Evaluating Knowledge-Oriented Management: An Iranian University
Alireza
Anvari¹, Rosnah Mohd. Yusuff ¹, Norzima Zulkifli¹,
Mohammad Hossein Hojjati², Yusof
Ismail³
¹ Universiti
Putra Malaysia , ² Islamic
Azad University, Shiraz , Iran , ³ Universiti Malaysia
ABSTRACT:
The rapid change in science and technology bring in widespread changes in
many different areas has challenged organizations managers. Hence to survive and compete in dynamic and
unpredictable situations, they have to revise their policies directed and their
leadership styles in the proper directions. One of these innovative instruments
is knowledge management which can play an effective role in Iranian
organizations specifically in universities. The major objective of the present
study is to identify and measure the promotion of knowledge - oriented
management in universities.
The research methodology comprised of
both; qualitative and quantitative method. A literature review of knowledge
management in the university was collected. Data obtained from 124 participants
(more than 40% of the population) has been analyzed. The instrument used was a
standardized questionnaire on knowledge management of which the internal
correlation was calculated through Cronbach’s alpha of 92%, and then analyzed using SPSS, and was
measured through t test and Pearson correlation. In this study, besides
descriptive statistics methods, depending on the type of variable, t test and
correlation coefficient were applied for investigating the correlation.
In general, the findings indicated that: There are some tokens of knowledge-
oriented management which were above the medium level (strategic vision and
leadership), the indexes for human resources and
general management were average, but especially internal process was lower than
average. The embracement of knowledge management was following an increasing
pace. Also the result showed, there was a significant
difference between two groups (lecturer and staff) perception and experience of
Knowledge – oriented management in the university. Furthermore, there are some
evidences such as software and hardware networks, resources, conducting
training, creating cultural basis, budgeting on research etc, imply the trend
of Knowledge- oriented management development.
Keywords: Knowledge management,
Knowledge-oriented, Measurement, Indicator, University
1. Introduction
In recent years, knowledge management (KM) has become a critical subject of
discussion in the business literature. Both business and academic communities
believe that by leveraging knowledge, an organization can sustain its long-term
competitive advantages (Bhatt, 2001). Nowadays, the competitive conditions and
context in organizations have developed to be more widespread and varied than
the past. Such context is changing so rapidly than for the majority of
organizations, it is far much more rapid than they can respond and keep up. In
the other words, as soon as there is a change in the mentioned conditions and
the organization attempts to react against the change and adapt itself with it
, the next change take place and the organization needs to adjust itself with
the new change so that it can maintain and survive.
There is no doubt that universities are no exceptions. Since they are the
centers for production and distribution of knowledge, they need to be potential
enough for more dynamicity and stability. Since the past, establishing
innovation and consequently, creating new knowledge have been regarded as
important achievements of academic institutions and they have mainly focused
their attempts on promoting knowledge and enriching intellectual capitals
through implementing the present resources. These resources include not only
information but also all the intellectual capitals as well as human resources
who need to be identified and used systematically through the proper management
methods. Emergence of KM following management of information is indicative of
attempts in the fields which put internal intellectual capitals and the
resources produced internally together with external resources and spread their
activities beyond educating and researching issues, touching the official
procedures of executive processes. To achieve this goal, Islamic Azad
University of Firouzabad as a centre for creation and
distribution of knowledge, just like any other organizations, calls for
implementing KM to be able to handle the potentialities and commitments of
skilled employees through identifying methods for creating, recognizing,
implementing and distributing organizational knowledge. So, at the organisational level, KM puts emphasis on the creation,
utilization and development of an organisation’s
collective intelligence (Loh et al., 2003).
Bhatt (2001) claims KM shapes the interaction pattern between technologies,
techniques, and people. However, that exclusive focus on people, technologies,
or techniques does not enable a firm to sustain its competitive advantages. It
is, rather, the interaction between technologies, techniques, and people that
allow an organization to manage its knowledge effectively. By creating a
nurturing and “learning-by-doing” kind of environment, an organization can
sustain its competitive advantages (Bhatt, 2001). So, this is a campaign by
which university can overtake its rivals in today’s complex and anarchic
contexts.
In this research, the attempt is focused on identifying level of knowledge –
oriented management (K-OM) and to find the strengths and weaknesses due to
achieve K-OM perfect, because the knowledge-based view promises to have one of
the most great depth changes in management thinking since the scientific
management revolution up to know (Grant, 2000). In fact, this study tended to
investigate the relationship between KM in the field of management and
infrastructure of Firoozabad Islamic Azad University,
its variables including the general management conditions, the leadership
style, the strategic vision, the internal processes for management, the
situation of human resources, as well as factors such as age, gender, education
level, experience, the type of the groups (faculty members and the staff).
Also, studying the hardware and software and researching facilities and other
concrete cases as a sign/evidence of KM was sought. At the same time, the study
aimed to clarify whether it is possible to provide the strategies for making
the KM more effective referring to the present findings? The research
methodology was mixed two methodologies (two phase study); the first phase was
qualitative method, and the second phase was quantitative method. By the way,
in this research we address the following questions according to literature:
Ø
What is the contribution of the
literature in the field of KM assessment in the organizations?
Ø
What are the KM evaluation
criteria?
And, qualitative study based on case study consisted of three questions:
Ø
Are there any evidences observed
for K-OM at university? And what are the strengths and weaknesses?
Ø
What are the perspective employees
toward K-OM?
Ø
Are there any significant
differences between two groups (lecturer and staff)?
2. A Review Study Of KM
In recent years, different researchers have focused on KM and its success
with various dimensions and aspects. Some authors have attempted to help the
organizational knowledge (Argyris, 1990; Sommerville and Dalziel, 1998; Goffee and Jones, 2001; Rampersad,
2002; Hall and Andriani, 2002; Hwang, 2003; Albers and Brewer, 2003; Kakabadse et al., 2003; Bose, 2004; Vlok,
2004; Goh, 2004; Abdullah et al.,
2005; Wu and Wang, 2006; Montequín et al., 2006;
Fernandez et al., 2006; Gillingham and Roberts, 2006;
Golban and Kianzade, 2005; Shen et al., 2007; Gumus, 2007; Tseng, 2008; Kayakutlu and Buyukozkan, 2008;
Chang and Wang, 2009; Chen and Lin, 2009; Wen, 2009).
Some KM studies dealt with the theoretical and fundamental (Barney, 1991,
1996; Von Krogh and Roos, 1995; Wernerfelt,
1984, 1995; Teece, 1998, 2000; Wheelwright and Clark,
1992; Argyris, 1990; Sveiby,
2001; Schultze and Leidner,
2002; Hall and Andriani, 2002; Rodrigues and Martis,
2004; Wong and Aspinwall, 2004, 2006; Papoutsakis and Vallès, 2006; Park, 2006; Gillingham
and Roberts, 2006; Lin, 2007; Thitithananon and Klaewthanong, 2007; Alrawi, 2007;
Tseng, 2008; Wu et al., 2008; McFarlane, 2008; Chen and Lin, 2009) played a significant role.
Other studies (Quinn, 1992; Drucker, 1993; Nonaka and Takeuchi, 1995; Prusak,
1997; Davenport and Prusak, 2000; Bhatt, 2001; Schultze and Leidner, 2002; Hijazi and Kelly, 2003; Wu and Wang, 2006; Papoutsakis and Vallès, 2006; Rodrigues et al., 2006; Alhawary
and Alnajjar, 2008)
have focused on relationship between KM and IT. Also, some authors consider
categories for KM (Drucker, 1990, 1991; Grant, 2000; Nonaka and Takeuchi, 1995; Sveiby,
1992, 1997; Von Krogh et al., 1998, 2000a, 2000b; Applegate et al., 1999; Bontis, 1999; Alavi and Leidner, 2001; Kakabadse et al.,
2003; McNurlin and Sprauge,
2004; Jafari et al., 2005; Khadivar
et al., 2005; Lee et al., 2005; Gillingham and
Roberts, 2006; Montequín et al., 2006; Papoutsakis and Vallès, 2006).
