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The Effect of Industry Extension Services Project on the Performance of Small and Micro Enterprises

Received: 25 January 2024     Accepted: 21 February 2024     Published: 12 April 2024
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Abstract

The purpose of the study was to investigate the effect of industry extension service projects on the performance of micro and small enterprises. Thus, the study utilized an explanatory and descriptive research design to achieve the objectives of the research. The study targeted MSEs that had been in operation for more than two years at the time of the study. The research had a total population of 606 MSEs, out of which a sample size of 241 operators was realized using Taro Yamane’s formula. Thus, a stratified sampling technique and simple random sampling were employed to select representative samples. Beside, primary and secondary data were used in the study. The analysis was conducted using SPSS version 20 on 223 fully responded questionnaires. The data was analyzed using descriptive and inferential statistics. In addition to this, correlation and regression models were used to analyze the variables of the study. The finding proved that IESP support provided by TVET trainers to MSEs was not adequate. Regression analysis indicated that entrepreneurship, technology, kaizen, and technical skill support had a positive and significant relationship with the performance of MSEs. Thus, it is recommended that the TVET College should provide regular industry extension service support to MSEs through four packages.

Published in International Journal of Economic Behavior and Organization (Volume 12, Issue 2)
DOI 10.11648/j.ijebo.20241202.12
Page(s) 67-76
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

IESP, TVET College, Micro and Small Enterprises, Performance

1. Introduction
Globally, legally registered MSEs account for roughly half of total employment in most developed countries, such as the EU. Hence, MSEs are considered as the "cornerstone" of economic development, and hence, they are a driving force towards alleviating poverty and unemployment at the national level .
In most African countries, MSEs play vital roles in the community, such as job creation, where current trends show that SMEs in Africa create over 80% of employment . For example, according to according to A Review of Empirical Evidence from Ethiopia , the income contribution of the MSE sector in Tanzania was about 20–30 percent of the GDP, and they consist of more than 1 million enterprises engaging 3 to 4 million people, or about 20–30 percent of the labor force of the country
In Ethiopia, the micro and small enterprise development is the primary strategy of GTP II to expand employment and reduce poverty, particularly focusing on women and youth. Therefore, the project is designed to make the MSE sector competent enough in the domestic and international markets through competitiveness in the market, providing high-quality products or services at a reasonable price, increasing sales, capital, and creation of employment opportunities. However, the market is full of old and previously existing products, from which the consumers already know the quality of the product or service. The ratio of MSEs' growth from existing level to the next level (from small to medium enterprises) is very small. The origin of this problem is that either the organizations may not implement the project or the project itself may not be able to deliver them.

1.1. Statement of the Problem

The designed industry extension service project provides various types of support services such as training to fill technical skill gaps; KAIZEN like 5s and 7s waste implementation; product quality improvement; productivity increase; business management and development skills; customer handling; developing entrepreneurship culture and bookkeeping skills; assessment and certification; technology adaptation and transfer; are major areas of support under the industry extension program; and all these are support services provided by technical and vocational colleges to MSEs.
Various studies conducted that infrastructure, management experience, marketing problems, bureaucracy, raw materials, poor infrastructure, and over-tax were the most binding constraints inhibiting the performance of MSEs. What makes this study different is that it will focus on industry extension services (in terms of technical, technology, kaizen, and entrepreneurship) and their effects on the performance of MSEs.
In closing, moreover, in Ethiopia, there is no extensive research on the effect of IESP on the performance of MSEs. The earlier ones have not been extensively studied beyond the four packages.

1.2. Research Question

The study was attempted to answer the following main research Question:
What is the effect of Industry extension service on the performance of?

1.3. Objectives of the Study

General Objective
The overall objective of this study is to examine the effect of industry extension service projects on the performance of MSEs.
Specific Objectives
To achieve the general objective, the research was guided by the following specific objectives:
1) To determine the effect of Kaizen support on the performance of MSEs.
2) To examine the effect of technology support on the performance of MSEs.
3) To evaluate the effect of technical skill training on the performance of MSEs.
4) To investigate the effect of Entrepreneurship training support on the performance of MSEs.

