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AN INVESTIGATION ON THE INFLUENCE OF
KNOWLEDGE MANAGEMENT FRAMEWORKS
INTEGRATION IN KENYAN SMES ON THEIR BUSINESS
OPERATIONS
BY
EMACULATE MBULA MUNYWOKI
UNITED STATES INTERNATIONAL UNIVERSITY
SUMMER 2017
AN INVESTIGATION ON THE INFLUENCE OF
KNOWLEDGE MANAGEMENT FRAMEWORKS
INTEGRATION IN KENYAN SMES ON THEIR BUSINESS
OPERATIONS
BY
EMACULATE MUNYWOKI MBULA
A Project Report Submitted to the School of Science and
Technology in Partial Fulfillment of the Requirement for the
Degree of Master of Science in Information Systems and
Technology
UNITED STATES INTERNATIONAL UNIVERSITY
SUMMER 2017
ii
STUDENT’S DECLARATION
I, the undersigned, declare that this is my original work and has not been submitted to any other
college, institution or university other than the United States International University in
Nairobi for academic credit.
Signed: ________________________ Date: __________________
Munywoki, Emaculate Mbula (ID No 624305)
This project has been presented for examination with my approval as the appointed supervisor.
Signed: ________________________ Date: _____________________
Prof. Jimmy Macharia, PhD
Signed: _______________________ Date: ____________________
Dean, School of Science and Technology
iii
COPY RIGHT
Munywoki, Emaculate Mbula © 2017
All rights reserved. This report may not be copied, replaced, recorded or transmitted by any
electronic or mechanical means without the consent of the copyright owner.
iv
ABSTRACT
Over years, the economic impact of Small and Medium Enterprises in our societies has been
significant. For instance, In Kenya, over 50 percent of jobs were created by this sector in 2005
leading to the growth of the country’s GDP. But despite its impact, SME’s often take the
biggest blow in periods of slow business. When there are reduced orders, cancelation of orders,
delayed payments by creditors, the impact is immediate as most of these firms don’t have a
wide array of products or services compared to large organizations. Due to their limited
resources, they operate without structures and have adopted informal business processes to
manage their knowledge asset.
For the last two decades, previous researchers have proposed a number of knowledge
management (KM) frameworks. Indeed there is abundant of literature on how large
organizations have adopted and are practicing KM using some of these frameworks with
outstanding results in their businesses. Unfortunately this is not the case for small and medium
enterprise (SMEs). Prior studies have posited the general consensus in relation to the fact that
the benefits of KM have not been fully exploited by small firms. Worse still, they argue that
there is very little contributions on the critical success factors for KM adoption in SMEs. A
more disappointing revelation from prior studies is the fact that empirical studies have been
rarely conducted on this topic. To address these gaps, this study aims to investigate: knowledge
management frameworks and practices infusion and adoption by Kenyan SME’s; the effect of
the Knowledge management frameworks and practices adopted by the Kenyan SME’s on their
achievement of their business strategy; and develop a more appropriate Knowledge
management Framework for SMEs achieving business efficiency.
The methodology adopted for this study is descriptive taking a mixed method approach with
three main stages as follows: a) A literature review on knowledge management frameworks,
practices and adoption in small business; b) A semi-structured self-administered survey
questionnaire developed and validated in a number of focus group discussions. The
questionnaire survey conducted through self-administration, and/or interviews with managers
of small firms belonging to the representative sample to be investigated; and (c) Experiment
v
with a new design of a simple knowledge management framework to demonstrate the adapted
SME Knowledge management Framework for achieving business efficiency. The project
looks to share insights on how knowledge management frameworks and practices are adopted
by Kenyan SME’s, the effects of the Knowledge management frameworks and practices
adopted by the Kenyan SME’s and their achievements in line with their business strategies and
how a refined knowledge management framework towards the Kenyan SME’s would aid in
achieving business efficiency and effectiveness hence success.
The approach used for this case provided a practical experience into SME’s and knowledge
management practices adopted by the Kenyan SME’s. Also, it provided key lessons that can
be borrowed by any other SME’s interested in managing their knowledge more effectively in
order to achieve efficiency, continued innovation and success. Startups and small organizations
looking for a practical way of managing and implanting knowledge in their organizations may
have point of reference. With the results, the study proposed a refined knowledge management
framework designed for SME’s in Kenya. This aids in implementation and management of the
Knowledge resource within any startups and SME’s. The suggested practices and elements
served as key component when any of the small organizations planned on how to manage new
and existing knowledge in order to achieve a competitive edge. Firms that leverage on
knowledge, experience efficient operations, successful innovations, ability to predict trends,
increase in customer service experience. Lack of reference material in relation to Knowledge
management practices for Kenyan SME’s made it a challenge to harness the necessary data.
The project provides a reference point for scholars and businesses in relation to knowledge
management practices within the Kenyan SME, a knowledge management strategy and
framework that can easily be adopted by SME’s.
vi
ACKNOWLEDGEMENT
My sincere gratitude goes to my supervisor Professor Jimmy Macharia, who provided
professional guidance and assistance in the completion of the research project. His numerous
valuable comments and appropriate feedback was highly significant to the content and
presentation of this project.
vii
TABLE OF CONTENT
STUDENT’S DECLARATION ............................................................................................. ii
COPY RIGHT ........................................................................................................................ iii
ABSTRACT ............................................................................................................................ iv
ACKNOWLEDGEMENT ..................................................................................................... vi
TABLE OF CONTENT ........................................................................................................ vii
LIST OF TABLES ................................................................................................................. xi
LIST OF FIGURES .............................................................................................................. xii
LIST OF ABBREVIATIONS ............................................................................................. xiii
CHAPTER 1: INTRODUCTION .......................................................................................... 1
1.0 Introduction ................................................................................................................ 1
1.1 Background of the Study ................................................................................................. 1
1.1.1 Knowledge Management .................................................................................... 2
1.1.2 SME’s ................................................................................................................. 4
1.1.3 The Role of SME’s in Our Societies................................................................... 5
1.1.4 Knowledge and Knowledge Management. ............................................................. 5
1.2 Statement of the Problem ........................................................................................... 6
1.3 General Objective ............................................................................................................ 7
1.4 Specific Objectives ..................................................................................................... 7
1.5 Justification of the Study ................................................................................................. 8
1.6 Scope and Limitation of the Study .................................................................................. 9
1.7 Definition of Terms ......................................................................................................... 9
1.8 Chapter Summary .......................................................................................................... 10
CHAPTER 2: LITERATURE REVIEW ........................................................................... 11
2.0 Introduction ................................................................................................................... 11
2.1 Theoretical Foundation ................................................................................................. 11
2.1.1: Knowledge Spiral Theory...................................................................................... 11
2.1.2 Theory on the Concept of Frames .......................................................................... 11
2.1.3 Knowledge Management Definition ...................................................................... 12
2.2 Knowledge Management Frameworks Influence on SME Performance Efficiency .... 13
2.2.1 Perspective versus Descriptive Frameworks .......................................................... 13
viii
2.2.2 SECI Framework .................................................................................................... 14
2.2.3 Cynefin Framework ................................................................................................ 15
2.2.4 Integrated Framework of Knowledge Management ............................................... 16
2.2.5 Iterative Model ....................................................................................................... 17
2.3 Knowledge Management Practices influence on SME Performance Efficiency .......... 19
2.3.1 Knowledge Creation and Acquisition. .................................................................... 20
2.3.2 Knowledge Transfer and Distribution .................................................................... 22
2.3.3 Knowledge Preservation ......................................................................................... 24
2.4 Organizational Performance Efficiency ........................................................................ 24
2.5 Conceptual Framework ................................................................................................. 27
2.6 Research Gaps ............................................................................................................... 28
2.7 Chapter Summary .......................................................................................................... 28
CHAPTER 3: METHODOLOGY ...................................................................................... 29
3.0 Introduction ................................................................................................................... 29
3.1 Research Design ............................................................................................................ 29
3.2. Population and Sampling Design ................................................................................. 30
3.2.1 Target Population ................................................................................................... 30
3.2.2 Sampling Design..................................................................................................... 30
3.2.3 Sampling Frames .................................................................................................... 30
3.2.4 Sampling Technique ............................................................................................... 31
3.2.5 Sampling Size ......................................................................................................... 31
3.3 Data Collection Methods ............................................................................................... 32
3.4 Research Procedures ..................................................................................................... 33
3.5 Validity & Reliability .................................................................................................... 33
3.6 Ethics ............................................................................................................................. 34
3.7 Data Analysis Methods ................................................................................................. 34
3.8 Chapter Summary .......................................................................................................... 35
CHAPTER 4: MODEL......................................................................................................... 36
4.0 Introduction ................................................................................................................... 36
4.1 Analysis ......................................................................................................................... 36
4.2 Modeling and Design .................................................................................................... 36
4.3 Proof of Concept ........................................................................................................... 41
ix
4.4 Chapter Summary .......................................................................................................... 43
CHAPTER 5: RESULT AND FINDINGS ......................................................................... 44
5.0 Introduction ................................................................................................................... 44
5.1 Demographics................................................................................................................ 44
5.1.1 Gender of Participants ............................................................................................ 44
5.1.2 Age of Respondents ................................................................................................ 45
5.1.3 Position in Business ................................................................................................ 45
5.1.4 SME Categories ...................................................................................................... 46
5.1.5 Years in Operation .................................................................................................. 47
5.1.6 Gross Turnover ....................................................................................................... 47
5.1.6 Level of Education .................................................................................................. 48
5.1.7 Number of Directors ............................................................................................... 49
5.1.8 Nature of the Business ............................................................................................ 49
5.1.9 Company Registration with the Ministry of Trade and Industry............................ 50
5.1.10 Organizational Structure ....................................................................................... 50
5.2 Knowledge Management Frameworks Influence on SME Performance Efficiency .... 51
5.2.1 Influence of KM Frameworks on SME Performance Efficiency ........................... 51
5.2.2 Principle Component Factor Analysis Loadings .................................................... 52
5.2.3 Instrument Reliability ............................................................................................ 55
5.2.4 Pearson Correlations for KM Frameworks and Practices ...................................... 56
5.2.5 Regression Analysis for KM Frameworks and Practices ....................................... 56
5.3 Knowledge Management Practices Influence on SME Performance Efficiency .......... 59
5.3.1 Approach Based on Individuals .............................................................................. 60
5.3.2 Knowledge Creation and Transfer .......................................................................... 61
5.3.3 Continuous Learning in the Organization .............................................................. 61
5.3.4 An Understanding of the Organization as a Global System ................................... 62
5.3.5 Development of an Innovative culture that Encourages R&D projects ................. 63
5.4 Organizational Performance Efficiency ........................................................................ 63
5.5 Chapter Summary .......................................................................................................... 66
CHAPTER 6: DISCUSSION, CONCULSIONS AND RECOMMENDATIONS .......... 67
6.0 Introduction ................................................................................................................... 67
6.1 Summary ....................................................................................................................... 67
x
6.2 Discussions .................................................................................................................... 68
6.2.1 Knowledge Management Frameworks Influence on SME Performance Efficiency
......................................................................................................................................... 68
6.2.2 Knowledge Management Practices Influence on SME Performance Efficiency ... 69
6.3 Conclusions ................................................................................................................... 71
6.3.1 Knowledge Management Frameworks Influence on SME Performance Efficiency
......................................................................................................................................... 71
6.3.2 Knowledge Management Practices Influence on SME Performance Efficiency ... 71
6.4 Recommendations ......................................................................................................... 72
REFERENCES .................................................................................................................... 74
APENDIX I: INTRODUCTORY LETTER ....................................................................... 87
APENDIX II: QUESTIONNAIRE ...................................................................................... 89
xi
LIST OF TABLES
Table 1: Classification of SME’s by the MSE’s Act of 2012 (GoK, 2010) ............................. 5
Table 2: Major KM Frameworks and their Key Shortcomings. ............................................. 18
Table 3: Population Distribution ............................................................................................. 30
Table 4: The Strata Table ........................................................................................................ 32
Table 5: Flow of the Implementation and Test Criteria. ......................................................... 43
Table 6: Position in Corporate Business ................................................................................. 46
Table 7: Highest Level of Education ...................................................................................... 48
Table 8 : Number of Directors ................................................................................................ 49
Table 9: Nature of the Business .............................................................................................. 49
Table 10: Firm Structures ....................................................................................................... 51
Table 11: Key for Codes Used in the Analysis ....................................................................... 51
Table 12: Various Knowledge Management Frameworks and their Adoption by Various
Firms ....................................................................................................................................... 52
Table 13: Rotated Component Matrixa ................................................................................... 53
Table 14:Total Variance Explained ........................................................................................ 54
Table 15:Codes Used for Knowledge Management Frameworks and Practices .................... 55
Table 16: KM Practices Constructs Cronbach’s Alpha .......................................................... 55
Table 17:Pearson Correlations for KM Practices ................................................................... 56
Table 18: Variables Entered/Removed a ................................................................................. 57
Table 19: Model Summaryb .................................................................................................... 57
Table 20:ANOVAa for KM Practices .................................................................................... 58
Table 21: Regression Coefficients a SME Performance Efficiency Constructs ..................... 59
Table 22: Descriptive Statistics for KM Practices .................................................................. 60
Table 23: Codes SME Performance Efficiency Constructs .................................................... 61
Table 24:Continuous Learning in the Organization................................................................ 62
Table 25: SME Performance Efficiency Constructs Cronbach’s Alpha ................................. 64
Table 26:Organizational Performance Efficiency Descriptive Statistics ................................ 64
xii
LIST OF FIGURES
Figure 1: SECI Model of Knowledge Creation (Nonaka & Takeuchi, 1995). ....................... 15
Figure 2: Cynefin Framework by Dan Snowden (Kurtz & Snowden, 2003) ......................... 16
Figure 3: Integrated Framework of Knowledge Management Model (Berry, 2010). ............ 16
Figure 4: Iterative Model (Alshamrani & Bahattab, 2015) ..................................................... 17
Figure 5: Conceptual Framework ........................................................................................... 27
Figure 6: Knowledge Management Model for SME’s in Kenya. ........................................... 37
Figure 7: A Visual of the Processes within the Process Acquire / Create .............................. 38
Figure 8: A Visual of the Processes within the Process Enrich .............................................. 38
Figure 9: A Visual of the Processes within the Process Distribute. ....................................... 39
Figure 10: A Visual of the Processes within the Process Sustain/ Divest .............................. 39
Figure 11: The Suggested AEDS Knowledge Management Framework ............................... 40
Figure 12: Hypothesis on KM practices, Frameworks and Systems. ..................................... 41
Figure 13: Flow of Information from the Different Processes ............................................... 41
Figure 14: AEDS Framework used to evaluate Feedback to the Firm. .................................. 42
Figure 15:A Pie chart on Participants vs. Gender ................................................................... 44
Figure 16:A Bar Graph showing the Varied Age Groups ....................................................... 45
Figure 17:Different Sectors Covered within the Survey......................................................... 46
Figure 18:Histogram showing Years in Operation ................................................................. 47
Figure 19:Bar Graph comparing Gross Turnover ................................................................... 48
Figure 20:Number of Firms Registered by Ministry of Trade ................................................ 50
Figure 21: Mean Rating of KM Practices on a Five Point Scale ............................................ 60
Figure 22: SME Organizational Performance Efficiency Improvement ................................ 65
Figure 23:SME KM Frameworks and Practices Model .......................................................... 66
xiii
LIST OF ABBREVIATIONS
KM: Knowledge management
KMF: Knowledge management frameworks
ADF: African Development Bank
CFS: Critical Success Factors
IFC: International Finance Corporation
1
CHAPTER 1: INTRODUCTION
1.0 Introduction
This chapter will discuss the research problem, the rationale for the research and the knowledge
management frameworks gaps the research ails to fill. It presents the research questions, states
the research aims and discusses the research objectives. It identifies the novelty of the research
and discuss the research benefits. It discusses the contributions of the research output to the
body of knowledge. The chapter finally presents the structure of the project.
1.1 Background of the Study
Knowledge is regarded as the new currency and has over the recent years (Carrillo F., Lluis de
la Rosa, & Canals, 2007; Omotayo, 2015; The Word Bank, 2012) and hence a competitive
incentive amongst organizations to leverage their knowledge assets in order to gain a
competitive edge and creative value in order to remain in the markets. SME’s have lagged
behind in development of knowledge management practices often not attaining their business
goals and off the markets over a short period of time. This is clear as it’s reflected in the
minimalistic literature available in regards to SME’s and practicing Knowledge Management
(Finkl & Ploder, 2009).
The mortality rate of SME’s in European markets with reference to the United Kingdom, the
formation of new firms here are at 17 % and have a failure rate of about 73% (Pratt & Virani,
2015). The African countries remain on a record high with at least five out of seven new
ventures failing in their first year of existence. (Adcorp, 2012). For instance, In South Africa,
the failure rate of SME’s in their first one year is between 50% & 95% depending on the
industry (Thobakani, Tengeh, Maziriri, & Madinga, 2016; Entrepreneur, 2016).
