Keywords

Owner manager, SME, Business Success, SDG

Introduction

Entrepreneurship is a key driver of economic growth and development, and has become an increasingly important avenue for creating employment opportunities in emerging economies (Abbas, Osunsan & Kibuuka, 2020). In Uganda, small and medium-sized enterprises (SMEs) make up the majority of the country's businesses, and play a critical role in driving economic growth and development. However, while SMEs have the potential to contribute significantly to economic development, many struggle to survive and achieve success. One factor that has been shown to influence the success of SMEs is the demographic characteristics of their owner-managers, such as their age, education level, and marital status (Osunsan et al, 2015).

In this paper, we examine the demographics of owner-managers and their influence on entrepreneurial performance in SMEs in Kampala, Uganda. We intend to investigate the link between owner-manager demographics and several indicators of business success (BS), such as firm growth, profitability, and sustainability (Isaga, 2015). We want to give insights into the elements that lead to successful entrepreneurship in the region through a study of the current literature on owner-manager demographics and business success, as well as a quantitative analysis of data obtained from SMEs in Kampala.

This study was aimed at to identifying the significant differences in business success with regards to (i) gender, (ii) age, (iii) marital status, (iv) education level and (v)work experience. Policymakers, company owners, and other stakeholders interested in fostering entrepreneurship and economic growth in Uganda should take note of our findings. By identifying the demographic features linked with business success, we intend to provide policymakers and other stakeholders with information on how to effectively assist SMEs in Kampala and other parts of Uganda. Furthermore, our findings may be valuable for Kampala company owners and prospective entrepreneurs, who can utilize this knowledge to better understand the aspects that will impact their success as entrepreneurs.

Literature Review

Business success

Business success may be defined as the extent to which an individual entrepreneur or a company endeavour meets its aims and goals, which may include financial profitability, growth, innovation, and social impact (Kolstad & Wiig, 2015). Personal happiness, market share, customer loyalty, employee satisfaction, and community participation are all subjective and objective metrics of success. A variety of elements determine business success , including the owner-manager's traits and talents, the quality of the business concept and strategy, the availability of resources, the competitive climate, and the regulatory and cultural background (Makhbul & Hasun, 2011). It is also a dynamic and ever-changing process in which entrepreneurs constantly adapt and learn from their experiences and problems in order to enhance their performance and achievements. Understanding the determinants and outcomes of business success is critical for promoting economic development, job creation, and social welfare, especially in emerging markets such as Kampala, Uganda, where entrepreneurship is a vital driver of growth and transformation (Suresh & Ramraj, 2012).

Business Success in SMES

Gender and Business success

Gender has been found to have a significant impact on business success. Research has shown that female entrepreneurs face unique challenges compared to their male counterparts, which can impact their ability to succeed in entrepreneurship (Peter & Munyithya, 2015). A study by Bullough, et al (2022) found that female entrepreneurs face challenges related to access to finance, social norms and expectations, and gender-based discrimination. These challenges can result in a lower level of business success for women. Similarly, research by Zolin, Stuetzer and Watson (2013) found that female-owned businesses tend to be smaller and less profitable than male-owned businesses, even when controlling for factors such as industry and business age. Other research, however, have indicated that gender can have a favorable impact on business success. According to Solesvik, Iakovleva, and Trifilova (2019), female entrepreneurs are more likely to have a social mission or reason for their firm, which can lead to better levels of happiness and motivation, as well as higher levels of consumer loyalty. Research by Anderson and Ojediran (2022) found that female entrepreneurs in developing countries, such as Uganda, face different challenges and opportunities compared to those in developed countries. In Uganda, female entrepreneurs face challenges related to access to finance, education, and business networks, but they also have opportunities to participate in government programs and initiatives aimed at promoting entrepreneurship. Finally, gender may have an impact on business success in both positive and bad ways. Female entrepreneurs may confront distinct hurdles in terms of access to capital, societal norms and prejudice, and other issues that might effect their capacity to thrive in business. Female entrepreneurs, on the other hand, may have specific qualities and possibilities, such as a social mission or access to government programs, that can help them succeed.

Owner Manager Age and Business success

Research on owner-manager age and business success has produced mixed findings. Some studies suggest that younger entrepreneurs may be more successful due to their higher levels of energy, risk-taking propensity, and adaptability to new technologies and market trends. For instance, Wennberg and DeTienne (2014) found that younger entrepreneurs are more likely to pursue innovative business models and take risks, which can lead to greater business success. Other research suggests that older entrepreneurs may be more successful because they have more experience, expertise, and social capital. According to Shane and Venkataraman (2000), elder entrepreneurs have more industry expertise and are better equipped to detect possibilities and create social networks that can assist their enterprises. Similarly, Kautonen, Luoto, and Tornikoski (2010) discovered that older entrepreneurs had a broader range of experience and expertise, which can assist them in making better decisions and navigating problems. Sarasvathy, Simon, and Lave (1998) suggests that successful entrepreneurs tend to rely on their experiences and expertise to recognize and exploit opportunities, rather than relying solely on novel or innovative ideas. This may suggest that older entrepreneurs, with their greater experience and expertise, may be more likely to achieve business success.