1.4. Significance of the Study

The study is important to the government in the determination and establishment of a stronger regulatory and legal framework for the MSE sector in Ethiopia. Besides, it can help various stakeholders in MSEs, mainly Oromia Job Creation and Vocational Bureau and TVET College identify gaps inherent in their MSEs and find ways of improving their financial performance. In particular, this paper could serve as a source of reliable information for the administration job creation and vocational office.

1.5. Scope of the Study

Among the different types of MSEs business classifications based on their size, the scope of the study was limited to only micro and small business enterprises.
2. Review of Related Literatures

2.1. Definitions of Micro and Small Enterprises

Micro and small business enterprises have been identified differently by various individuals and organizations, such that an enterprise that is considered small and medium in one country is viewed differently in another country .
Table 1. The revised definition of micro and small enterprises in Ethiopia.

Level Of Enterprise

Sector

Head Count Staff

Total Asset (ETB)

Total Asset (USD)<2016>

Total Asset (USD)<2019>

Micro

Industry

≦5

≦100,000

≦4,630 USD

≦3,500 USD

Service

≦5

≦50,000

≦2,310 USD

≦1,7500 USD

Small

Industry

6-30

100,001 ~1,500,000

4,630 ~69,500 USD

3,500 ~52,000 USD

Service

6-30

50,001 ~500,000

2,310 ~23,150 USD

1,7500 ~17,500 USD

Medium

Industry

31-100

1,500,001 ~20,000,000

69,500~926,000 USD

52,000 ~700,000 USD

Large

Industry

>100

>20,000,000

Source: (Ministry of Urban Development and Housing 'Micro and Small Enterprise Development Policy & Strategy, 2016).
The objectives of the 1997 strategy framework were to facilitate economic growth and bring equitable development, create long-term jobs, strengthen cooperation between MSEs, provide the basis for medium and large-scale enterprises, promote exports, and balance preferential between MSEs and bigger enterprises .

2.2. Production Theory

This theory is an effort to explain the principles by which a business enterprise decides how much of each commodity that it sells it will produce, and how much of each kind of labor, raw material, or fixed capital good that it employs (its inputs or factors of production) it will use. The theory of production involves some of the main fundamental principles of economics. These include the relationships between commodity prices and the wages or rents of the productive factors used to produce them, as well as the relationships between commodity prices and productive factors on the one hand, and the quantity of these commodities and productive factors produced or used on the other.

2.3. Economic Development Theory

According to , the ability to develop new ideas and innovate has become a priority for many organizations. Intense global competition and technological development have made innovation be a source of competitive advantage for the success of a business enterprise . Human Capital theory suggests that education and experience develop skills that enable workers to be productive .

2.4. Lean Management Theory

The theory of lean management developed by John , posits that companies are in business to make a profit. If they don't, they won't survive. There are two ways to increase profits: raising prices and lowering costs. Competitive pressures often limit the ability to do the former, so companies tend to focus on cutting costs. One of the more popular ways for companies to reduce costs is through lean management. Lean management focuses on improving processes. Every step a product takes, from raw materials to final assembly, is reviewed. Waste or duplication of effort is identified and eliminated to the maximum extent possible. As mentioned above, the focus is on creating benefits (lower costs, quicker turn times, etc.) for the customer. A system of "continuous improvement" is established to monitor the results on an ongoing basis. The goal is to create the perfect process.

2.5. Endogenous Growth Theory and the Knowledge-Based Theory

The knowledge-based theory also distinguishes between two types of learning based on the context within which they occur. First, there is exploitative learning, which is external to micro and small business enterprises and therefore must be acquired. Second, we have explorative learning, which obtains from inside the micro small business enterprises and thus can occur only through internal experiments , and hence is experiential in nature.
3. Research Methodology

3.1. Research Design

The researcher used descriptive and explanatory types of research design to conduct the research work. A qualitative and quantitative approach was employed in the research to accomplish the objectives of the study.

