Knowledge Management a Way to Gain a Competitive Advantage in Firms (Evidence of Manufacturing Companies)

Abstract

Knowledge as the basis of competition is the most important factor and the knowledge, innovations also Technology and knowledge based companies as the most important factor for survival is known. Knowledge Process Entrepreneurship, the creation of knowledge and the conversion of products and services through innovation. The most basic feature of Intelligent Organizations twenty-first century, the emphasis on knowledge and information. Unlike previous organizations, organizations advanced technologies today, require Acquisition, management and exploitation of knowledge and information to improve efficiency, manage and track Variations are endless. Knowledge is a powerful tool that can change the world And innovations made possible. Knowledge management is an interdisciplinary business model with all aspects of knowledge creation, Coding, sharing and using knowledge to enhance learning and innovation in the context of the company and Is working. This study developed a questionnaire and send it to companies located in the industrial town managers found that knowledge management has an impact on the surface of the competitive advantage's Knowledge management and competitive advantage, Innovation , Organizational performance, Customer satisfaction, The study variables were. Ranged the in 2,013th were tested. The results indicate that Knowledge management has made a significant competitive advantage.

Full text

Knowledge Management a way to gain a competitive
advantage in firms (evidence of manufacturing
companies)
Bahram Meihami1, Hussein Meihami2
1Department of Accounting, Ghorveh Branch, Islamic Azad University, Ghorveh, Iran
2Department of English Language Teaching, Ghorveh Branch, Islamic Azad University, Ghorveh, Iran
E-mail address: meyhami4@gmail.com
ABSTRACT
Knowledge as the basis of competition is the most important factor and the knowledge,
innovations also Technology and knowledge based companies as the most important factor for
survival is known. Knowledge Process Entrepreneurship, the creation of knowledge and the
conversion of products and services through innovation. The most basic feature of Intelligent
Organizations twenty-first century, the emphasis on knowledge and information. Unlike previous
organizations, organizations advanced technologies today, require Acquisition, management and
exploitation of knowledge and information to improve efficiency, manage and track Variations are
endless. Knowledge is a powerful tool that can change the world And innovations made possible.
Knowledge management is an interdisciplinary business model with all aspects of knowledge
creation, Coding, sharing and using knowledge to enhance learning and innovation in the context of
the company and Is working. This study developed a questionnaire and send it to companies located
in the industrial town managers found that knowledge management has an impact on the surface of
the competitive advantage's Knowledge management and competitive advantage, Innovation ,
Organizational performance, Customer satisfaction, The study variables were. Ranged the in 2,013th
were tested. The results indicate that Knowledge management has made a significant competitive
advantage.
Keywords: Knowledge Management; Competitive Advantage; Innovation; Customer satisfaction;
Organizational performance
1. INTRODUCTION
1. 1.What Is Knowledge?
Most definitions and explanations of knowledge seem to cover the same vocabulary,
concepts and words. Rather than provide a standard definition, the paper addresses the
general themes and fundamentals that have become evident in recent years.
 Knowledge goes through a process of sharing tacit with tacit knowledge, tacit to
explicit, explicit leverage, and explicit back to tacit.
 Knowledge can be created and tested.
International Letters of Social and Humanistic Sciences Online: 2013-10-29
ISSN: 2300-2697, Vol. 14, pp 80-91
doi:10.18052/www.scipress.com/ILSHS.14.80
© 2014 SciPress Ltd., Switzerland
This is an open access article under the CC-BY 4.0 license (https://creativecommons.org/licenses/by/4.0/)

