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\title{Determinants of Micro and Small Enterprises Performance in South West Ethiopia: The Case of Manufacturing Enterprises in Bench Maji, Sheka, and Kefa Zones}
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             \author[1]{Gemechu  Abdissa}

             \affil[1]{  izan-Tepi University, Mizan Teferi}

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\date{\small \em Received: 9 December 2015 Accepted: 5 January 2016 Published: 15 January 2016}

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\begin{abstract}
        


The aim of this study is to investigate the factors that affect the performance of SMEs in Bench Maji, Sheka, and Kefa zone particular to manufacturing sector. In this study, mixed research methods were used. Stratified simple random sampling was used to select proportional number of samples from the study area. Both primary and secondary source of data were used. To obtain the primary data, questionnaires were distributed for 278 micro and small sized enterprises owners and managers to access the performance status of their enterprises and also to examine factors affecting their performance. Secondary data were collected from books, journals, past research works, official documents and the Internet.

\end{abstract}


\keywords{small and medium enterprises (smes); performance, internal and external factors.}

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\let\tabcellsep& 	 	 		 
\section[{Introduction}]{Introduction}\par
he success of the government and a country, in regard to business development, is related to small business sustainability \hyperref[b6]{(Carrasco-Davila, 2005)}. Local and federal authorities had been developing programs that promote the creation of new jobs thru the small business (Plan Nacional de  {\ref Desarrollo, 2007)}.The small and medium business sectors are recognized as an integral component of economic development and a crucial element in the effort to lift countries out of purveys. The dynamic role of micro and small enterprises (MSEs) in developing countries as engines through which the growth objectives of developing countries can be achieved has long been recognized. Small businesses play an important role in the development of a country and serve as a means to sustain and grow economies \hyperref[b26]{(Ibrahim, Angelidis, \& Parsa, 2008)}. Due to the ease in starting and simplicity in operation, small businesses are initiated for various reasons depending upon entrepreneur motives and traits \hyperref[b31]{(Kozan et al., 2006)}. Small businesses contribute to lowering unemployment as well as generate new sources of employment.\par
Recent empirical studies show that MSEs contribute to over 60\% of GDP and over 70\% of total employment in low-income countries, while they contribute over 95\% of total employment and about 70\% of GDP in middle-income countries. Therefore, an important policy priority in developing countries is to reform the policies that divide the informal and formal sectors, so as to enable the poor to participate in markets and to engage in higher value added business activities \hyperref[b4]{(Ayyagari, Beck and Demirgüc-Kunt, 2003)}.\par
Policies to promote the development of MSEs are common in both developed and developing countries \hyperref[b48]{(Storey, 1994;} {\ref Levitsky, 1996;}\hyperref[b23]{Hallberg, 2000)}. In the case of developed countries, it has become commonplace for governments during the last two or three decades to implement policies or programs designed to promote aspects of micro and small-sized enterprises (MSEs). This has coincided with an increase in the importance, in terms of contribution to employment and GDP growth, of SMEs in most of the developed economies \hyperref[b48]{(Storey, 1994)}. In the case of developing economies, policies designed to assist MSEs have been an important aspect of industrial policy and multilateral aid programs such as those of the United Nations since the 1950s (Levitsky, 1996). However, while there are wide variations across countries the traditional picture is one where the relative importance of SMEs tends to decline as a country moves up the developmental ladder \hyperref[b23]{(Hallberg, 2000;} {\ref and Liedholm and Meade, 1999)}.\par
In addition, they also comprise a significant proportion of the business enterprises. It may therefore be argued that, purely from the viewpoint of their significance in their economies, MSEs warrant attention from governments. \hyperref[b48]{Storey (1994)} has argued, in the UK context, that the increased importance of MSEs means that public policies towards them cannot be considered in isolation from other influences in the economy and cannot be left to those with a particular interest in MSEs. The significance of SMEs in their economies makes it important for policymakers to ensure that these enterprises do not face impediment that hamper their ability to operate efficiently and do not face tedious administrative compliance costs. As Lattimore et al. (1998) note, while economic importance provides a strong basis for public policy consultation with small business, in itself it provides little justification for specific interventions.\par
Despite a long history of development efforts, MSEs were perceived rather as a synthetic construction mainly of "social and political" importance \hyperref[b23]{(Hallberg, 2000)}, especially throughout the 1980's and up to late 1990's. Although domestic MSEs constituted most of what could be and what are still deemed as the private business activity in most developing countries, private sector development strategies advocated for and implemented in these countries were skewed towards the needs of large-scale business, including foreign invested ones. This type of policy advice was partly motivated by the rather disappointing (Meyer-Stamer, Jörg and Frank Waltering, 2000) results achieved through extensive MSE support systems operated in developed countries since the 1970's.\par