To find how KM could obtain competitive advantages some researchers have
studied? (Senge,
1990; Rowley, 2000; Bhatt, 2001; Wangenheim et al.,
2001; Scott, 2000; Hall and Andriani, 2002; Loh et al., 2003; Castellanos et
al., 2004; Willcoxson, 2004; Wong and Aspinwall, 2004, 2006; Golban and
Kianzade, 2005; Sarkar Arani, 2005; Choy and Suk, 2005; Akhavan et al., 2005; Hazeri and Safarzade, 2007; Montequín et
al., 2006; Shen et al., 2007; Lin, 2007; Tseng,
2008; Wu et al., 2008; Chang and Wang,
2009; Chen and Lin, 2009).
In any case, there have been various researchers discussing different
aspects which are classified in several categories: Investigating the types of
research; Research based on Balanced Scorecard; The studies assessing the
measure of effect; The studies on measuring quantity; The studies investigating
the causative relationship between KM and the company of interest with or
without considering information
technology (
Bhatt (2001) categorized KM process into: knowledge creation; knowledge
validation; knowledge presentation; knowledge distribution; and knowledge
application activities, and he believes to capitalize on knowledge, an
organization must be swift in balancing its knowledge management activities
(Bhatt, 2001). Liebowitz et al (2000) classified the
various approaches according to four major focuses: Benchmarking focus;
Performance measurement focus; IC measurement focus; The Skandia ‘Business
Navigator’; Value focuses (Liebowitz et al., 2000). Alavi and Leidner (2001) summarized
the various views of knowledge. Perspectives Knowledge consist: vis -à- vis
data and information, State of mind, Object, Process, Access to information and
capability. A variety of KM approaches and systems needs to be employed in
organizations to effectively deal with the diversity of knowledge types and
attributes (Alavi and Leidner
2001). Kakabadse et al. (2003) summarized
perspectives of KM to five categories: philosophy-based model, cognitive model,
network model, community model and quantum model.
Mostafa Jafari et al
(2005) in an exploratory study, identified thirty three measurement methods of
knowledge and intellectual capital, and classified them in four groups: direct
intellectual capital, score card, marketing cost methods, and return on assets
(Jafari et al., 2005). According to their categories
some of methods such as: find real value, value-driven intellectual, creation
value, financial method and intangible assets measurement, are included in
group of direct intellectual capital; and also balanced score card,
intellectual capital index, intangible asset, knowledge monitoring cycle,
strategic assets map and intellectual
capital grading, are included in score card groups. They mentioned that comprehensive
visualization of organizational condition is created more than others by
methods of “direct intellectual capital” and “score card”, and they are
suitable and useful for private organizations, parts of organizations internal,
general organizations, social and cultural goals. Bontis
(1999) classified intellectual capital models into four groups: marketing cost
methods, return on assets, direct intellectual capital and score card, and
intellectual capital was defined as encompassing by Bontis
(2001) : human capital; structural capital; and relational capitals. Khadivar et al (2005) classified the studied methods in
three approaches: knowledge measurement in product and process, measurement of
knowledge value internal organization, and measurement of organization
conditions based on KM process (Khadivar et al.,
2005). They grouped comparative indexes of measurement methods in three groups:
Covering three main indicators of KM (people, structure, technology);
Continuous monitoring and contingency. They mentioned the
fact that any indicators can measure all of various aspects of KM in
organizations; consequently to get the best result, integrating some indexes is
the best way. Knowledge systems are the
core requirements for organizing, controlling, and collaborating across systems
of people, structures, and processes (McFarlane, 2008).
On the other hand, Jafary (2005) divided the
metrics under twofold: qualities and quantities, and claimed
the qualitative (Anecdotes and success stories, Employee awareness of
the program, User feedback detailing their experiences) and quantitative (Time
saved, Cycle time reductions, Contributions to knowledge database, Communities
of practice, Participation in communities of practice, Usage frequency, Number
of users) metrics should attempt to capture the relative success the pilot
program is having at getting users to share and transfer knowledge (Jafari et al., 2005).
Chang and Wang (2009) classified the measurement approaches in seven main
aspects including employee traits, strategy factor, superintendent traits,
audit and assessment, organizational culture, operating procedures and
information technology. According to Wen (2009), the
tool of knowledge management assessment is arranged of five basic
elements: strategy and leadership;
culture; technology; measurement; and process. Montequin
et al (2006) believes that their research identifies analyses and compares
intellectual capital (IC) elements that are relevant for SMEs.
There is a question, how they can be linked with the IC measurement methods for
determining if a company is ready for KM? They identified a set of knowledge
success factors (KSFs) relevant for SMEs and with a direct impact on business improvement in
order to meet KM requirements. The set of KSFs cover
the three main categories: technology, process and people (Montequin
et al., 2006). Some authors defined as a logistic function having five
components that can be used to determine the knowledge circulation process:
knowledge creation, knowledge accumulation, knowledge sharing, knowledge
utilization and knowledge internalization (Lee et al., 2005).
Wu and Wang (2006) identified five variables (system quality, knowledge or
information quality, perceived knowledge management system (KMS) benefits, user
satisfaction, and system use) were used as dependent variables in evaluating
KMS success. Bose (2004) presented three popular methods used by organizations
for measuring the performance of KM strategies. The balanced scorecard,
Economic value added, Skandia Navigator. Lin (2007) identified three key dimensions
of KM: KM process (knowledge acquisition, knowledge conversion, knowledge
application and knowledge protection), KM effectiveness (individual- level and
organizational-level KM effectiveness) and socio-technical support
(organizational support and information technology diffusion) based on the
previous literature. Chen and Lin (2009) showed that the more beneficial
managers’ label was toward KM project issues, in fact there is strong
correlation between attention to discuss and issues on organizational meetings.
As a result, managers’ various scope definition of KM had affected their
evaluation of the issues (Chen and Lin, 2009).
Adli (2006) proposed four key indicators: context,
input, process and output indicators. Sveiby (2001) recognized nine knowleledge transfers/conversions for
creating value in an organization: Transfers/conversions of knowledge: between
individuals; from individuals to external structure; from external structure to
individuals; from individual competence into internal structure; from internal
structure to individual competence; within the external structure; from
external to internal structure; from internal to external structure and within
internal structure. Daniël Vlok
(2004) considered fourteen dimensions in the three areas, background/structural
factors, knowledge production and knowledge integration. Recently, Wen (2009), considered five criteria of KM: Staff,
Information, Data, Knowledge, and Wisdom.
Whilst Loh
et al (2003) states there are some gaps between current KM and an expected KM,
there are a lot of KM applications but very few KM systems too. They listed the main criticisms of current
KM. In the end, the validity of knowledge and to build on its strengths,
knowledge mobilization is supplementary of KM. So based on their results, the
aim of Knowledge sharing was at helping
mobilize critical enquiry, thought leadership and research excellence to
influence and hopefully add value to the efforts of the managers who will build
the KM equivalents of companies (Loh et al., 2003).
However, the foremost challenge of the next few years will be to bring together
these theoretical and practical developments in a fuller specification of the
implications of the knowledge-based view for business strategies,
organizational structures, and management systems and inter organizational
relationships (Grant, 2000). As a result of the literature review of KM
performance evaluation, we can classify some into several perspectives (see
table 1).
3. Knowledge Management
>In Universities
Many authors have studied on knowledge and different meanings of knowledge (Argyris, 1990; Goffee and Jones,
2001; Ramperdsad, 2002; Hall and Andriani,
2002; Kakabadse et al., 2003; Fernandez et al., 2006;
Gillingham and Roberts, 2006; Golban
and Kianzade, 2005; Adli,
2006; Tseng, 2008; Wu et al., 2008; Cranfield and
Taylor, 2008; Chen and Lin, 2009; Chang and Wang, 2009). But, it seems the most
important challenges are creation and utilization of knowledge. However, the
greater challenge lies with the other two elements of knowledge management: in
the creation of a knowledge environment, and the recognition of knowledge as
intellectual capital (Rowley, 2000). Because, in today’s
world, people face with the difficulties which are more internationally
oriented rather than being nationally driven to be solved willingly. In
the other words, these difficulties are global and bring about with themselves
special international effects. As a result, international constructive will,
recognition, and attitudes will be necessary to decrease or eliminate them and
this will not be achieved except through the mutual recognition and
understanding of cultures, civilizations, economical political and social
conditions of nations. The required cooperation for dealing with difficulties
such as international disputes, third world countries poverty, environmental
hazards, population explosion, calls for constructive awareness and attitude;
and this important issue will only be gained through the mutual recognition and
understanding of nations from each other and about the roles they will play in solving such problems (Sarkar Arani, 2005).
