Knowledge Management for Competitive Advantage in Kenya.

Abstract

The two organisations in this study were chosen to investigate the relation between knowledge management and competitive advantage. Safaricom has knowledge management systems while organisation B has no knowledge management systems but has a task force which has a wealth of experience since the organisation was one of the first telecommunication companies to be established in Kenya. These two organizations were compared all factors held constant to find out if knowledge management can lead to competitive advantage. Secondary data was also used which determined that safaricom had a competitive edge over Organization B and the purpose of this study was to establish if knowledge management is a contributor of this fact. The target population was all the employees in the two organizations. Since the population was all the employees in the organization stratified random sampling was used to get the sample size the strata were the two organisations and a sample of employees was randomly selected in each organisation. Quantitative research technique was applied and instruments such as questionnaires were used to collect data. The Statistical Package for the Social Sciences was also used to process and analyse data. The key findings proved that knowledge management is key in maintaining competitive advantage.

Full text

International Journal of Research Publication and Reviews, Vol 5, no 5, pp 11728-11738 May 2024
International Journal of Research Publication and Reviews
Journal homepage: www.ijrpr.com ISSN 2582-7421
Knowledge Management for Competitive Advantage in Kenya: A
Comparative Study of Two Telecommunication Companies
¹David Ochieng Okoth, ²Mwende Mutuku, ³ Emmanuel Awuor
1. Regional Coordinator-Coast Region, The Management University of Africa, Nairobi, Kenya.
2. Human Resources Office, Kenya Power and Lighting Company Limited, Nairobi, Kenya
3 Professor (Associate), The Management University of Africa, Nairobi, Kenya.
Email: dokoth1@gmail.com
ABSTRACT
The two organizations in this study were chosen to investigate the relation between knowledge management and competitive advantage. Safaricom has knowledge
management systems while organization B has no knowledge management systems but has a task force which has a wealth of experience since the organization
was one of the first telecommunication companies to be established in Kenya. These two organizations were compared all factors held constant to find out if
knowledge management can lead to competitive advantage. Secondary data was also used which determined that safaricom had a competitive edge over
Organization B and the purpose of this study was to establish if knowledge management is a contributor of this fact. The target population was all the employees
in the two organizations. Since the population was all the employees in the organization stratified random sampling was used to get the sample size the strata were
the two organizations and a sample of employees was randomly selected in each organization. Quantitative research technique was applied and instruments such as
questionnaires were used to collect data. The Statistical Package for the Social Sciences was also used to process and analyze data. The key findings proved that
knowledge management is key in maintaining competitive advantage.
Key words: Competitive Advantage, Comparative study, Knowledge Management, Telecommunications
1. Background of the Study
Knowledge management refers to the process of capturing, developing, storing or sharing wisdom for effective use in organizations. There is a difference
between knowledge and information. On one hand information is raw data or facts and it forms the basis of knowledge but on the other hand knowledge
is concise and appropriate use of information using analysis and experience to derive meaning from it (Koenig, 2012). The key is learning how to create,
store and utilize knowledge and not just acquire and store information.
Knowledge management in not a new field of study. In fact, it is a field that began in the early1980s. However, research in this field experienced a drastic
decline from 30% overall academic research publications from the year 2002 to only 10% by the year 2009 (Serenko, Bontis, Booker, Sadeddin, &
Hardie, 2010). Knowledge management has two main aspects, tangible knowledge and explicit. Tangible knowledge is the skills that people possess
which is hard to be stored and are innate while explicit knowledge is the knowledge that can be stored in data banks. Knowledge Management has become
popular especially with scholars such as Drucker (1999), arguing that knowledge has replaced tangible assets as the principle driver of economic growth.
The knowledge economy explains that knowledge is the most valuable organizational resource capable of creating sustainable competitive advantage
(Grant, 2013).
Globally there is a paradigm shift towards Knowledge management because it seeks to produce a capability which improves organizations performance:
defined by processes and infrastructure (Gold, Malhotra, & Segars, 2001). In the past such knowledge was passed down from generation to generation
through formal apprenticeship especially for professions such as law. Information was also stored in corporate libraries and knowledge repositories but
these were just hubs of information which lay dormant and sometimes would not be accessed in year. This is not knowledge management but rather
information storing. In order for organizations to profit of the knowledge they have they must access it and make it work for them. This is the core value
of having functional knowledge management systems.
