African Journal of
Business Management

  • Abbreviation: Afr. J. Bus. Manage.
  • Language: English
  • ISSN: 1993-8233
  • DOI: 10.5897/AJBM
  • Start Year: 2007
  • Published Articles: 4137

Full Length Research Paper

Effects of microfinance services on the performance of small and medium enterprises in Kenya

Irene Rotich
  • Irene Rotich
  • Moi University, Kenya.
  • Google Scholar
Charles Lagat
  • Charles Lagat
  • Moi University, Kenya.
  • Google Scholar
Japhet Kogei
  • Japhet Kogei
  • Moi University, Kenya.
  • Google Scholar

  •  Received: 11 July 2014
  •  Accepted: 09 March 2015
  •  Published: 14 March 2015


The Micro, Small and Medium Scale Enterprises (MSMEs) sector in Kenya has grown tremendously over the last two decades but its growth is characterized by low productivity and survivalist enterprises. The sector is however very strategic in providing future employment for the economy. This paper reviews the effects of microfinance services on the performance of MSMEs using an explanatory research design. The study targeted 429 MSMEs registered by the Kiambu Municipal Council and sampled 270 enterprises. The study utilized multiple regression analysis set draw inferences on the study using SPSS statistical package. The study found access to savings schemes, managerial training and loan grace period to be statistically significant in determining the performance of MSMEs. This study concludes that increasing provision levels of micro finance will result in increased performance of micro enterprise. The study makes recommendations for microfinance service providers and policy development partners.


Key words: Microfinance, MSMEs, enterprises, performance, financial services.


The Consultative Group to Assist the Poor (CGAP) defines a Microfinance Institution (MFI) as an organisation that provides financial services to the poor in the form of credit, savings and insurance. Microfinance is also defined as provision of small- scale financial services to the low- income people (Robinson, 2001; Nair, 2001). Financial services provide the poor an opportunity to improve their livelihoods and, alongside with social services, can contribute to poverty reduction. People living in poverty, like everyone else, need a diverse range of financial services to run their businesses, build assets, smooth consumption, and manage risks (CGAP, 2012).

The microfinance industry was borne primarily out of a desire to help the world’s vulnerable and poor (Campion et al., 2008). Over the years, following numerous studies and models, it has become clear that the poor are actually bankable. Thus the microfinance industry today forms an integral part of the formal financial sector in many countries around the world. By 2006 there were more than 133 million microfinance clients, 70% of whom were among the world’s poorest people (Campion et al., 2008). Providers of financial services who enable people to cross such a poverty line have focused on credit, in particular credit for small enterprises, including agricultural production (Johnson and Rogaly, 1997).

The ability to both borrow and save with an MFI may increase micro entrepreneur’s profits through lower interest rates and access to appropriately  designed  loan products. This also improves their ability to manage working capital needs through borrowing and savings at different times as required (Ledgerwood, 1998). MFIs that target potential entrepreneurs often have poverty alleviation as an objective. The belief is that by aiding potential entrepreneurs to start up their own businesses, they will increase their incomes and consequently reduce their level of poverty. Most MFIs prefer to focus on existing businesses, with perhaps a small portion of their portfolio invested in start-up businesses, thereby reducing their risk horizon (Ledgerwood, 1998). However, potential entrepreneurs often need more than financial services. Many need skills training or other inputs to make their enterprises a success (Ledgerwood, 1998).

According to the Kenya Micro and Small enterprises bill, 2006, micro and small enterprises are defined as enterprises in both formal and informal sector, classified in farm and non- farm categories, employing not more than fifty employees and have a turnover not more than four million shillings. Small and medium enterprises in Kenya contribute between 18-25% to the country’s GDP and employ over about 17% of the total labour force in Kenya, (CBS, ACEG and   KREP Holdings, 1999). Most small business enterprises are self-financed or financed by loans from family or other informal sources. Small and medium enterprises in Kenya make a contribution for between 18-25% to the country’s GDP and employ over about 17% of the total labour force in Kenya (CBS, ACEG and KREP Holdings, 1999).

