KNOWLEDGE SHARING BEHAVIOR AND KNOWLEDGE MANAGEMENT CAPABILITY IN ENGINEERING ORGANIZATION

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Sengottuvel and Dr. U. Syed Aktharsha.”Knowledge Sharing Behavior and Knowledge Management
Capability in Engineering Organization”.-(ICAM 2016)
KNOWLEDGE SHARING BEHAVIOR AND KNOWLEDGE
MANAGEMENT CAPABILITY IN ENGINEERING ORGANIZATION
Mr. Sengottuvel
Research Scholar, Jamal Institute of Management,
Jamal Mohamed College, Tiruchirapalli –20
Dr. U. Syed Aktharsha
Associate Professor, Jamal Institute of Management,
Jamal Mohamed College, Tiruchirappalli –20
ABSTRACT
The purpose of this paper is to examine the relationship among the Knowledge Sharing
Factors, Knowledge Sharing Intention, Knowledge Sharing Behavior and Knowledge
Management Capability. For this study, a sample of 109 executive engineers of a leading
Engineering Organization, from Trichy was drawn from the population of 750 executive
engineers using a structured questionnaire. The results of Partial Least Square Path
Modelling (PLS-PM) have shown that the Attitude, Subjective Norms and Perceived
Behavioral Control are found to be significant predictors of Knowledge Sharing Intention,
then the Knowledge Sharing Intention of executive engineers are positively significant with
Knowledge Sharing Behavior and Knowledge Sharing behavior of executive engineers plays a
vital role in the Knowledge Management Capability of the Organization.
Key words: Knowledge Sharing Intention, Knowledge Sharing Behavior, Knowledge
Management capability and Partial Least Square – Path Modeling (PLS-PM)
Cite this Article: Sengottuvel and Dr. U. Syed Aktharsha. Knowledge Sharing Behavior and
Knowledge Management Capability in Engineering Organization. International Journal of
Management, 7(2), 2016, pp. 215-225, http://www.iaeme.com/ijm/index.asp
1. INTRODUCTION
The survival of almost all organization is dependent upon the creation and utilization of new
knowledge and it is therefore inevitable that knowledge needs to be shared. To create a knowledge
sharing culture you need to encourage people to work together more effectively, to collaborate and to
share in order to make organizational knowledge more productive. The sharing of knowledge is crucial
in business because the new knowledge leads to sustainable competitive advantage in the form of
competitive intelligence. Also the tacit knowledge resides in the minds of personnel and this
knowledge will be lost when they leave the organization. The extent of the knowledge is so wide and
substantial that it can result in organizations, large and small, “not knowing what they know.” There is
no standard expertise knowledge among organizations. Knowledge sharing also be fosters innovation
by encouraging the free flow of ideas; encourages staff innovation and creativity, provides a feedback
loop to re-work and re-use knowledge for the benefit of the organization and improves performance.
INTERNATIONAL JOURNAL OF MANAGEMENT (IJM)
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ISSN 0976-6510 (Online)
Volume 7, Issue 2, February (2016), pp. 215-225
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International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 -
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To leverage and manage organizational knowledge resources, organizations are adopting
knowledge management (KM) initiatives and are investing heavily in information and communication
technologies in the form of knowledge management systems (KMS) (Davenport & Prusak, 1998; Alavi
and Leidener, 2001; Osterloh et. al., 2000; Zack, 1999). Knowledge management rallies around
building the organization’s ability to acquire, organize and diffuse the knowledge throughout the
organization with the objective of improving its effectiveness, efficiency and competitiveness (Alavi
and Leidner, 1999). A key enabler of knowledge management is knowledge sharing (Nonaka and
Takeuchi, 1995; Alavi and Leidner, 2001). Sharing knowledge, many organizations assert is crucial to
exploiting core competencies and to achieve sustained competitive advantage (Argote and Ingram,
2000; Gold et al., 2001). Prahalad and Hamel (1990) observe that organization’s core competencies
reside in the collective learning of the organization be it production, marketing or technological
capabilities, that are inimitable by the competitors. To allow collective learning and to grow knowledge
assets, an organization must develop an effective knowledge sharing process and encourage its
executive engineers and partners to share knowledge about customers, competitors, markets, products
and so forth (Bock & Kim, 2002; Pan & Scarbrough, 1998; O’Dell & Grayson, 1998; Osterloh et al.,
2000).