In Africa, knowledge has been passed down from generation to generation using multiple methods which include oral literature, apprenticeship among
others. However, with the introduction of formal education some of these practices have been lost. Knowledge management can be seen as an avenue to
unite both the traditional African way of passing Knowledge from one generation to the next as well as the modern way which incorporates technological
systems to make the process fast and more efficient hence avoiding reinventing the wheel (Masolo, 2003). Numerous authors contend that there are
dissimilarities in the way people, especially those from different cultural backgrounds, interpret or accept knowledge sharing. Ribiere and Sitar (2002),

International Journal of Research Publication and Reviews, Vol 5, no 5, pp 11728-11738 May 2024 11729
argue that, as a result of their educational systems, western cultures do not encourage a social exemplar of knowledge sharing. Yeh and Ma (2005) concur,
arguing that western cultures are more likely to embrace values of self‐determination, independence and the attainment of personal interest.
In contrast, Nadene, Neels and Jaco,(2007) argues that Asian cultures nurture a sharing and teamwork environment or approach to activities. Very little
is mentioned in literature about knowledge sharing in African cultures and/or African organizations. Specifically, not much is known regarding knowledge
sharing in settings where the roles of dominance of one culture over another are reversed or neutralized, either by force or law, or by natural progression.
With this in mind this study is critical in addressing this matter.
In Kenya the case is no different. This study focuses on the telecommunication sector in Kenya more so organization which handles mobile services,
fixed line and broadband services. The telecommunication sector in Kenya is a fast growing and ever expanding sector which makes competitive
advantage key to be successful in this sector. For this reason, this sector makes a great population for a study in knowledge management. This study
focused on comparing two telecommunication organizations namely, Safaricom and Telecom Organization B. The objectives of the study were: To
investigate if knowledge management generation leads to competitive advantage between Safaricom and Organization B in Kenya; To analyze if access
to knowledge management tools results in competitive advantage between Safaricom and Organization B in Kenya; To find out whether embedding in
knowledge management leads to competitive advantage between Safaricom and Organization B in Kenya.
2. Literature Review
Theoretical Literature review
The theoretical approaches discussed include the contingency theory, the actor network theory and organizational learning theory.
Vroom and Yetton’s decision participation contingency theory
The central focus of this theory is to assess how the nature of a group, leader, and situation determine the degree to which the group is to be included in
the decision-making process. This is accomplished by a flowchart-style decision making procedure that arrives at a style of decision-making. These styles
are autocratic, consultative, and group. The autocratic essentially is a dictator, taking her or his cue from Transactional Leadership methods, which, in
essence say that the leader tells the group, "obey". The consultative approach has the leader going to the group for suggestions on how to carry out tasks.
The "group" method of decision making is the most democratic, where the group ultimately makes the decision (Vroom, Yetton, & Jago, 1988).
The theory states that there can be many styles of leadership and no one type fits all situations, thus making this a Contingency Theory. A leader sizes up
a situation, assesses the situation facing the group, determines how much support the group will give to the effort, and then effect a style of leading. There
is a mechanical process to do this involving seven questions and decision points. The underlying assumption of the Vroom-Yetton-Jago Decision Models
is that no one leadership style or decision making process fits all situations. By analyzing the situation and evaluating the problem based on time, team
buy-in, and decision quality, a conclusion about which style best fits the situation can be made. The model defines a very logical approach to which style
to adopt and is useful for managers and leaders who are trying to balance the benefits of participative management with the need to make decisions
effectively which leads to competitive advantage (Vroom, Yetton, & Jago, 1988).
This theory is the main theory featured in this research paper especially to come up with the five assumptions expounded on in this chapter. According
to this model, the effectiveness of a decision procedure depends upon a number of aspects of the situation which include the importance of the decision
quality and acceptance, the amount of relevant information possessed by the leader and subordinates, the likelihood that subordinates will accept an
autocratic decision or cooperate in trying to make a good decision if allowed to participate, the amount of disagreement among subordinates with respect
to their preferred alternatives (Grany, 2014). This theory works well with knowledge management since the decision making process is determined by
the available knowledge possess by the leader as well as the subordinates and proper use of that knowledge can lead to competitive advantage.
Knowledge Management System Modelling Matrix
Proper Knowledge management falls into one of the four domains of this knowledge matrix which is a collection of various theories as suggested by
Aboubakr and Woodman, (2007). These domains include: Personal KMS models (Epistemology-Actor) focus on knowledge of the individual, in
particular tacit knowledge. In this domain modelers attempt at representing KMS as cognitive maps of each individual’s knowledge – who knows what?