Kenyan SME’s are not any different. Past statistics show three out of five SME’s in Kenya fail
within the first year of operations (Kenya National Bureau of Statistics, 2007). Often, due to
their unique characteristics such as lack of financial resources, trained manpower, and lack of
a strategic plan for the business but more often, these organizations are unable to grow beyond
their vision. They also lack proper structures to run their day to day business operations. A point
of reference to aid them grow and achieve beyond their optimum levels in line with their
business strategy would be key and need to be designed to fit the Kenyan SME’s due to their
unique characteristics. Various previous researchers have suggested knowledge management
frameworks including SECI model, Nonaka model and integrated knowledge management
(Schutt, 2003). These frameworks have been adopted by different organizations round the world
2
where some have been transformed to success stories (SIEMENS, 2011). Unfortunately these
models need contextualization for SMEs particularly for developing countries, where
challenges in access of reliable power, technology is not comparable to developed nations.
Where such contextualization is not done, models developed for developed economies produce
catastrophic results for SMEs in developing economies like Kenya. This is evident and as an
example from the past statistics show three out of five SME’s in Kenya fail within the first year
of operations (Kenya National Bureau of Statistics, 2007). One of the major reasons for this
phenomena is the lack of a point of reference in regards to a knowledge management
frameworks that are designed to fit the Kenyan SME’s due to their unique characteristics and
environmental variables.
An argument may then be posed, why not use the existing frameworks designed for other
developing countries? The Kenyan SME’s has multiple unique challenges and have very unique
characteristics compared to their counterparts round the world (Wanjohi, 2012). Most of the
frameworks were designed purposely for large organizations and existing SME’s have had to
borrow from the frameworks. This often makes them loose their unique characteristics. (Rizea,
Parpandel, Caldararu, & Radu, 2011).
The study will propose a refined knowledge management framework designed for SME’s in
Kenya. This will aid in implementation and management of the Knowledge resource within any
startups and SME’s. The suggested practices and elements will serve as a key component when
any of the small organizations are planning a practical way of managing and implanting
knowledge in their organizations may have point of reference on how to manage new and
existing knowledge in order to achieve a competitive edge. Firms that leverage on knowledge,
experience efficient operations, successful innovations, ability to predict trends, increase in
customer service experience.
1.1.1 Knowledge Management
Knowledge management encompasses a wide area of study and much of it has not been
explored due to various reasons. Some Scholars such as Ibrahim and Reid (Ibrahim & Reid,
2010) are still discussing in length as to whether this is a management fad. There is little or
scarce empirical studies that clearly document and show how SME’s have adopted and infused
knowledge management frameworks, practices and elements in this area. The motivation
behind this research and project is the keen interest on knowledge management for SME’s for
academia and business purposes. The SME’s locally have had to borrow from existing
3
frameworks, internationally and from multinationals. Their unique characteristics make it
difficult for adoption as some of the features don’t match their needs hence unable to meet their
maximum output and inability to continue growing after a number of months in business.
The aim is to understand what knowledge management practices have been adopted by the
SME’s, their effects on infusion with the existing business strategies and refine already existing
knowledge management frameworks that have been adopted by some of the local successful
SME’s and introduce elements in order to generate one that can be incorporated within SME’s
locally. Proper valid frameworks will aid to avert cases of mushrooming small firms with
brilliant ideas being unable to survive the competitive markets and individuals loosing
livelihoods and as a translating to improved economies. Also, framework policies that can be
adopted by existing Kenyan SME’s to help harness knowledge without investing much in
regards to resources, something that SME’s in Kenya barely have (Memba, Gakure, & Karanja,
2012). Finally, document the processes, elements, challenges faced and anticipated as times
change that can be used as reference points when handling and implementing KM in the small
firms locally. This will play a role in contributing to this topic by generating empirical data that
will continue to support KM as valid theory and neither a trend nor fad.
Knowledge is categorized into two, Explicit and Tacit knowledge. Explicit knowledge can be
defined as objective and rational, expressed in sentences, numbers, words or formulas. This
knowledge can be shared, documented, transmitted and categorized to others (Debowski, 2005).
It’s easily captured and distributed because it’s easily passed as a physical material. Once coded
and stored, it’s easily accessible by anyone in the organization (Singh, 2008). Tacit knowledge
is stored in the minds of individuals as insights and intuitions. This is often difficult to access
since this is not centrally stored for access and workers may not be willing to share information
(Marzanah, Sidi, & Selamat, 2010). This is often developed through learning and experience
(Debowski, 2005). Knowledge is clearly an important commodity that has to be shared and
often improved amongst organizations in order to generate new ideas with the aim of solving
existing challenges. SME’s are known to be the key innovators of new ideas due to their
flattened nature hence less bureaucracy and hence workers are able to generate more viable
ideas (Rahman & Ramos, 2011). Most Knowledge management projects have either of these
three as their key aims .a )To visualize the roles of knowledge management in an organization
through maps and hypertext tools b) To develop and encourage a knowledge intensive culture
where behaviors such knowledge sharing, knowledge offering and proactively seeking
knowledge , c)To build a knowledge infrastructure that incorporates both a technical system
4
and its people facilitating resources such as space, tools, time and motivation hence able to
collaborate and interact (Davenport & Prusak, 1998).
1.1.2 SME’s
The concept of SME’s differs from one country to another depending on guidelines set. Often,
they are categorized based on employee headcount, Organizational asset base and revenue. The
World Bank define SME’s as firms that generate an annual revenue of $ 15 million, own an
asset base of $ 15 million and a maximum of 300 employees (Europe Investment Bank, 2011).In
the United States, all enterprises with less than 500 employees and generate an annual revenue
of $ 7million dollars are defined as SME’s. (United States International Trade Commission,
2010), Egypt Small Enterprise law defines SME’s as firms that generate a minimum capital of
50,000 EGP and a maximum of 1,000,000 EGP with a maximum of 50 employees (Moukhtar,
2015) .
In Tanzania, SME’s employ between 5 and 99 employees, and generating capital of up to Tsh.
800 million (Yahya & Mutarubukwa, 2015). In Kenya, SME’s are categorized in regards to the
number of employees and the institution’s annual turnover. The same are further sub
categorized to Micro and Small enterprise, with micro enterprises employing one to ten
employees and annual turnover of 500,000kes while small enterprises employ eleven to fifty
employees and an annual turnover of between 500,000 and 5 million shillings. (Ong'olo &
Awino, 2013).
5
Table 1: Classification of SME’s by the MSE’s Act of 2012 (GoK, 2010)
Entity No of employees Annual
Turnover Limit
Investment in
machinery and plant +
registered capital
Equipment
investment +
Registered
capital
Micro Less than 10
people
Not exceeding
KES 500000
Not exceeding KES
10Million
Not exceeding
KES 5M
Small More than 10
and less than 50
Between
500000KES to
KES 5Million
More than 10Million but
less than 50Milion
More than 5M
but less than 20
Million
The SME’s in Kenya are also further subdivided further to formal and informal businesses with
engagement in varied activities from agriculture, manufacturing to trade. This provides
employment for more than 74% of the total population in any financial year. (Ong'olo & Awino,
2013).
1.1.3 The Role of SME’s in Our Societies.
The SME’s in Kenya contribute up to 74 percent of jobs in the market that contributes to about
20 percent of the total GDP. In 2014, 80 percent of 800,000 jobs were created by the informal
sector where SME’s dominate (Ong'olo & Awino, 2013; Mutegi, 2015) .With SME’s making
provision for livelihoods for more than three quarters of the country, a need to preserve these
firms is dire. This can be done by harnessing necessary knowledge and ensuring it’s accessible
to all parties when needed.
Young organizations in developing countries generate more than their share of employment but
less than half of these startups make the five year mark. Again, only a fraction of these grow to
large organizations making room for more jobs. SME’s success is linked to how well it manages
its knowledge assets (Brush & Vanderwerf, 1992; ISCTE Lisbon University Institute, 2010;
North & Varvakis, 2016).
1.1.4 Knowledge and Knowledge Management.
Knowledge is deemed as a currency to any economy (Carrillo F., Lluis de la Rosa, & Canals,
2007). The ability to use existing knowledge by the SME’s to understand and predict trends,
creates room for innovation. The result? New ideas are identified, generating new avenues for
6
job creation thus revenue is generated and thus GDP growth for any economy (Wang & Noe,
2010).With the ability to predict future trends using available knowledge, SME’s can be able
to plan and manage its limited resources, predict tough business seasons and plan around them
hence ensuring business continuity.
Knowledge is an asset to SME’s and a need for management of this resource is necessary
(Omotayo, 2015).Knowledge management is a discipline that entails an integrated approach to
identify, capture, process and share an organization’s information assists. This may include
databases, un-captured expertise and experience by workers (Duhon, 1998).Studies on
knowledge management have been explored in regards to large organizations but little or no
studies have been undertaken in regards to the SME’s (Edvardsson & Durst, 2013). Knowledge
management is a practice important for SME’s in developing countries but most have been
unable to adopt and implement the same successfully due to varied challenges (Omar &
Arokiasamy, 2009). Such include lack of resources such as labor, capital, and lack of knowledge
sharing within themselves and organizations in the same trade due to fear of competition
amongst others.
1.2 Statement of the Problem
A knowledge based economy is driven by knowledge capital. Today’s economy has become
more information and knowledge driven and so the necessity for an effective way to manage
knowledge and information effectively. KM brings together three key organizational resources
~Processes, people and technology ~to enable an organization to effectively, efficiently use and
share information. The Kenyan SME‘s are significant as they provide jobs for up to 80 per cent
of the total population (Adeyeye, 2016) and are progressively significant as with regards to
continued inventions and innovations. In the recent times, with recession striking the African
market, many SME’s have shut down their operations or have had the need to cut down on their
operating costs. This has led to cases of unemployment and fall of incomes (International
Labour Office, 2015; Omondi , 2016). This translates to very few SME’s transiting into large
firms and leaving no room for fresh ideas into the economy.
The case in Nairobi, Kenya is not different. SME’s around Nairobi in the recent past have
experienced little or no growth in size and a number of them winding down operations. This is
due to the continued globalization of the economy and a more demanding market that pushes
the firms to re-structure their businesses and re-align their business strategies in line with the
changing market demands. This has not only affected the new brands in the market but also the
7
old and already established businesses and hence arises a need for concern (Njiru , 2014; Otuki,
2016). A need to wind down means a lack of a clear transitional plan in case of any disruption
i.e. A lack of explicit strategies and inability to handle knowledge management as it should and
only focusing on this from operational levels i.e. only need to adopt knowledge management in
form of systems and instruments (Hutchinson & Quintas, 2008).
A detailed research on SME’s adoption and infusion of Knowledge Management by Kenyan
firms yields a minimalistic result hence providing no reference point in line with management
of the knowledge assets within these firms. Minimal or lack of empirical data documenting the
implementation structures of KM ,strategies used ,success stories, effects and challenges faced
makes it also difficult for any organizations looking to achieve the same skeptical on adopting
the same. The policies offered as a counter measure to these problems seem ineffective (Kiveu
& Ofafa, 2014). As a result, the local SME’s have often been forced to borrow from existing
frameworks that have been designed and adopted by large organizations (Evangelista, Esposito,
Lauro, & Raffa, 2010). This is evident as organizational theory and practice conversations for
any knowledge management activities for SME’s are often derived from large organizations
policies and experiences. As a result, they lose their unique characteristics. (Edvardsson &
Durst, 2013). A need for this is hence necessary to guide the SME’s on how to harness, fully
exploit and manage this critical asset. This study seeks to fill the gap by establishing the
influence knowledge management frameworks have on business operations in relationship to
the Kenyan SME’s.
1.3 General Objective
The key objective of this study is carry out an in depth analysis on how knowledge management
frameworks influence business operations when integrated into Kenyan SME’s business
operations.
1.4 Specific Objectives
1.4.1 To investigate the influence of knowledge management frameworks by the Kenyan
SME’s
On their business operations.
1.4.2 To examine the effect of the existing Knowledge management practices adopted by the
Kenyan SME’s on their business operations.
8
1.4.3 To design a simple knowledge management framework that is appropriate for optimal
SME’s business operations.
1.5 Justification of the Study
The study is key in identifying proper practices suitable for the Kenyan SME’s in regards to
structures, policies that aid in successfully adopting KM in relation with their business strategies
and vision. The various benefits may be categorized as follows;
a) New contextual variables.
The Knowledge Management structures will help in harnessing, streamlining processes,
maximizing on returns and as a result aid SME’s in planning proper strategies that will help
sustain their businesses even through tough times (Daud & Yusoff, 2010) and hence ensuring
they don’t lose their identity (Edvardsson & Durst, 2013). The result is business continuity,
despite the tough economies and ability to compete with the large firms hence remaining in
business while remaining relevant; with the ability keep to re-inventing themselves when tough
times strike (Dave, Dave, & Shishodia, 2012).
b) Contribution to knowledge
The study will also be important in identification of literature, empirical data and a point of
reference for future studies undertaken by other scholars in relation to knowledge management
by SME’s in Kenya and also small firms looking study and infuse KM into their operations and
in need of previous data. (Evangelista, Esposito, Lauro, & Raffa, 2010; Cerchione, Esposito, &
Spadaro, 2015). A clear documentation of the effects of KM, the adoption and infusion of KM
structures will contribute in building the KM theory and proof that it’s not a passing trend
neither a fad but a reality and necessity for any organization looking to achieve a competitive
edge and enjoy business continuity (The Institute for Knowledge and Innovation Southeast Asia
(IKI-SEA) of Bangkok University, 2011), besides contributing to the literature of KM.
c) Framework for practice by SMEs
This study is important to help small firm’s owners and practioners understand that KM
adoption and practices need not to be an expensive trade due to their limited resources. A use
of the readily available and affordable tools, practices that support KM activities, can be
adopted. This can be demonstrated by designing and integrating simple Business Intelligence
systems to demonstrate KM activities using Google applications integrated with other powerful
9
tools to show how these can be used to create, harness and manage knowledge. This is important
to any practioner as they will now not avoid this practice due to resource limitations but will
adopt what’s available to gain an edge (7th International Conference on Knowledge
Management in Organizations, 2012; Gammelgaard, 2007).
1.6 Scope and Limitation of the Study
The study population will be SME’s in Westlands area in Nairobi Kenya. Westlands has over
years harbored SME’s of different sizes as the area caters for individuals of all walks of life. A
wide array of data would therefore be harnessed, there would be less travel as they are within
walking distances from each other and it’s within the confines of the Central Business District.
The study assumes that:
1. The features exhibited by the Nairobi small firms cut across all other small firms across
the country.
2. The challenges faced are similar across the small firms in the region
3. Most of the small firms lack proper operational structures and proper business strategies
and are in need of proper KM policies and structures to aid in management of their
knowledge resource.
1.6.1 Limitations
The study is limited to acquiring information on knowledge management practices from Small
and Medium Enterprise firms within the Nairobi city region, when ideally it should have been
more than one region of the country. This was not possible due to the limited financial resources
allocated and available to conduct the research.
1.7 Definition of Terms
Explicit knowledge: This is information that exists in books, publications, journals, databases.
It’s relatively easy to capture, identify, disseminate and store (Takala, 2008).
Frameworks: Often a layer structure that shows what programs ought to be built in order to
inter relate to already existing systems hence simplifying the production environment
(Jabareen, 2009).
Information: Defined as processed data, useful data, from it, conclusions can be drawn
(Sloman, 2009).
10
Knowledge economy: A system of by an organization that bases its operations on consumption
and production that is based on intellectual capital. Such organizations thrive on the
intangible assets such as workers intellectual capital (Brinkley, 2006).
Knowledge Management Systems: Are I.T based systems that act as repositories for data
storage and retrieval with the intention to improve collaboration, locate knowledge
sources, data mining capturing using knowledge hence improving the Knowledge
management process (King R. , 2009).
Knowledge: Defined as actionable information. With this information, as an organization
certain actions and decisions can be (Nonaka I. , 2013).
SME: Small and Medium Enterprise: These are businesses employing an average of one to fifty
workers, both on the formal and informal sectors (Berisha, 2015).
Tacit knowledge: Regarded to as unwritten, unspoken information held on to by human beings.
It’s based on a human being’s experience of emotion, observation, and experience.
Hence, it’s very difficult to capture. It is personalized and contextualized (Smith, 2001),
(Grant, 2007).
1.8 Chapter Summary
This chapter gives a synopsis behind the topic of discussion, and gives a background of KM
practices and SME’s .It documents the problem statement that creates the gap for the research,
identifies, the scope, limitations and assumptions throughout the study, and provides a
definition of the words throughout the text. The next chapter will critically review, how the
Kenyan SME’s have adopted KM practices, and existing knowledge management frameworks.