In recent years, KM has become a critical subject of discussion in the
business literature. Hazeri and Sarrafzadeh
(2007) believe universities are the main centers for producing and distributing
knowledge. Both business and academic communities believe that by leveraging
knowledge, an organization can sustain its long-term competitive advantages
(Bhatt, 2001).
So, in such situations, universities will play their new roles more
effectively through spreading knowledge among cultures, cultural values, the
researching skills for scientific thinking,
teamwork, and expanding the process of learning and teaching to the
overseas universities (Sarkar Arani,
2005).
Table 1
KM Categories Based On Specific Aspects
|
Perspective |
Classifications/categories |
No |
Author(s) |
|
Method-based |
·
Marketing cost methods, return on
assets, direct intellectual capital, score card |
4 |
Bontis, 1999 |
|
Major-focus-based |
·
Benchmarking focus, performance
measurement focus, Skandia Business Navigator, value focus |
4 |
Liebowitz et
al., 2000 |
|
Knowledge – steps |
·
Knowledge creation, knowledge
validation, knowledge presentation, knowledge distribution, and knowledge
application activities, knowledge capitalization, knowledge balancing |
6 |
Bhatt, 2001 |
|
Indicator-based |
·
General management, leadership style,
strategic vision, internal process, human resources |
5 |
Rampersad, 2002 |
|
Method-based |
·
The balanced score card, economic
value-added, Skandia Business
Navigator |
3 |
Bose, 2004 |
|
Area-based |
·
Background/structural factors,
knowledge production, knowledge integration |
3 |
Vlok, 2004 |
|
Area-based |
·
Knowledge measurement in products and
processes, measurement of knowledge value in internal organization,
measurement of organizational conditions based on KM processes |
3 |
Khadivar et al., 2005 |
|
Method-based |
·
Direct intellectual capital, score
card, marketing cost methods, return on assets |
4 |
Jafari et al., 2005 |
|
Knowledge –
applied |
·
Knowledge creation, knowledge
accumulation, knowledge sharing, knowledge utilization, knowledge
internalization |
4 |
Lee et al., 2005 |
|
KM – aspects |
·
Psychological, culture, process,
functionality, architecture |
5 |
Abdullah et al., 2005 |
|
Indicator-based |
Context indicator, input indicator,
process indicator, output indicator |
5 |
Adli, 2006 |
|
KM – aspects |
·
Technology, process, people |
3 |
Montequín et al., 2006 |
|
Model-based |
·
Cognitive model, network model,
community model, quantum model,
philosophy-based model, general
intellectual capital (IC) measurement model |
6 |
Kakabadse et al., 2003; & Montequín et al.,
2006 |
|
Indicator-based |
·
Knowledge or information quality,
perceived knowledge management system (KMS) benefits, user satisfaction, and
system use were used as dependent variables in evaluating KMS success |
4 |
Wu and Wang, 2006 |
|
Indicator-based |
·
KM process (knowledge acquisition,
knowledge conversion, knowledge application and knowledge protection), KM
effectiveness (individual-level and organizational-level KM effectiveness)
and socio-technical support (organizational support and information
technology diffusion) based on the previous literature |
3 |
Lin, 2007 |
|
KM – aspects |
·
People, structures
and processes |
3 |
McFarlane, 2008 |
|
Analysis-based |
·
Qualitative analysis, quantitative
analysis, non-financial indicator analysis, financial indicator analysis,
internal performance analysis, external performance analysis,
project-orientated analysis, organization-orientated analysis |
8 |
Chen and Lin, 2009 |
|
Different
aspects |
·
Employee
traits, strategy factors, superintendent traits, audit and assessment,
organizational culture, operating procedures, information technology |
6 |
Chang and Wang, 2009 |
The four pillars of knowledge and education suggested by UNESCO report
(1996): Everyone must learn to know; a future citizen must learn to do; people
must learn to live together; people must learn to be (The quality of being is
based on man’s ability to develop himself as a holistic personality and as a
responsible individual, with lifelong learning constituting part of his human
existence, without continuous compulsions or threats. According to Castellanos et al. (2004) in universities, an important
part of intellectual capital is the research development-transfer capital.
Since long ago, establishing innovation and consequently, creating new
knowledge has been one of the most remarkable achievements of academic
institutes and to achieve such goal , the main attempts of academic societies
have been focused on improving knowledge and enriching intellectual capitals
through implementing the existing resources. These resources include not only
the information resources but also intellectual and human resources which need
to be identified through employing proper methods of management and be used
systematically.
The university community and its major stakeholders stand to gain through
effective knowledge management and the further development of its knowledge sharing
culture enabled by top management support and allocation of sufficient
resources, suitable organisational structures (e.g.
the appointment of a chief knowledge officer as head of a KM unit). It is as a
reward system which puts a premium on knowledge sharing and innovation rather
than knowledge hoarding, top notch KM software solutions and effective KM
processes (Loh et al., 2003). Moreover, Wangenheim et al. (2001) in order to effectively and
efficiently support learning in university software R&D organizations, the
processes necessary to continuously create and share knowledge across the
organization have to be supported systematically. This is the goal of KM: to
deliver the right information or knowledge at the right time, at the right
place, in the right format, satisfying the quality requirements at the lowest
possible cost. In order to operationalize KM in
software R&D organizations in university environments, relevant know-how
has to be continuously build- up by gathering new explicit and tacit knowledge
during the planning and execution of R&D activities (Wangenheim
et al., 2001).
According to Loh et al. (2003) the missions and functions of universities are ‘pragmatized’ because of emerging new players and competing
markets for knowledge production, the availability of higher education to a
wider range of social classes and age groups, as well as the assimilation of
information technology into the university environment. The dynamics and
conduct of university research, in particular, has correspondingly become more
sensitive to industry collaboration opportunities, commercial exploitation, and
is increasingly over disciplinary. …They argued that knowledge management
concepts and tools can indeed benefit and have the potential to advance the
cause of research in the university. Based on Rowley’s (2000) typology of KM
objectives in universities, it was found that KM-led activities and tools in
the areas of knowledge repositories and knowledge access have been sufficiently
addressed to advance research in Singapore Management University (SMU). In
tandem with the rapid expansion of SMU, more emphasis will be put on the
cultivation of a knowledge-sharing environment and knowledge valuation (Loh et al., 2003).
With regard to the necessities explained, every attempt which paves the way
for understanding, recognition, discourse and interactions among the nations
should be praised. In this case, if the path is started by cultural,
scientific, educational and researching issues which are regarded as the prerequisites
of deep mutual recognition and understanding of cultures, economical and
political cooperation and interactions as well as bilateral and multilateral
international cooperation.
In these conditions, educational institutes including universities and higher
educational institutes not only should they provide the necessary opportunities
for cultivating individual capabilities and life skills and native cultures but
also they should take a combined approach to human beings and their competence
in all the fields and try to provide the opportunities for them. This is
important because of both economical and political reasons and cultural and
social reasons and the role of universities should be considered regarding
these two perspectives (Scott, 2000).
KM at universities can be assessed from different aspects such as: learning
organizations, approach oriented attitude toward KM, or duty- procedures
approach and approach of infrastructures or in the other words, hard wares and
soft wares of KM such as libraries, facilities for information technology, and
indexes for human resources, line and staff and researches. In a research, Hazeri
and Sarrafzade (2007), consider the relationship
between KM and the role of libraries: Librarians have been able to make big steps
ahead through implementing skills and policies for KM. Through information banks of human knowledge
resources, they have managed to increase the level of people’s knowledge about
“who knows what” and provide valuable guides for the ones seeking knowledge by
referring to knowledge , skills, studying - researching potentialities and
interests in these banks (Hazeri and Sarrafzadeh,2007).
On the other hand, from the point of view of the learning organization, the
concept of KM will be much more spread and introduces a reciprocal totality of
human-technology. The learning organization expresses an organized form through
capacity for learning and learning consequences which are behavioral change and
learning. Willcoxson (2004) has discussed the
approach of learning organizations to improve the quality of universities (Golban and Kianzade, 2005). The
Japanese had realized the importance of delays in the process of production,
since they had perceived the process of receiving the order, tabling the
production, preparing the ingredients, production and distribution as a
comprehensive system. These disorders in distribution of products, the wastage,
and inefficiency is echoed in the whole system (Senge, 1990). Creative learning calls for understanding the
systems which are controlling the events. When we fail to recognize the
systematic source of problem, we are left by ourselves to follow the evidences
instead of eliminating the major causes and as a result, the best way to react
is compatible learning. In fact, KM and IT in organizations have been
introduced following the issues in production organizations discussed by Senge (1990) to replace the compatible learning with
creative learning. To Senge (1990), the major reason
for transformation is demolition of students by the traditional system.