In the contemporary knowledge-driven economic environment, the development and management
of critical knowledge have become a critical and challenging task for managers to acquire sustainable
competitive advantages of their organizations. To acquire sustainable competitive advantages,
encouraging executive engineers in different units to actively share knowledge with one another to
enable them to develop skills and competences is a vital prerequisite. However, managers find it
practically difficult to facilitate effective interpersonal knowledge sharing activities among executive
engineers in organization because of a variety of human and organizational/environmental factors,
including concerns related to interpersonal relationships, self-interests, and organizational incentives
(Yang & Wu 2008). Therefore, researchers have intensively investigated the human and organizational
factors that influence individuals’ intention to share knowledge among one another in various
organizational contexts (Bock et al. 2005; Bock et al. 2006; He & Wei 2009; Kankanhalli et al. 2005;
Leonardi & Treem 2012; Lin et al. 2009). Therefore, additional research that investigates how
organizations may establish an environment that motivates knowledge sharing behaviors from a
holistic perspective is necessary in order to enhance the organizations’ ability to plan for, evaluate, and,
justify their efforts to encourage executive engineers’ knowledge sharing behaviors.
Knowledge is the most important intangible asset; therefore business managers strive in many
ways to use this asset to create the highest value (Quintas, 2002). However, how to efficiently control,
apply, and develop knowledge in order to effectively generate and reuse knowledge is determined by
enterprises’ knowledge management (KM) capabilities (Davenport et al., 1998; Leonard-Barton, 1995;
Soo et al., 2002). In other words, it is important to investigate how an enterprise effectively develops its
KM capability in order to provide and share intangible assets to win market competition. Furthermore,
the rapid development of technology and the internet not only accelerates the changes of external
environments, but also pressures enterprises to recognize that they need to evolve along with the
market trends and environmental changes. Due to the fact that the basic perspectives on traditional
resources lack a mechanism for transforming resources into competitive advantages, an enterprise may
be unable to identify the middle- and long-term dynamic changes in the environment in order to
immediately respond to market changes. Therefore, the only solution for an enterprise to enhance
organizational performance is through enhancing its corporate dynamic capability (Afuah, 2001).
Furthermore, in previous studies, many scholars have confirmed that KM capability and dynamic
capability influence organizational performance (Hasan and Al-hawari, 2003; Bassie, 1997; Wiig,
1997).
Capability refers to the ability to implement and integrate resources to achieve corporate goals, as
well as results acquired from long-term accumulation of interaction among various resources (Grant,
1995). KM capability is the ability of an enterprise to leverage existing knowledge through continuous
learning to create new knowledge (Bose, 2003). Liu et al. (2004) stated that KM capability not only
refers to the ability to acquire knowledge and information, but also to the organizational capability to
protect knowledge and information in order to encourage staff to use this ability as a tool to work more
efficiently. Freeze and Kulkarni (2007) further indicate that effective leverage of different knowledge
capabilities can be done through differing strategies, processes, and technologies. Due to the fact that
knowledge is a key strategic resource to create corporate value (Drucker, 1993; Zack, 1999; Bhatt et

217
al., 2005), enterprises strive to develop knowledge resources to the maximum in order to achieve
corporate goals. Furthermore, whether an enterprise can effectively utilize knowledge resources and
develop knowledge determines the pros and cons of KM capability. Hence, it can be understood that
KM capability has become a significant attribute of competitive advantage (Andrew, 2005).
However, researchers and practitioners have tried an integrative model that explores the
relationships among knowledge Sharing Intention, Knowledge Sharing Behavior and Knowledge
Management Capability in Manufacturing is very few. To fill this gap, this study develops a research
model that links knowledge Sharing Intention, Knowledge Sharing Behavior and Knowledge
Management Capability.
2. NEED OF THE STUDY
The purpose of this study is to identify and understand the various factors influencing the knowledge
sharing behavior of respondents and how it influences Knowledge Management capability of a leading
Engineering Organization in Trichy. It is needed to identify the executive engineer’s interest in
Knowledge Sharing with their Colleagues. The need of this study is to examine factors that promote or
discourage knowledge sharing behaviors of knowledge workers in the organizational context of a
leading Engineering Organization in Trichy. The need of this study is to analyze the knowledge sharing
and Knowledge Management capability of a leading Engineering Organization in Trichy. It is needed
to identify the top management support to the executive engineer’s knowledge sharing interest. It is
needed to identify the recognition & rewards given to motivate the executive engineers. The need of
this study is to develop insights that could be used by a leading Engineering Organization in Trichy in
developing realistic environments that are conducive to knowledge sharing.