There is no particular technology that is used for this domain, but it is rather based on cognition; Social KMS models (Ontology-Actor), for example
Wenger (1998), focus on knowledge of the group as a society, in particular knowledge flow and relationships. In this domain modelers merely refer to
communities of practice as the representation of KMS. IT has limited use in this domain and the main technique used for KM is story telling; Codified
KMS models (Epistemology-Analytical) e.g. Nonaka and Takeuchi (1995), focus on knowledge of the individual, in particular explicit knowledge or
knowledge that could be codified. In this domain modelers attempt at representing KMS as expert systems. IT has a wide usage in this domain especially
artificial intelligence; Taxonomy KMS models (Ontology-Analytical) e.g. Wiig (1997), focus on knowledge of the Group as a hierarchy, in particular
knowledge taxonomies. In this domain modelers refer to Intranets as an adequate representation of KMS. IT has a wide usage in this domain such as with
neural networks.

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Table 1: KMS Modelling Matrix.
Personal
Social
Tacit Knowledge
Relationships
Actor
Cognitive Maps
Communities of Practice
Cognition
Story Telling
Codified
Hierarchical
Analytical
Explicit Knowledge
Taxonomy
Expert System
Intranet
AI
Neural Networks
Source: Electronic Journal of Knowledge Management (2007)
Organizational Learning Theory
Organizational learning (OL), according to Argrys & Schon (1996) is a product of organizational inquiry. This means that whenever expected outcome
differs from actual outcome, an individual (or group) will engage in inquiry to understand and, if necessary, solve this inconsistency. In the process of
organizational inquiry, the individual will interact with other members of the organization and learning will take place. Learning is therefore a direct
product of this interaction.
Argrys and Schon emphasize that this interaction often goes well beyond defined organizational rules and procedures. Their approach to organizational
learning theory is based on the understanding of two (often conflicting) modes of operation:
Espoused theory: This refers to the formalized part of the organization. Every firm will tend to have various instructions regarding the way employees
should conduct themselves in order to carry out their jobs (like problem solving). These instructions are often specific and narrow in focus, confining the
individual to a set path. An example of espoused theory might be "if the computer does not work, try rebooting it and then contact the IT department."
Organizational Theory: This is the actual way things are done. Individuals will rarely follow espoused theory and will rely on interaction and
brainstorming to solve a problem. Theory in use refers to the loose, flowing, and social way that employees solve problems and learn. An example of this
might be the way someone actually solves a problem with their computer by troubleshooting solutions, researching on forums, asking co-workers for
opinions, among other.
The fact that there is a mismatch between these two approaches is potentially problematic if the company enforces its espoused theory. In order to create
an environment conducive to learning, firms are encouraged to accept theory in use, and make it easy for the individual to in teract with his working
environment in an undefined and unstructured way. Essentially they should provide the right environment for organizational inquiry to take place,
unconstrained by formal procedures (Argrys & Schon, 1996).
Levitt and James (1996) expand further on the dynamics of organizational learning theory. Their view presents the organization’s routine-based, history
dependent, and target oriented. While lessons from history are stored in the organizational memory, the event itself is often lost. They note that past
lessons are captured by routines "in a way that makes the lessons, but not the history, accessible to organizations and organizational members." The
problem most organizations face is that it is usually better to have the event rather than the interpretation. However, this is often too costly (both financially
and time-wise) to be feasible. OL is transmitted through socialization, education, imitation and so on, and can change over time as a result of interpretations
of history (Levitt & James, 1996). Argrys and Schon (1996) identify three levels of learning which may be present in the organization.
Single loop learning: Consists of one feedback loop when strategy is modified in response to an unexpected result (error correction). E.g. when sales are
down, marketing managers inquire into the cause, and tweak the strategy to try to bring sales back on track. Double loop learning: Learning that results
in a change in theory-in-use. The values, strategies, and assumptions that govern action are changed to create a more efficient environment. In the above
example, managers might rethink the entire marketing or sales process so that there will be no (or fewer) such fluctuations in the future.
Deuterolearning: Learning about improving the learning system itself. This is composed of structural and behavioral components which determine how
learning takes place. Essentially deuterolearning is therefore learning how to learn. Effective learning must therefore include all three, continuously
improving the organization at all levels. However, while any organization will employ single loop learning, double loop and particularly deuterolearning
are a far greater challenge.