Therefore, we need establish KM and organize it which are
still in the beginning and this research will be a step in this unknown field
for conceptual understanding and preparing the appropriate context for creation
of software concepts.
Due to the appearance of new knowledge producers in the education sector,
more and more universities are looking into the possibility of applying
corporate knowledge management systems (Loh et al.,
2003). In this case, there are some factors which effective on success KM in
university: Leadership, The nature of academic staff, Evidence of the benefits,
the taxonomy for the application of KM within the university, management
structure, history of the university (Cranfield and
Taylor, 2008). Hijazi and Kelly (2003) claim KM can
help to solving problem between industry and the university, such as: align IT
with social networks and dealings; Encourage and support the use of KM; Allow
knowledge transfer across different tasks; Apply knowledge to workers’
management and Practice tacit knowledge within your surroundings. Meanwhile,
Abdullah et al. (2005) proposed a framework of Knowledge management system:
Psychological: motivation, awareness, reward, strategy; Culture: truth,
believes, value, experience; Process: acquisition, stone, disseminate, use;
Functionality: agent, email, video conferencing, chats; Architecture:
application, technology, infrastructure, repositories.
4. Assessing KM At Universities
Regarding the KM in universities, Sar
karani (2005) has focused on the challenges of
In this study, the indexes for the success of the KM system have been
provided by a questionnaire. In this case, a combination of indexes introduced
in the questionnaire as suggested by Rampersad (2001)
and the questions cited in “journal of Knowledge of Management-Iran” (2007)
have been applied. The second index is generalizing the model of success for
the system of KM. The research suggests that the models accepted based on
theories or other supported models should be generalized. Since, the theories
and models offered in the academic theories have gained the necessary credit by
the researchers of society. And the third index for the model of success for
the KMS in the studied sample is its applicability in the formation and the
approach of KM toward that. In fact, evaluation in this study takes place
through two approaches: determining the characteristics of process-duty
approach or infrastructures- foundations.
4.1. The Specific Research
Questions
The research questions of the study were as follows:
Ø
Which level is the KM at this
university? In the other words, what is the status of the main parameters of KM
at Islamic Azad University including general management, the leadership style,
strategic vision, internal processes of management, and human resources?
Ø
What kind of relationship is there
between demographic factors as age, gender, education, experience and groups of
the study (faculty members and staff) and KM?
Ø
How can KM be practical at
university and how should the strategies be provided for enhancing
effectiveness of KM in Firoozabad Islamic Azad
University?
One hundred and twenty four faculty members and university staff (more than
40% of the whole population) were selected through stratified random sampling
and investigated through standardized instrument for management of knowledge
designed by the researcher. The collected data was analyzed using SPSS and to
test the hypotheses, t-test and Pearson correlation tests were applied.
5. The Methodology Of The Study
The present study is of a survey type and involved all the faculty members
and staff of Firoozabad Islamic Azad University. The population of the study was selected
through stratified sampling. The data obtained from 124 participants (more than
40% of the population) as the sample have been analyzed. In this study, besides
descriptive statistics methods such as percentage, mean and …, Depending on the
type of variable, t test and correlation coefficient were applied for
investigating the correlation.
5.1. Participants
Questionnaires were sent to employees with significant responsibility for
measuring the level of knowledge – oriented management. 140 faculty members and university staff were
selected through stratified random sampling and investigated through
standardized instrument for management of knowledge designed by the
researchers. The collected data was analyzed using SPSS. The t-test and Pearson
correlation tests were also applied.
From 140 questionnaires distributed, 131 employees completed back their
questionnaires, resulting in 124 (58 staff & 66 lecturers) usable responses
(see Table 2).
Table 2: Frequency Of Participants.
5.2. Sampling Design
Five sets of measures were adopted and used to measure each of the five constructs,
namely, general management, leadership style, strategic vision, internal
process and human resources. These measures were made by integrating Rampersad test (2001), journal of organizational knowledge
test (2007) and were subjected to a formal pre-test by some managers and
experts. Some minor modifications were carried out to make the meaning of some
items clearer. A variety of KM approaches and systems needs to be employed in
organizations to effectively deal with the diversity of knowledge types and
attributes (Alavi and Leidner,
2001). Therefore, the questionnaire not to following of a
especial idea. According to Alrawi (2007) there are
many aspects of KM, and how to apply in organizations, it depends to the
structure of organization. However, at present, the structure, processes, and
procedures of KM have not been defined as a tangible standard, and it is
difficult to find comprehensive and clear comment criteria (Wen , 2009).
An internal consistency analysis was performed separately for each variable
in the theorized model by calculating the Cronbach’s alpha, i.e. the reliability alphas. The results in
Table 1 show that the Cronbach-a
s for all the variables in the model were above the critical value of 0.7 (Nunnally, 1978). Hence, the authors concluded that all the
items had been appropriately assigned to each variable. The instrument
developed also had content validity, since the selection of measurement items
was based on an exhaustive review of the literature and a detailed evaluation
by academics and practitioners. Content validity depends on how well the
researchers created the measurement items to cover the content domain of the
variable being measured (Nunnally, 1978). The study
used a five-point rating scale, i.e. from 1 (strongly disagree) to 5 (strongly
agree). The reliability alphas (a) of different variables and sample items for
each variable are discussed as follows.
5.3. Findings Of The Study
Correlation and validity of the instrument’s statements through Cronbach method, the correlation for all the subscales of
KM were high and significant in 0.01, but the correlation for the indicators of
leadership style in the first rank (r=0.886), strategic vision in the second
rank(r=0.732), internal process in the third rank (r= 0.715), general
management in the forth rank (r= 0.682) and human resources (r= 0.679) is last
rank (see table 2).
Cronbach - as of general management was found .85,
Leadership had a very good (0.87).
Among the indicators, strategic vision is least (0.75), and others are more
than it (internal process=.83 & human resources=0.85). Fortunately, the
reliability alphas of Total KM (0.92) were very strongly (See table 3), and the
alpha value of 92% indicates that the research instrument enjoys a rather high
validity. Also, minimum of the alpha value for sub scales is equal to 75% and
has a rather high value.
Table 3: Statistical Information
|
Indicator |
No of Items |
Cronbach's Alpha |
Mean |
Correlations |
Sig |
|
General Management |
13 |
.85 |
39.64 |
.682** |
.000 |
|
Leadership Style |
7 |
.87 |
22.63 |
.886** |
.000 |
|
Strategic Vision |
5 |
.75 |
16 |
.732** |
.000 |
|
Internal Process |
7 |
.83 |
20.44 |
.715** |
.000 |
|
Human Resources |
7 |
.85 |
21.35 |
.679** |
.000 |
|
KM- Total |
39 |
.92 |
120 |
|
|
5.3.1. Description Of Data
5.3.1.1. Normal Distribution
Table 3 shows Mean, SD, Skewness and Kurtosis of 5
indicators: general management, leadership style, strategic vision, internal
process, human resources and total of KM. Normality distribution (fig 1) of
variables assessed based on Kurtosis and Skewness,
result exploratory analysis showed an excellent normality KM scale.
Figure 1: Normal Distribution
5.3.1.2. Means Of Different Variables
The mean values of the different variables are discussed as following (Table
4).
The mean values on a five-point scale (1= strongly disagree; 5 = strongly
agree) of the five indicators under KM were 39.64, 22.63, 16.02, 20.44 and
21.35 for general management, leadership style, strategic vision, internal
process and human resources. Also the mean of KM (sum) was 120, which indicated
that the respondents believed that the level of knowledge management according
to mentioned criteria’s was average and internal process was a little less than
average. Actually the employees did not indicate a positive approach on:
Ø
Learning environment characterized
by positive thinking, self esteem, mutual trust, willingness to intervene
preventively, taking responsibility for performances, openness, enjoyment, and
passion.