3.2. Target Population

As at June 30, 2021, According to of Administration job creation and vocational office data, there are 606 registered and active MSEs operators in operation for more than two years. These are (180 service, 197 trade, 57 industries, 166 economic infrastructure and six agricultures). Then, the target population for the study has comprised the 606(six hundred six) registered and active MSEs.

3.3. Sources of Data and Instruments of Data Collection

The study employed both primary and secondary sources of data Primary data were collected through structured questionnaires and interview based questionnaires containing both close and open-ended from MSE’s owners. While the secondary data was taken from books, journals, thesis papers, strategies, annual reports and documents of MSEs town administration job creation and vocational office.

3.4. Sampling Design and Technique

They are as follows: 180 services, 197 trades, 57 industries, 166 construction, and six agriculture. Accordingly, this study employed a stratified random sampling technique to select the required sample of MSEs from the above-listed MSE operators for this study. Thus, the researcher divided his population into five sectors based on the types of business classifications. Finally, a simple random sample was taken from each stratum and then those sub-samples were joined to form a complete stratified sampling..

3.5. Sample Size

For this study to select sample size a list of the population formally registered and inventoried MSEs until June 30, 2021 by the town administration and vocational office was obtained. The total population of the study is 606 MSEs, which includes agriculture (six), trade (197), service (180), construction (166) and industry (57). For this study's purpose, the researcher used the simplified formula of Taro Yemane’s Formula , considering 95% of confidence level and 5% margin of error sample size determination, which helps to calculate sample size. So that based on the formula adapted, the total sample can be
= 6061+6060.052
n =240.95 ~ 241
Table 2. Number of total and sample MSEs operators for the study by sector.

S/N

Types sectors

Target population (N)

Sample Size calculations

Sample Size (n)

1

Agriculture

6

6/606x241= 2.3 ~2

2

2

Trade

197

197/606x241= 78.3 ~78

78

3

Services

180

180/606x241= 71.59 ~78

72

4

Construction

166

166/606x241= 66

66

5

Industry

57

57/606x241= 22.6 ~2

23

Total

606

606/606x241=241

241

3.6. Data Analysis and Presentation

Accordingly, the data was analyzed via descriptive statistics by using mean, standard deviation, frequency, and percent. While in the case of the econometric model, the result was estimated by applying correlations, and multiple linear regression analysis. A correlation coefficient was employed to test the relationship between the variables.

3.7. Model Specification

Multiple Linear Regression Analysis was applied to investigate the effect of industry extension services projects on the performance of small and micro enterprises in the study site. An analysis of variance is used to test the significance of the model. R2 was used in this research to measure the extent of the goodness of fit of the regression model.
P= β0 + β1ES + β2KS + β3 TS + β4 TSS + Ɛit
Where: P is the dependent variable (performance of MSEs).
β0= Constant term or the value of intercept
ES is Entrepreneurship training support KS is kaizen Support
TS is technology support
TSS is Technical skill support
ES is Entrepreneurship training support
β1, β2, β3, β4, β5 are the coefficients associated with each independent variable Ɛit is error term (Residual)

3.8. Validity and Reliability Test

Accordingly, the coefficient was determined to be 0.913, as shown in Table 3. Thus, the instrument is trustworthy because the reliability coefficients are more than 0.9. As can be seen in the table below, the outcome of Cranach's Alpha is positive.
Table 3. Reliability Statistics.

