Analysis of Performance Determinants in Micro-Enterprises. The Case of Dodola District, Oromia Region
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Sprache:Englisch
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Erscheinungsdatum
24.09.2015
Verlag
GRINSeitenzahl
90 (Printausgabe)
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1099 KB
Auflage
1. Auflage
Sprache
Englisch
EAN
9783668052703
Master's Thesis from the year 2012 in the subject Business economics - Business Management, Corporate Governance, grade: A, Hawassa University (governance and development studies), course: masters, language: English, abstract: Nowadays, the contribution of micro-enterprises in employment creation, poverty reduction and hence economic growth is getting widespread acknowledgement.
However, their performance is usually constrained by various factors.
Thus, this research is basically aimed at investigating key determinants of performance among micro-enterprise businesses in Dodola town of Oromia region.
It examines the extent to which performance of micro-enterprises is associated with characteristics of the owner and business constraints.
To this end, primary data were gathered using interview schedule from a sample of 112 micro-enterprises selected using stratified random sampling.
Besides, two Focus Group Discussions were held with fourteen randomly selected micro-entrepreneurs.
To further triangulate the data Key informant interviews were held with three MSE office heads.
Then after primary data was analyzed using both descriptive and inferential statistics.
Characteristics of the enterprises and their entrepreneurs were analyzed using percentage, mean, median and standard deviation.
On the other hand, Pearson's chi-square(x2), paired sample t-test and multinomial logistic regression were used to make inferences about the subject under investigation.
In this study, performance of micro-enterprises was measured in terms of two main indicators namely profit and employment growth.
The results of paired t-test indicated statistically significant mean difference in socio-economic status of entrepreneurs before and after starting micro-enterprise business.
The multinomial logistic regression analysis revealed that education, experience, location and access to formal credit source are significant predictors of profit growth.
However, only education was found as a significant predictor of employment growth.
Key Words: Micro-enterprise; Performance; Multinomial Logistic Regression; Performance Determinants.
However, their performance is usually constrained by various factors.
Thus, this research is basically aimed at investigating key determinants of performance among micro-enterprise businesses in Dodola town of Oromia region.
It examines the extent to which performance of micro-enterprises is associated with characteristics of the owner and business constraints.
To this end, primary data were gathered using interview schedule from a sample of 112 micro-enterprises selected using stratified random sampling.
Besides, two Focus Group Discussions were held with fourteen randomly selected micro-entrepreneurs.
To further triangulate the data Key informant interviews were held with three MSE office heads.
Then after primary data was analyzed using both descriptive and inferential statistics.
Characteristics of the enterprises and their entrepreneurs were analyzed using percentage, mean, median and standard deviation.
On the other hand, Pearson's chi-square(x2), paired sample t-test and multinomial logistic regression were used to make inferences about the subject under investigation.
In this study, performance of micro-enterprises was measured in terms of two main indicators namely profit and employment growth.
The results of paired t-test indicated statistically significant mean difference in socio-economic status of entrepreneurs before and after starting micro-enterprise business.
The multinomial logistic regression analysis revealed that education, experience, location and access to formal credit source are significant predictors of profit growth.
However, only education was found as a significant predictor of employment growth.
Key Words: Micro-enterprise; Performance; Multinomial Logistic Regression; Performance Determinants.
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