Ø
Knowledge growth is promoted
through the organizational culture.
Ø
Problems are integral and are
tackled methodically by a systems approach.
Ø
The most important they did not
believe that their knowledge share spontaneously with each other.
It seems internal process is more challengeable and tangible than the
others.
Table 4: Descriptive Statistics
|
Indicators |
NO |
No of Items |
Mean |
SD |
Skewness |
Kurtosis |
|
General
Management |
124 |
13 |
39.6371 |
7.89806 |
-.018 |
-.093 |
|
Leadership
Style |
124 |
7 |
22.6290 |
5.80646 |
-.851 |
.032 |
|
Strategic
Vision |
124 |
5 |
16.0161 |
3.62687 |
-.535 |
-.398 |
|
Internal
Process |
124 |
7 |
20.4435 |
4.26424 |
-.635 |
-.079 |
|
Human
Resources |
124 |
7 |
21.3548 |
5.21598 |
-.755 |
-.218 |
|
KM-
Total |
124 |
39 |
120.0806 |
19.77623 |
-.797 |
.149 |
|
|
|
|
|
|
|
|
5.3.1.3. The Indicators Of Knowledge- Oriented Management
Table 5: An Analytical Survey Of Indicators
|
indicator |
Total mean |
Maximum |
Minimum |
||
|
issues |
Score |
issues |
Score |
||
|
General management |
3.05 |
(Making
mistakes is allowed; failures are tolerated and not penalized) |
[3.57] |
(The organization
has a network of knowledge workers) & (there is an active program for
developing ideas) |
[2.7, 2.8] |
|
Leadership |
3.23 |
(managers support
to dealing and transaction of knowledge) |
[3.56] |
(solving the
organization problems through teamwork) |
[2.71] |
|
Strategic vision |
3.07 |
(Executive
indexes for the purpose of learning and knowledge with the developing vision
at university) |
[3.46] |
(executive
indicators) |
[3.04] |
|
Internal process |
2.91 |
-------- |
------ |
(Transferring knowledge regularly, knowledge
measurement, & using friendly of information system and communication)
were lowest. |
[----] |
|
Human resources |
3.05 |
(proactive competence development policy) |
[3.21] |
(Managers and
employees are not judged enough, by what they do) &(The knowledge of
departing employees is not passed pervasive on to successors) |
[2.8] |
5.3.1.3.1. General
Management
From among 13 statements which were indicative of KM, the total mean was
3.05 and highest mean belonged to the
first statement (Making mistakes is allowed; failures are tolerated and not
penalized) being 3.57 and the lowest mean were 2.7, 2.8 for statements numbers
8 (The organization has a network of knowledge workers) and 11 (there is an
active program for developing ideas) In
the other words, the staff’s mistakes in the failure process were approached
without penalizing ,however the organization has not a suitable network of
knowledge workers, further more they believe there is not an active program for
developing idea.
5.3.1.3.2. Leadership Style
According to Lakshman (2007) and Bell De Tienne et al. (2004) leadership has been identified as a
key variable in the relationship between KM and organizational effectiveness by
researchers. Similarly, McFarlane (2008) contends that, “effective leadership
is a salient requirement in organizations where the knowledge worker is the key
to developing as well as unlocking the sources and potential for sustainable
competitive advantage in the knowledge economy”. The total mean for the 7
statements measuring leadership style was equal to 3.23 which is more than average score. Maximum is 3.56 belong to 17
(managers support to dealing and transaction of knowledge), Except for the
statements number 15 (solving the organization problems through teamwork) which
had a mean of 2.71 and indicated that solving organization problems through
teamwork was low, the mean for rest of the statements showed that:- the high
ranking principal of university, to a high level, makes sure to increase the
learning potentiality of learners and establishing learning organizations,- it
,to a great extent, is aware that knowledge plays a significant role in the
success of the organization,- the individual and team cooperation of managers
has been high in exchange of knowledge and learning,-they have been very active
in control and acquiring knowledge of the organization,- they have facilitated
learning to a great deal,- the management of university has been active in
identifying the processes and cultivating the learning process and
communication knowledge in high levels, and the participants highly considered
the management of knowledge to be a strategic matter.
5.3.1.3.3. Strategic Vision
KM for higher education in a global economy requires strategic alliances on
an international arena, and the creation of global knowledge repositories,
which are used to the competitive advantage of the partner in the alliance
(Rowley, 2000). In this case, there was 5statements measuring strategic vision.
The total average of them is 3.2 and indicated that the level of strategic
vision of sample was rather high especially from the employees point of view .In the other words, there has
been group learning for developing the core capabilities of the organization
and a medium level credit for university and knowledge in an above medium level
(3.07) . Executive indexes for the purpose of learning and knowledge with the
developing vision at university has been above the medium level (3.46) and
executive indicators (3.04) have had the value lower level for the
organization. All in all, participants showed a rather high strategic vision.
5.3.1.3.4. Internal
Processes
Process is one the triangle corner of Knowledge (McFarlane, 2008).There were
7 statements measuring the internal process variable of one of the parameters
of management of knowledge. The total mean of the internal processes are very
low and equal to 2.91 which is lower than the average. With regard to the score
average of each of the statements, it can be mentioned that : The staff and
lecturers and university have been acting rather poorly in case of regular and
wide exchange of knowledge. “Encouraging development in knowledge from
organization”, “systematic approach to the university problems” and
“responsibility, trust, self assessment and satisfaction” have been in medium level; and also, “transferring knowledge regularly”,
“knowledge measurement”, and “using friendly of information system and
communication” have been lower than
average. Documentation of developed and acquired knowledge has been very weak
and rarely accessible.
5.3.1.3.5. Human Resources
There were 7 statements measuring the concept of human resources of one of
the parameters of management of knowledge. The total mean of human resources
has been 3.05. but for the statements number 36 (proactive
competence development policy) which had a rather high mean equal to 3.21 and
indicated the strength in the quality of the internal and external training,
courses, working conferences, symposia and seminars., the mean for the
statements 34 and 39 were very low (2.8). In fact, the respondents believe
“Managers and employees are not judged enough, by what they do” and “The
knowledge of departing employees is not passed pervasive on to successors”.
5.4. Data Analysis
The main objective of this research was identifying and investigating the pattern
for establishing a knowledge oriented management at university. In the other
words, this research sought the answer to this question that are there any
signs observed at university for knowledge based management and how can this
new and efficient pattern can be implemented or strengthened at university? The
minor objectives of the study included studying the demographic features as
gender, age, education, and the groups of the study (faculty members and staff)
as well as studying the parameters of knowledge based management such as the
general style of management at university, the leadership style, the strategic
vision, the internal processes of management, and investigating the status of
human resources at university. According to table 4, the mean of 2 groups
(staff and lecturer) in general management is approximately the same. But for
others are indifferences. It means there are significant differences between
approach of staff and lecturer aspect of leadership, strategic, process and
resources. In addition, the ranges of SD in general management and also in
other measures show differences between two groups. It seems the approach of
lecturer were concentrated. So, it was assessment with more positive approach
by the lecturers, because they have more information and deeper/wider
vision.
Table 4: Group Statics
Items Position N Mean SD General management Staff 58 39.3448 10.05520 Lecturer 66 39.8939 5.40692 Leadership style Staff 58 20.1897 7.10438 Lecturer 66 24.7727 3.09240 Strategic vision Staff 58 15.2241 4.15930 Lecturer 66 16.7121 2.94443 Internal process Staff 58 18.6034 4.95219 Lecturer 66 22.0606 2.68832 Human resources Staff 58 18.1379 5.60216 Lecturer 66 24.1818 2.57150 Total of KM Staff 58 111.5000 24.73243 Lecturer 66 127.6212 8.95762
5.4.1. T-Test
In order to identify mean differences of KM staff and lecturer utilized a
series of T-Test; results revealed
that there is not a significant
differences in general management (t=-.371, p =.711), between staff (M=39.34,
SD=10) and lecturer (M=39.9, SD=5.4). Overhand, there is a significant
difference in:
leadership style (t= .4.549, p <.05), between staff (M=20.19, SD=7.1) and
lecturer (M=24.77, SD=3.1) strategic
vision (t= -2.27, p <.05), between staff (M=15.22, SD=4.16) and lecturer
(M=16.71, SD=2.94) internal process (t= -4.738, p <.05), between staff
(M=18.6, SD=4.95) and lecturer (M=22.06, SD=2.69) human resources (t= -4.701, p
<.05), between staff (M=18.14, SD=5.6) and lecturer (M=24.18, SD=2.6) and
for total of KM (t= -4.701, p <.05), between staff (M=111.5, SD=24.73) and
lecturer (M=128.62, SD=8.96).
