Knowledge management capabilities and organizational performance

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Knowledge management capabilities and organizational performance

DR.MOHAMAD KAZEM EMADZADE
Assistant Professor of Management Department, University of Isfahan, Isfahan, Iran

BEHNAZ MASHAYEKHI

MA Student of Management Department, University of Isfahan, Isfahan, Iran

ELHAM ABDAR
MA Student of Management Department, University of Isfahan, Isfahan, Iran


Abstract
Knowledge management (KM) has attracted significant attention from researchers and practitioners as a
facilitator of firm performance. Even though companies have implemented KM, they offer inconsistent support
that KM enhances firm performance. Thus, we examine the impact of specific knowledge management
resources on organizational performance.

Based on an empirical study consisted of 245 small size business
owners and managers at a management-level in their firms from 86 enterprises located in Isfahan , results show
that some knowledge resources (e.g. organizational structure, knowledge application) are directly related to
organizational performance, while others (e.g. technology, knowledge conversion), are not directly related to
organizational performance.
Keywords: Knowledge management, Infrastructure Capabilities, Process Capabilities, Organizational
performance

1. Introduction
In the last decade, the importance of knowledge has been highlighted by both academics and practitioners (Wu
&Lin, 2009). Nowadays, knowledge is the fundamental basis of competition (Zack, 1999; Grant, 1996) and,
particularly tacit knowledge, can be a source of advantage because it is unique, imperfectly mobile, imperfectly
imitable and non-substitutable. However, the mere act of processing knowledge itself does not guarantee
strategic advantage (Zack 2002); instead, knowledge has to be managed. In next year’s, firms that create new
knowledge and apply it effectively and efficiently will be successful at creating competitive advantages.
(Skyrme,2001) defines knowledge management (KM) as’ the explicit and systematic management of vital
knowledge–and its associated processes of creation, organization, diffusion, use and exploitation’. KM
principles have been studied and implemented in every organizational discipline and profession (Kebede, 2010).
From a practice perspective, firms are noticing the importance of managing knowledge if they want to remain
competitive (Zack, 1999) and grow (Salojنrvi, Furu,&Sveiby,2005). Thus, many companies everywhere are
beginning to actively manage their knowledge and intellectual capital (DeTienne, Dyer, Hoopes, & Harris,
2004): most large companies in the USA, and many in Europe, have some sort of KM initiative in place
(Davenport & Vِ
lpel, 2001).
Organizations develop KM capabilities to help support a range of vital operational and innovative activities. The
interest in organizational capabilities has created a focus on the development and implementation of KM
processes and infrastructure required to support daily work practices. Different resources make up the
knowledge capability of a firm. These include technology infrastructure, organizational structure and
organizational culture which are linked to a firm’s knowledge infrastructure capability; and knowledge
acquisition, knowledge conversion, knowledge application and knowledge protection which are linked to the
firm’s knowledge process capability (Alavi and Leidner, 2001; Gold et al., 2001). Taken together, these
resources determine the knowledge management capability of a firm, which in turn has been linked to various
measures of organizational performance (Grant, 1996; Gold et al., 2001; Lee and Sukoco, 2007; Zack et al.,
2009). Given the composite nature of knowledge capabilities, most firms will possess different levels and
combinations of resources (i.e. knowledge enablers and processes) that collectively make up their knowledge
capability. The contribution that each resource makes to organizational performance is therefore likely to vary
across firms; it is this unique makeup that enables benefits such as competitive advantage and improved
performance.
The purpose of this paper is to evaluate the impact of knowledge management resources on organizational
performance. The findings provide insights into the infrastructure and process capabilities needed to provide
knowledge support for organizational routines and activities.
This paper is organized as follows. Theoretical background discusses two capabilities of Knowledge
management and establishes the study hypotheses. Subsequent sections then describe the methodology, results,
and analysis. Finally, the last section discusses conclusions and presents limitations and recommendations.


