DETERMINANTS OF BUSINESS PERFORMANCE: A CASE

OF AGRIPRENUERS IN KENYA

BY

EDGAR GINA OCHIENG

UNITED STATES INTERNATIONAL UNIVERSITY - AFRICA

SUMMER 2020

DETERMINANTS OF BUSINESS PERFORMANCE: A

CASE OF AGRIPRENUERS IN KENYA

BY

EDGAR GINA OCHIENG

A Research Project Report Submitted to the Chandaria School

of Business in Partial Fulfilment of the Requirement for the

Degree of Masters in Business Administration (MBA)

UNITED STATES INTERNATIONAL UNIVERSITY -

AFRICA

SUMMER 2020

ii

STUDENT’S DECLARATION

I undersign, and 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.

This project has been presented for examination with my approval as the appointed

supervisor.

Signed: ____ __________ Date: 06-10-2020

Signed: Date: 06-10-2020

Prof. Paul Wachana

Signed: ______________ Date: ________________

Edgar Gina Ochieng (ID 638184)

Dean, Chandaria School of Business

iii

COPYRIGHT

All rights reserved. The copyright of this report vests in the author. No part of this research

may be reproduced, recorded, photocopied, stored or published without permission of

USIU-Africa or author. The research is to be used for private study or non-commercial

research purpose only.

© 2020 Edgar Gina Ochieng

iv

ABSTRACT

The purpose of the study was to establish the determinants of business performance of

agriprenuers in Kenya. The research questions that were used to guide the study are: What

are the effects of agripreneur’s socio-demographics on business performance? What is the

effect of agripreneur’s number of business location on business performance? What is the

effect of agripreneur’s prior training experience on business performance?

The study adopted descriptive research design. The population was 1,200 respondents,

from which a sample of 492 was selected using proportionate sampling by ranking the top

male and female agriprenuers.The collected data was analysed using SPSS.The analysis

revealed that 263 (53.5%) respondents were male, while 229 (46.5%) were female. The

descriptive findings showed that majority (36%) of the respondents were agripreneur’s

between the ages of 25-29 years. Socio-demographics had a positive effect on business

performance. On average, one more year contributed to an increase in monthly sales by

0.450 units. The p < 0.05 and thus significant. With all variables held constant, a unit

change in number of business location lead to a 0.886 change in business performance. The

variable was significant as the p<0.05. The study also revealed that prior training

experience was significant with a p<0.05. This meant that a unit change in prior training

experience lead to a 0.918 unit change in business performance in Kenya.

In conclusion, socio-demographic factors such as age had a statistical significance on

business performance of agriprenuers based in Kenya. The research study deduced that an

increase in the age of an agripreneur appears to increase business performance. Business

location on the other hand had statistical signigicance in influencing business performance.

The study discovered that the more the business location, the better the business

performance. Prior training experience had the highest impact on business performance

with a 91% change.

The study recommends that the government and private sector through CSR should look at

ways in which they can help founders of SMEs through age specific programs that can

positively affect business performance. In addition, improving access to number of

business location business location through infrastructural development will enhance

business performance. The study also recommends that the capacity of agripreneur’s should

be enhanced through trainings and workshops as appropriate.

v

Further studies should be carried out to compare whether the findings also apply for other

sectors in different areas in order to validate whether the findings can be generalized to

others in Kenya. There is also need to focus on other factors which are not covered in this

study such as competitors, economy, technology and politics.

vi

ACKNOWLEDGEMENT

I would want to acknowledge my Dad, for always putting education first and ensuring that

we as a family get the privilege of first class knowledge. My Mum for looking out for me

from above. My Second Mum for her unending support and push for me to complete my

studies and better myself. My brothers for making this journey worthwhile through small

but effective sacrifices, and finally, my supervisor Prof. Wachana, for ensuring that every

inquiry and concern is met with calm guidance.

vii

TABLE OF CONTENTS

STUDENT’S DECLARATION ........................................................................................ ii

COPYRIGHT .................................................................................................................... iii

ABSTRACT ....................................................................................................................... iv

ACKNOWLEDGEMENT ................................................................................................ vi

TABLE OF CONTENTS ................................................................................................ vii

LIST OF TABLES ............................................................................................................. x

LIST OF FIGURES .......................................................................................................... xi

ABBREVIATIONS AND ACRONYMS ........................................................................ xii

CHAPTER ONE ................................................................................................................ 1

1.0 INTRODUCTION........................................................................................................ 1

1.1 Background of the Problem........................................................................................ 1

1.2 Statement of the Problem ........................................................................................... 4

1.3 Purpose of the Study .................................................................................................. 5

1.4 Research Question ...................................................................................................... 5

1.5 Significance of the Study ........................................................................................... 5

1.6 Scope of Study ........................................................................................................... 6

1.7 Definition of Terms .................................................................................................... 6

1.8 Chapter Summary ....................................................................................................... 8

CHAPTER TWO ............................................................................................................... 9

2.0 LITERATURE REVIEW ........................................................................................... 9

2.1 Introduction ................................................................................................................ 9

2.2 Effect of Socio-Demographics on Business Performance ......................................... 9

2.3 Effect of Number of business location on Business Performance .......................... 18

2.4 Effect of Prior Training Experience on Business Performance ............................... 13

2.5 Chapter Summary ..................................................................................................... 28

CHAPTER THREE ......................................................................................................... 29

viii

3.0 RESEARCH METHODOLOGY ............................................................................. 29

3.1 Introduction .............................................................................................................. 29

3.2 Research Design ....................................................................................................... 29

3.3 Population and Sampling Design ............................................................................. 30

3.4 Data Collection Methods .......................................................................................... 31

3.5 Research Procedures ................................................................................................ 32

3.6 Data Analysis Methods ............................................................................................ 32

3.7 Chapter Summary ..................................................................................................... 32

CHAPTER FOUR ............................................................................................................ 33

4.0 RESULTS AND FINDINGS ..................................................................................... 33

4.1 Introduction .............................................................................................................. 33

4.2 Response Rate .......................................................................................................... 33

4.3 Socio- Demographic Information and Business Performance ................................. 33

4.4 Households ............................................................................................................... 37

4.5 Infrastructure Access ................................................................................................ 39

4.5 Funding..................................................................................................................... 43

4.7 Training and Business Performance ......................................................................... 44

4.8 Respondents’ County of Residence.......................................................................... 46

4.9 Multiple Regression Analysis .................................................................................. 47

4.9 Chapter Summary ..................................................................................................... 52

CHAPTER FIVE ............................................................................................................. 50

5.0 DISCUSSION, CONCLUSIONS AND RECOMMENDATIONS ........................ 53

5.1 Introduction .............................................................................................................. 53

5.2 Summary .................................................................................................................. 53

5.3 Discussion ................................................................................................................ 53

5.4 Conclusions .............................................................................................................. 55

5.5 Recommendations .................................................................................................... 56

ix

REFERENCES ................................................................................................................. 58

APPENDICES .................................................................................................................. 67

Appendix I: Letter of Introduction ................................................................................. 67

Appendix II: IRB Research Approval ............................................................................ 69

Appendix III: NACOSTI Approval................................................................................ 70

Appendix IV: Research Questionnaire ........................................................................... 71

x

LIST OF TABLES

Table 4. 1: Distribution of the Respondents by Highest Level of Education .................... 36

Table 4. 2: Number of People Supported by the Business ................................................ 37

Table 4. 3: Household Income Description ....................................................................... 38

Table 4. 4: How the Respondents Feel About their Household Income ............................ 38

Table 4. 5: Source of Energy ............................................................................................. 40

Table 4. 6: Source of Water ............................................................................................... 40

Table 4. 7: Owned a Mobile Phone ................................................................................... 41

Table 4. 8: Connection of Sewage System to Business or Homes……………………….43

Table 4. 9: Sources of Funds.............................................................................................. 43

Table 4. 10: Areas of Training ........................................................................................... 44

Table 4. 11: Main Challenges of Attending Training ........................................................ 45

Table 4. 12: Distribution of the Respondents by County of Residence ............................ 46

Table 4. 13: Model Summary ............................................................................................ 47

Table 4. 14: ANOVA ......................................................................................................... 47

Table 4. 15: Regression Coefficients ................................................................................. 48

xi

LIST OF FIGURES

Figure 4. 1: Distribution of the Respondents by Gender ................................................... 34

Figure 4. 2: Distribution of the Respondents by Age ........................................................ 34

Figure 4. 3: Distribution of the Respondents by Marital Status ........................................ 35

Figure 4. 4: Distance from Tarmac Road ........................................................................... 39

Figure 4. 5: Business Area Connection to a Mobile Network ........................................... 42

Figure 4. 6: Training Area Preferences .............................................................................. 46

xii

ABBREVIATIONS AND ACRONYMS

GOK

KNBS

SME

SMME

SPSS

GDP

Government of Kenya

Kenya National Bureau of Standards

Small Medium Enterprises

Small, Micro, and Medium Enterprises

Statistical Package for Social Sciences

Gross Domestic Product

CHAPTER ONE

1.0 INTRODUCTION

1.1 Background of the Problem

Entrepreneurship is defined in the literature as a process by which individuals—either on their

own or inside organisations—pursue opportunities without regard to the resources they

currently control. Entrepreneurs seemingly explore and start new activities despite the scarcity

of resources (FAO, 2011). The Resource-Based View (RBV) argues that resources, including

resources that are supplied to a company, contribute to the explanation of the company’s

competitive advantage. This leading perspective in organisational theory partly explains the

creation of resource pools. The RBV starts from the perspective of competition between

companies and examines to what extent resources are valuable and rare. In this sense, the RBV

is a useful perspective for strategic management research. However, this perspective does not

explain fully how entrepreneurs deal with combining a company’s resource pool within a

constrained resource environment. Entrepreneurs within a constrained resource environment

have to relate to the constraints in order to be able to wrest from that environment the valuable

combination of resources to develop their businesses (Mkhabela, & Nyhodo, 2011).

Entrepreneurs form the backbone of all successful economies globally since they are

considered as the vital source of economic growth in the provision of employment

opportunities, eradicating poverty and contributing to the development of gross domestic

product (GDP) of both developed and developing countries (Carron et al., 2017). Despite their

importance, less attention is drawn to them hence little information is available in the global

books about their motivation, emergence or performance. Generally, the world knows less

about those who become entrepreneurs and their journey of performance. Entrepreneurs use

their competencies to search, create and exploit business opportunities available within the

environment. Competency of the entrepreneurs is one of the significant determining factors

for success, performance and growth or failure of business operation. Thus,

understanding the nature of such competencies in the context of entrepreneurs is very

important (Mitchelmore & Rowley, 2013).

2

According to Usman and Kamau (2019), the knowledge gained from entrepreneurial exposure

enablespositive attitude towards improving entrepreneurship skills among students.

Entrepreneurial education is an effective way to promote and boost the interest of

entrepreneurship among agripreneurs. In United Kingdom, farmers associations

collaboratively organize, empower and educate the communities for self-reliance, poverty

reduction and economic growth. They promote farmer inspired and farmer owned producer

companies for quality production, value addition, storage and marketing and this has led to

increased agricultural production. Quality extension services are also provided to farmers on

organic farming, fair trade, certification, entrepreneurship for rural development, natural

resource management and conservation of agricultural ecology and biodiversity (Heins,

Beaulieu & Altman, 2010).

In Sub-Saharan Africa social factors, such as poverty and gender inequality, have greatly

affected and will still affect entrepreneurship. It is the only region where more than three-

quarters of the poor live in rural areas. By the mid twenty-first century, its rural population is

projected to increase by 63%. It is the only region in the world where the rural population will

continue to grow after 2050 (Thapa & Gaiha, 2011). This population growth means a massive

expansion of the labor force and a huge pressure on the agricultural sector. Agricultural

companies thus have the potential of enhancing economic growth by providing raw materials

and market for produce in large quantities and qualities and being catalysts for increased

production of farm produce. This implies that a country can rely essentially on its entrepreneurs

and small business (Liverpool-Tasie, Omonona, Sanou, Ogunleye, Padilla & Reardon, 2017).

The link between entrepreneur characteristics and firm performance has received a lot of focus

by studies. Studies (De Grip & Pleijers, 2019; Griffin, 2012; Lucas, 2017) show that

characteristics of an entrepreneur which include demographic factors, individual background,

personal traits, entrepreneur orientation, and entrepreneur readiness play an important role in

performance of small and medium enterprises (SMEs). These factors which form the character

and behaviour of the entrepreneur are crucial internal capacities that impact on firm

performance. Thus an enterprise reflects the characteristics of the entrepreneur whose

commitment and vision are central to firm performance. The entrepreneur combines both

3

tangible and intangible resources into a business organization (Mayuran, 2016). Sub Saharan

Africa and Asia have the highest levels of youth unemployment. OECD (2015) report indicates

that most youth in Sub Saharan Africa do not have adequate knowledge or capacity to engage

fully and efficiently in entrepreneurship due to lack of information, access to funding, and

business mentoring through entrepreneurship incubation programs. South Africa, Zimbabwe,

Kenya and Nigeria are some of the African countries running entrepreneurship incubation,

however, only Kenya and South Africa are running ICT based incubation programs. Some of

the challenges cited by International Labor Organization ILO (2012) include poor access to

information, lack of adequate ICT infrastructure, and lack of government based funding. The

increase in unemployment in South Africa from 8% to 11% in 2010 led the government to pass

legislation providing funding for entrepreneurship incubation programs (Noor, 2010). This was

done through establishing the Umsobomvu Youth Fund (UYF) in 2001 as a way of cultivating

interest in entrepreneurship, and at the same time enhancing financial facilitation on the same.

Systematic evidence from previous studies finds that the incompetence of several small and

medium scale firms in Nigeria have led to their collapse within a short period of operation

(Akhamiokhor & Adanikin, 2017). Given this assertions, it is logical to hypothesise that

entrepreneurial characteristics are a strong determinant of entrepreneurial success or

performance. Entrepreneurs who do not have the mental competence through age, educational

background or experience, may be faced with the inadequacies of running a new venture. The

shortcoming of such an entrepreneur will be ranging from family pressure, poor preparation,

lack of expertise and funding. Therefore, entrepreneurs who do not meet up with the expected

requisite qualities of a capitalist, may never break-even (Tu & Diem, 2016). The

entrepreneurial characteristics may reflect the entrepreneurial capabilities that will influence

business strategies, market orientation, methods of financing, management practices and

especially social capital. For example, an excellent personal relationship will help firms to

access scarce resources, to do business efficiently and to improve the firm’s performance

ultimately.

In Kenya, poor rural roads and other key physical infrastructure have led to high transportation

costs for agricultural inputs and products and this has really interfered with performance of

4

agribusinesses in the country. It also leads to spoilage of perishable commodities during

transportation. This causes high losses to farmers. This list of challenges facing Kenyan

agriculture and farmers is not exhaustive. They are however the major challenges that can be

solved if effective extension and advisory services accorded to farmers especially small-scale

farmers and this will boost performance of agribusinesses. The government also has a big role

to play in solving some of these challenges like the poor infrastructure, strengthening research,

extension and training and enhancing farmer access to affordable inputs and credit. Most of

the challenges are caused by lack of information and knowledge on how to avoid them or how

to solve or circumvent those that cannot be avoided (Ngugi, 2012)

1.2 Statement of the Problem

Agriculture and economy are argued by Abdul and Ngugi (2015) to be synonymous in Africa

and in other developing countries in the world. In effect, you cannot modernize the economy

in Africa without starting with agriculture. One of the catalysts to an Agribusiness revolution

in Africa will be a new focus on agricultural MSEs (Kelley, Singer & Herrington, 2012). More

than 74.2 percent of employment in Kenya comes from agriculture sector however, it is

characterized by high mortality rate where three out of five of these businesses fail within the

first few months of operation; over 60% fail each year; and most do not survive to their third

anniversary (KNBS, 2016; GOK, 2012). This high failure rate is mainly attributed to lack of

skilled work force and stiff competition in the market. Despite various government policies

that have been put in place to improve agribusinesses, these micro and small enterprises tend

have low survival rates.