It is obvious that the statements of “general management” were
understandable; it means most of the employees (staff & lecturers) are
satisfied enough. Since the others
indicators (leadership style, strategic vision, internal process & human
resources) needed to a wider vision and deeper sights. Because following
promotion of facilities by university to achieve KM. the lecturers seemed to be
more satisfied with the present situation.
Anova- one way, The anova was conduct for general management (F= .464, P= .708)
and strategic vision (F= 1.923, P= .129) there was no significant differences
between staff and lecturer. But, for leadership style (F=7.440, P< 0. 05),
internal process (F=8.156, P< 0. 05), Human resources (F=21.933, P< 0.
05) and total of KM (F=8.081, P< 0. 05), there is a significant differences
between two groups.
5.4.2. Kruskal-Wallis Test
|
Table
5. Test Statisticsa,b |
||||||
|
|
General
management |
Leadership
style |
Strategic
vision |
Internal
process |
Human
resources |
Total KM |
|
Chi-Square |
1.386 |
11.904 |
3.788 |
16.350 |
37.454 |
13.569 |
|
df |
3 |
3 |
3 |
3 |
3 |
3 |
|
Asymp. Sig. |
.709 |
.008 |
.285 |
.001 |
.000 |
.004 |
Anova result shows that. Homogenize of variance
has been violated, then we requested kruscal-wall s.
Results also, revealed that there is a relationship between leadership style
and education [(Ƙ=11.90, P=.008 / (Ƙ(df=3) = 11.90, P< .01)], internal process and education
[(Ƙ(df=3) = 16.350, P< .01)], human resources and education
[(Ƙ(df=3) = 37.454, P< .01)], and also between education
total of KM [(Ƙ(df=3) = 13.569,
P< .01)]. There were no significant differences between education and some
items such as: general management and strategic vision.
Spearman’s rho test was used in order to identify correlation between age
and KM. The result revealed that there is a no significant / weak negative
relationship between age and KM.
A series of one way Anova was used to determine
relationship between experience and KM.
Only the Anova table results (F (2, 121) =
3.32, P< .05) shows that mean of human resources is significantly different
within levels of relationship variable. The mean values table shows that the
more experience, the more the support. Also, the model from the Anova table showed that about 20% of variance in dependent
variables KM is explained by seven
independent variables, that position was a significant predictor , in this
model (Beta= .451, P< .05) in the first stage of analysis to request
multiple regression analysis result, of multiple regression emerged a
significant model (F (6,117) = 4.74, P=< .01).
6. Discussion Of The Findings
According to Wu et al. (2008) how to evaluate knowledge-based organizations
has become one of the most important issues in knowledge management, and KM is
an important strategy for improving organization competitiveness and
performance (Wong and Aspinwall, 2004, 2006). So, the
literature showed most of the studies, researches and theories are for
determining of criteria/indicators and method of measurement but hardly any
effort has been done to measure O-KM based on a series of criteria.
As a result, some of criteria were assessed strongly: Discussing mistakes
and errors instead of penalizing, commitment to learning, knowledge important
to success, focuses on developing knowledge, the ability of knowledge manager
on understanding and processing, Knowledge management as a strategic theme,
clearly objectives of learning. And some of criteria were assessedt
weakly: quality network of knowledge
workers, simply organisational structure , to be
active programme for developing ideas,
existing an atmosphere of fear and distrust, having being team for identify and
solving problem, doing exchange knowledge with each other, using communication
and information systems broadly spread, Documenting obtained knowledge made
available to everyone, Managers and employees are judged, share their knowledge
with colleagues are rewarded extra and having more promotion opportunities.
With considering to positive and negative points, it can be showed like to
“Robert Blake” and “Jane S. Mouton” (1965) model. It seems the
positive points indicates to be suitable behavioral and oriented- human. While,
the most of negative points indicates that there is problem in organizational
structure.
When managers have more wholly recognition of KM, they have better
understanding toward the issues and realize the importance. Meanwhile, they
also could understand better about the benefit the KM project can bring to the
companies and feel the immediacy to take the innovation (Chen and Lin, 2009).
According to Kidwell et al. (2000) KM should not be looked upon as an extreme
change, its better that the concern should be to focus on implementation of KM
seriously. Under above resulting (see figure 2) one of main problem of the
university is lack/weak procedure and organizational suitable structure. The
result of a researcher (Wen, 2009) showed
“procedures; persons, supporting organizational structure and information
technology’ are four key successes of KM.
In addition, in a ranking by Wen (2009),
the priority of criteria was identified: Information, Staff, Wisdom, Knowledge
and Data. Meanwhile in our research the
minimum score was given to internal process (there were information, knowledge,
and transaction, changeover, utilization, etc)
On top of that, to obtain the knowledge and turnover to others, bring
synergic power by human resources, Rodriguez et al. (2006) claimed the
dimensions of “People Competencies and Environment & Partnerships” and
“Externalization and Combination were high practiced. Moreover the study of Alhawary and Alnajjar (2008) showed that the information systems
technology had a significant impact on knowledge creation and conversion.
The result of Alhawary and Alnajjar
(2008) indicated that there
were no significant differences in the perception of academic staff at the Jordanian
universities for the use of information systems technology regarding the
purpose of knowledge creation and conversion.
But, the result of our research showed “there was a significant
difference in the perception of two groups (staff & lecturer). Furthermore,
the result of Jamshidi and Nemati
(2008) showed there was a significant difference between knowledge share
process and social capital experience.
Also, they showed that there is a significant difference between groups’
aspects of knowledge share and social capital concept. (Jamshidi and Nemati, 2008).It seems some of the problem were related to
history of the university (22 years) because, there is a correlation between
the history of the institution and its ability to respond to the challenges of
the 21st century Knowledge Economy ( Cranfield and
Taylor ,2008).
7. Conclusion
With regard to the findings, in sum it can be mentioned that there are
observable concrete indexes and signs and evidences of K-OM in the fields of research,
official and civil, scientific, educational, digital facilities, at university
and they are increasing in a not so rapid pace. Also from the point of view of
the lecturers and staff of the university under study, there have been advances
in the parameters of K-OM especially in leadership style and strategic vision
in the University in medium and above medium level. Indexes of internal process
of K-OM have not been very successful in the research environment and have been
evaluated to be weak. This calls for the principals of the University and other
similar universities to take actions. There was no significant relationship
found between KM and some variables such as age, gender, education. But there was a significant relationship
between KM with groups and experience of the study. In the end, there are some
strategies provided to increase the effectiveness of KM in the University.
As a result, to consider the combination of this research qualitative and
quantitative, it seems total of O-KM was above average and development trend of
O-KM was suitable (22years). But, it is proposed that organizational structure
and operational process should be improved or be done re-engineered.
Furthermore, the process of O-KM, knowledge creation, utilization, transformation,
up to date, as a plan is considered.
Research problems in research environment, generalizability
of the obtained findings to other similar environments, weakness of research
and experimental effects related to K-OM, can be regarded as the limitations of
this study. To faster establish management of knowledge in research environment
and with reference to the findings, there were some theoretical suggestions
provided for the university principals and researchers as well as some
practical strategies to the managers of organizations and executive managers.
8. References
Abdullah, R., Selamat, M.H., Sahibudin,
S. and Alias, R.A. (2005), “A Framework For Knowledge Management System
Implementation In Collaborative Environment For Higher Learning Institution”, Journal of Knowledge Management
Practice, Vol. 6, available at http://www.tlainc.com/articl83.htm (accessed 1
December 2009).
Adli, F. (2006), Knowledge Management, “Frashenakhti Andishe” press,
Akhavan,
P., Jafari, M., and Fathian,
M. (2005), “Exploring Failure-Factors of Implementing
Knowledge Management Systems in Organizations”, Journal of Knowledge Management Practice, Vol.
6, available at http://www.tlainc.com/articl85.htm (accessed 1 December 2009).
