VSRD International Journal of Accounts, Economics & Commerce Research, Vol. I Issue II December 2015 e-ISSN: © VSRD International Journals: www.vsrdjournals.com
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RESEARCH PAPER
PERFORMANCE DETERMINANTS OF MICRO AND SMALL ENTERPRISES IN ETHIOPIA : A STUDY CONDUCTED IN SODO AND BODITI TOWNS IN WOLAITA ZONE 1P.K.
Agarwal* and 2Alto Alemayehu of Management, Wolaita Sodo University, Wolaita, ETHIOPIA. *Corresponding Author’s Email ID:
[email protected] 1Professor, 2Lecturer, 1,2Department
ABSTRACT Micro and Small enterprises (MSEs) are important to economic growth and significantly essential to generate employment. Therefore, the future of the Ethiopian economy i n the urban area depends to a great degree on the success of MSEs as in many other developing countries. Ethiopian MSEs are facing a series of external and internal factors that have significant adverse effects on their growth and additionally there are challenges for them to make a greater contribution to the economy. The purpose of this research is to explicitly research and consider aspects that are hampering the performance (growth) o f MSEs in Sodo and Boditi towns of Wolaita Zone. The study was utilized causal research design to achieve the research objectives. The target population under study was 384 The study was conducted between February to June 2015. In this study, Primary and secondary data types and sources was used. The instruments to collect primary data were questionnaires and interviews. Sample size of 195 MSEs were selected to participate in this study, to determine the required sample size, stratified random sampling technique was utilized. The data collected was analyzed quantitatively and qualitatively. The major MSEs performance affecting factors were financial, marketing, working premise, infrastructural, government support and legal and internal management factors and this identified factors explained the variance of 77.7% of MSEs performance affecting factors and 22.3% of variance was did not explained by this study variables. Among six identified factors except public infrastructural factor all other factors were statistically significant and among significant factors financial constraint contribute very high impact (56.1%) on MSEs performance when other factors held constant and followed by marketing and management problems constraint. Keywords: MSEs, Performance.
1. INTRODUCTION The aim of the thesis is to focus on the external and internal factors that hampering the performance of micro and small enterprises (MSEs) in Sodo and Boditi towns of Wolaita Zone. The MSEs have an important role in the creation of jobs in the urban centers of Ethiopia. In addition, it is argued that the growth of the urban economy depends to a great extent to the success of the MSEs sector since they generate a significant contribution to poverty alleviation and employment creation. However, the current situation for the majority of MSEs in urban centers is in the low growth rate which would be attributed to a series of external and internal problems. Factors affecting the micro and small enterprises performance have been a well research area by different scholars for many years in different countries. Previous research indicates that several factors influence MSEs performance includes among many others: contextual factors, management constraints, MSEs professional background, entrepreneurship capabilities and preferences, the technology and micro environment (Olabisi, et al). Poor management and accounting practices, information asymmetries associated with lending to small scale borrowers have hampered the ability of smaller enterprises to raise finance and restricted the flow of finance to smaller enterprises. In spite of these
claims however, some studies show a large number of small enterprises fail because of non-financial reasons (Anne Ngima Kinyua, Jan.2014). Generally, the external and internal factors are significantly affecting the performance of MSEs in Ethiopia in general and Wolaita zone in particular. 2. STATEMENT OF THE PROBLEM Micro and small enterprises are integral components' in one country's economic development. Government recognized contributions in poverty reduction and employment opportunities in the urban areas. Despite its contribution, the various internal and external factors affecting their performance. Different scholars had identified the different internal and external MSEs performance affecting constraints such as, working capital shortage, market gap, information asymmetry, working place factors operators capabilities. MSEs face internal and external constraints both at start up and transition phases. In Africa, the failure rate of MSEs is 85% out of 100 enterprises due to lack of skills and access to capital (Admasu (2012). As many scholars suggested in their study, the common constraints facing MSEs in their operation are unfavorable legal and regulatory
