Abstract
The overall objective of this research was to examine motivational factors influencing households’ participation in micro and small enterprise in southern Ethiopia. Both quantitative and qualitative research method approaches were used and data collected from the respective sources through the questionnaires. The data was collected from 248 respondents. The collected data was analyzed by econometric and descriptive methods data analysis. From 10 variables expected to influence household's motivation to participate in MSE, five (5) variables were found to be the important factors influencing status of household’s participation in MSE in the study area. These variables include household, education, government support, loan access, and initial capital and work experiences of respondents. The education model result reveals that a positive sign and significant at 1% level of significance. Educational status of the households is determinant variable that influences participation of MSE in the area. The possible reasons are the literate people are better to manage; their capacity of accepting change makes them good analysts to participate in MSE. There is significance income difference participants and non-participants of SME. According from econometric results, loan access is determinant variable that influences the participation in the MSE in the area. It would be better for households if any concerned stakeholder gives skill development training how to manage income and saving to increase their capital to participate in SME.
Keywords
Motivation, Participation, Enterprises
1. Introduction
Economic inequality in the distribution of wealth is one of the most widely discussed and controversial issues and a daily growing concern very countries economy. Micro enterprise is believed to have a vital role in reducing poverty, creating job opportunity as well as improving economic development in developing countries like Ethiopia
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. In order to minimize the inequality and its devastating consequences in economy micro and small enterprise are significant role creating job opportunities and income generations. Micro and small enterprise can be service rendering, manufacturing, organizations, merchandise business scale, industry, agriculture and constriction
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In Ethiopia, micro and small enterprises (MSEs) play a significant role in the economy, contributing to employment generation, income generation, and poverty alleviation. The categorization of micro and small enterprises in Ethiopia is typically based on factors such as the number of employees, annual turnover, and capital investment. Microenterprises are the smallest businesses in Ethiopia, typically employing fewer than 10 people and small enterprises are slightly larger than microenterprises, which often employing between 10 to 100 people
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. However, micro and small enterprises play an energetic role in the progress of the economy of the developed nation due to the fact that it reduces the job problems by using lower capital per job, avoid extra costs for development of industrial infrastructure, reducing the risk of the investments, check imbalance between different sections of the economy and maximize the use of locally available resources
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. Micro and small enterprises (MSEs) play an important role in the economic growth in Ethiopia. SMEs/MSEs contribute to economic development in various ways: by creating employment for the rural and urban growing labor force, providing desirable sustainability and innovation. Studies suggest that the micro enterprises are probably owned by one or two family members and its paid-up capital is not more than 20,000 and small enterprises capital ranges from 20,000-500,000 Ethiopian birr
. Micro and small-scale enterprise sector has the potential to provide a livelihood for a considerably large number people and the sphere of the poor, rural and urban citizen of people in Ethiopia
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. Micro and small enterprises are major feature of the economic landscape in most developing countries
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. The micro and small enterprises is seen as the vital engine for economic development and job creation in addition to this to employment opportunities and provide necessary basic goods and service to be available at low cost the majority of low-income earners
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. In Ethiopia MSEs, create the best condition for the efficient functioning of an economy for national income development and speeding economic growth through enhanced capacity of domestics saving. Developing countries like Ethiopia are highly attached with different problems like poverty, unemployment, backward attitudes, famine, illiteracy, high population growth rate
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. But the development of micro businesses in Ethiopia is so slow and little attention was given to the development of the sector small business has played a significance role to the advancement of human society
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Most of the previous studies focused on focuses on effects of SME on household economy, but there is no study is conducted empirically on what factors motivates households’ participation in the MSEs in study area. Despite the acknowledged importance of MSEs, there has been little research into the specific motivational factors that promote or inhibit family engagement in these firms in Southern Ethiopia. Prior studies suggest that economic necessity, financial resource availability, market access, educational background, social networks, and government rules may all have a significant effect on participation. However, the relative effects of these factors and their interactions is uncertain.
