Determinants of Women Entrepreneurs’ Performance in Ethiopia (Evidence from Hawassa City Administration)

This study is conducted to assess the determinants of women entrepreneurs’ performance: the case of Hawassa City Administration, Ethiopia. The study employed an explanatory research design with quantitative and qualitative research approaches. The required data were collected from 278 selected women entrepreneurs by adopting a multistage sampling technique. The data collected through questionnaire were analyzed using SPSS software version 21. Inferential statistics such as correlation and multiple linear regression were applied. The data collected through key informant interview was analyzed qualitatively using narration for triangulation. The findings of the study showed that educated women had better entrepreneurship performance since they can easily use technologies and can get management experience easily. In the same way, women entrepreneurs experience to increase their profitability. Likewise, having sufficient start up capital for business, access to credit to expand an existing business, having sufficient working capital, and having had collateral to get credit are significant factors that affect women entrepreneurs’ performance. Equally, having high production capacity due to available capital, delivering a product that meets customers need with a fair price, having convenient display room and selling premises, and having good market linkages are significant factors that affect women entrepreneurs’ performance. Furthermore, having the desire for achievement, independence, wealth and having self-discovery and job satisfaction are significant determinants of women entrepreneurs’ performance. Therefore, the researcher recommends Hawassa city administration in collaboration with other NGO who were working with women should give continuous training to enable them to be more productive. Likewise, the financial institutions in the city should arrange long-term financial credit for women entrepreneurs.


Determinants of Women Entrepreneurs' Performance in Ethiopia (Evidence from Hawassa City Administration)
circumstance. The binding constraints on entrepreneurship and light manufacturing in Africa have identified. They are said to be the six binding constraints on African competitiveness in light manufacturing and include the availability, cost, and quality of inputs; access to industrial land; access to finance; trade logistics; entrepreneurial capabilities, both technical and managerial; and worker skills. These constraints vary by country, sector, and firm size. From these constraints those that are common constraints among the small firms such as MSEs are entrepreneurial skills and premises, inputs, and finance at startup and running business are the most important constraints (Dinh, 2011).

Market Factors
According to Bendixen and Migliorini (2006), the key antecedents that were found to affect the commencement and performance of women owned businesses generally are individual characteristics, organization factors, network factors and environmental factors. The increase of demand initiates the suppliers to produce more. High competition in the market affects newly developed and less capital firms. A suitable area of the enterprise has more contribution for sales and determines the size of customers(Ummah, 2012).

Institutional Factors
Prolonged organizational services consume working time of women entrepreneurs. Access adequate and affordable credit a major obstacle for many women-owned SMEs this in turn affect the resources and business of women entrepreneurs. The existence of credit service provides an opportunity of entrepreneurs to start and expand their enterprises. Publicizing clear information by service providers about the service they provide. Information strengthens the decision making ability of entrepreneurs. The imposed tax sometimes not proportional to the profit of the business this discourages women entrepreneurs either to start or continue their business (Stevenson, 2005).

Soci-demographic Factors
According to Al-Sadi and et al, (2010), increased educational opportunities for women and the level of education have led to increased productivity. Minniti and Bygrave (2003) argue that, though education is an important element of entrepreneurship, it has no direct relationship with the successful entrepreneurship; rather there are mixed results between education status and entrepreneurship ability. Formal education is not a prerequisite for becoming an entrepreneur. Available studies indicate that range of age is crucial for undertaking enterprises. In most cases, people within the age ranging from 20 -34 years are more likely to be entrepreneurs. Older age of people may have declined effects for entrepreneurship (Belwal, Al-Badi (2010). It is obvious that large family members have high consumption. In order to satisfy their need entrepreneurs having larger family size forced to devote more time in entrepreneurship activities to earn more money to satisfy their family need.

Motivational Factors
Another researcher on the same country had been conducted his study on Kitale municipality of Kenya also concluded that, women owned MSEs are experiencing low growth; even if a few small enterprises are experiencing high growth, the majority of micro enterprises are experiencing slow growth. The major factors that are affecting women MSEs growth negatively are motivation to do work (Oganchi, 2013). Need for achievement, independence, and self-reliant are the most important personality factors for business growth of women entrepreneurs and have a strong positive correlation with entrepreneurial success (Salfiya, 2012) on time decision has a great impact on business self-confident entrepreneurs can take a calculated risk and perform many actions by themselves (Hassan, 2013).