3. RESEARCH OBJECTIVES
 To study the demographic profile of respondents.
 To examine the impact of Knowledge sharing behavior on Knowledge management capability
of an organization.
 To measure the impact of knowledge sharing intention towards knowledge sharing behavior.
 To examine the influence of executive engineers attitudes, subjective norms and perceived
behavior control on knowledge sharing intention of executive engineers.
4. REVIEW OF LITERATURE
4.1. Knowledge Sharing Intention
Bock, Zmud, Kim and Lee (2005) examined factors that are believed to influence individuals'
knowledge-sharing intentions. Researchers drew upon the Theory of Reasoned Action (TRA) (Ajzen
and Fishbein 1980) for the study’s theoretical framework. To this framework, they have added extrinsic
motivators, social psychological forces and organizational climate factors. Using field survey of 154
managers from 27 Korean organizations, the researchers found that the attitude towards knowledge
sharing along with the subjective norms and organizational climate influence individual’s intention to
engage in knowledge sharing behavior. Other findings of the study indicate that anticipated reciprocal
relationships positively influence attitudes towards knowledge sharing while sense of self-worth and
organizational climate influence subjective norms. A surprising finding of the study is that anticipated
extrinsic rewards negatively influence the knowledge sharing behavior. One of the limitations of this
study is that while researchers examined the individual’s intention to share knowledge, they did not
examine the actual knowledge-sharing behavior.
4.2. Knowledge Sharing Behavior
Review of the extant literature on knowledge sharing indicates that there is no all-round definition of
knowledge sharing. Many researchers have defined knowledge sharing from their own point of view.
Some researchers even considered knowledge sharing, knowledge flows and knowledge transfer as
exchangeable terms and defined them as such. For instance, Alavi and Leidner (2001) liken knowledge
sharing to knowledge transfer and define it as the process of disseminating knowledge throughout the
organization. The dissemination can happen between individuals, groups or organizations using any

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type or number of communication channels. Similarly, Gupta and Govindarajan (2000), equating
knowledge sharing to knowledge flows theorize that knowledge flows comprise of five elements: value
of the source knowledge, willingness of the source to share knowledge, media richness of the
communication channel, willingness of the recipient to acquire knowledge and the absorptive capacity
of the recipient. Davenport and Prusak (1998) define knowledge sharing as process that involves
exchanging knowledge between individuals and groups. Connelly and Kelloway (2003) define
knowledge sharing as “a set of behaviors that involve the exchange of information or assistance to
other. It is separate from information sharing, which typically involves management making
information on the organization available to executive engineers. Whereas knowledge sharing contains
an element of reciprocity, information sharing can be unidirectional and unrequested”.
Connelly and Kelloway (2003) investigated a number of factors that impact executive engineer’s
perceptions of a knowledge sharing culture. The identified factors can be broadly categorized into
groups: organizational factors and individual factors. Organizational factors include individuals’
perceptions regarding management support for knowledge sharing, their perceptions about a positive
social interaction culture, organization’s size, and the presence of technology that can facilitate
knowledge sharing. Individual factors include age, gender and organizational tenure. The research
findings suggest perceptions about management’s support for knowledge sharing, and perceptions of a
positive social interaction culture to be significant predictors of a positive knowledge sharing culture.
Organizational size was negatively related to positive knowledge sharing culture such that smaller
organizations were linked more with positive knowledge sharing culture. Lastly, gender was found to
be significant moderator such that female participants needed more positive social interaction culture
before they would perceive a knowledge sharing culture as positive in contrast to their male
counterparts.
Constant, Keisler and Sproull (1994) studied the factors that support or constrain information
sharing in technologically advanced organizations. The factors they looked into are work experience,
computer experience, year of training and perceptions about organizational ownership of information.
Using interdependence theory (Kelley & Thibaut, 1978), the researchers advanced a theory of
information sharing. Researchers contend that information sharing behavior is affected by rational self-
interest as well as the social and organizational context. The results of their laboratory studies indicate
that attitudes about information sharing depend on the form of information. While sharing tangible
information depend on pro-social attitudes and norms of organizational ownership, sharing expertise
depends on people’s own identity and self-expressive needs.