Therefore, this study is going to fill the gap of previous study by adding empirically on motivational factors influencing households’ participation in micro and small enterprises in, Southern Ethiopia.
2. Literature Review
2.1. Theoretical Literature
Innovation and entrepreneurship are the major driving forces of growth and prosperity, and the core elements of national economic development policies in both developed and developing nations
. The most valuable 100 people to bring into deteriorating economy are not politicians, economists, scientists, engineers, but self-motivated, talented and forceful entrepreneurs. This indicates that poor countries need to redirect their socio-economic development policies and strategies towards this trend to achieve economic diversification; universal basic needs fulfillment and minimizes vulnerability in the current turbulent and uncertain global business environment
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Small business vitality is more prevalent in the developing economies as they constitute a significant part of the national economic productivity, they play a pivotal role in accelerating the evolutionary transition from agrarian dominated to industrial society. According to most studies, small business is more labor-intensive than the large ones and some even find that they also produce more output (value added) per unit of capital thus generate more output as well as employment for a given investment than do larger firms
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The small business sector is described as the natural home of entrepreneurship. It has to provide the ideal environment for enabling entrepreneurs to optimally exercise; they are seen as an essential spring board for growth, job creation and social progress. This sector is also seen as an important force to generate employment and more equitable income distribution change and through the combination of all of these measures, to stimulate economic development
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According to Central Statistics Authority (CSA) in 1996 up to 1997, one of the first comprehensive collections of data on micro enterprises sector was undertaken. According to this survey, there were almost 590,000 micro and 2,731 small scale industries found in the country. The Ethiopian Proclamation number 124 of 1977 has an official legal definition for small scale industries. These proclamation activities such as oil mills, garment factories, shoe factories, shoe polishing, candle making, steel works, bakers, grain mills metal works breweries etc. are included under the small-scale activities
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Micro enterprises are characterized by a number of highly diversified activities, which can create job opportunity for a large segment of the population. The characteristics of the informal sector (micro enterprises) have also been described as: it is easy to enter, it is financed mainly from personal and family resources, it requires low starting capital, it uses labor-intensive techniques, and it relies on the no formal school system such as apprenticeship and on-the-job training
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, In Ethiopian context, the challenge of job generation is equivalent to achieving the objective of sustainable growth and reduction of poverty. In fact, they are inseparable and interdependent long run development goals. Thus, with the rapidly increasing population of 3% per annum, and even faster growth of youth population reaching working age, combined with population pressure on agricultural sector, the demand for micro and small-scale business enterprises are increasing from day to day. One of the efforts of job is alleviated in most countries was through industrialization and development of large-scale enterprises, which is more favorable and conducted in developed countries. For countries like Ethiopia job problem can be solved by through development of MSES which job more people per capital than large firms
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. The micro scale enterprise sector is also described as the natural home of entrepreneur ship. It has the potential to provide the ideal environment for enabling enterprisers to optimally exercise their talents and to attain their personnel and professional goals. In all successful economies’ micro scale enterprise, are seen as an essential springboard for growth, job creation and social progress. The small business sector is also seen as an important force to generate job and more equitable income distribution, activate competition, exploit niche markets, and enhance productivity and technical change and, through the combination of measures, to stimulate economic development
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2.2. Empirical Literature Review
Some studies conducted on factors affecting involvement in micro and small enterprises says that age, educational level, saving and income affect participation on MSE MSE’s are special focus of government, giving that they comprise the largest share of total enterprises and employment in the non-agricultural sectors. In recognition of the important role MSE’s have to play in generating income and creating employment opportunities and reducing poverty, the government drafted its first micro and small enterprise development strategy in 1997. According to central statistical authority (CSA) survey, there are almost 570,000 MSE’s in Ethiopia 99.4% of which are micro enterprise with fewer than ten employees, accounting for 88.2% of private sector employment
