The Effect of Startup Capital of the Owner of Small Business Enterprises to Their Performance in Uganda

The effect of startup capital of the owner of small business enterprises to their performance in Uganda. Case study Kawempe.

KIMULI ISAAC 16/U/6039/EVE BSC(BS)(MAK)

A dissertation Submitted to the School of Statistics and Planning in Partial Fulfillment of the Requirements for the Award of the Degree of Bachelor of Science in Business Statistics of Makerere University

DEDICATION

I dedicate this report to Almighty God, to my beloved mum Nabatanzi Deborah for her unconditional love and standing together with me during the entire process of research.

May the almighty God Bless you abundantly

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ACKNOWLEDGEMENTS

First and foremost, I would like to thank the Almighty God foreseeing me through the entire course and more so this research project.

I wish to thank my supervisor, Mr. Musoke for his support and continued guidance during this research study. I would also like to thank my family whose encouragement, support and pride in me have been constant not only throughout my degree, but right throughout my life. I believe that the independence and strength that I possess is due to my upbringing and surroundings. You are, and have always been, the central point of this. Thank you for always being there for me. I thank all my lecturers at Makerere University School of Statistics and Planning ,from whom I have learned much throughout my training in my field of study. Finally my sincere gratitude goes to my course mates with whom we shared lectures and experiences.

TABLE OF CONTENTS

DECLARATION ...... i

DEDICATION ...... ii

ACKNOWLEDGEMENTS ...... iv

ABSTRACT ...... x

CHAPTER ONE ...... 1

INTRODUCTIONS ...... 1

1.1 Background ...... 1

1.2.PROBLEM STATEMENT ...... 3

1.3. Objectives ...... 3

1.3.1. Main objective of the study ...... 3

1.3.2 Specific objectives...... 3

1.4 Research hypothesis ...... 3

1.5 Scope of the study ...... 4

1.5.1 Geographical scope ...... 4

1.5.2 Time scope ...... 4

1.6 significance of the study ...... 4

1.6. justification ...... 4

1.7. Conceptual frame showing the relationship between the study variable ...... 5

CHAPTER TWO: ...... 8

LITERATURE REVIEW ...... 8

2.0 Introduction ...... 8

2.1 Theoretical evidenc ...... 8

2.1.1 on the theory of finance for privately held firms ...... 8

2.1.2 Pecking order theory ...... 8

2.1.3 Theory of production ...... 9

2.2 Emperical evidence ...... 10

2.2.1 Performance of small business concept ...... 10

2.2.2. Relationship between startup capital and the performance of small business enterprises in Kawempe division...... 11

2.2.3. The relationship between gender and performance of small business enterprise in Kawempe division...... 11

2.2.4 Relationship between access to credit and performance of small business enterprise in kawempe division...... 12

2.2.4Identification of the effect of age of the small business enterprises contribute to their performance in Kawempe division...... 12

2.3. Summary of literature...... 13

CHAPTER THREE ...... 15

METHODOLOGY ...... 15

3.0. Introduction ...... 15

3.1. Research design ...... 15

3.2. Study population ...... 15

3.3.Sample size and design ...... 15

3.4. Data collection methods ...... 17

3.4.1. Interview method...... 17

3.5Data collection tools ...... 17

3.5.1. Questionnaire ...... 17

3.6. Validity and reliability ...... 17

3.6.1. Validity ...... 17

3.6.2. Reliability ...... 18

3.7.Data analysis and management ...... 18

3.8.Ethical issues ...... 21

3.9.limitations ...... 21

CHAPTER FOUR ...... 22

RESULTS AND FINDINGS ...... 22

4.0. Introduction ...... 22

4.1. UNIVARIATE ANALYSIS ...... 22

4.1.1Demographic characteristics for the respondents in the study ...... 22

4.1.2.Business background ...... 24

4.1.3. Attitude towards business performance ...... 25

4.2. BIVARIATE ANALYSIS ...... 28

4.2.1. Relationship between profits and startup capital invested ...... 28

4.2.3. Relationship between daily profits and gender ...... 29

4.3. MULTIVARIATE ANALYSIS ...... 29

4.3.1. Association between daily profits with startup capital, age of business owner and gender of the small business owner...... 30

CHAPTER FIVE ...... 32

SUMMARY FINDINGS, RECOMMENDATIONS AND CONCLUSION ...... 32

5.0. Introduction ...... 32

5.1 summary of the findings ...... 32

5.2. CONCLUSION ...... 32

5.3. RECOMMENDATIONS ...... 33

5.4. AREAS FOR FURTHER RESEARCH ...... 33

REFERENCES ...... 34

Appendix 1: QUESTIONNAIRE ...... 36

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LIST OF TABLES

Table1.1 employment levels and annual turn over ...... 2 Table 3.1, showing sample distribution in the four parishes ...... 16 Table4.1: demographic characteristics...... 22 Table 4.2: business background ...... 24 Table 4.3: Respondents perception about business performance and attitude towards credit access ...... 25 Table 4.4: Relationship between profits and startup capital invested ...... 28 Table 4.5: Relationship between age of business owner and daily profits earned ...... 29 Table 4.6: relationship between daily profits and gender ...... 29 Table 4.7; summary of the model ...... 30 Table 4.8: association between daily profits with startup capital, age of business owner and gender of the small business owner...... 31

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LIST OF FIGURES Figure 1.1 showing conceptual frame work showing the relationship between thestudy variables 5 Figure 4.1 showing level of education of respondents ...... 23

ABSTRACT

The study sought to establish the effect of startup capital on the performance of small business enterprise. A descriptive research was used and within it a cross section research where data was collected once, was adopted. A total of 80 questionnaires were administered and the study managed to obtain 80 completed questionnaires representing 100% response rate. Data was analyzed descriptively using SPSS software so as to obtain a more statistical analysis of the collected data. Multiple linear regression model was used in this study to establish the relationship between two or more independent variables.

Results indicate that sample was proportionally distributed with 25% of respondents came from each region of study (Kalerwe, Mpererwe, Kyebando, Kanyanya). %. Majority of the respondents got their startup capital from their own personal savings (82.5%) followed those who got it from their family (7.5%). Few respondents got their startup capital from friends and banks representing 5.0% each. 50% of the small businesses had their profits within their targeted expectation and also the study results revealed that there was a significant positive effect of startup capital on the performance (profits) of small business enterprise with a p-value<0.05. This implies that the more capital you invest in the business the likely the profits of that business will reflect on that startup capital invested in keeping other factors constant. Therefore less startup capital exhibit a poor performance of small business enterprise in terms of profits. In general the study looked at the effect of startup capital on the performance of small business enterprise.

