SYSTEM ACCEPTANCE ROLE IN ACTUAL USE OF KNOWLEDGE MANAGEMENT SYSTEMS

Arabian Journal of Business and Management Review (OMAN Chapter)
Vol. 4, No.3; October. 2014
SYSTEM ACCEPTANCE ROLE IN ACTUAL USE OF KNOWLEDGE
MANAGEMENT SYSTEMS
Nasrin Budaghi
Department of Management, Germi Branch, Islamic Azad Unversity, Germi, Iran
Mohammad Feizi1
Department of Management, Meshginshahr Branch, Islamic Azad Unversity, Meshginshahr, Iran
Abstract
This study has done to the examining the system acceptance role in actual use of knowledge
management systems. The population of the study were both public and private active banks
employees in Meshginshahr city that use knowledge management system. According to Cochran
sampling, the sample size of this research was set at 175 that selected stratified sampling method.
To gathering of data, we used a questionnaire. All the reliability and validity of measures has
examined. Questionnaires reliability was estimated by calculating Cronbach’s Alpha; it was
0.789. In order to analyze the data resulted from collected questionnaires descriptive statistical
methods are used, and to display some statistical data we used column diagram. Findings show
that the mean of all variables were bigger than 3 and so we can say that system acceptance and it
dimensions (management support, evaluation system, perceived relevance, and available) have
important role in actual use of knowledge management systems at both public and private active
banks employees in Meshginshahr.
Key words: Knowledge management, management support, evaluation system, perceived
relevance, and availability, acceptance system
INTRODUCTION
Knowledge management efforts typically focus on organizational objectives such as improved
performance, competitive advantage, innovation, the sharing of lessons learned, integration and
continuous improvement of the organization (Gupta and Sharma, 2004). KM efforts overlap with
organizational learning and may be distinguished from that by a greater focus on the
management of knowledge as a strategic asset and a focus on encouraging the sharing of
knowledge (Maier, 2007). It is seen as an enabler of organizational learning and a more concrete
mechanism than the previous abstract research (Sanchez, 1996)
Previous knowledge management approaches focus on business aspects rather than education
(Alavi and Leidner, 2001). Innovative approaches for turning knowledge management into
practical teaching activities have been ignored. Many organizations pursue knowledge
management (KM) initiatives, with different degrees of success. One key aspect of KM often
neglected in practice is that it not only concerns technology. Technology merely provides the
tools with which employees can leverage their knowledge in the context of their work. Thus,
1
Correspondence author
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Arabian Journal of Business and Management Review (OMAN Chapter)
Vol. 4, No.3; October. 2014
how employees perceive the technology and interact with it is assumed to play a major role in
KM initiatives' success (Bals et al, 2007).
Early KM technologies included online corporate yellow pages as expertise locators and
document management systems. Combined with the early development of collaborative
technologies (in particular Lotus Notes), KM technologies expanded in the mid-1990s. (Alavi
and Leidner, 1999). Subsequent KM efforts leveraged semantic technologies for search and
retrieval and the development of e-learning tools for communities of practice (Capozzi
2007).Knowledge management systems can thus be categorized as falling into one or more of the
following groups: Groupware, document management systems, expert systems, semantic
networks, relational and object oriented databases, simulation tools, and artificial intelligence
(Gupta and Sharma, 2004).
More recently, development of social computing tools (such as bookmarks, blogs, and wikis)
have allowed more unstructured, self-governing or ecosystem approaches to the transfer, capture
and creation of knowledge, including the development of new forms of communities, networks,
or matrixed organisations (Calvin, 2005). However such tools for the most part are still based on
text and code, and thus represent explicit knowledge transfer (McAdam and McCreedy, 2000).
These tools face challenges in distilling meaningful re-usable knowledge and ensuring that their
content is transmissible through diverse channels (Gene, 2013).
The basic concept behind user acceptance frameworks is that user perceptions about information
technology influence their intention to use and ultimately their actual use of information
technology. In addition, the actual use of an information technology system has a feedback
relationship with user perceptions. Technology Acceptance Models (TAM) have typically been
used to explain why technology is or is not successful by studying the antecedents “perceived
usefulness” and “perceived ease of use” and their impact on intention to use technology (Davis,
1989). Empirical studies of TAM have consistently found that perceived usefulness is a strong
determinant of intention to use (Venkatesh & Davis, 2000). Research has also found that
perceived usefulness is a predictor of attitudes toward using technology both before
implementation and in the post-implementation environment (Meg Fryling, 2012).
This model emphasizes surveying individual attitudes toward information technology, and has
been widely employed in many significant studies of user attitudes (Liaw & Huang, 2003; Liaw,
Huang & Chen, 2007). The understanding of learners' attitudes can help effectively expand
system functions and meet learners' needs.
METHODOLOGY
The main purpose of the present research is evaluating the system acceptance to actual use
knowledge management systems. The research method is descriptive. We examine the
employees acceptance system to actual use of knowledge management systems according to four
dimensions; management support, evaluation system, perceived relevance, and availability.
The population of the study were both public and private active banks employees in
Meshginshahr city that use knowledge management system. According to Cochran sampling, the
sample size of this research was set at 175 that selected stratified sampling method.
To gathering of data, we used a questionnaire. All the reliability and validity of measures has
examined. Questionnaires reliability was estimated by calculating Cronbach’s Alpha; it was
0.789.
15
Arabian Journal of Business and Management Review (OMAN Chapter)
Vol. 4, No.3; October. 2014
In order to analyze the data resulted from collected questionnaires descriptive statistical methods
are used, and to display some statistical data we used column diagram. The analysis has
performed with SPSS.