| [5] | Aregawi, H. T., & Patnaik, B. C. M. (2023). Impact of Government Intervention on Manufacturing Enterprises Innovation level, in Ethiopia. Cogent Economics and Finance, 11(1). https://doi.org/10.1080/23322039.2023.2182034 |
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. On average ME employ one and half worker (this includes the owner and perhaps one occasional helper) and earn an annual operating surplus of 1300 birr. A sole proprietor operates 82% of urban enterprises of total employment. In these urban micro enterprises, family members accounted for 60 percent. Beyond family members, apprentices constituted a large proportion of the main MSE work force
| [3] | Ali, D., Deininger, K., & Harris, A. (2015). Using National Statistics to Increase Transparency of Large Land Acquisition Evidence from Ethiopia. http://econ.worldbank.org |
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The average micro enterprise has a capital of 3528 birr, a yearly production value of 3200 birr and annual surplus of 1300 birr. Although small enterprises significantly more productive and profitable than micro enterprises, small scale industries are also very small with an average of slightly more than three employees 1834 birr in annual operating surplus capital of 38,534 birr and production value of 68,800 birr. The constraints facing MSE’s in most developing economies are similar for instance, unfavorable legal and regulatory environment and income cases discriminatory regulatory practices, lack of access to markets, finance, business information, lack of business premises at affordable rent, low ability to acquire skills and managerial experience, low access to appropriate technology and poor access to quality business infrastructure
| [3] | Ali, D., Deininger, K., & Harris, A. (2015). Using National Statistics to Increase Transparency of Large Land Acquisition Evidence from Ethiopia. http://econ.worldbank.org |
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.
2.3. The Institutional Theory
As seen from different literature households’ participation in SME is mostly use institution theory. To participate in SME the rules and regulation are very important to motivate people to join in SME is essential. There are many legal supports to support MSE to effective and efficient like as financial legitimacy challenges, certification hurdles and regulatory legitimacy, operational legitimacy and environmental concerns, loan legitimacy and loan legitimacy influence the motivation to participate in SME
,
15].
Financial policy it is financial support important to households to participate in small and micro finance enterprises important tool to minimize financial problems of the households. When government and other financial support to households to join and start business to sustain their life.
Regulatory legitimacy is control and managing the business environment is crucial to increase the efficiency of the business organization and engages members to in SME.
Government support is a support in cash or kind is very important to households to start small and micro finance enterprises. Government motivates people to start business and to minimize existing poovery rate in a given economy. Specially in developing countries people need great support from people because households have not enough capacity to manage economic challenges.
Operational legitimacy and environmental issues are the operational policy of a given business organization is very important to efficiency and motivates households participate in SME. So that financial management and policy challenge the effectiveness other business.
Loan provision legitimacy it is policy in a given business positively affect the households to participate in SME and may also affect negative effect on the motivational factor to households to members in SME and essential to control the business system.
Figure 1. Theoretical frame work modified from Thakur, (2023).
Figure 2. The conceptual framework of the study.
3. Research Methodology
3.1. Area Description
Wolaita Sodo town of the Southern Nations, Nationalities, and Peoples’ Regional State (SNNPR), Ethiopia. Geographically, it is situated in southwestern Ethiopia about 327 kilometers to south of the national capital, Addis Ababa. The administrative zone is bordered in the north by the Soke River that separates the zone from Hadiya and Kambate zones: in the south by the Hamasa River and Lake Abbaya which separates it from Gamo and Gofa zones: in the west the by Omo River that separates it from Dawuro administrative zone and Konta special woreda: and in the east by the Bilate River which separates it from Arsi zone of Oromia regional region and Sidama zone
| [11] | Endris, E., & Kassegn, A. (2022). The role of micro, small and medium enterprises (MSMEs) to the sustainable development of sub-Saharan Africa and its challenges: a systematic review of evidence from Ethiopia. In Journal of Innovation and Entrepreneurship (Vol. 11, Issue 1). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1186/s13731-022-00221-8 |
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.