Knowledge management grows capability (Grant, 2013) is grounded in organizational learning (OL) theory where Knowledge Management can be
considered a change initiative designed to increase the organizational knowledge base (OKB) (Massingham & Diment, 2009). Knowledge Management
can improve organization learning and, therefore, increase the OKB. If people are learning, their knowledge is increasing. The OKB is the stock of
knowledge, which means its intangible assets, and increases should be reflected in higher market capitalization which leads to competitive advantage.

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Empirical Literature Review
For this theory to be applied five general assumptions concerning efficient knowledge management were identified. These theoretical assumptions are
based on the notion of knowledge sharing as a core element of knowledge management (Magnusson & Nilsson, 2011).
Knowledge Generation for competitive advantage
The notion of trust has long been a studied phenomenon with regards to its role in the context of business. As early as 1964, Simmel in (McAllister, 1995)
argued that trust is necessary if there is neither total knowledge nor total ignorance, and researchers have long sought an omnipotent and universal
definition of the term (Hwang & Burgers, 1997). Regardless of the fact that a number of researchers argue that the concept of trust and its effects on
business have not received the attention that it deserves (Porter, Lawler, & Hackman, 1975), there is a multitude of definitions and taxonomies covering
the subjects. On a general level the majority of definitions differentiate the content of trust to two diametrically divided sub-categories, namely competence
and goodwill (Hwang & Burgers, 1997).
These two aspects of trust reflect the complexity in the activity of trusting as encompassing an assessment of not only the ability of the receiver of trust
to fulfil his or her obligations, but also the willingness to achieve said obligations. These two dimensions of trust are further complemented by a
differentiation based on between what actor’s trust exists, namely inter-personal or inter-organizational (Rosseau, 1985) and in some cases even inter-
cultural or inter-national (Buckley & Casson, 1998). “Where there is trust there is the feeling that others will not take advantage of me” (Porter, Lawler
& Hackman, 1975, p.497).
As the quote above points out, the notion of trust is also closely related to the concept of opportunism by being an inhibitor of opportunistic behavior.
According to Barney (1999), opportunism can be defined as “...when a party to an exchange takes unfair advantage of other par ties to that exchange”.
(p.3) and argues that in order for opportunism to be held at bay, a new form of governance needs to be applied. This new form of governance (intermediate,
network or relational (Poppo & Zenger, 2002) governance) uncouples the traditional rigidity of organizational boundaries and opens up for the governance
of exchanges between organizations. In order for this form of governance to be successful, the level of opportunism needs to be controlled mainly through
the use of contracts and elaborate governance mechanisms (Barney, 1999). If elaborate contracts and governance mechanisms was all that was needed to
hinder opportunistic behavior in inter-firm collaborations all would be well. However, researchers such as Poppo & Zenger(2002), stipulate a somewhat
more complex relationship between the existence of opportunistic behavior and the use of contracts. The same researchers state that contracts do not
merely have the positive effect of making commitment explicit and provide customized approaches to handling exchanges, but they also have a side-
effect in acting as a motor for opportunistic behavior (Poppo & Zenger, 2002).
A number of researchers have dealt with the relationship between trust and complex contracts, and a split can be found between those that regard them
as substitutes and those that regard them as complementary (Poppo & Zenger, 2002). This research acknowledges the fact that contracts can function
both as structural constraints and affordances, but disagree with the notion that the two constructs exist on a single scale. The concept of trust would
most likely be irrelevant for further research if there was not a direct link between level of trust existing in a collaboration and the performance or outcome
of the collaboration which lead to competitive advantage. Poppo & Zenger (2002), Barney (1999) and Hansen (1995) argue that the level of trust in a
collaboration has direct effect on the competitive advantage of the collaboration and hence also the participating firms. This can partly be attributed to
the learning-effect that the network collaboration can foster (Chetty & Erikson, 2002).
When it comes to the link between trust and knowledge sharing, recently investigated the element of trust in virtual communities of practice (Ardichvilli,
Page, & Wentling, 2003). According to their findings various different kinds of trust need to be present for efficient knowledge sharing to be possible.
This is also supported by Politis in a more general study of knowledge transfer and its prerequisites and concerning the role of trust in KM and team
performance (Politis, 2003).