Kenya has a developing economy, agriculture being the chief economic activity. Most people in Kenya work in agricultural sector. Some practice subsistence farming while a very small number practice large-scale farming. Some people work as wage labourers in coffee farms or tea plantations. They depend on the small wages and life become rather unbearable at times. For those who practice small scale farming, their source of income is mainly from the sale of the farm produce. Some are engaged in small businesses such as the selling of agricultural goods in market places while others trade in livestock and selling of milk. There are all sorts of small businesses related to agricultural sector.

Kenyan microfinance has shown resiliency despite local droughts and high inflation rates that afflicted the economy in 2008 and 2009. With the Kenyan government and the Central Bank of Kenya (2005) emphasizing financial access as a key to modernizing the economy, the sector has been strengthened by progressive policies and innovative approaches to delivering financial services. A large deposit base, along with the existence of well-developed MFIs, has allowed financial and operational expenses to remain relatively low and has led to some of the highest profitability measures in the region.

The purpose of the study was to assess the contribution of microfinance institutions to the performance of the economically active low income traders in Githurai market, Kiambu County, Kenya, through delivery of microfinance products and  services.  

As with many developing countries, there is limited research and scholarly studies on the contribution of the MFIs to the growth of the economy. It is generally recognized that small businesses face unique challenges in their financing and management structure, which affect their growth and profitability  and  hence,  diminish  their  ability  to  contribute  effectively  to  sustainable development (Mead,1998). The general objective of the study was to find out the effect of microfinance services on the performance of micro, small and medium enterprises in Githurai market.


SMEs  (Small  and  Micro-enterprises)  within  the manufacturing  sector  have  not  seen  much development since independence due to financial constraints and other factors. Jua Kali Sector, a Kiswahili term for a hot sun, comprises low scale artisans who mostly apply appropriate intermediate technology. This sector, given all conditions for growth can bring about industrial revolution in Kenya. The phrase itself can tell it all.

Micro and small enterprises have potentiality of boosting economic growth. Although they are faced with many challenges, they still have opportunities to grow. These include linkage with multinational  companies,  networks  with  other  businesses,  diversification  of  market  and products, enabling environment and franchising  opportunities.  Such opportunities, if well utilized by the micro and small enterprises, can turn around their future in many developing countries (Wanjohi and Mugure, 2008).

Small businesses tend to have a poor collateral base and therefore get excluded from the credit market (Kimuyu and Omiti, 2000). Among other reasons for poor access to credit facilities are lack of information of credit sources, weak contract enforcement mechanisms and high transaction costs (Farchamps et al., 1994). Credit accessfor business expansion and capital investment are out of reach for MSMEs for the same reasons given above.

According to the CBS, ACEG and KREP Holdings (1999) many Small and Medium Enterprises (MSMEs) commence business while undercapitalized and this suggests major operational difficulties and problems in accessing credit. Unlike larger enterprises, MSMEs require less capital though such business owners are unlikely to belong to high income households and have low savings (Kimura, 1999). For 80% of MSMEs their main source of capital was personal savings (CBS, ACEG and KREP Holdings, 1999) and 19% from family contributions and sale of personal assets. Only a very small percentage of SME owners have access to credit for start-up. Eventually when these MSMEs commence business they encounter the challenge of working capital and this was where credit access plays a big role. Performance is a widely used concept in many areas. In enterprise management, Moullin (2003) defines an organization’s performance as “how well the organization is managed” and “the value the organization delivers for customers and other stakeholders.” Measuring perfor-mance is a multi-dimensional concept. Effectiveness and efficiency are the two fundamental dimensions of performance (Neely et al., 2002). Performance of small businesses is defined as their capability to lead to the creation of employment and wealth by business start-up, survival and sustainability (Sandberg et al., 2002).