3.2. Research Design
The survey design was used in order to gather information to address the objectives of the study. The study was applied mixed research methodologies namely both quantitative and qualitative research method to collect the data from the respective sources through the questionnaires. The primary data was collected from sampled households by using a structured questionnaire.
Table 1. The selected wards name in the study area.
Serial No | Name of wards/kebele | Total number households |
1 | Bossa Kecha | 115 |
2 | Arada | 243 |
3 | Ofa Sere | 196 |
4 | Fana Womba | 189 |
5 | Waja Kero | 134 |
6 | Kokate | 141 |
7 | Mehal | 156 |
8 | Gido | 224 |
9 | Larena Gututo | 172 |
Total | | 656 |
3.3. Sample Size
To determine sample of the study, Yamane, 1967 formula was used to determine the required sample size at 95% confidence level, and level of precision= 5% (0.05).
Sample size is determined as follows: -
Hence, the formula will be as below:
Table 2. Proportional sample size for each ward.
Serial No | Name of ward | Total households) | Sample Size(n) |
1 | Gido | 224 | 85 |
2 | Arada | 189 | 71 |
3 | Fana | 243 | 92 |
Total | | 656 | 248 |
3.4. Sampling Techniques
To address the objective of the study, multi stage sampling techniques were employed. In the first stage, among the six towns in the wolaita zone, Wolaita Sodo town was purposively selected because of the largest number of MSE participants in Wolaita zone. In the second stage, from nine the study wards, three wards were selected based on number of a number of households namely Gido, Fana Womba and Arada were selected. Finally, in third stage, the sampled households were selected by simple random sampling techniques.
3.5. Method of Data Analysis
Both descriptive and econometric techniques were used to analyze the data. The data was entered into computer and analyzed using statistical software STATA. In descriptive statistics mean, standard deviation, frequency, variance, maximum and minimum were used to show that the socio-economic characteristics of the households. The econometric methods particularly, binary logistic regression method was employed to address the objective of factors influencing households’ participation involve in MSE.
The dependent variable is households’ participation in MSEs which is measured by dichotomous nature variable that takes the value of one if the household participates in MSE and otherwise, zero and different socio economic and institutional independent variables were used based on the theory and prior studies to address the desired objectives of the study.
Model Specification
the functional form of logit model can be specified as follows:
For case of explosion, we write (
1) as
The probability the given household is household’s not participation in MSEs is expressed by (
2) while the probability of household’s participation in SMEs is, 1.
Li=1n () =Zi=β0+β1X1+β2X2+……+βnXn(4)
Where Pi= is a probability being participating on SMEs, ranges from 0 to 1.
Zi=is a function of n explanatory variables (X) which is also expressed as
β0=is an intercept, β1, β2……βn are slopes of the equation in the model.
Li=is log of the odds ratio, which is not only linear in Xi but also linear in the parameters.
Xi=is vector of relevant household characteristics.
If the disturbance term (Ui) is introduced, the logit model becomes.
3.6. Definition, Measurements, and Expected Signs Variables
Dependent variable is participation in MSEs: This is the dependent variable that takes a value of 1 if the household participate in SMEs and 0 if the household do not participate in MSE.
Table 3. Summary of variable definitions, measurements, and expected signs.
Variables | List of variables | Variable type | Measurement | Expected sign |
Dependent variable | Participation in SMEs | Dummy | Measured 1 participants, 0 is non-participants | |
Age | Age of households | Continuous | Continuous | - |
Sex | Sex of households | Dummy | Male=1, female=0 | - |
Marital status | Marital status | Dummy | 1. married, 2. single 3. widowed, 4. divorced | + |
Family size | The total number of people | Continuous | Continuous | - |
Education | Educational status | Categorical | 1. primary, 2. Secondary, 3. higher school, 4. college and above | + |
Market access | Access to market | Dummy | Access=1, unless=0 | + |
Work Experiences | Work experiences in any business | Continuous | Measured in years | + |
Loan access | Access to loan | Dummy | Access=1, unless=0 | + |
Initial capital | Access to capital | Dummy | 1 good access, other wise, 0 | + |
Government support | Government support | Categorical | 1 good quality, otherwise zero | + |
4. Results and Discussions
4.1. Descriptive Analysis
In this study descriptive statistic and inferential statistics comprised of logistic regression analyses were employed to analyze the data. The survey instruments questioners, in this study developed by the researcher based on theories and review of related literatures. The factors studied include assessing socio-economic status of households in the study area. A total of 248 respondents all were responded the questionnaire.