P.K. Agarwal and Alto Alemayehu
environment, lack of sufficient finance source and collateral, lack of access to markets lack of working premises at affordable rent; in ability to acquire skills and managerial expertise; low access to appropriate technology; and poor infrastructures There is a high failure rate of MSEs Wolaita Zone due to different factors. This is a researchable gap which needs the solution. Since the scientific research aim is to provide the solution to the problem, the researcher interested to find out the major MSEs performance constraints in Sodo and Boditi towns of Wolayita zone. 3. REVIEW OF RELATED LITREATURE MSEs Performance: Performance is defined simply in terms of output terms such as quantified objectives or profitability. (Rakhma Oktavina, 2007). Performance has been the subject of extensive and increasing empirical and conceptual investigation in the small business literature. Performance of MSEs enterprises is evaluated by assessing the share of the given enterprise on the basis of job creation and growth to the next higher level (W.L Njanja, et. Al (2012), Gebrechristos & Prof. S.S. AJafri (2014). Profits and employment opportunities created are only relevant factors to measure MSEs performance over a long period of time. Sales and employment are two important MSEs performance measurement indicators. Employment is often used in the interest for policy makers While Sales are the most common measure indicator of MSEs performance (W.L. Njanja, et. al, 2012). 4. EXTERNAL AND INTERNAL MSES PERFORMANCE AFFECTING FACTORS External MSEs performance affecting factors: Businesses are affected by external macro-environments that they cannot control them, such as political, economic, social, technological, environmental and legal factors which can rarely be influenced by management decisions since they are external to the company (W L Njanja, et.al, 2012). In his study, the researcher identified six MSEs performance affecting factors and discussed as follows. (1) Government Support and Legal Factors: Micro and small enterprises face difficulties at every stage of their activities, whether it is buying materials for production, organization of production, selling products in the market or sustaining the period between production and marketing. Regarding government support, MSEs get different support from government, there is inadequacy in government support for the fact that the support is not as much as MSEs need, (Zemenu Aynadis and Mohammed Mohammednur, 2014). According to Admasu Abera (2012), various governmental bodies designed various programs aimed at developing MSEs sector. Most of the programs were not given the appropriate backing and as such the impact of the programs could not be felt in the performance and competitiveness of MSEs. This is mainly because of the fact that these programmes or policies are not effectively implemented in line with their intended objectives owing to various reasons. According to the findings, the reason ranges from lack of visible commitment of some governmental bodies to lack of regular integration between the MSEs operators and the
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concerned bodies of the government. (2) Financial factors (Inadequate finance): Most of the micro and small enterprises depend on external finance or non-institution. Financial assistance by the various agencies, like financial corporations and commercial bank, often falls much short of their requirements. According to W.L. Njanja, et. al (2012) insufficient capital or lack of financial sources is the major obstacle for MSEs and usually entrepreneurs need to utilize personal financial sources to start up their business and to expand the operations, since the internal financial sources are normally insufficient. MSEs have difficulty in growing due to insufficient collateral, high transaction costs and incapability to deal with the complexity of formal financial institutions. The financial factors which include high collateral requirement from banks and other lending institutions, shortage of working capital, high interest rate charged by banks and other lending institutions, and too complicated loan application procedures of banks and other lending institutions are mostly affect the MSEs performance (Admasu Abera,2012). (3) Public Infrastructural Factors: Access to public infrastructure comprise water, electricity, serviceable roads, telecommunication, telephones, electronic