The URT MSMEs policy recognizes that MSMEs are confronted with unique problems including heavy costs of compliance resulting from their size. Other constraints include insufficient working premises and limited access to finance, Business Development Services, namely services related to entrepreneurship, business training, marketing, technology development and information are undeveloped and not readily available. MSMEs lack information as well as appreciation from such services and can hardly afford to pay the services. As a result, operators of the sector have rather low skills. Institutions and associations supporting SMEs are weak, fragmented and uncoordinated partly due to lack of clear guidance and policy for the development of the sector (URT, 2003).

A study by Amin et al. (2003) used a unique panel dataset from northern Bangladesh with monthly consumption and income data for 229 households before they received loans. They found that while microcredit is successful in reaching the poor, it is less successful in reaching the vulnerable, especially the group most prone to destitution (the vulnerable poor). Coleman (1999) also finds little evidence of an impact on the programme participants. The results, Coleman further explains, are consistent with Adams and von Pischke’s assertion that “debt is not an effective tool for helping most poor people enhance their economic condition” and that the poor are poor because of reasons other than lack of access to credit.

According to Mosley (1999), microfinance makes a considerable contribution to the reduction of poverty through its impact on income and also has a positive impact on asset level. But the mechanism through which poverty reduction works varies between institutions. Generally, institutions that give, on average, smaller loans reduce poverty much more by lifting borrowers above the poverty line, whilst institutions giving larger loans reduce it much more by expanding the demand for labour amongst poor people. Hulme and Mosley (1998) found evidence of a trade-off between reaching the very poor and having substantial impact on household income. They found that programmes that targeted higher-income households (those near the poverty level) had a greater impact on household income.

Mosley (2001), in his research on microfinance and poverty in Bolivia, assessed the impact of microfinance on poverty, through small sample surveys of four microfinance institutions. Two urban and two rural, using a   range  of  poverty  concepts  such  as  income,  assets holdings and diversity, and different measures of vulnerability. All the institutions studied had on average, positive impacts on income and asset levels, with income impacts correlating negatively with income on account of poor households choosing to invest in low-risk and low-return assets. The studies revealed also that in comparison with other anti-poverty measures, microfinance appears to be successfully and relatively cheap at reducing the poverty of those close to the poverty line. However, it was revealed to be ineffective, by comparison with labour-market and infrastructural measures, in reducing extreme poverty.

Nichols (2004) used a case study approach to investigate the impact of microfinance upon the lives of the poor in the rural China and found that the participation of poor in MFI program had led to positive impact in their life. Aczel (2000) conducted a study in Thailand on the role of microfinance in supporting micro entrepreneurial endeavor. The findings of the study indicated that the involvement of microfinance institutions in promotion of micro enterprise and processing industry plays a key role in economies of developed countries as a source of goods and services, income, savings and employment. Mochona (2006) studied the impact of microfinance in Addis Ababa-Ethiopia. He assessed the impact of microfinance on women micro enterprises that were clients of Gasha Microfinance Institution. The research findings indicated that only a few of the women clients of the Gasha Microfinance Institution reported increased incomes from their micro enterprise activities. Rahmat and Maulana (2006) researched on the Impact of Microfinance to Micro and Small Enterprise’s Performance Indonesia.

Bowen et al. (2009) researched on Management of business challenges among small and micro enterprises in Nairobi Kenya. The findings of the research indicated that over 50% of MSMEs continue to have a deteriorating performance with 3 in every 5 MSMEs failing within months of establishment. K'Aol (2008), in his research paper on the role of microfinance in fostering women entrepreneurship in Kenya, assessed the impact of Microfinance funding on women entrepreneurship in Kenya. The population consisted of women entrepre-neurs who had benefited from four major Kenya Rural Enterprise Program (K-REP) microfinance schemes within Nairobi and Nyeri. The findings revealed that most of the respondents in this study reported that their business had expanded and their house hold income had increased significantly as a result of having taken microfinance loans from K-REP. Simeyo et al. (2011)’s study revealed that loan provision, training and saving mobilization had the largest significant effect on performance. This study will utilize Simeyo (2011)’s framework that savings mobilization, access to capital and managerial training impacted positively on MSMEs performance in Kenya.