A study by the International Labour Organization (2012), found that currently the growth of

agribusinesses in Kenya are restricted by inadequate access to training, as well as follow up to

training inputs, and limited opportunity to avail themselves of external, formal managerial

capacity-building support. Further, despite the considerable Kenyan government support and

support of bodies interested in agriculture, an entrepreneur’s socio-demographics has an

impact on the business performance. Various reports show that many women led businesses

enter and exit these markets every year with a turnover rate of about 32% per annum

(Organisation for Economic Co-operation and Development, 2015). Consequently, even

5

though billions of dollars have been allocated to support women owned agribusinesses by way

of government funding, training, grants and consultative support services, the failure rates of

these women operated businesses remains high. Moreover, the agriculture businesses consider

roads to be very essential in making their businesses grow, Infrastructure such as access to

roads, water and electricity, plays a significant role in advancing an agripreneur’s competitive

edge (Noor, 2012).

Amha, Woldehanna, Tamrat and Gebremedhin (2014) noted that MSE are hampered by several

factors, which may differ from region to region within the country, between rural and urban

areas, between sectors, or between individual enterprises within a sector. High failure to grow

and be sustained of agricultural businesses in Kenya has become an increasing concern to the

government and stakeholders. It is against this background that the study considered looking

into the determinants of business performance of agriprenuers in Kenya.

1.3 Purpose of the Study

The purpose of the study was to investigate the determinants of business performance of

agriprenuers in Kenya.

1.4 Research Questions

1.4.1 What is the effect of socio-demographics on business performance of agriprenuers in

Kenya?

1.4.2 What is the effect of business location on business performance of agriprenuers in

Kenya?

1.4.3 What is the effect of agripreneur’s prior training experience on business performance of

agriprenuers in Kenya?

1.5 Significance of the Study

1.5.1 Industry

This study will help increase the amount of literature about determinants of business

perfomance of agriprenuers in Kenya. This as a whole will assist budding entrepreneurs avoids

the pitfalls and improve in different departments of the business. This will also help meet

6

customer needs and wants. This will also improve the overall quality of e-commerce businesses

as well as other businesses coming into the Kenyan market.

1.5.2 Policy Makers

This study will look to create awareness to the government and policy makers on ways they

can make a conducive environment for entrepreneurs as well as provide information on how

to help improve business performances. Whilst creating supporting laws and policing bodies

that help foster innovation and technology growth in Nairobi and Kenya as a whole. This will

in hindsight increase the level of businesses surviving from inception to growth.

1.5.3 Future Researchers

This research will provide new perspective to a research area that has long proven to be unique

to demographics with a lot of influence on the outcome dependant on dependant variables,

meaning findings on determinants of business performance from other countries cannot be

correctly applied to others.

1.6 Scope of Study

The scope of the study covers the determinants of business performance of agribusiness

entrepreneurs across 9 counties of Nyandarua, Nakuru, Kakamega, Bungoma, Kiambu,

Kericho, Kisumu, Siaya and Nairobi. The sample size will contain 492 respondents aged

between 18-35.

1.7 Definition of Terms

1.7.1 SME

Small and mid-size agencies (SMEs) are businesses that hold revenues, property or a number

of personnel beneath a certain threshold. Each country has its personal definition of what

constitutes a small and medium-sized corporation (SME). Certain dimension standards need

to be met and every so often the industry in which the enterprise operates in is taken into

account as well. Though small in size, small and mid-size agencies (SMEs) play an important

function in the economy. They outnumber massive companies considerably, hire massive

numbers of people and are commonly entrepreneurial in nature, helping to form innovation

(Liberto, 2019).

7

1.7.2 Entrepreneur

An entrepreneur is anyone who creates a new business, bearing most of the dangers and

enjoying most of the rewards. The entrepreneur is usually viewed as an innovator, a source of

new ideas, goods, services, and business/or procedures. Entrepreneurs play a key function in

any economy, the use of the abilities and initiative vital to expect wants and deliver suitable

new ideas to market. Entrepreneurs who prove to be successful in taking on the dangers of a

start-up are rewarded with profits, fame, and persisted growth opportunities. Those who fail,

go through losses and turn out to be less well-known in the markets (Hayes, 2020).

1.7.3 Training

Training is the action of instructing someone a specific skill. It may additionally also refer to

the teaching of a kind of behavior. It targets to improve a person’s capacity, capability,

performance, or productivity (Massagli, 2015).

1.7.4 Performance

The accomplishment of a given assignment measured against present acknowledged

requirements of accuracy, completeness, cost, and speed. In a contract, overall performance is

deemed to be the achievement of an obligation, in a manner that releases the performer from

all liabilities in the contract (Nganu, 2018)

1.7.5 Location

Named geographical area (such as an airport, seaport, container freight station or terminal) that

offers permanent facilities for motion of goods (such as customs, storage, and different guide

services) or is distinct for a noted purpose (Dixit & Turken, 2019).

1.7.6 Socio-Demographics

Socio-demographic looks at things such as, age, sex, education, migration heritage and

ethnicity, non-secular affiliation, marital status, household, employment, and income.

Different index variables are formed on the basis of socio-demographic variables. They

include, for example, entrepreneur socio-economic status, which combines statistics on

education and income. Socio-demographic important points are often used to describe realised

samples and to determine sampling error (Audi & Ali, 2017)

8

1.7.7 Business Growth

Business Growth is a stage where the enterprise reaches the point for expansion and seeks

additional options to generate greater profit. Business growth is a feature of the business

lifecycle, enterprise growth trends, and the owner’s desire for fairness value creation (Dladla

& Mutambara, 2018)

1.7.8 Business Performance

Business performance is the measuring of business accomplishments against intended goals.

This can include but is not limited to financial and production goals (Rotich & Yegon, 2015).

1.8 Chapter Summary

Chapter one presents the background of the study and its purpose. The research questions that

guided the study were: What are the effects of socio-demographics on business performance?

What is the effect of number of business location on business performance? What is the effect

of prior training experience on business performance? The research at entrepreneurs in nine

counties in Kenya: Nyandarua, Nakuru, Kakamega, Bungoma, Kiambu, Kericho, Kisumu,

Siaya and Nairobi. Chapter two looks at the literature review, whilst chapter three highlights

the study’s research methodology. Chapter four highlights the results and findings of the data

that has been analysed whilst chapter five presents the discussion, conclusions and

recommendations of the study.

9

CHAPTER TWO

2.0 LITERATURE REVIEW

2.1 Introduction

This chapter reviews literature on the determinants of business performance. The presentation

will follow the order in which research questions are organized. It begins by examining the

relationship between socio-demographics and business performance, followed by the effect of

number of business location on business performance, and finally it explores the link between

prior training experiences and business performance.

2.2 Effect of Socio-Demographics on Business Performance

2.2.1 Entrepreneur’s Age

It is an observed factor that young people are very aggressive, impatient and ready to take risk.

Hence this factor may influence on business practices of entrepreneurs. The individuals are

socialized to behave in ways that meet with the approval of their role set. To take an example,

a young person with a business owning parent may well be expected to join the family business

and not to do so would create a vacuum in the business. If we accept that entrepreneurs require

ideas, opportunities, resources skills and motivation for success, then the social structures and

situations to which they are exposed will impact on the choice process. Hurtado, Pineda and

Florencio (2017) found that actual and perceived entrepreneurial skills are acquired overtime

and consequently age has an impact on entrepreneurship. For example it has been suggested

that many people age thirty or less may not have acquired sufficient organizational experience

while those age forty five or more may no longer possess the acquired energy. However,

Syafruddin, Utama, Yasa and Marhaeni (2018) found that there are no hard and fast rules

concerning the right age for starting a business. According to Audi and Ali (2017), empirical

studies based on individual data have found an inverse U-shaped relationship between age and

the decision to start a business, using changes in the age distribution of the population of

western German regions over time, they found—in accordance with micro level analyses—an

inverse U-shaped relationship between the regional age structure and start-up activity in a

region. Moreover, their findings suggest that the age-specific likelihood of becoming an

10

entrepreneur changes with the size of the age cohort, pointing to the existence of a relationship

between the age of the entrepreneur and the performance of the enterprise.

Ogubazghi and Muturi (2014) point out that most of entrepreneurs in the United States start

business during their 30s and 40s, many researchers found that there is no limit of age for their

entrepreneurial aspirations. Age variation at the start of business seems to have no direct

relation to business success. According to Radipere and Dhliwayo (2014), at the start of any

business age is not a decisive factor, but with enough training and preparation, the earlier

someone starts business the better. Osunsan, Nowak, Mabonga, Pule, Kibirige and Baliruno

(2015) also note that age is related to business success if it includes both chronological age and

entrepreneurial age. This means that the older an entrepreneur is, the more experiences in

business he has. Age thus implies extensive experience. Many scholars mentioned that the age

cohort of the entrepreneur has a significant outcome on self-employment (Ahaibwe & Kasirye,

2015). Most of the scholars argued that young entrepreneurs have a better aspiration than older

entrepreneurs. Other authors also confirm that young entrepreneurs are more likely to be

energetic, and more inclined to test their capability than older entrepreneurs. De Gobbi (2014)

also found that older youth (aged 25-29) are more likely to be self-employed than younger

individuals whose ages between 20-24 years.

2.2.2 Level of Education

Education and skills are needed to run micro and small enterprises. Research shows that

majority of the lot carrying out micro and small enterprises in Kenya are not quite well

equipped in terms of education and skills. Majority of those who run MSEs are the ordinary

lot whose educational background is wanting. Hence they may not be well equipped to carry

out managerial routines for their enterprises. Pantea (2016) noted that those with more

education and training are more likely to be successful in the MSE sector. As such, for small

businesses to do well in Kenya, entrepreneurs need to be well equipped in terms of skills and

management. MSEs in ICT appear to be doing well with the sprouting of many commercial

colleges offering various computer applications. Further, studies show that most of those

running MSEs in the ICT sector have at least attained college level education (Radipere &

Dhliwayo, 2014). As culture is a learned behaviour, formal, non-formal and informal education

plays an important role in transferring cultural values from one generation to another.

11

However, Kolstad and Wiig (2015) said that education plays a subsidiary role in promoting

entrepreneurship, because entrepreneurs are born. It is often articulated that the supply of

entrepreneurs will ultimately be increased more if awareness of the feasibility and desirability

of starting a business is established at a young age. Thus education system is assisted to foster

support and encourage those interested in knowing what it is like to run a business. In Sri

Lanka, Moberg et al. (2014) noted that most of the successful entrepreneurs have not gone

through higher education or formal courses in entrepreneurship. Studies also show that, only a

few of the entrepreneurs have had family business connections at the time they started a

business. Prior experience and skills gained through informal learning have been useful in

making a start. Access to good education has a positive impact on firm performance since it

enhances entrepreneur’s self-confidence and self-efficacy (Kelley, Singer & Herrington,

2012). Business owners who have attended the highest school completed, they can have an

immense ability to learn a new system, process, and technical knowledge, access information,

new technology and innovation than those who have less access to education. This result is

also consistence with result of Amha (2015) who argued that entrepreneurs, who have higher

education, have positive associations with business survival and expansion. Another empirical

survey also confirmed that the individuals higher educational level has the positive relationship

with entrepreneurship in general and the business performance in a particular. Hence,

education can be used by people to equip themselves with the basic Know-how and skills to

confront daily problems (Ghani, Kerr & O’Connell, 2011).

2.2.3 Gender

A survey conducted by Hurtado, Pineda and Florencio (2017) in South Africa, Kenya and

Tanzania noted that MSEs provide employment to more than 50 per cent of the income-earning

population. The study estimated that in Kenya small enterprises generate 12-14 per cent of the

Gross Domestic Product (GDP). Kenya’s economic landscape also reflects the dominance of

MSEs as the most dynamic aspect of the private sector. One significant characteristic of the

sector is that as it has grown, it has also become an important employer of the female labour

force in the country. According to the World Bank (2011), the number of men and women

owning micro-enterprises in Kenya was almost equal, at 670,727 enterprises owned by men

compared to 612,848 owned by women accounting for 47.4 per cent of all those in MSEs. The

results showed that women tended to operate enterprises associated with traditional women's

12

roles, such as hairstyling, restaurants, hotels, retail shops and wholesale outlets. The survey

also indicated that women tended to operate smaller MSEs than men and made less income

than them. As noted earlier, about half (52.6 per cent) of all employees are men and 47.4 per

cent are women. This compared to the national employment statistics of 2003 and 2004 which

indicated that only 30 per cent of the total workforce was made up of women (Kenya National

Bureau of Statistics, 2016). The MSEs sector, therefore, holds more promise for women in

providing and accessing employment opportunities. While government statistics indicate that,

in recent years, the number of women owned firms with employees has increased, even with

this growth women remain underrepresented in terms of their proportion of the high-growth

firms. Various scholars conducted on gender differences in entrepreneurial performance in

many countries and found different results. For instance, Mayuran (2016) shows the

relationship between entrepreneurship and earnings among youth in the USA and the study

found that male youth entrepreneurs are more than male youth employed as well as women.

Furthermore, the study made by Ebitu (2013) in the USA and Australia with related to youth

self-employment and found men has higher probability to move to self-employment than

female. Syafruddin, Utama, Yasa and Marhaeni (2018) in Italy also found that women self-

employed were less likely to survive than men.

On the other hand, in many African scholars analysed entrepreneurs gender differences in the

overall performance of the business, but most of them have not found main differences between

men and women (Ahaibwe & Kasirye, 2015). Similarly, other scholars in USA and India also

found not major gender differences in business performance (Robb & Watson, 2012).Based on

the above literature, we concluded that female youth entrepreneurs more constraints than youth

male entrepreneurs. Therefore, this implies that there is a gender difference for youth

entrepreneurs in entrepreneurial activities. Vallabh (2015) researched on the influence of

demographic factors on business performance in small to medium tourism enterprises

(SMTEs). Demographic factors such as age, gender, education, earnings and experience has a

substantial impact on business performance. The focus location of this research is the Eastern

Cape Province, economically the poorest province in South Africa. The research empirically

looks at whether gender, training and earnings of the business have a widespread influence on

the business performance of Small Medium Tourism Enterprises (SMTEs) in the South African

13

context. Quantitative research was deemed suitable for the study, whereby systematic random

sampling was employed to pick a sample of 332 respondent organisations. The findings exhibit

that the relationship between gender and profits in relation to business performance used to be

observed to be significant. Only 38% of managers indicated that they had obtained both a

diploma and postgraduate qualification. The lack of schooling poses a core undertaking in

phrases of human assets for the tourism sector, when searching for expert employees to meet

future wishes of the industry. In order for managers to be more effective, it is advocated that

government intervenes by merchandising academic and training initiatives and be gender

touchy through encouraging extra women to research at tertiary institutions.