Osterloh et al., (2000) assert that effective knowledge creation and transfer is closely related to the
motivation management. They analyzed various organizational and motivational devices with respect
to their suitability to generate and transfer knowledge. In doing so, they noted that certain
organizational forms have the capacity to crowd out intrinsic motivation and therefore are detrimental
to the effective transfer of knowledge.
4.3. Knowledge Management Capability
Gold et al. (2001) pointed out that KM capability consists of knowledge infrastructures and KM
processes. The knowledge infrastructure includes technology, structure, and culture; while KM
processes include the organizational capabilities of knowledge acquisition, conversion, application, and
protection. Simultaneously, in order to effectively leverage knowledge infrastructure, it is crucial to
rely on KM processes, which makes it possible to store, transform, and transfer knowledge.
Tanriverdi (2005) investigated the influence of KM capability on the corporate performance of
multi-business-unit corporations and divided KM capability into product KM capability, customer KM
capability, and managerial KM capability. Furthermore, Tanriverdi also described knowledge creation,
transfer, integration, and leverage as the four main dimensions to measure the influence of three kinds
of KM capability on corporate performance.
Fan et al. (2009) further combined knowledge infrastructure and KM processes and proposed
seven attributes (i.e. technology, structure, culture, acquisition, conversion, application, and protection)
to be applied in a fuzzy multiple decision-making method to measure organizational KM capability.
On the other hand, Aujirapongpan et al. (2010) explained corporate KM capability based on the
perspectives of resource-based and knowledge-based capabilities. Resource-based capability refers to
different angles of resources to investigate KM capability and an assumption that possessing different

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resources will result in different KM capabilities and influence the infrastructure capability of KM
capability, including technology, organizational structure, and culture.
5. RESEARCH MODEL
Research model is descriptive in nature. It is a detailed plan of how the goals of research will be
achieved. For the present study, single cross sectional Survey research model is used in order to
understand the relationship among knowledge sharing Intention, Knowledge Sharing Behavior and
Knowledge Management Capability. This research curiosity has led to the construction of following
research model (figure 1) and its corresponding hypotheses.
H1: Attitude towards Knowledge Sharing has significant positive association with knowledge sharing
Intention.
H2: Subjective Norm has significant positive association with knowledge sharing Intention.
H3: Perceived Behavioral Control has significant positive association with knowledge sharing
Intention.
H4: Knowledge Sharing Intention has significant positive association with knowledge sharing
Behavior.
H5: Knowledge Sharing Behavior has significant positive association with knowledge Management
Capability.
Figure 1 Proposed Research Model

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6. RESEARCH METHODOLOGY
This basically is an empirical study and as the name suggests it relies on experience or observation
alone, and it can even be without due regard for system and theory (Kothari, 2004). This is basically a
data-based research, which can give conclusions based on observation. As far as the approach is
concerned, it is both qualitative as well as quantitative in nature. Literature pertaining to Knowledge
Sharing Intention, Knowledge sharing behavior and Knowledge Management Capability have been
studied to understand the relevance of each one of them, and also, to study their antecedents and
consequences of the same and used in the formulation of the working hypothesis.
7. RESPONDENTS
The respondents are executive engineers of a leading engineering organization - Trichy. The workforce
comprises over 750 executive engineers. The sample size of the study is 109 executive engineers.
Disproportionate simple random sampling was adopted. Pilot study was undertaken with a sample of
30 random executive engineers so that necessary modifications can be incorporated to enhance the
quality of survey instrument. The reliability and convergent validity of the instrument have been
verified. Finally, the metric in the form of a self-administered questionnaire with 5-point Likert scale
was distributed to 155 executive engineers (response rate 70%), who are basically executive engineers
working in a leading engineering organization - Trichy, to collect data.
8. QUESTIONNAIRE
The questionnaire consists of two parts namely Part I and Part II. The part I contained 9 questions on
Demographic factors of users such as Name, age, gender, Marital Status, educational qualifications,
experience, department, designation and Annual Income. Part- II consists of the conceptual factors
such as, Knowledge sharing behavioral factors with 16 questions, Knowledge sharing intention with 7
questions, Knowledge Sharing Behavior with 7 questions and Knowledge Management Capability with
21 questions. The scaling values are 1- Strongly Agree; 2- Agree; 3- Neutral; 4- Disagree; 5- Strongly
Disagree.