Cultural Factors
The perception of the society towards women entrepreneurs. Rigid social norms, values and attitude act as barrier in rural women entrepreneurship development (Afiya, 2012). The collaboration of the society with entrepreneurs. Social net works are crucial to the success of potential entrepreneurs (Zhen and et al, 2008). Women face additional or at least different social, cultural, educational and technological challenges than men when it comes to establishing and developing their own enterprises, and accessing economic resources (Pat and et al, 2004). Besides these, another authors on the same point described that the major factors that constrained women from business venture are mostly gender-based discrimination, and awareness about gender balanced participation in business (Afza, Hassan, & Rashid, 2010).

Entrepreneurship Theory
Entrepreneurs innovate and innovation is considered as a critical driver of economic growth in the formulation of the endogenous growth theory (Abosede & Onakoya, 2013). The critical dynamic driving force for entrepreneurship is innovation. But innovation is perceived differently in numerous theories as inventions, new combination, or inventive risk taking. Entrepreneurship theory suggests that the people and what they do determine economic development. The study of entrepreneurs as personalities scrutinizes the variables that describe their appearance, such as the psychological profile (the need for achievement, the capacity to control, tolerance of ambiguity and a tendency to take risks) or non-psychological variables (education, experience, networks, the family, etc.), and personal characteristics. Entrepreneurship is vital for economic progress as it manifests its fundamental importance in different ways: i) by identifying, assessing and exploiting business opportunities; ii) formed strata. Proportional allocation was used to compute the exact number of subjects in each location which was a correct representation from the strata. The received data was classified, summarized, coded, sorted and SPSS and excel software used in analysis. From this study, it was observed that although there is the possibility of women entrepreneurs operating business enterprises in the same capacity and magnitude as men, traditional roles and practices such as domestic commitments, low levels of education, lack of property ownership and lack of opportunity driven motive to start enterprises continues to influence the performance of women entrepreneurs negatively in terms of monthly income sales, profit margin and types of business enterprise.
According to Amanuel (2012), a research conducted in Hosanna town at Hadiya Zone on challenges and opportunities of women entrepreneurs arrived to the following findings. They include discriminatory environment of women entrepreneurs in the study area, limitation on the service delivery of financial institutions, the issue of collaterals in MFI limited access to credit, limitation of searching new market by women entrepreneurs, training gap on basic business skills, self-employment problem, management skill gap of women entrepreneurs, lack of book keeping, lack of working premise facilitation by government, shortage of infrastructure facilities, limitation on grace periods for newly launched women entrepreneurs organization are what are recommended by the researcher based on his findings.
A research conducted by Mulugeta (2010) in Dessie town at Amahara Region, on factors affecting the performance of women entrepreneurs in MSEs identified that limitation of economy, social /cultural and legal/ bottlenecks, administrative bottlenecks, limited agents to support women entrepreneurs financially and lack of experience sharing are the main findings of his research.
According to Eshetu (2008) in his book of 'Women Entrepreneurship in Micro, Small and Medium Enterprises' describes women depend on MSMEs as a source of livelihood essentially because national governments fail to meet their requirements for survival and entrepreneurial aspiration. They have actively engaged and earn their livelihood in small enterprisers where government policies, regulations, owner's business skills, availability of finance, appropriate business trainings, and market matter most for their survival. Even though women entrepreneurs in Ethiopia start a number of new businesses, they find it harder to grow their business to the next higher level. Survival of a business firm is defined as the ability of the firm to continue its operation and remain in business during a certain period of time in a competitive market.