11
CHAPTER 2: LITERATURE REVIEW
2.0 Introduction
This chapter looks to identify Knowledge Management Practices, study past frameworks
designed with the aim of managing the knowledge asset. A review of SME’s characteristics
within Kenya and what makes them unique compared to others around the world and hence
large organization frameworks cannot be replicated on the small firms are also discussed. A
conceptual framework, variables influencing KM infusion and adoption will be discussed in
relation to these small firms.
2.1 Theoretical Foundation
How a firm manages its knowledge has a profound impact on its success or failure as an
organization and hence it’s critical knowledge management procedures be based on a solid
theoretical foundation.
2.1.1: Knowledge Spiral Theory
This Theory focuses on how knowledge moves from its tacit nature to explicit form then to
individuals then forms a basis for innovation, invention and continuous learning (Dalkir, 2011).
The Four modes of knowledge conversion socialization, externalization, combination and
internalization. A clear understanding of these processes, ensures the firm understands clearly
how tacit and explicit knowledge interact in a firm and also knowledge managers are able to
assess practices adopted to ensure all forms of conversion are developed and supported
adequately. The theories above clearly support the fact that a growing understanding of how
knowledge management is a major component in the success of any organization. Continued
discoveries of the different forms of knowledge, relationships forged between the objects,
processes that transform the knowledge and a full understanding of the results lead to
understanding organizational knowledge and proper knowledge management (Nonaka &
Konno, 1998).
2.1.2 Theory on the Concept of Frames
Frameworks play key role in sense- making in cases where problems occur. Sense making can
be easily defined as the process where analyst seek to answer the very basic question, “What is
going on here?” Goffman discusses the idea of frames and their roles in helping an individual
understand the series of activities. A frame helps decode whether the series of activities are real
or not hence prioritizing what is important. The frames are further categorized into two; Primary
12
frame and secondary frame (Aidemark , 2007). A primary frame originates from individuals in
social /cultural contexts and this often harnesses tactic knowledge whilst a secondary frame that
are meaningful knowledge further transformed into a pattern or activity. Goffman states that
every activity encountered ought to be framed no matter how detailed or simple it is, as it is
subject to various interpretation (Goffman , 1986).
2.1.3 Knowledge Management Definition
Knowledge Management has been in existence from the 20th Century but has only been
emphasized on since the 20th century. Knowledge management, due to its multi-dimensional
nature is defined differently (Darroch, 2003). Knowledge management (KM) is defined as a
comprehensive approach that includes capture, receipt and transfer of information in an
organization that considers policies, procedures, knowledge and experience of employees and
by as a business practice that integrates essential strategies, techniques, policies and procedures
(Davenport & Prusak, 1998). For this study, KM is limited to four knowledge creation and
acquisition, sharing and responsiveness.
The potential of knowledge management seems not to have been fully exploited by SME’s
through the previous studies done and this is clear in the little research and the limited reference
material available in line with this topic. Also, research on knowledge management in SME’s
highlights different features compared to large organizations hence need for different structures
to guide and govern the same (Pillania, 2006). Though large organizations have taken a lead in
introducing and implementing knowledge management, it’s important for SME’s to manage
their intellectual and collective assets (Frey, 2001).
Research by previous scholars such as Thorpe on Knowledge management in SME’s suggests
the context can be broken into three clear fields, the Knowledgeable SME manager/ owner or
entrepreneur, Knowledge systems and practices embedded to fit the firm’s context and
immediate networks and Institutional and policy frameworks intended to support knowledge
production within the SME’s (Thorpe, Holt, Macpherson, & Pittaway, 2005).In addition, five
key unique characteristics have been discussed by (Desouza & Awazu, 2006) that distinctively
set apart knowledge management practices in SME’s in relation to the large organizations.
SME’s lack explicit knowledge repositories and business owners / entrepreneurs /business
managers act as the knowledge repositories. The common knowledge possessed by members
of the SME’s is deep and broad, and it’s necessary when managing issues of knowledge
transfer, sense making and application. SME’s are skilled at avoiding knowledge loss by
employing mechanisms such as close ties among its members hence even employees choose to
13
leave, not much information is lost , the resources within the firm can easily be used to mobilize
a replacement. Due to their limited resources, SME’s find themselves borrowing off foreign
sources to meet their deficit in cases of knowledge creation. SME’s often manage their
knowledge right using the humanistic way that does not encompass technology. Technology is
in minimal use when in automation of services such as the cash register, and informative
purposes such as handling employee contact information in a simple database.
Knowledge often generated by SME’s is tacit in nature. This is due to the ad hoc way of running
their organizational activities. Any technology that is adopted by these firms can only be
adapted to the organizational needs and not vice versa (Wong K. , 2005) and (Wong &
Aspinwall, 2005) highlight eleven key factors in adoption and implementation of Knowledge
management in SME’s. These include management leadership and support, organizational
culture, Information Technology, Purpose and strategy, Organizational infrastructure, activities
and processes, resources, motivational aids, education and training, human resource
management. These are key in ensuring when SME’s are planning and developing Knowledge
Management strategy. This also provides a basis to evaluate their Knowledge management
practices (Wong K. , 2005).
2.2 Knowledge Management Frameworks Influence on SME Performance Efficiency
2.2.1 Perspective versus Descriptive Frameworks
Knowledge management frameworks are necessary to help understand SME’s view,
investments, establish a common working ground hence aiding KM users to comprehend KM
investments or initiatives and identify the ones that can aid in achieving a competitive edge
(Handzic, 2006) . Though these frameworks do exist, they lack empirical evidence related to
the hypotheses and coherence to support the different concepts presented hence creating a gap
(Choochote K. , 2013).
Existing frameworks have been categorized into two broad categories, perspective and
descriptive frameworks. Perspective frameworks incline towards methods to be adhered to
while conducting Knowledge management. Descriptive frameworks try to characterize
Knowledge management phenomena and are further divided into two, integrated models and
partial (Azyabi, Fisher, Tanner, & Gao, 2012).Partial frameworks seem to incline towards
resources and groupings. Knowledge management has its focus on the knowledge of its staff,
hiring, training and retaining its personnel that’s often regarded to as the intellectual assets of
14
any business (Alawneh, Abuali, & Almarabeh, 2009). Examples of partial framework are
demonstrated in Nonaka and Konno’s work. Nonaka distinguished tacit and explicit knowledge
using Polanyi’s original concepts in regards to tacit knowledge (Polanyi, 1966), and hence
generating a concept of knowledge creation spiral. It’s considered as a process that involves
interaction between explicit and tacit knowledge. The spiral model elaborates the process of
explicit and tacit knowledge being exchanged and transformed through four nodes;
Socialization, Combination, Externalization and Internalization (Handzic, 2006). Socialization
aids in transfer of knowledge from one individual to another, combination allows combining of
existing explicit knowledge to new explicit forms. Externalization helps convert tacit
knowledge to explicit knowledge inform of models and concepts. Internalization aids in
absorption of explicit knowledge, creating more room knowledge creation (Handzic,
2006).Prescriptive frameworks aim to provide road maps as to how conduct Knowledge
management. Such include Sequential evolutionary models, and the iterative model.
2.2.2 SECI Framework
To further provide the ideal conditions for knowledge creation, the “ba” concept was
introduced. It also attempts to outline the relationship between information management
systems and knowledge management in line with information (Frost, 2015).Information
systems in Knowledge management play an important role, the data-information knowledge
hierarchy is commonly used in Information Systems. This helps classify knowledge into various
categories, as an object hence easily stored in a computer system and knowledge as information
embedded in people’s minds. The categories play a major role in distinguishing knowledge in
each context (Azyabi, Fisher, Tanner, & Gao, 2012).Partial frameworks integrate diversity to
make provision for improved methods in knowledge management hence able to manage a wider
range of issues, theories and methods.
15
Figure 1: SECI Model of Knowledge Creation (Nonaka & Takeuchi, 1995).
Integrated models in knowledge management frameworks use combination of processes and
strategy but focuses of key initiatives. These are often manifested in terms of context diagrams
(Goswami & Goswami, 2013). It classifies knowledge according to its nature to help in
understanding how in turn it’s managed. From it, patterns and trends are identified. Context
diagrams help in visualizing hence able to identify any emerging trends.
2.2.3 Cynefin Framework
The Snowden’s model content-narrative-context highlights the three key components of
knowledge management and the relationship (April, Milton, & Gorelick, 2012).His emphasis
on content vs context is key in ensuring real understanding. He classified content as known,
chaotic, knowable and complex. Known content has evidence to support provided information,
knowable content encompasses community of practices where professionals share knowledge,
Chaos arise where there’s a new situation and a need to impose a new pattern in order to make
them easily understood and manageable.
16
Figure 2: Cynefin Framework by Dan Snowden (Kurtz & Snowden, 2003)
2.2.4 Integrated Framework of Knowledge Management
Integrated framework of Knowledge management model suggests two types of factors. The
Organizational environment and Technological infrastructure. These are considered as major
enablers that facilitate knowledge transfer within any environment. The model further suggests
that organizational environment is the key determinant to what technological infrastructure
would support knowledge process (Handzic, 2006).
Figure 3: Integrated Framework of Knowledge Management Model (Berry, 2010).
17
Dynamism in Integrated Frameworks is key as it has an emphasis on knowledge activities and
processed in the cycles of growth. Knowledge management heavily relies on social, technology
and organizational factors hence it’s considered a social- technical undertaking and dependent
of context (Biloslavo & Zornada, 2001).
2.2.5 Iterative Model
Iterative model proposes a cyclical and parallel knowledge management approach. The
Knowledge management method in this case includes creating awareness and identification of
knowledge management problems, strategy, design, prototyping and continuous evaluation and
maintain ace. Siemens AG applied a knowledge strategy process that did result to knowledge
management action and a project plan (Ramhorst, 2001). The phases don’t need to follow a
linear process but can build on each other depending on the nature and aim of a particular
knowledge management initiative. (Freudenthaler, Eisenhauer, & Stenger, 2003).
Figure 4: Iterative Model (Alshamrani & Bahattab, 2015)
The Sequential model lays emphasis on three stages. The first stage, organizations work from
within to harness the valuable knowledge about them. Second stage, with the knowledge easily
harnessed, find new use for it and finally, create an environment suitable for knowledge creation
with the aim for innovation. Below is a summary of the various common frameworks and their
said shortcomings.
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Table 2: Major KM Frameworks and their Key Shortcomings.
Knowledge management
framework
Author & year KM components Area of study Short comings
Knowledge Creation
Framework
Nonaka (1991,
1994) &Nonaka
and Takeuchi
(1995)
Externalization
Combination
Internalization
Socialization
Inclines towards
descriptions on
evolution and
conversion
between explicit
(easy to codify)
and tacit
knowledge
(difficult to
articulate).
Knowledge that
can lead to a
knowledge
creation spiral in
any organization
Scholars argue
that this is not a
KM Framework
parse. It only deals
with the creation
of knowledge,
which is only a
portion of what
Constitutes KM.
A systems thinking
framework Knowledge
management-CRM
Rubenstein-
Montano
et al. (2001a)
Bose and
Sugumaran
(2003)
Acquisition
Processing
Deployment
The frameworks
Only provide a
set of activities
where the
emphasis is on
the knowledge
cycle processes
or activities.
The framework
mainly addresses
the phases of
knowledge flow
(from creation to
application) in an
organization
without providing
guidance on how
to implement KM.
Agile knowledge
management framework
Dr. Jeff Sutherland
and Ken Schwaber
(1992)
Conceptualize
Reflect
Act
Retrospect
Designed for
application
development on
complex
projects
The framework
has several weak
points.
1. Unstructured
process of
working.
2.Unsuitable for
large scale
organizations
3.Lack of accurate
documentation
and artefacts
4.Absence of
problem solving
phase
5.Not architecture
based
6. No activity of
building
prototypes or
19
conceptual model
of the product.
Knowledge Life Cycle Ruggles 1997,
Liedner & Alavi,
1999
Identify/
Create
Store
Share
Use
Learn
Improve
This framework
follows
knowledge
through the
stages of its life
cycle from
creation to
disposition
The main
disadvantage :
1.No provision for
the richness
inherent in KM
systems
2. It doesn’t show
cases where
research might be
lacking.
Integrated Framework Berry , 2010 Initiation
Generation
Modeling
Repository
Distribution &
Transfer
Use
Retrospect
This framework
utilizes a fully
integrated
approach to
adopt
the systems and
social thrusts of
enterprise wide
KM
Regarded to as
overwhelming.
Often lacks a
supporting
implantation
model to enhance
its practical utility.
2.3 Knowledge Management Practices Influence on SME Performance Efficiency
SME’s around the world operate on a knowledge based economy, and this heavily characterized
by conversion of knowledge into an assets involved in economic exchanges. Reason why
knowledge is” THE” resource in the post industrial age are mainly economic and technological.
Technology has afforded access and management of large amounts of information,
globalization of markets provoking organizations to adopt structures and create alliances with
different organizations to then adopt better to continuous market changes (Meaza A. ,
Cilleruelo, Zamanillo, & Zarrabeitia , 2012). A need for SME’s to understand how to create
and infuse KM related activities in their daily operations is key if they have to survive the
constantly changing markets and meet its demands.
20
2.3.1 Knowledge Creation and Acquisition.
Knowledge creation is the process in which new useful information is generated. It often
revolves around knowledge sharing within a firm and also externally (Shetty & Narayanasamy,
2008). Knowledge creation theories by Nonaka mention that creation of knowledge is the
infusion of tacit and explicit knowledge through socialization, externalization, internalization
and combination (SECI model) often made possible due to shared office spaces, emails and
conversations, experiences, ideas experiments in organizations hence regarded to as enablers of
knowledge creation (Konno, Nonaka, & Toyama, 2002). With the continued growth of small
firms, there is the need for knowledge creation and management which plays a key role in
generating competitive advantage, (Choochote K. , 2013) through innovation of new ideas
hence developing great values for core competencies of any businesses, and hence achieving
the business goals and business continuity (Tiwana, 2001).
Governments play varied roles in this from favorable policy creation to internalization. In
Europe, they provide policy frameworks and ensure that the designed policies favor the SME’s
working market in order to encourage continued innovation. In Tanzania, a clear defined
framework in relation to SME’s and growth has been laid down by the government. This
ensures continued innovation and growth of SME’s and pushes them towards achieving their
Vision 2025 (Ministry of Industry and Trade, 2003).
In Kenya, the sessional paper no. 2 of 2005: Development of Micro and Small Enterprises for
Wealth and Employment Creation for Poverty Reduction was designed to generate a framework
for SME’s in Kenya. The key interest did include the legal, tax, technology, finance and
business networks in relation to SME’s available locally (Syekei & Opijah, 2012; Government
of Kenya, 2005).This in turn led to the Micro and Small Enterprises Bill 2011 which was drafted
with the focus was on formal SME’s in the urban settings (Wanjohi, 2012). Platforms for
knowledge creation and exchange have been provided such as Jitihada Business Plan
Competition, by the government but no frameworks for knowledge management have been
presented (Kenya Institute of Management, 2009).
Financial deepening is another channel by governments to aid in knowledge creation in order
to reduce SME’s information acquisition costs. This is done through generating and
dissemination of information on SME’s leading to efficient markets in which the prices
incorporate all necessary and available information. This also opens channels in flow of
financial foreign resources to the local economies enhancing liquidity. Small firms often benefit
from these sort of grants hence training the locals on new skills and also financing research and
21
development in these firms (Ochanda, 2014). Infusion of KM practices vary from continent to
another due to their different characteristics and needs by the displayed by the SME’s. The
European Union have adopted KM practices in varied ways. In Kenya, SME’s here have access
to affordable internet and use this to acquire and exchange data, both internally and externally.
It also acts as an interactive space for customers to meet suppliers on a global scale. This is also
used to carry out research on new trends (Apak & Atay, 2014).
SME’s in the European market are important as they are the core in driving the investment and
innovation. They provide employment for its people as 98 out of 100 businesses are SME’s and
employ the bigger percentage of the work force. Due to continuous changing consumer needs
and wants throughout the markets, European governments have continuously encouraged
Innovation by its SME’s by ensuring the economic policies adopted work against market failure
that may in anyway affect SME’s growth. SME’s here enjoy government funding in research
and development as it encourages innovation and investment. Also, most medium firms have
research and development as a core department in their firms as knowledge management
practice (Abel-Koch, et al., 2015). In Kenya, few SME’s have invested in Research and
development department due to the finance constraint. The few that have this departments, have
merged this as a department in the marketing docket hence not fully maximizing the role of
research and development. The small firms are keen to encourage cultures where knowledge
can be freely shared through socialization. This could be within the firm and externally. With
European firms adopting teleworking, Some of the small firms locally have adopted
information is sharing through collaborative tools, common meal rooms and continuous breaks
are encouraged throughout working hours to facilitate conversations that result to exchange of
tacit knowledge (King W. R., 2011).