9. SAMPLE CHARACTERISTICS
Out of 109 respondents, 67 percent of the executive engineers were Males. 18 percent of the executive
engineers were between the age group of 36-45 years. Nearly 50 percent of the executive engineers
were married. 50 percent of executive engineers were UG degree holders. 39 percent of executive
engineers were working for 2-3 years. About 40 percent of executive engineers were in cadre of
Engineers. 33 percent of executive engineers were working in engineering department. About 27
percent of executive engineers were drawing a monthly salary ranging from 50001 - 75000.
10. DATA ANALYSIS
10.1. Reliability and Validity
The study has employed ‘Cronbach alpha coefficient’ for assessing the reliability of the scale.
According to Nunnally (1978), Cronbach alpha level of 0.60 or above is considered to be acceptable
for construct. Also, Convergent validity of all the constructs was examined using the measure of
Average Variance Extracted (AVE) that is the average variance shared between a construct and its items
(Fornell & Larcker, 1981). Chin et al 1999 & 2003 indicated that a construct with an AVE of over 0.5 is
expected to have adequate convergent validity.

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Table 1. Reliability and Validity
Dimensions No. of items
Cronbach’s
Alpha value
AVE value
Attitude towards Knowledge Sharing 5 0.75 0.67
Subjective Norm 5 0.74 0.51
Perceived behavioral Control 6 0.85 0.50
Knowledge Sharing Intention 7 0.85 0.54
Knowledge Sharing Behavior 7 0.87 0.58
Knowledge Management Capability 21 0.96 0.61
Total Items 51
Table 1 presents that all the constructs namely Attitude towards Knowledge Sharing, Subjective Norm,
Perceived behavioral Control, Knowledge Sharing Intention, Knowledge Sharing Behavior and
Knowledge Management Capability exhibit adequate reliability with internal consistency values of
0.75, 0.74, 0.85, 0.85, 0.87, 0.96 respectively which is greater than recommended alpha value of 0.60.
Also, The AVE of each of construct was over 0.40 which satisfies the standard values.
10.2. Model Validation
In order to test the proposed Hypothesis, this study employed a construct level Correlation analysis as
an initial verification. Visual PLS is used to compute the constructs scores. Using these constructs
scores as a base, the study explored the relationship between the variables using SPSS package 21.0.
The construct correlation has been presented in the table 2.
Table 2. Construct Level Correlation of Model
Hypoth
esis
Independent variables Dependent Variables
Pearson’s
Correlation
Signific
ance
level at
1 %
H1 Attitude towards Knowledge
Sharing
Knowledge sharing
Intention
-0.825 0.000
H2
Subjective norms
0.833 0.000
H3
Perceived Behavior Control
0.843 0.000
H4
Knowledge sharing Intention
Knowledge sharing
behavior
0.813 0.000
H5 Knowledge Sharing behavior
Knowledge management
Capability
0.947 0.000
The correlation table indicates that there exists a positive relationship between subjective norms,
perceived behavior control towards Knowledge Sharing Intention except Attitude towards Knowledge
Sharing which is negatively correlated to Knowledge Sharing Intention with the R value of -0.825.
Also there found to be positive correlation between Knowledge sharing Intention and Knowledge
Sharing Behavior with R value of 0.813 and also the Knowledge Sharing Behavior and Knowledge
Management Capability with R value of 0.947. Staples et al (1998) indicated that through the bivariate
correlation are significant between the construct, it is still required to assess the path coefficient in the
structural model as a causal effect. (Efron 1979, Efron and Gond, 1983) expressed that in order to
ensure that path coefficients are statistically significant, this study has employed a bootstrap and jack
knife re-sampling procedures to estimate standard errors for calculating values using visual PLS. The
results are examined and the t-statistic value at the 0.05 level is 1.96. If the t-statistic value is greater
than 1.96, the path is considered to be significant.