 Knowledge can be distinguished from data and information.
 Explicit knowledge is usually filtered, stored, retrieved and dispersed across the
organisation.
 A culture that does not foster and reward the sharing of knowledge cannot expect
technology to solve its problems (Srinivas 2000).
1. 2. KM definition
KM is often viewed as multidimensional and multidisciplinary concept. There are many
definitions of KM in the literature, thus comparisons must be made to know the focus by each
author. Some of the focuses are highlighted below. Professor Michael Sutton (2008) of the
Gore School of Business at Westminster College reported at the ICKM (International
Conference on Knowledge Management) meeting in 2008 that he had assembled a library of
more than 100 of them (Mclnerney C. and Koeing M., 2009). Three definitions of KM ones
are presented here. At the very beginning of the KM movement, Davenport (1994) offered
the following: “knowledge management is the process of capturing, distributing, and
effectively using knowledge”. This definition has the virtue of being simple, stark, and to the
point. A few years later, the Gartner Group created another definition of KM, which is
perhaps the most frequently cited (Duhon, 1998): “A discipline that promotes an integrated
approach to identifying, capturing, evaluating, retrieving, and sharing all of an enterprise’s
information assets. These assets may include databases, documents, policies, procedures, and
previously un-captured expertise and experience in individual workers”.
1. 3. The Knowledge Transformation Process
As stated earlier, knowledge goes through a transformation process, which can be
facilitated through the utilisation of Decision Support Systems (DSS), Artificial Intelligence
(AI). The paper covers the main area of focus, the explication of knowledge, with further
detail of this transformation process to be found in the following reference (Nemati, Steiger
et al. 2002). DSS are IT and software specifically designed to help people at all levels of the
company, below the executive level, make decisions. DSS can play an important role in the
transformation process of explicating knowledge, for example, through the specification of
mathematical modelling. Specifically, the goal of these models, and of the decision variables,
must be explicitly articulated by the decision-maker. Furthermore, the decision maker must
also explicitly articulate the model constraints. This specification of explicit knowledge
"represents the tacit knowledge the worker has developed over time, within the decision-
making environment" (Nemati, Steiger et al. 2002). DSS can further enhance the explication
of knowledge by "eliciting one or more what-if cases, representing areas the knowledge
worker would like to investigate" (Nemati, Steiger et al. 2002). In effect, the tacit knowledge
of historical decisions is transformed into explicit form, to be shared and leveraged for
improved decision making. Once this knowledge has been transformed and stored, it can be
leveraged by making it available to others when and where they need it. (Nemati, Steiger et
al. 2002) suggests that "explicit knowledge stored in the form of instances of a mathematical
model (what-if cases) can be leveraged via deductive and/or inductive model analysis
systems". Model-specific knowledge is applied to a single instance of a model, addressing
such questions as "why is this the solution?," "why do the solutions to two model instances
differ so much?". DSS can also help workers to learn, i.e. the process of converting explicit
knowledge to implicit knowledge. Known as internalisation, this process involves the
"identifying bodies of knowledge relevant to the particular user's needs" (Warkentin,
International Letters of Social and Humanistic Sciences Vol. 14 81

Sugumaran et al. 2001). It involves extracting knowledge and filtering it to match a particular
problem against the body of knowledge. Internalising explicit and/or new knowledge may
arise through a decisionmaker modifying his/her internal mental model that is used as his/her
performance guide for a specified situation (Nemati, Steiger et al. 2002).
2. KM PROCESSES
We earlier defined knowledge management as performing the activities involved in
discovering, capturing, sharing, and applying knowledge so as to enhance, a cost-effective
fashion, the impact of knowledge on the unit’s goal achievement. Thus, knowledge
management relies on four main kinds of KM processes. As shown in Figure 2, these include
the processes through which knowledge is discovered or captured. It also includes the
processes through which this knowledge is shared and applied. These four KM processes are
supported by a set of seven KM sub-processes, as shown above with one Sub-process -
socialization - supporting two KM processes (discovery and sharing). Of the seven KM sub-
processes, four are based on Nonaka (1994). Focusing on the ways in which knowledge is
converted through the interaction between tacit and explicit knowledge, Nonaka identified
four ways of managing knowledge:
Figure 1. KM processes (Jihene Chebbi Ghannay and Zeineb Ben Ammar Mamlouk, 2012).
2. 1. The Knowledge Management Processes Cycle
Figure 2 is a process cycle model of KM. Such cycle models provide a useful way to
organize one’s thinking about KM processes. There have been numerous KM processes cycle
models that describe the relationships of the key processes of KM, ranging from Davenport
and Prusak’s (2000) 3-stage model (“Generate, Codify/Coordinate, Transfer”) to Ward and
Aurum’s (2004) 7-stage (“Create, Acquire, Identify, Adapt, Organize, Distribute, Apply”).
The process cycle model of Fig. 2 is particularly valuable in that it uses the generally
accepted terminology of KM and makes use of alternative paths in order to make important
distinctions. The various activities listed as bullet-points under some of the major phases are
82 Volume 14