Cronbach's Alpha

Cronbach's Alpha Based on Standardized Items

N of Items

.909

.913

5

Source: SPSS output
4. Result and Discussion

4.1. Gender of the Respondents

Results in figure 1 below show that 142 (63.7) percent of the selected sample respondents were males and 81 (36.3) percent were females. The findings also indicate that male is dominant in MSEs' operations because the gender distribution reflects a wide variation of the gap.
Figure 1. Male versus Female

4.2. Age of the Respondents

First, 61 (27.34) percent of respondents were between the ages of 18 and 25, followed by 132 (59.2) percent of respondents between the ages of 26 and 35; 21.9 percent of respondents between the ages of 36 and 45, and 9 (4) percent of respondents above the age of 46. This indicates that most of the respondents were aged between 26 and 35 years old, 132 (59.2) percent. This indicates that most of the MSEs were owned and run by a youth and productive labor force.
Table 4. Distribution of Age of the respondents.

Age group

Frequency

Percentage

18-25 Year

61

27.4

26-35 Year

132

59.2

36-45 Year

21

9.4

> 46 Year

9

4.0

Total

223

100%

Source: Survey Data

4.3. Entrepreneurship Training Support on Performance of MSEs

TVET College may not support the trainees in this variable. The individual and grand mean (1.9318) values justify it very well. The individual and grand mean values in the table below clearly show that the Entrepreneurship training given to MSE’s operators is not adequate enough. The standard deviation shows that not all respondents were in agreement with that since there was a small variance between answers. However, from the standard deviation of 91, we can understand that more than half of the respondents agreed with the statement.
Table 5. Descriptive Statistics of Entrepreneurship training support given to MSEs.

N

Mean

Std. Deviation

I have acquired effective accounting skills

223

1.7444

.88131

Helped me to keep the enterprise financial source documents

223

2.3363

1.04359

Supported me to know the enterprises’ assets, liabilities, and capitals

223

2.1345

.34199

Helped me to know accounting and record-keeping skills

223

1.6592

.93985

I can now better implement my business plans

223

2.0045

1.00224

It helped me to daily record my costs and revenues

223

1.9372

.79163

I Supported to knowing my cash flows

223

1.9058

1.00230

My ability to take risks has been enhanced

223

1.5785

.98725

It has empowered me to know my profit and loss

223

2.0135

1.20240

Grand mean

1.9318

.91029

Source: SPSS output

4.4. Kaizen Support on Performance of MSEs

As it is shown in table below, the average mean and SD values of responses for Kaizen support equate to 2.02 and 0.93, which indicates that respondents are not certain about the kaizen effects of MSEs performance. This reveals that the Kaizen training support provided to operators of MSEs is not sufficient. With a calculated mean value of 2.0249, the majority of respondents agreed that the majority of MSEs operators were not appropriately practicing Kaizen rules such as housekeeping rules, reducing wastage, producing materials based on customer need, improving product quality, customer satisfaction, ordering items, reducing cost, resource utilization, and value-adding. Thus, TVET College may not provide training on the continuous improvement.
Table 6. Aggregate Mean Scores of Performance and Kaizen support Factors.

N

Mean

Std. Deviation

Helped me to apply housekeeping rules

223

1.9103

.52077

It helped me to reduce wastage

223

1.9013

1.29070

It empowered me to Produce materials based on customer need

223

2.1928

.85083

It helped me to Improve product quality

223

1.9148

.80924

It supported me to Increased customer satisfaction

223

1.8565

.90397

Helped me to reduce Cost

223

2.0897

1.35933

helped me make better use of my resources

223

2.2466

.73348

Helped to do value-adding activities

223

2.0404

1.19050

It supported me in ordering items in a hasty manner

223

2.0717

.73782

Grand mean

2.0249

0.93297

Source: SPSS output

4.5. Technology Supports on Performance of MSEs

As it is shown in table below, the average mean and SD values of responses for technology support equates to 1.9905 and 0.89740 indicates that respondents are not certain about the technology effects of MSEs' performance. This reveals that about technology training support provided to operators of MSEs is not sufficient.
Table 7. Aggregate mean scores of performance and Technology supports factor.

N

Mean

Std. Deviation

It helped me with the selection of feasible technologies

223

.83729

.83729

It helped me to compete technologically

223

.90173

.90173

It enabled me to copy new technologies.