It was observed that there was a significant positive relationship between startup capital and performance of small businesses. It is clear that startup capital is a major constraint on the performance of small business and plays a vital role before one thinks of any business.

Furthermore the excessive borrowing has been cited as a constraint in lowering the business profits. This is because increasing proportion of the debt in startup capital could result into high bankruptcy costs which in turn impacts negatively on the business profits.

Whereas inaccessibility to credit services is a major impediment phenomenon in that small scale business owners should also go for external financing in order to raise enough capital which in turn will impact the profits of the small business positively.

In order to ease people’s access to startup capital, the government should fund capable people with sound ideas of how to start, manage and run small businesses and also formulate plans and policies regarding small business enterprises

CHAPTER ONE

INTRODUCTIONS

1.1 Background

According to European Union, small scale business is the one that has fewer than fifty employees either turnover its balance sheet less than 10 million. Today most of the large cooperation’s started as small scale business. According to World Bank group, small scale businesses play a major role in most economies particularly developing countries. According to World Bank, 600 million jobs will be needed in the next 15 years to absorb the growing global work force, mainly in Asia and sub-Saharan Africa. However access to capital is a key constraint of small scale business performance and hence without capital small scale business are likely to stagnate. Further studies have emerged that thousands of small scale businesses start up fail every year but significant numbers of them fail before the first year of their operation while majority of them fail in their second year of operation (Dickenson, 1981 Almus, 2004). Small scale enterprises is seen as the key drive for employment creation and economic growth. This has been necessitated by the increasing awareness within the government of Uganda that large scale industries are less likely to generate employment opportunities given the high capital intensity of output. The small business enterprises are the engine of growth and development of Uganda and the world at large (ministry of trade industry and cooperatives(MTIC) report). Small business enterprise are the key drivers in fostering innovation, wealth creation and job creation in Uganda. It employs over 2.5 million people which is a fair figure for the employment levels in Uganda. This signifies their undisputed role in the economic development of Uganda and more so since youth unemployment is at 61.6 %( Action Aid international Uganda(AAU), Development Research and training(DRT), Uganda national NGO forum, 2012(UNNGOF)) In Uganda according to Uganda bureau of statistics (UBOS), small business enterprises are businesses which employ between 5 and 40 people but having a total asset of about 10 million Ugx but not exceeding 100 million Ugx. Uganda Bureau of Statistics (UBOS) that the total numbers of businesses registered in Kampala was nearly 26,000 of which those employing 5 or more persons were 17,084 hence showing a growth of over 60% of Small

Scale Businesses hence the number of small business enterprise in Uganda has been increasing over the years (Nuwagaba and nzewi, 2013:26).

Table1.1 employment levels and annual turn over Employment level Turn over ( millions) 5-10 millions 1-4 Small scale businesses 5-9 Small scale businesses 10-19 Small scale businesses 20-49 Small scale businesses Source : 2010/11 census business establishment.

According to Uganda Bureau of Statistics report on COBE (census of business establishment), 2010/11 , their 251,409 retail business in Uganda and 15,474 whole sale businesses in Uganda. Many Ugandan small businesses opt for micro loans in micro finance limited. According to the population and housing census 2002, Kawempe division is located in the northern part of kampala with 19 parishes in which include; Bwaise 1, Bwaise 2, Bwaise 3, Kalerwe, Kanyanya, Kazo-Angola, Kyebando, Makerere 3, Mpererwe, Mulago 2, Ssebaggala kawempe 2, komamboga, kawempe1, kikaaya, Wandegeya, mulago1, mulago2, mulago3, Makerere2, makerere1, Makerere university, . Kawempe division occupies 3245.2 hectares. It a population of 268,659 people in the area with 128,624 males and 140,035 females. Kawempe division has 67,132 household. According to Action Aid(2003), kawempe division has 15 markets which include; Dembe, Bwaise, kalinabiri, wandegeya kabaka, wandegeya B, Wandegeya Veterans, progressive, Bivamuntuuyo, kizito, Nsangi, Keti falowo, Mpererwe, New Market opposite oil market, Kubilole.

1.2. PROBLEM STATEMENT

Small business enterprises are competitive and flexible in nature. The small business enterprises are the engine of growth and development of Uganda and the world at large (ministry of trade industry and cooperatives (MTIC) report). Most of the businesses are reported to be failing with in the first five years while 5% to 10% survive and make it to maturity (private sector foundation Uganda, 2006). According to Action Aid (2003), lack of money is a major problem at household level by 79% in Kawempe division who have little to save. This therefore hinders acquisition of startup capital hence affecting the performance of small business enterprise in Kawempe division. This has also led to an increase in unemployment rate by 21.4% of the population (Action Aid, 2003) in Kawempe division hence it is suggested that they have knowledge about small businesses but have no money.

1.3. Objectives

1.3.1. Main objective of the study

To examine the extent to which the startup capital affects the performance of small business enterprises in Kawempe division. 1.3.2 Specific objectives.

I. To identify the effect of age of the small business owner enterprises contribute to their performance in Kawempe division II. To investigate the relationship between gender and performance of small business enterprise in Kawempe division. III. To investigate the relationship between access to credit and performance of small business enterprise in Kawempe division. 1.4 Research hypothesis I. Access to capital doesn’t affect the performance of small scale business enterprises in Kawempe division II. Age of the business owner doesn’t significantly affect small scale business performance in Kawempe division

III. Gender of the business owner doesn’t affect the performance of small scale businesses in Kawempe 1.5 Scope of the study

1.5.1 Geographical scope

Kawempe division is one of the five major administrative division of Kampala district. The study will be carried out in Kawempe division since it is the largest division of Kampala with a population of about 265,000(national population census 2002). The informal settlements in Kawempe division are characterized with many people having lesser incomes with little to save (Action Aid, 2003). This characteristic of lesser income favors the establishment of small scale business enterprises. 1.5.2 Time scope. The study will take 2 months due to a number of parishes in Kawempe division that is 19 parishes with differing populations (population and household by parish, 2002) and also the researcher thinks that this period is enough for him to prepare a proposal, collect and analyze the data and finally report the findings. 1.6 significance of the study. The findings of the study will be of great importance to the researcher himself, small business owners, Makerere University, the government.

Researchers and other people who may find the study useful, may find the findings useful in knowing the distribution of small business enterprises and how many people are employed in those small businesses. This in turn may help he government of Uganda to carry out effective plans in terms of tax collection.

1.6. justification

This study shows a greater number of people employed in small business enterprises hence if not noticed by the government, it may result into an increasing unemployment in the country and many able labor force leaving the country for opportunities elsewhere. Furthermore, the findings may become a resourceful reference material to various stakeholders in the economy and readers in general interested in gaining interest in the role played by small businesses in the economy.