Business owners are trained by the governments through government funded projects to ensure
continued innovation amongst the SME’s. In Kenya, this is done often with the Kenya
Association of Manufacturers (Kenya Association of Manufacturers, 2017). This ensures
business continuity and job opportunities for members (Dawe & Nguyen, 2007) , External and
in-house training programs for employees to ensure they maintain existing skill sets and also
update their skills in line to improve their competences (OECD, 2013). Also, adoption of
strategic alliances and partnership to share knowledge, and adoption of a culture that promotes
sharing of knowledge across the organization using activities such as socialization by during
tea break sessions, team building activities (Svetina & Prodan, 2008). Employees in these firms
share working spaces and this provides a platform for exchange of ideas and hence knowledge
22
creation (Thang, Quang, & Son, 2013). These firms are run by individuals who often are the
business owners who supervise the operations, business plans and decision making. This makes
their busy schedules and tedious, hence insufficient time for any strategic planning. With them
facing limitations in resources such as finances and expertise, more often than not, most of the
knowledge then remains with the key employees and not stored anywhere or shared (Wong &
Aspinwall, 2004).
Knowledge acquisition by SME’s in Kenya is heavily reliant on face to face meetings with their
suppliers and customers. This could be in form of feedback from services or goods rendered,
complaints, inquiry on new products due to continued changes in preference and taste by
customers (Gumboh & Gichira, 2015).In the recent times, networking forums in varied fields
have also presented a platform for exchange of knowledge, such include SME Expo’s organized
by the Kenyan government where different stakeholders in the SME sectors to meet up and
exchange ideas (ICT Authority, 2016).
With the rise of social media and new web technologies, SME’s have also embraced knowledge
creation and acquisition from these platforms through carrying out surveys, sharing
questionnaires, blogging, presentation sharing and videos through collaboration tools to share
and acquire information (Kiveu & Ofafa, 2013) .Though social media platforms are free and
the rest affordable, most local SME’s are not fully exploiting this technologies, with some of
the SME managers against use of social media in the working premises during working hours,
and to some extent, blocking exchange of knowledge and sharing to avoid losing their
competitive nature. Blocking exchange and sharing of knowledge leads to loss of billions in
any financial year , lack of knowledge in existing best practices in specified areas of operations
and as a result, loss of business relationships and knowledgeable staff members. (Mosoti &
Masheka, 2010).
2.3.2 Knowledge Transfer and Distribution
With adoption and infusion of technology by SME’s there’s facilitation of activities such as
collaborative work using virtual teams, design of mind maps to capture knowledge,
documentation and continuous updates on lessons learnt and best practices. Small and Medium
firms in Kenya have slowly integrated social media Social media platforms such as Facebook,
LinkedIn, Instagram and Twitter have then become a key a part of the organizations day to day
activity as these are used as direct platforms where the firms can interact directly with their
existing and potential clients both locally and internationally for market-oriented and customer
23
facing processes (Meske & Stieglitz, 2013; European Union, 2013; Josee, Karemu, Kanchori,
& Okibo, 2014).
Kenyan SME’s are not very different and borrow some of the practices adopted on a global
scale. They run their operations without proper structures and organizational policies in place
and only incorporate these when need arise. SME’s have adopted flat structures. This
encourages innovation and entrepreneurship due to lack of bureaucracy and their informal
structures (Adisa, Abdulraheem, & Mordi, 2014). Due to their resource limitations especially
finances, have not adopted technology hence unable to invest in document management systems
or any database systems to harness data. The much technology in these firms is point of sale
terminals for capture of business transactions for goods and services offered. (Ongori & Migiro,
2010; Ardjouman, 2014).
Most SME’s in Kenya, run their operations in an informal manner, having incorporated
technology to harness information but lack trained human resource on knowledge creation and
management, poor attitudes towards technology and sharing of knowledge due to cultural
impediments result to inability to harness the benefits of knowledge management as a tool,
hence unable to create knowledge and manage it. (Mosoti & Masheka, 2010).The Small and
medium organizations in Kenya are mostly privately owned by individuals, and have few
employees, between five and fifty. With busy schedules and working with limited capital and
limited resources, SME’s owners barely have time to strategize, hence unable to train their
employees in regards to knowledge hence most of the employees are not keen in embracing
knowledge management practices. (Lutabingwa, William, & Kenneth, 2015).
Studies over knowledge management practices by SME’s in Kenya have established four
common processes borrowed off the Integrated Innovation framework. New knowledge for
most of the SME’s is created during reverse engineering hence evoking innovation of a new
product. Through this, a product is dismantled or a service is scrutinized to help establish a flaw
and hence need to improve the existing items. Also, a trial and error method is used for new
products or services. The product sample is released to a few members of the public with the
aim of getting a response in order to improve the item before release into the market spaces for
consumption. Knowledge application is hindered by uncertainty, in regards to the market
response to the item produced, lack of resources such as funds and lack of proper technologies
(Wangare, 2015).
24
However, SME’s find it difficult to share or exchange knowledge due to various factors such
as lack of trust with parties involved hence worried that their information may end up misused
or used to gain advantage over them by competitors hence losing out on future business hence,
they choose not to engage in this process. SME’s may be willing to share in formation but also
this becomes difficult to harness tacit knowledge off employees who have the skill sets but are
unable to communicate. (Riege, 2005) Interactive sections , exhibitions, forums to encourage
knowledge sharing in order to encourage knowledge creation are now a common phenomenon
in the Kenyan markets but SME’s tend to remain to their old ways of harnessing information
such as suppliers and client feedback and suggestions hence less innovation and inventions.
Information that is shared on this platforms include how SME’s can access financing for such
institutions and showcases, production methods of existing merchandise and services and rarely
do sessions on inter sectors knowledge sharing occur (ICT Authority, 2016).
2.3.3 Knowledge Preservation
Knowledge preservation of existing information is a challenge due to in ability to collect it.
Lack of proper ways to harness it from existing sources, when collected, improper knowledge
is collected to individuals posing the wrong questions or failure to proper communication
channels. With lack of resources such as capital and training personnel, it becomes difficult to
convert tacit to explicit knowledge. SME’s are also not keen on preserving models that aid in
production of products, as once the same are released into the markets due to the need to
continue generation of new products (Wangare, 2015).
2.4 Organizational Performance Efficiency
The adoption of knowledge management practices by firms are essential in integrating its
operations into a knowledge based economy. These practices are of different in types and forms
depending on the size of the organization. Often, if well integrated, they are directly related to
innovation. In different regions of the world, knowledge management practices are also
different in varied ways. In Basque, SME’s link their knowledge management practices to the
ability to easily access knowledge transfer channels. They attribute technology as a key factor
that aids their firms in managing the intangible resources and have embraced document
management technology platforms that enables them to capture explicit knowledge and store it
an easy to access repository for ease in transmission. (Meaza A. I., Cilleruelo, Zamanillio, &
Zarrabeitia , 2012).
25
Knowledge Management practices often affect firms in a positive manner improving
organizational performance by ensuring they are efficient and effective. Knowledge
management is said to support assimilation of knowledge by building the knowledge resource
stock and aids in transformation of knowledge, whether new or existing. This impacts an
organization positively in terms of its performance (Claiborne, 2011).Organizational
performance is key in testing the success of SME’s performance and often discussed by scholars
through strategic variables such as KM practices. Previous studies evaluate performance on
Return on assets, new product success, and market penetration, profits attained and sales growth
over a period of time and customer satisfaction. Whilst these are used to measure organizational
performances, scholars differ on assessment of organizational performance amongst the SME’s
hence different from one scholar to another. (Johnsen & McMahon, 2005) consider return on
assets, return on shareholder salaries, dividends and return on interests as the performance
indices for SME’s whilst (Koh, Demirbag, Bayrak E., Tatoglu, & Zaim, 2007) used measure
organizational performance, share and growth of market and profitability as the indices for
measuring organizational performance. (Huang, 2001) Argues that effectiveness, efficiency,
productivity, life quality, innovation, and profitability the indices to measure organizational
performance.
With all this considered viable for measuring performances, some of the key indices are used
in this study. This include productivity, financial performance, staff performance, Innovation,
work relationships and customer satisfaction. Customer satisfaction is key for any organization
to continue in business and firms ought to be responsive to customer needs if they are expected
to achieve a competitive advantage. Few studies have been done and indicate that firms that use
suitable KM practices have a chance in enhancing their organizational capabilities, which often
result to better performance. Ronald (2006) in his study indicated that performance of an
organization is dependent on a firm’s ability to integrate knowledge into their core strategies
and processes hence value addition. In addition, he stated that a firm has to also develop
efficient mechanisms to create, transfer and integrate knowledge. Zack et.al (2009) in their
research also reveal that KM practices have a positive and an indirect influence on
organizations’ financial performance and (Kiessling, Richey, Meng, & Dabic, 2009) suggested
a positive effect on organizational outcomes by KM practices.
Continuous information flow in an organization means there’s continuous learning within the
firm. This could be through various platforms such as the collaborative tools adopted within the
firm and hence exchange of knowledge. All this is supported by Information Technology within
26
the firms. Information Technology revolution has ensured that getting information is no longer
a challenge but the challenge is then obtaining quality information that can aid an institution
make key decisions that impact the firm in a positive way , ensuring competitive advantages
amongst its peers. (King W. R., 2011). With changing times, Informational technology is
widely adopted by firms to ensure its people have access to reusable codified knowledge that
facilitates conversations with an aim to create new knowledge. Exchange of ideas through
sharing or discussions elicit solutions, and a result, an organization is able to create a
competitive edge for itself. This facilitates innovation. With innovation, new ideas are
generated and as a result, creates a sustainable competitive edge (Wastyn & Czarnitzki, 2010).
Also, reduced costs are experienced by organizations when employees share knowledge and
implement knowledge management policy using a codified platforms (Zheng, Yang B., &
McLean, 2010). Organizations that have adopted management leaderships that encourage
knowledge retention amongst its organizational plans, workforce and human capital strategies
tend to success in the future as knowledge management is key in survival of any enterprise in
the knowledge based economies (Bontis & Serenko, 2009).
Technology facilitates creation, sharing, storage and use of knowledge whenever needed by the
organization. When adopted and infused into operations, Technology that supports knowledge
management in an organization is often referred to as Knowledge management systems (KMS).
They include databases, document management systems, collaboration and business intelligent
systems amongst others (Sedighi, 2006; Zhang & Zhao, 2006). Provision of platforms such as
Emails, video conferencing aids and implementation of expert and decision systems in these
provide a platform on how tacit knowledge can be retrieved off databases with ease and shared
when required. (Al-Alawi, Al-Marzooqi, & Mohammed , 2007). Due to limited capital
structures, technology is regarded expensive and hence a need for a proper plan on how to
integrate technology into these firms, clearly indicating how these will aid the firms achieve
their business goals ,objectives without deviating from their vision and mission. (Organization
for Economic Co-operation and Development, 2000).
Various researchers have highlighted in their research, what key roles technology plays in
support of Knowledge management processes. They aid in development and systemization of
knowledge management practices (Mallet, Rousseau, & Valoggia, 2006), enhance
collaborations, knowledge discovery and quick decision processes (Davenport & Prusak, 1998)
.Also a well-designed technology has the capability of integrating fragmented flows of
knowledge (Gold, Malhotra, & Segars, 2001) and in addition, technology supports all modes
27
of knowledge creation and not limited to transfer of explicit knowledge (Lee & Choi,
2003).Knowledge management is key in identifying organizational structures, firm’s processes
and technology for analyzing during the project. A well designed knowledge framework can be
used in the firm’s acquisition activities and processes. This information can be used in future to
plan for future projects in terms of resource allocation and risk identification (Haddad &
Ribière, 2007).
2.5 Conceptual Framework
Knowledge has become one of the most important driving forces for business success.
Organizations are becoming more knowledge intensive. A lot of organizations in the global
market are aware and try to understand the Knowledge Management (KM) field with an aim to
improve their businesses and remain competitive. Knowledge has always been the central in
the functioning of society. However, in today’s “knowledge economy”, organizations are
increasingly aware of the need for a “knowledge focus” in their organizational strategies as they
respond to changes in the environment. The aim of this paper is to describe the theoretical
concepts and approaches of KM process that could be implemented in organizations by
reviewing KM process theories and present suggestions for what a general process should
include based on analysis of various models presented in KM with the main emphasis on the
review of the concept of goal definition, validation ,training on knowledge processes in order
to make sure that KM process initiative delivers a competitive advantage to the organization. .
Independent Variables Dependent variable
Figure 5: Conceptual Framework
H2
KM practices adopted and
infused by SME’s
KM frameworks and
systems SME Organizational
Performance Efficiency
28
2.6 Research Gaps
The Kenyan SME’s are often a family run business, an imitated or borrowed idea or as a result
of a project in progress that transits into a business. A drive through the Nairobi Central
Business District and one cannot help but notice multiple same concept business ideas running
across the streets e.g. Mpesa shops, clothes boutique stores etc., a clear depiction of lack of
innovativeness amongst its people hence repeated ideas. The result, slow growth in the
economy (Adcorp, 2012).
Researchers identify that 65.1 percent of the Small enterprises fail within their first year of
operations due to simple management mistakes (Berisha, 2015). This is includes but not limited
to lack of business vision, lack of a valid business strategy due to “copying and paste
“tendencies, an “ad hoc” way of running these organizations using trial and error methods, use
of intuition and less analytic skills when in operation of the small firms, lack of managerial
skills, lack of training lack of networking sessions for knowledge sharing hence minimal
innovation, lack of organizational structures amongst others. These then shift the focal points
of the business to short term success and not long term resulting to their short lifetime in the
markets (Adeyeye, 2016).
2.7 Chapter Summary
This chapter has critically reviewed immense literature on key knowledge management
frameworks, effects on knowledge management practices on business operations and literature
in designing simple knowledge management system for Small and Medium Enterprises. The
next chapter will focus on the research methodology of the study
29
CHAPTER 3: METHODOLOGY
3.0 Introduction
This chapter will present the approach that will be employed by the researcher to carry out the
study. It is distinctively alienated into five sections. Section one discusses the research design
that will be adopted the study. The second Section sheds light about the population, sampling
design, sampling frame, sampling technique, and sample size. Section three will elaborates on
the data collection method. Section four discusses the research procedure employed while the
fifth section expounds on how the researcher will analyze and interpret data that will be
collected from the field of study.
3.1 Research Design
A research design is defined as a blueprint for the collection, measurement, and analysis of data.
It can also refer to the plan, organization and structure of investigation with an aim of obtaining
relevant answers to research questions or simply a framework; guiding analysis of data
collected from the field. Simply put across, the research design or plan comprises of the ultimate
master program of the research and comprises of a clear outline of what the researcher is to do
from the onset of writing of the research questions, specific objectives to the final analysis of
data.
The study approach adopted for this project was a descriptive research design. This was adopted
as the interest of this study is to depict the current situation in regards to integration of
knowledge management frameworks and their influence of on business operations amongst the
SME’s in Kenya. This was achieved through a survey amongst the Kenyan SME’s to find out
to what extent have knowledge management practices been adopted as a strategy for improving
business operations and tools such as frameworks to aid streamline the business processes.
To collect data, questionnaires were administered to various SME’s owners and employees in
firms that had adopted knowledge management practices.
30
3.2. Population and Sampling Design
3.2.1 Target Population
A target population refers to the group of events, elements, people or things of interest that a
researcher wishes to base his investigations in on any study. It incorporates all the elements
about which the researcher wish or is interested in making some inferences based on the sample
statistics (Kithae, Gakure, & Munyao, 2012; Sekaran & Bougie, 2013; Cooper & Schindler,
2014). The target population in this study were the licensed SME’s by the Nairobi County
government as per the 2015 statistics. An estimated 65,000 SME’s are based in Nairobi, of
which 400 have their business operations around the Westlands area. The Target population for
this research was drawn from SME’s business ventures operating in Kenya, which are not in
any way, homogeneous in nature. The study focused on about 113 SME business that are
involved in both service and production. The figure was settled on due to a number of factors.
The firms in question had to at least display various characteristics of SME’s ,avoided startups
and had to have at least been practicing Knowledge management within for a minimum of six
months to be able to share valid data across to aid in research purposes.
Table 3: Population Distribution
Business Type Population
Colleges 13
Supermarkets 7
Bars 15
Casinos 6
Boutiques 115
Banks 17
Chemists 27
Kindergartens 6
Butcheries 12
Restaurants 22
Beauty shops 35
Curios 252
Green Groceries 14
Mechanics 12
Hotels 12
565
3.2.2 Sampling Design
3.2.3 Sampling Frames
Sampling frame is a list or procedure to identify all elements of a target population .It involves
collection of data from samples selected and identified for observations and analysis.
31
(Walliman, 2011). The researcher prepared a list of the identified SME’s operating in the area
of study as some are not registered with the County Council or the registrar of companies.
3.2.4 Sampling Technique
Sampling is the process of selecting the number of observations cases to be examined off the
large identified group or population. This data may be collected from the whole population
popularly called censors or can be collect data from a smaller part of the population referred to
as a sample. The study used the simple random sampling to select the one hundred and thirteen
owners and employees from the sampling frame of five hundred and sixty five SME’s. This
was considered an appropriate figure for the descriptive survey.