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2. Theoretical background and conceptual model
When it comes to the relationship between IT resources and organizational performance the resource-based
view (RBV) offers a useful lens for understanding this link. In essence, the RBV argues that ‘‘firms possess
resources, a subset of which enables them to achieve competitive advantage, and a further subset which leads to
superior long-term performance’’ (Wernerfelt, 1984, p.108). However, the RBV is void of a single definition of
the term ‘‘resource’’ (Wade and Hulland, 2004) with many researchers using the terms ‘‘resources’’ and
‘‘capabilities’’ interchangeably (Christensen and Overdorf, 2000; Gold et al., 2001; Sanchez et al., 1996). The
RBV also recognizes that while some resources may lead to performance enhancements, others do not, and that
the combination may differ across industries and firms. As such, a key challenge for firms is to identify and
leverage those resources that directly impact organizational performance (Wade and Hulland, 2004; Zack et al.,
2009). KM capabilities are integral for effective knowledge sharing between individuals. Knowledge use is
associated with people and behavior and organizations benefit when knowledge is shared in context and
according to need. Organizations need to adopt an integrative approach to developing KM capabilities that
covers all potential sources of knowledge and reduces barriers to knowledge sharing and organizational
learning. KM capabilities, namely infrastructure and processes, provide the support structure required to share
knowledge within the context in which it is required. Organizations aim to develop KM capabilities into a state
where KM practices are institutionalized and embedded into its daily work practices. For a KM initiative to
achieve such an organizational state, the knowledge infrastructure and process capabilities need to develop from
an initial state of low availability, accessibility, usage and practice to a state of organizational capability of high
availability, accessibility, usage and practice (Gold et al 2001, Khalifa and Liu 2003).
Fig. 1 presents the research model. Infrastructure capabilities, such as knowledge-based culture, structure,
technology, and process capabilities, such as Knowledge Acquisition, Knowledge Conversion, Knowledge
Protection and Knowledge Application are proposed to have an impact on the firm performance. The rationale
for these factors and the relationship among them is described in the following sections.

Figure (1) Research model (Annette M. Mills and Trevor A. Smith, 2010)




















2.1 KM Infrastructure Capabilities
Gold et al (2001) identify information technology, organizational structure, and culture as infrastructure
capabilities, and acquisition, conversion, application and protection as process capabilities, and Khalifa and Liu
(2003) while advancing Gold et all’s (2001) proposition establish leadership, culture and KM strategy as
infrastructure required to develop a KM initiative.
Information technology is an infrastructure capability as it facilitates knowledge flow and eliminates barriers to
communication within an organization. Although an appropriate technology infrastructure is essential for
effective knowledge management, studies that examine the link between information technologies and measures
of organizational performance are often inconclusive, and fail to demonstrate whether IT is directly related to
performance (Powell and Dent-Micallef, 1997; Webb and Schlemmer, 2006). For example, Powell and Dent-
Micallef (1997) in their study of US firms, found that IT in and of itself did not enhance organizational
performance, but could increase organizational performance when combined with other human and business
assets. Teece et al. (1997) further suggested that the absence of an association between technology and
performance could be because technology (e.g. IS resources) is easily copied, making it a fragile source of

Organizational
Performance

Knowledge Infrastructure
Capability

Technology Infrastructure
Organizational Culture
O
r
g
anizati
o
nal
S
tr
uc
t
u
r
e