Research has shown that access to external finance was the most significant factor contributing to  the  growth of small firms (Brown et al., 2003). Furthermore, the majority of SMEs have been found to be heavily dependent on bank finance (Norton, 2003; Group of Ten, 2001) and Kenya MSMEs are not the exception.

Many MSME 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 (Hill, 1987). 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 MSME owners are ill prepared to face changes in the business environment and to plan appropriate changes in technology.  Majority of those who run MSMEs are ordinary lot whose educational background is lacking. Hence they may not be well equipped to carry out managerial routines for their enterprises (King and McGrath, 2002).

In order to achieve the objectives of the study, the following hypotheses were formulated;

H0: Access to credit has no effect on the performance of micro, small and medium enterprises in Kenya.

H0: Managerial training has no effect on the performance of micro, small and medium enterprises in Kenya.

H0 Savings mobilization has no effect on the performance of micro, small and medium enterprises in Kenya.


This study adopted explanatory research design in investigating the effect of microfinance services on the performance of small medium micro enterprises in Kiambu county Kenya. Explanatory research design was chosen because in business research, the cause-effect relationship is less explicit (Cooper and Pamela, 2006). The target comprised the 429 MSMEs registered with Kiambu Municipal Council and operating within the Githurai Market.  The MSMEs in Githurai Market largely deal in shoes, new clothes, Mitumba (imported used cloths), green vegetables, various accessories, fruits and consumables. Stratified random sampling technique was used in deriving the desired sample of 270 MSMEs.

The study relied on primary sources of data using structured questionnaires which were self-administered to owners of the MSMEs to gather primary quantitative data. The five-point-Likert scale questionnaire was divided into five sections: demographic information, access to credit information, managerial training, savings mobilization and performance of MSMEs. Data on access to credit was measured through respondents’ perception on whether it was easy to access loans from micro finance institutions. Data on savings mobilization was obtained using the five point scale Likert questionnaire where respondents’ satisfaction was measured. Data on managerial training focused on the three key business acumen skills namely capital investment decisions, basic business skills and risk management skills. The performance of MSMEs was measured using the growth in income. The research study was carefully planned to ensure all ethical standards are met and that the chances of misleading results were minimized.

Descriptive and inferential statics were used in data analysis.  Multiple linear regression analysis was used to establish the relationship and magnitude between micro finance services (independent variables) and performance of micro enterprise (dependent variable) where SPSS statistical package was used for this purpose. This analysis was based on the Simeyo et al. (2011)’s model which is specified as follows:

Micro enterprise performance = ƒ (Loan, Savings mobilization and Training)

Thus, the model ROA = α +β1LS + β2SM + β3MT + ε…....………….1

Where, ROA – Micro enterprise performance, measured by growth in ROA,

α – Constant (autonomous performance),

LS – Access to credit,

SM – Savings mobilization,

TM – Managerial training

β1, β2, β3 – Coefficients of the independent variables and ε – Error term.


Out of 270 questionnaires distributed 243 of them were received and used for analysis, which was a 90% response rate. Out of these, 243 were found usable for the study and 10 questionnaires were discarded due to incompleteness and large number of missing values. The majority (51.3%) of the respondents fell within the 31- 40 years age bracket, 25.3 per cent were below 30 years while 23.4% were over 40 years of age. 34% of the respondents were male and 66% of the respondents were female owners of micro and small enterprises which is a reflection of the target population.

On education, the majority of the respondents (45.6 %) completed secondary school followed by those who had completed primary education (35.1%). Only a small proportion of the respondents had acquired college (16.8 %) or university level (2.5%), showing low levels of education among the MSMEs owners and managers.     