3.2.5 Sampling Size
The sample size is a smaller set of the larger population (Cooper & Schindler, 2006).
Determining the sample size will be very important in the collection of accurate results within
quantitative survey design. The bigger the sample size, the better the chances for more accurate
information. Mugenda (2003) states that the sample ought to be carefully selected to be the
representative of the whole population and the need for the researcher to make sure that the
subdivision entailed in the analysis is accurately catered for.
The Sample size was determined by how many people were to be interviewed and to get results
that did reflect the target population as precisely as possible. The sample size is dependent on
the population and confidence level. The confidence level is regarded as the margin of error
expected in a sample. Using a confidence level of 90 percent and the sample size of the SME’s
is 565, Formula used to achieve the sample size:
Where n is the desired sample size (113)
n = N
1+Ne2
n = 565 n= 214
1+565(0.1)2
32
N is the population size (565)
And e is the margin of error (0.1)
From a business population of 565 SME’s 113 were picked. Below is the strata table:
Table 4: The Strata Table
Strata Population Proportion Sampling
Percentage
Sample
Size
Colleges 13 0.3016449 30.16% 4
Supermarkets 7 0.8359718 83.60% 6
Bars 15 0.17977059 17.98% 3
Casinos 6 0.94305502 94.31% 6
Boutiques 115 0.78312725 78.31% 90
Banks 17 0.32472466 32.47% 6
Chemists 27 0.57454677 57.45% 16
Kindergartens 6 0.598211 59.82% 4
Butcheries 12 0.47916257 47.92% 6
Restaurants 22 0.63629094 63.63% 14
Beauty shops 35 0.54755492 54.76% 19
Curios 252 0.0682383 6.82% 17
Green Groceries 14 0.467104 46.71% 7
Mechanics 12 0.96976849 96.98% 12
Hotels 12 0.58236491 58.24% 7
565 214
3.3 Data Collection Methods
Data collection is a process of gathering and measuring information on targeted variables in an
established systematic manner, which as a result enables one to answer relevant research
questions and evaluate the given outcome. For this research, primary data was used by
employing a survey method. Cross-sectional survey structure was adopted in collecting data
from respondents in the field. This method was adopted because it is well known and often
takes a snap shot of a population at certain times thereby permitting conclusion relating to
phenomena in a wide population to be drawn. It is mainly preferred since because it is concerned
with answering definite questions such as who, how, what which, when and how much (Kariuki
& Waiganjo, 2014; Cooper & Schindler, 2014).A self-administered questionnaire was the tool
of choice to collect data. A questionnaire as a data collection tool was used because of its three
unique advantages. First, a questionnaire is practical in nature and the respondent simply
participates by filling out the questions. Secondly, large amounts of information can be
collected from a huge number of individuals in the field during a short period of time and in a
comparatively cost effective way. Thirdly, the questionnaire can be administered by the
33
researcher himself or by any number of people authorized by the researcher with limited effect
to its validity (Cooper & Schindler, 2014). The questionnaire for the study was be divided into
five main sections. Sections one gathered data related to the demographics. These are items
related to things such as gender, age, and job status. The second section collected information
pertaining the first specific objective on key knowledge management frameworks. Sections
three gathered data on effects of current knowledge management practices on business
operations. Lastly, the fourth section collected information pertaining the development of
knowledge management framework and system presented that can be used for SME’s in Kenya.
The researcher got consent from United States International University and obtained a letter of
introduction to the respondents. The researcher also sought consent from the SME owners and
human resources to carry out the study in their organizations. The questionnaires were
distributed in two ways, through emails and also through physical copies administered by the
researcher. This was necessary in case any clarifications that needed to be done.
3.4 Research Procedures
Sekaran and Bougie (2013), argue that the main advantage of personally administered
questionnaire is that the researcher or at times a member of the research team can gather all the
completed responses within a short time and any query or doubt arising from respondent can
be clarified on the spot. A total of 113 questionnaires were handed out in the end of the study
because of the strict budget. 77 to the SME’s owners ,management and key decision makers in
a business, and 35 to the respective employees of these firms who had been working for an
average of 3-5 years in the same firms.
3.5 Validity & Reliability
The content validity of the research instrument was ascertained by the consulting lecturer on
the extent to which the questionnaire topics represent the topics and themes in the area of study.
In order to test and ascertain whether the questionnaire generated consistent measurements, a
test- retest pilot study was conducted within two SME’s a week before the actual questionnaire
distribution. These questionnaires did not form part of the final study. Off the two, a reliability
check using the Pearson Product Moment correlation technique was adopted. According to
Cooper and Schindler (2014), pilot testing is mainly conducted to help the researcher detect any
weakness in design and instrumentation as well as providing proxy data for selection of
probability sample.
34
3.6 Ethics
The researcher did obtain consent to carry out the study from the university, The Human
Resource Managers and employees in the study. The researcher also assured respondents that
the information shared would be treated with utmost confidentiality. This is clearly articulated
in the letter from the researcher and University to the respondents seeking permission to collect
this information from them and containing these assurances. (Attached on Appendix A).
3.7 Data Analysis Methods
The participants had five working days to ensure that the data has been remitted or questionnaire
filled up. The researcher collected the physical copies of the questionnaires and the others
remitted via email. A reminder was sent on day three to all participants. The questionnaires will
be scrutinized for consistency and completion of information provided. The researcher will then
code the items on a code book to guide data key in on a spreadsheet ready for analysis. The data
will then be analyzed using SPSS, a descriptive statistics software. The results will be presented
in form of frequencies, percentages and also relevant graphics such as bar graphs, pie charts
amongst others. SPSS is often used because of its said advantages of offering a variety in data
products such as at the data entry builder and data editor. A data editor is similar to an excel
sheet with ease to view data/ contents stored in these files (Mbogo, 2011).
Themes were used to analyze the qualitative data off the open ended items. The qualitative data
was analyzed using Likert scale and the results visually represented using charts, tables and
pies. SPSS was used to perform normality and reliability tests and generate reports of the
statistics showing various features such as chi-square tests of associations and regression.
Regression shows the direction in which variables move as they change after performing an
analysis the regression statistics will be used to predict the dependent variable when the
independent is unknown. In this case, to establish a relationship between knowledge
management frameworks, SME’s Success and business continuity. The regression model was
of the form;
Y = β0 + β1X1 + β2X2 + β3X3 + β4X4 + ε
Where:
Y= Organizational performance
β0 = Regression Constant
X1= Knowledge Source
X2= Knowledge Type
35
X3= Knowledge Process
X4= Knowledge Breadth
ε = Error term
The information was represented in form of graphs, pie charts and table. As a result, ease in
users to accessing credible information with ease.
3.8 Chapter Summary
This chapter discussed the research methodology. The research design was discussed first
where the researcher defined research design and the type of design used in the study. The
chapter then explained the target population for the study. The researcher elaborated on
sampling design, sampling frame, sampling technique and the sample size. Data collection
methods was expounded upon including the instrument used to collect data. A research
procedure was also deliberated upon. The chapter finally discussed data analysis methods for
the study.
36
CHAPTER 4: MODEL
4.0 Introduction
The Chapter in detail elaborates the solution offered in this case, a detailed suggestion as to
how the Knowledge Management framework is designed and is to work.
4.1 Analysis
There are many models that have been designed and published in relation to knowledge
management. However, they tend to focus on large organizations while this research has its
interest on the small and medium enterprises (Choochote & Nurse , 2013).
Kenyan SME’s Exhibit very unique characteristics. Their lack of capital, operation on
minimalistic finances, “adhoc” business operations make it difficult for them to adopt the pre-
existing knowledge management frameworks in the market. The pre- existing frameworks have
been designed for large organizations and few for SME’s in developed countries hence may
force the firms to change their business operations to suit what is in the market and not their
initial intended operations, hence losing the business vision (SME Toolkit Kenya, 2016;
Kedogo, 2013). The result, a shorter lifespan or no business at all. From the research done, it’s
clear, there’s a need for a proper framework that considers all challenges both mentioned and
the unmentioned.
4.2 Modeling and Design
Many SME’s find it difficult to design their own knowledge management strategy. Probably to
lack of the know-how on how to design one. The model below is simple to understand and use
and has taken into consideration, our local SMEs and their unique needs. The result, SME’s
that are able to innovate their own products and hence achieve a competitive advantage.
.
37
Figure 6: Knowledge Management Model for SME’s in Kenya.
The AEDS model combines four elements when effectively combined ought to generate a
viable strategy that could easily be transformed to a viable framework for the Kenyan SME’s.
Each of the components will be further discussed below.
Acquire is the first phase of the Model. Under this, several activities are listed within the same.
The SME must be fully aware of its business operations. They would need to have an articulate
vision, mission, motivation and plan. This would need to be articulated to the business
members, employees or documented by the vision bearer if it’s a sole proprietor ship or a family
business. The members would need to understand the precise business operations, the business
goal and their roles in these organizations. A clear role display ensures no repetitive roles.
The vision bearer also needs to share his knowledge on past channels used to achieve business
competitiveness, business continuity and growth. In cases where the firms are pre-existing or
have been in business, research and discovery of new knowledge could be done from existing
customer data and from the same evaluate client trends. This would aid in innovation of a new
product
Acquire/ Create
Enrich
Distribute
Sustain / Divest KM
S
38
Figure 7: A Visual of the Processes within the Process Acquire / Create
Enrich
Enrich is the second phase of the model. This revolves around the knowledge already shared or
harnessed from the business being applied to the business in order to generate;
a) A solution to a pre-existing problem
b) To value add in order to innovate or invent
c) To trigger socialization that leads to exchange of information/ knowledge
d) To manage the existing organizational policies with an aim to meet the existing
Business goals.
The firms need to provide mechanisms or make provision for avenues where its workforce can
be in a position to share experiences, interact
Figure 8: A Visual of the Processes within the Process Enrich
Acq
uir
e
Awareness
Understand
Create/DiscoverE
nri
ch
Apply/ Use
Value Addition
Manage
39
Distribution
This is the third phase of the model. All the information harnessed, it can either be re-
engineered, stored or shared across to the departments to ensure it benefits all parties in place.
This phase is critical as the data is in this case needs to be “right for consumption” before
distribution. This ensures its maximized benefits to the organization, meets the organization’s
needs in terms of its business strategy. In case of errors, new additions to existing
Figure 9: A Visual of the Processes within the Process Distribute.
Sustain/ Divest
Regarded as the final phase in this model. Useful information and data then are kept and are
readily accessible and any obsolete data, may then be discarded over time due to changing
business needs. The stored information may be developed further to innovate/invent or it may
be re-engineered to generate a new business idea as a result, either new business ideas hence
business continuity ,stored for access for future references or the pre-existing firm achieves
efficiency and effective business operations. Once this is done, the process begins afresh and
the cycle continues.
Figure 10: A Visual of the Processes within the Process Sustain/ Divest
Distribution
Re-create
Store
Share
Assess
40
Figure 11: The Suggested AEDS Knowledge Management Framework
41
4.3 Proof of Concept
Modeling
Figure 12: Hypothesis on KM practices, Frameworks and Systems.
For this research, the value H1 evaluates Knowledge Management Practices and their effects
on Efficiency and Effectiveness, H2 evaluates Knowledge Management Frameworks and
Systems and their effects against efficiency and effectiveness.
Figure 13: Flow of Information from the Different Processes
KM practices adopted and
infused by SME’s
KM frameworks and
systems Efficiency &
Effectiveness
H1
H2
42
The diagram below will test the AEDS Framework using a case scenario to further using actual
information to see if it meets an SME’s Needs.
Case scenario: A client issues feedback. The AEDS Acting as CMS to provide a client with a
solution/ reaction to the issues presented.
Figure 14: AEDS Framework used to evaluate Feedback to the Firm.
43
Table 5: Flow of the Implementation and Test Criteria.
Value Knowledge
Management Goals
Knowledge
Management
Strategy
Implementation
Efficiency &
Effectiveness
Improve /Streamline
daily business
operations with
embedded business
processes.
Systematically capture,
evaluate & share
knowledge
~Identify viable sources
of information and link
relatable ones.
~Design and develop a
repository for feedback.
~ Design and share roles
/ responsibilities for
team members
~Identify policies, flows
that work for the firm.
Competitiveness Stimulate continued
innovation/ invention
Value addition through
further research,
~ Provide hubs/ avenues
for knowledge
exchange.
~Reward new ideas
Business Continuity Encourage knowledge
units sharing between
staff and adoption of
simple ,existing and
affordable technology
Distribution ~ Embrace
organizational social
media pages as such as
closed groups as
avenues for knowledge
sharing.
The above must be supported by Knowledge Management components for them to
materialize. This includes, Human capital, Processes and Technology.
4.4 Chapter Summary
This chapter using visuals helps understand further the suggested knowledge management
framework for the SME’s and further puts into test the suggested processes to see if they can
actually be used to generate a viable solution . The next chapter shares the results and findings
off the field surveys done in relation to the project.
44
CHAPTER 5: RESULT AND FINDINGS
5.0 Introduction
This chapter presents the findings and discussions of the study. The findings and discussion are
presented according to the research objectives. The researcher conducted an analysis of the
descriptive statistics of the research variables and presented the findings. The findings from the
research study are presented in table form and figures. The response rate was 25 respondents
out of the sampled 45, which is slightly above fifty percent.
5.1 Demographics
The researcher considers the background information to be very meaningful because of the role
it plays in enabling the understanding of the logic of the responses issued by the respondents of
each respective organization. The study sought to establish general information of the identified
respondents in the study where the study sought to establish what industry the company is in,
the nature of business, education level, the number of years the company has been in operation
and to establish whether the company is registered with the ministry of trade.
5.1.1 Gender of Participants
Pertaining the gender of respondents, 13 respondents were male (representing 52%, N=25)
while 12 participants (accounting for 48% of the total respondents). The pie chart below shows
these statistics clearly;
Figure 15: A Pie chart on Participants vs. Gender
Male13(52.0%)
Female12(48.0%)
GENDER OF PARTICIPANTS
45
5.1.2 Age of Respondents
The study sought to find out whether the age distribution of respondents in the SME industry.
Among the respondents who responded to the questionnaire, 4 respondents (16%, N=25)
indicated that they were between 21 and 25 years of age. The majority group consisted of 7
respondents (28%, N=25) who were aged between 26 and 30 years of age. 6 participants (24%,
N=25) indicated that they were between 31 and 35 years of age. 4 respondents were aged
between 36-40 years. 2 respondents (8% of the total sample population) were between 41 and
45 years of age.
Figure 16: A Bar Graph showing the Varied Age Groups
5.1.3 Position in Business
The study went further to determine the position in business the respondent occupied and the
study was able to find the following responses as displayed in the figure 4.2. The figure shows
that a majority 68.0% were employees, 24.0% were the entrepreneurs or business owners. The
2 missing values accounted for all our 25 respondents.
46
Table 6: Position in Corporate Business
Frequency Percent Valid Percent
Cumulative
Percent
Valid Entrepreneur 6 24.0 26.1 26.1
Employee 17 68.0 73.9 100.0
Total 23 92.0 100.0
Missing System 2 8.0
Total 25 100.0
5.1.4 SME Categories
The study went further to determine the category of industries the SMEs fall into and the study
was able to find the following responses as displayed in the figure 4.3. The figure shows that a
majority 36% were consultancy companies, while minority were transport and logistics as well
as building and construction companies.
Figure 17: Different Sectors Covered within the Survey
Manufacturing2(8.0%)
Transport and logistics1(2.0%)
Consultancy9(36%)
Building and construction
1(4.0%)
Service providers3(12.0%)
Higher Education2(8.0%)
Hospitality/Clinic2(8.0%)
Telecommunication
2(8.0%)
POSITION IN CORPORATE BUSINESS
47
5.1.5 Years in Operation
The study went further to determine the number of years the company has been in operation
was able to find the following responses as displayed in the figure 4.4. The histogram shows
that the mean number of years the company has been in operation was 6.6 years and the standard
deviation was 2.693
Figure 18: Histogram showing Years in Operation
5.1.6 Gross Turnover
The study sought to establish the financial position of the company by outlaying its gross
turnover. Among the respondents who responded to the questionnaire, majority of the
companies (12 companies) attained a gross turnover of between 4-10 million Kenya shillings,
6 companies indicated that they attained a gross turnover of between 3-4 million. 4 companies
reported a turnover greater than 10 million. Only 1 company attained a gross turn over between
2-3 Million Kenya Shillings. The clustered bar chart below shows these statistics;
48
Figure 19: Bar Graph comparing Gross Turnover
5.1.6 Level of Education
The study sought to establish the level of education of respondents. It found out that majority
of the respondents (11 participants) had attained a university degree, and 36% had a master’s
degree. Least of the respondents had a college certificate and Doctorate degrees in the higher
end, which contributed to lower than 10% of the population.