Knowledge Process
Capability

Knowledge Acquisition
Knowledge Conversion
Knowledge Protection
Knowledge Application
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competitive advantage. Although technology is not always linked directly to organizational performance,
research shows that when combined with other resources IT can enhance performance and lead to sustained
advantage (Clemons and Row, 1991; Powell and Dent-Micallef, 1997). So although the technology
infrastructure may not contribute directly to organizational performance, it is an essential enabler of other
knowledge resources such as knowledge acquisition and knowledge application processes, which may
themselves enhance organizational performance (Seleim and Khalil, 2007).
A flexible organizational structure encourages knowledge sharing and collaboration across boundaries within
the organization, while a rigid structure often has the unintended consequence of inhibiting such practices.
Organizational structure capability for facilitating the flow of knowledge is shaped by an organization’s policies,
processes, and system of rewards and incentives, which determine the channels from which knowledge is
accessed and how it flows (Leonard-Barton 1995). Knowledge management theorists largely conclude that
changes in an organization’s structure, such as moving from hierarchical to flatter networked forms, are
essential for the effective transfer and creation of knowledge in the organization (Beveren, 2003; Gold et al.,
2001; Grant, 1996; Nonaka and Takeuchi, 1995). Such changes by extension have been positively associated
with improved outputs in both service and financial terms (Richert, 1999).
An organization’s culture is central to encourage interaction and collaboration between individuals that are
important to facilitate knowledge flow, and provides individuals the ability to self-organize their own
knowledge and practice networks to facilitate solutions for problems and share knowledge (O’Dell and Grayson
1998). Organizational vision, mission and values embody the culture of the organization and determine the types
of knowledge that are desired and the types of knowledge related activities that are encouraged (Leonard-Barton
1995). An appropriate culture within a firm can encourage people to create and share knowledge (Holsapple &
Joshi, 2001; Leonard-Barton, 1995). Sin and Tse (2000) found that organizational cultural values such as
consumer orientation, service quality, informality and innovation were ‘‘significantly associated with marketing
effectiveness’’ (Sin and Tse, 2000, p. 305). More recently, Aydin and Ceylan (2009) also showed that cultural
dimensions were related to organizational performance. Thus it is expected that:
H1. Technology is not (directly) related to organizational performance.
H2. Organizational culture is positively related to organizational performance.
H3. Organization structure is positively related to organizational performance.

2.2 KM Process Capabilities
The KM processes of an organization are focused towards obtaining, sharing, storing, and using knowledge.
Gold et al. (2001) suggested that knowledge process capabilities (required for storing, transforming and
transporting of knowledge throughout the organization) are needed for leveraging the infrastructure capability.
Four broad dimensions are identified ‘‘acquiring knowledge, converting it into useful form, applying or using it,
and protecting it’’ (Gold et al., 2001, p. 190).
Knowledge acquisition: Knowledge acquisition refers to the degree to which the firm develops or creates
knowledge resources across functional boundaries. it is enabled by the processes and activities of interaction,
feedback, innovation, brainstorming, and benchmarking. Knowledge acquisition reflects in part, a subset of a
firm’s absorptive capacity – more specifically, it can be viewed as a ‘‘potential capacity’’ that reflects a firm’s
ability to use its knowledge to create advantage, but does not guarantee that knowledge will be used effectively
(Cohen and Levinthal, 1990). Research suggests strong and positive links between knowledge acquisition and
performance measures. For example, Song (2008) showed that knowledge creation practices were significantly
related to organizational improvement. Further, when acquired knowledge is used appropriately, a significant
and positive link is observed between knowledge acquisition and organizational performance (Lyles and Salk,
1996; Seleim and Khalil, 2007).
Knowledge conversion: Knowledge conversion is made possible through the processes and activities of
synthesis, refinement, integration, combination, coordination, distribution, and restructuring of knowledge.
Shared contexts and common representation are required for knowledge conversion, and facilitated by group
problem solving and decision-making. Information technologies like email, repositories, intranet portal,
teleconferencing, and the activities of mentoring, collaboration and training play a key role in transferring
knowledge. Forums such as communities of practice and centers of excellence, and training provide a platform
for the transfer of knowledge. Thus, it is expected that the knowledge conversion process could influence
performance outcomes.
Knowledge application: Knowledge application refers to the degree to which the firm applies the knowledge
resources that are shared across functional boundaries. It allows the firm to reap returns on its knowledge
resource. The capability to utilize a related knowledge base in decision making and problem solving allows the
firm to respond more effectively to environmental changes. Knowledge is used in a context in which users can
learn and also produce new knowledge. In learning process there must be analysis and critical assessment of
ideas plans and knowledge. many organizations encourage organizational learning in which individuals and
teams can apply the knowledge gained to initiatives’ such as new product development with the ultimate aim of
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improved performance in areas such as ‘‘speed to market’’ and innovation (Sarin and McDermott, 2003). For
knowledge to impact organizational performance it has to be used to support the firm’s processes. Hence, it is
through knowledge utilization that acquired knowledge can be transformed from being a potential capability
into a realized and dynamic capability that impacts organizational performance (Cohen and Levinthal, 1990;
Seleim and Khalil, 2007; Zahra and George, 2002).
Knowledge protection: Knowledge protection is necessary for effective functioning and control within
organizations. This would typically include the use of copyright and patents along with information technology
systems that allow knowledge to be secured by filename, user name, password and file-sharing protocols that
ascribe rights to authorized users (Lee and Yang, 2000). However, knowledge protection is often challenging in
part because the copyright laws that are intended to protect knowledge are limited in their treatment of the
knowledge environment (Everard, 2001). Notwithstanding such limitations, the knowledge protection process
should not be abandoned or marginalized (Gold et al., 2001) and protecting knowledge from illegal and
inappropriate use is essential for a firm to establish and maintain a competitive advantage (Liebeskind, 1996).
Moreover, since knowledge is crucial for competitive advantage, storing and protecting knowledge is expected
to create value for the organization (Lee and Sukoco, 2007). Taken altogether, it is expected that:
H4. Knowledge acquisition is positively related to organizational performance.
H5. Knowledge conversion is positively related to organizational performance.
H6. Knowledge application is positively related to organizational performance.
H7. Knowledge protection is positively related to organizational performance.