Conceptual Framework of the Study
As it is reviewed in the review of related literature section, the linkage between selected independent variables and performance of women entrepreneurs are presented іn Figure 2.1. The conceptual framework constructed by modifying different literatures to suit the purpose of this study.   Manufacturing  34  71  36  27  32  33  29  21  Construction  28  70  100  32  31  27  32  25  Trade  76  44  235  69  80  81  74  51  Service  89  76  33  93  97  62  71  20  Total  227  261  404  221  241  203  206 117 Source: Trade and industry office (2018) 3.6. Sampling Technique and Sample Size As per the report of Hawassa City trade and industry office (2018), about 906 women entrepreneurs which are found to be functional and have more than two years of work experience in selected sub-cities. Therefore, this data were used as a benchmark to calculate the sample size. Accordingly, the representative sample size was determined by using the formula developed by Yamane (1967)  Therefore, 278 women entrepreneurs were determined as the total sample size of the study. In order to select the individual respondents, a multistage sampling procedure were applied. The stage wise sampling technique has been provided hereunder.
In the first stage of sampling, three sub cities such as Meneharia, Haikdar and Tabor were selected purposively from eight sub-cities since maximum number of registered and experienced women entrepreneurs found in these sub cities. In the second stage of sampling, among 1200 women entrepreneurs which were registered in the above sample sub-cities, 906 functional women entrepreneurs were identified and selected purposively based on the functionality of the enterprise. In the third stage of sampling, proportional number of women entrepreneurs were selected from each types of business based on proportional stratified sampling technique (see Table 3.2). Nk=the population size of k th strata. N=the total population size. n=the total sample size. In the fourth stage of sampling, an individual respondent in each sample enterprise were selected using systematic random sampling technique to ensure that there is no over or under representation in the sample as it is in the sampling frame (Bhattacherjee, 2012). In systematic random sampling, the respondents were selected from the list of women entrepreneurs by k th interval (k=Ni/ni). Accordingly, if the first individual (i) would be selected  Vol.11, No.22, 2019 26 randomly from between 1 and k, and the next member would be (i+k) th , then (i+2k) th , and follows for each types of enterprise in the same fashion until 278 respondents was achieved .

Data Collection Tools
The study employed different data collection tools. Questionnaire and key informant interview were employed to collect quantitative data and key informant interview were employed for collecting qualitative data.

Inferential Analysis 4.4.1. Correlation Analysis
The correlation coefficients value range from -1 (a perfect negative relationship) to +1 (a perfect positive relationship) or a direct relationship between two variables. A value of 0 indicates no linear relationship between two variables (Kothari, 2004). In order to identify their individual relation with the dependent variable, the independent variables were analyzed one by one using correlation analysis. Therefore, independent variables such as age, family size, business experience, economic factors, institutional factors, marketing factors, motivation factors, and cultural factors were tested their degree of relationship with women entrepreneurs performance before conducting the regression analysis. To know the strength and type of correlation between variables, the following table set as a rule of thumb for discussion of variables. -.229** -.317** .522** .818** .266** .739** .507** .545** 1 Source: Own survey data, 2018 **Correlation is significant at the 0.01 level (2-tailed) *. Correlation is significant at the 0.05 level (2-tailed).
As Table 4.8 presents, age has negative and statistically significant association with women entrepreneurs' performance (r = -0.229, p<0.01). As well, family size has negative and statistically significant relationship with women entrepreneurs' performance (r = -0.317, p<0.01). Similarly, business experience has positive and statistically significant relationship with women entrepreneurs' performance (r = 0.522, p<0.01). Also, economic factors have positive and statistically significant relationship with women entrepreneurs' performance (r =0.818 p<0.01). Correspondingly, institutional factors have positive and statistically significant relationship with women entrepreneurs' performance (r =0.266, p<0.01). Additionally, marketing factors have positive and statistically significant relationship with women entrepreneurs' performance (r = 0.739, p<0.01). Furthermore, motivation factors have positive and statistically significant relationship with women entrepreneurs' performance (r = 0.507, p<0.01). Lastly, cultural factors have positive and statistically significant relationship with women entrepreneurs' performance (r =0.545, p<0.01). Based on Bhattacherjee (2012) rule of thumb, the result implies that some of the independent variables have weak and moderate correlation to each other but they have weak, moderate strong and very strong relationship to the dependent variable.

Regression analysis
Since multiple linear regression analysis facilitates the evaluation of the level of effect that multiple independent variables that cause on a particular dependent variable, multiple linear regression analysis is applied. Before applying regression analysis, all the necessary assumptions were made. The result of Table 4.10 shows that the R value of the model was 0.949 which shows the highest degree of relationship between independent and dependent variables. The adjusted R 2 value of the regression model was 0. 898, indicating that 89.8% of variance in women entrepreneurs performance was accounted by socio-demographic  Vol.11, No.22, 2019 27 factors, economic factors, institutional factors, marketing factors, motivation factors and cultural factors. The remaining 10.2% of variance in women entrepreneurs' performance was accounted by other factors which were not included in this study.  Table 4.11 shows that the ANOVA table indicated that the multiple regression model itself is statistically significant or not significant. The f-ratio is used to test whether or not R 2 could have occurred by chance alone. In short, the f-ratio found in the ANOVA table measures the probability of chance departure from a straight line. On results of the output found in the ANOVA table, the model is statistically significant when socio-demographic factors, economic factors, institutional factors, marketing factors, motivation factors and cultural factors were included (F=271.973, p<0.001). Therefore, the overall equation was found to be statistically significant.

