

knowledge sharing to take place. Also these organisations

have superiors who take the place of role models and help

them learn positive behaviour and skills. Also both these

organisations adopt open and flexible work environments

which encourage employees to come forward to exchange

their knowledge and skills. Further these organisations are

also transparent in their dealing encouraging sharing of

knowledge to take place. Also these organisations display

positive feedback on the behaviour of employees and this

result in success knowledge sharing environment in

organisations and academic institutes.

Further, the study also revealed that there exists

significant variation of certain dimensions of knowledge

sharing with respect to nature of organisations. These

dimensions were appreciation, encourage innovation, and

respect for employee. Appreciation is a dimension

wherein there is significant difference in perception of

academic institute and corporate. This means that

superiors and peers more openly appreciate good and

valuable work of a colleague and design reward system

that encourage knowledge sharing to take place and

finally add to the organisation’s competitiveness.

Encouraging innovation is another dimension wherein the

values differ significantly; indicating that through co-

operation of peers and seniors innovative opportunities

can be created for employees thus creating a culture for

knowledge sharing to take place. Displaying respect for

employees is a basic expectation of any employee in an


KM - 26

organisation. This brings within an employee a certain

level of willingness to share knowledge and expertise,

which otherwise is a resource kept tightly held in their

minds. The value of this dimension is different with

respect to nature of organisation.

VII. CONCLUSIONS-MANAGERIAL

IMPLICATIONS

The research study revealed that there exists a significant

difference in certain parameters of knowledge sharing

with organisational variables. These variables are

appreciation, encourage employees and respect for

employees and there was no significant variation with

respect to other dimensions. Further the study also

revealed that the mean values obtained was high for most

of the dimensions were in the corporate sector while it

was high in academic institutes only with respect to two

dimensions, they being encourage innovation and positive

feedback. The academic institutes, therefore, need to

learn from the corporate sector and promote a culture of

knowledge sharing prevalent in corporate sector to

enhance their productivity.

Proposed Research Model:

Adaptability

Appreciation

DevelopingEmployee

Encourage Innovation

Respect for Employee

Role Model

Superior Attitude

Transparency

Positive Feedback

KnowledgeSharing

Fig. 1

Table-1.

Gender

Frequency Percent Valid Percent Cumulative

Percent

Valid 1 91 59.9 59.9 59.9

2 61 40.1 40.1 100.0

Total 152 100.0 100.0

Table-2.

Age


Percent

Valid 1 103 67.8 67.8 67.8

2 34 22.4 22.4 90.1

3 7 4.6 4.6 94.7

4 8 5.3 5.3 100.0

Total 152 100.0 100.0

Table-3.

Exp


Percent

Valid

1 103 67.8 67.8 67.8

2 33 21.7 21.7 89.5

3 16 10.5 10.5 100.0

Total 152 100.0 100.0

Table-4.

CORP/AC


Percent

Valid 1 62 40.8 40.8 40.8

2 90 59.2 59.2 100.0

Total 152 100.0 100.0

Table-5.

Hypothesis t/f Sig

value

Remarks

Ho1 There is no significant variation

of Adaptability viz a viz nature

of organisation.

0.125 0.212 Accepted


of Appreciation viz a viz nature

of organisation.

2.044 0.040 Rejected


of Developing Employee viz a



Ho4 There is no significant variation of Encourage Innovation viz a



Ho5 There is no significant variation of Respect for Employee viz a




of Role Model viz a viz nature of organisation.



of Superior Attitude viz a viz nature of organisation.



of Transparency viz a viz nature of organisation.



of Positive Feedback viz a viz

nature of organisation.



KM - 27

Table-5.

Analysis of the dimensions of Knowledge sharing with nature of

organization

CORP/A

C N Mean Std. Deviation

TR 1 62 3.4355 .72278

2 89 3.2191 .87485

AD 1 62 3.2944 .59459

2 89 3.1517 .74584

RE 1 62 3.6734 .73355

2 89 3.3848 .82577

AP 1 62 3.5040 .83530

2 89 3.2360 .78729

DE 1 62 3.2688 .84249

2 89 3.1461 .78970

EN 1 62 3.1492 .77942

2 89 3.4242 .84813

PF 1 62 3.3226 .74160

2 89 3.3708 .96326

RM 1 62 3.1237 .57334

2 89 3.0824 .70582

SA 1 62 3.4731 .77424

2 89 3.3221 .90934

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KM - 28

Abstract— This qualitative study aims to explore and

describe the knowledge sharing networks used by

academicians to share their knowledge. The study was

conducted in a Malaysian public university. A single case

study strategy used to gather deeper insights on the

knowledge sharing networks. A face-to-face semi-structured

interviews were used to collect the study data over a six

month period. A total of 15 renowned academicians were

interviewed. Content analysis method was used to extract the

themes from the qualitative data. This study reveals that

academicians share their knowledge through three main

knowledge sharing networks. These networks are Business

Club Network, Research Network, and Personal Network.

The research findings may expand an area of knowledge

sharing networks in universities which still theoretically and

empirically not sufficiently covered.

Keywords- Knowledge Sharing Network; Academicians;

Malaysian Public Academic Institutions.