2.3. Knowledge management capabilities and organizational performance.
There is a general consensus in the literature that knowledge management is linked to organizational
performance (Gold et al., 2001; Gosh and Scott, 2007; Lee and Sukoco, 2007; Liu et al, 2005; Zaim et al.,
2007). For example, Gold et al. (2001) and Zaim et al. (2007) showed that both knowledge infrastructure
capability and knowledge process capability have a significant and positive impact on organizational
effectiveness. Lee and Sukoco (2007) found that knowledge management capabilities affect innovation and
organizational effectiveness. Gosh and Scott (2007) also argued that knowledge infrastructural capabilities such
as technology, organizational culture and organizational structure, need to correspond with knowledge process
capabilities (e.g. actual flow and use of knowledge) in order to achieve considerable improvements in
effectiveness. In assessing the relationship between knowledge management practices and performance
outcomes, Zack et al. (2009) found that knowledge management practices are related to measures of
organizational performance. Thus, it is expected that:
H8. Knowledge infrastructural capability is positively related to organizational performance.
H9. Knowledge process capability is positively related to organizational performance.

3. Methodology
3.1. Measures
A multiple-item method was used to construct the questionnaires. Questions were structured in a Likert scale
model (1 to 5) with ‘strongly disagree,’’ ‘‘disagree,’’ ‘‘neither agree nor disagree,’’ ‘‘agree,’’ and ‘‘strongly
agree’’ as the choices. To evaluate the research hypotheses, a questionnaires was developed to capture measures
of knowledge management capabilities and organizational performance. The measures consisted of multi-item
constructs adapted from Gold et al., 2001:

• knowledge infrastructure capability which comprised technology, organizational structure, and
organizational culture;
• knowledge process capability which comprised knowledge acquisition, knowledge conversion,
knowledge application, and knowledge protection; and
• organizational performance.

The respondents in this study were small size business owners and managers at a management-level in their
firms from 86 enterprises located in Isfahan. Out of the 245 respondents that were asked to participate in this
study, we received 206 usable responses. Since the aim of this research was to better understand the
relationships between the individual factors that make up the firms’ knowledge management capabilities and
organizational performance, two levels of analysis were conducted. First, a decomposed model of knowledge
management capabilities was examined–this looked at the links between organizational performance and
particular resources (i.e. enablers and processes) that make up a firm’s knowledge infrastructural capability and
knowledge process capability. The composite model was also evaluated and the results compared with the
findings from the decomposed model.