RESULTS AND CONCLUSION
The demographic data gathered from questionnaire shows that eighty Seven percent of the
responders are male and thirteen percent of the responders are female. The responder’s degree is
14.9 percent MA, 59.4 percent Bachelor, 24 percent Diploma and 1.7 percent have No degree. It
means that the most of the responder have university degree.
Table1- Responders Gender and Degree
Valid
Frequency Percent
Gender
Degree
Male
Female
Total
153
22
87.4
12.6
175
100.0
No degree
Diploma
Bachelor/Profession
al
Master
Total
3
42
1.7
24.0
104
59.4
26
175
14.9
100.0
Table 2 shows age of the responders. 1.1 percent of responders have under 30 years’ old, and
37.7 percent have between 30-40, 34.3 percent 40-50, and finally 26.9 percent have more than
51 years of work experience. It shows that most the personnel age are between 30- 50.
Table 2- Age of the responders
Valid
Frequency
Percent
Below 30 years old
2
1.1
Between 30 and 40
66
37.7
Between 41 and 50
60
34.3
Above 51 years old
47
26.9
Total
175
100.0
From the precedence point of view about 9.7 percent of responders were Less than 5 years. 9.1
percent between 5-10, 24.6 percent have between 10 - 15, 37.7 percent have between 15 - 20,
and finally 18.9 percent have experience more than 21 years. It shows that all the managers have
good experience.
Table 3- experience of the responders
Frequency
Percent
Valid
17
9.7
5 to 10
16
9.1
10 to 15
43
24.6
15 to 20
66
37.7
Above 20 Years
33
18.9
Total
175
100.0
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Arabian Journal of Business and Management Review (OMAN Chapter)
Vol. 4, No.3; October. 2014
We examine the employees trust to actual use of knowledge management systems according to
three dimensions management support, evaluation system, perceived relevance, and available.
The following table shows the Frequency distribution (Mean and standard deviation) of system
acceptance to actual use of knowledge management systems. The acceptance system to actual
use of knowledge management systems calculated by management support, evaluation system,
perceived relevance, and available indexes.
Table 4: Mean and standard deviation of Management support and its dimensions
Variable
Management Use from System
System as an integral part of career
Provide adequate resources by organizations
Training programs offered at organization
Total Management support
Mean
3.97
3.74
4.37
4.05
4.03
SD
.979
.835
.892
.804
.775
Graph 1: Mean of Management support dimensions
Training programs offered at organization
4.05
Provide adequate resources by
organizations
4.37
3.74
System as an integral part of career
3.97
Management Use from System
3.4 3.5 3.6 3.7 3.8 3.9 4 4.1 4.2 4.3 4.4 4.5
According to table 4 and Graph 1 Management Use from System has 3.97 mean, System as an
integral part of career has 3.74, Provide adequate resources by organizations has 4.37 mean, and
Training programs offered at organization has 4.05 mean. Total Management support has 4.03
mean and it means that Management support have an important role in actual use of knowledge
management systems.
Table 5 : Mean and standard deviation of Evaluation system and its dimensions
Variable
Mechanisms exist to verify the
contents entered into the system
Reward systems based on the level
of participation in the system
Total Evaluation system
Graph 2: Mean of Evaluation system dimensions
17
Mean
4.30
SD
.784
4.38
.770
4.34
. 643
Arabian Journal of Business and Management Review (OMAN Chapter)
Vol. 4, No.3; October. 2014
Reward systems based on the level of
participation in the system
4.38
Mechanisms exist to verify the contents
entered into the system
4.3
4.26 4.28 4.3 4.32 4.34 4.36 4.38 4.4
According to table 5 and Graph 2 Mechanisms exist to verify the contents entered into the
system has 4.30 mean and Reward systems based on the level of participation in the system has
4.38. Total Evaluation system has 4.34 mean and it means that Evaluation system have an
important role in actual use of knowledge management systems.
Table 6: Mean and standard deviation of Perceived relevance and its dimensions
Variable
System role in accomplishing tasks quickly
System role in improving employee performance
System role in the ease of doing work by user
System role in enhancing control over user job
total Perceived relevance
Mean
3.65
3.39
4.07
3.78
3.72
SD
1.155
.908
1.189
1.005
.983
Graph 3: Mean of Perceived relevance dimensions
System role in enhancing control
over user job
3.78
System role in the ease of doing
work by user
4.07
System role in improving
employee performance
3.39
System role in accomplishing
tasks quickly
3.65
0
1
2
3
4
5
According to table 6 and Graph 3, System role in accomplishing tasks quickly has 3.65 mean,
System role in improving employee performance has 3.39, System role in enhancing control over
user job has 3.73 mean, and System role in the ease of doing work by user has 4.07 mean. Total
Perceived relevance has 3.72 mean and it means that Perceived relevance have an important role
in actual use of knowledge management systems.
Table 7: Mean and standard deviation of Availability and its dimensions
Variable
Take advantage of easy system
Understanding of the system
18
Mean
4.49
4.49
SD
.787
.772
Arabian Journal of Business and Management Review (OMAN Chapter)
Flexibility in interacting systems
Total Availability
Vol. 4, No.3; October. 2014
3.35
4.11
1.422
.630
Graph 4: Mean of Availability dimensions
3.35
Flexibility in interacting systems
Understanding of the system
4.49
Take advantage of easy system
4.49
0
1
2
3
4
5
According to table 7 and Graph 4 Take advantage of easy system has 4.49 mean, Understanding
of the system has 4.49, and Flexibility in interacting systems has 3.35 mean. Total Availability
has 4.11 mean and it means that Availability have an important role in actual use of knowledge
management systems.
Findings show that the mean of all variables were bigger than 3 and so we can say that system
acceptance and it dimensions (management support, evaluation system, perceived relevance, and
available) have important role in actual use of knowledge management systems at both public
and private active banks employees in Meshginshahr.
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