Table 7: Highest Level of Education
Frequency Percent Valid Percent
Cumulative
Percent
Valid Certificate 1 4.0 4.2 4.2
Diploma 2 8.0 8.3 12.5
Degree 11 44.0 45.8 58.3
Masters 9 36.0 37.5 95.8
Doctorate 1 4.0 4.2 100.0
Total 24 96.0 100.0
Missing System 1 4.0
Total 25 100.0
49
5.1.7 Number of Directors
The study sought to establish the number of directors the company the company had since its
inception. The study found out that the mean number of directors was 4, with a deviation of a
figure of 2. The maximum number of directors indicated was 12 directors while the minimum
was 2 directors.
Table 8 : Number of Directors
Statistics
Number of directors the SME has
N Valid 24
Missing 1
Mean 4.25
Median 4.00
Mode 4
Std. Deviation 2.132
Variance 4.543
Range 10
Minimum 2
Maximum 12
5.1.8 Nature of the Business
Pertaining the nature of business, the majority 19 companies (76.0% of the total population)
were private limited companies. 3 companies were NGO while only one company was a CBO
as shown in the table summary below.
Table 9: Nature of the Business
Frequency Percent Valid Percent
Cumulative
Percent
Valid Private Limited Company 19 76.0 82.6 82.6
NGO 3 12.0 13.0 95.7
CBO 1 4.0 4.3 100.0
Total 23 92.0 100.0
Missing System 2 8.0
Total 25 100.0
50
5.1.9 Company Registration with the Ministry of Trade and Industry
The figure below shows that 21 companies (84.0% of the total population) were registered with
the ministry of trade and industry. 4 companies had not registered with the ministry of trade
and industry as shown in the figure below.
Figure 20: Number of Firms Registered by Ministry of Trade
5.1.10 Organizational Structure
The statistics on the year the firm started showed that most firms were started in 2004. The
newest firm was formed in 2015 while the earliest was formed in 1995. Pertaining the number
of workers the company had at start, most companies showed that they had 2 workers at the
beginning, the mean was approximately 8 workers while the range was 39 workers. The
statistics on the number of workers the company has at present showed that on average a
company had 36 workers while the range was 196 (Maximum = 200 workers while Minimum
= 4 workers) with a deviation of 38 workers. The statistics on the number of business branches
the business has at start showed that on average most companies started with one branch. The
statistics on the number of business branches the business has at present showed that most
companies have 3 branches at the time the research was being done, as shown in the table below.
21(84.0%)
4(16.0%)
IF THE COMPANY IS REGISTERED WITH THE MINISTRY OF TRADE AND INDUSTRY
Yes No
51
Table 10: Firm Structures
Statistics
Year the firm
started
Number of
workers
company had
at start
Number of
workers
company has at
present
Number of
business
branches the
business had at
start
Number of
business
branches the
business has at
present
N Valid 24 25 25 25 25
Missin
g
1 0 0 0 0
Mean 2004.67 7.52 35.80 1.24 2.68
Median 2003.50 5.00 31.00 1.00 2.00
Mode 1999a 2a 7a 1 1
Std. Deviation 5.387 8.392 38.831 .436 2.231
5.2 Knowledge Management Frameworks Influence on SME Performance Efficiency
5.2.1 Influence of KM Frameworks on SME Performance Efficiency
The study sought to establish which Knowledge management frameworks and their Influence
on SME Performance Efficiency. Table 12 and Figure 21 shows that IBM Corp. (2001) is the
most used among the respondents (37%), while CEN – Comite´ Europe´en de Normalisation
(2003 is the least used or least popular framework as shown in the Figure 21 using the key
shown in Table 11.
Table 11: Key for Codes Used in the Analysis
Code Institutional origin Name of framework
FRA1 Science, Davenport/Prusak (1998).
FRA2 Science, Heisig (2000).
FRA3 Enterprise, IBM Corp. (2001).
FRA4 Enterprise Siemens AG (Ehms/Langen 2002).
FRA5 Management Consultant APQC/Arthur Andersen (1996
FRA6 Management Consultant
FRA7 Associations EIRMA – European Industrial Research Management
Association (1998).
FRA8 Associations CEN – Comite´ Europe´en de Normalisation (2003).
FRA9 Standardization bodies SAI – Standards Australia International (2001).
FRA10 Standardization bodies GKEC – Global Knowledge Economics Council (Vaupel
2002).
52
Table 12: Various Knowledge Management Frameworks and their Adoption by Various
Firms
Frequency
of
Framework
Usage
FRA1 FRA2 FRA3 FRA4 FRA5 FRA6 FRA7 FRA8 FRA9 FRA10
Percent Percent Percent Percent Percent Percent Percent Percent Percent Percent
Do not use 20.0 24.0 8.3 45.8 32.0 44.0 16.0 52.0 12.0 37.5
Slightly Used 36.0 32.0 0.0 8.3 20.0 4.0 44.0 12.0 8.0 8.3
Used
Averagely
20.0 16.0 20.8 8.3 8.0 16.0 4.0 0.0 28.0 16.7
Used greatly 24.0 24.0 37.5 25.0 28.0 20.0 16.0 16.0 24.0 12.5
Used fully 0.0 4.0 33.3 12.5 12.0 100.0 20.0 20.0 28.0 25.0
Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
Figure 21 clearly shows that IBM Corp. (2001) –FRA3 and SAI – Standards Australia
International (2001) –FRA9 are the most used KM frameworks, while Davenport/Prusak (1998)
and SAI – Standards Australia International (2001) are the least used KM frameworks.
Figure 21:Framework Mean Score on a Five Point Likert Scale
5.2.2 Principle Component Factor Analysis Loadings
The result of factor analysis are shown in the Table 13. All factors measuring the dependent
variable organizational; performance efficiency loaded into one component namely component
1. Consequently, the 24 items were recoded as OPE1 to OPE14 for further analysis.
53
Table 13: Rotated Component Matrixa
Components 1 2 3 4 5 6 7 8 CAP1 .836 .228 .022 .079 .048 -.058 .198 .176 CAP2 .809 .149 .059 -.135 .127 -.014 .319 .039 CAP3 .776 -.001 .177 .254 .166 -.039 .252 .116 CAP4 .787 -.003 .166 .502 .019 -.057 .198 .018 GRO1 .730 .137 .039 .293 .102 .297 .427 .020 GRO2 .852 .
2
6
1
.024 .038 .170 .187 .220 -.018 GRO3 .807 .383 -.156 .176 .064 -.108 .163 -.018 GRO4 .733 .359 -.251 .169 -.096 -.103 .140 .043 GRO5 .746 .339 -.264 -.009 -.096 -.116 .301 .096 OFE1 .803 .359 -.110 -.050 -.160 .045 -.121 .180 OFE2 .874 .157 -.280 -.051 .012 .020 -.165 .072 OFE3 .724 .267 -.075 .332 .230 -.253 -.086 .146 OFE4 .790 .255 -.055 .221 .219 .024 .044 .039 STA1 .809 .340 -.297 .156 -.036 .141 .103 .045 STA2 .826 .463 -.160 .023 -.030 .089 .073 .118 STA3 .835 .132 -.265 -.229 -.011 .212 .008 -.041 STA4 .750 -.117 -.125 .084 .364 .303 .123 .006 COM1 .848 .169 .094 -.093 .056 .159 .138 .319 COM3 .774 .332 -.185 -.028 -.252 -.104 -.068 .197 COM4 .800 .274 -.084 -.081 -.095 -.025 -.155 .210 COM5 .697 .136 -.011 -.106 -.219 -.125 .128 .488 COM6 .858 .159 .002 .057 -.007 .138 .112 .197 COM7 .776 .147 .133 .008 .352 -.206 .124 .117 COM8 .827 -.073 .169 .088 .321 .168 -.009 .012 FRA1 .311 .846 .137 -.134 -.154 .155 -.036 .006 FRA2 .192 .871 .201 -.140 -.135 .088 -.008 -.163 FRA4 .407 .844 .233 .148 .058 .080 .068 .015 FRA5 .266 .899 -.058 .060 -.016 .100 -.042 .104 FRA6 .172 .875 .063 -.003 .097 .115 .189 .305 FRA7 .239 .862 .158 .084 .260 -.044 .146 .176 FRA8 .281 .866 .121 .088 .283 -.025 .165 .056 DIC1 .034 .519 .651 -.401 -.004 .104 -.082 -.043 DIC2 -.153 .167 .701 .016 .106 .252 .420 -.085 DIC3 -.277 .218 .814 .022 .072 -.012 -.269 .162 DIC4 -.051 .158 .851 .026 -.019 .098 -.181 .103 DTP3 .275 -.003 -.047 .731 -.343 .124 .200 .182 DTP4 -.025 .014 -.032 .924 .098 .185 .046 -.122 ABI1 .427 .141 -.001 .003 .774 .304 -.031 -.105 ABI2 .035 .063 .063 -.063 .883 .008 .137 -.020 UOG21 .137 .083 .089 .298 .031 .882 .165 .020 UOG22 -.032 .244 .190 -.004 .146 .872 -.045 .064 CRO1 .286 .159 -.184 .266 .116 -.033 .816 .062 CRO2 .479 .144 -.281 .020 .067 .254 .659 .048 UOG11 .429 .249 -.004 -.040 .019 -.105 .244 .749 UOG12 .274 .064 .170 .056 -.073 .170 -.113 .795
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 9 iterations.
The Table 14 is showing the Eigen values and percentage of variance on the dependent
variable that are explained. In the middle section of this table are the eigenvalues and
percentage of variance explained for the eight factors of the initial solution that are regarded
as significant. Certainly the factor number one of the initial solution is contributing 46.139
and hence much more important than the other factors. However, in the right hand part of
the table, the eigenvalues and percentage of variance explained for the eight rotated factors
are displayed. Whilst, taken together, the eight rotated factors explain just the same amount
of variance, 87.133% as the eight factors of the initial solution. The effect of rotation is to
54
spread the importance more or less equally between the eight rotated factors. You will note
in the above table that the eigenvalues of the rotated factor are, 37.078, 16.248, 7.271, 5.713,
5.538, 5.502, 5.401, and 4.635, compared to 46.189, 12.676, 7.732, 5.649, 5.01, 4.157,
3.397, and 2.578 in the initial solution.
Table 14: Total Variance Explained
Total Variance Explained
Comp
onent
Initial Eigenvalues Extraction Sums of Squared
Loadings
Rotation Sums of Squared
Loadings
Total % of
Variance
Cumulative
%
Total % of
Variance
Cumulati
ve %
Total % of
Variance
Cumul
ative
%
1 20.785 46.189 46.189 20.785 46.189 46.189 16.685 37.078 37.078
2 5.704 12.676 58.865 5.704 12.676 58.865 7.312 16.248 53.327
3 3.479 7.732 66.596 3.479 7.732 66.596 3.272 7.271 60.598
4 2.542 5.649 72.246 2.542 5.649 72.246 2.571 5.713 66.310
5 2.254 5.010 77.255 2.254 5.010 77.255 2.492 5.538 71.848
6 1.871 4.157 81.413 1.871 4.157 81.413 2.476 5.502 77.351
7 1.529 3.397 84.810 1.529 3.397 84.810 2.431 5.401 82.752
8 1.160 2.578 87.388 1.160 2.578 87.388 2.086 4.635 87.388
9 .991 2.203 89.590
10 .811 1.803 91.394
11 .712 1.582 92.975
12 .657 1.461 94.436
13 .553 1.230 95.666
14 .416 .924 96.589
15 .357 .793 97.382
16 .316 .702 98.084
17 .243 .540 98.624
18 .209 .464 99.089
19 .176 .390 99.479
20 .156 .347 99.826
21 .078 .174 100.000
The results of factor analysis eliminated the items of the factor “Competence development and
management based on competences” from further analysis since the measuring items did not
load together for this construct. Further, then factor “An understanding of the organization as a
global system” items loaded into two separate components namely UOG1 and UOG2. These
factors shown in Table 15 were retained for further analysis.
55
Table 15: Codes Used for Knowledge Management Frameworks and Practices
Code Meaning
DTP Orientation towards the development, transfer and protection of knowledge CRO Continuous learning in the organization UOG1 An understanding of the organization as a global system1 UOG2 An understanding of the organization as a global system2 DIC Development of an innovative culture that encourages R&D projects ABI Approach based on individuals COM Competence development and management based on competences FRA KM Frameworks
OPE Organizational Performance Efficiency
5.2.3 Instrument Reliability
The reliability of a measure indicates the extent to which the measure is without bias or error
free and hence offers consistent measurement across time and across the various items in the
instrument (Straub, Boudreau, & Gefen, 2004). According to Sekaran (2003), the purpose of
reliability is to assist in assessing the goodness of measure, and indicates accuracy in
measurement. This study used the most popular test of inter-item consistency reliability that is
the Cronbach’s Alpha coefficient (Sekaran, 2003) Table 16 presents the Cronbach’s
coefficient alpha for the constructs Items. According to Sekaran (2003), reliabilities less than
0.6 are considered to be poor, those in the 0.7 range, acceptable, and those over 0.8 good.
Table 16: KM Practices Constructs Cronbach’s Alpha
Construct Items Cronbach’s Alpha Comment
OPE 24 0.982 Good
FRA 7 0.968 Good
DIC 4 0.844 Good
DTP 2 0.790 Acceptable
ABI 2 0.694 Acceptable
UOG2 2 0.848 Good
CRO 2 0.886 Good
UOG1 2 0.676 Acceptable
From the correlation Table KM frameworks denoted by FRA have a positive and significant
relationship (r=0.561) with Organizational Performance Efficiency (OPE) at 99% confidence
interval. This proves our proposition that Knowledge management frameworks have an
influence in the organizational performance of SMEs.
56
5.2.4 Pearson Correlations for KM Frameworks and Practices
Table 17 presents the Pearson correlation coefficients for KM Frameworks and Practices used
by SMEs
Table 17:Pearson Correlations for KM Practices
OPE FRA DIC DTP ABI UOG2 CRO UOG1
OPE 1 .
FRA .561** 1
DIC -.035 .421* 1
DTP .268 .028 -.163 1
ABI .298 .258 .133 -.075 1
UOG2 .141 .264 .225 .248 .257 1
CRO .559** .376 -.091 .175 .308 .159 1
UOG1 .593** .448* .147 .122 .046 .079 .310 1
**. Correlation is significant at the 0.01 level (2-tailed).
*. Correlation is significant at the 0.05 level (2-tailed).
5.2.5 Regression Analysis for KM Frameworks and Practices
The Table 18 shows the variables entered in the regression to investigate the aim of objective
one of this study. These are Orientation towards the development, transfer and protection of
knowledge-(DTP), Continuous learning in the organization-(CRO), An understanding of the
organization as a global system1-(UOG1), An understanding of the organization as a global
system2-(UOG2), Development of an innovative culture that encourages R&D projects-(DIC),
Approach based on individuals-(ABI), Competence development and management based on
competences-(COM), KM Frameworks-(FRA), and Organizational Performance Efficiency-
(OPE). Where the last one is the dependent variable and the other are the independent variables.
57
Table 18: Variables Entered/Removed a
Model Variables
Entered
Variables
Removed
Method
1
UOG1, ABI,
DTP, DIC,
UOG2, FRA,
CROb
. Enter
a. Dependent Variable: OPE
b. All requested variables entered.
This Model Summary Table 19 displays R, R squared, adjusted R squared, and the standard
error. R is the correlation between the observed and predicted values of the dependent variable
- Organizational Performance Efficiency-(OPE). The values of R range from -1 to 1. The sign
of R indicates the direction of the relationship (positive or negative). The absolute value of R
indicates the strength, with larger absolute values indicating stronger relationships. R squared
is the proportion of variation in the dependent variable explained by the regression model. The
values of R squared range from 0 to 1. In this case R Square= 59.6% is the percentage of
variations that are explained by the model. The value 59.6% sufficiently shows that the models
adequately fits the population.
Table 19: Model Summaryb
Model R R
Square
Adjusted
R Square
Std. Error of
the Estimate
Change Statistics Durbin-
Watson R Square
Change
F
Change
df1 df2 Sig. F
Change
1 .772a .596 .394 .69594 .596 2.947 7 14 .040 2.415
a. Predictors: (Constant), UOG1, ABI, DTP, DIC, UOG2, FRA, CRO
b. Dependent Variable: OPE
Besides R-squared (as presented above in Table 19), this study also used ANOVA (Analysis of
variance) to check how well the model fits the data. From the results shown in the ANOVA
Table 20, the F statistic is the regression mean square (MSR) divided by the residual mean
square (MSE). When the significance value of the F statistic is small (smaller than say 0.05)
then the independent variables do a good job in explaining the variation in the dependent
variable- Organizational Performance Efficiency-(OPE). On the other hand when the
significance value of F is larger than the threshold 0.05, then the independent variables do not
58
explain the variation in the dependent variable, and usually the null hypothesis that all the
population values for the regression coefficients are 0 is accepted. In this study we observe that
the significance of 0.040<0.05 hence we accept the proposition that the independent variables
- Orientation towards the development, transfer and protection of knowledge-(DTP),
Continuous learning in the organization-(CRO), An understanding of the organization as a
global system1-(UOG1), An understanding of the organization as a global system2-(UOG2),
Development of an innovative culture that encourages R&D projects-(DIC), Approach based
on individuals-(ABI), Competence development and management based on competences-
(COM), and KM Frameworks-(FRA), explain the variations in the dependent variable.