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3.2. Results and analysis
SPSS version 17.0 were used to assess the links between knowledge management capabilities and organization
effectiveness. We adopt empirical studies to analyze the impact of knowledge management capabilities on firm
performance. Descriptive statistics (i.e. mean and standard deviation (SD)) for each construct are shown in
Table 1. Table 1 also shows that composite reliabilities ranged from 0.904 to 0.948 and average variance
extracted (AVE) from 0.667 to 0.789 exceeding recommended cut-offs (Chin, 1998). Construct AVEs were also
greater than the variance shared between the constructs (Table 2) satisfying the criteria for discriminant validity
(Chin, 1998). Regarding the reliability of the measures, we conducted a confirmatory factor analysis (CFA) for
each one of the constructs. Measurement model shows high reliability and validity of the scales (Table 1).
Cronbach’s alpha is above .70. Scale composite reliability indexes are higher than .70, as recommended by other
studies, and average variance extracted is above 0.50,minimum value proposed by Fornell and Larcker (1981).
As maybe observed from Table 1, measurement model shows appropriate indexes of goodness-fit: a non-
significant 2, GFI, CFI and IFI above .80, RMSEA below .08, and RMR between .055 and .065.
The results showed the decomposed model accounted for 0.778 of the variance observed for organizational
performance. For knowledge process capability, three processes were significant vis-a` -vis organizational
performance: knowledge acquisition (b = 0.123; p ≤ 0.05), knowledge application (b = 0.502; p ≤ 0.001), and
knowledge protection (b = 0.136; p ≤ 0.05); H4, H6 and H7 were supported. Knowledge conversion capability
was not significant (b = 0.037); H5 was not supported. Of the knowledge infrastructural capabilities,only
organizational structure (b = 0.301; p ≤ 0.05) was significant vis-a`-vis organizational performance; technology
infrastructure (b = 0.041) was not expected to be significant. Hypotheses H1 and H3 were supported. Contrary
to expectation, organizational culture was not significant (b = 0.058); H2 was therefore not supported. The study
results provided strong empirical support for the decomposed model, accounting for 0.778 of the variance
observed for organizational performance. For the composite model, the amount of variance explained was
0.753. Consistent with expectations, knowledge infrastructural capability (b = 0.346; p ≤ 0.05) and knowledge
process capability (b = 0.648; p ≤ 0.001) were both significant vis-a` -vis organizational performance,
supporting hypotheses H8 and H9.
The results for the decomposed model (Table 3) showed that of the three infrastructural capabilities, only
organizational structure had a significant impact on organizational performance; neither technology nor
organizational culture had a significant impact on organizational performance. For knowledge process
capability, knowledge acquisition, knowledge application and knowledge protection also impacted
organizational performance, but not knowledge conversion. A summary of the results of the model tests for the
decomposed model and the composite model are shown in Table 3.

4. Conclusions

4.1. Discussion
Through knowledge management processes, companies can have more related information to provide a high
level of management to select and compare, and come out with more effective strategies to gain the utmost
benefits. The results showed that for the current study, organizational structure, knowledge acquisition,
knowledge application and knowledge protection were significantly related to organizational performance.
However, technology, organizational culture and knowledge conversion did not have a significant impact.
This research suggests appropriate investments in knowledge management initiatives can enhance
organizational performance. However, this study shows that not all of the resources are direct contributors.
Although resources such as technology, culture and knowledge conversion are necessary for effective
knowledge management (Gold et al.,2001) they did not impact organizational performance directly. However,
firms can ill afford to neglect these dimensions as they work in combination with and support other resources,
such as knowledge acquisition and knowledge application that may contribute directly to organizational success
(Van den Bosch et al., 1999; Seleim and Khalil, 2007).
The findings suggest that although the individual resources collectively determine a firm’s overall knowledge
management capability which, as a composite is related to organizational performance, each resource is not
directly linked to performance. The decomposed model therefore offers insights into relationships at the
dimensional level that are not readily inferred from composite models. This study offers useful insights into the
knowledge management–performance link. There has been little research that decomposes the effects of
knowledge management in relation to organizational performance. The results suggest the decomposed
approach is useful for understanding the complex relationships embodied in the knowledge management–
performance link, which cannot be surmised from a composite model.