While contributions of MSEs were recognize, many programs and policies were developed to support them, their journey in many instances is short-lived with high rate of failure mostly in Africa due to several factors \hyperref[b38]{(Michael and Jeffrey, 2009;}\hyperref[b34]{Lussier, 1996;} {\ref Honjo,2000;} {\ref ILO,2007;} {\ref Wiboonchutikula, 2001;}\hyperref[b55]{Zewde and Associates, 2002)}.There are many obstacles hindering their growth like competitions, lack of access to credit, cheap imports, insecurity, debt collection, marketing problems, lack of enough working space, identical products in the same market, change in demand and absence of market linkages, lack of raw material accessibilities  {\ref (Wiboonchutikula,2001)}.\par
Okpara \& Wynn (2007) research on smallbusiness development has shown that the rate of failure of MSEs in development countries is higher than the developed world. According to Geberhiwot and Wolday, (2006) more than 11,000 MSEs were surveyed and about 5 percent of them admitted having main constraints like lack of working space for production and marketing, shortage of credit and finance, regulatory problems (licensing, organizing, illegal business), poor production techniques, input access constraints, lack of information, inadequate management and business skill, absence of appropriate strategy, lack of skilled human resource, low level of awareness of MSEs' as job area, low level of provision and interest for trainings and workshop. These constraints confirm with other developing countries, especially poor management, corruption, lack of training and experience, poor infrastructural development, insufficient profits and low demand for product and services.\par
Shiffer and Weder (2001) clearly show that there are size-based policy biases against MSEs, and more so against smaller firms in the microeconomic environment. These biases cover all areas: legal and regulatory frameworks, governance issues, such as bureaucracy and corruption, access to finance and property rights. Governmental interventions on all fronts are required. The existence of such biases point out to either market or government failure and is closely related to the capacity of the stakeholders involved. At times, markets may correct these failures. However, in some cases, removal of failures in the business environment may require adopting structuralist (selective intervention) approaches rather than market-friendly approaches, as market forces may not be sufficient to remedy the capacity deficits in the system. The choices made will be political, but they should be based on sound analyses \hyperref[b32]{(Lall, 2001)}.\par
Even though in the past decades the focus of Ethiopian government was mainly on large organizations, particularly on manufacturing sector, the recent wave of private sector development initiatives however shifted the policy efforts to MSEs and SMEs. This new orientation has been possible because of poor performance in most state owed companies and the tension introduced by globalization and the increased need for competiveness \hyperref[b55]{(Zewde \& Associates, 2002;}\hyperref[b24]{Hamilton and Fox, 1998)}. Thus, the health of micro and small business sectors is very important for the overall economic growth potential and future strength of an economy since they utilize local resources, satisfying vital needs of large segment of the population with their products and services, serve as sprees of technological, marketing and management capacity and skill acquisition, and enable technological process via adoption technology  {\ref (FeMSEDA, 2004)}.\par
The south west region is endowed with ample natural resource. MSEs make productive use of resources and improved the efficiency of domestic markets, thus facilitating long-term economic growth. MSEs also seem to have advantages over other largescale competitors in that they are able to adapt more easily to market conditions and utilize the ample resources. The sector has the potential to contribute towards creating employment opportunities and reducing poverty. However, even if ample resource is available in the region they have not performed creditably well and hence have not played the expected vital role in the economic growth and development of the country. This situation has been of great concern to the government, citizenry, operators, practitioners and the organized private sector groups.\par
Therefore, the basis for this study is that the government formulated some policies, and established many institutions to promote the smooth functioning of SMEs. However, the sector is not performing up to the expectations of many stakeholders as it has been suffering from several problems. Therefore, the study aims at identifying the impact of the varied problems on the performance of MSEs in Bonga, Mizan-Aman, and Teppi Towns. 
\section[{II.}]{II.} 
\section[{Materials and Methods}]{Materials and Methods} 
\section[{a) Research Design}]{a) Research Design}\par
According to Mark et al. (2009:101) mixing qualitative and quantitative approaches gives the potential to cover each method's weaknesses with strengths from the other method. In this study, a combination of qualitative and quantitative approaches of doing research was employed, which has been practiced, as recommended by  {\ref Creswell (2009:203-216)}. 