Organizational Performance Efficiency-(EFE).
Table 20:ANOVAa for KM Practices
Model Sum of
Squares
df Mean
Square
F Sig.
1
Regression 9.993 7 1.428 2.947 .040b
Residual 6.781 14 .484
Total 16.773 21
a. Dependent Variable: OPE
b. Predictors: (Constant), UOG1, ABI, DTP, DIC, UOG2, FRA, CRO
After checking for the model fit, the analysis proceeded to find the relative importance of
each independent variable in predicting the dependent variable- Organizational Performance
Efficiency-(EFE). The unstandardized (B) coefficients are the coefficients of the estimated
regression model. In this study the regression equation can be written as follows:
Organizational Performance Efficiency-(EFE) =0.2+0.248*FRA - 0.291*DIC + 0.98*DTP
+0.216*ABI - 0.029*UOG20+ 0.259*CRO + 0.429*UOG1
59
Table 21: Regression Coefficients a SME Performance Efficiency Constructs
Model Unstandardized
Coefficients
Standardized
Coefficients
T Sig. 95.0% Confidence
Interval for B
Collinearity Statistics
B Std.
Error
Beta Lower
Bound
Upper
Bound
Toleranc
e
VIF
(Constant) .200 1.820 .110 .914 -3.702 4.103
FRA .248 .149 .363 1.661 .119 -.072 .567 .604 1.656
DIC -.291 .266 -.232 -1.092 .293 -.862 .280 .638 1.567
DTP .098 .280 .067 .350 .732 -.503 .699 .788 1.269
ABI .216 .241 .170 .897 .385 -.300 .732 .800 1.250
UOG2 -.029 .245 -.023 -.118 .908 -.555 .497 .748 1.338
CRO .259 .257 .222 1.010 .330 -.292 .810 .598 1.673
UOG1 .429 .236 .347 1.820 .090 -.077 .935 .795 1.258
a. Dependent Variable: OPE
5.3 Knowledge Management Practices Influence on SME Performance Efficiency
The five KM practices investigated in this study were Orientation towards the development,
transfer and protection of knowledge-(DTP), Continuous learning in the organization-(CRO),
An understanding of the organization as a global system1-(UOG1), An understanding of the
organization as a global system2-(UOG2), Development of an innovative culture that
encourages R&D projects-(DIC), Approach based on individuals-(ABI), and Competence
development and management based on competences-(COM). These remained after factor
analysis for further analysis. Competence development and management based on competences
(COM) items did not load onto this construct, hence it was dropped from further analysis.
60
Table 22: Descriptive Statistics for KM Practices
N Minimum Maximum Mean Std.
Deviation
Variance Skewness Kurtosis
Statistic Statistic Statistic Statistic Std. Error Statistic Statistic Statistic Std. Error Statistic Std.
Error
DIC 25 2.25 5.00 3.6400 .14440 .72198 .521 -.163 .464 -.609 .902
DTP 24 3.00 5.00 3.8333 .13003 .63702 .406 .418 .472 -.539 .918
ABI 25 3.00 5.00 4.0600 .13329 .66646 .444 -.122 .464 -.865 .902
UOG2 25 3.00 5.00 3.8200 .13503 .67515 .456 .284 .464 -.923 .902
CRO 25 2.00 5.00 3.7800 .15567 .77835 .606 -.049 .464 -.250 .902
UOG1 25 1.50 4.50 3.4800 .14283 .71414 .510 -.764 .464 .967 .902
Valid
N (list
wise)
24
5.3.1 Approach Based on Individuals
From the results shown in Table 22 and Figure 22 it is evidence that the KM practice Approach
based on individuals (ABI) had the highest mean rating (4.06) in the five Likert point scale and
is therefore the most adopted KM practice by SMEs. Further, from the correlation results shown
in Section 5.2, Table 17 had a positive influence (r=0.298) to organization performance
efficiency (OPE) although it was not significant.
Figure 21: Mean Rating of KM Practices on a Five Point Scale
61
Table 23: Codes SME Performance Efficiency Constructs
Code Meaning
DTP Orientation towards the development, transfer and protection of knowledge CLO Continuous learning in the organization UOG1 An understanding of the organization as a global system1 UOG2 An understanding of the organization as a global system2 DIC Development of an innovative culture that encourages R&D projects ABI Approach based on individuals
5.3.2 Knowledge Creation and Transfer
The study sought to find out the behavior on continuous learning in the organization (CRO) on
influencing Organization Performance Efficiency (OPE) in SMEs. From the results shown in
Table 22 and Figure 22 it is evidence that CRO KM practice had the fourth highest mean rating
(3.83) in the five Likert point scale and is therefore the second most adopted KM practice by
SMEs. Further, from the correlation results shown in Section 5.2, Table 17 DTP had a positive
influence (r=0.268) to Organization Performance Efficiency (OPE) although it was also not
significant.
5.3.3 Continuous Learning in the Organization
The study sought to find out orientation towards the development, transfer and protection of
knowledge of the SMEs (DTP) influence on Organization Performance Efficiency (OPE).
From the results shown in Table 22 and figure 22 it is evidence that CLO KM practice had the
second highest mean rating (3.78) in the five Likert point scale and is therefore the fourth most
adopted KM practice by SMEs. Further, from the correlation results shown in Section 5.2, Table
17 CLO had a positive influence (r=0.559) to Organization Performance Efficiency (OPE).
This was significant at the 99% confidence interval. This clearly implies that most of the
companies that represent 52% of the population have a career plan to stimulate continuous
learning. Further, few of the firms that constitute 40% of the population have their employees
receive general training which is applied to their usual tasks. Additionally, the study found out
that 44% of the companies have a continuous improvement system in place allowing for
improvement in processes which have reached the set quality standards as shown in the Table
24.
62
Table 24: Continuous Learning in the Organization.
Strongly Disagree Disagree Neutral Agree Strongly Agree
Row N % Row N % Row N % Row N % Row N %
The firm has a career
plan to stimulate
continuous learning
0.0% 0.0% 36.0% 52.0% 12.0%
Employees receive
general training which
is applied to their usual
tasks
0.0% 4.0% 32.0% 40.0% 24.0%
A continuous
improvement system is
in place allowing for
improvement in
processes which have
reached the set quality
standards
0.0% 4.0% 36.0% 44.0% 16.0%
5.3.4 An Understanding of the Organization as a Global System
The study sought to find out how “An Understanding of the Organization as a Global System”
KM practice influence Organization Performance Efficiency (OPE) in SMEs. Factor analysis
loadings split this practice into two coded UOG1 and UOG2 in the subsequent analysis results.
From the results shown in Table 22 and figure 22 it is evidence that UOG2 KM practice had
the third highest mean rating (3.82) in the five Likert point scale and is therefore the third
most adopted KM practice by SMEs. Further, from the correlation results shown in Section
5.2, Table 17 UOG2 had a positive influence (r=0.141) to Organization Performance Efficiency
(OPE) although it was also not significant. However, the results shown in Table 22 and Figure
22 reveal that UOG1 KM practice had the third least mean rating (3.48) in the five Likert point
scale and therefore the least adopted KM practice by SMEs. Further, from the correlation results
shown in Section 5.2, Table 17 UOG1 had a positive influence (r=0.593) to Organization
Performance Efficiency (OPE). This was significant at the 99% confidence interval.
63
5.3.5 Development of an Innovative culture that Encourages R&D projects
The study sought to find out the influence of Development of an Innovative culture that
Encourages R&D projects (DIC) on Organization Performance Efficiency (OPE) in SMEs.
From the results shown in Table 22 and Figure 22 it is evidence that DIC KM practice had
the fifth highest mean rating (3.64) in the five Likert point scale and is therefore the fifth most
adopted KM practice by SMEs. Further, from the correlation results shown in Section 5.2, Table
17 DIC had a positive influence (r=-0.035) to Organization Performance Efficiency (OPE). This
relationship is not significant.
5.4 Organizational Performance Efficiency
The dependent variable Organizational Performance Efficiency (OPE) was operationalized by
the following constructs: - Capital profitability (CAP), Growth (GRO), Operational and
financial efficiency (OPE), Stakeholder satisfaction (STS), and Competitive position (COP).
64
Table 25: SME Performance Efficiency Constructs Cronbach’s Alpha
Construct Items Cronbach’s
Alpha
Comment
Capital profitability (CAP), 4 0.934 Good
Growth (GRO) 5 0.945 Good
Operational and financial efficiency (OFE) 4 0.921 Good
Stakeholder satisfaction (STA) 4 0.923 Good
Competitive position (COM) 7 0.94 Good
Organizational Performance Efficiency(OPE) 24 0982 Good
The results of factor analysis shown in section 52. Table 13 showed that the constructs from
Organizational Performance Efficiency (OPE) was operationalized by the following constructs:
- Capital profitability (CAP), Growth (GRO), Operational and financial efficiency (OPE),
Stakeholder satisfaction (STS), and Competitive position (COP) all loaded into one component
or factor. This factor is Organizational Performance Efficiency (OPE). Consequently this was
the factor that was operationalized to measure the dependent variable.
Table 26: Organizational Performance Efficiency Descriptive Statistics
The study sought to establish Operational and financial efficiency of the companies. The five
pointy Likert Scale where 1-No improvement, 2- Some improvement, 3-Average involvement,
4- Great improvement, 5-Extremely improved was used to measure the constructs for the
dependent variable Organizational Performance Efficiency (OPE). From the results shown in
N Minimum Maximum Mean Std.
Deviation
Variance Skewness Kurtosis
Statistic Statistic Statistic Statistic Std. Error Statistic Statistic Statistic Std. Error Statistic Std. Error
CAP 25 2.00 5.00 3.3200 .19870 .99352 .987 .035 .464 -1.174 .902
GRO 25 1.40 4.80 3.2720 .20261 1.01305 1.026 -.179 .464 -1.318 .902
OFE 24 1.75 5.00 3.3438 .19201 .94066 .885 .017 .472 -1.254 .918
STA 25 2.00 5.00 3.5400 .19879 .99394 .988 -.059 .464 -1.433 .902
COM 25 2.14 4.71 3.3714 .16782 .83910 .704 .389 .464 -1.451 .902
Valid N
(list
wise)
24
65
Table 26 and Figure 23, it is evidence that Stakeholder satisfaction (STA) had the greatest
improvement that can be seen in the mean rating (3.54) ranges from average to great
improvement. This was followed by Competitive position (COM), Operational and financial
efficiency (OFE), Capital profitability (CAP), and Growth (GRO) with mean ratings of 3.37,
3.34, 3.32, and 3.27 respectively. It is evidence from Table 26 and Figure 23 that all had above
average improvement. Additionally, growth had the least improvement.
Figure 22: SME Organizational Performance Efficiency Improvement
The results and findings presented in this chapter enables us to refine the model conceptualized
in chapter 2 and 4 as shown in Figure 24. Taking the correlations or β-coefficients represented
in the regression Table 21, we indicate the same on the relationship paths of Figure 24.
66
Figure 23: SME KM Frameworks and Practices Model
5.5 Chapter Summary
This Chapter presents the results and findings from the data analyses done on the data collected
and further explains the data in visual forms such as pie charts, bar graphs, simple tables to aid
understand the figures shared. Correlation and regression analysis was also presented. In the
next chapter, using the analysis achieved here, conclusions and recommendations will be
shared.
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CHAPTER 6: DISCUSSION, CONCULSIONS AND RECOMMENDATIONS
6.0 Introduction
This final chapter ushers in discussions, conclusions and recommendations regarding the study.
The chapter is subdivided into five parts. Part one focuses on the methodology used, the
summary of the findings from the field of study and results. Part two focuses on discussions
around the three specific objectives in relation to the project .That is a review on the influence
of knowledge management frameworks as a practice by Kenyan SME’s , its effects and a
suggested framework that has been designed with the characteristics of the SME’s in mind that
form the base of the study. Conclusions drawn then follow using the findings and results that
were obtained in chapter four. Then lastly, recommendations arising from the study specific
objectives are listed at the end.
6.1 Summary
The purpose of the study was to investigate the influence of integrating Knowledge
management frameworks on the Kenyan SME’s as a practice with the aim of improving
business operations. The Study had three specific objectives a) A review on existing knowledge
management frameworks adopted as a practice by Kenyan SME’s, b) its effects and as a result
design a framework that had been designed with the unique Kenyan characteristics of the
SME’s in mind. The three were independently examined and tested. The research employed a
descriptive approach to harness data with focus on SME’s around the Westlands area of
Nairobi. Stratified random sampling approach was adopted to gather data that was used in
research as it provides data to analyze subgroups while facilitating the use of different methods
in strata hence enabling the researchers to easily control the size of the strata they choose to
work with. This method is also viable in populations that are not of homogenous nature.
Westlands harbors various SME’s that provide an array of services. Data collection was done
using a questionnaire that was self-administered by the researcher. Questionnaires are viable
due to their various benefits. They are considered practical in nature, large amounts can be
collected over a short period of time in a comparably cost effect way. They can also be
distributed by third parties with limited effect to its validity.
The questionnaire was sub sectioned to capture general data and specific data in relation to the
research. The data collected then processed through SPSS and data generated represented in
graphs, pie charts. Demographic data was tabulated by use of frequencies and percentages.
Reliability tests were done on variables presented; Organizational Performance Efficiency, KM
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Frameworks, Development of an innovative culture, Approach based on individuals,
understanding of the organizations as a global system2, continuous learning understanding of
the organization global system1 and competence development and management by SME’s
yielded Cronbach’s Alpha - if Item Deleted values as 0.98, 0.96, 0.844, 0.79, 0.69, 0.84, 0.88
and 0.676 respectively for the variables. The results of Cronbach's Alpha confirmed reliability
of the data collection instrument
Pearson’s Chi-square tests were performed to establish relationships between the variables
presented. In this study we observe that the significance of 0.040<0.05 hence we accept the
proposition that the independent variables - Orientation towards the development, transfer and
protection of knowledge-(DTP),Continuous learning in the organization-(CRO),An
understanding of the organization as a global system1-(UOG1), An understanding of the
organization as a global system2-(UOG2),Development of an innovative culture that
encourages R&D projects-(DIC), Approach based on individuals-(ABI),Competence
development and management based on competences-(COM), and KM Frameworks-(FRA),
explain the variations in the dependent variable. Organizational Performance Efficiency-(EFE).
6.2 Discussions
The study sought to identify if Small and Medium firms in Kenya did embrace Knowledge
management practices in their daily operations. Results revealed most organizations have
somewhat have adopted best practices but not necessarily aligned knowledge management
frameworks to their business vision, mission and goals hence missing out on the full benefits
that are synonymous with Knowledge management.
6.2.1 Knowledge Management Frameworks Influence on SME Performance Efficiency
The study sought to understand how small enterprises were influenced by knowledge
management frameworks. The research identified adoption of the IBM Corp. Framework and
the Standards Australian International Frameworks as the most adopted frameworks by
SME’s in the study. From the correlation table, KM Frameworks denoted a positive and
significant relationship with organizational Performance (r =0.561) and 99% confidence level
proving that KM frameworks indeed have an influence in the organizational performance of
the SME’s. In reference to the available literature, many firms do acknowledge the role that
KM and its tools play in improving organizational efficiency. A properly crafted knowledge
management framework clearly shows the knowledge infrastructure (technology,
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organizational culture and structure) Knowledge processing ability (acquire, distribute, apply
and convert) on varied dimensions of organizations efficiency and effectiveness.
However most firms find it difficult to embrace it due to lack of empirical data that clearly
links the two i.e. knowledge management and organizational efficiency (Jayasingam,
Ramayah , Janta, & Ansari , 2010). Also, a lack of a clearly standardized framework to
measure organizational performance has been a challenge, as different scholars have
suggested different ways of measuring organizational success. Desouza and Raider (2006)
suggested that knowledge management be measured in terms of customer retention,
innovation rates, speed to market and employee retention whilst (Tiwana, 2001) reviewed
popular KM metrics such as the balance score card, Skandia Navigator ,Economic Value
Added amongst others.
6.2.2 Knowledge Management Practices Influence on SME Performance Efficiency
In the study, five KM practices were adopted. This included, Orientation towards the
development, transfer and protection of knowledge, Continuous learning in the organization),
an understanding of the organization as a global system1, an understanding of the
organization as a global system2, Development of an innovative culture that encourages R&D
projects. Approach based on individuals and Competence development and management
based on competences. Approach based on individuals (ABI) had the highest mean rating
(4.06) in the five Likert point scale and was adopted as a KM practice by SMEs. Further, from
the correlation results shown in Section 5.2, Table 17 had a positive influence (r=0.298) to
organization performance efficiency.