meant to be illustrative and not necessarily definitional. The model of Fig. 2 shows that the
initiation of the KM cycle involves either the creation or the acquisition of knowledge by an
organization. Knowledge creation involves developing new knowledge or replacing existing
knowledge with new content (Nonaka, 1994). The focus of this is usually on knowledge
creation inside the boundary of the firm or in conjunction with partners. The four bullet
points under “Creation” refer to Nonaka’s (1994) four modes of knowledge creation –
socialization (the conversion of tacit knowledge to new tacit knowledge through social
interactions and shared experiences), combination (creating new explicit knowledge by
merging, categorizing, and synthesizing existing explicit knowledge), externalization
(converting tacit knowledge to new explicit knowledge) and internalization (the creation of
new tacit knowledge from explicit knowledge). Illustrative of these four modes respectively
are apprenticeships, literature survey reports, “lessons learned” repositories and individual or
group learning through discussions. In contrast to knowledge creation, knowledge acquisition
involves the search for, recognition of, and assimilation of potentially valuable knowledge,
often from outside the organization (Huber, 1991).
The bullet points under “Acquisition” illustrate some processes for acquiring
knowledge from external sources – searching (as on the Internet) (Menon and Pfeffer, 2003),
sourcing (selecting the source to use) (King and Lekse, 2006) and grafting (adding an
individual who possesses desired knowledge to the organization) (Huber, 1991). After new
knowledge is created or acquired, KM mechanisms should be in place to prepare it to be
entered into the organization’s memory in a manner that maximizes its impact and longterm
reusability. Knowledge refinement refers to the processes and mechanisms that are used to
select, filter, purify and optimize knowledge for inclusion in various storage media.Under
“Refinement” in the figure, the bullet points suggest that tacit, or implicit, knowledge must be
explicated, codified, organized into an appropriate format and evaluated according to a set of
criteria for inclusion into the organization’s formal memory. Of course, explicit knowledge
needs only to be formatted, evaluated, and selected. Of the various steps that are involved in
doing so, “culling” refers to identifying the most significant exemplars in an emerging
collection; “organizing” refers to identifying recurrent themes and linking individual
knowledge items to the themes and “distilling” is creating a synopsis or set of pointers
(McDonald and Ackerman, 1997).
Organizational memory includes knowledge stored in the minds of organizational
participants, that held in electronic repositories, that which has been acquired and retained by
groups or teams and that which is embedded in the business’s processes, products or services
and its relationships with customers, partners and suppliers (Cross and Baird, 2000). As
shown in the figure, in order for knowledge to have wide organizational impact, it usually
must be either transferred or shared. Transfer and sharing may be conceptualized as two ends
of a continuum. Transfer involves the focused and purposeful communication of knowledge
from a sender to a known receiver (King, 2006a). Sharing is less-focused dissemination, such
as through a repository, to people who are often unknown to the contributor (King, 2006).
Many of the points on the hypothetical continuum involve some combination of the two
processes and both processes may involve individuals, groups or organizations as either
senders or receivers, or both. Once knowledge is transferred to, or shared with, others, it may
be utilized through elaboration (the development of different interpretations), infusion (the
identification of underlying issues), and thoroughness (the development of multiple
understandings by different individuals or groups) (King and Ko, 2001) in order to be helpful
in facilitating innovation, collective learning, individual learning, and/or collaborative
problem solving (King, 2005). It may also be embedded in the practices, systems, products
International Letters of Social and Humanistic Sciences Vol. 14 83