Access to Knowledge for competitive advantage
This assumption is better explained using the actor network theory (ANT). ANT is a theory concerned with the production of facts or knowledge (Callon,
2001). In particular, this methodology highlights the networks giving raise to, and sustaining, various forms of knowledge. No one has ever observed a
fact, theory or machine that could survive outside the networks that gave birth to them (Latour, 1997, p.248). From this perspective networks comprise
of interconnections between human and non-human act ants – that is, ‘documents devices and people’ (Latour, 1997). This simplifies the view of actors
acting in networks into a set of example descriptions of roles involved in knowledge sharing.
Process knowledge refers to knowledge of business processes. Knowledge Management Systems (KMS) support knowledge management activities by
integrating information and communication technologies. As an effective process management tool, workflow management systems (WfMS) allows a
business to analyze, stimulate, design, enact, control and monitor general business processes (Leamann & Altenhauber, 1994). In practice, workflow
participants possess different needs and types of authority when obtaining information about business processes, they represent different roles. The
definition of roles and the delivery of relevant and necessary documents to workers in order for them to complete their tasks in a workflow environment
have been addressed (Abecker, Bernardi, Maus, Sintek, & Wendel, 2000).
The role of Artificial Intelligence (AI) in knowledge management is by Tsui, Gardner and Staab (2000) states in their editorial of Knowledge based
Systems. There is a general consensus that Knowledge Engineering has a far more technical focus on knowledge, its representation, organization and
reasoning. KM is more aligned towards capturing, sharing and reusing knowledge in or among organizations. There is still no system that can converse

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with a human, should one nevertheless try to tackle the even larger problems in KM”? The answer to this question is that most commercial KM tools
available already comprise of some sort of AI technology, Bayesen reasoning, ontologies, data mining, intelligent agents.
Turner and Keegan (2000) described operational control processes in project based organizations. The project organization creates an interface between
its projects and its clients and noted two roles, broker and steward. They found these roles in almost all project based organizations and argue for their
respective importance regardless of project. The roles may be described as follows: The broker shall maintain the relationship with the client. This entails
the identification and attraction of new clients, a bid for and win work, a liaison with the client during the work and the delivery of the product.
Furthermore, he should ensure the satisfaction of the client and should win follow-up businesses. The role combines ambassador for the firm and resource
investigator for the client. The steward puts together the network of resources to deliver the project, ensuring the right people at the right time to ensure
that the right thing happens. It is the project manager’s role to manage the process. The role of the Steward is almost abstract, but an essential one,
complementing the complementing the Broker and Manager in the core three (Turner & Keegan, 2000).
Knowledge embedding for competitive advantage
One of the main influential factors on the successful knowledge sharing within organization is the existence of an organizational culture that supports the
effective sharing of knowledge (Magnusson & Nilsson, 2011). According to major studies on Knowledge Management or Organizational Learning,
culture is a key barrier to success in related initiatives. (The conference Board, 2000). According to Schein (Schein, 1992) organizational culture is
defined as “a pattern of shared basic assumptions that the group learned as it solved its problems of external adaptation and internal integration, that has
worked well enough to be considered valid and, therefore, to be taught to new members as the correct way to perceive, think, and feel in relation to those
problems” (p. 12). One aspect of an organizational culture is the knowledge culture. Knowledge culture is the totality of values and norms in an
organization that have been developed over time, are accepted by the organizational members and have an influence on the creation, sharing and usage
of knowledge (Schein, 1992).
In the epoch of the knowledge society which is characterized by a tremendous increase in the amount of available knowledge and information sources
and very short knowledge-lifecycles, the willingness of the organizational members to share knowledge becomes one of the most important aspects of
organizational culture (Schultze & Boland, 2000). Based on the findings of empirical studies it can be said, that the willingness to share knowledge, is
positively related to profitability and productivity and negatively to labor costs. Smith and MacKeen (2000) characterize a knowledge sharing culture by
the openness of the organizational members to share knowledge, to teach and to mentor colleagues by using a variety of different media like conversations,
meetings, data bases (Smith & McKeen, 2002).
Especially in knowledge based organizations the existence of a culture that encourages and values knowledge and knowledge sharing is of central
importance. The organizational culture defines the range of autonomy, trust and values which have a strong impact on the communication, the sharing of
knowledge and the innovativeness of an organization (Zyngier, 2006). Panhans (2004) states in her article about the way to a culture for cooperative
learning and working that lots of knowledge management initiatives fail due to the existing organizational culture. Knowledge sharing is directly related
to individual learning and co-operative working. The cultural prerequisites for co-operative learning are trust, open communication, self-confidence,
consciousness, the ability and possibility to think critically, leadership, the ability to solve conflicts, the ability to make decisions and the feeling of
togetherness (Panhans, 2004).