1.7. Conceptual frame showing the relationship between the study variable Figure 1.1 showing conceptual frame work showing the relationship between the study variables

INDEPENDENT VARIABLE DEPENDENT VARIABLES Startup capital performance i. Profits

CONTROL VARIABLES

i. age of the small business owner ii. gender of the small business owner

Source: Hirsrich and Brush (1987), Brush (1991), Kalleberg and leicht (1991), Kiiru, mereiro, Masaviro(1998), Ngobo (1995)

The conceptual framework above shows that once the startup capital is enough, the resultant decision can affect the performance of small business enterprise

Empirical evidence suggests that women owned businesses earn less money (Hirsrich and Brush, 1987; Brush, 1990) and oftenly don’t grow rapidly as male owned businesses (Kalleberg and

Leicht, 1991). According to Kiiru, Mereiro, Masaviro(1998) for Kenya rural enterprise, confirm that finance is still a major constraint in the small business sector. Ngobo (1995) , makes a detailed analysis of finance as a constraining factor and includes collateral, interest rates, extra bank charges, inability to evaluate financial proposals and lack of financial management skills as hindrances to small enterprise growth.

Performance of small businesses depends on the independent variables such as startup capital, age of the business, Gender of small business owner. The relationship of the variables are displayed above.

Key definitions

Collateral; a person or a business asset used as a guarantee in case the cash generated by small business is not sufficient enough to repay the loan. If a potential borrower has no collateral, the borrower will need a consigner who has collateral to pledge. Otherwise it may be difficult to obtain a loan(Small Business Association, 2013). Calice et al. (2012) report that 94% of their sample indicates that the lending banks tend to demand collateral as a requirement in granting loans to SMEs. They also discuss that 50% of the lending institutions tend to have problems with the definition and registration of the collateral. Also, because of the bigger credit risk of smaller Companies, the lending institutions demand higher value collateral than required fromlarger companies when granting loans to the SMEs. Convincingly, Calice et al. (2012) show, through a survey graph, that SMEs are more unstable and informal and their businesses are harder to evaluate so lenders tend to ask for a higher value collateral compared to what they demand from larger companies. Banks are often reluctant to lend money to small businesses because of low expected profit margins, asymmetrical information and high risks (EIM, 1998).

Startup capital; financial amount required to start up a business (Reynolds, 2002).According to Holtz-Eakin, Joulfaian & Rosen, (1994) financing through bank loans or investors can be difficult and disadvantageous for the small business owner for many reasons. Researchers agree that access to resources is an important influence on business start-ups and that those with little personal wealth have higher failure rates in new business than their wealthier counterparts (Holtz-Eakin, Joulfaian & Rosen, 1994). Bates, (1997), Dunn and Holtz-Eakin (1996), Evans and Jovanovic (1989), and Fischer and Massey (2000) assert that financial capital is critical for entrepreneurship and that liquidity constraints inhibit start-ups. They reason that business start-

6 ups often require a substantial sum of money in order to buy the necessary equipment and supplies. This viewpoint emphasizes that equity, particularly from family wealth holdings, allows entrepreneurs to obtain credit, and those with little personal wealth simply cannot secure necessary start-up capital (Bates, 1990). Bank loans in particular are much relied upon. This is also put forward by Riding and Swift stating that “It is well known that small businesses rely heavily on banks for both shortand long-term debt capital” (Riding and Swift, 1990, p. 329). Other important sources of external finance are family members, suppliers and other business partners (Van Uxem and Bais, 1996).

Business Performance; business performance is defined as operational ability to satisfy the desires of a company\s major shareholders. Li, Ragu-Nathan and Subba Rao (2006) and Orunfleh and Tarafdar (2014) see firm performance as how well an organization achieves its financial and market. Performance is one of the most important objectives of financial management because one goal of financial management is to maximize the owner’s wealth (McMahon, 2005). When the business becomes mature, profits have to be produced. Edmister (2007) among other researchers have suggested that small firms need to concentrate on performance. Jen (2003) found performance to be a significant determinant of a small firm’s credit risk. Thomas and Evanson (2007) stress the aim of a business is not only the generation of sales, but also generation of profits. Profit is especially important because it is necessary for the survival of a business. Low performance contributes to under-capitalization problems because it leads to retained earnings and therefore to a reliance on external capital (Davidson & Dutia, 2001).

CHAPTER TWO:

LITERATURE REVIEW

2.0 Introduction

This chapter shows literature review from other researchers about the effect of startup capital to the performance of small business enterprise in Kawempe division.

2.1 Theoretical evidence

2.1.1 on the theory of finance for privately held firms

According to James S Ang (1992), suggests that the simplest definition of small firms is that they are privately owned. Owners/managers of small businesses often have to make business and decision on how they would ultimately affect their own person wealth. Due unlimited liabilities (proprietorship and partnership) and incomplete limited liabilities (in the corporation form where lenders require personal guarantee or assets as collateral), business risk is no longer separable from personal risk. Business bankruptcy could cause personal bankruptcy. Small businesses use different financing sources. In addition to the owners savings, family and friends, they also likely to obtain financing from suppliers and advances from customers.

2.1.2 Pecking order theory

Pecking order theory is the result of Asymmetric information. The pecking order model does not discuss the optimal capital structure as significant point, but states that firms have two main sources to fund its financial needs which are internal and external finance; the theory claims that firms prefer to use firstly internal finance such as excess liquid assets or retained earnings then external finance. If internal financing is not enough to fund investment projects, firms may or may not obtain external financing, and if they do, In order to minimize additional costs of asymmetric information, the managers head for choosing between the different sources of external finance, firms prefer to use debt leverage firstly, secondly issuance of preferred stock and finally issuance of common stock

According to Myers (1984), this theory suggests that their no well-defined capital structure; instead the debt ratio is the result of hierarchical financing over time. The foundation of this theory is that firms have no defined debt to value ratio. Management has a preference to choose internal financing before external financing. When a firm is forced to use external financing, managers chose the least risky and demanding source first. When it is necessary to issue external sources, debt issuance is preferred to new equity. From the asymmetric information point of view is the pecking-order hypothesis (Myers 1984), which suggests that firms finance their needs in a hierarchical fashion. Myers (1984) and Myers and Majluf (1984) have pointed out the role of managerial preferences in the choice of financing resources. These choices are made by considering the relative costs of the various sources of finance due to information asymmetries and transaction costs. The pecking-order theory proposes that firms prefer to use internal sources of capital, relying on external sources only when the internal ones are exhausted. As a result, firms prefer to use less information-sensitive securities, with retained earnings being the most preferred financing source, followed by debt, and then equity capital.