Continuous learning in the organization on influencing Organization Performance Efficiency
in SMEs. From the results in the tables, it is evident that continuous leaning as a KM practice
had the fourth highest mean rating (3.83) in the five Likert point scale and therefore the
second most adopted KM practice by SMEs. Further, from the correlation results, Orientation
towards the development, transfer and protection of knowledge had a positive influence
(r=0.268) to Organization Performance Efficiency. This was significant at the 99%
confidence interval. From the survey, this clearly implied that most of the companies that
represent 52% of the population have a career plan to stimulate continuous learning. Further,
few of the firms that constitute 40% of the population have their employees receive general
training which is applied to their usual tasks. Additionally, the study found out that 44% of
the companies have a continuous improvement system in place allowing for improvement in
processes which have reached the set quality standards. Continuous learning is described by
70
King (2009) as the main facilitator for KM driven performance. It aids transform a firms
embedded knowledge into a structured organizational process through creation, distribution
and application that continuously improves a firms practices. This practice within the firms
ensures continued information flow, elicits discussions and in the process, knowledge units
are exchanged effortlessly. The result, new ideas being generated and the innovation process
continues (Oliver, 2008).
The study also sought to find out the influence of Development of an Innovative culture that
Encourages R&D projects on Organization Performance Efficiency in SMEs. The results
shown in Table 22 and Figure 22 it is evident that Development of an Innovative culture that
Encourages Research and Development projects KM practice had the fifth highest mean rating
(3.64) in the five Likert point scale and therefore the fifth most adopted KM practice by SMEs.
Further, from the correlation results shown in Section 5.2, Table 17 Development of an
Innovation culture that encouraged research and development had a positive influence (r=-
0.035) to Organization Performance Efficiency. An innovative culture within a firm is a process
that creates change in the existing environment and ensures its competitors respond to it. With
globalization and a highly competitive market, new and ever changing technology, short
product life cycles and ever changing customer tastes and preferences continued research and
development is key for business continuity. SME’s play such a huge role in continued
innovations. Though, lack of capital puts them at a risk of not continuously being in a position
to generate new ideas as often. They lack the manpower and resources to have fully fledged
research and development departments (Thomä & Zimmermann, 2016; Bayarçelik, Tasel, &
Apak, 2014). The study also acknowledged 48 Percent of the firms had no definite response as
to what’s achieved with all feedback collected from their customers. Feedback plays a major
role in identifying a customer needs and acts as tool to collect information directly from the
client. When incorporated as a best practice, a firm will not only achieve business
competiveness over its peers, but will be able to solve a client problem directly hence business
continuity
On adoption of the KM Frameworks and practices, from the research, its clear efficiency and
effectiveness which were the main variables being tested against were experienced by various
constructs. The dependent variable Organizational Performance Efficiency was operationalized
by the following constructs: - Capital profitability, Growth Operational and financial efficiency
Stakeholder satisfaction and Competitive position. From the study, it is evident that Stakeholder
satisfaction had the greatest improvement that can be seen in the mean rating (3.54) ranges from
71
average to great improvement. This was followed by Competitive position Operational and
financial efficiency Capital profitability and Growth with mean ratings of 3.37, 3.34, 3.32, and
3.27 respectively. All had above average improvement. In reference to existing literature,
Knowledge Management practices in general often affect firms in a positive manner hence
improving organizational performance by ensuring they are efficient and effective. Knowledge
management often assimilation of knowledge by building the knowledge resource stock and
aiding in transformation of knowledge, whether new or existing. This impacts an organization
positively in terms of its overall performance (Claiborne, 2011).
6.3 Conclusions
6.3.1 Knowledge Management Frameworks Influence on SME Performance Efficiency
Adoption of Knowledge Management Frameworks helps organization by guiding it through its
targets. This is done through the clear breakdown shared interims of achievable shared by
components of the framework. This research identified 37 percent of its respondents as having
adopted the IBM Corp Knowledge Management Framework. IBM is a multinational firm
(Gupta, Perepu, & Govind , 2009). Adoption of its knowledge management framework would
mean SME’s having to adopt some of the viable practices off the framework. The result, the
SME’s not in a position to achieve their maximum output and also, loss of their characteristics
and hence not achieving their business goals thus risking no business continuity (Evangelista,
Esposito, Lauro, & Raffa, 2010).
6.3.2 Knowledge Management Practices Influence on SME Performance Efficiency
The Research identifies a need for Information Technology. Information Technology revolution
has removed a barrier of obtaining quality information aids any institution in making key
decisions that impact the firm in a positive way , ensuring competitive advantages amongst its
peers. (King W. R., 2011). A need to adopt simple technologies to facilitate knowledge creation,
sharing, storage and use of knowledge whenever needed by the organization is key to any SME
thriving the competitive markets.
A need for continuous learning amongst the SME’s is needed as this creates opportunities for
employees to learn more, and also further disseminate the same information to create a new
product or service (Chen & Huang, 2009). Kenyan SME’s operate on minimalistic capital hence
more often than not, not in a position to invest in a fully-fledged Research and Development
department. This means inability to continue innovating since its people are not often trained
72
or encouraged to do so. A lack of continued learning means, no ideas, new products or services
and hence minimal business continuity in the long run.
The research acknowledged 56 percent of the firms adopting collaborative tools, which viable
way of SME’s relaying knowledge units throughout the firms. This is achievable using social
media platforms such as closed groups in social media, blogs, bulletins, memos amongst others.
Most Kenyan SME’s have adopted these tools in their practices but often use them to gather
data from clients directly and not to share knowledge units. This is not only achievable but cost
effective to the firms (Phosaard & Wiriyapinit , 2011).
The research highlighted business stakeholders, i.e. Owners, employees and customers
achieving varied levels of satisfaction and the businesses experiencing notable changes in
regards to growth, business efficiency and effectiveness. If the firms would adopt more of
knowledge management practices and tools, more success, growth, satisfaction, refined
business processes, increased profit margins and business continuity certainly would be attained
(Edvardsson & Durst, 2013).
6.4 Recommendations
The following are recommendations based on the research undertaken. SME owners need to
take an initiative in exploring various ways of knowledge units’ creation, management, support,
transfer and within their firms despite them being small. With technology in place and readily
available, accessibility to open source softwares to manage their business operations and hence
knowledge management doesn’t require an organization to invest heavily when adopting this.
For instance, a Small firm could consider social media platforms as they are not only avenues
for social interactions but complete knowledge management tools. Social media platforms can
be used in harnessing customer feedback. This is one of the non-expensive knowledge
repositories that is readily available. An online presence for the organization is key as it saves
the organization, a need for an intranet. Collaborative social media platforms such as Facebook
offers closed group forums where ideas can be generated, projects initiated and monitored.
The government also needs to play a major role in educating is SME holders on the need for
knowledge management. SME’s play such a major role in Kenya as they provide jobs and hence
livelihood for more than 70 percent of the GDP. It’s said, a government is as good as its people.
Having done the study on ow the SME’s in Kenya Adopt knowledge management frameworks
73
to improve business operations and having suggested a viable knowledge management strategy
and framework, a study on the firms that have undertaken the suggested model to see how
further their business have been refined and factors to improve in order to grow the SME’s and
ensure they achieve a maximum output.
74
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APENDIX I: INTRODUCTORY LETTER
Dear Sir/Madam,
RE: RESEARCH PROJECT
The undersigned researcher is a master’s student in USIU pursuing a Master’s in information
systems and technology. The researcher would like to investigate on how Kenyan SME’s
integrate knowledge management frameworks to improve their business operations. Your
88
organization has been selected to be part of this study. You are kindly requested to assist by
responding to the questions posed as truthfully as possible. The information obtained will be
treated with the utmost confidentiality and used for the purpose of the study only.
Thanks in advance for your cooperation.
Yours Faithfully,
Emaculate Mbula Munywoki
Student ID: 624305
89
APENDIX II: QUESTIONNAIRE
My name is Emaculate Mbula Munywoki, a student in United States international university,
pursuing a master’s degree in information systems and technology. This questionnaire is
distributed in order to gather information regarding how Kenyan SME’s integrate knowledge
management frameworks to improve their business operations. Through your participation, the
study will be able to make possible recommendations that will highlight the identify the key
identify knowledge management frameworks and practices that are adapted by Kenyan SME’s
as well as to examine the effect of the Knowledge management frameworks and practices on
business operations. Further it will design a simple knowledge management System that
demonstrates the adapted SME Knowledge management Framework. The information you
provide will be treated with confidentiality and will solemnly be used for the purpose of this
study.
SECTION A: GENERAL INFORMATION
Please answer the following questions about yourself and company by checking with a tick
the box In front of the appropriate information or by providing the information requested where
appropriate.
1. Name of the corporate
………………………………………
2. My gender is
Male Female
3. Please specify your age range.
1. 15-20,
2. 21-25,
3. 26-30,
4. 31-35,
5. 36-40,
41-45,
46-50,
51 or over
4. Position in corporate business
Entrepreneur (Owner)
Employee
5. What industry is your SME?
Manufacturing Sector
Retail Chains
Transport and logistics
Consultancy
Building and construction
Retail Stores
Service Providers
Higher Education Sector
Agri-Business
Tourism
Hospital /Clinic
90
Wholesale
Apparel
Telecommunication
Pharmacy
Spare parts
Other Specify_____
3. How many years has the business been in
operation? ____________Years
4. What is the gross turn over?
< 1 million
1–2 million
2- 3 million
3-4 million
4-10 million
>10 million
5. What is your highest level of education?
Certificate
Diploma
Degree
Masters
Doctorate
7. How many directors does the SME have?
___
8. What is the nature of the business?
Sole Proprietor
Private Limited Company
Company Limited by Guarantee
NGO
CBO
Government Parastatal
6. Is the company registered with
the Ministry of Trade and
Industry?
Yes No
7. When was the firm started?
8. How many workers did you have at the
start?
..........................................................
9. How many workers do you have at
present? ……………………………
10. How many business branches did your
business have at the start? .....................
11. How many business branches does your
business have at present? ......................
91
SECTION B: KNOWLEDGE MANAGEMENT FRAMEWORKS AND PRACTICES
In a scale of 1 to 5 indicate your opinion in the level you agree with then following statements
in your organization on use of knowledge management practices
Knowledge Management Frameworks and Practices
Str
ongly
Dis
agre
e
Dis
agre
e
Neu
tral
Agre
e
Str
ongly
Agre
e
Orientation towards the development, transfer and protection of
knowledge
DTP1 The firm has a system to codify its explicit knowledge 1 2 3 4 5
DTP2 Information technologies and systems (intranet, internet, etc.) are
available to give the employee access to the information required 1 2 3 4 5
DTP3 Mechanisms are in place to encourage the members of an organization to
share information 1 2 3 4 5
DTP4 Inter-departmental projects are carried out in the firm 1 2 3 4 5
Continuous learning in the organization
CLO1 The firm has a career plan to stimulate continuous learning 1 2 3 4 5
CLO2 Employees receive general training which is applied to their usual tasks 1 2 3 4 5
CLO3 A continuous improvement system is in place allowing for improvement
in processes which have reached the set quality standards 1 2 3 4 5
An understanding of the organization as a global system
UOG1 A system exists to inform clients, suppliers, employees, according to the
needs detected 1 2 3 4 5
UOG2 The firm encourages knowledge transfer through instruments such as
inter-functional teams, quality circles, improvement groups, etc. 1 2 3 4 5
UOG3 Best practices in one department are shared by others 1 2 3 4 5
UOG4 There are incentives when the overall aims of the firm are achieved 1 2 3 4 5
UOG5 The firm has systems that capture and deal with information about
processes 1 2 3 4 5
Development of an innovative culture that encourages R&D projects
DIC1 Employees who develop R&D projects have the necessary training to put
them into practice 1 2 3 4 5
92
DIC2 Techniques are established to develop external benchmarking, which
enables the company to learn about the success or failure of other firms 1 2 3 4 5
DIC3 R&D projects are provided with control mechanisms to monitor them 1 2 3 4 5
DIC4 When an R&D project finishes, feedback is obtained that is useful in
developing new projects 1 2 3 4 5
Approach based on individuals
ABI1 Tasks are established to identify the information resources necessary for
the organization 1 2 3 4 5
ABI2 The firm encourages teamwork 1 2 3 4 5
ABI3 Procedures are established (such as surveys or discussions) to find out
employees’ opinions and levels of satisfaction 1 2 3 4 5
ABI4 The managers inform of and reward their collaborators’ achievements 1 2 3 4 5
Competence development and management based on competences
COMD1 The organization has systems to measure its employees’ competences 1 2 3 4 5
COMD2 Remuneration and promotion systems have an influence on the
development of competences, ideas and knowledge by the employees 1 2 3 4 5
COMD3 The firm uses benchmarking techniques to improve its employees’
competences 1 2 3 4 5
12. On a scale of 1 to 5 indicate with a circle your opinion in the level in which your
organizations uses the following frameworks in your organization
Code
Top 10 Knowledge Management
frameworks from various origins
Do n
ot
use
Sli
ghtl
y u
sed
Use
d a
ver
agel
y
Use
d g
reat
ly
Use
d fu
lly
Institutional origin Name of framework
FRA1 Science, Davenport/Prusak
(1998).
1 2 3 4 5
FRA2 Science, Heisig (2000). 1 2 3 4 5
FRA3 Enterprise, IBM Corp. (2001). 1 2 3 4 5
FRA4 Enterprise Siemens AG
(Ehms/Langen
2002).
1 2 3 4 5
93
FRA5 Management
Consultant
APQC/Arthur
Andersen (1996
1 2 3 4 5
FRA6 Management
Consultant
1 2 3 4 5
FRA7 Associations EIRMA – European
Industrial Research
Management
Association (1998).
1 2 3 4 5
FRA8 Associations CEN – Comite´
Europe´en de
Normalisation
(2003).
1 2 3 4 5
FRA9 Standardization
bodies
SAI – Standards
Australia
International (2001).
1 2 3 4 5
FRA10 Standardization
bodies
GKEC – Global
Knowledge
Economics Council
(Vaupel 2002).
1 2 3 4 5
SECTION C: EFFECT OF THE KNOWLEDGE MANAGEMENT FRAMEWORKS
AND PRACTICES ON ORGANIZATIONAL PERFROMANCE
13. On a scale of 1 to 5 indicate your opinion on the level the effect of organization
knowledge management
KM practices effect on Scale for measuring organizational
performance
No i
mpro
vem
ent
Som
e im
pro
vem
ent
Aver
age
invo
lvem
ent
Gre
at i
mpro
vem
ent
Extr
emel
y i
mpro
ved
Capital profitability
CAP1 Average economic profitability ROA (subjective scale 1-5) 1 2 3 4 5
CAP2 Average financial profitability ROI (subjective scale 1-5) 1 2 3 4 5
CAP3 Average profitability in sales ROS (subjective scale 1-5) 1 2 3 4 5
CAP4 Average gross production margin (subjective scale 1-5) 1 2 3 4 5
Growth
GRO1 Average annual growth in sales 2011-2016 (subjective scale 1 2 3 4 5
94
GRO2 International annual average growth in sales 2011-2016 (subjective scale
1-5) 1 2 3 4 5
GRO3 Market share increase 2011-2016 (subjective scale 1-5) 1 2 3 4 5
GRO4 Market share increase 2011-2016 (objective value in percent) 1 2 3 4 5
GRO5 Expected growth in sales 2017-2019 (subjective scale 1-5) 1 2 3 4 5
GRO6 International expected growth in sales 2003-2005 (subjective scale 1-5) 1 2 3 4 5
Operational and financial efficiency
OFE1 Financial solvency (subjective scale 1-5) 1 2 3 4 5
OFE2 Financial liquidity (subjective scale 1-5) 1 2 3 4 5
OFE3 Labor productivity (subjective scale 1-5) 1 2 3 4 5
OFE4 Labor productivity - ratio added value/average total personnel objective
value in millions in Ksh) 1 2 3 4 5
OFE5 Cost-efficiency - total unit cost of the product - (subjective scale 1-5) 1 2 3 4 5
Stakeholder satisfaction
STA1 Wealth creation (subjective scale 1-5) 1 2 3 4 5
STA2 Customer satisfaction (subjective scale 1-5) 1 2 3 4 5
STA3 Employee satisfaction (subjective scale 1-5) 1 2 3 4 5
STA4 Global image of the environment (subjective scale 1-5) 1 2 3 4 5
Competitive position
COM1 Domestic competitive position (subjective scale 1-5) 1 2 3 4 5
COM2 East Africa competitive position (subjective scale 1-5) 1 2 3 4 5
COM3 Overall competitive position (subjective scale 1-5) 1 2 3 4 5
COM4 Prices/internal competitive position (subjective scale 1-5) 1 2 3 4 5
COM5 Prices/external competitive position (subjective scale 1-5) 1 2 3 4 5
COM6 Quality/internal competitive position (subjective scale 1-5) 1 2 3 4 5
COM7 Quality/external competitive position (subjective scale 1-5) 1 2 3 4 5
Thank you for your response.
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