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Figure 2. Structural Equation Results of Model
Table 3: Bootstrap Summary of Model and Hypothesis Result
Hypothesis
Entire sample
estimate
Mean of sub
sample
Standard
error
t-
Statistic
R square
value
Result
H1 0.367 0.3864 .0566 6.4793
0.844
Significant
H2 0.255 .2496 .0745 3.4249 Significant
H3 0.374 .3625 .0829 4.5114 Significant
H4 0.817 .8245 .0263 31.0711 0.667 Significant
H5 0.954 .9552 .0096 99.2396 0.909 Significant
As presented in figure 2 and table 3, the path linking Attitude towards Knowledge Sharing to
Knowledge Sharing Intention was found to be significant at 0.05 level (beta=0.367, t=6.497),
indicating Attitude towards knowledge sharing has significant effect on Knowledge sharing intention.
This provides support for H1.
The path linking Subjective Norms to Knowledge Sharing Intention was found to be significant at
0.05 level (beta=0.255, t=6.497), indicating Subjective norms towards knowledge sharing has
significant effect on Knowledge sharing Intention. This provides support for H2.
The path linking Perceived Behavioral Control to Knowledge Sharing Intention was found to be
significant at 0.05 level (beta=0.374, t=4.511), indicating Perceived Behavioral Control has significant
effect on Knowledge sharing Intention. This provides support for H3.
The path linking Knowledge Sharing Intention to Knowledge Sharing Behavior was found to be
significant at 0.05 level (beta=0.817, t=31.071), indicating Knowledge sharing intention has significant
effect on Knowledge sharing behavior. This provides support for H4.
The path linking Knowledge Sharing Behavior to Knowledge Management Capability was found
to be significant at 0.05 level (beta=0.954, t=99.240), indicating Knowledge sharing behavior has
significant effect on Knowledge management capability. This provides support for H5.
Collectively, Attitude towards Knowledge Sharing, subjective norms and perceives behavior
control explained about 84 percent of the variance in the knowledge sharing Intention of executive
engineers. In addition, the knowledge Sharing Intention explained a variation of 66 percent in
Knowledge Sharing Behavior. And the Knowledge Sharing Behavior explained about 90 percent of
the variance in the Knowledge Management capability.
11. DISCUSSION
11.1. Knowledge Sharing Intention
It is theorized that Knowledge Sharing Intention are to be predicted by Attitude towards knowledge
sharing, Subjective Norm and Perceived Behavior Control. In other words, it can be understood that

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Knowledge Sharing Behavior adopted by the organization significantly predicts Knowledge Sharing
Intention of executive engineers.
The overall results of the structural model analysis revealed that Attitude towards knowledge
sharing, Subjective Norm and Perceived Behavior Control acted as significant predictors in Knowledge
Sharing Intention among executive engineers.
From the analysis, it is revealed that Attitude, Subjective Norm and Perceived Behavior Control
had a significant effect on Knowledge sharing Intention. This finding is consistent with the findings of
Bock, Zmud, Kim and Lee (2005). In this the researchers found that the attitude towards knowledge
sharing along with the subjective norms and organizational climate influence individual’s intention to
engage in knowledge sharing behavior. It implies that the Attitude towards knowledge sharing increase
the knowledge Sharing Intention among.
11.2. Knowledge Sharing Behavior
In this study, it is hypothesized that Knowledge sharing Behavior of an executive engineers is to be
determined by Knowledge Sharing Intention of executive engineers. It implies that Knowledge sharing
intention is the significant predictor of Knowledge Sharing Behavior. From the analysis, it is found that
Knowledge sharing intention had a significant effect on Knowledge Sharing Behavior.
11.3. Knowledge Management Capability
From the analysis of this study it is hypothesized that Knowledge Management capability is to be
determined by Knowledge Sharing Behavior of executive engineers. It implies that Knowledge sharing
Behavior is the significant predictor of Knowledge Management Capability. From the analysis, it is
found that Knowledge sharing behavior had a significant effect on Knowledge Management Capability.
11.4. Research Limitations and Future Research
There are few limitations to this research study. First, the research setting for the current study was a
leading engineering organization in Trichy district. Respondents were limited to executive engineers of
the leading engineering organization in Trichy only. As such, the study may limit the extent to which
respondent behaviours can be generalized to the general work force. The results of this study can be
regarded as being representative of the perceptions of the general knowledge work force. To further
increase the generalizability however, future research should replicate the study’s findings with larger
samples and in different contexts. Second, the study focuses on attitudes towards knowledge sharing,
subjective norms and perceived behaviour control that influence knowledge sharing Intention of
knowledge workers. Future research should focus on other Knowledge Sharing factors. Finally, the
study’s findings are based on the modest sample size of 109 respondents. Although PLS Graph can
handle small sample sizes and generates valid results, a larger sample with more statistical power
would have permitted me to use other covariance based structural equation modelling tools such as
LISREL. Future research should verify the findings of this research study using covariance based tools.