Pecking Order Theory (POT) that dictates hierarchical orders of financing decisions of firms (Matias & Serrasqueiro, 2016). Agliardi et al (2016), Mwarari & Ngugi (2013) noted order of preference in POT first, second and third sources of financing as internal, debt and equity financing respectively. According to Proença et al (2014), small companies do opt for internal financing; however, this will depend on firm’s internal funding capacity to meet its needs at each stage, Agrebi (2009). Matias & Serrasqueiro (2016) established that SMEs financing decisions follow POT predictions, in case of debt financing decision if firms don’t generate enough funds internally then, Proença et al (2014), short-term debt is preferred than long term debt.

2.1.3 Theory of production

According to Cob and Douglas (1928:151) hypothesized production as a function of labour and capital. Cobb-Douglas production function (as it later became known), is still the most ubiquitous tool in theoretical and empirical analysis of growth and productivity. It is widely used to represent the relationship of an output to inputs. Essentially, it considers a simplified view of the economy in which production output (P) is determined by the amount of labour (L) involved and the amount of capital (K) invested, resulting in the following equation.

푝 푘, 푙 = 푏퐿훼 푘훽

Where α and β are output elasticity of capital and labor respectively

, the Cobb-Douglas model has attractive mathematical characteristics, such as highlighting diminishing marginal returns to either factor of production. It is in this regard that we utilize it in to estimate performance (profits and sales) output as a function of start up capital, age of the small business, age of the small business owner and gender of the small business owner. Having regard that the production function is non-linear, we log-transform the Cobb-Douglas model to derive the following equation: LnPerformance = β0 (constant) + β1lnStart up capital + β2 lnAge of small business owner + β4lnGender of the small business owner + εt where lnPerformance- is the log of performance measured in profits earned and sales made lnStart up capital- is the log of startup capital measured in financial terms (shillings). lnAge of small business owner- is the log of age of small business owner measured in years. lnGender of small business owner- Is the log of gender of small business owner.

β1- β4- are the coeffients of explanatory variables.

According to the study, it is in this regard that performance output that is profit, sales as a function of capital, age of owner of the small business, age of the business, gender of the small business owner

2.2 Emperical evidence

2.2.1 Performance of small business concept

Global Enterpreneurship monitor (2004), defined performance as the act of performing; of doing something successfully; using knowledge as distinguished from merely possessing it. However, performance seems to be conceptualize, operationalized and measured in different ways thus making cross-comparison difficult.

According to smith and Reece (1999), In general business performance is defined as operational ability to satisfy the desires of a company’s major shareholders. The performance profile of small businesses is a complex matter and multi-dimensional in scope and character (scase and Goffe, 1984). It embraces a convergence of; owners-manager motivations, goals and capabilities; internal organization factors; regional specific resources and infrastructure; and external relationships (Storey, 1994;Miitra and Matlay, 2000; Shaw and Conway, 2000). Kallon (1990) also found out that access to commercial credit did not contribute to entrepreneurial success in any significant way.

2.2.2. Relationship between startup capital and the performance of small business enterprises in Kawempe division.

Financial constraint remains a major challenge facing small scale businesses in Kenya (Wanjohi and Mugure, 2008). Finding start-up finance for the business is the biggest hurdle that many entrepreneurs go through. Even after getting started, getting sufficient finance to sustain business growth is another problem. Research findings by McCormick et al (1996), Daniels et al (2003) Kinyanjui (2006) show how SMEs are constrained by finance. Studies undertaken by Kiiru, Mirero and Masaviro (1988) for Kenya Rural Enterprise Programme (K-Rep) confirm that a major constraint within the small business enterprise sector is financing. In South Africa Eeden (2004) found finance as cited as one of the most prominent constrains. Insufficient financing is as much a problem as lack of finance and as a result of scarcity of finance, small enterprises are unable to expand, modernize or meet urgent orders from customers. The profit Margins are usually little to support growth. Most studies (Ngobo, 1995; Kibera and Kiberam, 1997; Chijoriga and Cassiman, 1997), point to finance as one of the key constraints to small enterprise growth.

2.2.3. The relationship between gender and performance of small business enterprise in Kawempe division.

Studies have revealed that women-owned firms were more likely to close and had lower levels of sales, profits, and employment (Kalleberg and Leicht 1991; Rosa et al. 1996; Robb 2002; Robb and Wolken 2002). Some of the differences are dramatic: as we shall see below, estimates from the Characteristics of Business Owners (CBO) survey indicate that the

11 sales of female-owned firms are roughly 80% lower than the average sales of male-owned firms. See Gatewood et al. (2003) for a comprehensive review of the literature and Coleman (2001) for a discussion of constraints faced by female-owned firms. A key constraint on businesses headed by women is the difficulty they face accessing finance. Women own 39 percent of the businesses in the Uganda Business Register (Government of Uganda 2002b). Women entrepreneurs face a clear gender bias in access to credit, receiving just 9 percent of available credit (about 1 percent in rural areas) (Mukasa and others 2004; Tripp and Kwesiga 2002).

2.2.4 Relationship between access to credit and performance of small business enterprise in kawempe division.

Berger and Udell (1995) argue that, given the strong relationship between lenders and borrowers, it is highly unlikely that the borrower fails to honour his debt, otherwise it would be difficult to find other banks willing to grant loans at the credit terms. Therefore when small business enterprises meet their obligations financial performance is improved.

In Uganda access to credit of small business enterprises is moderate through commercial banks. According to Bank of Uganda report (2011), more than 40% of the total private sector credit has annually been allocated to small business enterprise compared to agriculture and other services sector sectors which fall below 40% of the total private sector. This indicates that the amount allocated can relatively cause transformation of the sector.

The number of poor in Kawempe division has not reduced especially in the surburbs of Bwaise, Kalerwe, and Mulago poverty has also increased (Kawempe division, 2003). This hinders small business owners from accessing credit due to lack of collateral security hence poor performance of small businesses in kawempe division.

2.2.4Identification of the effect of age of the small business enterprises contribute to their performance in Kawempe division.

Literature on small business survival suggests that younger businesses in their formative years are more likely to be concerned with survival than growth if they do not fail within the first few

12 years of starting up (Cowling, 2006). Business performance is likely to improve as both the firm and entrepreneurs become more aged and thus experienced (Vassilakis, 2008).

2.2.5Identification of the effect of age of the small business own contribute to their performance in Kawempe division.