4.1.1. Demographic Status of Households in the Study Area
The first objective of the study was the socio-economic status of the of the respondents in the study area. The socio-economic and demographic characteristics of the respondents such as sex and marital, educational status and were discussed in the study area.
Table 4. Sex of the respondents.
Sex | Frequency | Percent |
Female | 77 | 31.05 |
Male | 171 | 68.95 |
Total | 248 | 100.00 |
Source: survey result
As seen from the above
Table 4, from total 248 respondents responded the questionnaire, 31.05% were female and remained 68.95% were male in the study area. This shows that most of the respondents were male in compared to female from total population.
Table 5. Participation status in MSE and sex of respondents.
Cross tabulation Sex of respondents |
Participation status | Female | Male | Total | % |
0 | 30 | 59 | 89 | 35.89 |
1 | 47 | 112 | 159 | 64.11 |
Total | 77 | 171 | 248 | 100 |
Source: Survey result
As shown
Table 5, above from total 89 (35.89%) non- participants in MSE households, 30 were female and 59 were male households. Similarly, from total 159 (64.11%) participants in MSE households, 47 were participants females in MSE and 112 were participants male in MSE respectively. When we see this results, male households were more engage in MSE than female households in the area.
4.1.2. Socio Economic Status of Households in the Study Area
In this table below the continuous variables which included in the study were explained below table.
Table 6. Descriptive statistics of the continuous variables.
Variables | Obs | Mean | Std. Dev. | Min | Max |
Age | 248 | 38.58871 | 8.481952 | 30 | 68 |
Family size | 248 | 3.060484 | 1.169956 | 1 | 6 |
Income | 248 | 14010.14 | 6558.373 | 5000 | 50000 |
Work experiences | 248 | 1.399194 | 1.348983 | 0 | 9 |
Source: Survey result
As indicated in above
table 6, from one of the socio-economic indicator variables, the first one is age of the respondents. From the total 248 household involved in answering the survey question, the maximum age was 68 and minimum age was 30 and also the mean age of the respondent is 39 and standard deviation is 8 respectively in the area. At same time the maximum family size was 6 and the minimum family size was 1 with mean family size of 3 and standard deviation of 1 respectively. Similarly, the maxim income household get was mouthily 50,000 ETB and the minimum income was 5,000 ETB with mean income of 14010.14 and the standard deviation of 6558.373 respectively in the study area. The maximum business experience has a given households had 9 years and minim of 1 years with mean working experience of business of 1.4 and 1.3 respectively.
4.2. Econometric Estimation Results
Before estimation of the logistic regression model there was post estimation tests were conducted like multicollinearity through VIF and goodness of fit by Hosmer-Lemeshow test and Akaike criteria statistic in appendix.
4.2.1. Multicollinearity Test
The results of the logit regression model are presented in
Table 7, there is no multicollinearity problem in the data because calculated is less 10. Multicollinearity occurs between independent variable when the VIF values is greater than 10.
Table 7. Multicollinearity test result.