Lucas (2017) studies the impact of demographic and social factors on firm performance in

Kenya. The factors investigated include education level, gender and age of the firm. In addition

to these factors, the research additionally investigated the impact of labour force, capital and

firm’s ownership structure on performance. Ordinary least squares method and descriptive data

had been used. The study found that training level and age of the firm have a positive effect on

performance. Firms operated by men have been found to have a better overall performance

than those operated by females. In addition, the research discovered that partnerships,

cooperatives and companies (both private and public limited) function better than family

owned businesses.

2.3 Effect of Business location on Business Performance

2.3.1 Geographic Location

Geographic location has its implications for access to markets and other resources like finance,

skilled labour, subcontractors, infrastructure, distribution and transport logistics and other

facilities. MSE success also depends on neighbourhood appearance and continued or

maintained future business operations in that location. Dladla and Mutambara (2018) on the

Orthodox regional development theory' stresses that urban areas have favourable supply-side

conditions for firm development. They also noted that MSEs located in urban areas typically

have a relative ease of access to customers and the inputs required (i.e. finance, premises,

technology, etc.) to produce goods or services. MSEs located in urban areas may benefit from

agglomeration economies and spatial externalities (i.e. specialized infrastructures, information,

14

network of suppliers, specialized labour, specialized knowledge, concentration of existing

exporters, etc.). Recently, De Grip and Pleijers (2019) detected that urban firms benefiting

from external agglomeration economies were more likely than rural firms to be exporters.

However, the costs associated with most inputs are generally higher in urban areas, which may

constrain MSE development. Seo and Lee (2019) suggested that enterprises located in urban

areas might face different closure possibilities than their rural counterparts. Dixit, Clouse and

Turken (2019) found that firms in remote rural areas were less active on various dimensions

of innovation. This may be influenced by the fact that most rural areas have less well developed

financial and business service sectors than urban areas.

Further, lower awareness and usage of external business advice have been reported by firms

located in rural areas (Lackeus, 2013). Orthodox regional development theory fails to

adequately explain the counterfactual case of the existence of successful MSEs located in

peripheral and resource sparse environments, which can benefit from protective greenhouse

conditions (i.e. lower densities of economic activity and a smaller number of potential

competitors). While MSEs located in peripheral (and rural) areas may encounter greater

resource constraints than urban MSEs, this environmental resource scarcity, according to

Mitchelmore and Rowley (2010), in fact stimulates them to exhibit greater proactive

entrepreneurial behavior. Tighter external selection pressures generally make it more difficult

for a firm to be established in a resource-sparse environment. Further, only the best among

potential entrepreneurs may attempt to establish and develop businesses. Many start-up errors

can occasionally be remedied, but a poor vicinity choice is difficult, and occasionally

impossible to exchange. The vicinity of a commercial enterprise drastically affects business’s

survival. Each area preference gives a range of potentials, opportunities and from time to time

threats which frequently emerge as a benefit or an impediment. It is consequently vital that

enterprise owners and managers pay attention and consider seriously, those factors that will

decide the quality of their location decisions. Given the high degree of enterprise failure among

SMMEs all over the world and South Africa in particular; the study is a contribution to the

illumination of the perception of new ventures in the vicinity of region decisions; so that they

are able to make informed decisions which can also enhance the possibilities of survival of

their businesses (Rotich, Cheruiyot & Yegon, 2015).

15

2.3.2 Physical Infrastructure

Physical infrastructure is the totality of basic physical facilities upon which all other economic

activities in the system significantly depend (Mukulu, 2012). According to Vijay and Ajay

(2011), infrastructures are those services without which primary, secondary and tertiary

production activities cannot function. These infrastructures can be extended to include

education, public health to transportation, communication, power and water supply.

Infrastructure therefore, can be seen as both a final good providing services directly to

consumers and intermediate input that enter into 17 the production function of other sectors

and raises the productivity of the factors employed. The New Growth Theory (Endogenous

Growth Model) recognizes the influence of policy variables like infrastructure provision in

production function. Infrastructure therefore, can serve as an externality variable that can

facilitate the production function of private sector, thereby improving the efficiency of the

factors of production and growth. Kochadai (2012) argues that: infrastructure contributes to

economic growth both through supply and demand channels by reducing cost of production,

contributing to the application of modern technology, raising the economic returns of labour

(by reducing workers‟ time in non- productive activities or improving health), Infrastructure

contributes to rising quality of life by creating amenities, providing consumption goods

(transport and communication services) and contributing to macroeconomic stability and that

Infrastructure does not create economic potential; only develops it where appropriate

conditions (i.e. other inputs such as labour and private capital) exist. Infrastructure contributes

to economic development through the promotion of private sector development by increasing

access to the factors of production, goods and market (Penchev & Salopaju, 2011). By

extension, an efficient transport network enhances the growth potential of a country and is

liable system of energy generation and distribution brings modern technologies and processes

to SMEs.

In addition, infrastructure could enable SMEs to work cooperatively and achieve economies

of scale, and ensure price and non-price competitiveness. High transport costs associated with

movement of goods from the rural to urban areas in particular is becoming more vulnerable as

fuel keep increasing. Furthermore, a dependable system of energy at an affordable price is

essential to all economic activity and failure to provide accessible power sources is a constraint

16

to production efficiency and competitiveness. Griffin (2012) submits that infrastructural

deficiencies are the frequent complaints by all businesses in many countries, domestic and

foreign owned firms, alike. It is noteworthy that power failure, transport costs and other

infrastructural problems among SMEs poses the greatest difficulties to continued business

activity. Building physical and social infrastructures have become a cornerstone for business

development. Lumbwe Anyadiegwu and Mbohwa (2018) researched on the impact of location

decision on small, micro, and medium enterprises’ performance in Johannesburg. This research

has the grasp of area decision of SMMEs in the city of Johannesburg. Particularly, the study

investigated the degree to which the predetermined variables (labour, electricity factors,

proximity to customers, proximity to suppliers, proximity to competitors, and protected and

healthful location) affect the dependent variable which is business performance. The research

established that among all the variables, lower priced electrical energy tariffs has the strongest

and advantageous relationship with business performance. It was also found that protection

and health and excessive customer flow have a relationship with business performance.

Nevertheless, the theoretical effects show that all six unbiased variables influence area

decisions and consequently enterprise performance. Furthermore, extra corporations as part of

their contribution to the growth and development of SMMEs, should sponsor applications and

conferences to share thoughts and experiences on the import of vicinity choice and what

standards can be used for place analysis to allow SMMEs make knowledgeable region

selection decision for their business. This study only targeted manufacturing and service

industries in Johannesburg, South Africa. Consequently, this could limit the generality of the

findings to different sectors such as the buying and selling and distribution sectors.

Moos and Botha (2016) studied location with a look at South African businesses with the topic

“How do age and location affect a business? Evaluating the objectives, outputs and outcomes

of small business policy”. As a growing country, South Africa needs a high-quality policy that

will create a beneficial surroundings for small organizations to prosper. The consequences of

the research exhibits that solely the location (the metropolitan municipality where the

commercial enterprise is located) has a statistically widespread effect on the objectives, outputs

and outcomes of the small business policy. The age of the business has no effect. The effects

mean that the vicinity of the start-up / established enterprise proprietors does have an effect on

17

their standpoint on the objectives of the small business policy. The objectives are considered

and interpreted differently in the distinctive provinces and therefore in the extraordinary

metropolitan municipalities. Start-up and established commercial enterprise proprietors count

on comparable outputs such as finance and incentives that have to reach all regions of the

country to aid with their commercial enterprise endeavours. Outcomes such as improving the

regulatory surroundings and decreasing enterprise start-up barriers are perceived in a different

way in the distinctive metropolitan municipalities. The findings of the research amplify

understanding of the small enterprise policy in terms of its appropriateness for the age of a

business. They confirm that location performs a key function in shaping small business and

entrepreneurial activities.

Val, Hernandez and Fuentes (2018) looked at geographical factors and business failure: An

empirical study from the Madrid metropolitan area. The overall intention of the study was to

test the influence of geographical factors on business failure in a city context, particularly in

the Madrid metropolitan area. In order to attain this purpose, they analysed the relevance of

geographical proximity to exterior economic agents and transport facilities, which ought to

have a bearing on the firms’ possibilities of survival. In addition, they evaluated if the

interaction of nearby peer corporations additionally has an impact on their probabilities of

survival. The information used consists of a sample of industrial SMEs located in the

municipality of Madrid. This statistics was difficulty to a join-count test in order to realize

possible spatial co-localized spatial patterns among pairs of related peer companies. This

evaluation yielded significant results concerning the spatial distribution of healthful and failed

companies. Subsequently, we used a spatial probit model to analyse the impact of geographical

proximity variables on business failure. The results verify spatial co-localized patterns in pairs

of failed companies. Therefore, failed businesses are possibly to be surrounded by other failed

companies. In addition, proximity to exterior financial agents reduces the chance of failure,

mainly regarding Logistic Centres (DMinLS) and Industrial estates (DMinIP). The findings

confirm that geographical proximity to other businesses is beneficial, owing to higher

information flows and easier access to exclusive modes of transportation. These consequences

also highlight how recommended it is for companies to be positioned in the proximity (less

than 2.39 Km) of Research Centres and Universities. The benefits encompass fine access to

18

information. In addition, proximity favours synergies between R&D centres and companies,

which fosters innovation activities and reduces their cost. These results have a tendency to

make organizations less possibly to fail. Finally, neighborhood density of corporations also

enhances the likelihood of firm survival. Higher neighborhood density decreases the

probability of business failure, but solely when other firms are located in close proximity to

the challenge companies.

2.4 Effect of Prior Training Experience on Business Performance

2.4.1 Training Program Characteristics

According to World Bank (2011), for entrepreneurship training to be effective, it must not only

be through factual knowledge and limited to skills acquired in the classroom, but also through

other more practical interventions. Hurtado, Pineda and Florencio (2017) assert that

entrepreneurship training programmes mostly focus on two areas; training for business start-

ups, which centres mainly on the domain of knowledge, experience and aptitudes of

entrepreneurs and training those who will start-up businesses by creating entrepreneurs. GEM

(2012) states that some common cited objectives of entrepreneurship training include; to

acquire knowledge relevant to entrepreneurship; to acquire skills and synthesis of action plans;

to identify and stimulate entrepreneurial drive, to develop empathy and support for all unique

aspects of entrepreneurship; to devise attitudes towards change and to encourage new start-ups

and other entrepreneurial ventures. The debate on what should constitute the entrepreneurship

training content continuous as various empirical studies continues to have different views. A

study by Azim and Al-Kahtani (2014) established that depending on the duration, target

audience, resource availability and perceived efficacy of the training’s multiplicity objectives

for different entrepreneurs, different training content can be observed. In this respect,

objectives determine the contents of the training program. From secondary data, Azim and Al-

Kahtani (2014) outlined the following to constitute the content of entrepreneurship training,

which are preferred in different development stages. During the formation stage the focus

should be on understanding the nature of entrepreneurship, characteristics of an entrepreneur,

importance of entrepreneurship, creativity and innovation skills, business idea generation,

opportunity identification, 26 entrepreneurial and ethical self-assessment. During the

development stage, the focus should be on product identification, business planning, market

19

selection, financial planning, and making financial presentations. During the implementation

stage, entrepreneurship training should lay emphasis on communication skills, especially

persuasion; creativity skills; critical thinking and assessment skills; leadership skills;

negotiation skills; and problem-solving skills. The study was however, based on secondary

data. Consequently, different scholars have put forward different objectives, contents and

modalities for entrepreneurship training programs to be effective (Ahaibwe & Kasirye, 2015).

Empirical study by Mayuran (2016) in Jaffna district in Sri Lanka on the impact of

entrepreneurship training on performance of small enterprises established a positive correlation

between entrepreneurship training and firm performance. The study found out that customer

care, marketing, quality maintenance and financial management were being taught as the

content of entrepreneurship training. The content was basically business management skills

and the effect of the other entrepreneurial skills on performance was not addressed. The

methodology focused only on the correlation between the independent variable and the

dependent variable. This study focused on the content of training to include managerial skills,

technical skills and entrepreneurial skills. The study also used descriptive and inferential

statistics. Study by De Gobbi (2014) explored the entrepreneurship training for emerging

SMEs in South Africa. The study analysed the course content to include motivation,

entrepreneurship skills and business skills. Motivation content included; need for achievement,

ability to inspire and ability to cope with failure. Entrepreneurship skill included; creativity,

innovation, ability to take risks, idea generation and opportunity identification. Business skills

included; management, leadership, financial management, marketing skills, human resource

skills, business planning and operational skills. The study recommended the need to strengthen

entrepreneurial skills for the emerging entrepreneurs to understand how to generate business

ideas, screen the ideas and identify business opportunities from the generated business idea.

However the study did not collect data from business entrepreneurs but from periodic

employees and trainers. The data collection was through interviews and lacked quantitative

data. Hence, the findings cannot be generalized.

A study by Pantea (2016) on the impact of entrepreneurship training on performance of micro,

small and medium enterprises in Nakuru County, investigated the nature and content of

20

entrepreneurship trainings offered by Kenya Institute of Business Training and Joint loans. The

study found out that the trainers focused on management of working capital, record keeping,

and marketing. The study however, recommended inclusion to the content of training; risk

management, business expansion strategies and management of loan delinquency and default.

These components are part of business management skills and it is clear that the curriculum

used was not comprehensive. Despite this, the study used a small response rate of 37 SMEs

operators. The study was also limited in scope to Nakuru County and programs offered by

Kenya Institute of Business Training and Joint loans. This calls for further investigation on the

content of trainings offered by other organizations on entrepreneurship training. According to

Kolstad and Wiig (2015), the content of entrepreneurship training should include; managerial

skills, technical skills, and entrepreneurial skills. Managerial Skills include competencies in,

business management, marketing, record keeping, financial management, and human resource

management. Technical skills include; ability to practice competences acquired such as;

computing, tailoring, mechanical and motor vehicle skills, carpentry among others.

Entrepreneurial skills include; abilities such as; creativity, innovativeness, risk taking, 28

persistence, self-drive among others. Business management skills are required to run the

business on a daily basis. One of the dictionary definitions of good management is the skilful

use of materials and time towards the achievement of business objectives. Business

management skills cover all the conventional management training areas in a business.

Organizations that are well managed develop a loyal customer base, grow and prosper

(Radipere & Dhliwayo, 2014).

Having inadequate business management skills is one of the most prominent reasons for failure

of SMEs (Kelley, Singer & Herrington, 2012). Technical skills are defined as those specific

skills needed to work within a specific occupation. Technical skills include expertise in;- the

knowledge of the industry, its standards and practices; the ability to use the tools, procedures

and techniques of the specified field, the understanding of how specific things work;

product/service-specific knowledge that enable one to know what the particular product could

do and what it could be used for; process knowledge or how to manufacture the relevant

product and all steps that need to be taken to develop and produce the product or perform the

tasks necessary to render the service (Ghani, Kerr & O’Connell, 2011). GEM (2012) identified

21

the essential traits of successful entrepreneurs to include; ability to be innovate and creative,

ability to recognize business and social opportunities, resourceful in solving problems; self-

confidence- believes in his or her abilities, has positive attitude, ability to cope with failure,

understands and manages risks, values independence; drive to successes persistent, ability to

take initiative, has high energy level, is able to focus intensely; curiosity possesses a deep

curiosity about how thing work, has a passion for learning; strong people skill- can motivate

others, is a team builder. The attributes underlying these traits include; 29 imagination,

creativity, tolerance for risks, divergent thinking ability, analytical skills, passion, self-

assurance, interpersonal skills, self-drive. Thus, empirical review outlines the importance of

managerial skills, technical skills and entrepreneurial skills. This study established the content

of entrepreneurship training thought to SMEs in ICT sector and how the content influenced

their performance. The study gave recommendations on what the trainees felt needed to be

included in the content of training.