Alavi, M. and Leidner,
D.E. (2001), “Review: Knowledge Management and Knowledge Management Systems:
Conceptual Foundations and Research Issues”, MIS Quarterly, Vol. 25, No. 1,
pp.107–36.
Albers, G.A. and Brewer, S.
(2003), “Knowledge Management and the Innovation Process: The Eco-Innovation
Model”, Journal of Knowledge Management Practice, Vol. 4, available at
http://www.tlainc.com/jkmpv4.htm (accessed 1 December 2009).
Alhawary, F.A. and Alnajjar, F.J. (2008), “Impact Assessment of I/S
Technology Utilization On Knowledge Creation And Conversion:
An Empirical Study In Jordanian Universities”, Journal of Knowledge Management Practice, Vol.
9, No. 1, available at http://www.tlainc.com/articl151.htm (accessed 1 December
2009).
Alrawi, K. (2007), “Knowledge Management and the
Organization's Perception: A Review”, Journal of Knowledge Management Practice, Vol. 8, No. 1, available at
http://www.tlainc.com/articl131.htm (accessed 1 December 2009).
Applegate, L.M., McFarlan, F.W. and McKenney, J.L. (1999), Corporate Information Systems
Management: Text and Cases, 5th edition, Irwin/McGraw-Hill,
Argyris, C. (1990), Overcoming Organizational
Defenses: Facilitating Organizational Learning, Prentice-Hall,
Barney, J.B. (1991), “Firm Resources and Sustained Competitive Advantage”,
Journal of Management, Vol. 17, No. 1, pp.
99–120.
Barney, J.B. (1996), “The Resource-based Theory of the
Firm”, Organizational Science, Vol. 7, No. 5, pp. 66–77.
Bell De Tienne, K., Dyer, G., Hoopes,
C., and Harris, S. (2004), “Toward a model of effective knowledge management
systems: Conceptual foundations and research issues”, Journal of Leadership and
Organizational Studies, Vol. 10, No. 4, pp. 26–43.
Bhatt, G.D. (2001), “Knowledge management in organizations: examining the
interaction between technologies, techniques, and people”, Journal of Knowledge
Management, Vol. 5, No. 1, pp. 68–75.
Bontis, N. (1999), “Managing organizational
knowledge by diagnosing intellectual capital: framing and advancing the state
of the field”, International Journal of Technology Management, Vol. 18, Nos.
5/6/7/8.
Bontis, N. (2001), “Assessing knowledge assets: a
review of the models used to measure intellectual capital”, International
Journal of Management Reviews, Vol. 3, Issue 1, pp. 41–60.
Bose, R. (2004), “Knowledge management metrics”, Industrial Management and
Data Systems, Vol. 104, No. 6, pp. 457–68.
Castellanos, A.R., Rodríguez,
J.L. and Ranguelov, S.Y. (2004), “University
R&D&T capital: What types of knowledge drive it?” Journal of Intellectual
Capital, Vol. 5, No. 3, pp. 478–99.
Chang, T-H. and Wang T-H. (2009), “Using the fuzzy multi-criteria decision making approach
for measuring the possibility of successful knowledge management”, Information
Sciences, Vol. 179, pp. 355–70.
Chen, H-J. and Lin, T-C. (2009), “Exploring source of the variety in organizational
innovation adoption issues – An empirical study of managers’ label on knowledge
management project issues in
Cranfield, D.J. and Taylor, J. (2008), “Knowledge
Management and Higher Education: a
Drucker, P.F. (1990), “The Emerging Theory of
Manufacturing”, Harvard Business Review, Vol. 68, No. 3, pp. 94–102.
Drucker, P.F. (1991), “The New Productivity
Challenge”, Harvard Business Review, Vol. 69, No. 6, pp. 69–79.
Drucker, P.F. (1993), Post-Capitalist Society,
Butterworth-Heinemann,
Fernandez, J.T., Segura, S.L., Salmeron,
J.L. and
Goffee, R. and Jones, G. (2001), “Followership –
It’s Personal Too”, Harvard Business Review, Vol. 79, No. 11, pp. 63–70.
Goh, A..L.S. (2005),
“Harnessing knowledge for innovation: an integrated management framework”,
Journal of Knowledge Management, Vol. 9, No. 4, pp. 6–18.
Golban,
Grant, R.M. (1996), “Prospering in Dynamically-competitive Environments:
Organizational Capability as Knowledge Integration”, Organization Science, Vol.
7, No. 4, pp. 375–87.
Grant, R.M. (2000), “Shifts in the World Economy: The Drivers of Knowledge
Management”, in Despres, C. and Chauvel,
D. (Eds), Knowledge Horizons: The Present and the
Promise of Knowledge Management, Butterworth-Heinemann,
Gumus, H. (2007), “The Effect of Communication on
Knowledge Sharing In Organizations”, Journal of Knowledge Management
Practice, Vol. 8, No. 2, available at http://www.tlainc.com/articl133.htm
(accessed 1 December 2009).
Hall, R. and Andriani, P.
(2002), “Managing Knowledge for Innovation”,
Hazeri,
A. and Sarafzade, M. (2007), “Knowledge Management in
Universities and Role of Libraries on it”, Journal of Information Demonstrator
and Bulletin of Iran Scientific Documents, Vol. 4 and 5.
Hijazi, S. and Kelly, L. (2003), “Knowledge
Creation in Higher Education Institutions: A Conceptual Model”, Proceedings of
the 2003 ASCUE Conference, June 8 – 12,
Hwang, A.S. (2003), “Training strategies in the management
of knowledge”, Journal of Knowledge Management, Vol. 7, No. 3, pp. 156–66.
Jafari, M.,
Jamshidi, L. and Nemati,
M.A. (2008), “An investigation of knowledge share and experience on social
capital development within IT units of
Kakabadse, N.K., Kakabadse,
A. and Kouzmin, A. (2003), “Reviewing the knowledge
management literature: towards a taxonomy”, Journal of Knowledge Management,
Vol. 7, No. 4, pp. 75–91.
Kayakutlu, G. and Buyukozkan,
G. (2008), “Assessing knowledge-based resources in a utility company: Identify
and prioritise the balancing factors”, Energy, Vol.
33, pp. 1027–37.
Khadivar, A., Elahi, H.
and Nezafati, N. (2005), “Study, classification and
comparison of Knowledge Measurement methods”, Paper presented at the Fifth
International Conference of Industrial Engineering, 3–6 May, Science and
Kidwell, J. J., Vander Linde, K.M. and Johnson, S.
L. (2000), “Applying Corporate Knowledge Management Practices in Higher
Education”, Educause Quarterly, No. 4, pp. 28–33.
Lakshman, C. (2007), “Organizational knowledge
leadership: A grounded theory approach”, Leadership and Organization
Development Journal, Vol. 28, No. 1, pp. 51–75.
Lee, K.C., Lee, S. and Kang, I.W. (2005), “KMPI: measuring knowledge
management performance”, Information & Management, Vol. 42, pp. 469–82.
Liebowitz, J., Rubenstein-Montano, B., McCaw, D., Buchwalter, J., Browning, C., Newman, B., Rebeck, K. and the Knowledge Management Methodology Team
(2000), “Knowledge Audit”, Knowledge and Process Management, Vol. 7, No. 1, pp.
3–10.
Lin, H-F. (2007), “A stage model of knowledge
management: an empirical investigation of process and effectiveness”, Journal
of Information Science, Vol. 33, p. 643.
Loh,
B., Tang, A-C., Menkhoff, T., Chay
Y.W. and Evers, H.D. (2003), “Applying knowledge management in university
research”,
McFarlane, D.A. (2008), “Toward
A Knowledge Management Body of Knowledge (KMBOK): A
Philosophical Discourse in KM Concepts and Ideas”, Journal of Knowledge Management Practice, Vol.
9, No. 4, available at http://www.tlainc.com/articl167.htm (accessed 1 December
2009).
McNurlin, B.C. and Sprague, R.H. Jr. (2004),
Information Systems Management in Practice, 6th edition, Pearson Educational
Inc., New Jersey.
Montequín, V.R., Fernández, F.O., Cabal, V.A. and
Gutierrez, N.R. (2006), “An integrated framework for intellectual capital
measurement and knowledge management implementation in small and medium-sized
enterprises”, Journal of Information Science, Vol. 32, p. 525.
Nonaka, I. and Takeuchi, H. (1995), The
Knowledge-Creating Company, Oxford University Press, Boston, MA.