11.5. Implication for Practice
The study has highlighted the importance of Knowledge Sharing Behavior in Organizations and its
corresponding impact on the Knowledge Management Capability. The Attitude towards knowledge
sharing, Subjective Norms and Perceived Behavioral control. It will enable the organization to pay
special focus on these three Knowledge Sharing factors which are important in predicting Knowledge
Management Capability through Knowledge Sharing Intention.
In addition, this paper has put forward some valuable insights to guide executive engineers who
are in practice, to identify problems in their respective areas and will help them in getting rid of the
same by taking self-corrective actions.
Moreover, at final the Attitude towards knowledge sharing, Subjective Norms and Perceived
Behavioural Control should always adopted by executive engineers as Significant Parameters for
Knowledge Sharing Intention, in which Knowledge Management capability of an organization can be
flourish.

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12. CONCLUSION
In conclusion, the purpose of this study is to investigate the associations between the Knowledge
Sharing Intention, Knowledge Sharing Behavior and Knowledge Management Capability among
executive engineers of a leading engineering organization in Trichy. A sample of 109 executive
engineers was drawn from a leading engineering organization in Trichy. A model is developed and
tested using structured modeling approach. The empirical findings have revealed that Attitude towards
knowledge sharing, Subjective Norms and Perceived Behavioral Control are associated with
Knowledge Sharing Intention. As the same the Knowledge Sharing Intention of the executive engineers
are also been significant with the Knowledge Sharing Behavior of the executive engineers. Also, the
findings have demonstrated that the knowledge sharing behavior of executive engineers is closely
linked to Knowledge Management Capability of the Organization. It is concluded that when there are
Proper way is for to share knowledge in organization, it will encourage executive engineers to share the
knowledge. When there is effective Knowledge Sharing Behavior among executive engineers, it will
result in the development of Knowledge Management Capability in Organizations.
13. REFERENCES
[1] Afuah, A. (2001), “Dynamic boundaries of the firm: are firms better off being vertically
integrated in the face of a technological change?” The Academy of Management Journal,
Vol. 44 No. 6, pp. 1211-1228.
[2] Ajzen, I., and Fishbein, M. “Understanding Attitudes and Predicting Social
Behavior,”Prentice-Hall, Englewood Cliffs, NJ, 1980.
[3] Alavi, M., and Leidner, D. E. "Knowledge Management Systems: Issues, Challenges and
Benefits," Communications of AIS (1), 1999, pp. 1-37.
[4] Alavi, M., and Leidner, D. E. "Review: Knowledge Management and Knowledge
Management Systems: Conceptual Foundations and Research Issues," MIS Quarterly
(25:1), 2001, pp. 107-136.
[5] Anderson, J.C. and Gerbing, D.W. (1992), “Assumptions of the two-step approach to
latent Variable modelling”, Sociological Methods and Research, Vol. 20 No. 3, pp.321-
33.
[6] Ardichvill, A., Page, V. and Wentling, T. (2003), “Motivation and barriers to
participation in Virtual knowledge-sharing communities of practice”, Journal of
Knowledge Management, Vol. 7 No. 1, pp. 64-77.
[7] Argote, L., and Ingram, P. "Knowledge Transfer: A Basis for Competitive Advantage in
Firms," Organizational Behavior and Human Decision Processes (82:1), 2000, pp.150-
169.
[8] Aujirapongpan, S., Vadhanasindhu, P., Chandrachai, A. and Cooparat p. (2010),
“Indicators of knowledge management capability for KM effectiveness”, The Journal of
Information and Knowledge Management Systems, Vol. 40 No. 2, pp. 183-203.
[9] Bagozzi, R.P. and Yi, Y. (1988), “On the evaluation of structural equation model”,
Journal of Academy of Marketing Science, Vol. 16 No. 1, pp. 74-94.
[10] Bandura, A. (1986), Social Foundations of Thought and Action: A Social Cognitive
Theory, Prentice-Hall, Englewood Cliffs, NJ.
[11] Bartol, K. and Srivastava, A. (2002), “Encouraging knowledge sharing: the role of
organizational reward systems”, Journal of Leadership and Organization Studies, Vol.19
No. 1, pp. 64-76.