Omolo (2015) looks at training and development on performance of small and medium

enterprises in Kisumu. The ecological concept of small enterprise growth and improvement

was used to guide the study. The study was carried out in SMEs in Kisumu County using cross

sectional survey research design, on a target populace of 777 and a sample of 260 clustered

randomly chosen SMEs, which represent 30% of the target population. Data was gathered

using structured, semi structured, Likert scale questionnaire and focus group discussion

techniques. Data was analyzed with percentages and multiple regression techniques, stated

using tables, charts, graphs and figures. The discovering of the study confirmed that the

performance of an SME is related with the reputation of training and development and that the

better the reputation of training and development in an SME, the higher the performance of the

SME. Matofari (2015) on the other hand looked at the effect of training practices on the

performance of small and medium size hotel enterprises in Mombasa County, Kenya. The

correlation between this study and whether entrepreneur prior training affects business

performance is due to the fact that the study looks at three training practice components:

training plans, training methods and training programs, whilst looking at its effect on business

performance. The assumption is that any entrepreneur with the correct training component can

positively impact his/her business and in the event that they find themselves in training, they

22

will be better off than their first time counterparts. The study was carried out in 24 resorts in

the County, which represented the units of evaluation for this study. Specifically a descriptive

survey aimed at a targeted population from a representative pattern was used. The survey

involved collecting information through administering a questionnaire to the sample.

Statistical bundle for social sciences was used to analyse data. The data then then summarized

using tables and bar graphs. The study determined out that there is a positive cascading effect

between training exercise variables and performance of SME resorts within Mombasa County.

The study additionally determined out that most sampled SME resorts prefer using on-the-job

training technique to train their personnel and observation of employees’ overall performance

is the most favoured method of comparison after training. The gap identified by Matofari

(2015) is that existing literature says that training practices are absolutely derived from massive

organizations. The options provided to SMEs on training exercise matters are primarily from

massive organizations. This is in line with the assumption that massive corporations training

practices can be scaled- down and utilized to small and medium sized enterprises. However

this assumption is absolutely incorrect certainly due to the fact SMEs are not scaled down

versions of massive businesses therefore tons of the training practices employed are no longer

effective in small and medium sized organizations.

Mayuran (2016) studied the impact of entrepreneurship training on performance of small

enterprises in Jaffna District. This research aimed at analysing the effect of entrepreneurship

training on overall performance of small enterprises. The conceptual framework takes the

shape of a structural equation model where entrepreneurial conduct is viewed as a product of

the training program. Training on consumer care, Quality maintenance, advertising and

economic administration have been considered beneath this model. Data was amassed via

questionnaires bought from 60 personnel from Small enterprises from Jaffna District. The

study utilized correlation and regression records to analyse the data. The findings showed a

substantial effective impact of entrepreneurship training on performance of small enterprise.

From the linear regression analysis, can be concluded that entrepreneurship coaching

contributed 85% towards the performance of small organization in Jaffna district.

23

2.4.2 Entrepreneur Trainee Competencies

Ninety percent of business failures are associated with management inadequacy which consist

of either management inexperience or incompetence (Amha et.al., 2014). Many MSE owners

or managers lack managerial training and experience. Lackeus (2013) asserts that experience

is the best predictor of business success, especially when the new business is related to earlier

business experiences. Entrepreneurs with vast experiences in managing business are more

capable of finding ways to open new business compared to employees with different career

pathways. There is widespread acknowledgement that the success, performance, survival and

growth of a SME are heavily dependent on the competencies of the entrepreneur (Valerio et.al,

2014). Mitchelmore and Rowley (2010) however point that there is an overall consensus on

the discussion of, presumably, the individuals who start and transform their business to possess

given entrepreneurial competencies. The authors state that these entrepreneur’s competencies

can be described as a certain group of competencies which is relevant to the successful

performance of entrepreneurship. Entrepreneur’s competencies relate to their survival and

success. In their study, the researchers summarize that the entrepreneurial competencies can

be defined as higher level characteristics which represent the total entrepreneur’s ability to

successfully perform a job role and as comprising of knowledge, skills and personality traits

which are influenced in turn by the education, training, family background, experience and

other demographic aspects of the entrepreneurs. Training has the ultimate effect of shaping

entrepreneurial competency or orientation and therefore contributes to entrepreneurial survival

and performance (Mukulu, 2012). According to Vijay and Ajay (2011), a competence is an

underlying characteristic of persons, which results in effective and/or superior performance in

a job. A job competence is the underlying characteristics of a person, in that may be motive,

traits, skills, aspects of one’s self-image, a body of knowledge, set of skills and cluster of

appropriate motives/traits that an individual possess to perform a given task. Entrepreneurs

especially those operating in the SME context, face numerous situations that require them to

make quick decisions, therefore having the abilities to undertake high level of conceptual

activities are important for the survival and success of their business. They posit that

competency model could shed some light into ways to increase the likelihood of business

survival and success especially in the context of a developing country.

24

The complexity in business operation in a continuously changing competitive business

environment which results from fast technological advancements requires quick remedial

action (Otieno, Bwisa & Kihoro, 2012). An entrepreneur is expected to interact with these

environmental forces which require him to be highly competent in different dimensions like

intellectual, attitudinal, behavioural, technical and managerial aspects (Penchev & Salopaju,

2011). Entrepreneurs are therefore challenged to deploy a set of competencies to succeed in

their entrepreneurial endeavours. In fact, the competency is a wider concept which includes

the knowledge, attitudes, behaviours and skills which help a person capable of transforming

his ideas into realities with an excellence in its performance in a given context. It does not refer

to those behaviours which do not demonstrate excellent performance. Finally, competencies

are not work motives, but do include observable behaviours related to motive (Kochadai,

2012). Endi, Suracham, Armanu and Djumilah (2013) found that entrepreneurial competencies

propel business performance, the higher the competence that SME owners portray the higher

the likelihood of good business performance. Most of the business failures are due to SME

owner-manager’s incompetence, inadequacy and inexperience in managing their business and

taking quick remedial action in crisis situations. Entrepreneurial competencies portfolio has a

positive impact on the organizational performance as such are positively related to

entrepreneurial survival and specifically, high entrepreneurial competencies and high

managerial competencies are linked to satisfaction on financial performance whereas high

managerial competencies and high technical competencies are linked to satisfaction on non-

financial performance. Entrepreneurial competencies are a predictor of SMEs business survival

and success (Ahmad, Ramayah, Wilson & Kummerow, 2010).

Many SMEs owners or managers lack managerial training and experience. The typical owner

or managers of small businesses develop their own approach to management, through a process

of trial and error. As a result, their management style is likely to be more intuitive than

analytical, more concerned with day-to-day operations than long-term issues, and more

opportunistic than strategic in its concept (Gerli, Gubitta & Tognazo, 2011). Although this

attitude is the key strength at the start-up stage of the enterprise because it provides the

creativity needed, it may present problems when complex decisions have to be made. A

consequence of poor managerial ability is that SMEs owners are ill prepared to face changes

25

in the business environment and to plan appropriate changes in technology. Majority of those

who run SMEs are ordinary lot whose educational background is lacking. Hence they may not

well be equipped to carry out managerial routines for their enterprises (Griffin, 2012).

Management skills relate to the owner/manager and the enterprise. Abdul and Ngugi (2015) in

a survey of small business failure maintain that entrepreneurs often have good ideas and are

competent but they do not have a clue on how to run a business and have no underlying

appreciation of business fundamentals. Professional experience has been cited as an important

factor affecting many aspects of entrepreneurial firms. Experience takes many guises and

breadth of experience is shown to be an important factor driving the performance of firms,

with the number of previous jobs positively related to new firm performance. Ropega (2011)

found a positive association between education and small business success. The likelihood of

failure was also found to be associated with the owner/manager’s work experience prior to

business launch and education. Human capital is the most critical agent of SME performance.

The recruitment of academically qualified employees is a necessary start for sustainable human

capital development in all organizations. Human capacity has become a critical index of

competition in the world of business to the extent that the development of such capacities

through training has become top priority in designing the strategic plan of business

organizations (Gerli, Gubitta & Tognazzo, 2011).

Madatta (2011) observes that the poor growth of many enterprises of all sizes, suggest that the

scarcity of competent managers is a more serious constraint on economic development. As the

enterprise becomes larger, the more need for managers to plan, coordinate and control the

activities of the enterprise. The owner who is likely to be the manager of the small enterprise

may not have the training, skills and experience to steer the operations of the business

successfully hence affecting business performance. He/she may operate in a very rigid

environment sometimes not dictated by sound business and management decision but by social

and cultural norms. The inability to keep proper records, to separate business operations from

personal, manage cash flow and growth is likely to affect business performance. The informal

sector has proved that it can be a factor that can boost economic growth in Kenya. In this sector,

practical skills are being developed at low cost and with financial support; various types of

small scale technology could be developed for labour-intensive enterprises that could absorb

26

hundreds of young job seekers. However, those who run the businesses in this sector lack

adequate business skills mainly attributed to low levels of education. It is not sufficient to know

how to produce a high quality product. The producer must also know how to sell it effectively

and how to control the financial side of the business and in doing that the entrepreneur must

be skilled in business (Mukulu, 2012). Studies show that the owners of the business with prior

work experience have relatively higher growth than those who had no prior work experience.

Research by Lackeus (2013) investigated that individual’s previous work experience has

significant influence their choice to start a business than individuals with no previous work

experience. Other scholars also argue that prior work experience of an entrepreneur has a

positive relationship with business growth (Amha, Woldehanna, Tamrat & Gebremedhin,

2014; Valerio, Parton & Robb, 2014). This indicated that past work experience has a vital role

for the entrepreneur in acquiring managerial skills to run their successful business. Another

investigation made by Mwangi and Namusonge (2015) in Kenya found that the perceived

business performance of youth entrepreneur has a positive significant correlation with their

prior work experience.

2.4.3 Nature of Training

The nature of training needs to be based on identified training needs, training objectives, an

understanding on the part of the trainees, the resources available and an awareness of learning

principles. Cheston and Kuhn (2012) explained that the most popular training and development

method used by organizations can be classified as either on-the-job or off-the-job. Looking at

the sophistication of the equipment in GPHA, the on-the-job training would be very ideal.

According to Cheston and Kuhn (2012), there are a variety of training approaches that

managers can use and these include: on-the-job training which is the most widely used training

method, as in comparison, on-the-job method of training is simple and less costly to operate.

Observing this method critically, the training places the employee in actual work situations

and makes them appear to be immediately productive. Here, there is a close collaboration

between trainer and learner. There are three common methods that are used in on-the-job

training and these are; learning by doing, mentoring and shadowing and job rotation. Learning

by doing is a very popular method of teaching new skills and methods to employees. Here the

now employee observes a senior experienced worker and learns what to do. The advantage

27

here is that this method is tried and tested and fit the requirements of the organization. The

disadvantages are that the senior worker is not usually trained in the skills and methods of

training therefore it can be a process that may be time consuming as a new comer struggles to

cope with the senior worker’s explanations. Far more successful is to use a senior or

experienced worker who has been trained in instruction or training method and whose teaching

skills are coordinated with a developed program linked to off-the-job courses (Namusonge,

2015).

Mentoring is another version of the system whereby a senior or experienced employee takes

charge of the training and development of a new employee. This suggests a much closer

association than master/apprentice and elements of a father/son relationship can exist whereby

the mentor acts as an advisor and protector to the trainee (Efobi & Orkoh, 2018). Shadowing

and job rotation usually aims to give trainee managers a feel for the organization by giving

them the experience of working in different departments. Trainees must be encouraged to feel

it is not time wasting and people in the various departments in which they are temporarily

working must feel a commitment and involvement in the training if it is to work. Unfortunately,

trainees are not usually welcomed and are seen by supervisors and workers in the department

as obstacles to the daily routines. If well structured and planned with the cooperation of all

departmental supervisors, this method can be a worthwhile learning experience (Lourenço,

Sappleton, Dardaine-edwards, Mcelwee, Cheng, Taylor & Taylor, 2014).

Job rotation is another version of training that became popular in the 1970s to help relieve

boredom and thereby raise the productivity of shop floor workers. It is a management technique

used to rotate incumbents from job to job or from department to department or from one plant

to another in different geographical areas. The rotation is done on co-ordinate basis with a view

to exposing the executives and trainees to new challenges and problems. It is also aimed at

giving executives broad outlook and diversified skills (Firdousi, 2013). If appropriately

implemented this can be an excellent learning experience for workers and suitably fits with

Human Resource Management concepts of team-work and empowerment whereby people are

encouraged to greater responsibility for their work and that of the team. On the negative side,

there have been criticisms that not enough structured training is given to enable workers to do

28

these jobs well. However, the researcher believes that on-the-job method of training has a

setback. A critical review of the method reveals that, although employees learn doing the job,

their productivity tends to be low because they do not have the skills and knowledge needed

to be effective and efficient. In an on-the-job training method, the emphasis is more on the

acquisition of specific, local knowledge in a real situation. Unlike on-the-job method, off-the-

job method emphasizes developing an understanding of general principles providing

background knowledge and generating an awareness of comparative ideas and practices (Huka,

Mbugua, & Njehia, 2015).

Vestibule Training is also method of training where the worker is trained to use machine or

perform a task similar to the ones in the real work situation. Under this method of training, the

training program is conducted out of the job in an area separate from the work place under the

supervision of a skilled instructor. After going through the vestibule training for a specified

time period, the trainees are expected to apply their newly acquired skills when they are

assigned to their real job (Jones, Beynon, Pickernell & Packham, 2013).

2.5 Chapter Summary

In chapter two, literature review has been presented. It looked at various determinants of

business success with socio-demographics, number of business location and prior training as

framework factors. Chapter three presents the research methodology as adopted in the study.

Chapter four highlights the results and findings of the data that has been analysed. Chapter five

presents the discussion, conclusions and recommendations of the study.

29

CHAPTER THREE

3.0 RESEARCH METHODOLOGY

3.1 Introduction

This chapter aims to highlight the determinants of business performance of agriprenuers in

Kenya by highlighting the research methodology adopted in the study. The chapter is arranged

as follows: research design, population and sampling design, sampling frame, sampling

technique, sampling size, data collection methods, research procedures, data analysis methods,

and chapter summary.

3.2 Research Design

Research Design is the plan that guides data collection to acquire the targets of research, i.e.,

to generate new information primarily based on present ones (Regoniel, 2017). There are two

types of research designs. Qualitative and quantitative research designs. The qualitative

research design method involves the use of qualitative data, such as interviews. The qualitative

research approach involves records series of non-public experiences, introspection, stories

about life, interviews, observations, interactions and visual texts which are significant to

people's life.Quantitative Research on the other hand encompasses a variety of techniques

worried with the systematic investigation of social phenomena, the usage of statistical or

numerical data (Watson, 2015). Therefore, quantitative research involves size and assumes that

the phenomena below study can be measured. It sets out to analyse statistics for developments

and relationships and to verify the measurements made. Some items, such as peak and weight,

are effortless to measure; others, such as what humans think or feel, are tough to measure.

There are two types of variables in Quantitative Research: independent and dependent. An

independent variable may additionally influence the measurement of the dependent one.