and relationships of the organization through the creation of knowledge-intensive
organizational capabilities (Levitt and March, 1988).
2. 2. Organizational Learning
There are various ways to conceptualize the relationship between knowledge
management and organizational learning. Easterby-Smith and Lyles (2003) consider OL to
focus on the process, and KM to focus on the content, of the knowledge that an organization
acquires, creates, processes and eventually uses.Another way to conceptualize the
relationship between the two areas is to view OL as the goal of KM. By motivating the
creation, dissemination and application of knowledge, KM initiatives pay off by helping the
organization embed knowledge into organizational processes so that it can continuously
improve its practices and behaviors and pursue the achievement of its goals. From this
perspective, organizational learning is one of the important ways in which the organization
can sustainably improve its utilization of knowledge. Indeed, Dixon (1994) , in describing an
“organizational learning cycle,” suggested that “accumulated knowledge… is of less
significance than the processes needed to continuously revise or create knowledge” (p. 6).
These processes are closely related to the notion of “continuous improvement” through which
an organization continuously identifies, implements and institutionalizes improvements. The
improvements are embedded in the organization through routines that may be written
policies, prescribed machine settings, quality control limits or “best practices” for dealing
with frequently occurring circumstances.
2. 3. The Basics of Knowledge Management and Organizational Learning Knowledge
Knowledge is often defined as a “justified personal belief”. There are many taxonomies
that specify various kinds of knowledge. The most fundamental distinction is between “tacit”
and “explicit” knowledge. Tacit knowledge inhabits the minds of people and is (depending on
one’s interpretation of Polanyi’s (1966) definition) either impossible, or difficult, to
articulate. Most knowledge is initially tacit in nature; it is laboriously developed over a long
period of time through trial and error, and it is underutilized because “the organization does
not know what it knows” (O’Dell and Grayson, 1998, p. 154). Some knowledge is embedded
in business processes, activities, and relationships that have been created over time through
the implementation of a continuing series of improvements. Explicit knowledge exists in the
form of words, sentences, documents, organized data, computer programs and in other
explicit forms. If one accepts the useful “difficult-to-articulate” concept of tacit knowledge, a
fundamental problem of KM is to explicate tacit knowledge and then to make it available for
use by others. One can also distinguish among “know what,” “know how” and “know why”
levels of knowledge. “Know what,” knowledge specifies what action to take when one is
presented with a set of stimuli. For instance, a salesperson who has been trained to know
which product is best suited for various situations has a “know-what” level of knowledge.
The next higher level of knowledge is “know-how” – i.e., knowing how to decide on an
appropriate response to a stimulus. Such knowledge is required when the simple
programmable relationships between stimuli and responses, which are the essence of “know-
what” knowledge, are inadequate. This might be the case, for instance, when there is
considerable “noise” in symptomatic information so that the direct link between symptoms
and a medical diagnosis is uncertain. “Know how”-type knowledge permits a professional to
determine which treatment or action is best, even in the presence of significant noise. The
84 Volume 14

highest level of knowledge is “know-why” knowledge. At this level, an individual has a deep
understanding of causal relationships, interactive effects and the uncertainty levels associated
with observed stimuli or symptoms. This will usually involve an understanding of underlying
theory and/or a range of experience that includes many instances of anomalies, interaction
effects, and exceptions to the norms and conventional wisdom of an area.
2. 4. Knowledge Management Systems
Knowledge management systems (KMS) are applications of the organization’s
computer-based communications and information systems (CIS) to support the various KM
processes. They are typically not technologically distinct from the CIS, but involve databases,
such as “lessons learned” repositories, and directories and networks, such as those designed
to put organizational participants in contact with recognized experts in a variety of topic
areas. A significant difference between many knowledge management systems and the
organization’s CIS is that the KMS may be less automated in that they may require human
activity in their operation. While information systems typically require that humans make
choices in the design phase and then operate automatically, KMS sometimes involve human
participation in the operation phase. For instance, when a sales database is designed, people
must decide on its content and structure; in its operational phase, it works automatically.
When a “lessons learned” knowledge repository is created, people must make all of the same
design choices, but they must also participate in its operational phase since each knowledge
unit that is submitted for inclusion is unique and must be assessed for its relevance and
important.
2. 5. e-Knowledge Networks for Business Improvement
We will discuss one long-term alliance, suggested by Warkentin (Warkentin,
Sugumaran et al. 2001), as a trend likely to develop from implementing strategic e-
knowledge networks in the context of supply chain. The supply chain process involves
organisations acquiring resources and providing goods or services, (Johnson, Scholes 1999).
Progressive supply chain management aims to improve the co-ordination "across the supply
chain to create value for customers, while increasing the profitability of every link in the
chain" (Warkentin, Sugumaran et al. 2001). It is this co-ordination aspect that addresses the
role of shared knowledge, enabling the analysis and management of all supply change
activities. In other words according to Choi et al. (Choi, Budny et al. 2004) the supply chain
involving knowledge is referred to as knowledge supply chain and in this context they define
knowledge as technologies, inventions and know-how that helps businesses bring products to
markets. The material flow is the physical flow of material and the knowledge flow is like the
flow of technique that connects the parts together. Figure 1 illustrates a material flow in a
typical supply chain. It shows how material moves from supplier to customers’ and at every
stage a value is added to the material, whilst, a network generates value not just through
goods, services and revenue, but also through knowledge. Knowledge becomes a medium of
exchange in its own right, with success dependent on building a rich web of trusted
relationships. The supply chain network proposed by Warkentin (Warkentin, Sugumaran et
al. 2001) is extended to emphasise the creation of a value network for a complex e-business
environment. In support of this trend towards e-networks, additional focus has been given to
the implications on the value chain. Verna (Verna 2000b) states "the traditional view of value
chain is outdated by the new enterprise model of the value network".Before the introduction
of the Internet, the traditional view of the supply chain was that of inefficient communication
International Letters of Social and Humanistic Sciences Vol. 14 85

