1. Introduction
The development of small and medium-sized enterprises (SMEs) plays a very important role in the global economy and production (
Tong et al. 2022) and these firms are regarded as the backbone of economic growth in all developed and undeveloped economies to sustain the country’s economy and establish a supply chain system (
Diabate et al. 2019). Small and Medium-Sized Enterprises (SMEs) remain a vital vehicle for encouraging economic growth and development in today’s globe. In many regions of the world, considerable attention has been paid to the well-being and sustainability of SMEs, recognizing the critical role they play in the country’s growth (
Shitaye 2022;
Malaza 2010;
Eniola 2014). This suggests that small and medium-sized firms (SMEs) play an important part in the global economy’s development and growth, as well as in poverty alleviation.
Small and medium-sized entities (SMEs) also play an important role in a country’s economy, mainly in developing countries, due to their beneficial contributions to improved income distribution, job creation, poverty alleviation, rapid industrialization, regional development, and export growth (
Mamo 2020). Micro businesses, as well as smaller businesses with the capacity to generate more employment, have proven to be powerful proponents of economic expansion (
Kinfe 2019). Hence, in developing countries, small businesses are regarded as important contributors to job formation (
Asa and Prasad 2014;
Gregurec et al. 2021;
Igwe et al. 2018).
Ethiopia is also a developing country in Africa where Small and Medium Enterprises (SMEs) contribute significantly to most economies. SMEs not only serve as important to creating job opportunities, but they also contribute to the country’s economic growth, particularly as a catalyst for the shift to an industrialized society. SMEs are regarded as breeding grounds for the growth of major organizations (
Olana 2020). According to the United Nations Industrial Development Organization, Ethiopia has the lowest new venture rates in Sub-Saharan Africa and the fewest private firms per capita (
Shitaye 2022). As a result, the Ethiopian government is focused on micro and small businesses, primarily because of their significance to job creation. However, several specific issues have been confronted by small and medium-sized firms (SMEs) (such as COVID-19, political instability, and corruption). As a result, it is critical to investigate the issues that impede SMEs’ long-term success. This study was thus inspired to look at aspects impacting SMEs’ long-term growth, which will be detailed below.
Small businesses account for a large proportion of employment in Ethiopia, particularly in Ethiopia. However, their efforts have been futile due to administrative insecurity in the form of military coups, civil wars, and other civil unrest, which has resulted in poor organizational performance (
Cepel et al. 2020;
Gerald et al. 2020;
Hosseininia and Ramezani 2016). This political stability created space for massive corruption in the form of bribery, lobbying, cronyism, and nepotism, all of which directly or indirectly harm the growth of SMEs (
Daneji and Bazza 2013;
Lambovska et al. 2021). In addition to these factors, global epidemic disasters such as the coronavirus (COVID-19) frequently endanger the lives of Small and medium-sized businesses. Coronaviruses (COVID-19) typically expose SMEs to a variety of challenges and may endanger their lives (
Asa and Prasad 2014;
Fenetahun et al. 2021;
Allard et al. 2021).
Although other studies (
Varsakelis 2006;
Al-Tit et al. 2019) have continued to evaluate the factors that determine the performance of SMEs as well as their sustainable growth, none of them consider coronavirus and political instability as explanatory variables and how they affected SMEs in developing countries, particularly in the context of Ethiopia. In fact, as per the knowledge of the researchers, Ethiopia is severely challenged by political instability and corruption, in addition to COVID-19. Thus, in Ethiopia, political insecurity, and corruption, in addition to pandemic disease, are the most significant impediments to the growth of SMEs (COVID19). Thus, the study intends to investigate the current factors affecting the sustainable growth of SMEs in Ethiopia. Based on the premises stated above, the study has the following objectives:
To evaluate the effect of corruption on the performance of SMEs.
To determine the extent to which political instability affects the growth of SMEs.
To evaluate the overall effects of COVID-19 on the long-term sustainability of SMEs.
Following the above-mentioned specific goal, the discoveries of this study have significant ramifications for scientific knowledge and the community. The study will help the government develop and implement policies based on scientific knowledge. This research will also contribute to academic literature and assist other researchers who wish to research a similar topic. Finally, the results of this analysis will provide many companies and SMEs with a systematic method for increasing their innovation capabilities, as well as a valuable source of ongoing competitive advantage for their sustainability during pandemics, and after COVID-19, of their performances in politically unstable environments.