223

.69595

.69595

Our enterprise’s innovation has helped us achieve strategic goals and objectives

223

1.51596

1.51596

It supported me to apply a new organizational structure

223

.49528

.49528

My enterprise tends toward being ahead in introducing new products/services

223

.71905

.71905

Helped me to substitute technologies to be imported

223

.75581

.75581

It enabled me to apply problem-solving technologies

223

1.16520

1.16520

Empowered me to implement new designs

223

1.03040

1.03040

Aggregate mean scores

1.9905

.89740

Source: SPSS output

4.6. Technical Skill Supports on Performance of MSEs

The results of the analysis, as shown in table 8 below, showed that the mean score and SD values were 1.98 and 1.02, respectively. This reveals that technical skill training support given to operators of MSEs is not adequate.
Table 8. Aggregate mean scores of performance and technical skill supports factor.

N

Mean

Std. Deviation

It empowered me to take care of my machines effectively

223

2.1749

.80028

I have improved my task simplicity

223

1.7713

.88363

It has Helped me to reduce task redundancy

223

2.1749

1.02706

It enabled machinery to operate on the company's premises

223

1.9821

1.64936

It helped me fill in the identified gaps

223

2.0448

.49114

My machine repair skills have improved

223

1.9821

.68421

Improve efficiency

223

1.6099

.77418

I can identify and analyze problems in complex situations

223

2.1839

1.52378

My Enterprise has been able to establish linkages with other alliances in order to gain access to goods and services.

223

1.9327

1.35897

Grand Mean

1.9841

1.02140

Source: SPSS output

4.7. Performances of MSEs (Dependent Variable)

The overall performance of MSEs as measured by the nine parameters in table clearly reveals that it is extremely low. Thus, based on the descriptive statistics in table 9, the mean score and SD of MSEs' performance was 2.0135 and .98236, which indicates the respondents disagreed to a small extent that their businesses performed extremely poorly. The mean values in the table clearly indicate that MSEs have very poor performance.
Table 9. Business Performance.

N

Mean

Std. Deviation

My business has been able to increase its sales consistently

223

2.1659

1.29598

Helped us improve market share growth

223

1.9776

1.01982

It helped me enter new markets

223

2.3184

.93094

We often launch new products/services into the market

223

2.2197

.60862

Our employees' numbers have increased.

223

2.0045

1.00224

We have experienced a steady increase in year-on-year profitability

223

1.9372

.79163

Capital investment has improved

223

1.9058

1.00230

Our productivity has improved significantly

223

1.5785

.98725

We have reduced costs

223

2.0135

1.20240

Grand mean/Aggregate Score

2.0135

.98236

Source: SPSS output

4.8. Correlation Analysis of Industry Extension Service Project and Performance of MSEs

Table 10. Correlation table on performance and industry extension service project.

Performance

Entrepreneurship

Kaizen

Technical

Technology

Pearson Correlation

1

.837**

.843**

.706**

.653**

Performance

Sig. (2-tailed)

.000

.000

.000

.000

N

223

223

223

223

223

Entrepreneurs hip

Pearson Correlation

.837**

1

.688**

.685**

.612**

Sig. (2-tailed)

.000

.000

.000

.000

N

223

223

223

223

223

Kaizen

Pearson Correlation

.843**

.688**

1

.631**

.552**

Sig. (2-tailed)

.000

.000

.000

.000

N

223

223

223

223

223

Technical

Pearson Correlation

.706**

.685**

.631**

1

.567**

Sig. (2-tailed)

.000

.000

.000

.000

N

223

223

223

223

223

Pearson Correlation

.653**

.612**

.552**

.567**

1

Technology

Sig. (2-tailed)

.000

.000

.000

.000

N

223

223

223

223

223

**. Correlation is significant at the 0.01 level (2-tailed).
The correlation matrix/table tells us there is a positive relationship between entrepreneurship, Kaizen, technology, and technical skill and the performance of MSEs, and they are moving positively in the same direction, or the relationship is positive. This implies that IES support given in the areas of fourth packages can bring remarkable results in the performance of MSEs.