I. INTRODUCTION

Knowledge is a vital resource for organizational [1].

Many researchers emphasize the importance of sharing

knowledge to increase the organization value [3,4,5]

including academic institutions [6]. The network leads to

intensifies and diffuse ideas and knowledge to high level

of extent which could not be reached by individuals or

organizations alone [17]. It is important for individual,

particular, within learning institutions to engage and share

with other members. In their paper, [7] emphasize that the

individual learning has to cooperate and interact with their

dynamic social environments so as to contribute to

organizational learning. The network is playing an

important role for sharing knowledge. As [10], creating a

knowledge network is the most valuable activities which

knowledge management should focus on. The benefit of

creating effective knowledge networks which include

enhancement of organizational efficiency [10]. Such that,

this research aims to explore and describe the knowledge

sharing networks used by academicians in public

academic institutions.


Recently, the knowledge sharing networks have

received increased consideration. The "networks'' term

can be understood as those between individuals, groups,

or organizations [7]. Knowledge network is "a set of

actors connected by a set of repeated interaction of formal

and/or informal ties" [8, p.4]. The actors according to

them, encompass humans and organizations such as

academic institutions or industry organizations and so

forth. The relationships among those actors describe as

ties. The relationships between actors can be classified

according to "contents (e.g. products or services,

information, emotions), form (e.g. duration and closeness

of the relationship) and intensity (e.g. communication-

frequency)" [7, p.182]. For the purpose of this research,

knowledge network is referred to individuals and

organizations cooperate and connected together with the

aim of sharing knowledge.

Several knowledge networks have been identified and

described. Through reviewing literatures, five important

types of network have been identified. These networks are

Community of Practice Network, Business Club network,

Personal network, Strategic Alliance network, Research

network, and Learning network. Most of these networks

have different activities and ties characteristics. Some of

them, however, have similar characteristics, especially, in

the ties relationship. Those five networks could be found

in many sectors including education sector.

The Business Club network has been defined by [8] as

"Platform where responsible people or representatives of

organizations can meet each other with the aim to learn

from each other by gathering, talking, listening and

exchanging experiences" (p.27). This network normally is

establish and manage by a partnership of interested

organizations including local councils, utility companies,

government, and universities, and all actors in this

network should have expertise in relevant and specific

areas that needed by most [11]. In their study [8],

highlight that, Business Clubs are often established for a

specific purpose, like for instance, developing sustainable

practices in a certain sector. On the other hand, the

Community of Practice network defined as "A group of

people informally bound together by shared expertise and

passion for a joint enterprise" [12, p.139]. In a community

of practice, individual share their experiences and

knowledge in free- flowing. The communities of practice

normally comprise members who share knowledge, ideas

and insight, experience in an interested area [13].

According to [13], these communities have more

opportunity to increase over time compared with being

projected or driven by a specific deadline. The Personal

network consists of the set of people including relatives,

friends, colleagues, fellow members of organizations, and

acquaintances with whom the focal person has a direct

personal relationship [14]. The personal network is

Knowledge Sharing Networks Used by Academicians in Malaysian Public

University

S. Alsaleh*1, H. Haron

2

1 General Directorate of Health Affairs in Hail, Ministry of Health, Hail, Saudi Arabia

2 Faculty of Computer and Mathematical Sciences, University Technology Mara (UiTM),Shah Alam, Malaysia

(1 [email protected])

(2 [email protected])


KM - 29

characterized by a decentralized structure since its

members initiate and make a lateral relationship [8]. The

Strategic Alliance network is a group of organizations

entering into voluntary and formal arrangements to share

common knowledge with several purposes including

technologies, product development, and enhance services

[15]. The Research network can be defined as a collection

of associations, social companies, governmental

organization, institutions, [individuals] which

collaborating to do research [8]. Here, according to [8] the

"innovation takes more and more place at the interface

between different domains of expertise, to offer solutions

to increasingly complex challenges. In such environment,

the need for specialization as well as collaboration

between the actors increases" (p.16). Finally, the Learning

network is a network within an organization where its

structures and systems has established with the aim of

increasing the participants’ knowledge [16]. Members of

this network have the opportunity to interact and share

their knowledge with professionals in similar fields and

interests [16]. Table 1 in Appendix A summarizes the

knowledge network types and its main characteristics.

III. METHODOLOGY

The research orientation was a descriptive form of

qualitative research. Because the aim of this research is to

comprehensively describe and build in depth

understanding of knowledge networks being used by

academicians, thus, a qualitative approach is most

appropriate. The key element for qualitative research is to

learn about the issue from participants and involve in the

best practices to get the information needed [22].

According to [18], implementing a qualitative research

can contribute to both a theoretical as well as empirical

advancement. To determine the research participants, a

purposeful technique was used. The purposeful sampling

is the main technique in a qualitative research that would

assist the researcher to choose the most appropriate

sample who be able to answer questions of research [19].

To minimize the potential researcher bias, a high level of

integrity has been done. For example, the participants had

been noted that their involvement in the study is volunteer

and they have a freedom to deny or accept to participate.

Participants who accept the invitation, they had a choice

to suggest the appropriate both place and time to conduct

the interview. The data were collected from fifteen

academic staffs in one Malaysian public universities. The

qualitative research sample size is often small [20, 21].