In the white paper on knowledge management by Koskiniemi (1998) it is stated that knowledge management is as much cultural as it is technological
and that a culture that does not foster and reward sharing of knowledge cannot expect technology to solve its knowledge challenges. Successful knowledge
management depends very much on the commitment of top-management. Koskiniemi (1998) of Buckman Labs says that Ninety percent of moving an
organization to success in knowledge sharing or learning is in having the right culture. If your people are not confident that they can or should
communicate freely, then all the best technology will be unable to pry knowledge out of them, or help them absorb knowledge. (The Conference Board
2000, p. 47). The American Productivity and Quality Centre (APQC) found in an empirical study conducted in 2000 out that however strong commitment
and approach to knowledge management are, the culture is stronger. Companies successful in promoting a strong knowledge-sharing culture do not try
to change their culture to fit their knowledge management approach. They build their knowledge management approach to fit their culture (The
Conference Board, 2000).
Knowledge sharing is tightly linked to a pre-existing core value of the organization. The organization introduces the approach, tools, and structures to
support knowledge sharing in a way that matches the overall style of the organization. Knowledge-sharing activities build on existing networks people
use in their daily work. Peers and immediate supervisors of those actively involved in sharing knowledge support, even exert, pressure to share. There is
an appropriate level of senior management support and involvement. (McDermott & O’Dell, 2000). Davenport (1998) identifies several factors of an
organizational culture that inhibit the successful transfer of knowledge within an organization. Deficits in trust, differences in cultures and language
habits, lack of time and meeting-opportunities, incentives for knowledge carriers, lack of capacity to absorb new knowledge, not invented here syndrome
and the intolerance towards mistakes and the need for help. Those deficiencies have to be identified and reduced by appropriate measures (Davenport &
Prusak, 1998).
Conceptual framework
Conceptual framework should demonstrate an understanding of what variable influences what.
Independent variable Dependent variable

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Figure 1: Conceptual Framework showing the relationship between the variables
Knowledge is a source of competitive advantage. This is grounded in the knowledge-based view of the firm’s (KBV) proposition that knowledge is the
firm’s most valuable resource (Grant, 2013). The KBV argues that knowledge is know is more important than the traditional sources of economic power
(Storey & Barnett, 2000), mainly because knowledge is embedded in products and services and this makes it difficult for competitors to copy. Knowledge
meets the criteria for competitive advantage found by the resource-based view of the firm (RBV), e.g. scarcity, durability (Grant, 2013). There is not one
right way to get people to share, but many different ways depending on the values and style of the organization. Organizations with a culture that supports
sharing knowledge have a visible link between sharing knowledge and solving practical business problems.
3. RESEARCH METHODOLOGY
The study applied ex post facto casual-comparative design. As explained by Gall, Borg, and Gall (2006), in this design, the researcher does not manipulate
the variables under study but instead, examines the variables in their existing condition (Olseen & George, 2004). Therefore, the researcher conducted
the study within the existing staff in the telecommunication organizations and the impact of knowledge management on the three aspects of competitive
advantage.
The telecommunication sector in Kenya has 13 companies however since this is a comparative study only two organizations were considered: the
competitive leader and another organization that does not have as much competitive advantage in the field. In these organizations all departments were
sampled but only employees working in the headquarters in Nairobi were sampled due to the researcher’s discretion. The target number of respondents
was 100 and 116 from the institutions namely Safaricom and Organization B respectively which was a total of 216 respondents.
Orodho and Kombo (2002) describe a sample as a finite and representative number of individuals of objects in the population to be studied. Since the
target population is diverse stratified random sampling was used. The strata were the two organizations of which 100 participants were randomly selected
in each floor of their organizations buildings. The companies this study focused on include Organization B and Safaricom who both deal with mobile
services, fixed line and broadband services. The headquarters of these organizations are based in Nairobi although most of them are national and
multinational organizations.
Data was collected from both primary and secondary sources. Questionnaires were used to collect the primary data that focused on knowledge
management and the five aspects of knowledge management discussed in empirical literature review. Secondary data on competitive advantage of the
two organizations was collected from organizations portfolios and other researches.
