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Determinants of Sustainable Growth of SMEs in Developing Countries: The Case of Ethiopia

Doctoral School of Economics and Regional Sciences, Hungarian University of Agriculture and Life Sciences, Páter K. Str. 1, 2100 Gödöllő, Hungary
Department of Management, Colleges of Business and Economics, Ambo University, Ambo P.O. Box 19, Ethiopia
Institute of Economic Sciences, Hungarian University of Agriculture and Life Sciences, Páter K. Str. 1, 2100 Gödöllő, Hungary
Author to whom correspondence should be addressed.
Economies 2022, 10(8), 189;
Submission received: 11 May 2022 / Revised: 5 July 2022 / Accepted: 22 July 2022 / Published: 1 August 2022
(This article belongs to the Special Issue Determinants of Firm Performance in Developing Countries)


Small and medium-sized businesses (SMEs) played a significant role in domestic employment and inclusive GDP in developing countries such as Ethiopia. Accordingly, the purpose of this study is to investigate the determinants of sustainable growth of SMEs in developing countries, notably in Ethiopia. To achieve the objectives of this study, both descriptive and explanatory research designs were used. In addition to this, primary data was collected from SMEs engaged in service, manufacturing, trade, construction, and urban agriculture. The sampling techniques used for this study is the stratified simple random sampling technique in which 194 employees of SMEs were drawn as a sample size for this study. Moreover, multiple linear regression models were used with the Statistical Package for the Social Sciences (SPSS) version 23 software as the data analysis tool. According to the study’s findings, crucial issues such as the coronavirus and political uncertainty in Ethiopia, which have allowed for widespread corruption, are now harming the growth of SMEs. According to the findings, political instability, corruption, and COVID-19 are now having a substantial effect on the growth of SMEs in Ethiopia. These concerns have serious consequences for the long-term sustainability of Ethiopian SMEs. 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 bringing political stability to the region, particularly in Ambo town, Ethiopia.

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.

2. Related Literature Review and Proposed Hypothesis

2.1. Theoretical Literature Review

The theory is critical for emerging disciplines such as sustainable growth knowledge for SMEs in strategic management. Scholars of strategic management theory have captured the essence of the theory and the challenge it poses to the discipline. The theory defines the phenomenon or explains how it works (Nyoni and Bonga 2018). Hence, the study examines the following Related Theories of SME Sustainable Growth.

2.1.1. Institutional Theory

Institutional theory refers to advanced components or competencies associated with the long-term growth of SME businesses that inspire management practices to pursue long-term business growth (Ahmad et al. 2020; Douglas et al. 2017; Glover et al. 2014). The overall impression of institutional theory is centered on the rules established by the institutes, whereas the novel perspective focuses on institutional entrepreneurship, such as the use of sustainable business representations and an emphasis on opportunities Neudorfer and Theuerkauf 2014. The business organization seeks rightfulness to meet the needs of stakeholders and society (Shumetie and Watabaji 2019). The effects of institutional factors have resulted in massive or isomorphic conclusions about business sustainability (Adam and Alarifi 2021; Ratten and Usmanij 2020). Business sectors encourage innovation within the framework of the institutional structure through collaboration with various stakeholders to boost the long-term growth of SMEs. The sustainable business enterprise is an improvement for an increasing proportion of SMEs worldwide, with the hope of increased productivity, flexibility, and beneficial social and environmental outcomes (Sobaih et al. 2021).
The three aspects of the institutional theory are transparency, fairness, and complexity. According to Luo et al. (2005), unclear regulations enable government officials to engage in corrupt activity and take advantage of vulnerabilities in the rules. Policies that can be reasonably executed and applied are defined as fair. Complexity, on the other hand, is a set of difficult-to-understand legislation and socio-cultural circumstances that lead to individuals participating in a corrupt activity (Luo et al. 2005; Pillay and Kluvers 2014).