The research undertook a descriptive approach. Descriptive research is study used to describe

situations. There are three main descriptive research methods. This are observational, case-

study and survey methods. The research used questionnaire survey as a data collection method

of choice. The research aimed to establish the following research questions: What is the effect

30

of socio-demographics on business performance? What is the effect of number of business

location on business performance? What is the effect of prior entreprenership training on

business performance? The collection and data analysis ensured that the researcher was able

to determine the nature of the relationships. The research will inform policy makers on how

best they can assist entreprenuers in their bid to improve business performance.

3.3 Population and Sampling Design

3.3.1 Population

Population refers to the source of the sample. Through study of the sample, one is able to make

inferences or generalization about the population.(Saunders, 2016). The population for this

research were 1,200 agriprenuers in nine counties in Kenya, namely Nyandarua, Nakuru,

Kakamega, Bungoma, Kiambu, Kericho, Kisumu, Siaya and Nairobi.

3.3.2 Sampling Design

Sampling Design is the framework that serves as the groundwork for the decision of a survey

sample and impacts many different vital aspects of a survey as well. In an extensive context,

survey researchers are fascinated in obtaining some type of data through a survey for some

population, or universe, of interest (Lavrakas, 2011). Sampling design can also be defined as

the representation of the population of interest, from which a pattern is to be drawn. The

sampling design can also be same to the population, or it might also be solely phase of it and

is consequently concern to some under coverage, or it may have an oblique relationship to the

population,

3.3.2.1 Sampling Frame

Sampling frame is the source material or system from which one draws a sample. It is a list of

all those within a population who can be sampled, and can also encompass individuals,

households or institutions (Johnson & Kuby, 2012). The sampling frame for this study was 492

entrepreurial participants from nine counties of Nyandarua, Nakuru, Kakamega, Bungoma,

Kiambu, Kericho, Kisumu, Siaya and Nairobi. and was obtained from respondents of the Metro

Agrifood Living Lab project.

31

3.3.2.2 Sampling Technique

There are two types of sampling techniques that can be used when it comes to research.

Probability Sampling and Non-probability Sampling. Probability sampling uses randomization

so as to ensure that everyone in the target population have a chance of being selected.. It

includes selecting a preferred pattern measurement and selecting observations from a

population in such a way that each statement has an equal chance of determination until the

favoured pattern measurement is performed. Propotional sampling on the other hand is where

a researcher divides the finite population into different subpopulation after which random

sampling techniques are applied (Bock, 2019). This study used proportionate sampling by

ranking the top male entreprenuers with the top female entreprenuers so as to ensure equal

gender representation.

3.3.2.3 Sampling Size

Sample size is a count number of individual samples or observations in any statistical setting,

such as a scientific scan or a public opinion survey. Though an extraordinarily simple concept,

desire of pattern size is a quintessential willpower for a project (Zamboni, 2018). Too small a

sample yields unreliable results, while an overly large sample needs an exact deal of time and

resources. In this study, the sample size was 492 respondents. The selection criteria used to

narrow down to the sample size was that the respondents had to be of the ages of between 18

to 35 years, must have good spoken and written English literacy and their business must have

been in existence for more than six months. Even though female participants ranked lower

than their male counterparts, affirmative action was used so as to apply different benchmarking

scales as the study looked to allow for a 60% female representation.

3.4 Data Collection Methods

This research study relied on primary data that was collected from the

respondents.Questionnaires were used as the main data collection technique due to it’s

quantitative nature. The questionnaires include both structured and open ended questions. The

questionnaire provided the advantage of a high degree of standardisation, as well as being

structured and time saving. It was also advantageus to the respondents due to it’s anonymity

factor.

32

3.5 Research Procedures

The research started with The letter was then submitted to NACOSTI so as to get a research

permit from the Government of Kenya. Participants were made aware of the purpose of the

study as well as the fact that this was a voluntary exercise. Thereafter, data collection was

conducted.

3.6 Data Analysis Methods

The data collected for the study was statistically analysed using the Statistical Package for

Social Sciences (SPSS). Descriptive statistics was generated using this step and included

frequency tables as well as percentages which were used to clearly capture the demographic

profile of all participants. Multiple regression analysis was used so as to determine the

relationship between business performance and socio-demographics, business location and

prior training experience.

3.7 Chapter Summary

This chapter has presented the methodology used in the study in order to answer the research

objectives raised in chapter one. It provides a summary of the research design, population and

sampling design, sampling frame, sampling technique, sampling size, data collection methods,

research procedures as well as the data analysis methods used. Both descriptive and explorative

research designes were used for this study. SPSS was then used as the statistical analysis tool.

Chapter four presents the results and findings of the study. Chapter five presents the discussion,

conclusions and recommendations of the study.

33

CHAPTER FOUR

4.0 RESULTS AND FINDINGS

4.1 Introduction

The purpose of the study was to investigate the determinants of business perfomance of

agriprenuers in Kenya. The chapter presents both data analysis and research findings of this

study. In order to simplify the discussions, the presentation was done using graphs, charts and

tables that summarize the collective reactions of the respondents. The data analysis looked to

answer: What is the effect of socio-demographics on business performance? What is the effect

of number of business location on business performance? What is the effect of prior training

experience on business performance? With a sample size of 492, agriprenuers from 9 counties

of Nyandarua, Nakuru, Kakamega, Bungoma, Kiambu, Kericho, Kisumu, Siaya and Nairobi

were selected.

4.2 Response Rate

The study population was 1,200, out of which a sample of 492 were selected, and their

questionnaires dully filled. This represented a response rate of 100% which was within what

Kothari (2003) prescribed as a significant response rate for statistical analysis, as it was higher

than 50%.

4.3 Demographic Information

4.3.2 Age of Respondents

The study findings indicated that 33.9% of the respondents were between 31-35 years, 36.4%

were between 26-30 years, 24.4% were between 20-25 years while 5.3% were between 36-40

years. This revealed that most of the entrepreneurs in the counties of study were between 26-

30 years.

34

Table 4.1: Age of Respondents

Age Group Frequency Percent

20-25 120 24.4

26-30 179 36.4

31-35 167 33.9

36-40 26 5.3

Total 492 100.0

4.3.3 County of Residence

From the responses obtained, 18.7% of the entrepreneurs were from Bungoma, 16.9% were

from Kakamega, 3.9% were from Kericho, 4.5% were from Kiambu, 8.5% were from Kisumu,

2.8% were from Nairobi, 12.6% were from Nakuru, 16.3% were from Nyandarua while 15.9%

were from Siaya County.

Table 4.2: County of Residence

County Frequency Percent

Bungoma 92 18.7

Kakamega 83 16.9

Kericho 19 3.9

Kiambu 22 4.5

Kisumu 42 8.5

Nairobi 14 2.8

Nakuru 62 12.6

Nyandarua 80 16.3

Siaya 78 15.9

Total 492 100.0

35

4.3.4 Marital Status

The study findings revealed that 41.3% of entrepreneurs in the study counties were married,

0.8% were separated, 57.3% were single while 0.6% of the respondents were widowed as

shown in table 4.4 below.

Table 4.3: Marital Status of Respondents

Marital Status Frequency Percent

Married 203 41.3

Separated 4 .8

Single 282 57.3

Widowed 3 .6

Total 492 100.0

4.4 Effects of Socio-Demographics on Business Performance

4.4.1 Gender of the Respondents

Out of a sample of 492 respondents, 263 were male as represented by 53.5% while 229 were female as

represented by 46.5%. This implies that the researcher was not biased when collecting data. It also means

that the male correspondents were the most beneficiaries of entrepreneurial training. It can also be seen

that male respondents got more sales than female. The results are as shown in Table 4.1.

36

Table 4. 4: Distribution of the Respondents by Gender

Sales Total Percent

N/A Less

than

20000

Ksh.

20000-

Ksh.

30000

Ksh.

31000-

Ksh.

40000

Ksh.

41000-

Ksh.

50000

Ksh.

50000

and

above

Male 13 122 62 24 5 37 263 53.5

Female 24 96 51 17 10 31 229 46.5

Total 37 218 113 41 15 68 492 100.0

4.4.2 Age Bracket of the Respondent

The research further required the respondents age. The findings reveal that most of the respondents as

shown by 36.0% were aged between 25-29 years, 34.3% were aged between 30-34 years, and 17.7% were

aged between 20-24 years while 12.0% were aged between 35-39 years. This implies that the researcher

considered all the required age groups and hence the data collected was reliable and accurate. As can be

seen on Table 4.2, the youth bracket of between the ages of 20-29 years get less monthly sales compared

to those who are above 30 years old. However the age bracket of between 20-24 years had greater

combined sales than the rest of the age groups.

37

The findings were presented in Table 4.2.

Table 4. 5: Distribution of the Respondents by Age

Sales Total % Mean Std.

Dev. N/A Less

than

20000

Ksh.

20000-

Ksh.

30000

Ksh.

31000-

Ksh.

40000

Ksh.

41000-

Ksh.

50000

Ksh.

50000

and

above

20-

24

years

37 30 20 0 0 0 87 17.7 4.74 0.54

25-

29

years

0 141 36 0 0 0 177 36.0 2.06 0.60

30-

34

years

0 47 57 38 0 27 169 34.3 1.00 0.00

35-

39

years

0 0 0 3 15 41 59 12.0 0.37 0.49

Total 37 218 113 41 15 68 492 100.0

The findings reveal that most of the respondents as shown by 36.0% were aged between 25-29 years,

34.3% were aged between 30-34 years, and 17.7% were aged between 20-24 years while 12.0% were

aged between 35-39 years. This implies that the researcher considered all the required age groups and

hence the data collected was reliable and accurate. The study also established that most of the people who

benefit from this entrepreneurial training are youth. This implies that the youth bracket, of those between

the ages of 18-35 years are more vibrant and have better business ideas worth training those above the 35

years of age as can be seen by the percentage of those taking part in entrepreneurial training. The 12%

above 35 years of age were 35 at the time of training.

38

Figure 4. 1: Distribution of the Respondents by Age

4.4.5 Respondents’ Highest Level of Education

The study further looked into the respondents’ highest level of education. The results were displayed on

Table 4.4. 30.3% of the respondents had finished high school, 26.4% had reached college level, 23.6%

had attained a Bachelor degree, 6.5% had reached Technical Training/ Polytechnic, 4.9% had finished

primary school, 3.9% had reached some high school, 2.0% indicated others not mentioned (dropping out,

Diploma, Special school, joining university, 4th year), 1.8% indicated some primary school while 0.6%

indicated they had reached the Masters level. This implied that most if the respondents had acquired

enough basic education to understand the questionnaire and give reliable data. The results also show that

most of the entrepreneurs with a big margin in sales per month had completed high school while others

like those who had reached college and those who had acquired a Bachelor degree also had more sales.

Therefore, it can be concluded that those with more education can get more sales than those who do not

as they are able to could grasp ideas and can manage their businesses well enough.

39

Table 4. 6: Distribution of the Respondents by Highest Level of Education

Sales Total Percent

N/A Less

than

20000

Ksh.

20000-

Ksh.

30000

Ksh.

31000-

Ksh.

40000

Ksh.

41000-

Ksh.

50000

Ksh.

50000

and

above

Some primary

school

0 6 0 1 1 1 9 1.8

Finished

primary school

1 11 3 2 0 7 24 4.9

Some high

school

1 6 3 2 4 3 19 3.9

Finished high

school

20 68 31 9 1 20 149 30.3

Technical

Training/

Polytechnic

1 10 12 6 0 3 32 6.5

College 6 56 31 11 8 18 130 26.4

Bachelor

degree

5 59 29 8 1 14 116 23.6

Masters 0 0 1 1 0 1 3 .6

Others Specify 3 2 3 1 0 1 10 2.0

Total 37 218 113 41 15 68 492 100.0

40

4.5.1 Inferential Statistics

4.5.1.1 Correlation Analysis on the Effects of Socio-economic Demographics on Business

Performance

Correlation analysis revealed that there is a significant relationship between physical location and

business success, r (0.450); p-value < 0.05. This implied that socio-economic demographics influences

business performance.

Table 4.7: Correlation Analysis on the Effects of Socio-economic Demographics on Business

Performance

Socio-economic

demographics

Business

Performance

Socio-economic

demographics Pearson Correlation 1 .450**

Sig. (2-tailed)

0

N 492 492

Business Performance Pearson Correlation .450** 1

Sig. (2-tailed) 0

N 492 492

** Correlation is significant at the 0.01 level (2-tailed).

4.5.1.2 Regression Analysis

The findings in Table 4.19 revealed an adjusted R square value of 0.192 which implies that 19.2% of the

variation in business performance is attributed by variations in socio-economic demographics and the

remaining 80.8% of variation is attributed to other factors outside the regression model.

41

Table 4.8: Model Summary for Socio-economic Demographics

Model R R Square

Adjusted

R Square

Std. Error of

the Estimate

1 .450a 0.203 0.192 0.18958

a Predictors: (Constant), socio-economic demographics

The Analysis of Variance (ANOVA) was used in determining whether there was a

statistically significant relationship between socio-economic demographics and business

performance.

Table 4.9: Analysis of Variance (ANOVA) for Socio-economic Demographics

ANOVAa

Model Sum of Squares Mean Square F Sig.

1 Regression 1.262 1.262 168.229 .000b

Residual 0.345 0.008

Total 1.607

a Dependent Variable: Business Performance

b Predictors: (Constant), Prior Training

Experience

4.6 Effects of Business Location on Business Performance

4.6.1 Infrastructure Access

4.6.1.1 Distance of Business from Nearest Tarmac Road

The research shows that 36.2% of the respondents’ business was less than 1km from the

tarmac. However 35.0% of the respondents also noted that their businesses were more than

3km from the tarmac. This is a huge number that points at the need for continued infrastructure.

42

Figure 4.4: Distance of Business from Nearest Tarmac Road

The study established that those that were closer to the road had far much better sales than

those who more than one kilometre away from the tarmac road. This is associated to the fact

that those near the road can access their goods faster and safer than the rest. Also, most business

people or consumers would easily be found closer to the road. This therefore implies that

monthly sales increase the closer the entrepreneurs are to the road.

Table 4.10: Distance from Tarmac Road & Sales

Sales Total Percent

N/A Less

than

20000

Ksh.

20000-

Ksh.

30000

Ksh.

31000-

Ksh.

40000

Ksh.

41000-

Ksh.

50000

Ksh.

50000

and

above

Less

than

1Km

16 78 44 14 7 19 178 36.3

Between

1-3 Km

5 62 36 13 4 22 142 29.0

More

than 3

Km

16 77 33 13 4 27 170 34.7

Total 37 217 113 40 15 68 490 100.0

0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

30.00%

35.00%

40.00%

Between 1-3 km Less than 1 km More than 3 km

Distance of Business from Nearest Tarmac Road

43

4.6.2.2 Main Source of Energy

Source of energy was also looked at with regards to location based factors. KPLC and Solar

was the biggest energy contributors with 36.7% and 28.6% respectively. That accounts to

65.3% of energy source.

Table 4.11: Main Source of Energy

Category Frequency Percentage (%)

Biogas 1 0.20%

KPLC 181 36.70%

KPLC/Solar/Biogas/Kerosene/Biogas/Other 69 14.00%

Kerosene 34 6.90%

Kerosene/Other 5 1.00%

Solar 141 28.60%

Solar/Biogas 2 0.40%

Solar/Kerosene/Other 30 6.00%

Solar/Other 13 2.60%

No Response 5 1.00%

4.6.2.3 Mobile Network Connectivity

Mobile Network Connectivity was seen as advanced within the 9 counties, with 92.1% having

network coverage. 5.5% recorded no mobile connectivity with 2.4% of the respondents giving

no response.