Regression analysis was used to identify which aspects of knowledge management influence competitive advantage and to what extent. This data was
presented in the form of tables in chapter four. These finding also highlighted key demographic issues such as age, gender, educational background and
employment history this data was presented as graphs in chapter four. Also correlation analysis was conducted to identify which was the most important
aspect of each of the five aspects of knowledge management namely knowledge generation, access, embedding, facilitation and transfer.
4. RESEARCH FINDINGS AND DISCUSSIONS
Knowledge Management for competitive Advantage
For both organizations a summary of the knowledge management aspects shows how each organization performed on each aspect on table 1.0.
Table 2.0: Summary of the five aspects of Knowledge Management
Knowledge Generation
Competitive Advantage
Knowledge access
Knowledge Embedding

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Group Statistics
Organization
N
Mean
Std. Deviation
Std. Error Mean
KMGen
Safaricom
30
2.2000
.66436
.12130
Organization B
30
2.7833
.71539
.13061
KMAccess
Safaricom
30
2.2000
.66436
.12130
Organization B
30
3.3667
1.06620
.19466
KMEmbedding
Safaricom
30
3.6000
.81368
.14856
Organization B
30
2.1000
.71197
.12999
In a scale of one to five (5 – strongly disagree and 1- strongly agree), it is clear from the table above that Safaricom (2.20) was slightly better at knowledge
generation than Organization B (2.78). This means that most of Safaricoms respondents believed that the organization was good at generation knowledge
while the respondents at Organization B did not strongly believe so but were almost neutral about it.
It is also clear from the table above that Safaricom (2.20) is better when it came to access of Knowledge in fact they incorporate the latest technology and
have knowledge management systems as compared to Organization B (3.37) respondents who disagree and believe they do not have access to knowledge.
It was interesting to note that Organization B (2.10) respondents feels that their organization encouraged them to continue with their education and they
received multiple training opportunities. On the other hand, Safaricom (3.60) respondents did not feel that they were given opportunities to train and they
were too busy to further their education. Although this is what the data showed it was interesting to note that Safaricom respondents had higher levels of
education than that of Organization B respondents. This was a key factor in the research since it showed that Organization B has quite exposed staff who
attend multiple trainings but since they do not have systems in place to share, store and access this knowledge at a later data this knowledge is never
properly managed and when a staff leaves they leave with all the knowledge they had.
Knowledge generation
When all the questions testing knowledge generation were analyzed using linear regression analysis it was found that how the both organizations generated
knowledge within the Safaricoms well as with their business partner had the most impact on knowledge generation. This is shown in table 2.0. These two
had the strongest variance as shown in the histogram below as figure 1.0.
Table 2.0: Knowledge Generation linear regression analysis
Coefficients
Model
Unstandardized
Coefficients
Standardized
Coefficients
T
Sig.
95.0% Confidence
Interval for B
Correlations
Collinearity
Statistics
B
Std. Error
Beta
Lower
Bound
Upper
Bound
Zero-
order
Partial
Part
Tolerance
VIF
1
(Constant)
1.130E-015
.000
.000
1.000
.000
.000
KM
generation(Ext)
1.810E-014
.000
.000
.000
1.000
.000
.000
.863
.000
.000
.012
82.013
KM
generation(Bus)
.500
.000
.711
32192170.798
.000
.500
.500
.889
1.000
.124
.030
33.092
KM generation(Int)
.500
.000
.491
15724110.210
.000
.500
.500
.749
1.000
.060
.015
66.226
KM
generation(Exp)
-1.377E-014
.000
.000
.000
1.000
.000
.000
.669
.000
.000
.102
9.809
KM
generation(Oral)
2.432E-014
.000
.000
.000
1.000
.000
.000
.743
.000
.000
.014
73.811
KM
generation(Org)
-3.682E-014
.000
.000
.000
1.000
.000
.000
.873
.000
.000
.007
147.653

International Journal of Research Publication and Reviews, Vol 5, no 5, pp 11728-11738 May 2024 11735
a. Dependent Variable: KMGen
It can therefore be concluded that since most respondents had a positive response to Knowledge generation it is key to competitive advantage especially
since without proper knowledge generation there can be no knowledge management.
Knowledge access
It is also clear from the table 6 that for the strongest factor affecting knowledge access according to regression analysis conducted on SPSS was the
overall usage of IT to store or access knowledge.
Table 3: Knowledge Access linear regression
Model
Unstandardized
Coefficients
Standardized
Coefficients
T
Sig.