2.1.2. Resource-Based View Theory

The resource-based view theory was primarily concerned with opportunities based on the exceptionality of resources that would result in competitive advantages (Asa and Prasad 2014). The study improved understanding of the study’s framework and tactics that focus on long-term franchising improvement by emphasizing management awareness. The resource-based view theory, while retaining the dynamic competencies theory, stated that decision-making authors required a very necessary basis to clarify how an enterprise’s culture of openness and innovation grows into timely, dramatic, or qualifications versatility in vibrant markets (Darcy et al. 2014; Kiiru 2015; Laukkanen et al. 2013). The resource-based view of the firm and the concept of long-term competitive advantage are frequently absent from the culture of SMEs, which is characterized by a distressing effort toward sustainability and development (Kiiru 2015).
Resource-based theory helps to understanding how SMEs respond to environmental shocks such as the pandemic-like COVID-19 and its impacts. According to the resource-based approach, the reason for partnerships arises from the value-creation potential of business resources gathered (Laukkanen et al. 2013). These strategic resources can serve as a basis for developing company skills that will lead to greater performance over time. As a result, the theory is utilized to envision how SMEs are with the rippling impact of COVID-19 on economic industries, and their preservation is becoming more crucial than ever.

2.1.3. Diffusion of Innovation (DOI) Theory

Darcy et al. (2014) derived the Diffusion of Innovations (DOI) theory from the perception of innovation and technological alignment to describe the concept of how innovation could be transferred between dissimilar people over time through various means (Guo et al. 2020; Winarsih and Fuad 2021). The theory of diffusion involves the establishment of innovative cultures that promote the efficacy of innovation competitive advantages that support the long-term growth of SMEs in a new market dynamic. The adoption of new advanced technologies and non-technological advancements are the biggest factors of SMEs’ long-term viability, competitive advantage, and efficiency (Leydesdorff and Meyer 2006; Price et al. 2013). As a result of the novelty display of practices and actions undertaken by enterprises and their innovation responsibilities, which lead to enterprise sustainability, achievement, and all-encompassing growth, various scientific research, primarily in the areas of SMEs, is thriving (Das and Teng 2000; Hadjimanolis 2019; Jia et al. 2020; Rogers 1995; Srisathan et al. 2020).

2.1.4. Stakeholders Theory

R. E. Freeman promoted the stakeholder theory, which has placed a strong emphasis on business ethics (Bahri et al. 2021). The stakeholder theory expresses concern about maximizing the value-added of stakeholder wealth to outperform competitors (Globerman and Shapiro 2003). As a result, sustainable industrial firms must cultivate a culture that integrates environmental, social, and economic systems into their mission-driven business practices (Al-Tit et al. 2019). In other statements, the company is founded to satisfy vendors, purchasers, clients, and workers as powerful stakeholders in the environment, economy, and society (Hammed 2018). In brief, local firms’ growth point to wellness reform efforts beyond just basic cultural fitness and work collaboratively to cultivate more flexible actions based on cultural capacity to comply with dramatic change (Neudorfer and Theuerkauf 2014). Once these principles are met, the sustainability processes will be attained, with businesses becoming attracted to make growth, mostly in the long run, to promote the ability of the organizational culture for the sustainable development of SMEs.
According to the principles of stakeholder theory and from the standpoint of business sustainability, the enterprise is a system whose life is dependent on its surroundings. Workers, consumers, residents, rivals, distributors, suppliers, and stockholders are all examples of stakeholders. Institutions such as banks, political authorities, monitoring groups, and others may also be considered stakeholders. As a result, the purpose of this study was to investigate the ramifications of stakeholder theory about political uncertainty in Ethiopia.