\section[{b) Data Collection}]{b) Data Collection}\par
The study employed both primary and secondary sources of data collection. 
\section[{c) Target Population}]{c) Target Population}\par
In this study the target populations is all MSEs operating within three twons (Mizan-Aman, Bonga and Tepi). According to Federal Micro \& Small Development Agency of Ethiopia there are 973 MSEs operating within Mizan-Aman, Bonga and Tepi (FMSAE, 2014). The study targets those enterprises within the three towns because the towns have a concentration of various MSE types and can thus be representative of most enterprise sectors in Benchi-Maji, Kaffa and Sheka zones. 
\section[{d) Sample Size Determination}]{d) Sample Size Determination}\par
As to the sample size determination, from among different methods, the one which has developed by  {\ref Carvalho(1984)},ac cited by Zelalem(2005) was used. The method is presented in table below. So, according to the above table, 278 sample size was determined for this particular study. 
\section[{III. Data Presentation, Analysis and}]{III. Data Presentation, Analysis and}\par
Discussion of Results 
\section[{a) Pearson Correlation Analysis}]{a) Pearson Correlation Analysis}\par
This research is investigating the strength of relationships between the studied variables. The study employs the Pearson correlation which "measures the linear association between two metric variables"  {\ref (Hair et al., 2008)}. The Pearson correlations were calculated as measures of relationships between the independent variables and dependent variables. This test gives an indication of both directions, positive (when one variable increases and so does the other one), or negative (when one variable increases and the other one decreases \hyperref[b43]{(Pallant, 2010)}. The test also indicates the strength of a relationship between variables by a value that can range from --1.00 to 1.00; when 0 indicates no relationship, -1.00 indicates a negative correlation, and 1.00 indicates a perfect positive correlation \hyperref[b43]{(Pallant, 2010)}. For the rest of the values is used the following guideline:-\par
? small correlation for value 0.1 to 0.29 ? medium correlation for 0.3 to 0.49 ? Large correlation for 0.50 to 1.0 \hyperref[b43]{(Pallant, 2010)}.\par
Like the demographic factors, the scale typed questionnaire entered to the SPSS software version16.00, to process correlation analysis. Based on the questionnaire which was filled by the SME members, the following correlation analysis was made. As one can observe from the correlation fig 4.1 in the above, the values of correlation are also used for checking multicollinearity. The correlation between each of the independent variables is not too high, meaning that the correlation is not above value 0.5. It can be concluded that in this study there is no problem with multicollinearity. The strongest relationship between the independent variables is 0.497 between politics, entrepreneurial and marketing. 
\section[{Global}]{Global}\par
The Pearson correlations between independent variables management factor, social, marketing factors, infrastructural factor, political, financial factor, technological factor, land availability and the dependent variable SMEs performance are depicted in Figure  {\ref 4}.1 above. 
\section[{? Correlation Analysis between Political factor and SMEs performance}]{? Correlation Analysis between Political factor and SMEs performance}\par
Pearson correlation test was conducted to see the degree of relationship between the independent variable i.e. political factor and SMEs performance. The results of the correlation between these variables are shown in figure  {\ref 4} The values of correlation are also used for checking multicollinearity. The correlation between each of the independent variables is not too high, meaning that the correlation is not above value 0.5. It can be concluded that in this study is no problem with multicollinearity.\par
i 
\section[{. Regression Analysis of the Manufacturing sector and SMEs performance}]{. Regression Analysis of the Manufacturing sector and SMEs performance}\par
The model summary in table  {\ref 4}.1 presents how much of the variance in the dependent variable is explained by the model. The multiple coefficient of determination denoted as R square is 0.695. The value of the R square indicates that 69.5 percent of variance in the dependent variable was explained by the model. By looking at the Sig.-value in table 4.1, it is possible to interpret whether the particular independent variable has a significant relationship with the dependent variable. The relationship is significant if the Sig. value is not larger than 0.05. The results show that there is a significant relationship for political (0.000), social (0.002), land available (0.001), Technological factor (0.003), Infrastructural factor (0.002), Marketing factors (0.002), Financial factor (0.003) and Management factor (000). This means that the variables are good predictors of the dependent variable. The multiple regression result table 4.1 indicates that, all the internal and external factors that used in this study have positive and significant influence on the explained variable. The value of (?= .640, .285, .716, .530, .844, .383, .508, and 0.174) for political, social, land availability, technology, infrastructure, marketing, financial, and management factors respectively. Furthermore, the study aims to identify which of the variables contributed the most to prediction of the dependent variable. This information can be investigated via Standardized coefficient Beta in table  {\ref table} 4.1. In this study the highest Beta value is 0.844 for infrastructure factor, and second highest is 0.716 for land availability. The independent variables management factor (.174), social (.285), technology factor (.530), financial factor (.508), and political factors (.640) are also good predictors. These results indicate that the variables infrastructure factor and political factor make the strongest unique contribution in explaining the dependent variable SMEs performance . 