media and postal services which are all crucial for business startup, development and growth. Limited access to public infrastructure services is a major constraint to MSEs performance (Muneeb, et.al, 2012). Increasing price of transportation mainly resulted from low or inadequate supply of infrastructure and facilities and increasing fuel and spare-part prices has negatively affected the enterprises by draining MSEs revenue (Mulugeta Yohanes, 2011). (4) Marketing factors : Admasu Abera (2012), inadequate market and difficulty in Searching new market, lack of demand forecasting, and asymmetry in market information, poor customer relationship and, lack of promotion to attract potential customers are marketing constraints. Berihu, et. al (2014), in their research showed that the marketing factors are one of the major challenges that hampers the growth and development of MSEs in Ethiopia which are in terms of access to sufficient and sustainable market and includes inadequacy of market, difficulty of searching new market, lack of demand forecasting, lack of market information and absence of relationship with an organization/association that conduct marketing research were significantly affect the MSEs performance. (5) Working Premise Factors: working places are related to access to land and associated time and cost of land related transactions have been identified as one of the key constraints to growth by both the formal and informal components of the private sector. Working place factors were absence of own premises unsuitability of current working and selling place, high cost of renting houses (Admasu Abera, 2012). The working place factors affect MSEs performance, the supply of working spaces is small relative to demand (Berihu, et.al, 2014). Internal MSEs performance affecting factors
P.K. Agarwal and Alto Alemayehu
Internal constraints/factors are those constraints that affect the MSEs owner/ manger’s ability to operate efficiently, despite internal factors the skills and competencies of the individual owner/manager which are crucial to how well the business faces up to the inevitable crises that arise. Important to note about these constraints is the fact that they are controllable by the owner/manager. According to W. L Njanja (2012), internal factors within an organization reveal how management decisions and the features of an MSEs can affect on the decisions taken regarding the performance of an MSEs. Factors that are frequently considered part of the internal environment include management competences in this study. (6) Management Factors: Small business are owned by one person or small group of people and managed by their owners, who with all management usually with the other little help W. L Njanja (2012), claimed that MSEs performance is dependent on managerial knowledge. Poor division of duties and responsibility among employees, Poor organization and ineffective communication, Poor selection of associates in business, shortage of well trained and experienced employees, and lack of training facilities are main MSEs management constraints (Admasu Abera, 2012). Internal management factors are mostly affect the MSEs performance (Eshetu Bekele and Zeleke Woku, 2008), For example, in their research Eshetu and Zelke identified and explained that the poor managerial skills constitutes (54%) to MSEs failure. 5. OBJECTIVES OF THE STUDY The main objective of the study is to investigate the internal and external factors that are mostly affecting the performance of MSEs in Sodo and Boditi towns of Wolaita Zone. The specific objectives are: To examine the sources of finance and other source of finance related challenges that affects the performance of MSEs in the Sodo and Boditi towns of Wolaita Zone. To assess the internal obstacles that are hindering the performance of MSEs in Sodo and Boditi towns of Wolaita Zone To examine the major external obstacles which are hampering the MSEs performance in Sodo and Boditi towns of Wolaita Zone. 6. RESEARCH HYPOTHESIS H1 Financial factors have a significant impact on the performance of MSEs in Sodo and Boditi towns of Wolaita Zone. H2 Marketing Factors has a significant impact on the performance of MSEs financial factors in Sodo and Boditi towns of Wolaita Zone. H3 Working place factors has a significant impact on the performance of MSEs in Sodo and Boditi towns of Wolaita Zone H4 Public Infrastructure has a significant impact on the performance of MSEs in Sodo and Boditi towns of Wolaita Zone. H5 Government support and legal factors has a significant impact on the performance of MSEs in