2.2. Empirical Literature Review

2.2.1. Political Instability and Its Effects on the Sustainable Growth of SMEs

The study’s econometric model results show that Ethiopian political instability has a negative and significant impact on enterprises’ innovativeness. Because of ongoing political unrest, businesses are unable to introduce new products and/or processes into their operations (Shitaye 2022). Political instability entailed an understanding of the disparities in power between the national elite who rule the country and the non-elites (Nyoni and Bonga 2018). The institutional environment in which enterprises operate is a major component of a political system. Political instability has a negative and significant impact on the national innovation system (Gregurec et al. 2021).
According to previous research, political chaos is a significant impediment to the growth of SMEs and the wider economic implementation of different nations (Allard et al. 2021; Fenetahun et al. 2021; Gregurec et al. 2021; Varsakelis 2006). Foreign direct investments, which are critical to the long-term growth of SMEs, can be difficult to attract in politically unstable countries (Al-Tit et al. 2019). Political instability, combined with massive corruption, is a common trend in Africa, resulting in deep underdevelopment and poverty (Nyoni and Bonga 2018). Ethiopia is currently one of the countries affected by political instability, which causes a budget shortfall, weakens collaborations between academics and practicing businesses, and reduces government spending on technology (Shitaye 2022).
Conflicts and political instability can indeed increase the risk of a systemic SMEs crisis. Our findings indicate that the political environment has a significant impact on the business performance of multinational corporations (Arezki and Gylfason 2013). According to a Nigerian study, the Nigerian political environment is characterized by frequent changes in government policies and programs, which hurt corporate long-term planning. This is due to party politics, which has resulted in threats of conflict and wars, rising levels of crime and terrorism, kidnapping, and bomb blasts, among other things, impeding business patronage and scaring away foreign investors from the country (Arezki and Gylfason 2013). As a result, high levels of corruption in politically volatile countries always create entry barriers for foreign-owned businesses. This fact may discourage the free flow of ideas while also limiting the innovativeness of local businesses. The following hypothesis is built based on these premises.
Political instability affects the performance of SME and statistically significant.

2.2.2. Corruption and Its Effects on the Sustainable Growth of SMEs

Corruption has previously been defined as the misuse of public authority for personal gain (Ahmad et al. 2020; Douglas et al. 2017). It is an unofficial payment that harms a company’s long-term viability (Glover et al. 2014). This research also investigated the contributing factors to misconduct in Ethiopia, such as poor governance, a lack of transparency and openness, a lack of democratic culture, an absence of clear regulatory requirements and authorizations, and a lack of institutional control, and how they affect the sustainable development of SMEs (Shitaye 2022). As a result, the aforementioned factors are currently having a significant impact on the sustainable development of Ethiopian SMEs. Even though there have been numerous studies on the topic of corruption and (poor) institutional quality, most existing studies used only one proxy, often in isolation, for corruption and other institutional quality indicators. Furthermore, statistical tests are generally conducted based on rather small and very specific samples, with a particular emphasis on Africa’s least developed countries (Teixeira and Guimarães 2015).
Enterprises’ awareness of recent developments and technological issues has a significant positive impact on their innovativeness. In this regard, access to the Internet, training, and foreign markets all have a positive and significant impact on the innovativeness of Ethiopian businesses. Furthermore, widespread corruption in government service delivery would exacerbate Ethiopia’s ongoing political instability. The difficult and complex corruption participation of government officials, as well as business owners and managers, significantly exacerbates the country’s long-term political instability. The strong correlation between widespread corruption and instability implies that corruption has a significant impact on business innovation (Shitaye 2022).
Rising corruption and political insecurity in West Africa contribute to underdevelopment by undermining government revenue, production, savings, investment, growth, and income distribution (Nimfa et al. 2021; Srisathan et al. 2020). According to (Alonso and Garcimartín 2013), corruption reduces enterprise innovativeness by increasing distrust and uncertainty in governmental institutions and the overall business environment. On the other hand, Varsakelis (2006) stated that corruption would have a lubricating and accelerating effect on the innovativeness of businesses, particularly in countries with poor governance systems. Corruption has a significant negative impact on innovation activities in many countries.
Considering that both social and economic inequality based on corruption have a statistically significant positive effect on the risk of ethnic war while holding all other variables constant, it was noted that high levels of corruption in politically unstable countries always create entry barriers for foreign-owned enterprises (Douglas et al. 2017). This fact may discourage the free flow of ideas while also limiting the innovativeness of local businesses. The debate over the relationship between corruption, political instability, and development is still ongoing.
The empirical literature on the destabilizing effect of political instability is relatively settled, but the effect of corruption on development has remained polarized. This is because some studies contend that corruption stifles development while others contend that, in some circumstances, corruption may be economically desirable simply because it provides a solution to inefficient regulation, bureaucratic delay, and bottlenecks, which may lead to ineffective governance. The study also discovered that implementing policies to ensure political stability and effective corruption control at the same time is ineffective and harms regional development (Nyoni and Bonga 2018). The following hypothesis is built based on these premises.
Corruption affects the performance of SME and statistically significant.