and allocation. Information flowed in a linear fashion, either upstream or downstream. In
addition, a further drawback was the lack of connection to one's customers, as organisations
were forced to communicate through wholesalers, distributors and retailers. Dispersion of
information beyond one link in the supply chain was inhibited through a lack of formal
relationships. Furthermore, the "information flow through linkages was constrained due to a
lack of standard data representation schemes, therefore, the sharing of information beyond
immediate supply chain partners was impossible" (Warkentin, Sugumaran et al. 2001).
Figure 2. Knowledge management processes in the corporate(Joseph M. Firestone and Mark W.
McElroy, 2005).
The traditional view of knowledge was to hoard it and If organisations were to share
this valuable information, a competitive edge would be lost (Verna 2000b). However, the
consensus among new economy organisations is to provide an open environment for the
sharing of information. Organisations are encouraged to work "in close co-ordination to
optimise the flow in the entire supply chain" (Warkentin, Sugumaran et al. 2001). The
concept of the e-supply chain proposes a new relationship between suppliers, partners and
customers as well as integration of processes, information systems and interorganisational
problem solving (Manthou, Vlachopoulou et al. 2004). The e-supply chain is the backbone of
a virtual network, linking each participant as one cohesive unit.
The chain comprises a series of value-added stages, starting with the supplier and
ending with the consumer. The focus of the e-supply chain is on the bi-directional flow of
information, each stage is a supplier to its adjacent downstream stage and a customer to its
86 Volume 14

upstream stage. Each participant is therefore able to assume many roles within the supply
chain, but the ultimate relationship comes down to a supplier and a customer role.
3. KM AND CI TO ACHIEVE COMPETITIVE ADVANTAGE
3. 1. What is meant by competitive advantage?
Concept of competitive advantage has a long tradition in the strategic management
literature. Ansoff (1965) defined it thusly characteristics of unique opportunities within the
field defined by the product-market scope and the growth vector. This is the competitive
advantage. It seeks to identify particular properties of individual product markets which will
give the firm a strong competitive position”. NNN South (1981) defined competitive
advantage as the “philosophy of choosing only those competitive arenas where victories are
clearly achievable”.
Porter (1985) states "competitive advantage grows fundamentally out of value a firm is
able to create for its buyers that exceeds the firm's cost of creating it." He argued that a firm’s
ability to outperform its competitors lay in its ability to translate its competitive strategy into
a competitive advantage. Competitive strategy entails positioning the firm favorably in an
industry relative to competitors.
He confirmed that there are, in general, only two possible competitive advantages a
firm may possess, a cost advantage or a differentiation advantage. Others, particularly
proponents of the resource-based view of the firm (Barney, 1991; Conner, 1991), have
extended the definition to include a wider range of possible advantages such as physical
capital (Williamson, 1975), human capital (Becker, 1964), technological opportunities and
learning (Teece, 1980; 1982; 1986), and organizational capital (Tomer, 1987).
3. 2. Synergy between CI and KM to obtain competitive advantage
Knowledge management (KM) is the process through which organizational
performance is improved through better management of corporate knowledge. Its goal is to
improve the management of internal knowledge processes so that all information required for
corporate decisions can be made available and efficiently used. Competitive intelligence (CI)
is a process for gathering usable knowledge about the external business environment and
turning it into the intelligence required for tactical or strategic decisions. Both KM and CI
systems are designed to enhance the information resources of an enterprise, but often target
different information types and sources.
While CI is concerned with gathering information from the external environment to
enable the company to gain competitive advantage (Williams, 2002), most investigation into
KM has focused on capturing the knowledge stored within the minds of individual employees
(Nidumolu, Subramani, & Aldrich, 2001). Bagshaw (2000), Johnson (2000), Rubenfeld
(2001), and Williams (2002) all focus on the use of KM for collecting, managing, and sharing
internally generated knowledge.
The combination of effective KM and appropriate CI provide the right mix of the right
information to the right decision maker at the right time. Certainly, these two fields are
starting to blend into the same melting pot. However, each field has some unique qualities
that differentiate it from the other.
International Letters of Social and Humanistic Sciences Vol. 14 87