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Sodo and Boditi towns of Wolaita Zone H6 Internal management factors has a significant impact on the performance of MSEs in Sodo and Boditi towns of Wolaita Zone 7. RESEARCH METHODOLOGIES The types of research design employed under this study were causal. Then this study describes, Correlate and predicts the effect of internal and external factor influence on the MSEs performance in Sodo and Boditi towns of Wolita zone. Sampling Procedure: As a study area for this research Sodo and Boditi towns from Wolayita zone were purposely chosen. This is b/c (1) MSEs strategy focuses urban areas; (2) the failure rate is high in two towns when compared with other wolaita zone towns and (3) nearness to collect data in short time. Target Population: The target population of this study was 384 (Sodo 307 and Boditi 77) which consists 134 from manufacturing sector 171, from construction sector and 79 from urban agriculture sector. Sampling Design: Among probability sampling techniques, Stratified random s a m p l i n g technique was utilized. Researcher first selected Sodo and Boditi towns by using purposive sampling. Manufacturing, construction and urban agriculture sectors were selected by using stratified random sampling technique and 195 participants selected from three sectors. Sample Size: This study applied a simplified formula provided by Yamane (1967) in order to determine the required sample size at 95% confidence level with the precision level of 5%, Hence, the sample size(n) =196 and total population(N) =384. Data Collection and Collection Instruments: Primary data and secondary were collected to this study. Five point liket scale questionnaires were designed and used to examine how strongly participants agree or disagree with the statements on a five point scale. Primary data collected from 161 MSEs operators and 15 interviewees' and Secondary data was taken from Wolaita Zone, Sodo town and Boditi town trade and industry sectors annual reports and policy manuals. Data Processing and Analysis: Collected Data edited, coded, c l a s s i f i e d , analyzed and presented to meet the research objective. 8. FINDINGS AND DATA ANALYSIS Questionnaire Return Rate: One hundred seventy five (175) questionnaires were distributed across the three sectors in two towns and out of them 161 were completed and collected successfully which representing 92 % response rate. Out of the 175 questionnaires administered, 61, 78 and 36 were distributed to manufacturing sector, construction sector and urban agriculture sectors respectively. The numbers of questionnaires retrieved from manufacturing sector, construction sector and urban
P.K. Agarwal and Alto Alemayehu
agriculture sector are 58, 71 and 32 respectively. This represents a response rate of 95%, 91% and 89 % for manufacturing, construction and urban agriculture respectively. Categories of Micro and small enterprise: The sample frames were operating in three sectors of the MSEs. 44% of micro and small enterprises were engaged in construction, 36% were engaged in manufacturing and
No 1 2 3 4 5 6 7 8
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20% were engaged in urban agriculture sector. This category division of MSEs by three sectors was believed to be helpful to study each sector critical factors that affect the performance of MSEs. This is because MSEs in different sectors face different types of problems. That means the degree of those critical factors in manufacturing sector may vary from the factors that are critical to construction and urban agriculture sectors
Table1: Source of Capital of the Business Source of start-up Capital Frequencies Percent Valid Percent Personal saving 67 41.61 41.61 Family 29 18.01 18.01 Micro finance institutions 30 18.64 18.64 Bank 5 3.10 3.10 Idir/Iqubi 8 4.98 4.98 Friends/relatives 11 6.83 6.83 NGOs 6 3.73 3.73 Others 5 3.10 3.10 Total 161 100 100
Cumulative Percent 41.61 59.62 78.26 81.36 86.34 93.17 96.9 100 Source the field survey, 2015
MSEs major start-up capital source are personal saving which constitutes 41.61% and are the most commonly used sources, and followed by micro finance institutions which constitutes 18.64% of MSEs start-up finance sources and followed by, family which constitutes 18.01% of start-up fund and followed by friends/relatives which constitutes 6.83% of MSEs finance source. This truth demonstrates that the main source of finance for MSEs in study area (Sodo and Boditi towns) are personal saving, micro finance institutions and family because of this three finance sources jointly constitutes 78.26% .The remaining finance sources constitutes only 21.74%.generally as shown in the table 1 informal finance sources play the vital role in establishment of MSEs. 9. MORE THAN ONE SOURCES OF FINANCE THE MSES USED The most micro and small enterprises uses more than one finance sources as their business finance source because single source is not enough in generating sufficient initial capital. As shown in the figure above,50 % of MSEs jointly used personal saving and micro finance institution to start their business and followed by family and friends which constitutes 16% and followed by family and micro finances which constitutes,11%. Other remaining combined finance sources constitutes, NGO and family (7%) Idir/Iqubi and family (5%), personal saving and bank (4%),others (4%) and Idir/Iqubi and MFI(3%).Interview