Variables | VIF | 1/VIF |
Sex | 1.18 | 0.8844810 |
Age | 1.27 | 0.788118 |
Family size | 1.27 | 0.79274 |
Marital status | 1.21 | 0.823845 |
Education | 1.02 | 0.977304 |
Market access | 1.18 | 0.850649 |
Loan access | 1.13 | 0.884663 |
Government support | 1.41 | 0.707164 |
Initial capital | 1.12 | 0.894188 |
Work experiences | 1.08 | 0.924093 |
Mean VIF | 1.19 | |
Source: Survey result
4.2.2. Model Characteristics
The likelihood ratio statistics shows that; the model result is significant at less than 1 percent probability level indicating that the hypothesis that the coefficient except the intercept is equal to zero is rejected. Another measure of goodness of fit used in logistic regression analysis is prediction success, which indicates the number of sample observations correctly predicted by the model.
In logistic regression models, the R-square statistic cannot be exactly computed like linear regression, so the pseudo-R-square statistic for approximation of the goodness of fit is computed, instead. Larger pseudo-R-square statistics indicate that more of the variation is explained by the model. The estimated value of chi-square is 89.53 which are significantly with 1% degrees of freedom at one percent significance level and also, we judge goodness of fit of the model Hosmer-Lemeshow test which says the model to fit the data p value should greater than a given p value of data assumption. If this assumption fit the model is adequate. In this case chis square value our null hypothesis is accepted because of p value is greater than 0.05 with chi square value of 253.14 and p value of 0.112.
Table 8. Factors Influencing Households Participation in MSE.
Participation | Odds Ratio | Std. Err. | z | P>z |
Sex | 0.9956923 | 0.38747 | -0.01 | 0.991 |
Age | 0.987264 | 0.0220023 | -0.58 | 0.565 |
Marital status | 1.289962 | 0.5489068 | 0.6 | 0.55 |
Family size | 0.7544215 | 0.1203901 | -1.77 | 0.077 |
Education | 1.58118 | 0.2897751 | 2.5 | 0.012*** |
Gov't support | 1.95205 | 0.3194192 | 4.09 | 0.000*** |
Loan access | 2.344159 | 0.8562543 | 2.33 | 0.02** |
Market access | 1.160048 | 0.4345202 | 0.4 | 0.692 |
Initial capital | 6.577346 | 2.447784 | 5.06 | 0.000*** |
Work experiences | 1.392351 | 0.2038394 | 2.26 | 0.024** |
_cons | 0.0476712 | 0.0736205 | -1.97 | 0.049 |
LR chi2(10) = 87.41, Prob > chi2 = 0.0000, Log likelihood = -118.18084, Pseudo R2 = 0.2700 |
Source: Survey result
4.3. Factors Influencing Households’ Participation in MSEs
From 10 variables expected to influence household's participation in MSE, five (5) variables were found to be the important factors influencing status of household’s participation in MSE in the study area. These variables include household education level, government support, loan access, initial startup capital and work experiences business of respondents. The rest 5 explanatory variables were found to have no significant influence on MSE participation (
Table 8).
Explanation of Significant Explanatory Variables
Household education: The model result reveals that this variable has the expected positive sign and significant at 1% significance level. As a result, education increases the probability of being participant among sample respondents increase. The possible reasons for this are the that, literate people are better to manage; their capacity of accepting change makes them good analysts to participate in MSE. The odd ratio of education greater than one indicates that, other variables remain constant; the probability of households to participate in MSE is increase by a factor of 1.578118 as the household heads become educated, with 95% confidence interval with p value of 0.012 in the study area. This study finding confirms findings of
| [18] | Kagnew Abebaw, W. (2018). Factors Affecting the Performance of Micro and Small-Scale Enterprises: Experience from North Shewa Zone, Ethiopia. Journal of Investment and Management, 7(2), 70. https://doi.org/10.11648/j.jim.20180702.14 |
[18]
.
Government support: It is found to be an important variable which affect positively households’ motivation to involve in MSE and statistically significant at less than 1% level of significance. This is because for a household having government support motivates the probability to participate in MSE was increased by odds ratio of 1.95205 with p value of 0.000 keeping other variables remain constant. This is because of when government gives different incentives in cash or kind to in engage in MSE, the chance to involve is at same time increases. The finds consistent with finding of
| [6] | Atsibha Gebreyesus, S. (2022). factors affecting the effectiveness of budget management in a case of the ministry of finance and economic cooperation of Ethiopia. IEDSR association, 7(17), 251-263. https://doi.org/10.46872/pj.476 |
[6]
.