\section[{Regression analysis of}]{Regression analysis of}\par
These results enable to conclude that the model explains 69.50 percent of the variance in SMEs performance. The largest unique contribution is provided by the variables infrastructure factor, Land availability, and political factor. Thus, these variables represent good predictors of the dependent variable.\par
IV. 
\section[{Conclusions}]{Conclusions}\par
This research was conducted in Bench Maji, Sheka and Kefa Zone capital towns (Mizan-Aman, Tepi and Bong) respectively with the prime intent of critically assessing the factors affecting the performance of MSE operators engaged in manufacturing activities. Specifically, the study attempted to examine the internal and external factors that affect the performance of MSEs, to describe the characteristics of small enterprises operating in the study area and to recommend possible solution to alleviate the problem of MSEs. Based on the objectives and findings of the study, the following conclusions are worth drawn.\par
According to (Enock Nkonoki, 2010), the main factors/problems that limits small firm's success/growth into two groups; first is the factors that originate from within the firm (in other words they are internal to the firm) and the second group is factors that originate from outside the firm (these are external to the firm). In line with the Enock, 2010 findings, the regression result of this particular study showed, all the internal and external variables (factors) included in this particular study were statistically significant and therefore, affects the performance of SMEs in the study area was affected by both variables.\par
The finding of this research shows that, most of the MSEs operators have no efficient experience and management knowhow to perform their activities effectively and efficiently. These lead to them unsuccessful because they run their business activities without having adequate knowledge about the business environment. Lack of managerial know-how places significant constraints on SME development.\par
Regarding infrastructural facilities, most of MSEs operators had no adequate infrastructural facilities at the given study area, specially insufficient and interrupted electric power and water supply. These lead to them, unable to generate adequate profit by satisfying the needs of the customers. Infrastructural problem is not only the problem of the study area problem it is a country wide problem, therefore this problem is not solved by the MSEs operators rather than by the government of the country.\par
The result of the finding shows that majority of MSEs operators in the study area does not have enough working premises. Because of this, the MSEs operators are not perform their business related activities effectively and efficiently. And also, the location of the working premises is not suitable for attracting the new customers that means, the working premises have no access to market.\par
Regarding other external environmental factors, majority of MSEs operators activities are affected by external related problem such as technological related problems i.e. the MSEs operators are did not have the opportunity to get modernized technology at the given study area which made them unsuccessful. And the other external problem is, there was a problem of market linkage with the external parties such as vendor, suppliers and customers. Because of there was a problem of marketing linkage through external parties, most of the time the MSEs operators are kept their products in the store. It is true that, finance, working place, infrastructural, marketing factors are factors that affect the performance of MSEs, this does not mean that all factors are equally affect the performance of the business enterprises. As compared with the other factors, technological factors, lack of infrastructural facilities, shortage of working premises and shortage of finances for start-up and expansion purposes are the top most factors that affect the growth and success of MSEs activities at Bench Maji, Sheka and Kefa Zone.\par
V.  \begin{figure}[htbp]
\noindent\textbf{11} \par 
\begin{longtable}{P{0.42742857142857144\textwidth}P{0.102\textwidth}P{0.18942857142857142\textwidth}P{0.13114285714285714\textwidth}}
Population Size\tabcellsep \tabcellsep Sample Size\tabcellsep \\
\tabcellsep Low\tabcellsep Medium\tabcellsep High\\
51-90\tabcellsep 5\tabcellsep 13\tabcellsep 20\\
91-150\tabcellsep 8\tabcellsep 20\tabcellsep 32\\
151-280\tabcellsep 13\tabcellsep 32\tabcellsep 50\\
281-500\tabcellsep 20\tabcellsep 50\tabcellsep 80\\
501-1200\tabcellsep 32\tabcellsep 80\tabcellsep 125\\