Pearson correlation coefficient was used to determine the strength and direction of association between provision of micro finance and performance of MSMEs (Table 1). 





From the results all correlations are significant (P<0.01). The correlations 0.947, 0.945 and 0.945 show a strong positive relationship between access to credit, savings mobilization and training respectively (as independent variables) and performance (as dependent variable). It was also necessary to check the possibility of multicollinearity between predictors. The correlations among the independent variables (predictors) are less than 0.900, indicating absence of collinearity (Field, 2005).

Multiple regression analysis was used to establish the effect of access to credit, savings mobilization and managerial training on performance of micro enterprise. The analysis also shows the relationship between the variables. The coefficients of  regression results are presented in Table 2 and when these beta coefficients are substituted in the equation, the model becomes:

ROA = 0.507 + 0.385 LS +0.272 SM + 0.281 TM+ε………………………… {Equation 2}





This means that even without the three independent variables (access to credit, savings mobilization and training), the performance of micro enterprise is expected to stand at 0.507 (Y-intercept). The coefficients of access to loan, savings mobilization and training are 0.385, 0.272 and 0.281 respectively. They are all positive, meaning that as the magnitudes of the independent variables (access to credit, savings mobilization and training) increases, the magnitude of the dependent variable (performance) also increases.

Table 2 also shows the beta values converted in the same scale to enable comparison. Access to credit, having the largest beta of 0.385 has the largest effect on performance. The second most important variable was training with a beta of 0.281. The least important predictor of these three variables is savings mobilization with a beta of 0.272.


The findings indicated that the access to credit, savings mobilization and training in micro enterprise investment was on average satisfactory to the micro entrepreneurs. The study concluded that there existed a relationship between extent of provision of microfinance and performance of microenterprises and that micro finance significantly affected performance of micro enterprises. It therefore implies that improvement in the provision levels of micro finance will result in increased effect on performance of micro enterprise. Training in micro enterprise investment as a component of micro finance help clients in business management and minimizing transaction related risks. The results are in line with that of Kithae et al (2013) that the financial sector had very high positive correlation with performance of women entrepreneurs and also Lagat (2012) on the impact of youth enterprise fund in Kenya.

The study recommends that microfinance service providers and policy development partners could consider including a micro-insurance scheme in the micro finance package. Also extension of the current loan grace period of one month would give the entrepreneurs adequate time to invest the loan and use the returns from the investment for loan repayment. The government and development partners could consider channeling more funds for micro financing programs to bring on board many unemployed people that are currently out of reach of the programs as this will help spur economic development and alleviate unemployment.

The current study was a cross sectional survey based on a small sample size taken from only Kiambu county, Githurai market. It is therefore recommended a similar study but employing longitudinal survey on a larger sample. 


The author(s) have not declared any conflict of interests.


Aczel DA (2000). Complete Business Statistics. New York, Mc Graw Hill Company.


Amin S, Rai AS, Topa G (2003). "Does microcredit reach the poor and vulnerable? Evidence from northern Bangladesh, J. Dev. Econ. 70(1): 59- 82.


Bowen M, Makarius M (2009). Management of business challenges among small and micro enterprises in Nairobi Kenya. KCA J. Bus.Manage., 2(1).


Brown JD, Earle JS, Lup D (2003). "What makes small firms grow? Finance, human capital, technical assistance, and the business environment in Romania". Staff Working Paper, Upjohn Institute, Kalamazoo, Retrieved on 28 November at


Campion A, Linder C, Knotts K (2008). Putting the 'Social' Into Performance Management: A Practice based Guide for Microfinance. Microfinance Gateway. Retrieved from


Central Bureau of Statistics [CBS] (1999). African Centre for Economic Growth [ACEG] and KREP Holding. National Micro and Small Enterprises Baseline Survey. Nairobi: CBS


Coleman BE (1999). The impact of group lending in Northeast Thailand. J. Dev. Econ. 60(1):105–141.