2.2.3. Coronavirus (COVID-19) and Its Effects on the Sustainable Growth of SMEs

The coronavirus has already had a significant impact on economic activity in every region of the world. COVID-19 has been declared a pandemic by the World Health Organization (WHO) in May 2020, and it has become a global emergency due to its impact on the entire global population and economy (Olana 2020). The world is witnessing the closure of each business activity and the stay-at-home principle by quitting various trading directions that can significantly impact the global economy (Gerald et al. 2020; Mamo 2020). The COVID-19 pandemic has had an impact on all economic sectors and institutions, including small and medium-sized enterprises (SMEs) (Cepel et al. 2020).
SMEs were the ones most vulnerable to the pandemic’s risks. Many countries worked hard to implement various financial and non-financial support measures to prevent temporary layoffs, such as reducing work hours, creating alternative jobs and workplaces, and enacting measures to protect self-employed people. Many countries worked hard to adopt measures to assist SMEs, such as searching for new work modes and markets, developing, and implementing various mentoring programs, and holding financial seminars (Eniola 2014).
Previous research on SMEs’ responses to the COVID-19 pandemic and performance enhancement has demonstrated that each strategy has an impact on the business (Cepel et al. 2020; Daneji and Bazza 2013; Gerald et al. 2020; Lambovska et al. 2021). The findings of Guo et al. (2020) emphasize the importance of innovation in assisting SMEs in addressing the challenges posed by the COVID-19 emergency. Similarly, Gerald et al. (2020) contended that involved calculated quickness alleviates the adverse effects of the COVID-19 downturn on SMEs’ achievement. These findings apply a managerial strategy to the practices of SMEs in responding to the crisis. Their findings are significant because they focused on the long-term performance of SMEs rather than the short-term performance of large corporations. However, the impact of these tactical responses on SMEs’ long-term performance and efficiency prospects requires further investigation.
SMEs in the service industry were dealing with the COVID-19 disruption and trying to gain insights into the drivers and technologies that influenced their response to the COVID19 pandemic. According to the literature review, the focus of SMEs’ transformational initiatives during the COVID-19 disruption shifted slightly from technology to social, customer, and organizational changes (Sanders 2017). The following hypothesis is built based on these premises.
COVID-19 pandemic affects the performances of SMEs and statistically significant.

2.3. Conceptual Framework

The conceptual framework shown in Figure 1 guides this study. The graph depicts the coronavirus, political insecurity, corruption, and inflation. The conceptual framework, on the other hand, hypothesizes that the above explanatory variables may have had an impact on small and micro-enterprises, as illustrated in the figure below.

3. Methodology

3.1. Research Approach

Both quantitative and qualitative research methods were used in the study. A mixed approach aids in the integration of various types of data in the same study and collecting diverse types of data best provides an understanding of a research problem (Creswell 2014; Post et al. 2020). These two approaches are frequently used in business and management research, particularly in the study of cause-and-effect relationships. The research under consideration was carried out using a mixed research approach; the rationale for combining both quantitative and qualitative data is to better understand the research problem by combining both numerical values from quantitative research and the detail of qualitative research, as well as to neutralize the limitations of using either approach alone. According to Creswell (2009), the mixed research approach employs separate quantitative and qualitative methods to compensate for the shortcomings of one method with the strengths of the other.