It is a fact that the age of business owners in all studies reviewed is measured in years, and more specifically within age groups (Kaunda, 2012; Osunsan and Sumil, 2012; International Labour Organization, 2005; Weber & Schaper, 2004). The ILO (2006) revealed that one-third of all successful entrepreneurs originate from the age group of 18 to 34 years. Similarly, Osunsan and Sumil (2012) found that majority of small business owners were within the age range of 20 to 39, accounting for half of small business owners in their study. Weber & Schaper (2004) on the other hand claimed that 31 % of small businesses where in fact started by those over the age of 50. Osunsan (2011) however, pointed out that starting up a businesses and realizing success in any aspect of life (including business) is not a subjected to age, but to individual drive and determination. Scholars such as Levesque and Minniti (2006), Watkins et al. (2003), and Storey (1994) suggested that younger business owners run businesses that perform better (in terms of growth), their argument is hinged on the believe that younger business owners are more motivated, energetic, committed and are less risk averse. Davidsson (1991) made a similar observation by pointing out that older business owners have probably realized their aspiration and have less drive due to the fact that the need for mortgage payments and supporting a family is not longer present. The opposite is true for young business owners. Belenzon and Zarutskie (2013) pointed out that firm performance drops as the owner grows older and they specifically mentioned that owners above the age of 54 show a great level of performance decline in their business. Cressy and Storey (1995) suggest that the survival rates of business by older entrepreneurs are higher than those by younger entrepreneurs; in order for a business to survive long it has to perform well and survive. On the basis of literature

2.3. Summary of literature

According to Curran and Blackburn (2001), small businesses have been distinguished from larger companies by such criteria as financial turnover, assets, market share, numbers employed and ownership. Further small businesses should be defined those with fewer than 50 employees

13 and have a turnover or balance sheet that does not exceed € 10 million (European commission, 2003b).typically small business performance is measured in economic or financial terms (Brush and Verderwerf, 1991). However there is empirical evidence that show that women owned business earn less money (Hisrich and Brush, 1987; Brush, 1990) and often don’t grow rapidly as male owned businesses (kalleberg and Leicht, 1991). According Levesque and Minniti (2006), Watkins et al. (2003), and Storey (1994) Younger business owners perform better in terms of growth. An organization\s financial performance can be measured by total sales, liquidity, and profitability (Kelley and Nakosteen, 2005; McMahon, 2001; Miller, Wilson and Adams 1988; Birley and Westhead 1994).

CHAPTER THREE

METHODOLOGY

3.0. Introduction

This section involved research design, study population, sample size and design, data collection methods and tools, data management and analysis, validity and reliability, ethical issues, limitations

3.1. Research design William G (2003), defines research design as the scheme, plan or outline that is used to generate answers to the research problem. A descriptive research was used and within it a cross section research where data was collected once, was adopted due to the limited time and financing. Descriptive statistics involves analyzing the relationship between variables. According to Kothari (2004), Descriptive research includes survey and fact finding enquiries of different kinds. The major purpose of descriptive research is description of affairs as it exists at present. The main characteristics of this method is that the researcher has no control over variables; he can only report what has happened and what is happening (Kothari, 2004). The reason for using this method is seen in its characteristics of prior specification of research questions and hypothesis. Thus information needed is clearly defined

3.2. Study population

The study area was Kawempe division but small businesses were selected for the case study analysis. Kawempe division is one of the five divisions of Kampala with the third highest total urban population (UBOS, 2002).

3.3.Sample size and design

Cluster sampling design was used in this study where parishes in Kawempe were used as clusters, within each cluster simple random sampling was adopted since it gives chances of selection of the elements (Kathori, 2004). Cluster sampling involves grouping population and then selecting the groups or clusters rather than individual elements in the sample (Kathori, 2004).

For population that are large Cochran (1963;75) developed the equation 1 to yield a representative sample for proportions.

푍2푝(1−푝) n= ………………..3.0 푒 2

Where n is the sample size

Z is the standard normal deviate corresponding to the degree of confidence selected. Two

confidence intervals used as a rule for the population mean are 95% and 99%. This study will

select 95% n confidence interval, z = 1.96.

p is the estimated proportion of an attribute that is present in the population

e is the error caused by examining a sample instead of the whole population.

n=(1.96)2*(0.987)(0.013)/(0.05)2

n=20 respondents in each parish

Table 3.1, showing sample distribution in the four parishes Area Sample size Kanyanya 20 Mpererwe 20 Kalerwe 20 Kyebando 20

Source: primary data 2019

A sample of 80 respondents was selected and of which 20 respondents was selected from the 4 parishes selected. This particular sample size was selected because it was easier to manage and it was enough to generate findings as well as to generalize the findings to a bigger population.

3.4. Data collection methods 3.4.1. Interview method

Interview is a conversation whose purpose is to gather description of interviewee with respect to interpretation of meanings of the described phenomena (Kvale, 1996) This method is usually done in qualitative research and occur when the researcher ask one or more participants in general, open ended questions, closed ended questions and record their answers (Creswell, 2012). Interviews are particularly useful for uncovering the story behind a participant experience and persuing in-depth information around the topic. The main task in interviewing is to understand what the interviewee say (McNamara, 1999)

3.5Data collection tools

3.5.1. Questionnaire

The data collection tool that was employed in this study was a questionnaire. The use of a questionnaire is one of the common data collection tool employed in research (kothari, 2004). Questionnaires are used extensively to gather data on current conditions, practices, opinions and attitudes quickly and in precise way (Orodho, 2008). Questionnaires provide the cheap way of obtaining data (Mugenda, 2003). Both open ended and closed ended questionnaires will be adopted.

3.6. Validity and reliability

3.6.1. Validity

Validity; Validity refers to the degree to which a measuring instrument measure what it predicted to measure (MacKenzie et al., 2016; Oluwatayo, 2012). In a qualitative study, the validity techniques should be well-stated (MacKenzie et al., 2016).

The validity of research instrument is referring to capabilities of the questionnaire to measure a construct or variable to be measured (Cresswell, 2014). The content validity or face validity refers to the ability of the instrument to collect data that will meet the objectives of the study (Noah, 2002). An instrument has a high validity if its degree of ability to measure what is supposed to be measured is high (Majid, 1990). Kirk and Miller (1986) stated that the validity

17 of the questionnaire was measured by determining the value of correlation between the scores of each item and the total score. The Pearson correlation is used to analyze the score of each item by the total score of the item of a construct. Abu Bakar (1995) also states that the minimum correlation coefficient value and acceptable is 0.30. Nunally and Bernstein (1994) stated that the correlation value between items with a total score of more than 0.25 is considerably high. 3.6.2. Reliability

This is the degree to which a test consistently measures whatever it measures (Mugenda and Mugenda, 2003). Charles (1995) adheres to the notions that consistency with questionnaire items are answered or individual scores remains relatively the same can be determined through the test retest method at to different times. The data collection methods, coding techniques and analysis can improve reliability (Barusch et al., 2013; Mangioni & McKerchar, 2013). Reliability of a scale (factor or construct) is to examine its internal consistency by calculating Cronbach’s alpha. This method indicates the extent to which items (elements) within a scale are homogenous or correlated (Saraph et al., 1989; Badri et al., 1995). It is also reflective of the consistency between different items in a scale, in measuring the same attribute. Generally, alpha values greater than 0.7 are regarded as sufficient (Nunnally, 1994; Cuieford, 1965).