The university has been chosen to be a site for this

research because it is one of the largest universities in

Malaysia with about 480 academic programs in both

modes of study (i.e. Coursework and research), so, that

would offer great opportunities for identifying and deep

understanding the various knowledge networks that its

academic staff is really shared with.

The data were collected from the participants over a

six month period through conduct face-to-face semi-

structured interviews. Besides, other activities are

considered during the data collection and coding. For

instance, the participants during conducting the interview

have been encouraged to elaborate more through probing

questions based on their answer. The research question

developed based on grasping the problem of research

through both reviewing as well as examining of related

literatures. As [22], the qualitative researcher "do not tend

to use or rely on questionnaires or instruments developed

by other researchers" (p.45). The interviews continued

until the respondents no give differing information, and

data saturation developed in their responses. Reaching to

the saturation stage determines the point at which

adequate data have been generated, accordingly, the

sufficient number of participants to be involved [23].

Only two participants' having an Associate Professor

positions' and thirteen having a Professor positions', three

of them are deans of faculty. Two more participants'

answers were deleted since they did not give considerable

and informative information because of their limited free

time. The study participants work in many faculties and

disciplines. In spite of the participants work in different

faculties, the conclusion is that they have been a

homogeneous participants as all of them were academic

staff and there was no any non-academic staff engaged.

According to [24], the researcher should heed the finding

validity when he/she conducts a qualitative research.

Steps were taken in a credible scholarly to ensure the

research findings validity. Specific strategies to promote

qualitative research validity have recommended by [9]. In

this study, there were two strategies have been used to

promote the findings which are the Low Inference

Description and Data Triangulation. Table 1 illustrates

these strategies. The low Inference Description in this study has been

tested through present the views of respondents by using

quotations from the participants' answers. "A verbatim is

the lowest inference descriptor of all because the

participants' exact words are provided in direct quotation"

[9, p. 285]. In addition, [22] point out that the researcher in

qualitative research should bring in the voice of participants

in the study such as use many quotes. Data Triangulation

for this research, a multi-interview in different places and

times have been done.

TABLE 1

QUALITATIVE RESEARCH VALIDITY STRATEGIES

N Strategy Description

1 Low inference

description

The use of Description phrased very

closed to the participants' accounts and

researchers' field notes. Verbatim (i.e.

Direct quotations) is a commonly used

type of low inference descriptor.

2 Data Source

triangulation

The use of multiply data sources to

help understand a phenomenon.

"Another important part of data triangulation involving

collecting data at different times, at different places, and

with different people" [9, p. 289].


KM - 30

IV. DATA ANALYSIS & FINDING

Data Analysis

The site which this research conducted was a public

university in Malaysia and has been established in 1956.

The university has been chosen since it is one of the

largest universities in the country. It has expanded

nationwide with fifteen branch campuses distributed in all

the country states. Also, it has three satellite campuses,

nine city campuses and twenty-one affiliated colleges.

With this vast network as well as seventeen thousand

workforce, the university offers about five hundred

academic programs, and there are about one hundred and

seventy two thousand students study at the university. It

has earned a good reputation as being one of Malaysia's

innovative and entrepreneurial universities, as it has

formed linkages with many and various industrial sectors.

Fifteen participants were involved in this research, nine

males and six females. For the confidentiality purpose, the

participants' names have been hidden. All the participants

in this study held a PhD degree which is the highest

degree can all universities grant, thus, the participants in

this research consisted of highly educated academicians.

The participants' expertise during the interview were very

noted. For instance, they gave long and informative

answers and explanation when they asked during the

interview. The data were collected from the study

participants who work in various faculties and disciplines

through face-to-face semi-structured interviews over a six

month period. Although the participants work in different

faculties, the conclusion is that they have been a

homogeneous participant group since all of them were

academicians. To minimize the bias as much as possible,

the schedule of all interview was prepared in a standard

manner for all participants, allowing minimal allowances

for researcher’s bias. During the data collection and

coding, other activities were recorded and considering.

For instance, in the interview, the participants have been

encouraged to discuss and talked more through probing

questions. The interviews were conducted until the

participants no longer provided differing or new

information, and data saturation developed in the answers.

A qualitative content analysis was conducted to

analyze all the data that have been collected from the

participants. As a qualitative research, the study procedure

established an analysis as well as coding the participants'

answers. In the coding process, the interviews with the

study participants have been taped by using the electronic

voice recorder and then transcribed into textual format.

The participants' responses have been reviewed numerous

times to determine the concepts and name of the

networks. The categorization process of knowledge

sharing network has been achieved based on group of a

similar participants answer together. According to [2]

"Code labels emerge from several sources…. They might

be also drawn from names the researcher composes that

seem to best describe the information" (p.185). Protégé

software was used to analyze and model the findings in a

graphical context and to determine the relationships

among the Networks types became apparent.

Research Findings

The research found three main networks which

academicians share their knowledge with others through.

These networks are Business Club network, Research

network, and Personal network.