conducted with MSEs operators shows that majority of MSEs uses more than one finance sources as their start-up capital. This shows that the single finance source is merely generate the needed start-up capital. Sufficiency of Borrowed Finance: 44% of respondents response shows that their current working capital is not sufficient,42% of MSEs current working capital is medium(moderate),11% of MSEs current working capital is very low and only 3% and 0% of MSEs respond that their current working capital is enough and more than enough. This tells that the enterprises who currently operating in Sodo and Boditi towns of Wolaita Zone are faced working capital shortage for example in the above figure, the respondents response clearly suggest that 55% of MSEs faced working capital shortage. Challenges facing MSEs due to finance shortage: Shortage of MSEs working capita resulted problems in their operation. challenges of working fund shortages are limited further expansion which constitutes 45% and followed by MSEs sales or profit reduction which constitutes 25% and followed by reduction of product variety which can been produced constitutes 26% and finally this working capital shortage make 4% of MSEs to loss their credit repayment capacity and ability. Internal Management Constraint:
Table 2: Effect of management factors on MSEs performance Items Mean Lack of clear work and duty division among group members 3.03 Poor association and inefficient communication among group members 3.10 Inefficient group members selection of group members 3.09 Lack of well trained and experienced group member 3.20 Lack of low cost training 3.71 Conflict within group members 3.29 Grand mean/standard deviation 3.237
Standard Deviation 1.051 1.020 1.021 1.055 1.045 .979 1.0285
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Source the field survey, 2015 As shown in table 2, above, the mean score of 3.71 with standard deviation of 1.045 clearly showed that the lack of effective and low cost training constraint is major internal management constraint. According to the respondent’s average response, Conflict within group members and lack of well trained and experienced group member are another moderate enterprises performance hampering internal management factor which shows the mean score of 3.29 and 3.20 with standard deviation of 1.055 and 1.045 respectively. As shown in the above table regarding the Poor association and inefficient communication among group members, inefficient group members selection and lack of clear work and duty division among group
members respondents are unwilling to decide on it because their mean scores are clearly indicates this truth, 3.10, 3.09 and 3.03 with the standard deviation of 1.020, 1.021 and 1.051 respectively. This shows the most respondent are neither ‘agree’ nor ‘disagree’ with the issue of Poor association and inefficient communication among group members, inefficient group members selection of group members and lack of clear work and duty division among group members. The mean scores and standard deviations clearly show that they are almost undecided. External MSEs Performance Affecting Factors:
Table 3: Effect of Financial Factors on Performance of MSEs Item Mean Standard Deviation Shortage of credit institutions. 3.54 .915 Loan application procedures of banks and other lending institutions are too complicated. 3.71 .892 Shortage of working capital 3.86 .952 High collateral requirement from banks and other lending institutions 3.74 .779 High interest rate charged by lending institutions 3.39 .930 Poor accounting practice to keep various expenses and revenue 3.18 1.095 Grand mean/standard deviation 3.57 .927 Source: Field data 2015 As discussed in the first section in source of finance the adequacy of working capital is critical factor as showed in the above table 3, which shows the mean scores of 3.86 standard deviation of 0. 952. High collateral requirement from banks and other lending institutions, complicated loan application procedures of banks and other lending institutions and lack of credit institutions are also major MSEs performance affecting constraints which shows the mean score of 3.74, 3.71 and 3.54 with the standard deviation of 0.779, 0.892 and 0.915 respectively. Interest