Summary of Findings
The basic purpose of this study was to identify the determinants of women entrepreneurs' performance in Hawassa city administration, Southern Nations Nationalities and Representative State, Ethiopia. A total of 278 women entrepreneurs were participated in responding the questionnaire and the collected data were analyzed using descriptive statistics such as frequency, percentage, mean and standard deviation. Furthermore, inferential statistics such as correlation and multiple linear regressions were used. Based on the information from analysis and discussion parts, the following summaries are made: • In relation to background characteristics of women entrepreneurs, the majority (82.7%) of them were found in the age group of 25-34. Additionally, half of women entrepreneurs had certificate and above. Similarly, the majority (53.6%) of them were single. Also, the majority (86.3%) of women entrepreneurs' family size was in between 1 and 5. Furthermore, their average business experience was 4.79 years and their average last year profit was 9158.27 birr. The majority (67.7%) of them start their own business to be self-employed.
• The ranges of values were presented as disagreeing if the mean score is between 1.00 and 2.60, neutral if the mean score is between 2.60 and 3.40 and agree if the mean score is above 4.20. Therefore, the interpretations of all Likert scale items such as economic factors, institutional factors, marketing factors, motivation factors, and cultural factors were presented were done based on these classifications. p<0.01), marketing factor (r = 0.739, p<0.01), motivation factor (r = 0.507, p<0.01) and cultural factors (r =0.545, p<0.01) have statistically significant relationship with women entrepreneurs' performance. The result shows that some of the independent variables have weak and moderate correlation to each other but they have weak, moderate, strong and very strong relationship to the dependent variable.
• The result of the model summary of multiple linear regression analysis indicated that the overall relationship between the dependent and independent variables is strong (R= 0.949).
• The adjusted R 2 value of the regression model was 0.898, indicating that 89.8% of variance in women entrepreneurs performance was accounted by socio-demographic, economic factors, institutional factors, marketing factors, motivation factors and cultural factors. The remaining 10.2% of variance in women entrepreneurs' performance was not accounted by socio-demographic factors, economic factors, institutional factors, marketing factors, motivation factors and cultural factors.
• The ANOVA table indicated that the multiple regression model itself is statistically significant or not significant. Accordingly, it is found that the model is statistically significant when age, education level, family size, business experience, economic factors, institutional factors, marketing factors, motivation factors and cultural factors were included (F=271.973, p<0.001). Therefore, the overall equation was found to be statistically significant.

Recommendations
In order to fill the identified gaps of women entrepreneurs' performance in the study area, the following recommendations are forwarded based on major findings and conclusion.
• It is found that leaving the to total household responsibility to women enterprenuers decrease their performance. Therefore, the household members should support women entrepreneurs by sharing the home responsibilities of women's to devote all their efforts in the business, also women's should have to share their responsibilities to others. • Education level is found to be a significant factor for women entrepreneurs' performance. So that the administration government should design the formal mode of education for women who did not attend formal education to enable them at least to read and write; thereby grasping coffee marketing members' knowledge and get an access to different advanced market communication media. • Experienced women entrepreneurs were benefited to sell more of their product. Therefore, the Hawassa city administration in collaboration with other stakeholders should give training to enable them to be more productive. In addition, they should facilitate the women entrepreneurs' to have knowledge share program among each other. • Economic factors were found to be determinants of women entrepreneurs' performance. Which means it is the base for women entrepreneurs' performance. Therefore, financial institutions in the city should arrange long-term financial credit for women entrepreneurs. To increase capital and to expand the existing business the city cooperative promotion office, unions and other concerned stakeholders should involve in designing a mechanism to promote women entrepreneurs saving and to increase their profit. • Marketing is a factor that affects the performance of women entrepreneurs. Therefore, the Hawassa city administration in collaboration with trade and industry office needs to involve effectively in supporting women entrepreneurs by offering convenient display room and selling premises. To search market and to sell their product at a better price, trade and industry office should create market linkage with unions, cooperatives, government organizations and NGOs. • Motivational factors found to be a significant factor that affects the performance of women entrepreneurs. Therefore, in order to increase their profit, women entrepreneurs should have the desire for achievement, independence, wealth and self-discovery and job satisfaction.