Table 4.12: Mobile Network Connectivity

Category Frequency Percentage (%)

Yes 453 92.10%

No 27 5.50%

No Response 12 2.40%

44

4.6.2.4 Geographical Coverage of Business

Most businesses only had between 1-2 location coverages at a valid percentage 74.80%, with

only 16.87% of the respondents having more than three locations in which their business

covered. This meant that this was an ideal indicator of business progress, as the more location

coverage the more sales one can get.

Table 4.13: Geographical Coverage of Business

Location Frequency Percent

0 4 0.81%

1 368 74.80%

2 83 16.87%

3 10 2.03%

4 11 2.24%

5 3 0.61%

6 1 0.20%

7 1 0.20%

No Response 11 2.24%

Total 492 100%

4.6.2.5 Inferential Statistics

4.6.2.5.1 Correlation Analysis on Effects of Business Location on Business Performance

Pearson’s correlation was used to analyse the statistical relationship between business location

and business performance. Table 4.14 indicates that there was a strong positive correlation

between the variables at 1% level of significance. The r value for the relationship between

business location and performance was 0.886. Since p, 0.00 for all the independent

variables<0.05 is an indication that the independent variables were good predictors of the

dependent variable.

45

Table 4.14: Correlation Analysis between Business Location and Business Performance

Business Location

Business

Performance

Business Location Pearson Correlation 1 .886**

Sig. (2-tailed)

0

N 492 492

Business Performance Pearson Correlation .886** 1

Sig. (2-tailed) 0

N 492 492

** Correlation is significant at the 0.01 level (2-tailed).

4.6.2.5.2 Regression Analysis

Regression analysis was conducted to establish the relationship between business location and

business performance. R2 or the coefficient of determination measures the extent with which

business location was used to explain variation in business performance. From the, the value

of adjusted R2 is 0.785. This implies that 78.5% variation in business performance is explained

by business location. The correlation coefficient R of 0.886 shows that there was a strong

positive correlation between business location and business performance.

Table 4.15: Model Summary for Business Location

Model R R Square

Adjusted

R Square

Std. Error of the

Estimate

1 .886a 0.785 0.781 0.0866

a Predictors: (Constant), Business Location

The analysis of variance in the table 4.16 shows the model result of model fitness which

indicates an F -statistic of 168.229 and a p-value of 0.000<0.05. Since F-calculated is greater

than the F-critical (value = 80.883), this shows that the overall model was statistically

significant. This indicates that the model is fit for prediction at 95% confidence level.

46

Table 4.16: Analysis of Variance (ANOVA) for Business Location

ANOVAa

Model Sum of Squares Mean Square F Sig.

1 Regression 1.262 1.262 168.229 .000b

Residual 0.345 0.008

Total 1.607

a Dependent Variable: Business Performance

b Predictors: (Constant), Business Location

Table 4.17: Coefficient Analysis for Trainee Business Location

Coefficientsa

Model

Unstandardized

Coefficients

Standardized

Coefficients T Sig.

B Std. Error Beta

1 (Constant) 1.335 0.024

55.422 0

Business

Location 1.036 0.08 0.886 12.97 0

a Dependent Variable:

Business Performance

The results in the Table 4.17 shows that when trainee business location is taken into account and

the constant held at zero the business performance will be 1.335. However, the significance

value is 0.00 which is less than the critical value of 0.05. This implies that the constant is

statistically significant. The results computed indicates a 1% increase in trainee’s business

location will lead to 88.6% increase in the business performance.

47

4.9 Effects of Prior Training Experience of Trainee on Business Performance

4.9.1 Training and Business Performance

The study sought the number of trainings (workshops, seminars, conferences) attended by the

respondents in the last three years. Table 4.15 shows the results. From the findings, most of

the respondents indicated that they had attended one training but the most number of trainings

attended by the some of the respondents were 5. The results showed that those that went

through more training sessions had more knowledge on strategies they could implement to

better their sales, and hence had more sales than the rest. This can be seen in Table 4.15 where

those who attended more than one training had better sales. The researcher required to know

the areas in which the respondents had received training on. The research findings were as

shown on Table 4.16.

Table 4.18: Number of Trainings Attended

Sales Total Mean Std.

Dev. N/

A

Less

than

2000

0

Ksh.

20000

-Ksh.

30000

Ksh.

31000

- Ksh.

40000

Ksh.

41000

-Ksh.

50000

Ksh.

5000

0

and

abov

e

N/A 37 30 0 0 0 0 67 0.45 0.50

1

Training

0 188 56 0 0 0 244 1.23 0.42

2

Training

s

0 0 57 38 0 0 95 2.40 0.49

3

Training

s

0 0 0 3 15 45 63 4.67 0.57

4

Training

s

0 0 0 0 0 20 20 5.00 0.00

More

than 4

0 0 0 0 0 3 3 5.00 0.00

48

Total 37 218 113 41 15 68 492

The findings reveal that 66.5% of the respondents indicated that they had received training on

entrepreneurship, also 63.6% received training on keeping records, 57.3% received training on

marketing, 53.7% received training on generating business ideas, 49.8% received training on

financial literacy, 44.9% received training on adding value to food items, 32.1% received

training on registering businesses, 26.6% received training on basic writing, 24.6% received

training on use of computers. The respondents moreover indicated the main challenges of

attending training as shown on Table 4.11.

Table 4.19: Areas of Training

Frequency Percent

Keeping records 313 63.6

Basic writing 131 26.6

Adding value to food items 221 44.9

Registering businesses 158 32.1

Financial literacy 245 49.8

Use of computers 121 24.6

Marketing 282 57.3

Generating business ideas 264 53.7

Entrepreneurship 327 66.5

From the results, the main challenges of attending training as per 59.3% of the respondents

was the distance to training venues, 53.9% indicated the lack of opportunity, 36.6% indicated

the fees required, 8.5% indicated the family, 4.7% indicated the low education level, 3.3%

indicated the difficult training, 1.8% indicated that the previous training they had attended did

not help them while 0.2% indicated the they felt bad in the classroom. Some 13.4% of the

respondents also added other challenges such as transport fare, timings of the training, strict

measures and relevance of the training.

49

Table 4.20: Main Challenges of Attending Training

Frequency Percent

Distance to training venues 292 59.3

Family 42 8.5

Low education level 23 4.7

Fees required 180 36.6

Difficult training 16 3.3

I feel bad in the classroom 1 0.2

Lack of opportunity 265 53.9

Previous training I attended did not help me 9 1.8

Other 66 13.4

The respondents were further required to indicate where they would prefer that the training

takes place if offered the opportunity to train. As shown in Figure 4.11, 46.8% of the

respondents indicated that they preferred somewhere within their county in order for them to

save time and reduce costs; 34.5% indicated near their homes or businesses due to convenience

and reduction in transport expenses; while 18.7% indicated away from their county in order to

get more exposure/networking.

Figure 4. 2: Training Area Preferences

50

4.9.2 Inferential Statistics

4.9.1.2 Correlation Analysis on Training Experience of a Trainee on Business

Performance

The results of the correlation analysis showed a strong positive correlation between prior

training experience and business performance where the (P-value was 0.000<0.05, and Sig. (2-

tailed), was 0.918) across the nine counties in the study.

Table 4.21: Correlation between Prior Training Experience and Business Performance

Prior Training

Experience

Business

Performance

Prior Training Experience Pearson Correlation 1 .918**

Sig. (2-tailed)

0

N 492 492

Business Performance Pearson Correlation .918** 1

Sig. (2-tailed) 0

N 492 492

** Correlation is significant at the 0.01 level (2-tailed).

4.9.1.3 Regression Analysis

The results in the table 4.22 indicates that R2 is 0.843 implying that independent variable can

predict the dependent variable at 84.3%. Also, the variation between business performance and

prior training experience is explained by 84.3%. This shows a relationship between business

performance and prior training experience. From the findings the value of R2 is an indication

that the variation of 84.3% on monthly sales is due to changes in prior training experience at

95% confidence interval.

Table 4.22: Model Summary for Prior Training Experience

Model R R Square

Adjusted

R Square

Std. Error of

the Estimate

51

1 .918a 0.843 0.84 0.07402

a Predictors: (Constant), Prior Training Experience

The ANOVA in table 4.23 measured the extent to which the regression model predicted the

outcome variable. The F-test calculated at 5% significance at two degrees of freedom. The p-

value of 0.00 was less than 0.005. These imply that prior training experience is statistically

significance in predicting business performance.

Table 4.23: Analysis of Variance (ANOVA) for Prior Training Experience

ANOVAa

Model Sum of Squares Mean Square F Sig.

1 Regression 1.262 1.262 168.229 .000b

Residual 0.345 0.008

Total 1.607

a Dependent Variable: Business Performance

b Predictors: (Constant), Prior Training

Experience

A unit increase in the prior training experience leads to a 1.295 increase in business

performance. Conversely, prior training experience was found to be statistically significant as

the p value was less than 0.05.

Table 4.24: Coefficient Analysis for Prior Training Experience

Coefficientsa

Model

Unstandardized

Coefficients

Standardized

Coefficients t Sig.

B Std. Error Beta

1 (Constant) 1.295 0.022

58.267 0

52

Prior training

experience 1.601 0.102 0.918 15.724 0

a Dependent Variable: Prior Training

Experience

4.10 Chapter Summary

This chapter highlighted the results and findings of the study. Descriptive statisitics was first

presented so as to showcase the general attributes of respondents selected for the study. The

rest of the study presented analysis as guided by the research questions. There after regression

analysis was done so as to determine business performance of agriprenuers in Kenya. Overall,

socio-demographics had a positive effect on the agribusiness performance in Kenya. Number

of business location and prior training experience also had a significant effect on business

performance. All the variables were significant at p<0.05. The next chapter will present the

discussion, conclusions and recommendations of the study.

53

CHAPTER FIVE

5.0 DISCUSSION, CONCLUSIONS AND RECOMMENDATIONS

5.1 Introduction

This chapter presents the summary of the empirical findings derived from the study, the

discussions, conclusions, relevant recommendations and recommendations for further

research. The overall objective of the study was to establish the determinants of business

performance.

5.2 Summary

The study sought to establish the determinants of business performance. The study was guided

by the following research questions: What is the effects of socio-demographics on business

performance? And what is the effect of number of business location on business performance?

What is the effect of prior training experience on business performance? The research study

covered entrepreneurs from 9 counties in Kenya: Bungoma, Siaya, Kisumu, Nyandarua,

Kiambu, Kakamega, Nakuru, Kericho and Nairobi. 492 entrepreneurs were selected from a

population of 1200 to participate in the research. Both descriptive and inferential statistics were

analysed with the use of SPSS, with findings presented using tables and figures. In the first

objective socio-demographics had a positive effect on business performance. On average, one

more year contributed to an increase in monthly sales by 0.450 units. The p < 0.05 and thus

significant. In the second objective, with all variables held constant, a unit change in number

of business location lead to a 0.886 change in business performance. The variable was

significant as the p<0.05. In the third objective, the study revealed that prior training

experience was significant with a p<0.05. This meant that a unit change in prior training

experience lead to a 0.918 unit change in business performance in Kenya.

5.3 Discussion

5.3.1 Socio- Demographics and Business Performance

The study found that a majority of the respondents were between the ages of 25-29 years. From

the regression analysis, socio-demographics (age) had a positive effect on business

54

performance. The findings were in line with those of Hurtado, Pineda and Florencio (2017)

who found that actual and perceived entrepreneurial skills are acquired overtime and

consequently age has an impact on entrepreneurship. For example it has been suggested that

many people age thirty or less may not have acquired sufficient organizational experience

while those age forty five or more may no longer possess the acquired energy. This study also

found that most of the respondents were the head of the households and were male. The

findings coincided with World Bank (2011), the number of men and women owning micro-

enterprises in Kenya was almost equal, at 670,727 enterprises owned by men compared to

612,848 owned by women accounting for 47.4 per cent of all those in MSEs. The study found

that most of the respondents had finished high school. The findings were in line with those of

Pantea (2016) noted that those with more education and training are more likely to be

successful in the MSE sector. As such, for small businesses to do well in Kenya, entrepreneurs

need to be well equipped in terms of skills and management. MSEs in ICT appear to be doing

well with the sprouting of many commercial colleges offering various computer applications.

5.3.2 Business location and Business Performance.

The research established that most of the businesses were close to the tarmac road and got their

energy from electricity (from KPLC). Further, the most of the businesses get their water from

a borehole. A majority of the entrepreneurs owned a mobile phone that was a smartphone.

Further, majority of the businesses were at a place with mobile network coverage and therefore

the entrepreneurs used the internet regularly. Their homes although were not connected to the

sewage system. These findings noted that MSEs located in urban areas typically have a relative

ease of access to customers and the inputs required (i.e. finance, premises, technology, etc.) to

produce goods or services. MSEs located in urban areas may benefit from agglomeration

economies and spatial externalities (i.e. specialized infrastructures, information, network of

suppliers, specialized labour, specialized knowledge, concentration of existing exporters, etc.).

Further, De Grip and Pleijers (2019) detected that urban firms benefiting from external

agglomeration economies were more likely than rural firms to be exporters. However, the costs

associated with most inputs are generally higher in urban areas, which may constrain MSE

development. Seo and Lee (2019) suggested that enterprises located in urban areas might face

different closure possibilities than their rural counterparts.

55

5.3.3 Prior Entrepreneurial Training and Business performance

The study found that the entrepreneurs received training on entrepreneurship, keeping records,

marketing, generating business ideas, financial literacy, adding value to food items, registering

businesses, basic writing and use of computers. The study also established that most of the

entrepreneurs were challenged by the distance to the training venues and preferred somewhere

within their county in order for them to save time and reduce costs. The findings conform to

the findings of Lackeus (2013) asserts that experience is the best predictor of business success,

especially when the new business is related to earlier business experiences. Entrepreneurs with

vast experiences in managing business are more capable of finding ways to open new business

compared to employees with different career pathways. Additionally, the findings concur with

Mitchelmore and Rowley (2010) who discovered that training has the ultimate effect of

shaping entrepreneurial competency or orientation and therefore contributes to entrepreneurial

survival and performance.

5.4 Conclusions

5.4.1 Socio-demographics and Business Performance

The study concluded that socio-demographics have a positive and significant effect on business

performance. The study concluded that demographics such as age and level of education affect

the performance of a business to a great extent. With many young women and men unable to

secure formal employment opportunities, encouraging entrepreneurship is an ever more

important way of harnessing their enthusiasm, energy and ambition to contribute to economic

development while record keeping, inventory control, operation of a bank account are some of

the key things that if taught, the youth enterprises will stand a higher chance of surviving

because a lack of skills has been seen as a major challenge to entrepreneurs and thus skills

acquired through training can provide a long lasting solution towards survival of businesses.

5.4.2 Number of business location and Business Performance

The study further concluded that business location has a positive and significant effect on

business performance. Specifically, the study showed that the more a business is in different

areas, the more it grows and hence better performance.

56

5.4.3 Prior Training Experience and Business Performance

The study concluded that prior training experience has a positive and significant effect on

business performance. The study deduced that the content of training positively significantly

influence business performance.