1201-3200\tabcellsep 50\tabcellsep 125\tabcellsep 200\\
3021-10000\tabcellsep 80\tabcellsep 200\tabcellsep 315\\
1001-35000\tabcellsep 125\tabcellsep 315\tabcellsep 500\\
35001-15000\tabcellsep 200\tabcellsep 500\tabcellsep 800\end{longtable} \par
  {\small\itshape [Note: (Source: Zelalem, Issues and Challenges of Rural WaterScheme, 2005)    ]} 
\caption{\label{tab_0}Table 1 . 1 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{} \par 
\begin{longtable}{P{0.03688602765855985\textwidth}P{0.4454697186456843\textwidth}P{0.002026704816404387\textwidth}P{0.36561754887935144\textwidth}}
\tabcellsep \tabcellsep \tabcellsep ?\\
\tabcellsep \multicolumn{2}{l}{Political Factor and SMEs performance have moderate relationship}\\
\tabcellsep (r=0.331 with p<0.01).\tabcellsep 0.652\\
\tabcellsep \multicolumn{2}{l}{? Correlation Analysis between Infrastructural factor Social Factor and SMEs performance}\\
\tabcellsep \multicolumn{2}{l}{.367 Pearson correlation test was also conducted for}\\
\tabcellsep \multicolumn{2}{l}{these variables and the results are shown in fig 4.1}\\
\tabcellsep \multicolumn{2}{l}{Land Available above. As it is indicated in the figure, there is significant}\\
\tabcellsep \multicolumn{2}{l}{positive correlation between Infrastructural factor and 0.561 SMEs performance. In other words Infrastructural factor}\\
32 Volume XVI Issue X Version I Year ( ) Global Journal of Management and Business Research\tabcellsep \multicolumn{2}{l}{Technological Factor Infrastructural Factor Marketing Factors Financial Factor and SMEs performance are correlated in a strong .331 relationship (r=0. 889 with p<0.01). .889 .462 .411 .396 ? ? Correlation Analysis between Financial factor and .738 SMEs performance Management Factor For these variables Pearson correlation test was conducted and the results are shown in fig 4.1 above. Entrepreneurship Factor As it is shown in the table, there is significant correlation between financial factor and SMEs performance. In other words Financial factor and SMEs performance have high or moderate relationship (r=0.411with p<0.01).}\tabcellsep hand, Political factor and SMEs performance have strong relationship (r=0.652 with p<0.02). ? Correlation Analysis between Social factor and SMEs performance Pearson correlation test was also conducted for these variables and the results are shown in figure above. As it is indicated in the fig 4.1, there is significant positive correlation between Social factor and SMEs performance. In other words Social factor and SMEs performance are correlated in a moderate relationship (r=0 .367 with p<0.01). ? Correlation Analysis between Land available and SMEs performance For these variables Pearson correlation test was conducted and the results are shown in fig 4.1 above. As it is shown in the figure, there is significant correlation SMEs Performance\\
\tabcellsep \tabcellsep \tabcellsep between Land available and SMEs performance. In\\
\tabcellsep \tabcellsep \tabcellsep other words Land available and SMEs performance\\
\tabcellsep \tabcellsep \tabcellsep have high or strong relationship (r=0. 561 with p<0.03).\end{longtable} \par
  {\small\itshape [Note: A ? Correlation Analysis between technological factor and SMEs performance For these variables Pearson correlation test was conducted and the results are shown in fig 4.1 above.]} 
\caption{\label{tab_1}}\end{figure}
 			\footnote{© 2016 Global Journals Inc. (US) 1} 			\footnote{© 2016 Global Journals Inc. (US)} 			\footnote{Determinants of Micro and Small Enterprises Performance in South West Ethiopia: The Case of Manufacturing Enterprises in Bench Maji, Sheka, and Kefa Zones} 			\footnote{Determinants of Micro and Small Enterprises Performance in South West Ethiopia: The Case of Manufacturing Enterprises in Bench Maji, Sheka, and Kefa Zones This page is intentionally left blank} 		 		\backmatter   			 
\subsection[{Acknowledgements}]{Acknowledgements}\par
Our gratitude to the many individuals who have helped shape this work cannot adequately be conveyed in a few sentences. Our heartfelt thanks go to all our friends and family who directly or indirectly contributes their unlimited initiation and facilitation in the work. Unforgettable warmest appreciation also goes to our employer Mizan-Tepi University who supports in all the finances and encourage us to finish this piece of work.\par
Last but not the least, we wish to give our thanks to all managers, owners of SMEs and employees for their willingness to participate in filling the questionnaires. 			  			  				\begin{bibitemlist}{1}
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