3.2. Research Design

This is a survey study with an explanatory research design. Explanatory designs attempt to establish cause-and-effect relationships to explain variance in the dependent variable or predict organizational outcomes. When the emphasis is on cause-and-effect relationships, the study can be explanatory, explaining which causes result in which effects (Yin 1994; Yin 2013). The primary goal of explanatory research design is to determine how events occur and which ones may influence specific outcomes. It also assists the researcher in planning and implementing the study in a way that will allow the researcher to obtain the desired results, increasing the chances of obtaining information that can be associated with the real situation (Myers et al. 2013). As a result, the study employed an explanatory research design.

3.3. Target Population

A population is a collection of elements from which a sample is drawn (Wahyuni 2012). As a result, the current employees of SMEs registered in Ambo town were the study’s target population. The sampling frame used in this study comprises 378 employees who are involved in working on SMEs legally registered.

3.4. Sample Size

As previously stated, the total population of the study is 378 employees, which is a sizable number. As a result, the sample size for the study was determined using the sample size determination formula developed by (Yamane 1967). Yamane’s sampling formula was used to determine sample respondents, with a 95 percent confidence level and a level of precision (e) of 5.
n = N ( 1 + N ( e ) 2
  • n = sample size
  • N = number of people in the population
  • e = allowable error (%)
Substitute numbers in the formula
n = 378 ( 1 + 378   ( 0.05 ) 2 = 194
After calculating the sample size using the Yamane formula, the study’s sample size of 194 is adequate to represent the population.

3.5. Sampling Techniques

The study used probability sampling based on the stratified random sampling technique. This method was chosen because the technique reduces sample selection bias and therefore ensures that certain segments of the population are not underrepresented or overrepresented. In the sampling procedure, the enterprises were stratified into four strata and the sample of each sector was determined by proportional sampling methods, as provided in the Table 1 below overleaf.

3.6. Sources of Data and Method of Data Collection

The study was primarily used to achieve the study’s goal. Structured questionnaires (both closed-ended and open-ended) and informative interviews were used to collect primary data.

3.7. Method of Data Analysis

As previously stated, the research is planned to use a mixed method. As a result, both qualitative and quantitative data analysis methods were employed. The qualitative method was used for the interview, whereas the quantitative analysis method was used for the survey questionnaire. After the data was collected, it was edited, coded, and analyzed using inferential statistics such as multiple linear regressions and Pearson Correlation, as well as a significance test of the variables, using the Statistical Package for the Social Science (SPSS version 23) software as the data analysis tool.

3.8. Model Specification

The Model is
Y = α + β 1 × 1 + β 2 × 2 + β 3 × 3 + ε
  • Y = SMEs Performance
  • β = Regression coefficient
  • X1 = COVID-19
  • X2 = Political Instability
  • X3 = Corruption
  • ε = Standard error.

3.9. Reliability and Validity Analysis

The scale’s reliability indicates how free the data is from random error. According to Hamed Taherdoost (2016), reliability is the degree to which a construct’s measure is consistent or dependable. Moreover, Hamed T. suggested four consistency cut-off points: outstanding consistency (0.90 and above), highly reliable (0.70–0.90), moderate reliability (0.50–0.70), and poor stability (0.50 and below). The greater the internal consistency of the scale items, the closer Cronbach’s alpha coefficient is to 1.0. Cronbach’s alphas were calculated to assess the reliability of each study variable. Because this reliability statistic is found to be greater than the minimum required threshold of 0.7, it is statistically acceptable. The Cronbach’s alpha value for all items indicated that the information gathered through questionnaires is reliable and can be used for further statistical analysis. Based on the results of the pre-test, the researcher attempts to rephrase some unclear questions without affecting the overall context of the instrument. Then, before distributing the questionnaires to the respondents, it was confirmed that those that passed the pre-test were effective in meeting the study’s objectives.