1. Business Club Network

Business Club network in this research refers to a

platform where academicians meet others for talking,

listening, and exchanging experiences as well as

knowledge with the aim to learn from each other. Through

Business Club network, the research results reveal that the

academicians share their knowledge with three groups of

people include academicians at Local and International

Universities, with workers in Government organization,

with workers in Private organizations. Details about

university names, locations as well as details about both

government and private organizations types and names are

listed in tables 2,3,4,5,6 in Appendix A. Fig.1 shows the

organizations which the academicians share with which

considered under the Business Club network.

2. Research Network

Research network refers to a group of individuals from

same or different associations, companies, governmental

organization, institutions which collaborating to do

research. This research finding indicated that the

academicians share their knowledge with five main

research group networks which are Chemical Technology

research group, Chemical Engineering research group,

Information Retrieval research group, Knowledge

Management Society research group, and Asian

Information Retrieval Society research group.

In general, in Research network, the research groups

usually share their knowledge virtually through some

Internet applications such as email and forums, because

they probably belong to different organizations at

different places and countries.

Fig.1: Organizations in Business Club Networks

In addition to sharing knowledge virtually through the

Internet, they have weekly or monthly meetings where

their research group members shares their research

knowledge through face-to-face discussion. Fig.2 shows


KM - 31

the Research Networks names that have been identified in

this research.

3. Personal Network

The Personal network consists of the set of people

including relatives, friends, colleagues, fellow members of

organizations, and acquaintances with whom the focal

person has a direct personal relationship. Under this

network, the research found three main people who

academicians share their knowledge with which are

Colleagues, Friends, and Students. For the purpose of this

research, the colleagues refer to an academic and non-

academic staff who works with academician in the same

workplace (i.e. University).

It can be interpreted from the participants' responses

that they share their knowledge with different groups of

people through these three networks. There were eight

groups of people they were shared with. These groups

include Academicians in Local Academic Institutions,

Academicians in International Academic Institutions,

Workers in Governmental Organization, Workers in

Private Organization, Research Groups, Friends, Students,

and Colleagues. Fig.3 shows the Personal knowledge

network which academicians share with. In Appendix A,

Fig.1 illustrates all the knowledge sharing networks that

academicians share their knowledge with.

V. FINDINGS DISCUSSION

The multiple efforts of data analyses have been

conducted to ensure thematic categories were accurate.

Many research articles were reviewed with the aim of

understanding of qualitative findings. The purpose of this

study is to explore, describe the knowledge sharing

networks among academicians in academic institutions.

The category analyses centered on research question

which was what are the knowledge networks used by

academicians to share their knowledge. In other words,

with whom they share their knowledge.

Fig.2: The Research Networks Name

Fig.3: The Personal Knowledge Networks

As has been found, the academicians share their

knowledge with eight groups of people which are

academicians at local academic institutions, academicians

at international academic institutions, workers in

government organization, workers in private organization,

research group members, friends, students, and

colleagues. Through reviewing and analyzed a knowledge

network related literatures, these groups of people belong

to different types of knowledge network. In this research,

the academicians in the universities, the workers at

governmental and private organizations have been

categorized under a Business Club Network because they

normally have been appointed and candidates by their

institutions or organizations to attend some knowledge

sharing related activities (such as conference, seminars,

colloquiums etc..) with aims of learning from each other.

The Business Club is a platform where responsible people

or representatives of organizations gathering and talking

with each other in order to learn [8]. "The business clubs

are typically initiated and run by a partnership of

interested organizations such as local councils, utility

companies, government, technical support organizations,

regulators, and universities, with expertise in specific

areas of relevance to most members of the business

group" [11, p.330]. The second knowledge sharing networks which the

research result revealed is the Research Network. Five

different Research groups have been identified (i.e. Chemical

Technology research group, Chemical Engineering research

group, Information Retrieval research group, Knowledge

Management Society research group, and Asian Information

Retrieval Society research group) and classified them under

the Research Network. These categorized under the

Research network because their main aim from

communication and collaboration is merely for doing a

research. As [8] points out, the Research Network is a group

of people in different organizations and institutions which

they are collaborating to do research. Further, the

academicians share their knowledge with their colleagues,

students and friends groups. It has been found that these

groups of people whom academicians share their knowledge

with are belong to a Personal network. The Personal

network consists of the set of people including relatives,


KM - 32

friends, colleagues, fellow members of organizations, and

acquaintances with whom the focal person has a direct

personal relationship [14] included students. The students

have been included in this network because the nature of

direct relationship between them and their lecturers

(academicians) as it is indicated by [14]. It should be noted

that the sharing of knowledge here with students does not

mean teaching. The researcher in this research differentiates

between teaching and sharing. Sharing of knowledge with

students means that when the academicians have not or it is

not their duty or responsibility to share with that particular

students like for instance when academicians share

knowledge that not related to their subjects such as social

knowledge.

VI. Conclusion & Future Work Recommendations

This study identified three main knowledge sharing

networks used by academicians in academic institutions.

These networks are Business Club Network, Research

Network, and Personal network. This research extends

prior research on knowledge sharing networks in academic

institutions, particular, universities. The study findings

might provide useful insights for university

administrations to exploit and utilize these knowledge

sharing networks to enhance their academic staff

performance through sharing the most valuable

knowledge. It is hopefully also this research contribute to

current and future research on knowledge sharing

networks, specifically, in the universities. As this research

focused on the solely knowledge sharing networks among

academicians in universities, it is recommended to study

the type of knowledge sharing networks that being used

by other staff in the academic institutions such as for

instance, non-academic staff.