Cronbach’s alpha can mathematically be defined as: α=k × μ / {λ+ (k–1) μ}……………………………….3.1

Where, K refers to the number of scale items, μ refers to the average of all covariance between items λ refers to the average variance of each item.

3.7.Data analysis and management

Data management

Data coding; here the researcher began to scan the recorded data and develop categories of phenomena. This enables the researcher to manage data by labeling, storing and retrieving it according to codes. Data can be coded descriptively or interpretively (Miles and Huberman,

1994). Coding; The data analysis helped provide larger meanings to the codes (Mangioni & McKerchar, 2013; Pietkiewicz & Smith, 2014). Editing. Editing is the procedure that improves data coding (Kothari, 2004).Editing of data will also be done every after interview conducted in order to ensure correctness and completeness of information. Data analysis

According to cooper and schindler (2011:90) data analysis involves reducing collected data to manageable size. Data analysis; Data analysis is not off-the-shelf manageable to suit a particular situation (Miles, Huberman, & Saldana, 2013). The researcher must be adaptive and flexible in combining strategies that generate and organize themes in the data analysis process (Leedy & Ormrod, 2013). After collection of the data it was managed properly, it was analyzed descriptively using SPSS software so as to obtain a more statistical analysis of the collected data.

Univariate analysis

For the case of univariate data, an explanatory data analysis tool, descriptive statistics was used in order to find out how many employees are employed in each selected business and their mean number. The mean number can be mathematically represented as follows

1 Mean = 푛 푥…………………3.2 푛 푖=1 n is the sample size x explanatory and dependent variables

X1 start up capital

X2 Age of the owner of small business

X3 Age of the business

X4 Gender of the small business owner

Bivariate analysis

In this analysis, two variables were tested for their significance that is chi-square test to test for independence of two categorical data sets and also compare their two frequencies, ANOVA was performed to examine the effect of each categorical variable on small business performance and also its T-test to compare means for categorical and continuous variables, correlation to test for linear association between two continuous variable. Mathematical formular for chisquare is as follows;

2 2 푛 푚 (푂푖푗 −퐸푖푗 ) 푥 = 푖=1∗ 푗 =1 …………………………3.3 퐸푖푗

Where i=1,2,3…….n j=1,2,3…….m n- number of categories m -number of categories O- is the observed frequency E- is the expected frequency

Multivariate analysis

Multiple linear regression model was used in this study because it attempts to model the relationship between two or more independent variables.

푦 = 훽0 + 훽1푥1 + 훽2푥2 + ⋯ + 훽푛 푥푛 + 휀……………3.5

Y is the small business performance

X1 start up capital

X3 Age of the business owner

X4 Gender of the small business owner.

3.8. Ethical issues

Seeking permission from small business owners was done in order to collect the viable data with them knowing about it. Confidentiality of the business owner information was done in order to keep their information anonymous. 3.9. Limitations

Small business owners find it hard to reveal the information about their businesses Most small businesses are not familiar with English language hence hindering the use of questionnaire. Transport costs might affect the research because of the many areas that have to be visited in Kawempe division

CHAPTER FOUR

RESULTS AND FINDINGS

4.0. Introduction

This chapter contains the results and interpretation relating to the sample characteristics of the survey. The research was guided by the research objectives. A total of 80 respondents from three areas that is Kalerwe, Mpererwe, Kyebando, and Kanyanya completed the questionnaires. Data from questionnaires was analyzed using SPSS.

4.1. UNIVARIATE ANALYSIS This involved descriptive statistics about the demographic statistics, business background, business performance, respondent’s attitude towards credit access.

4.1.1Demographic characteristics for the respondents in the study This included area, age, gender, level of education.

Table4.1: demographic characteristics Demographic characteristics Frequency Percent Area Kalerwe 20 25.0 Mpererwe 20 25.0 Kyebando 20 25.0 Kanyanya 20 25.0 Total 80 100.0 Age group 20 years and below 1 1.3 21-30 40 50.0 31-40 23 28.7 41 and above 16 20.0 Total 80 100.0 Gender Male 34 42.5 Female 46 57.5 Total 80 100.0 Source: primary data 2019 Results indicate that sample was proportionally distributed with 25% of respondents came from each region of study. Indicate that most of the respondents involved in small businesses are aged

22 between 21 and 30 years (50.0%) followed those aged between 31 and 40 years (28.7%) and those aged between 41 and above represented 20% of the whole sample. The least age group involved in small businesses were aged between 20 years and below representing only 1.3% of the whole sample. There were more female respondents indicating 57.5% compared to their male counterparts representing 42.5% of the whole sample. This indicates that the female respondents were much more cooperative than the male who claimed to be too busy to respond to the questions that were being asked to them.

Figure4.1 showing level of education of respondents

Source: primary data 2019 Figure 2 above shows that majority of the respondents engaged in small business were secondary holders (23 respondents) followed by those who attained a certificate (16 respondents) and the undergraduates were 15. Diploma holders were 14 followed by post graduate holders (6 respondents) and those who stopped at primary level were 5. Only 1 respondent was not educated.

4.1.2.Business background This involves the type of business, how respondents raised their startup capital, number of employees, period of existence of business, and whether they pay taxes, attitude towards daily profits

Table 4.2: business background Business background Frequency Percent Type of business Retail 62 77.5 Wholesale 14 17.5 Mobile money 4 5.0 Total 80 100.0 How startup capital was raised Personal savings 66 82.5 Family 6 7.5 Friends 4 5.0 Borrowed from banks 4 5.0 Total 80 100.0 Period the business has existed Below 4 years 53 66.3 5-10 20 25.0 11-15 5 5.0 16-20 0 0.0 21-25 0 0.0 26-30 3 3.8 Total 80 100.0 Do small businesses pay taxes Yes 78 97.5 No 2 2.5 Total 80 100.0 Attitude on daily profits Below target 27 33.8 Target 40 50.0 Above target 13 16.2 Total 80 100 Number of employees 1-4 74 92.5 5-9 4 5.0 10-19 1 1.3 20-49 1 1.3 Total 80 100.0 Source: primary data 2019 Majority of the business that respondents engaged in was retail business representing 77.5% of the whole businesses that were in the sample followed by wholesale business representing 17.5%

24 and the least was mobile money business with only 5%. Majority of the respondents got their startup capital from their own personal savings (82.5%) followed those who got it from their family (7.5%). Few respondents got their startup capital from friends and banks representing 5.0% each. Most of the small business enterprise have existed less than 4 years constituting 66.3% followed by those that existed between 5 and 10 years (25.0%), those exited between 11- 15 were 5.0% followed by those that existed between 26 and 30 years (3.8%). No business existed between 16-20 years and 21-25 years. Majority of the small businesses pay taxes constituting 97.5% while only few small businesses don’t pay taxes constituting 2.5%. 50% of the respondents had their profits at a set target followed by those who had their profits below target(33.8%), 16.2% of the respondents had their daily profits below target. majority of the respondents employed less than 4 workers (92.5%) followed by 5.0% who employed not more than 9 employees. Few respondents employed not more than 19 workers (1.3%) followed by those who employed less than 49 workers (1.3%). This implies that majority of the businesses are small sized.