Marital Status and Business success

Several studies have been conducted to investigate the relationship between marital status and business performance. According to one viewpoint, a person's marital status might hinder their ability to establish and manage a successful business owing to the possible impact of family responsibilities and commitments on their time and finances (Cardella, Hernández-Sánchez & Sanchez Garcia, 2020). Other study, however, reveals that marriage might give support and resources that can improve an individual's capacity to establish and maintain a successful business (Cardella, Hernández-Sánchez & Sanchez Garcia, 2020). For example, Elam and Terjesen (2010) discovered that being married was positively connected to business success among Norwegian women entrepreneurs. According to the authors, this might be because married women receive greater social and financial support from their partners, helping them to overcome hurdles to business. Similarly, Bellou (2010) discovered that being married was connected with business success among self-employed women in Greece. Shinnar et al. (2014), on the other hand, discovered that being divorced or separated was inversely connected with business success among small company owners in the United States. The authors suggest that this may be due to the negative impact of divorce or separation on an individual's financial and emotional well-being, which can affect their ability to focus on and invest in their business.

Education Level and Business success

Several studies have examined the relationship between owner-manager education level and business success in small and medium-sized enterprises (SMEs). Education level can be seen as an important factor that affects the success of entrepreneurial ventures, as it may impact the owner-manager's knowledge, skills, and abilities to manage and grow their business (Peters & Brijlal, 2011).

Research has found mixed results regarding the relationship between education level and business success (Kolstad & Wiig, 2015). Some studies have found a positive relationship, suggesting that higher levels of education are associated with higher levels of business success (Kolstad & Wiig, 2015). For example, a study by Khelil et al. (2019) in Tunisia found that higher levels of education were positively associated with SME performance, as measured by profitability and growth. Similarly, Al Mamun et al. (2019) discovered that ownermanagers with greater levels of education had better financial performance and were more likely to provide new goods and services than those with lower levels of education in a study conducted in Bangladesh. Another study conducted in Pakistan by Mahmood et al. (2016) discovered that education level was connected with business success as evaluated by sales growth and profitability.

However, other studies have found a negative or no significant relationship between education level and business success (Dickson, Solomon & Weaver, 2008). However, there appears to be sufficient data to suggest a substantial and positive relationship between entrepreneurs' educational accomplishments and their entrepreneurial performance (Kolstad & Wiig, 2015). The relationship between education and the decision to pursue entrepreneurship, on the other hand, is less obvious and varies greatly among countries. When focused on specific nations, particularly developed economies, there appears to be a favourable association between an individual's degree of education and the possibility of selecting entrepreneurship. Surprisingly, the link is not linear, as people with at least some college education are more likely to start a business than those with greater levels of education (Kolstad & Wiig, 2015).

Work experience and Business success

According to Lerner et al. (1997), Fairlie and Robb (2008) and Meyer (2020) previous work experience of business owners is considered a positive determinant of business success and has a potential influence on various entrepreneurial factors. Their research suggests that prior work experience in a similar industry or the number of years of self-employment in that industry can significantly impact the performance of new startups. Osterman (1995) and Bishop (1996) emphasize that any work experience contributes to labour force development and economic success. Work experience benefits individuals, employees, and business owners by enhancing personal development, soft skills, and self-discovery. Soft skills, including teamwork, clear communication, system development, and presentation skills, are considered universally essential (Holzherr, 2013). Holzherr (2013) highlights the role of work experience in self-discovery, providing individuals with insights into their preferences and strengths within various career options and industries. This self-awareness, particularly gained at a younger age through diverse job experiences, benefits future entrepreneurs by guiding them in understanding their preferences and strengths across industries. Additionally, work experience is associated with more complex advantages, such as the development of critical thinking, leadership skills, and better coping mechanisms for work-related stress (Dragoni et al., 2014; Verhofstadt et al., 2017). Aldrich et al. (1989) emphasize the importance of work experience as a platform for networking, highlighting its significance on personal, professional, and social levels, which is crucial for business success. Contemporary studies also suggest that the number of years as a self-employed individual may influence entrepreneurial activity.