95.0% Confidence
Interval for B
Correlations
Collinearity Statistics
B
Std. Error
Beta
Lower
Bound
Upper
Bound
Zero-
order
Partial
Part
Tolerance
VIF
1
(Constant)
.095
.104
.915
.364
-.113
.303
KM IT usage
.949
.034
.964
27.638
.000
.880
1.017
.964
.964
.964
1.000
1.000
2
(Constant)
-.436
.110
-3.958
.000
-.657
-.216
KM IT usage
.725
.042
.737
17.365
.000
.641
.808
.964
.917
.454
.379
2.635
KM IT
supplier info
.364
.053
.289
6.810
.000
.257
.471
.869
.670
.178
.379
2.635
3
(Constant)
-.405
.104
-3.895
.000
-.614
-.197
KM IT usage
.590
.060
.600
9.762
.000
.469
.711
.964
.794
.240
.160
6.262
KM IT
supplier info
.321
.052
.254
6.122
.000
.216
.426
.869
.633
.150
.349
2.865
KM IT
updated
.180
.062
.180
2.929
.005
.057
.304
.926
.364
.072
.159
6.294
4
(Constant)
-.366
.101
-3.631
.001
-.569
-.164
KM IT usage
.762
.091
.774
8.399
.000
.580
.944
.964
.750
.197
.065
15.364
KM IT
supplier info
.303
.051
.240
5.983
.000
.202
.405
.869
.628
.141
.342
2.923
KM IT
updated
.263
.068
.263
3.873
.000
.127
.398
.926
.463
.091
.120
8.317
KM IT sharing
-.246
.100
-.247
-2.459
.017
-.446
-.045
.925
-.315
-.058
.055
18.304

International Journal of Research Publication and Reviews, Vol 5, no 5, pp 11728-11738 May 2024 11736
Knowledge embedding
It was interesting to note that from the table 4 only the aspect of pursuing higher education as an aspect of embedding knowledge was considered important
enough to affect embedding of Knowledge according to regression analysis done on SPSS.
This data is consistent with the empirical literature review studies.
Table 4: Knowledge Embedding Coefficient
Coefficients
Model
Unstandardized
Coefficients
Standardized
Coefficients
T
Sig.
95.0% Confidence
Interval for B
Correlations
Collinearity
Statistics
B
Std. Error
Beta
Lower
Bound
Upper
Bound
Zero-
order
Partial
Part
Tolerance
VIF
1
(Constant)
.000
.000
.
.
.000
.000
KM embedding
Higher Edu
1.000
.000
1.000
.
.
1.000
1.000
1.000
1.000
1.000
1.000
1.000
a. Dependent Variable: KMEmbedding
5. CONCLUSION AND RECOMMENDATIONS
Conclusion
Knowledge management is clearly key to organizations as this study has proved and can lead to competitive advantage however each organization must
scrutinize itself and find out how best it can generate, access, embed, facilitate and transfer knowledge and which knowledge management tools are
suitable to help achieve its organizational goals and maximize on the knowledge and skills in that organization. The study of Knowledge Management is
largely a new concepts and not many studies have been done especially in Africa. This means that this in an area that requires intensive study and research.
However, the researcher recommends the following research areas.
Research needs to be done on effective types of knowledge management that can be applies too tacit, explicit or even both tacit and explicit knowledge.
The two organizations in this study were chosen to investigate the relation between knowledge management and competitive advantage. Safaricom has
knowledge management systems while organization B has no knowledge management systems but has a task force which has a wealth of experience
since the organization was one of the first telecommunication companies to be established in Kenya. These two organizations were compared all factors
held constant to find out if knowledge management can lead to competitive advantage. Secondary data was also used which determined that safaricom
had a competitive edge over Organization B and the purpose of this study was to establish if knowledge management is a contributor of this fact
Recommendations
Organizations should come up with knowledge management policies that clearly stipulate how knowledge is generated, accessed, embedded, facilitated
and transferred. Every employee that undergoes training should also be trained on how to store that knowledge for further refer and easy access for others
seeking that knowledge. Knowledge management systems should also be evaluated to know if they are just used as dustbins when knowledge is stored
never to be accessed again or if they are interactive and adequately used by employees in an organization to bring about competitive advantage. Forums
should also be organized where staff can interact and share their experiences every so often especially between the young and the older employees and
mentorship initiatives taken to ensure flow of knowledge.
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