4.1.3. Attitude towards business performance Table 4.3: Respondents perception about business performance and attitude towards credit access Perception about performance frequency Percent What is the trend of your customers for the last 8 months Below target 23 28.8 Target 51 63.7 Above target 6 7.5 Total 80 100.0 To what degree has your business achieved its most important goals Below target 29 36.2 Target 36 45 Above target 15 18.8 Total 80 100.0 The volume of assets the business has raised for the last 8 months Below target 23 28.8 Target 46 57.5

Above target 11 13.7 Total 80 100.0 The growth rate of the business it has registered Below target 27 33.8 Target 40 50.0 Above target 13 16.2 Total 80 100.0 The market share for the last 8 months Below target 22 27.5 Target 45 56.3 Above target 13 16.2 Total 80 100 Factors affecting the business High electricity bills 11 13.8 Increased rent 19 23.8 Unstable market 12 15.0 Increased taxes 38 47.4 Total 80 100.0 Attitude towards credit access It’s easy to access credit from money lenders Strongly disagree 22 27.5 Disagree 10 12.5 Uncertain 21 26.2 Agree 15 18.8 Strongly agree 12 15.0 Total 80 100.0 The business often borrows money from money lenders Strongly disagree 25 31.3 Disagree 20 25.0 Uncertain 8 10.0 Agree 21 26.3 Strongly agree 6 7.4 Total 80 100.0

It takes a short time to be given a loan after your application Strongly disagree 6 7.5 Disagree 15 18.8 Uncertain 22 27.5 Agree 28 35.0 Strongly agree 9 11.2 Total 80 100.0 One of the business priorities is its willingness to pay back the borrowed credit Strongly disagree 10 12.5 Disagree 17 21.3 Uncertain 16 20.0 Agree 23 28.8 Strongly agree 14 17.4 Total 80 100.0 Source: primary data 2019 Most of business owners (63.7%) attained their targeted customers for the last 8 months compared to those whose who attained below targeted customers(28.8%) and those who attained above targeted customers(7.5%). few of the business owns, their businesses has not yet achieved its important goals as it shows that these contribute 36.2% of the whole sample followed by those who went beyond target(18.8%) and majority had reached their desired target(45%) . most the businesses had attained their desired assets contributing (57.5%) followed by those whose business assets are below target(28.8%) and then those went beyond their set target(13.7%). Majority of the businesses has registered their target growth rate(50.0%) followed by those who are below their target(33.8%) and those who went beyond their target(16.2%). 56.3% of the businesses have attained their target market share for the last 8 months followed by those who are had only attained below target(27.5%) and those who were above target(16.2%). most small businesses are affected by increased taxes constituting 47.4% compared to those who are affected by increased rent(23.8%), unstable market(15%) and then high electricity costs(13.8%). majority of the respondents(27.5%) strongly disagree that it’s easy to access loans from money lenders followed by those who were uncertain(26.2%), those who agreed were (18.8%), (15.0%) of the respondents strongly agreed, (12.5%) of the respondents disagreed. majority of the

27 respondents(31.3%) strongly disagree that business often borrows money from money lenders followed by those Agreed(26.3%), those who Disagreed(25.0%), (10.0%) of the respondents were Uncertain, Strong agreed were 7.4%. (35%) of respondents agreed that It takes a short time to be given a loan after your application, followed by Uncertain(27.5%), Disagree (18.8%), Strong agree(11.5%). most of the respondents Agreed(28.8%) that one of the business priorities is willingness to pay back the borrowed credit, followed by those that that Disagreed(21.3%) then those that were Uncertain were (20.0%), (17.4%)Strong agree, Strongly Disagree(12.5%).

4.2. BIVARIATE ANALYSIS This involved hypothesis testing, relationship between daily profits and startup capital, relationship between age of the business and daily profits, relationship between gender and daily profits

4.2.1. Relationship between profits and startup capital invested Table 4.4: Relationship between profits and startup capital invested Profits startup capital invested Pearson Correlation 1 .659** Sig. (2-tailed) .000 N 80 80 Source; primary data 2019 There is a significant strong positive correlation between startup capital and the daily profits made (p-value<0.05). This concludes that, the higher the startup capital invested in the small business the higher the daily profits. In South Africa Eeden (2004) found finance as cited as one of the most prominent constrains.

4.2.2. Relationship between age of business owner and daily profits earned Table 4.5: Relationship between age of business owner and daily profits earned Sum of Df Mean Square F Sig. Squares Between .212 .496 1 .496 1.583 Groups Within Groups 24.428 78 .313 Total 24.924 79 Source: primary data 2019 It is evident that there is a weak positive relationship which is insignificant (p-value>0.05). This indicates that the more years of the business owner doesn’t guarantee that it will achieve higher profits. Osunsan (2011) however, pointed out that starting up a businesses and realizing success in any aspect of life (including business) is not a subjected to age, but to individual drive and determination

4.2.3. Relationship between daily profits and gender Table 4.6: relationship between daily profits and gender Sum of Squares Df Mean Square F Sig. Between 3866879923.274 1 3866879923.274 .065 .799 Groups

Within Groups 4623152670076.726 78 59271188077.907 Total 4627019549999.999 79 Source; primary data 2019 It is evident that daily profits are not related to gender. 4.3. MULTIVARIATE ANALYSIS Multiple linear regression was used in order to establish the combined effect of the independent variables that is startup capital, how long has the business been in existence and gender. The regression analysis was done to address the three objectives which were to identify how startup capital contribute to the performance of small business enterprise in the area under study, To identify the effect of age of the small business enterprises contribute to their performance in Kawempe division, to investigate the relationship between gender and performance of small business enterprise in Kawempe division.

Table 4.7; summary of the model Model R R Adjusted Std. Change Statistics Square R Error of Square the Estimate R F df1 df2 Sig. F Durbin- Square Change Change Watson Change 1 .684a .468 .447 .41766 .468 22.294 3 76 .000 1.687 Source: primary data 2019 a. Predictors: (Constant), how long has the business existed, gender, startup capital invested b. Dependent Variable: profits From the table above, it shows that 44.7% (adjusted R Square)of the variance of the dependent variable(profits) is explained by the independent variables(startup capital, age of business owner).