4.9. Model Summary

A linear regression analysis has been conducted in order to examine the contribution of independent variables that affect the dependent variable. Based on the study, the correlation coefficient (r) was .921. Therefore, this implies that there is a strong relationship between industry extension service projects and the performance of MSEs. And R square value is .848.
This revealed that the dependent variable (Performance of MSEs) is 84.8% explained by the four industry extension support packages (independent variables: Technical, Technology, Kaizen, and Entrepreneurial support). So in this study, the only explanatory variables were technical, technology, kaizen, and entrepreneurship supports.
Table 11. Industry extension service project and Performance Model Summary.

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

1

.921a

.848

.845

.23321

a. Predictors: (Constant), Technology, Kaizen, Technical skill, Entrepreneurship
5. Conclusion and Recommendations

5.1. Conclusion

The study concludes that, industrial extension service supports provided through TVET trainers to MSEs do not bring requested improvement in the performance of MSEs and the overall effect of the service packages on the performance of MSEs is very poor.

5.2. Recommendations

The study suggested that the Government of Ethiopia should develop and implement the curriculum and training materials for this project. Hence, the government should come up with a forum that creates awareness among MSEs owners on the importance of the adoption of industry extension service projects. The study also recommended that the TVET College should provide regular industry extension service support to MSEs through fourth packages.
Abbreviations
AATVETA: Addis Ababa Technical and Vocational Education Training
GDP: Growth Domestic Product
EU: European Union
GTP: Growth and Transformation Plan
IES: Industrial Extension Services
IESP: Industrial Extension Services Project
IMF: International Labor Organization
MIP: The Micro Enterprise Innovation Project
MoE: Ministry of Education
MSEs: Micro and Small Business Enterprises
MSMEs: Micro, Small and Medium Enterprises
NGOs: Non-Governmental Organizations
SMEs: Small and Medium Enterprises
SPSS: Statistical Package for Social Sciences
TVET: Technical and Vocational Education and Training Institutions
USAID: United States Agency for International Development
U.S.: United States
Author Contributions
Efrem Regasa Shiferaw is the sole author. The author read and approved the final manuscript.
Conflicts of Interest
The authors declare no conflicts of Interest.
References
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[3] Bereket, T. (n.d.). The Role of Micro and Small Enterprises in Employment Creation and Income Generation A Survey Study of Mekelle City, Ethiopia, Mekelle University Thesis.
[4] Berihu G. (2017). Determinants Of Micro And Small Enterprises Performance In Godere Woreda Of Gambella Regional State, Ethiopia, Arba Minch University, Ethiophia.
[5] Drucker, P. F. (1999). Knowledge-Worker Productivity: The Biggest Challenge. California Management Review.
[6] 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. Journal of Innovation and Entrepreneurship.
[7] Esmael, S. (2014). Capit Al Growth Constraints of Micro and Small Enterprises: The Case of Jimma Town. Jimma University, Ethiopia.
[8] Hollenstein, H. (1996). A composite indicator of a firm’s innovativeness. An empirical analysis based on survey data for Swiss manufacturing. Research Policy.
[9] Kassa, E. T. (2021). Determinants of the continuous operations of micro and small enterprises during COVID-19 pandemic in Ethiopia. Journal of Innovation and Entrepreneurship.
[10] Krafcik, J. F. (1988). Triumph of the Lean Production System. Sloan Management 30, 41-52.
[11] Yamane, T. (1967). Statistics: An Introductory Analysis (No. HA29 Y2 1967).
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Cite This Article
  • APA Style

    Shiferaw, E. R. (2024). The Effect of Industry Extension Services Project on the Performance of Small and Micro Enterprises. International Journal of Economic Behavior and Organization, 12(2), 67-76. https://doi.org/10.11648/j.ijebo.20241202.12