Enterprising Solutions Global Consulting, (2005). LLC, "Rwanda Microfinance Sector Assessment" (2005) European Union Government of Kenya (2005). "Sessional paper No. 2: Development of micro and small Enterprises for wealth and employment creation for poverty Reduction" Kenya.


Hill T (1987). Small business production/operations management. Macmillan Education Ltd.


Hulme D, Mosley P (1998). Microenterprise Finance: Is There a Conflict Between Growth and Poverty Alleviation? World Dev. 26(5): 783–790.


Johnson S, Rogaly, B (1997). Microfinance and poverty reduction. Oxfam publications.


Kimuyu P, Omiti J (2000). Institutional Impediments to Access to Credit By Micro and Small Scale Enterprises in Kenya. Discussion Paper No. 026/2000.


King K, McGrath S (2002). Globalisation, Enterprise and Knowledge, Oxford: Symposium.


Kithae PP, Nyaga J, Karoki JM (2013). An Evaluation of Legal, Legislative and Financial Factors Affecting Performance Of Women Micro Entrepreneurs In Kenya, Eur. J. Bus. Manage. (Online), 5:8.


Ledgerwood J (1998). "Sustainable Banking with the Poor" Microfinance Handbook. The international bank for reconstruction and Development World Bank.


Mead DC (1998). "Micro and Small Businesses tackle poverty and growth (but in different proportions" Paper presented at the conference on Enterprises in Africa: between poverty and growth. Centre for African Studies, University of Edinburgh. Mochona S (2006). Impact of Micro finance in Addis Ababa: The case of Gasha Micro Finance Institution. Ethiopia.


Mosley P (1999). Microfinance and Poverty: Bolivia Case Study, draft, University of Reading, England.


Mosley P (2001). Microfinance and Poverty in Bolivia, J. Dev. Stud. 37 (4): 101-132.


Moullin M (2003). 'Defining Performance Measurement,' in Perspectives on Performance, 2(2):3.


Nair A (2001). Sustainability of Microfinance Self Help Groups in India: Would Federating Help? Woodrow Wilson School of Public and International Affairs, India, Princeton University.


Neely A, Adams C, Kennerley M (2002): The Performance Prism: The Scorecard for Measuring and Managing Business Success, Financial Times Prentice Hall, London.


Nichols S (2004). A Case Study Analysis of the Impacts of Microfinance Upon the Lives of the Poor in Rural China, RMIT University, Melbourne, 2000.


Norton A (2003). "Basel 2 – SME 0, Another tricky hurdle for business?" Credit Management, p 40. Fafchamps M, Biggs T, Conning J, Srivastava P (1994).Enterprise Finance in Kenya. Regional Program on Enterprise Development Africa Region: The World Bank.


Rahmat M, Maulana A (2006). The Impact of Microfinance to Micro and Small Enterprise's Performance and the Improvement of their Business Opportunity. Department of Economics, Padjadjaran University.


Robinson M (2001). The microfinance revolution: Sustainable finance for the poor. Washington DC: World Bank.


Sandberg K. Vinberg S, Pan Y (2002). An exploratory study of women in micro enterprise; owner perceptions of economic policy in a rural municipality: Gender-related diffrencess.In:CD proceedings of 12th Nordic conference on Small Business Research. Creating Welfare and Prosperity through Entrepneurship.Kuopio Finland. pp.1-14


Simeyo O, Martin L, Nyamao NR, Patrick O, Odondo AJ (2011). Effect of provision of micro finance on the performance of micro enterprises: A study of youth micro enterprises under Kenya Rural Enterprise Program (K-REP), Kisii County, Kenya. 5(20): 8290-8300.


Wanjohi AM, Mugure A (2008). "Factors affecting the growth of MSEs in rural areas of Kenya: A case of ICT firms in Kiserian Township, Kajiado District of Kenya Wanjohi"