ACKNOWLEDGMENT

The authors of this research paper introduce their

thankfulness to the Saudi Ministry of Higher Education

for its moral support and encourage.

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KM - 33

Appendix A

Table 1: Knowledge Network Types in Literatures

N Author/s Knowledge Network Characteristics

1 (Schutte & Du Preez, 2008)

Wenger and Snyder (2000)

Community of Practice Network - Informal ties

2 Van Tilburg (1998) Personal Network - Informal ties

3 Hyde et al. (2002) Business Club Network - Initiated & run by a partnership of interested

organizations -Need expertise in specific relevance areas

4 (Rowley, Behrens, & Krackhardt,

2000)

(Mowery, Oxley, & Silverman, 1996)

Strategic Alliance Network - Formal ties

- Private initiative

5 (Apostolou et al., 2003) Learning Network - Formal ties. -Interaction among different organizations with similar

needs.

Table 2: Local Universities Summary

N University name

1 Universiti Sains Malaysia (USM).

2 Universiti Malaysia Terengganu.

3 Universiti Teknologi Malaysia (UTM).

4 Universiti of Malaya (UM).

5 Melaka Manipal University.

6 Universiti Putra Malaysia (UPM).

7 Universiti Malaysia Perlis.

8 The University of Nottingham.

9 Universiti Kebangsaan Malaysia (UKM).

10 International Islamic University of Malaysia (IIUM).

11 Universiti UTARA Malaysia (UUM).

12 Tunku Abdul Rahman Universiti.

13 Universiti of Selangor (UNISEL).

Table 3: Countries and Universities Names

N Country University

1 Japan 1. Tokyo University

2. Kyushu University

3. Nagoya University 4. Tsukuba University

5. Waseda University

2 Indonesia 1.Indonesia Islamic University

3 India 1. B.S. Abdur Rahman University

2. Manipal University 3. Noorul Islam University

4 Germany 1. Hannover University

5 South Korea 1. Daegu University

6 Brunei Darussalam 1. Universiti Islam Sultan Sharif Ali

Table 4: Governmental Organizations Name

N Governmental Organizations

1 SIRM (Standards and Industrial Research Institute of Malaysia)

2 Malaysian Dental Council

3 Ministry of Health

4 Ministry of Higher Education

5 Department of Environment

6 Prime Minister Department

7 Police Force

8 Construction Industry Development Port (CIDP)

9 EU-Malaysia Biomass Sustainable Production Initiative


KM - 34

Table 5: Private Organizations Name

N Private Organization

1 Malaysian Film Festival

2 PLC System Malaysia Company

3 Global Green Synergy company

4 Ribogreen company

5 Perodua company

6 Proton company

7 Shell company

8 TESS Company

9 Matrix company

Table 6: Colleagues Types and Positions

N Non-academic staff Academic staff

1 Recodes managers Junior lecturer

2 Archivists Lecturer

3 Knowledge management officers Senior lecturer

4 Librarians Professor

5 Technicians

6 Managers of human resource departments

7 Assistance engineering

8 Lab assistances

Figure 1: Knowledge Sharing Networks


KM - 35

Abstract - Higher education institutions are considered as

specialists and experts in knowledge sharing activities.

Furthermore, Knowledge sharing activities in universities

is a common occurrence for both administrative and

teaching department. knowledge sharing activities help

higher education institutions to achieve success and have

future development. Academic staff tacit knowledge

considered as a key role in creating, dissemination and

transferring of new knowledge to spur innovation as well

as it will enhance teaching and research method.

Academic staff are promoted and evaluated based on their

individual academic research output. Thus, knowledge

retention is seen as a power for the academic staff. To

overcome knowledge retention problem, management

must encourage academic staff must work together and

try to eliminate the barriers which affect knowledge

sharing activities. Knowledge sharing barriers between

academic staff can be categorized into internal barriers

such as individual barriers and external barriers such as

organizational and technological barriers. Both internal

and external barriers are important for knowledge

sharing activities. The main aim of this review paper is to

highlight the barriers that affect knowledge sharing

activites among academic staff in Malaysia universities.

Keywords–Academic staff, Knowledge sharing

barriers, Malaysia.

I. INTRODUCTION

Higher education institutions are specialists and experts

in knowledge sharing activities [1]. In addition, higher

education institutions have different interests, goals,

priorities, values and needs compared to other business

organizations [2]. As well as their working environment

are different from any other working environment [3],

because the majority of the employees are knowledge

workers [1].

Knowledge sharing activities in universities is a

common occurrence for both administrative and

teaching department, knowledge sharing activity in

administrative department can benefit the administrative

services, alumni services and the development of the

strategic planning, as well as for teaching department

knowledge sharing activities will enhance research

process, curriculum development process [4].

The overall success in higher education institutions and

future development are based on knowledge sharing

activities [5]. Knowledge sharing activities considered

as a normal daily work for the academic staff inside the

higher education institutions [6].