In general, the paper’s structure was set up in accordance with the following format: In
Section 2, the topic of reviewed literature and the formulation of hypotheses was covered; in
Section 3, the study’s overall approach is described. The data analysis and interpretation were covered in
Section 4; the discussion of the findings and the study’s conclusion were included in
Section 5 and
Section 6, respectively.
Section 7 of this paper contains limitations of the study and suggestions for future research.
4. Results and Interpretations
4.1. Introduction
This chapter discusses the presentation, interpretation, and analysis of the study’s data. Questionnaires and interviews were used to collect data. Multiple regression analysis was used to evaluate the determinant factors and their effects on SMEs. A total of 194 questionnaires were distributed, with 194 of them returned. SPSS (version 20) statistical software was used to present and analyze the collected data, and Multiple Regression Analysis was also used to test the study’s hypotheses and the effects of the independent variables on the dependent variable.
4.2. Validity and Reliability
The study used Cronbach’s alpha (a measure of the internal reliability of the questionnaire items) by using data from all the respondents to measure the reliability of the scores obtained. Separate reliability tests were computed for each of the variables. Cronbach alpha measures how strongly item responses obtained at the same time correlate with one another, and the widely accepted social science cutoff is that alpha should be greater than 0.70 for a set of items to be considered a scale (
Field 2009). As a result, the Cronbach’s alpha test was performed using SPSS, and the results are as follows:
The Cronbach’s alpha reliability statistics value of the scale for all predictors and outcome variables is shown in the
Table 2 below. The calculated coefficients of alpha for this study were 0.984 for all variables, which is greater than the required threshold of 0.70, indicating that the variables are internally reliable. As a result, all variables yielded results greater than 0.7, which is statistically significant, indicating that the data were reliable.
4.3. Descriptive Analysis of CE on Performances of SMEs
The overall average mean in the above
Table 3 is 4.48. As a result, COVID-19 has a greater impact on the long-term performance of SMEs. Another issue that threatens the viability of Ethiopian SMEs is political instability. As a result, the mean of corruption is 3.92 with a standard deviation of 0.83, the mean of political stability in Ethiopia is 4.21 with a standard deviation of 0.84, and the mean of COVID-19 is 4.48 with a standard deviation of 0.56. These findings were backed up by the interviews, in which participants were asked to elaborate on what they meant by the term determinant factors affecting SMEs. According to the responses of SMEs in Ambo town, several responses were verified. As a result, a business venture could be identifying opportunities, solving current problems, networking new business ideas, taking risks, and innovating. All these suggestions came from different respondents, demonstrating their thoughtfulness; however, the question was whether they would be implemented in Ambo Town. There were some perplexing results, where one would indicate agreement, but then disagree with the elements being used in the SMEs sectors of Ambo town.
4.4. Results of Inferential Statistics
According to the above model summary, which is shown in
Table 4, there is a highly significant relationship (
p = 0.000) between the dependent variable and the linear combination of the predictor variables denoted by R. (0.942). The coefficient of determination (R-square) is a measure of how well the predictor variables can be used to predict the criterion variable. As a result, the set of the above independent variables explained 88.6 percent of the variation in the dependent variable. R-squared, on the other hand, measures the proportion of variation in the dependent variable explained by independent variables, regardless of how well they are correlated with the dependent variable. This is not a desirable goodness-of-fit statistic property. Adjusted R-squared, on the other hand, provides an adjustment to the R-squared statistic, such as an independent variable that correlates with the dependent variable increasing adjusted R-squared and any variable without a strong correlation decreasing the adjusted R- squared. As a result, to see the model’s success in the real world, adjusted R-squared is preferable to R-squared (
Burns and Burns 2008). As a result, adjusted R-squared, the proportion of variation explained by the regression of the dependent variable on the combined effect of all predictor variables, is 88.3 percent. As a result, in general, the independent variables (such as COVID-19, Corruption, and Political Instability) can predict the dependent variable (the performance of SMEs) by 85.3 percent, with extraneous variables predicting 14.7 percent.