Loan access
Loan access is positively influencing households’ motivation to involve in MSE and found to be statistically significant at less than 5%. This is because for a household who got loan access motivates the probability to participate in MSE was increased by odd ratio of 2.344159 with 95% confidence interval with p value of 0.024 by keeping other variables remain constant. From the result of the logit model indicated that sample households who had access to loan have probability of being participant is MSE is high. The higher odd ratio here shows that that the probability of being engage in MSE becomes increased when loan access increases by one unit. The finds similar with the finding of
| [22] | Mirjam Van Praag, C. (2003). Business Survival and Success of Young Small Business Owners. In Small Business Economics (Vol. 21). |
[22]
.
Initial startup capital
It is found to be an important variable which affect positively households’ motivation to involve in MSE and found to be statistically significant at less than 1% level of significance. Keeping other variables remain constant a household having initial capital to start up business increases, the probability to participate in MSE was increased by odds ratio of 6.596284 and p value of 0.000 This is higher value of odds ratio because of when household have good initial capital, they motivated to engage in MSE, due that the chance to involve in business is increases. The finds agrees with finding of
| [17] | Haque, M. F., Haque, M. A., & Shamimul Islam, M. (n.d.). Motivational Theories-A Critical Analysis. In ASA University Review (Vol. 8, Issue 1). |
[17]
.
Work experiences: It is found to be an important variable which affect positively households’ motivation to involve in MSE and found to be statistically significant at less than 5% level of significance. This is because for a household having work experiences motivate the probability to participate in MSE was increased by odds ratio of 1.392351 with p value of 0.024 keeping other variables remain constant. This is because of when has work experiences in a particular business the probability to in engage in MSE is increase. This was because of business experience they have they easily generate other business idea and get money and can do different MSE.
5. Conclusions and Policy Recommendations
Small business has played a significance role to the advancement of human society. It was largely through small business that civilization was speeded. The micro and small enterprises is seen as the vital engine for economic development and job creation.
The Primary data was collected from the sample households of 248. The collected the data was analyzed by econometric and descriptive methods data analysis. The factors that affect the motivation of households to participate in SMEs. In total of 248 households was involved in responding the questionnaire. Sodo town was purposively selected for this study because it has largest number of households who not involving MSE than other town in the area. Econometric analysis was employed particularly logistic regression model method to identify the factors motivating households to participate in MSE. The data was entered into computer and analyzed using statistical software STATA. In descriptive statistics mean, standard deviation, frequency, variance, maximum and minimum were used. Generally quantitative method of data analysis was employed. From 10 variables expected to influence household’s motivation to participate in MSE, six (6) variables were found to be the important factors influencing status of participation in MSE in the study area. These variables include household educational level, and government support, loan access, initial startup capital and work experiences of respondents. From these five variables like as educational level, and government support, loan access, initial startup capital and work experiences five variables significantly and positively affect the participation of households in SME and one variable family negatively affect the motivation to participate in SME. There is implies that there is significant income difference between SME participants and non-participants household in the study area. Government support is very critical variable which affect households to motivate participation in in SME, as result of this government would follow households by giving training on SME importance and business development. Educational status of the households is determinant variable that influences participation of MSE in the area. Any stakeholder who are responsible for MSE should know the educational level of households in the study area.
Abbreviations
MSE | Micro and Small Enterprises |
VIF | Variance Inflation Factor |
Author Contributions
Yisehak Ossa Jokka is the sole author. The author read and approved the final manuscript.
Conflicts of Interest
The author declares no conflicts of interest.