II. RELATED WORK

Faculties in academic institutions have their own

idiosyncratic characteristics [7], and the academic staff

tacit knowledge considered as a key role in creating,

dissemination and transferring of new knowledge to

others organizations to spur innovation [3]. As well as

knowledge sharing activities will enhance the teaching

method which will reflect on student learning and

achievement [3].

knowledge sharing activities can be improved when

higher education institution success in creating a

knowledge sharing culture and environment that

support and encourage academic staff to work together

[4]. In addition, academic staff perceptions and attitudes

toward knowledge sharing are different from other

organizations since they are fully aware of the

important of knowledge sharing activities and how its

benefit on themselves [7].

Knowledge retention as an opposite of knowledge

sharing between the academics staff could be a big

problem, since the academic staff are promoted and

evaluated based on their individual academic research

output [8]. As well as knowledge sharing concerns

about the desire of individuals to share with others the

knowledge they have acquired or created [9]. Thus,

there are a strong motivation for knowledge retention

between academic staff [8]. To overcome this retention,

top management must eliminate any kind of barriers

that may affect knowledge sharing activitie, to help

increase academic staff performance [10].

Academic staff should be encouraged to work together

and exchange their own knowledge as they are the

major component in knowledge management and

collaborative learning to produce new knowledge as a

result of handling existing knowledge [11].

Knowledge sharing activities can be influence by many

factors these factors are divided into internal and

external barriers. Internal barriers which can come from

individually-driven considerations such as: perception,

attitude, behaviour and intention towards knowledge

Knowledge Sharing Barriers Among Academic Staff Perspective from Malaysia

U. N. U. Ahmad

1, A. Hatamleh*

2

1 .Faculty of Management, University of Teknologi Malaysia Johor Bahru , Malaysia

2. Faculty of Management University of Teknologi Malaysia Johor Bahru , Malaysia,

[email protected], [email protected]




KM - 36

sharing activities. External barriers can come from

organizational environment and culture such as:

working condition, organizational structure , and

technological challenge [4].

knowledge management researchers have shifted their

attention from organizational and technological factors

to human factors [12]. Individual barriers get more

attention from the researchers trying to identify and

classify these barriers which affect knowledge sharing

activities since these barriers comes from the person’s

internal being [4].

III. METHODOLOGY

Based on published paper regarding knowledge sharing

among academics staff in Malaysia case, this paper will

highlight the internal and external barriers that can

affect knowledge sharing activities among them.

IV. DISCUSSION

Since knowledge sharing refers to the process of

capturing knowledge or moving knowledge from a

source unit to a recipient unit. Internal barriers that can

inhibit academic staff from applying the knowledge

sharing activities is the individual barriers .

Potential Individual barriers

Barriers stem from individual perception or attitude or

behaviour towards knowledge sharing activities At the

individual level, barriers are diverse .This review has

identified them as shown below:

Lack of Trust.

Personal attitude.

Subjective norms.

Personal expectation.

Lack of rewards.

Lack of time.

Staff is reluctant to seek knowledge

from their seniors because of the fear.

Misused of knowledge.

Misunderstanding the value and

benefit of knowledge sharing.

Knowledge is power.

Poor verbal / written communication

and interpersonal skills.

Affective commitment.

Affiliation.

Reciprocal Relationship.

Peer pressure.

Motivation and opportunities to share.

Lack of trust among academic staff and their attitudes

toward knowledge sharing have been considered the

most important barriers that can affect knowledge

sharing activities , followed by subjective norms and

personal expectations. Lack of time and rewards come

in the third place.

External barriers that can inhabit academic staff from

applying knowledge sharing activities is organization

and technology barriers.

Potential Organizational Barriers

Creating a knowledge sharing culture and environment

that support and encourage academic staff to work

together are a key issues related to organization.

Barriers that can come form organization level are

shows below:

Organizational support.

Incentive system.

Management system.

Organizational culture.

Quality of the place and space.

Lack of formal and informal activities.

Physical work environment.

Management support.

Team spirit.

Academic staff well share their knowledge when they

have effective management support as well as they get

good incentive systems. In addition, quality of physical

work environment and formal an informal space for the

academic staff are vital to increase knowledge sharing

activities.

Potential Technological Barriers

Knowledge sharing is an individual and organizational

issue as it is a technological challenge. Technology has

the ability to offer big access to large amounts of data

and information. as well as provide long distance

collaboration. Technology that works effectively in

some organizations may fail in others. The potential

technology barriers to knowledge sharing are:

IT Application.

IT availability.

IT for knowledge sharing

(collaboration).

Distributed Model.

Information technological literacy.


KM - 37

V. CONCLUSION

Knowledge sharing activities is vital to the success of

knowledge management practices in all organizations,

including of universities. Effective knowledge sharing

is essential for the organization to take advantage of the

knowledge that employees have generated or acquire.

Both external and internal factors are equally important

for the academic staff to increase their activities of

knowledge sharing. Based on this review, knowledge

sharing barriers can inhibit the academic staff

perfomance and should be eliminated . Higher

education institutions should have affective strategic

plans to promote knowledge sharing activities. Effective

support from top management may help academic staff

to increase publication and dissemination of knowledge.

Good awareness must be created for the academic staff

to ensure how much the benefit that can be acquired for

them and for community when they apply knowledge

sharing activities.