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.

7. Limitations and Future Research Directions

The study sample did not include all the country’s SMEs. It had primarily focused on SMEs found in only one region of the country’s specific zonal town. As a result, future research must consider SMEs in all regions of the country. Future research should focus on other industry-level factors influencing SME performance, in addition to corruption and political instability, and include other macroeconomic indicators such as unemployment ratio, recession, and boom impacts.

Author Contributions

Supervision: C.B.I.; comments on the manuscript at all stages: C.B.I. and A.D.; conceptualization: G.A., A.A. and A.D.; design: G.A. and A.A.; data acquisition: A.A.; analyzing and interpreting the data: A.A. and G.A.; writing the original draft: A.A. and G.A.; final review: C.B.I. and A.D. All authors have read and agreed to the published version of the manuscript.


This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.


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Figure 1. Conceptual framework of the study. Source: Own compilation from the related literature reviewed.
Figure 1. Conceptual framework of the study. Source: Own compilation from the related literature reviewed.
Economies 10 00189 g001
Table 1. Study Population and Sample.
Table 1. Study Population and Sample.
Respondent’s SectorsTarget PopulationSample PercentageSample Size
Service sectors12433%64
Manufacturing sectors6317%32
Construction sectors8623%44
Merchandising sectors10528%54
Total378 194
Source: own compilation.
Table 2. Reliability and Validity.
Table 2. Reliability and Validity.
Reliability Statistics
Cronbach’s AlphaCronbach’s Alpha Based on Standardized ItemsNo. of Items
Source: Survey results of 2022.
Table 3. Descriptive analysis.
Table 3. Descriptive analysis.
Descriptive Statistics
NMeanStd. Deviation
Political instability1944.21520.84045
Valid N (listwise)194
Source: Survey results of 2022.
Table 4. Model summary.
Table 4. Model summary.
Model Summary b
ModelRR SquareAdjusted R SquareStd. Error of the EstimateDurbin-Watson
10.942 a0.8860.8850.309010.121
a. Predictors: (Constant), COVID-19, Corruption, Political instability. b. Dependent Variable: performances of SMEs. Source: Survey results of 2022.
Table 5. Table of ANOVA.
Table 5. Table of ANOVA.
ModelSum of SquaresDfMean SquareFSig.
1Regression141.672347.224494.5670.000 b
a. Dependent Variable: performances of SMEs. b. Predictors: (Constant), COVID-19, Corruption, Political instability. Source: Survey results of 2022.
Table 6. Table coefficients.
Table 6. Table coefficients.
Coefficients a
ModelUnstandardized CoefficientsStandardized CoefficientstSig.
BStd. ErrorBeta
1(Constant)−0.9790.231 −4.2350.000
Political instability0.6780.1040.6276.5320.000
a. Dependent Variable: performances of SMEs. Source: Survey results of 2022.
Table 7. Sample test.
Table 7. Sample test.
One-Sample Test
Test Value = 0
TDfSig. (2-Tailed)Mean Difference95% Confidence Interval of the Difference
Political instability69.8561930.0004.215214.09624.3342
Performances of SMEs65.5251930.0004.280934.15214.4098
Source: Survey results of 2022.
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Abdissa, G.; Ayalew, A.; Dunay, A.; Bálint Illés, C. Determinants of Sustainable Growth of SMEs in Developing Countries: The Case of Ethiopia. Economies 2022, 10, 189.

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Abdissa G, Ayalew A, Dunay A, Bálint Illés C. Determinants of Sustainable Growth of SMEs in Developing Countries: The Case of Ethiopia. Economies. 2022; 10(8):189.

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Abdissa, Gemechu, Abebe Ayalew, Anna Dunay, and Csaba Bálint Illés. 2022. "Determinants of Sustainable Growth of SMEs in Developing Countries: The Case of Ethiopia" Economies 10, no. 8: 189.

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