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APA Style
Jokka, Y. O. (2025). Motivational Factors Influencing Households’ Participation in Micro and Small Enterprises (MSEs) in Southern Ethiopia. International Journal of Economic Behavior and Organization, 13(3), 118-128. https://doi.org/10.11648/j.ijebo.20251303.12
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Jokka, Y. O. Motivational Factors Influencing Households’ Participation in Micro and Small Enterprises (MSEs) in Southern Ethiopia. Int. J. Econ. Behav. Organ. 2025, 13(3), 118-128. doi: 10.11648/j.ijebo.20251303.12
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Jokka YO. Motivational Factors Influencing Households’ Participation in Micro and Small Enterprises (MSEs) in Southern Ethiopia. Int J Econ Behav Organ. 2025;13(3):118-128. doi: 10.11648/j.ijebo.20251303.12
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@article{10.11648/j.ijebo.20251303.12,
author = {Yisehak Ossa Jokka},
title = {Motivational Factors Influencing Households’ Participation in Micro and Small Enterprises (MSEs) in Southern Ethiopia
},
journal = {International Journal of Economic Behavior and Organization},
volume = {13},
number = {3},
pages = {118-128},
doi = {10.11648/j.ijebo.20251303.12},
url = {https://doi.org/10.11648/j.ijebo.20251303.12},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijebo.20251303.12},
abstract = {The overall objective of this research was to examine motivational factors influencing households’ participation in micro and small enterprise in southern Ethiopia. Both quantitative and qualitative research method approaches were used and data collected from the respective sources through the questionnaires. The data was collected from 248 respondents. The collected data was analyzed by econometric and descriptive methods data analysis. From 10 variables expected to influence household's motivation to participate in MSE, five (5) variables were found to be the important factors influencing status of household’s participation in MSE in the study area. These variables include household, education, government support, loan access, and initial capital and work experiences of respondents. The education model result reveals that a positive sign and significant at 1% level of significance. Educational status of the households is determinant variable that influences participation of MSE in the area. The possible reasons are the literate people are better to manage; their capacity of accepting change makes them good analysts to participate in MSE. There is significance income difference participants and non-participants of SME. According from econometric results, loan access is determinant variable that influences the participation in the MSE in the area. It would be better for households if any concerned stakeholder gives skill development training how to manage income and saving to increase their capital to participate in SME.
},
year = {2025}
}
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TY - JOUR
T1 - Motivational Factors Influencing Households’ Participation in Micro and Small Enterprises (MSEs) in Southern Ethiopia
AU - Yisehak Ossa Jokka
Y1 - 2025/10/31
PY - 2025
N1 - https://doi.org/10.11648/j.ijebo.20251303.12
DO - 10.11648/j.ijebo.20251303.12
T2 - International Journal of Economic Behavior and Organization
JF - International Journal of Economic Behavior and Organization
JO - International Journal of Economic Behavior and Organization
SP - 118
EP - 128
PB - Science Publishing Group
SN - 2328-7616
UR - https://doi.org/10.11648/j.ijebo.20251303.12
AB - The overall objective of this research was to examine motivational factors influencing households’ participation in micro and small enterprise in southern Ethiopia. Both quantitative and qualitative research method approaches were used and data collected from the respective sources through the questionnaires. The data was collected from 248 respondents. The collected data was analyzed by econometric and descriptive methods data analysis. From 10 variables expected to influence household's motivation to participate in MSE, five (5) variables were found to be the important factors influencing status of household’s participation in MSE in the study area. These variables include household, education, government support, loan access, and initial capital and work experiences of respondents. The education model result reveals that a positive sign and significant at 1% level of significance. Educational status of the households is determinant variable that influences participation of MSE in the area. The possible reasons are the literate people are better to manage; their capacity of accepting change makes them good analysts to participate in MSE. There is significance income difference participants and non-participants of SME. According from econometric results, loan access is determinant variable that influences the participation in the MSE in the area. It would be better for households if any concerned stakeholder gives skill development training how to manage income and saving to increase their capital to participate in SME.
VL - 13
IS - 3
ER -
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