Nunnally, J.C. (1978), Psychometric Theory,
Papoutsakis, H. and Vallès,
R.S. (2006), “Linking Knowledge Management and Information Technology to
Business Performance: A Literature Review and a Proposed Model”, Journal of
Knowledge Management Practice, Vol.
7, No. 1, available at http://www.tlainc.com/articl106.htm (accessed 1 December
2009).
Park, J-H. (2006), “The Role Of
Trust On Knowledge Creation In A Virtual Organization: A Social Capital
Perspective”, Journal of
Knowledge Management Practice, Vol. 7, No. 4, available at
http://www.tlainc.com/articl125.htm (accessed 1 December 2009).
Prusak, L. (1997), Knowledge in Organizations,
Quinn, J.B. (1992), Intelligent
Rampersad, H.K. (2001), Total Quality Management; an executive guide to
continuous improvement, Springer- Verlag,
Rampersad, H. (2002), “Increasing Organizational
Learning Ability Based On A Knowledge Management Quick
Scan”, Journal of Knowledge Management Practice, Vol. 3, available at http://www.tlainc.com/jkmpv3.htm
(accessed August 2006).
Rodrigues, L.L.R., Gayathri,
R.S. and Rao, S. (2006), “Empirical Study Based
Evaluation of KM Models in the IT Sectors: Implications for Quality Outcomes”, Journal of Knowledge Management
Practice, Vol. 7, No. 3, available at http://www.tlainc.com/articl116.htm
(accessed 1 December 2009).
Rodrigues, L.L.R. and Martis,
M.S. (2004), “System Of Human Resource And Knowledge
Management in Engineering Education”, Journal of Knowledge Management Practice,
Vol. 5, No. 1, available at http://www.tlainc.com/articl77.htm (accessed 1
December 2009).
Rowley, J. (2000), “Is higher education ready for knowledge management?”, International Journal of Educational Management, Vol. 14,
No. 7, pp. 325–33.
Sarkar Arani, M.R. (2005), Knowledge Management, research or
knowledge creation, Ghoo Press,
Schultze, U. and Leidner,
D.E. (2002), “Studying knowledge management in information system research:
Discourses and theoretical assumptions”, MIS Quarterly, Vol. 26, No. 3, pp.
213–42.
Scott, W.R. (2000), Organizations: rational, natural, and open systems,
Prentice Hall International,
Senge, P. (1990), “The leader’s new work: building
learning organizations”, Sloan Management Review, Fall,
pp. 7–23.
Shen, P.D., Lee, T-H., Tsai, C.W. and Chen, Y.F.
(2007), “Case Studies on the Implementation of Knowledge Management in the
Distribution Industry: Worldpeace and Alltek”, Electronic Commerce Studies, Vol. 5, No.3,
pp. 263–86.
Sommerville, J. and Dalziel,
S. (1998), “Project Teambuilding – the applicability of Belbin’s
team-role self-perception inventory”, International Journal of Project
Management, Vol. 16, No. 3, pp. 165–71.
Sveiby, K.E. (1992), “Strategy formulation in
Knowledge-intensive industries”, in Hussey, D.E. (Eds),
International Review of Strategic Management, Vol. 3, pp. 167–86.
Sveiby, K.E. (1997), The
New Organizational Wealth – Managing and Measuring Knowledge-Based Assets, Berrett-Koehler,
Sveiby, K.E. (2001), “A Knowledge-based Theory of the Firm To
Guide Strategy Formulation”, Journal of Intellectual Capital, Vol. 2,
No. 4, pp. 344–58.
Teece, D.J. (1998), “Capturing Value from Assets:
The New Economy, Market, and Intangible Assets”,
Teece, D.J. (2000), “Strategies for Managing
Knowledge Assets: The Role of Firm Structure and Industrial Context”,
Thitithananon, P. and Klaewthanong,
T. (2007), “Knowledge Management is a Perfect Education Development Tool: Is
Thailand’s Higher Education Really Ready to Embrace it?”, Journal of Knowledge Management
Practice, Vol. 8, No. 2, available at http://www.tlainc.com/articl135.htm
(accessed 1 December 2009).
Tseng, S. M. (2008), “Knowledge management system performance measure
index”, Expert Systems with Applications, Vol. 34, pp. 734–45.
Venkatraman, N. (1994), “IT-Enabled Business
Transformation: From Automation to Business Scope Redefinition”, Sloan Management
Review, Vol. 35, No. 2, pp. 73–87.
Vlok, D . (2004), “An Assessment of the Knowledge Processing Environment in
an Organisation – A Case Study”, Master’s thesis,
Von Krogh, G. and Roos, J. (1995), “A Perspective
on Knowledge, Competence and Strategy”, Personnel Review, Vol. 24, No. 3, pp.
56–76.
Von Krogh, G., Ichigo, K., and Nonaka,
I. (1998), “Knowledge Enablers”, in Von Krogh, G., Roos,
J. and Kleine, D. (Eds.), Knowing in Firms:
Understanding, Managing and Measuring Knowledge, Sage,
Von Krogh, G., Ichigo, K. and Nonaka,
Von Krogh, G., Nonaka, I. and Nishiguchi,
T. (Eds.) (2000b), Knowledge Creation: A Source of Value,
Wangenheim, C.G., Lichtnow,
D., Wangenheim, A. and Comunello,
E. (2001), “Supporting Knowledge Management in University Software R&D
Groups”, Springer Verlag, Berlin/Heidelberg, pp.
52–66.
Wernerfelt, B. (1984), “A resource-based view of the firm”, Strategic
Management Journal, Vol. 5, No. 2, pp. 272–80.
Wernerfelt, B. (1995), “The resource-based view of
the firm: ten years after”, Strategic Management Journal, Vol. 16, No. 3, pp.
1986–98.
Wen,
Y-F. (2009), “An effectiveness measurement model for knowledge
management”, Knowledge-Based Systems, In press.
Wheelwright, S.C. and Clark, K.B. (1992), Revolutionizing Product
Development: Quantum Leaps in Speed, Efficiency, and Quality, The Free Press, A Division of Macmillan, Inc.,
Willcoxson, L. (2004), Using the Learning
Organization Concept For Quality Development Within A
University,
Wong, K.Y. and Aspinwall, E.
(2004), “Characterizing knowledge management in the small business
environment”, Journal of Knowledge Management, Vol. 8, No. 3, pp. 44–61.
Wong, K.Y. and Aspinwall, E. (2006), “Development
of a knowledge management initiative and system: a case study”, Expert Systems
with Applications, Vol. 30, No. 4, pp. 633–41.
Wu, J-H. and Wang, Y-M.
(2006), “Measuring KMS success: A respecification of
the DeLone and McLean’s model”, Information &
Management, Vol. 43, pp. 728–39.
Wu, L-C., Ong, C-S. and Hsu, Y-W. (2008), “Knowledge-Based Organization
Evaluation”, Decision Support Systems, Vol. 45, pp. 541–9.
Contact the Authors:
Alireza Anvari, Ph.D Candidate in Industrial And
Systems Engineering, Universiti Putra Malaysia (UPM);
Tel: +989112551127; Email: ar_anvar@yahoo.com
Rosnah Mohd. Yusuff, Lecturer/Associate Professor in Industrial
Engineering and Management, Dept. of Mechanical and Manufacturing Engineering,
Faculty of Engineering, Universiti Putra Malaysia,
43400 UPM, Serdang, Selangor; Tel: 603-8946-6342;
Fax: 603-86567122; Email: rosnah@eng.upm.edu.my
Dr Norzima Zulkifli,
Department of Mechanical and Manufacturing Engineering, Universiti
Putra Malaysia 43400 UPM, Serdang
Seyed Mohammad Hossein
Hojjati, Lecturer/Associate Professor, Dept. of
Engineering Faculty of Industrial Engineering and Technology Management,
Islamic Azad University- Shiraz branch, Iran; Tel: +98-711-6215680; Fax:
+98-711-6217067; Email: hojjaty_mh@iaushiraz.ac.ir
Yusof Ismail, Lecturer/Professor, Dept. of Manufacturing Engineering, Faculty
of Manufacturing Engineering and Technology Management,
University Malaysia Pahang; Tel: 09-5492449; Fax: 09-5492689; Email: mdyusof@ump.edu.my