rate charged by banks and other lending institutions are moderately affecting the enterprises performance .Its mean score is 3.39 with the standard deviation of 0.930 and the Poor accounting practice of MSEs to keep various expenses and revenue is poorly m affecting enterprises performance and its mean score is 3.18 with the standard deviation of 1.095. Marketing Factors:
Table 4: Effects of Marketing Factors on MSEs Performance Factors Mean Standard deviation Inadequate market for my product. 3.96 .880 Lack of Market information to predict the future product demand 3.60 .832 low customer demand for my product 3.40 .824 Shortage of required input availability 3.71 .786 Lack of advertising to attract potential customers 3.39 .995 Poor customer relationship and handling 3.35 .944 Competition from other similar enterprises 3.76 .914 Fail in product price and rise in input cost 3.58 .920 Grand mean/standard deviation 3.594 .887 Source: The field data, 2015 As indicated in the above table, under marketing factors, inadequate market for MSEs product is major MSEs performance affecting problem with having mean score and standard deviation of 3.96 and 0.88. Second to inadequate market, competition from other similar enterprises is another MSEs Performance hampering constraint with mean score and standard deviation of 3.76 and 0.914. Shortage of required row materials is also affects the MSEs performance in Sodo and Boditi towns and its mean score and standard deviations are 3.71 and
0.786. Lack of Market information to predict the future product demand and Fail in product price and rise in input cost are also affecting the MSEs performance in the study area. As shown in the above table the of lack of market information to future demand prediction and product price and input cost fluctuations are scores mean of 3.60 and 3.58 and standard deviation of 0.832 and 0.920 respectively. Low customer demand for my product, lack of advertising to attract potential customers and Poor customer relationship and handling are loosely affecting
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the performance of MSEs compared to other marketing related constraints in Sodo and Boditi towns and their mean scores are 3.40,3.39 and 3.35 with the standard deviation of 0.824,0.995 and 0.944 respectively. In an interview conducted with an operator of the sectors, indicated that getting market opportunity is basic problem
but currently the government gives great market opportunities to micro and small enterprises to motivate them to further development stages. Working Premise Factors:
Table 5: Impact of Working Premise Factors on MSEs performance Factors Mean Standard Deviation Absence of own working and selling place. 4.23 .853 Current working /selling place is not suitable. 3.88 .876 The rent which paid too working/selling house is too high. 3.23 .937 Improper procedure in transferring working and selling places to enterprises. 3.27 .934 Grand mean/standard deviation 3.65 .90 Source: Field data, 2015 As indicated in the above table, Absence of own working and selling place(working premises) is a major MSEs performance affecting problem with having mean score and standard deviation of 4.23 and 0.853. Place where in which not suitable to MSEs Currently to work or sell the products is affecting MSEs performance with mean score and standard deviation of 3.88 and 0.876. Indicated in the above table, the mean scores of improper procedure in
transferring working and selling places to enterprises and the high rent amount of money paid to working/selling house are 3.27 and 3.23 with standard deviation of 0.934 and 0.937 respectively and they are poorly affecting the performance of MSEs in Sodo and Boditi towns of Wolaita Zone. Public Infrastructure Factors:
Table 6: Effect of Public Infrastructural Factors on MSES Performance Item Mean Standard deviation Frequent electric Power interruptions 4.17 1.001 Insufficient and interrupted water supply 3.83 .976 Lack of road access to market linkage 3.30 .936 Not have sufficient and quick transportation service 3.24 .925 Lack of appropriate dry waste disposal system 3.28 .943 Grand mean/standard deviation 3.564 .9562 Source: Field data, 2015 As indicated in the above table, Frequent electric Power interruptions is a critical constraint which affecting the MSEs performance in the study area. The mean score and standard deviation of electric power interruption are 4.12 and 1.001 respectively it clearly shows that this constraint major constraint in affecting MSEs performance.