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KM - 38

Abstract–Prior researches have shown that

Knowledge Management (KM) processes have

significant impact on organizational performance.

Yet, whether KM processes have an impact on

business-IT alignment appears unclear. This paper

reviews prior literature on KM and KM processes

and proposes a relationship between KM processes

and business-IT alignment.

Keywords–Knoweldge Management, Knowledge

Management Procesess, Business-IT alignment

I. INTRODUCTION

In this new millennium era, the value of knowledge

management has increased significantly. The

combination of information and practice is known as

knowledge and is increasingly regarded as a key asset in

organizations. It is important for organizations to

manage knowledge as this has been cited as

contributing to organizational performance [1; 2].While

knowledge management has been found to act as a

mediator between information technology (IT) and

business relationship, knowledge driven culture

contributes to improved communication across business

units or between different multi-business firms[3].

Previous research has concentrated on aligning

knowledge strategy with business strategy or between

knowledge strategy with IT strategy and it was found to

give impacts on organizational performance [4; 5].

However, to the best of the researchers’ knowledge, it

appears that prior research has not addressed the

influence of knowledge management processes on the

alignment between business and IT. Hence, this paper is

set out to propose a relationship between KM processes

and business-IT alignment.


A. The importance of KM in organization

According to Davenport [6], “Knowledge

management is the process of capturing, distributing,

and effectively using knowledge”.Perhaps, Gartner

Group [7] provides the most frequently cited definition

of KM :

“Knowledge management is a discipline that

promotes an integrated approach to identifying,

capturing, evaluating, retrieving, and sharing all

of an enterprise’s informationasset. These assets

may include database, documents, policies,

procedure in individual workers.”

A different perspective from O’Dell [8] about

describing KM:

“a conscious strategy of getting the right

knowledge to the right people at the right time and

helping people share and put information into

action in ways that strive to improve organizational

performance”.

KM refers to the capability to manage knowledge.

Organizations must manage their knowledge assets to

be able to utilise them for the organization’s

competitive advantage. By strategically managing

organizational knowledge through KM processes, KM

practices have the tendency to be successful [9] which

will then improve organizational performance [10].

B. KM processess capabilities

Organizational competitiveness is said to be

attributable to KM processes. KM processes emphasize

on acquiring, sharing, integrating, storing and using

knowledge [11]. According to Chang and Chuang [12],

KM processes are the degree to which a firm creates,

shares, and utilizes knowledge resources across

functional boundaries.

Prior literature suggests other definitions of KM

processes: Lai and Chu [13] divided KM processes into

six phases: (i) initiation phase which refers to the

understanding of the requirement for knowledge, (ii)

generation phase that specifies the identification of the

present knowledge, (iii) modeling phase that validates

the constructed knowledge, (iv) repository phase that

maintains the explicit knowledge and makes capable for

knowledge sharing, distribution and transfer to

distribute knowledge, (v) use phase explains knowledge

development as a commercial value, and finally (vi)

retrospection phase is related to reviewing the process,

performance and impact of knowledge management and

sensing if new knowledge is constructed.

Alavi and Leidner [14] considered four KM

processes: (i) knowledge creation phase is the

combination of new knowledge resources and this

combination needs to be (ii) stored because

organizations tend to lose track of the acquired

A Literature Survey of Knowledge Management Processes and Business-IT

Alignment

Y.Yahya*1,2

, N.Mohamed2, NZ.Rahim

1

1Advanced Informatics School, UniversitiTeknologi Malaysia, Kuala Lumpur, Malaysia

2International Business School, UniversitiTeknologi Malaysia, Kuala Lumpur, Malaysia



KM - 39

knowledge and retrieve will support organization’s

memory and individuals to access knowledge, (iii)

transfer phase involves with transfer of tacit and

explicit knowledge between individuals and groups

while delivering speed access to knowledge sources and

also providing communication channels, and (iv)

application phase is the application of knowledge in

various sites. These four KM processes are essential for

effective organizational knowledge management.Gold

et al. [15] classified KM processess into four elements:

acquisition knowledge, convert the knowledge into

something useful by combining or integrating

knowledge, application and using knowledge, storing is

the process of keeping knowledge within organizations

and, lastly is protection which secures knowledge assets

from unauthorized personnel.

Venkatraman and Tanriverdi [3] identified four

interrelated organizational processes which applied

knowledge processes for managing cross-unit

knowledge collaboration. The four processes are:

creation of knowledge resources to generate cross unit

knowledge collaboration or renew the existing ones;

transfer of related knowledge resources; integration of

the transferred knowledge resources with the existing

knowledge; and leverage of the received and integrated

knowledge resources.

In sum, KM processes help organizations to

manage knowledge by creating, storing, transfering and

using of it in order to enhance organizations’

performance. In the subsequent section, we will review

business-IT alignment literature.

C. Business-IT Alignment

Business-IT alignment or termed as Strategic

Alignment has been one of the top concerns of IT

practitioners, company executives and scholars for

decades. The concept of strategic alignment has been

part of information systems agenda for many years.