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    ACS Style

    Shiferaw, E. R. The Effect of Industry Extension Services Project on the Performance of Small and Micro Enterprises. Int. J. Econ. Behav. Organ. 2024, 12(2), 67-76. doi: 10.11648/j.ijebo.20241202.12

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    AMA Style

    Shiferaw ER. The Effect of Industry Extension Services Project on the Performance of Small and Micro Enterprises. Int J Econ Behav Organ. 2024;12(2):67-76. doi: 10.11648/j.ijebo.20241202.12

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  • @article{10.11648/j.ijebo.20241202.12,
      author = {Efrem Regasa Shiferaw},
      title = {The Effect of Industry Extension Services Project on the Performance of Small and Micro Enterprises
    },
      journal = {International Journal of Economic Behavior and Organization},
      volume = {12},
      number = {2},
      pages = {67-76},
      doi = {10.11648/j.ijebo.20241202.12},
      url = {https://doi.org/10.11648/j.ijebo.20241202.12},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijebo.20241202.12},
      abstract = {The purpose of the study was to investigate the effect of industry extension service projects on the performance of micro and small enterprises. Thus, the study utilized an explanatory and descriptive research design to achieve the objectives of the research. The study targeted MSEs that had been in operation for more than two years at the time of the study. The research had a total population of 606 MSEs, out of which a sample size of 241 operators was realized using Taro Yamane’s formula. Thus, a stratified sampling technique and simple random sampling were employed to select representative samples. Beside, primary and secondary data were used in the study. The analysis was conducted using SPSS version 20 on 223 fully responded questionnaires. The data was analyzed using descriptive and inferential statistics. In addition to this, correlation and regression models were used to analyze the variables of the study. The finding proved that IESP support provided by TVET trainers to MSEs was not adequate. Regression analysis indicated that entrepreneurship, technology, kaizen, and technical skill support had a positive and significant relationship with the performance of MSEs. Thus, it is recommended that the TVET College should provide regular industry extension service support to MSEs through four packages.
    },
     year = {2024}
    }
    

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  • TY  - JOUR
    T1  - The Effect of Industry Extension Services Project on the Performance of Small and Micro Enterprises
    
    AU  - Efrem Regasa Shiferaw
    Y1  - 2024/04/12
    PY  - 2024
    N1  - https://doi.org/10.11648/j.ijebo.20241202.12
    DO  - 10.11648/j.ijebo.20241202.12
    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  - 67
    EP  - 76
    PB  - Science Publishing Group
    SN  - 2328-7616
    UR  - https://doi.org/10.11648/j.ijebo.20241202.12
    AB  - The purpose of the study was to investigate the effect of industry extension service projects on the performance of micro and small enterprises. Thus, the study utilized an explanatory and descriptive research design to achieve the objectives of the research. The study targeted MSEs that had been in operation for more than two years at the time of the study. The research had a total population of 606 MSEs, out of which a sample size of 241 operators was realized using Taro Yamane’s formula. Thus, a stratified sampling technique and simple random sampling were employed to select representative samples. Beside, primary and secondary data were used in the study. The analysis was conducted using SPSS version 20 on 223 fully responded questionnaires. The data was analyzed using descriptive and inferential statistics. In addition to this, correlation and regression models were used to analyze the variables of the study. The finding proved that IESP support provided by TVET trainers to MSEs was not adequate. Regression analysis indicated that entrepreneurship, technology, kaizen, and technical skill support had a positive and significant relationship with the performance of MSEs. Thus, it is recommended that the TVET College should provide regular industry extension service support to MSEs through four packages.
    
    VL  - 12
    IS  - 2
    ER  - 

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    1. 1. Introduction
    2. 2. Review of Related Literatures
    3. 3. Research Methodology
    4. 4. Result and Discussion
    5. 5. Conclusion and Recommendations
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