3. 3. The transition from the industrial to the knowledge-based thinking
One of the most industrialized countries of the world that we still call it, is that the No
other industry. We are witnessing a rapid transition from an industrial society to a knowledge
society. Society Based on the increasing importance of knowledge as the fourth factor of
production is based. Many of All products and services, research and development costs are
exorbitant. Yet Production costs are much lower. Employ a large number of consultants in the
form Investment advisory services are made by the company, the cost of waste Companies to
a minimum. Investing in the knowledge base, as well as Consultants have prepared
concurrently and that obviously cost a lot to create the but it Than their actual results to
employer becomes cheaper. In fact, we still speak of the industrialized countries, much of our
thinking is now, among the Industrial production is still based on the concepts of the early
twentieth century and perhaps Nineteenth returns, but today the knowledge and the capacity
to manage, create, and publish it, the main purpose Successful companies. This can be done
with concepts like brand management, marketing Directly to customers and ... Interpreted.
But this is only a visual transition from the industrial market Market knowledge is another
characteristic of the economy is evolving (Yosefi et al, 2011).
3. 4. The emergence of the theory of competitive advantage
The evolution of the concept of competitiveness, is a school science project. In this
section Along with their concepts and theories of the respective schools and purposes will be
provided. It is the first school classics. The advantage of the classical school of international
trade. Will be considered by economists to be the only point in the economic activity of
Terms of trade are considered two different geographical areas. In this section On the
evolution of economic theory, economists seek to prove the competitive nature of the
variables and criteria are. The most important element of classical thought, if minimum
government intervention in economic affairs, especially trade International and motivated
individual to achieve the balance of the public. Provide notions advantage Absolute (Smith)
and comparative advantage (Ricardo), which was based on the cost of production,
concomitant with Industrial Revolution, England had a positive effect on development. Smith
's theory An absolute boon for space - based free trade and lower manufacturing costs outside
of Was the basis for the international division of labor(Daneshfard et al,2010).
4. METHODOLOGY
The overall objective of this study was to investigate the effect of knowledge
management on competitive advantage in firms and Organizations in which the subject and
purpose of the study is descriptive – correlation Is used. Data in this survey is based on
questionnaires Literature adjusted for its validity in terms of academics and experts use To
check the reliability of a sample of n = 30 questionnaires distributed among the population
SPSS software using Cronbach's alpha is measured. The Inventory Includes 22 items that 8
questions related to the independent variables (knowledge management) and for each One of
the three dependent variables, five questions were designed.
88 Volume 14

4. 1. Research hypotheses
Major and minor premises of this research can be stated as follows:
1. There is a significant relationship between knowledge management and competitive
advantage.
Minor hypotheses are as follows:
1.1. There is a Significant relationship between knowledge management and organizational
performance.
1.2. There is a Significant relationship between knowledge management and customer-
oriented.
1.3. There is a significant relationship between knowledge management and product
innovation.
4. 2. Data Analysis
After reviewing the data from the questionnaires in order to test each of the first and
second Primary and secondary research hypotheses, drawing tables contain the results of
sampling size variables Tion was jointly independent of assumptions associated with the use
of tables and tests D. Summers correlation, the correlation coefficient of the independent
variable on the dependent was obtained as follows:
In the first step of the analysis was to examine the reliability of the sample
The initial questionnaire was distributed and collected the questionnaire Cronbach's alpha for
variables: chvariable the calculated results showed good reliability of the questionnaire.
Cronbach's alpha is calculated by the following:
Table 1. Computing Cronbach alpha.
Scale
Cronbach's alpha
Corrected correlation
organizational performance
0/854
0/385
customer satisfaction
0/741
0/750
innovation
0/731
0/758
Test results showed that the Pearson correlation coefficient between knowledge
management as the independent variable and the dependent variable organizational
performance as equals 78 %. Indicating a direct correlation between the two variables, and
there is a significant relationship between the variables. Pearson test of knowledge
management and innovation process:
Table 2. The first hypothesis test.
N
Sig
r
115
0/000
0/78
International Letters of Social and Humanistic Sciences Vol. 14 89

Test results showed that the Pearson correlation coefficient between management
Knowledge as independent variables and customer satisfaction as the dependent variable
equals 72 %. Indicating a direct correlation between the two variables, and there is a
significant relationship between the variables.
Pearson correlation test results and customer knowledge management:
Table 3. The second hypothesis test.