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4.2. Limitations and recommendations
It is obvious that knowledge management processes have positive and outstanding effects on firm performance.
Although the results are interesting and promising, they need to be taken with caution because there are
limitations in this research. First, this study focused on small firms. Thus, caution should be exercised in
generalizing the results to firms with a different environment and competitive structure, and this research’s
result is not sufficient and not representable. Therefore the researchers should investigate the key factors in
determining various types of knowledge management in different aspects. Second, subjective measures for
performance were included in the questionnaire. In future we can also try to consider objective measures for
performance, such as ROA or ROI. Third, in future research, a sampling frame that combines firms from
different countries could be adopted in order to provide a more international perspective to the subject.

Item
MEAN
SD
SCRa
AVE
Alpha Cronbach

Knowledge infrastructure capabilities

Organizational structure (OS)
4.762
1.341
0.912
0.667
0.812
Organizational culture (OC)
4.934
1.122
0.935
0.686
0.795
Technology (TC)
4.091
1.326
0.942
0.712
0.821

Knowledge process capabilities
Knowledge acquisition (KQ)
5.436
1.531
0.911
0.789
0.742
Knowledge conversion (KC)
4.824
1.657
0.942
0.759
0.739
Knowledge application (KA)
5.195
1.382
0.948
0.732
0.867
Knowledge protection (KP)
4.588
1.327
0.921
0.742
0.823
Organizational performance (OP)
4.791
1.412
0.904
0.713
0.867

Table 1: Confirmatory factor analysis (CFA)
a
Scale composite reliability
2(137) = 337.05
GFI = .82, CFI = .85, IFI = .84, RMSEA= .073, RMR = .061


Item
OS
OC
TC
KQ
KC
KA
KP
OP

Knowledge infrastructure capabilities
Organizational structure (OS)
0.773







Organizational culture (OC)
0.735
0.794






Technology (TC)
0.634
0.623
0.831






Knowledge process capabilities
Knowledge acquisition (KQ)
0.711
0.741
0.602
0.782




Knowledge conversion (KC)
0.658
0.683
0.714
0.739
0.789



Knowledge application (KA)
0.698
0.724
0.673
0.762
0.794
0.783


Knowledge protection (KP)
0.610
0.573
0.631
0.596
0.636
0.615
0.811

Organizational performance
(OP)
0.732
0.742
0.587
0.732
0.752
0.816
0.695
0.852
Table 2: Inter-construct correlations and discriminant validity








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Hypotheses
β
Significance
Decomposed model


Knowledge infrastructural capability


H1. Technology is not (directly) related to organizational performance
0.041
ns
H2. Organizational culture is positively related to organizational performance
0.058
ns
H3. Organizational structure is positively related to organizational performance
0.301
p ≤ 0.05
Knowledge process capability


H4. Knowledge acquisition is positively related to organizational performance
0.123
p ≤ 0.05
H5. Knowledge conversion is positively related to organizational performance
0.037
ns
H6. Knowledge application is positively related to organizational performance
0.502
p ≤ 0.001
H7. Knowledge protection is positively related to organizational performance
0.136
p ≤ 0.05
R-Squared
0.778
-
Composite model


H8. Knowledge infrastructural capability is positively related to organizational performance
0.346
p ≤ 0.05
H9. Knowledge process capability is positively related to organizational performance
0.648
p ≤ 0.001
R-Squared
0.753
-

Table 3: Summary of results for the model tests








































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