5.5 Recommendations

5.5.1 Socio-demographics and Business Performance

The study recommends that the government and private sector through CSR should look at

ways in which they can help founders of SMEs through both age and gender specific programs

that can positively affect business performance. Programs such as female only incubators can

help bridge the gap between female founders and their male counterparts.

5.5.2 Number of business location and Business Performance

The study recommends that improving access to number of business location through

infrastructural development will enhance business performance. In addition, the government

should also play a part in subsidizing costs through business grants that help entrepreneurs

expand into other locations much quicker.

5.5.3 Prior Training Experience and Business Performance

The study recommends that the capacity of agripreneur’s should be enhanced through trainings

and workshops as appropriate. The study also recommends that SME businesses in Kenya to

grow and become sustainable, concerted effort should be made by SME business owners in

building social networks that guarantee success. Networking brings in new clients, and creates

loyalty for existing clients hence the ability of SME’s to grow. SME owners should equally

invest in their own business education, the education of their employees and family members

regarding business operations. Secondly, SME business owners should enhance their business

education so as to understand the intricate operations of business, not only in value addition,

but also how to develop and maintain social networks with clients. Broadening the content of

training which will equip the trainees with technical and managerial knowledge on how to

successfully operate the business.

57

5.5.3.1 Recommendations for Further Studies

A comparative study should be carried out to compare whether the findings also apply for other

sectors in different areas in order to validate whether the findings can be generalized to others

in Kenya. The study also recommends further studies to focus on other factors which are not

covered in this study such as competitors, economy, technology and politics.

58

REFERENCES

Abdul, R. O. & Ngugi, K. (2015). Influence of entrepreneurial competencies on the growth of

small and medium enterprises in Kenya: A case of Nairobi County. International

Journal of Social Sciences and Entrepreneurship, 4(4), 1-22.

Abor, J. & Quartey, P. (2010). Issues in SME development in Ghana and South Africa.

International Research Journal of Finance and Economics, 39(6), 215-228.

Ahaibwe, G. & Kasirye, I. (2015). Creating Youth Employment through Entrepreneurship

Financing: The Uganda Youth Venture Capital Fund. Kampala: Makarere University

Press.

Ahmad, N.H., Ramayah, T., Wilson, C. & Kummerow, L. (2010). Is Entrepreneurial

Competency and Business Success Relationship Contingent Upon Business

Environment? A Study of Malaysian SMEs. International Journal of Entrepreneurial

Behavior & Research, 16(3), 182-203.

Akhamiokhor, S., & Adanikin, A. (2017). Entrepreneurial strategies and small and medium

scale enterprises (SMEs) development in Ogun State, Nigeria. International and Public

Affairs Journal, 1(1), 34-38.

Amha, W. (2015). Growth of youth-owned MSEs in Ethiopia: characteristics, determinants

and challenges. Ethiopian Journal of Economics, 24(2), 93-128.

Amha, W., Woldehanna, T., Tamrat, E. & Gebremedhin, A. (2014). The characteristics and

determinants of entrepreneurship in Ethiopia. Ethiopian Journal of Economics, 24(1),

131-165

Audi, M., Ali, A. (2017). Entrepreneur trainee’s socio-economic Development, Demographic

Changes And Total Labor Productivity. Pakistan: A Co-Integrational and

Decomposition Analysis.

Aylin, I. (2013). Europe restructuring in SMEs: Comparative Growth and Sustainable Jobs.

Dublin: Euro found.

Azim, M. T. & Al-Kahtani, A. H. (2014). Entrepreneurship Education and Training:ASurvey

of Literature. Life Science Journal, 11(1), 127-135.

Bock, T (2019). What is Random Sampling. Displayr. https://www.displayr.com/what-is-

random-sampling/

59

Carron, M., Alarcon, P., Karani, M., Muinde, P., Akoko, J., Onono, J. … Rushton, J. (2017).

The Broiler Meat System in Nairobi, Kenya : Using a Value Chain Framework to

Understand Animal and Product Flows, Governance And Sanitary Risks. Preventive

Veterinary Medicine, 147, 90–99.

Cheston, Y. M. & Kuhn, N. B. (2012). Mediating Role of Training on the relationship between

Micro-Finance Factors and Women micro Entrepreneurs’ business performance in

Gombe Nigeria: a Conceptual Framework.

De Gobbi, M. S. (2014). Making Youth Entrepreneurship Work in Sub-Saharan Africa: Some

Factors of Success. Open Journal of Business and Management, 2(04), 305.

De Grip, A. & Pleijers, A. (2019) Workshop Attendance as a Mode of Learning: Evidence

from the Netherlands. Vocations and Learning, 12, 361–385.

Dixit, A., Clouse, C. & Turken, N. (2019). Strategic Entreprenuer trainee’s number of business

sitesbusiness location Decisions: Importance of Economic Factors and Place Image.

Rutgers Business Review. 4(1).

Dladla, G.L. & Mutambara, .E. (2018). The The Impact of Training and Support Interventions

on Small Businesses in the Expanded Public Works Programme – Pretoria Region.

Graduate School of Business & Leadership, University of KwaZulu-Natal.

http://dx.doi.org/10.20944/preprints201809.0436.v1/

Ebitu, N. (2013). Financing Small and Medium Enterprises in Ghana .Challenges of Accessing

Bank Credit: Ghana.

Efobi, U., & Orkoh, E. (2018). Analysis of the Impacts of Entrepreneurship Training on

Growth Performance of Firms. Journal of Entrepreneurship in Emerging Economies,

10(3), 524-542

Ekanem, L. (2010). Liquidity Management in Small Firm. .A learning Perspective Journal of

Business Development, 17(1) 12-19.

Endi, S., Surachman, A, & Djumilah, H, (2013). Entrepreneurial Characteristics and

Competency as Determinants of Business Performance in SMEs. Journal of Business

and Management, 7(3), 30-38.

FAO. (2011). Food and Agriculture Organisation. FAO-Adapt Framework Programme on

Climate Change Adaptation, Rome.

60

Firdousi, F. (2013). Significance of determining assessment needs and training in the service

sector. International Journal of Business and Social Science, 2 (17), 113-116.

GEM. (2012).Global Entrepreneurship Monitor. Global Report.

Gerli, F., Gubitta, P., & Tognazzo, A. (2011). Entrepreneurial Competencies and F i r m

Performance: An Empirical Study Paper presented at t h e VIII International Workshop

on Human Resource Management Conference Proceedings, Seville. Retrieved from:

https://www.researchgate.net/publication/228314296_Entrepreneurial_Competencies

_and_Firm_Performance_An_Empirical_Study

Ghani, E., Kerr, W. & O’Connell, S. (2011). Promoting entrepreneurship, growth, and job

creation. Reshaping Tomorrow. New Delhi: Oxford University Press.

GOK, (2012). Economic Survey. Ministry for Planning and National Development. Nairobi:

GOK.

Griffin, R. W. (2012). Managing New Venture Formation and Entrepreneurship. In Griffin, R.

W. (Ed.), Management: Principles and Practices. Stamford, CT: South-Western

Cengage Learning.

Hayes,A (2020). What is an entrepreneur? Investopedia

https://www.investopedia.com/terms/e/entrepreneur.asp

Heins, L. H., Beaulieu, J., & Altman, I. (2010). The Effectiveness of Women' s Agricultural

Education Programs : A Survey from Annie's Project. Journal of Agricultural

Education, 51(4), 1–9.

Huka, G. S., Mbugua, Z. K., & Njehia, B. (2015). Effects of business training needs analysis

on competencies of trainees: The Kenyan experience. Journal of Humanities and

Social Science, 20 (1), 76-85.

Hurtado,.J.M., Pineda,. J.M.B. & Florencio,.B.P (2018). Study of the influence of entreprenuer

trainee’s socio-economic factors in the international expansion of Spanish franchisors

to Latin American countries. https://doi.org/10.1371/journal.pone.0190391

International Labour Organizations (ILO). (2012). Women Entrepreneurs in Kenya: Factors

Affecting Women Entrepreneurs in Micro and Small Enterprises in Kenya. ILO,

Regional Office for Africa, Geneva.

Johnson, R.&Kuby, P. (2012). Elementary statistics (11th

ed).Cengage Learning.

61

Jones, P., Beynon, M.J., Pickernell, D., & Packham, G. (2013). Evaluating the impact of

different training methods on SME business performance. Environment and Planning

C Government and Policy, 31 (1), 56-81.

Kelley, D. J., Singer, S., & Herrington, M. (2012). The global entrepreneurship monitor. 2011

Global Report, GEM.

Kenya Economic Report (2011). Transforming Institutions for Effective Delivery of Kenya

Vision 2030, Nairobi: Kenya Institute for Public Policy Research and Analysis.

Kenya National Bureau of Statistics (2016). Micro, Small and Medium Enterprises Survey.

Nairobi: Government printer.

King’ori, N.G & Theuri., S.F (2016). The Role of Entrepreurship Training and Education in

Enhancing Growth of Small and Medium Enterprises in Kenya: A Case Study of

Mombasa County. Doi: 10.9790/0837-21040197106.

Kinyanjui, R. (2012). Private Enterprise Behavior: Renewed Commerce Avenues. Bombay.

Kithae, P. P., Gakure, R. W. & Munyao, L. M. (2012). The Place of Micro and Small

Enterprises in Achievement of Kenya s Vision 2030. Journal of USChina Public

Administration, 9(12), 1432-1440.

Kochadai, M. (2012). Entrepreneurial Competency: A Study with reference to socially and

economically Backward Communities in Chennai City. Unpublished PhD Thesis,

Pondicherry: Pondicherry University.

Kolstad, I. & Wiig, A. (2015). Education and entrepreneurial success. Small Business

Economics, 44(4), 783–796.

Kothari, C. R. (2003). Research methodology: Methods and techniques (4th

ed). New Delhi:

VishwaParakashan.

Lackeus, M. A (2013). Developing entrepreneurial competencies. An Action-Based

Approach and Classification in Education. Gothenburg, Sweden: Chalmers University

of Technology.

Lavrakas, P. J. (2008). Encyclopedia of survey research methods (Vols. 1-0). Thousand Oaks,

CA: Sage Publications, Inc. doi: 10.4135/9781412963947

Liberto, D. (2019). Small and Mid-size Enterprise (SME) Definition. Retrieved from

https://www.investopedia.com/terms/s/smallandmidsizeenterprises.asp

62

Liverpool-Tasie, S., Omonona, B., Sanou, A., Ogunleye, W., Padilla, S., & Reardon, T.(2017).

Growth and Transformation of Food Systems in Africa: Evidence from the Poultry

Value Chain in Nigeria. Nigerian Journal of Agricultural Economics(NJAE), 7(1), 1–

15.

Lourenço, F., Sappleton, N., Dardaine-edwards, A., Mcelwee, G., Cheng, R., Taylor, W., &

Taylor, A. G. (2014). Experience of Entrepreneurial Training for Female Farmers to

Stimulate Entrepreneurship in Uganda. Gender in Management: An International

Journal, 29(7), 382–401.

Lucas, S. (2017). The Impact of Demographic and Social Factors on Firm Performance in

Kenya. Journal of Business and Economic Development, 2(4), 255-261. doi:

10.11648/j.jbed.20170204.18

Lumbwe, K.A., Anyadiegwu, E.N. & Mbohwa,C. (2018).The Impact of Location Decision on

Small, Micro, and Medium Enterprises’ Performance in Johannesburg. IEOM Society

International.

Madatta, J. (2011). The role of entrepreneurial competencies on the success of the SME’s in

Tanzania: The case study of Ilala and Temeke Municipals. An Unpublished MSc

Thesis, University of Tanzania.

Matofari,M.E.W. (2015). Effects of Training Practices on the Performance of Small and

Medium Size Hotel Enterprises in Mombasa County, Kenya. Technical University of

Mombasa

Mayuran, L. (2016). Impact of Entrepreneurship Training on Performance of Small Enterprises

in Jaffna District. Global Institute for Research & Education., 5(2), 1-6.

Mbogo, M. (2011). Influence of Managerial Accounting Skills on firm’ Success and Growth

of Small and Medium Enterprises in Kenya. Journal of Language, Technology and

Entrepreneurship in Africa, 3(1), 15-18.

Migiro, H. (2011). Success and Failures of Micro Businesses in Africa. Business Challenges.

California: Benvas Publishing Group.

Mitchelmore, S. & Rowley, J. (2010). Entrepreneurial competencies: a literature review and

development agenda. International Journal of Entrepreneurial Behavior & Research,

16(2), 92-111.

63

Mitchelmore, S., & Rowley, J. (2013). Entrepreneurial competencies of women entrepreneurs

pursuing business growth. Journal of small business and enterprise development.

Mkhabela, T., & Nyhodo, B. (2011). Farm and Retail Prices in the South African Poultry

Industry : Do the Twain Meet? Overview of the South African Poultry Industry.

International Food and Agribusiness Management Review, 14(3), 127–146.

Moberg, K., Vestergaard, L., Fayolle, A., Redford, D., Cooney, T., Singer, S. ... & Filip, D.

(2014). How to assess and evaluate the influence of entrepreneurship education. A

report of the ASTEE project with a user guide to the tools, the Danish Foundation for

Entrepreneurship–Young Enterprise.

Moos., M & Botha., M. (2016). How do age and location affect a business? Evaluating the

objectives, outputs and outcomes of small business policy. S.Afr.j.econ.manag.sci,

19(3). Doi: http://dx.doi.org/10.17159/2222-3436/2016/v19n3a3

Moya, M. (2011).Kenyan Tackle Poverty: Micro Enterprise in Africa. University of Pittsburg.

Mukulu, E. (2012). Transfer of Training in Micro and Small Enterprises in Kenya. Aurora, IL:

Lambert Academic Publishing.

Mulatu, M. & Prasad, R. D. (2018). A study on factors affecting success of women

entrepreneurs in Tigray region, Ethiopia. A case study of Adigrat town entrepreneurs.

American Journal of Economics and Business Management, 1(1), 10-19.

Mwangi, K. P. & Namusonge, G. S. (2015). Entrepreneurial Factors Influencing the

Performance of Youth Enterprise Development Funded Youth Owned Enterprises in

Kirinyaga County. Strategic Journals business and change Management, 2 (106),

1595–1620.

Namusonge, M. (2015). The role of entrepreneurship, education and training in stimulating

entrepreneurial careers. paper presented at the 3rd International Entrepreneurship

Conference organized by United States International University.

Nganu,. M (2018). Entrepreneurhip Training and Perfomance of Small and Micro Enterprises

in Information Communication Technology Sector in Nairobi City County, Kenya.

Kenyatta University.

Ngugi, P. (2012). Challenges Hindering Sustainability of SME family Enterprises after the Exit

of their Founders in Kenya, A PhD Dissertation, JKUAT, Nairobi, Kenya.

64

Ngunjiri, N. (2018). Why many small businesses fail to grow after launch. Retrieved from

https://www.businessdailyafrica.com/lifestyle/pfinance/Why-many-small-businesses-

fail-to-grow-after-launch/4258410-4348356-ikbl6x/index.html

Noor, M.R. (2010). Financial Constraints and Opportunities of Micro Entreprise

Entreprenuers: A Theoretical Framework, 2010 International Conference on Business

and Economics Research. Kuala Lumpur, Malaysia: IACSIT Press.

Ogubazghi, S. K. & Muturi, W. (2014). The Effect of Age and Educational Level of

Owner/Managers on SMMEs’ Access to Bank Loan in Eritrea: Evidence from Asmara

City. American Journal of Industrial and Business Management, 4, 632-643.