4.3.1. Association between daily profits with startup capital, age of business owner and gender of the small business owner. The Unstandardized Coefficients of determination under the B column in Table 4.8(model 1) were used to substitute the unknown beta values of the regression model. The beta values indicated the direction of the relationship. A positive or negative sign indicates the nature of the relationship. The significant values (p-value) under sig. column indicate the statistical significance of the relationship or the probability of the model giving a wrong prediction. A p- value of less than 0.05 is recommended as it signifies a high degree of confidence.

Table 4.8: association between daily profits with startup capital, age of business owner and gender of the small business owner. Model Unstandardized Standardized t Sig. Collinearity Statistics Coefficients Coefficients B Std. Error Beta Tolerance VIF (Constant) 5.029 .298 16.893 .000 startup capital 5.719 ∗ 10−8 .000 0.643 7.643 .000 .992 1.008 1 invested Age -.147 .096 -.130 -1.528 .131 .971 1.030 Gender -.156 .091 -.146 -1.721 .089 .970 1.031 Source: primary data 2019

a. dependent variable; profits b. Independent variable; startup capital, age and gender. From the table above, unlike gender and age, startup capital has a significant impact on the daily profits exhibiting a p-value <0.05 and also for a 1 unit change in startup capital there is a 5.719 ∗ 10−8 change in the daily profits. The years the business has existed have no significant impact on the daily profits. stoner (1996), as he suggests that profitability has been a widely used measure of financial performance. In South Africa Eeden (2004) found finance as cited as one of the most prominent constrains.

푦 = 5.029 + 5.719 ∗ 10−8startup capital invested − 0.147age − 0.156gender

CHAPTER FIVE

SUMMARY FINDINGS, RECOMMENDATIONS AND CONCLUSION

5.0. Introduction

The study sought to establish the effect of startup capital on the performance of small business enterprise .A total of 80 questionnaires were administered and the study managed to obtain 80 completed questionnaires representing 100% response rate. The questionnaires contained questions that addressed the objectives of the study. This chapter presents discussion on the findings in chapter four. This is followed by conclusions and further recommendations. The presentation of the findings is in line with the objectives of the study.

5.1 summary of the findings

As exhibited in chapter four,50% of the small businesses had their profits within their targeted expectation and also the study results revealed that there was a significant positive effect of startup capital on the performance (profits) of small business enterprise with a p-value<0.05. This implies that the more capital you invest in the business the likely the profits of that business will reflect on that startup capital invested in keeping other factors constant. Therefore less startup capital exhibit a poor performance of small business enterprise in terms of profits. This is in line with stoner(1996), as he suggests that profitability has been a widely used measure of financial performance. The study found out that most small businesses prefer to use personal savings and contributions from relatives because they find it very difficult to access financing from commercial banks due to strict requirements such as collateral security and high repayment costs. The study therefore recommends that banks and other credit giving financial institutions should come up with creative policies that make it easy for the Small businesses to access financing.

5.2. CONCLUSION

In general the study looked at the effect of startup capital on the performance of small business enterprise. It was observed that there was a significant positive relationship between startup capital and performance of small businesses. It is clear that startup capital is a major constraint on the performance of small business and plays a vital role before one thinks of any business.

5.3. RECOMMENDATIONS

In order to boost small business performance, the following are emphasized

Gender relations. There is need for more women empowerment since majority of small businesses are owned and run by women. Commercial banks perceive women as high risk borrowers and this is due to the property rights which limit women’s ability to own land that is very essential as collateral tool for them to access finance.

Government policies. The study found out that the government policy and regulations has a moderating effect on the performance of small businesses in Kawempe division. The study therefore recommends that the government should move in quickly to create policies that favor the growth and expansion of small businesses. This will save the businesses from the challenges they face when trying to access financing from mainstream commercial banks

5.4. AREAS FOR FURTHER RESEARCH

There is further research needed on the role of financial and non-financial institutions on the performance of small businesses.

Research on factors affecting business performance which are not finance related.

Effect of managerial competence, information availability and other factors that affect the general performance of Small businesses.

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Appendix 1: QUESTIONNAIRE Dear respondent

Thank you for volunteering to complete this questionnaire. Your responses are important and your thoughts considerations are highly appreciated. The purpose of this questionnaire is to facilitate research on the effect of startup capital to the performance of small business enterprise in kawempe division Kampala district by Mr. Kimuli Isaac who is undertaking a bachelor’s degree in business statistics at Makerere University.

The study is purely academic, therefore all your responses will be treated at most confidentially. the findings and recommendations will benefit small business owners. kindly answer personally and tick where possible so that we can be able to analyze data accurately. Thank you very much for your cooperation.

SECTION 1: DEMOGRAPHIC CHARACTERISTICS 1. Area/location of the business …………………………………………………….. 2. What is your age? 1. 20 years and below 2. 21-30 3. 31-40 4. 41 and above 3. What is your gender? 1. Male 2. female 4. What is your level of education? 1. post graduate 2. undergraduate 3. diploma 4. secondary 5. certificate 6. primary 7. not educated

SECTION2: BUSINESS BACKGROUND 5. What type of business do you operate 1. retail business 2. wholesale business 3. mobile money

6. How did you raise you start up capital for your business 1. personal savings 2. family 3. borrowed from banks 4. friends

7. Number of employees 1. 1-4 2. 5-9 3. 10-19 4. 20-49 4. For how long has the business existed………………………………………….. 1. Yes 2. no

8. Startup capital invested…………………………………………….. SECTION 3. PERFORMANCE OF YOUR BUSINESS 9.Use the scale of four the following items regarding small business performance

Below target Below target target Above target Bp1 Start up capital invested in Bp2 What is the trend of your customers for the last since the business started Bp3 To what degree has your business achieved its important goals Bp4 The volume of assets achieved since the business started Bp5 The level of profits the business has raised since the business started Bp6 The growth rate of business has registerd over time Bp7 The market share for the last 5 years key 1. below target 2. target 3. above target

10. daily profits earned……………………………………………. 11.factors affecting your business

1. Electricity costs 2. Increased rent 3. unstable market increased taxes

SECTION 4. ACCESS TO CREDIT 12.use a scale of five to answer the following question.

Strongly Disagree(2) Uncertain(3) Agree(4) Strongly disagree(1) agree(5) Ac1 Its easy to access credit from money lenders Ac2 The business often borrows money lenders Ac3 It takes a short time to be given a aloane after application Ac4 One of the business priorities is willingness to pay back the borrowed credit key 1. strongly disagree 2. disagree 3. uncertain 4. agree 5. strongly agree