However each definition of the concept varies

depending on its own perspective on how they see the

alignment should be performed. The term alignment

was used interchangeably between fit, integration,

linkage and harmony. Henderson and Venkatraman [16]

acknowledged strategic alignment as a process of

continuous adaptation and change. They agreed that

strategic alignment is the degree of fit and integration

between business strategy, IT strategy, business

infrastructure and IT infrastructure. Luftman et al. [17]

have a different perspective on strategic alignment

where in essence, business and information technology

strategies are in alignment when business objectives are

enabled, supported, and stimulated by information

technology strategies. In other words, IT is in harmony

with business strategies, goals and need. Reich and

Benbasat [18] define strategic alignment as “…the

degree to which the information technology mission,

objectives, and plans support and are supported by the

business mission, objectives, and plans…”. According

to Kearns and Sabherwal [19], achieving strategic

alignment is essential in order to improve organizational

performance.

The current concept of strategic alignment models

shows researchers’ endeavor to find a way to link

business and IT strategies in order to increase

organizational performance. Hence, it is important to

measure this alignment and to measure its effectiveness. A few empirical studies have found that business

strategy which are shared and supported by IT strategy,

influences business performance [20; 21].Even though

there are urgent needs to have strategic alignment to

increase organizational performance, only a few

organizations consider themselves in alignment [22].

According to Chan [23], poor alignment contributes to

sub-optimal organizational performance even though

the organization may invest heavily in information

systems. One factor affecting strategic alignment has

been identified as the understanding of why alignment

needs to be aligned successfully [20; 24; 25; 26].

Although there has been much attention paid to factors

affecting alignment, theory-based empirical research on

the impact of factors on strategic alignment as well as

the impact of the alignment on business performance is

still under studied [25].

D. KM and Business-IT Alignment

Luftman[17] ranked the most important enablers

and inhibitors of strategic alignment. One of the

enablers is IT people who understand the business but at

the same time one of the inhibitors is IT people who do

not understand the business. This requires for both IT

people and business executives to understand each

other’s domain in order to develop shared

understanding and to achieve their objectives and

actions successfully [25]. This supported Reich and

Benbasat findings that shared domain knowledge as one

of the determinants that influence the business-IT

alignment. According to them shared domain

knowledge is “the ability of IT and business executives,

at a deep level, to understand and be able to participate

in the other’s key processes and to respect each other’s

unique contribution and challenges”. They have pointed

out the importance of sharing knowledge of the

business area and actions taken to encourage training of

IT professional in business areas. When both IT and

business executives have common understanding, it will

improve communication. According to Tanriverdi [1],

four knowledge processes known as creation of related

knowledge, transfer of related knowledge, integration of

related knowledge and leverage of related knowledge

were identified to exploit the cross unit knowledge

synergies that requires coordination across business

units.

Based on the enablers and inhibitors defined by

Luftman, the coordination between IT units and

business units were needed to improve strategic

alignment between business and IT. The knowledge


KM - 40

processes may support knowledge integration and

knowledge sharing between the two units.

This is in line with Kearns and Sabherwal [19] who

found two kinds of behaviour related to business-IT

alignment: business managers’ participation in strategic

planning and IT managers’ participation in business

planning. Based on the empirical results, organizational

emphasis on KM influenced the two behaviours that

support business-IT strategic alignment. It was

emphasized that KM processes can be used to facilitate

knowledge integration across business and IT.

III. DISCUSSION

Previous researches have found that the alignment

between KM strategy with business strategy and KM

strategy with IT strategy influences organizational

performance. Apart from that, KM processes also play a

vital role in shaping organizational performance.

Through KM processes, organizations will have more

relevant information to provide the management with

more effective strategies for organizational benefits

[12].

In business-IT alignment, developing effective

strategies requires effective knowledge sharing and

knowledge integration. All of these can be achieved via

KM processes. Prior researches have shown that KM

processes significantly affect KM performance and

organizational performance. However, the impact of

KM processes on business-IT alignment is still vague. It

may have its own underlying arguments and meanings

which may contribute to the body of knowledge.

Therefore, it may be noteworthy to investigate the

impact of KM processes on business-IT alignment.

IV. CONCLUSION

Knowledge is important. KM processes can lead to

better knowledge integration and knowledge sharing

among business and IT units. It is assumed that these

capabilities may improve knowledge alignment between

business and IT. Therefore, this study proposes further

investigation on the relationship between knowledge

processes and business-IT alignment.

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KM - 41

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KM - 42

Abstract - The purpose of this study is to examine the

relationship between the critical success factor

(CSF) and critical barriers of the knowledge

management (KM) at Higher Education Institutions.

A greater success may come from the knowledge

management as it opens the way for the real

competition between organizations to performance,

and so it becomes significant that the knowledge

management is interpreted as a key concept in the

organizational development, being a strategic issue

for their survival in the modern society. A

qualitative research method was used in order to

examine the relationship between the CSF and

perceived benefits of the knowledge management.

Keywords - Critical success factors, Critical barriers,

Knowledge management, Higher education

institutions

The Critical Success Factors and Critical Barriers of Knowledge Management

Implementation at Higher Education Institutions

A. Aida*, M. Masrom, N. H. Nik Mahmood

Razak School of Engineering and Advanced Technology, Universiti Teknologi Malaysia, Kuala Lumpur, Malaysia (*[email protected])

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