The analysis of variance (ANOVA) table shown in
Table 5 above provides statistics on the overall significance of the model being tested. The significant value in the model, also known as the
p-Value, is 0.000, indicating that the independent variables in the model explain the dependent variable. The ANOVA (Analysis of variance) table above shows that, based on the total observation value (159.814), the regression model explains most of the observations (141.672). The model does not account for the remainder (18.142). As a result, it is possible to conclude that regression explains most of the observations, whereas extraneous variables explain the remainder. The mean square of the model (regression) is 47.224, and the mean square of the residual is 0.095, representing the average amount of variation explained by extraneous variables (the unsystematic variation). The F—ratio (494.567) is a measure of the proportion of variation explained by the model to variation explained by extraneous variables. As a result, the value of F is large enough to conclude that the set of independent variables is contributing to the variance of SMEs’ sustenance, and thus the model represents an actual practice of the business operators under study.
The above
Table 6 shows that an unstandardized coefficient of an independent variable (also known as B or slope) measures the strength of its relationship with the dependent variable (sustainability of SMEs); this means that variation in the independent variables corresponds to variation in the growth of SMEs (such as Corruption, Political instability, and COVID-19). A coefficient of 0 indicates that the dependent variable does not change consistently as the independent variables change. The coefficient for Corruption in this research model is −0.07, the coefficient for Political Instability is 0.678, and COVID-19 is 0.540. Therefore, for each independent variable mentioned above, there was a consistent variation in the growth of SMEs. That is, Corruption predicts a 7% decline in SME growth, whereas Political Instability predicts a 67.8% increase in SME growth and COVID-19 predicts a 54% increase in SME growth.
The standardized beta coefficient column also demonstrated an individual variable’s contribution to the model. The beta weight is the average variation in the dependent variable (the growth of SMEs) when the independent variables (such as corruption, political insecurity, and COVID-19) increase or decrease by one standard deviation (all other independent variables are held constant). Thus, political insecurity has the greatest influence on the growth of SMEs (0.627), followed by COVID-19 (0.337). The table above also shows that, except for corruption, all the explanatory (independent) variables included in this study can significantly explain the variation in the dependent variable at a 95% confidence level.
The first entry in
Table 7 is the t-statistic value, followed by the degrees of freedom (Df), and finally, the corresponding
p-value for the 2-tailed test, denoted as Sig. (2-tailed).
With 193 degrees of freedom, the t-statistic is 65.320. 0.000 is the corresponding two-tailed p-value. Using a 5% significance level, we can see that the p-value obtained is less than 0.05. At the 5% level of significance, we can reject the null hypothesis at p = 0.05, which means that the sample mean is significantly different from the hypothesized value and the average corruption in the small business enterprise is not the same in all small business sectors. A 69.856 t-statistic with 193 degrees of freedom 0.000 is the corresponding two-tailed p-value. Using a 5% significance level, we can see that the p-value obtained is less than 0.05. At the 5% level of statistical significance, the null hypothesis is rejected, indicating that the sampling distribution significantly differs from the set of predictor variables and that the average political instability in the small firm is not the same across all small business areas of the economy. Thus, a110.128 t-statistic with 193 degrees of freedom 0.000 is the corresponding two-tailed p-value. Using a 5% significance level, we can see that the p-value obtained is less than 0.05. At the 5% level of significance, we can reject the null hypothesis at p = 0.05, which means that the sample mean is significantly different from the hypothesized value and the average COVID-19 in the small business enterprise is not the same in all small business sectors.
5. Discussions of the Main Findings
SMEs are regarded as critical to the general development of society. They are crucial to economically and socially uplifting citizens, as countries cannot just produce jobs for all community members. SMEs are one of the finest venues for young people to be entrepreneurial, develop new technology, and develop replacement items to replace imported goods (
Anderson and Eshima 2013;
Freeman and Phillips 2002;
Rosyadi et al. 2020). As a result, the study investigated the determining elements that influence the performance of small and micro businesses (SMEs) in the Oromia Region, Ambo town, Ethiopia. Primary data was collected using regression analysis and descriptive and explanatory research approaches. The Likert scale was used to represent respondents’ agreement: strongly agree, agree, neutral, disagree, and strongly disagree. The research findings were analyzed using the regression analysis approach. All independent factors have a significant influence on the business of SMEs. The study findings are supported by other research results (
Hamsal and Ichsan 2021;
Mark and Nwaiwu 2015;
Quazi et al. 2014).