[12] Bassie, L.J. (1997), “Harnessing the power of intellectual capital”, Training and
Development, Vol. 51 No. 12, pp. 25-30.
[13] Bock, G. W., and Kim, Y. G. "Breaking the Myths of Rewards: An Exploratory Study of
Attitudes about Knowledge Sharing," Information Resource Management Journal (15:2),
2002, pp. 14-21.

225
[14] Bock, G.W., Zmud, R.W. and Kim, Y.G. (2005), “Behavioral intention formation in
knowledge sharing: examining the roles of extrinsic motivators, social-psychological
forces, and organizational climate”, MIS Quarterly, Vol. 29 No. 1, pp. 87-111.
[15] Browne, M.W. and Cudeck, R. (1993), Alternative Ways of Assessing Model Fit, Sage
Publications, Newbury Park, CA.
[16] Cabrera, E.F. and Bonache, J. (1999), “An expert HR system for aligning organizational
culture and strategy”, Human Resource Planning, Vol. 22 No. 1, pp.51-60.
[17] Chau, P.Y.K. and Hu, P.J.E. (2001), “Information technology acceptance by individual
professionals: a model comparison approach”, Decision Sciences, Vol. 34No. 4, pp. 699-
719.
[18] Connelly, C.E. and Kelloway, E.K. (2003), “Predictors of executive engineers’
perceptions of knowledge sharing culture”, Leadership & Organization Development
Journal, Vol. 24 No. 5,pp. 294-301
[19] Davenport, T. H., and Prusak, L. “Working Knowledge: How Organizations Manage
What They Know,” Harvard Business School Press, Boston, 1998.
[20] Fan, Z.P., Feng, Bo, Sun, Y.H. and Ou,W. (2009), “Evaluating knowledge management
capability of organizations: a fuzzy linguistic method”, Expert Systems with
Applications, Vol. 36 No. 2, pp. 3346-3354.
[21] Gold, A.H., Malhotra, A., Segars, A.H. "Knowledge management: an organizational
capabilities perspective", Journal of Management Information Systems, (18:1), 2001,
pp.185-214.
[22] Gupta, A. K. & Govindarajan, V. “Knowledge Management’s Social Dimension: Lessons
from Nucor Steel,” Sloan Management Review (42:1), 2000, pp. 71-80.
[23] Hasan, H. and Al-hawari, M. (2003), “Management styles and performance: a knowledge
space framework”, Journal of Knowledge Management, Vol. 7 No. 4, pp. 15-28.
[24] Leonard-Barton, D. (1995), Wellsprings of Knowledge: Building & Sustaining the Source
of Innovation, Harvard Business School Press, Boston, MA.
[25] Nonaka, I. & Takeuchi, H. “The Knowledge Creating Company: How Japanese
Companies Create the Dynamics of Innovation”. New York: Oxford University Press,
1995.
[26] Osterloh, M., and Frey, B. S. "Motivation, Knowledge Transfer, and Organizational
Forms," Organization Science (11:5), 2000, pp. 538-550.
[27] Pan, S., & Scarbrough, H. “A socio-technical view of knowledge-sharing at Buckman
Laboratories,” Journal of Knowledge Management, (2:1), 1998, pp. 55-66
[28] Prahalad, C. K. and Hamel, G. "The core competence of the corporation." Harvard
Business Review, (May-June), (68:3), 1990, pp. 79-91.
[29] Quintas, P. (2002), “Managing knowledge in a new century”, in Little, S., Quintas, P. and
Ray, T. (Eds), Managing Knowledge, Open University Press, Buckingham, pp. 1-14.
[30] Soo, C., Devinney, T., Midgley, D. and Deering, A. (2002), “Knowledge management:
philosophy, processes and pitfalls”, California Management Review, Vol. 44 No. 4, pp.
129-150.
[31] Tanriverdi, H. (2005), “Information technology relatedness, knowledge management
capability, and performance of multi business firms”, MIS Quarterly, Vol. 29 No. 2, pp.
311-334.
[32] Wiig, K.M. (1997), “Knowledge management: where did it come from & where will it
go?” Expert Systems with Applications, Vol. 13 No. 1, pp. 1-14.
[33] Zack, M. H. "Managing Codified Knowledge," Sloan Management Review (40:4), 1999,
pp. 45-58.

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