Omolo, J. W. (2015). Training and Development on Performance of Small and Medium

Enterprises in Kisumu County, Kenya. Kisumu: Sryahwa Publications.

Organisation for Economic Co-operation and Development. (2015). OECD Science,

Technology and Industry Scoreboard: Towards a Knowledgebased Economy. Paris:

OECD.

Osunsan, O. K., Nowak, J., Mabonga, E., Pule, S., Kibirige, A. R., & Baliruno, J. B. (2015).

Firm Age and Performance in Kampala, Uganda: A Selection of Small Business

Enterprises. International Journal of Academic Research in Business and Social

Sciences, 1(5), 412-422.

Otieno, S., Bwisa, H. M., & Kihoro, J. M. (2012). Influence of strategic orientation on

performance of Kenya's manufacturing firms operating under East African regional

integration. International Journal of Business and Social Science, 3(5).

Pantea, M. C. (2016). On entrepreneurial education: dilemmas and tensions in nonformal

learning. Studies in Continuing Education, 38(1), 86-100.

Penchev, P. & Salopaju, A. (2011). Entrepreneurial competencies needed by managers in their

work. Unpublished Master’s Thesis, Sweden: Jönkoping International Business

School.

Radipere, S. & Dhliwayo, S. (2014). The role of age and business on small business

performance in the South African small enterprise. Problems and Perspective in

Management, 12(4), 7-12.

Regoniel, P. (2017). Research Design: A Simplified Definition for Beginning Researchers.

Simply Educate. https://simplyeducate.me/2017/02/12/research-design/

65

Ropega, J. (2011). The Reasons and Symptoms of Failure in SME. International Advances in

Economic Research, 17(4), 476-483.

Rotich, J., Cheruiyot, P. & Yegon, C. (2015). The Impact of Entreprenuer trainee’s socio-

economic Factors on the Perfomance of Small and Medium Size Enterprises: The Case

Study of Kericho County, Kenya. Global Institute for Research & Education, 3(4),

263-267.

Seo,W.Y.& Lee, H.Y (2019). Effects of internal and external factors on business performance

of start-ups in South Korea: The engine of new market dynamics. International Journal

of Engineering Business Management. Doi:

https://doi.org/10.1177%2F1847979018824231/

Situma, S. (2016). SMEs: The golden key to a flourishing Kenyan economy. Retrieved from

https://www.standardmedia.co.ke/business/article/2000225102/smes-the-golden-key-

to-a-flourishing-kenyan-economy

Syafruddin,B., Utama, S., Yasa, M., & Marhaeni, N. (2018). Effect of Entreprenuer trainee’s

socio-economic and Demographic Factors against Social Capital, Farming

Performance and Farmers Welfare in Sumbawa, Indonesia. IOSR Journal of

Economics and Finance, 9(1), 1–8. doi: 10.9790/5933-0901040108

Thapa, G., & Gaiha, R. (2011). Smallholder farming in Asia and the Pacific: Challenges and

opportunities. In IFAD conference on new directions for smallholder agriculture (Vol.

25). International Fund for Agricultural Development Rome.

Tu, P. A., & Diem, N. H. (2016). Entrepreneurial characteristics and private firm performance

in the Mekong River Delta. Can Tho University Journal of Science, 3, 38-48.

Usman, A., & Kamau, J. (2019). Determinants of Entrepreneurial Orientation among Muslim

Students in Kenya: A Case of United States International University-Africa.

Val., M.M.S., Hernandez., F.L. & Fuentes., C.C.R (2018). Geographical factors and business

failure: An empirical study from the Madrid metropolitan area. Doi:

https://doi.org/10.1016/j.econmod.2018.05.022

Valerio, A., Parton, B. & Robb, A. (2014). Entrepreneurship Education and Training

Programs Around the World. Dimensions for Success. Insights from Ghana, Kenya and

Mozambique.

66

Vallabh, S., Dinesh, S. & Mhlanga, O. (2015). Influence of demographic factors on business

performance in small to medium tourism enterprises (SMTEs). African Journal of

Hospitality, Tourism and Leisure, 4.

Vijay, L., & Ajay, V. K. (2011). Entrepreneurial Competency in SME’s. Bonfring

International Journal of Industrial Engineering and Management Science, 1(1), 5-10.

Wang, Y., Watkins, D., Harris, N. & Spicer, K. (2010).Conflicts Between Successions Issues

and Business performance. Journal on Business Management, 11(9), 251-275.

Watson, Roger. (2015). Quantitative research. Nursing standard (Royal College of Nursing

(Great Britain) : 1987). 29. 44-8. 10.7748/ns.29.31.44.e8681.

World Bank (2011). Kenya Unlocking Growth Potential: Strategies, Policies, Actions.

Zamboni, J (2018). What is the meaning of sample size? Sciencing,

https://sciencing.com/meaning-sample-size-5988804.html

67

APPENDICES

Appendix I: Letter of Introduction

CONSENT FORM FOR THE METRO AGRIFOOD LIVING LAB PHASE II

PROJECT

Your privacy is very important, and all information collected will be handled responsibly. An

effort will be made to be as open and transparent as possible with how your information is

handled. All project members who come in contact with your personal information are aware

of the sensitive nature of the information that you have disclosed to us. They are trained in

the appropriate use and protection of your information. Only necessary/relevant information

will be collected, and this information will only be shared with your consent. Our privacy

protocols are in accordance with the USIU-Africa’s regulatory body Institutional Review

Board.

Information will be collected, used, and disclosed for the following purposes:

To establish and maintain contact with you

To send you newsletters and other information mailings

To remind you of upcoming opportunities

To use your photos on marketing materials, reports & social media exclusively for

this program

By signing this form, I have agreed that I have voluntarily and freely given consent to the

collection, use and/or disclosure of my personal information as outlined above. Additionally,

I accept the above conditions for continuing being part of the Effectiveness of the Metro

Agri-Food Living Lab for Gender Inclusive Youth Entrepreneurship Development in Kenya

Project.

68

__________________ ___________ ______________

_____________

Full Name Signature Phone Number Date

69

Appendix II: IRB Research Approval

70

Appendix III: NACOSTI Approval

71

Appendix IV: Research Questionnaire

METRO AGRIFOOD LIVING LAB BASELINE AND VERIFICATION TOOL

1. Name

2. Unique Code

3. What is your gender?

Male [ ] Female [ ]

4. What is your Date of birth:

5. What is your County of residence?

a. Sub-county………………………………………………………

b. Nearest prominent feature e.g. school/church/hospital/police station, any

other……………………..

6. What is your marital status?

Single [ ] Married [ ] Widowed [ ] Divorced [ ] Separated [ ]

7. What is your highest level of Education?

No formal education Technical Training/ Polytechnic

Some primary school College

Finished primary school Bachelor degree

Some high school Masters

Finished high school Others Specify

Households

8. Who is the head of your household? (State whether it is father, mother, yourself,

husband/wife, other please specify)

___________________________________________________

9. How many people (family members or others) do you support through your business?

(indicate the number)

10. Which of the following best describes your household income:

I rely entirely on somebody else’s income [ ]

72

My income contributes to a few household expenses [ ]

I contribute the most to household expenses [ ]

I am the main provider in my household [ ]

11. Which of the following phrases describe best your feelings about your household's income

these days:

I live comfortably on the present income. __________________________________

My present income is just enough for survival ___________________________

I find it hard to manage on the present income. ___________________________

I find it very hard to manage on the present income. ___________________________

Infrastructure access.

12. How far is your business from the nearest tarmac road?

Less than 1Km [ ] Between 1-3 Km [ ] More than 3 Km [ ]

13. What is your source of energy (tick all that apply)

Electricity (from KPLC) [ ] Solar [ ] Kerosene [ ] Biogas [ ]

Other specify: _____________________________________________________

14. What is your source of water? (tick all that apply)

Piped water supply from the County Government [ ] Borehole [ ] River [ ]

Spring Water [ ] Harvesting [ ] Buying [ ]

Other specify: _____________________________________________________

15. Do you own a mobile phone?

Yes [ ] No [ ]

i) If yes would you consider to be a smart phone?

Yes [ ] No [ ]

ii) Thinking of a normal week, how many days do you use it to make business calls,

receiving/ making payments or any other business

use:________________________

iii) Is your business area connected to a mobile network?

Yes [ ] No [ ]

iv) Do you use internet on your phone?

73

Yes [ ] No [ ]

a. If yes, how much time do you spend in a week on internet?

________________________________

b. How much money do you spend in a week on internet?

___________________________________

16. Is your business or home connected to a sewage system?

Yes [ ] No [ ]

Business

17. The business was started by

Myself [ ]

Myself with Partner [ ]

My family [ ]

Myself and family [ ]

Bought from someone [ ]

Other specify [ ]

18. List of assets owned/leased/used by the Business?

a. Available evidence of the lease agreement/title/logbook/payment.

19. How did you finance the start of your business?

Own savings only [ ]

Informal borrowing and own

savings [ ]

Loans [ ]

Government funds [ ]

Sponsor [ ]

20. How much money did you spend to start your current business?

21. What is the overall value of your agribusiness today? (Probe/notes)

a. Any other information to support the evaluation and assessment

22. How long have you been in agribusiness (months)

_________________________________________

23. How many businesses have you owned in the past?

________________________________________

74

24. What is the nature of your agribusiness (check all that apply)?

Producer [ ]

Processor [ ]

Retailer [ ]

Broker [ ]

Supplier [ ]

Consultant [ ]

Trainer [ ]

Extension services [

] [ ]

Others (specify):

________________________________________________________________

25. Please provide a brief description of your agribusiness’s main activity.

___________________________________________________________________________

___________________________________________________________________________

___________________________________________________________________________

_______________________________________

26. My current typical monthly sales are (Ksh):

____________________________________________________

27. How many hours per week do you spend on your business?

_______________________________________

28. Are you engaged in any other income generating activity besides this agribusiness?

Yes [ ] No [ ]

If yes, please specify __________________________________________________________

29. What kind of records do you keep? Tick all that apply

Total sales

[ ]

Expenses [ ]

Credit customer

[ ]

Supplier [ ]

Customer

names [ ]

Revenue [ ]

Profit and

Losses [ ]

Stocks

[ ]

Goods sold

[ ]

Costs of sales

[ ]

Others

___________

75

30. How do you keep these records? Tick all that apply

Receipts from those I buy from [ ]

Record in a receipt book [ ]

On a computer [ ]

Record SMs transactions [ ]

Keep a file [ ]

Commit to memory [ ]

Written ledger [ ]

Other:________________________________________________________________________

Take a clear picture of the evidence Receipts, ledgers, file etc….

31. What challenge(s) do you face (if any) while implementing/scaling up your business? (Please

rank from the highest barrier as 1 to the lowest as 3)

a) Availability of raw materials h) Lack of business-related knowledge

b) Lack of technical skills i) Compliance and regulatory issues

c) Poor Market access j) Customer acquisition and retention

d) Absence of external funding k) Lack of time due to household work/childcare

e) Poor Business Model l) I do not face any difficulties related to my

business

f) Lack of human resource m) Other/Specify:

32. How many employees are in your agribusiness? (Probe).

___________________________________how many are male------- and how many are

female --------

33. How many of those employees are family members (Probe).

____________________________________

34. Who makes decisions regarding the income from your agribusiness?

Myself My spouse (husband or wife)

My parents or guardians Other

76

35. Out of your total monthly sales, how much do you spend on…?

a) Salaries (amount) Ksh. ______

b) Savings (amount) Ksh. ___________

c) Personal expenses (amount) Ksh. _____

d) Other business expenses (amount) Kshs. _______________________

36. As far as your personal finances, how often do you keep/put money aside or save (Circle one)?

Daily Weekly Monthly Once every 3

months

Once every 6

months

Almost

never

Never

On a scale of 1-5 where 1=Strongly Disagree, 2-agree, 3=Neutral,

4-agree, and 5=Strongly Disagree, please tick the appropriate box

about the following statements.

SD D N A SA

37a. Most of your family, friends and neighbors are in a similar

financial situation as you are

37b. In the morning, you usually know approximately how much

money you will earn that day.

38c. You are prepared to spend now and let the future take care

of itself

38. What legal documents does your business have? (Please tick all that apply):

County government License [ ]

Company registration [ ]

KEBS registration [ ]

Public health certificate [ ]

Halal registration [ ]

Union registration [ ]

KRA PIN [ ]

NEMA certificate [ ]

Business name [ ]

77

TLB/NTSA licence [ ]

None. [ ]

Other/Specify……………………………

70

39. Available as proof.. (Upload)

40. What is the geographical coverage of your business/Market (Towns & Counties):

_____________________________________________________________________

____________

Funding

41. I am familiar with the following sources of funds

Bank loans Equity (owner provided capital)

Mobile money Government grants

Saccos Table banking

42.a. In the past 2 years, which of the below personal financing sources have you relied upon

most in an emergency (rank from most frequent to least frequent)

Sell something as an asset or something

valuable

Savings

An informal private lender (loan shark) A formal financial

institution

Money from working more or finding work for less employed household members

42.b. In the past 2 years, which of the below non-personal financing sources have you relied

upon most in an emergency (rank from most frequent to least frequent)

Religious leaders or community leaders A community welfare group or

fund

From colleagues or a loan from an

employer

Family, relatives, or friends

Some other source (specify)

42.c. In the past 2 years, which of the below personal financing sources have you relied upon

most in regular business (rank from most frequent to least frequent)

Sell something as an asset or something

valuable

Savings

70

An informal private lender (loan shark) A formal financial

institution

Money from working more or finding work for less employed household members

42.d. In the past 2 years, which of the below non-personal financing sources have you relied

upon most in regular business (rank from most frequent to least frequent)

Religious leaders or community leaders A community welfare group or

fund

From colleagues or a loan from an

employer

Family, relatives, or friends

Some other source (specify)

43. Do you participate in an informal savings group or investment group e.g. Chama or

SACCO?

Yes [ ] No [ ]

44. Would you find formal financial services complicated and confusing

Yes [ ] No [ ]

45. What have been the major challenges in your attempt to raise funds for your business?

I do not know where to get the

funds

Lack of security

Lack of business records

Training

46. List trainings (workshops, seminars, conferences) attended in the last three years.

___________________________________________________________________________

___________________________________________________________________________

____________

47. In what areas have you received training?

70

Keeping records Use of computers

Basic writing Marketing

Adding value to food

items

Generating business

ideas

Registering businesses Entrepreneurship

Financial literacy Other

48. What would you say are the main challenges to you attending training?

Distance to training

venues

Difficult training

Family I feel bad in the classroom

Low education level Lack of opportunity

Fees required Previous training I attended did not help

me

Other

49. If offered the opportunity to train, would you prefer that the training takes place;

Near my home or business

Somewhere within my

county

Away from my county

Why?

50.a. If offered the opportunity to train, would you prefer that the training takes place near your

home or business, why?

50.b. If offered the opportunity to train, would you prefer that the training takes place near

somewhere within your county, why?

50.c. If offered the opportunity to train, would you prefer that the training takes place away

from your county, why?

Mentorship

53. Do you have a person that you look up to as a mentor or coach? Yes

No

If Yes, who is this person to you?

70

Parent Religion or community

elder

Spouse Government officer

Relative A business man or woman

Other (specify)

54. If Yes, which of the following areas do they help you to improve?

Business Education

Family management Religious matters

Personal discipline Others

55. Which of the following best describes your feeling on mentorship?

It is a good thing

It is a bad thing

Not sure

56. What would you say are the main challenges to mentorship?