The study’s findings reveal significant effects of independent variables (corruption, political instability, and COVID-19) on the performance of SMEs. As a result, it can be concluded that all variables examined in this study play a significant role in lowering the performance of SMEs. Corruption is one of the obstacles impeding the growth of SMEs not only in Ethiopia but throughout the world. It reduces SMEs’ profit margins, threatening their viability. Against this context, the researcher hypothesized that corruption might be negatively associated with the performance of small and medium-sized businesses. Furthermore, widespread corruption in public service delivery will exacerbate Ethiopia’s ongoing political instability. Thus, political considerations are also rated negatively in developing countries. Hence, based on the investigations of this study, the following hypotheses were discussed below:
Hypothesis 1 (H1). Corruption has a negative correlation with SMEs’ sustainability, but no statistically significant effects. Result: p = 0.944 and beta has a negative coefficient, so the null hypothesis is accepted, and the alternative hypothesis is safely rejected, implying that corruption hurts the sustainability of SMEs but is not statistically significant (Creswell 2009). The result of the finding is supported by other researchers (Ellahi 2020; Quazi et al. 2014). Hypothesis 2 (H2). There are effects and a positive correlation (p0.05) between political stability and the performance of SMEs. Result: p = 0.020 and Beta is positive, hypothesis 2 is accepted, and the null hypothesis is safely rejected, indicating that political stability has a significant impact on the performance and sustainability of SMEs. This study’s findings are consistent with the finding that reveals that political instability, defined in terms of governmental duration, is likely to harm economic growth. This study is also supported with the study of (Mark and Nwaiwu 2015; Kwon 1997). Hypothesis 3 (H3). There are effects and a positive correlation (p0.05) between the performance of SMEs and COVID-19. Result: p = 0.005 and Beta is positive, implying that hypothesis 3 is accepted and the null hypothesis is safely rejected, implying that COVID-19 has a significant impact on the performance of SMEs (Rogers 1995; Sanders 2017). 6. Conclusions, and Recommendations
The focus of the study was on the determinants and their effects on the sustainable growth of small and medium-sized enterprises in developing nations, notably Ethiopia. Intending to transform the SME sector into a driver of job creation and economic growth, it is critical to understand the variables that impact the growth of SMEs in Ethiopia, specifically in Ambo town. This study provides empirical evidence on SMEs based on a sample of 194 in Ambo town. For the analysis of data, the research utilized both descriptive and explanatory methods. Based on the findings of the surveyed literature and empirical investigations, the study reached the following important conclusions.
This study’s findings are expected to provide insight into the current trends and challenges that determine the sustainable growth of small and medium-sized enterprises (SMEs) during COVID-19 in Ethiopia. According to the findings of this study, the political scene has a direct influence on the success of enterprises. This is due to party politics, which has resulted in, among other things, the hazards of bloodshed and conflict, rapidly growing rates of crime and terrorist actions, abductions, and bomb strikes, withholding economic support, and driving away investment opportunities from the country. According to the study’s results, Ethiopian political uncertainty has a negative and considerable influence on the survival of SMEs. As a result of the ongoing political uncertainty, businesses find it difficult to implement new goods and/or procedures into their activities.
The analysis also reveals that corruption has a significant impact on Ethiopian small and medium-sized businesses. According to the findings of this study, most respondents believe that government officials illegally take money from them. This appears to confirm the findings of a study by (
Oyelola et al. 2013), who discovered that SME owners/managers were frequently harassed by government officials who extorted money from them. Furthermore, widespread corruption in government service delivery would exacerbate Ethiopia’s ongoing political instability. Corruption has both direct and indirect effects on small and medium enterprises because of a significant connection between both corruption and political instability.
Furthermore, the COVID-19 epidemic has hurt the Ethiopian economy, threatening the survival of small and medium-sized companies (SMEs) across the country. As a result, there is a need for a new approach, notably by providing financial aid for current company activities and loans for small ventures, to guarantee that most SMEs survive the COVID-19 pandemic. Hence, the study strongly advocates for sequential policy reform in the region, as well as a review of current policies aimed at ensuring effective corruption control in the region and bring political stability to the region, particularly in Ambo town, Ethiopia.