N
Sig
r
115
0/000
0/72
Test results showed that the Pearson correlation coefficient between management
Knowledge and innovation as an independent variable as the dependent variable equals
Indicating a direct correlation between the two variables, and there is a significant
relationship between the variables. Pearson test of knowledge management and product
innovation:
Table 4. The third hypothesis test.
N
Sig
r
115
0/000
0/62
5. DISCUSSION AND CONCLUSIONS
Knowledge management as a key tool for the management of the new century,
systematic and strategic Defined processes, acquisition, transfer and application of
knowledge by individuals Organizations that promotes innovation, productivity and
competitiveness and promote Moreover, contribute to problem solving, decision making,
strategic planning, dynamiclearning Prevent mental decline as assets increase awareness of
the organization and flexibility the increase.
Knowledge management as a mechanism to enable systematic organizing of the
Knowledge will lead to better use of resources. Necessary when using this mechanism more
It is obvious that organizations are aware of the effects and results of its use. Hence it in this
paper we investigate the use of knowledge management in organizations' attempts. To so that
a comprehensive analysis of the impact of knowledge management must be comprehensive
view All parts of the organization, it requires taking into account the effects on the process of
knowledge management Different parts of the organization.
The current study The first exploratory study included a review of the literature and
conducting interviews to formulate hypotheses We then proceed to evaluate the hypotheses
investigated by carrying out the survey. Analysis results Confirm the hypothesis. The
research results indicate that knowledge management can include the subset of competitive
90 Volume 14

advantage and customer satisfaction, organizational performance, and organizational
innovation can make a significant impact.
References
[1] Adamides E. D., N. Karacapilidis, Technovation  (20006) 50-56.
[2] Alavi M., D.E. Leidner, MIS Quarterly N (2001) -.
[3] Aranda D. A., Molina-Fernandez L. M., Industrial management & Data systems ()
(2002) .
[4] Bagshaw M., Industrial and Commercial Training 32 (2000) 179-183.
[5] Daneshfard, Allah Karam, Zakrei Mohammad, Effects of Knowledge Management
Consulting engineers to strengthen the competitiveness of enterprises. (2010)
Quarterly Rahbord yas.
[6] Deeds D. L., C. Hill, Journal of Business Venturing 11 (1996) 41-55.
[7] Jihene Chebbi Ghannay, Zeineb Ben Ammar Mamlouk, Synergy Between Competitive
Intelligence and Knowledge Management - a key for Competitive Advantage, (2012),
Journal of Intelligence Studies in Business.
[8] Motwani J., Gopalakrishna P., Subramanian R., “ Source of knowledge acquisition by
U.S. managers : An empirical analysis “, (2005), Idea Group Publishing, P. 16-19.
[9] Newman B., Conard D., The knowledge Management Forume. (1999).
Available at: www.km-forume.org
[10] Scarbrough H., International Journal of Manpower (5) (2003) 514.
[11] Shelfer K., "The Intersection of Knowledge Management and Competitive Intelligence:
Smartcards and Electronic Commerce." Knowledge Management: (2004), Lesson
Learned: What Works and What Doesn’t. Eds. Michael E. D. Koenig and T. Kanti
Srikantaiah. New Jersey: Information Today, Inc, 419-442
[12] Wong K. Y., Industrial management & data system 105(3) (2005) 261-265.
[13] Yamin S., Gunasekaran A., Mavonda F. T., Technovation 19(8) (1999) 507-518.
[14] Yosefi Ehsan, Fizi Jaafar, Mohammad Soliamani, Evaluation of the impact of
knowledge management on innovation (Among managers and employees of technology
companies based in the University of Science and Technology Park, Quarterly ingenuity
in Humanities, 3 (2011).
( Received 25 October 2013; accepted 29 October 2013 )

International Letters of Social and Humanistic Sciences Vol. 14 91