Insufficient and interrupted water supply is also affects MSEs performance with mean score of 3.83 and standard deviation of 0.976 respectively Government Support and Legal Issues:
Table 7: Effects of Government Support and Legal on MSEs Performance Item Factors Lack of appropriate government support in terms of technology transfer, training, creating market linkage, credit facility, working place facility, constancy service from government bodies. Inconsistency in policy and regulations Unreasonable amount of tax levied on my business. Bureaucracy in registration process and licensing Insufficient government reward system Unwanted Political intervention Grand mean/standard deviation
As indicated in the above table, under government support given to MSEs and legal issues, lack of appropriate government support in terms of technology transfer, training, creating market linkage, credit facility, working place facility, constancy service from government
Mean
Standard deviation
3.94
.940
3.63 .857 3.48 .929 3.37 .921 3.56 .843 2.85 1.020 3.47 .9183 Source: Field data, 2015
are constrained MSEs performance as clearly indicated in the table with its mean scores of 3.94 and standard deviation 0.94. The mean scores of inconsistency in policy and regulations and insufficient government reward system are 3.63 and 3.56 with standard deviation of 0.857
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and 0.843 respectively and affecting the MSE enterprises performance in the Sodo and Bodit towns of Wolaita Zone. Unreasonable amount of tax levied on MSEs operation and bureaucracy in registration process and licensing are moderately affecting MSEs performance in the study area with the mean scores of 3.48 and 3.37 and
standard deviation of 0.929 and 0.921 respectively. Whereas there is no government bodies’ involvement or intervention in MSEs operation as indicated in the above table in its mean score 2.85 and standard deviation 1.020. Comparison of Mean Values and Dispersion:
Table 8: Comparisons Means and Standard Deviation Internal and External MSEs per Fitemce Affecting Factors
Grand Mean
Grand Deviation
Access to Working place Marketing factors Financial factors Access to public infrastructure Government support and legal issues Internal Management factors
3.65 3.594 3.57 3.564 3.47 3.237
.90 .887 .927 .9562 .9183 1.0285
All external and internal factors have a great impact on MSEs performance. this does not necessarily mean that all factors have equal impact .As shown in the table 4.9 access to working factor is the first factor which affecting MSEs performance and followed by access to market, access to finance and access to public infrastructure which are significantly affecting MSEs performance whereas
Rank of MSEs Performance Affecting Factors 1st 2nd 3rd 4th 5th 6th Source: The Field data, 2015
government support and legal issues and managerial capabilities affect MSEs performance moderately. Apart from calculated means and standard deviation, the researcher also tried to interpret the extent of effect of each factors by correlation coefficients and beta coefficients to know the extent of each factors.
Pearson's Product Moment Correlation Coefficient Table 9: The Relationship between MSEs Performance and Affecting Factors and Factors Factor Each Other
Performance Financial factors Marketing Working premise Infrastructural Gov.t support & legal Managerial
Correlation P. value Correlation P. value Correlation P. value Correlation P. value Correlation P. value Correlation P. value Correlation P. value
Performance
Financial
Marketing
Working
Infrastructural
1
.789** .000 1
.736** .000 .630** .000 1
.683** .000 .549** .000 .721** .000 1
.583** .000 .561** .000 .535** .000 .594** .000 1
.789** .000 .736** .000 .683** .000 .583** .000 .469** .000 .558** .000
.630** .000 .549** .000 .561** .000 .497** .000 .371** .000
.721** .000 .535** .000 .535** .000 .497** .000
.594** .000 .459** .000 .435** .000
.400** .000 .335** .000
Govt. Support and Legal .469** .000 .497** .000 .535** .000 .459** .000 .400** .000 1 .513** .000
Management .558** .000 .371** .000 .497** .000 .435** .000 .335** .000 .513** .000 1
Source: the field data (2015) **. Correlation is significant at the 0.01 level (2-tailed) The above table .9 provides a matrix of the correlation coefficients for the dependent and independent variables (correlation direction, strength and significance). Each variable is perfectly correlated with itself and so correlation = 1 along the diagonal of the table. The findings indicate that financial factors was significantly associated with MSEs performance (r =0.789, P