Methodology

The present study was directed towards a target population of 510 individuals, specifically sourced from 346 registered companies or businesses classified under the SME category in the Kampala central division. The sample set of companies represented three distinct business sectors: trade, service, and manufacturing. The sample size was established utilizing the Krejcie and Morgan's (1970) table, which provides practical ratios in accordance with the SME population size. As per the table, a sample size of 217 was recommended; nevertheless, the study managed to obtain a response rate of 193, which is deemed acceptable. The research surveyed ownermanagers or their representatives from the SMEs, utilizing closed-ended questionnaires. The validity of the questionnaire was ensured through the Content Validity Index (CVI) which was 0.850. As per Amin (2005), the instrument should be valid with a C.V.I of 0.7 or above in this study it was 0. 863. Furthermore, the reliability of the questionnaire was tested using Cronbach Alpha, which was found to be above 0.7, signifying that the survey instruments were reliable (Park, 2021). To establish the influence of age, gender, work experience, education level on business success an independent t test and One Way ANOVA was used to assess differences Dickson, Solomon and Weaver (2008).

Findings

Response rate

The targeted number of questionnaires was 181, and the actual responses received were 165, resulting in a response rate of 91.0%. For interviews using guides, the targeted number was 36, and 28 responses were obtained, yielding a response rate of 77.7%. In total, considering both questionnaires and interviews, the targeted number of respondents was 217, and the total number of responses received was 193, resulting in an overall response rate of 88.9%. This response rate was above the recommended two-thirds (67%) response rate by Flick (2009). This indicated that the researcher was able to obtain enough data for a comprehensive report.

Profile of Respondents

The demographic characteristics of the respondents can be summarized as follows. In terms of gender, 55.4% of the respondents were male, while 44.5% were female. Regarding age groups, there were no respondents in the 10-19 age category. The age distribution showed that 11.9% of the respondents were in the 20-29 age group, 24.8% in the 30-39 age group, 33.1% in the 40-49 age group, and 30.05% were above the age of 50. In terms of education, 56.5% of the respondents held a bachelor's degree, 23.3% had a master's degree, and 1.03% held a PhD. Additionally, 7.77% had less than a year of working experience, 20.72% had 1-2 years of experience, 53.88% had 3-5 years of experience, and 17.61% had 5 years and above of working experience s (Kautonen, Luoto and Tornikoski, 2010; Sarasvathy, Simon and Lave, 1998).

Descriptive Statistics

Figure 1 shows the mean value of 4.25 indicates that the data tends to cluster around this central value. This means that, on average, the majority of data points in the dataset are close to 4.25. The standard deviation of 0.101 provides information about the dispersion or spread of the data. With a relatively small standard deviation, it suggests that the values in the dataset are tightly clustered around the mean of 4.25. This indicates that there is less variability or deviation from the mean (Elam and Terjesen, 2010; Bellou, 2010).

Differences in demographics and Business success in SMEs

Gender and Business success in SMEs

Table 1 & 1a shows independent-samples t-test was conducted to compare the Business success for males and females Wennberg and DeTienne (2014). Since the Levene’s Test for Equality of Variance is less than .05, this means the variance of the two groups (male/female) are not the same Kolstad and Wiig (2015). Thus, Equal variances not assumed. There was no significant difference in business success levels for males (M=4.27, SD=.16) and females [M=4.27, SD=.23; t (295.94) =-.452, p=.65]. The magnitude of the differences in the means was very small (eta squared=.006) Mahmood et al. (2016) and Al Mamun et al. (2019).

Table 1 Group Statistics
BS	Gender	N	Mean	Std. Deviation	Std. Error Mean
	Female	89	4.2565	0.08844	0.00937
	Male	104	4.2513	0.11022	0.01081

Table 1a Independent Samples Test
			Business success
			Equal variances assumed	Equal variances not assumed
Levene's Test for Equality of Variances	F		4.283
	Sig.		0.039
t-test for Equality of Means	t		-0.446	-0.452
	df		327	295.944
	Sig. (2-tailed)		0.656	0.652
	Mean Difference		-0.0098	-0.00982
	Std. Error Difference		0.02201	0.02173
	95% Confidence Interval of the Difference	Lower	-0.0531	-0.05258
		Upper	0.03348	0.03294

Owner Manager Age and Business success in SMEs

The ANOVA table (2 & 2a) shows that there is no significant difference between the mean scores of Business success across different age groups, as the F-ratio is only 0.279, with a p-value of 0.840. The Tukey HSD post-hoc test, which is conducted to compare the mean scores of Business success between different age groups. The results indicate that there are no significant differences in mean scores between any of the age groups, as all p-values are greater than 0.05 (Cardella, Hernández-Sánchez & Sanchez Garcia, 2020). Overall, the results suggest that there are no significant differences in the Business success scores across different age groups.

Table 2 Descriptives
Age	N	Mean	Std. Deviation	Std. Error	95% Confidence Interval for Mean		Minimum	Maximum
					Lower Bound	Upper Bound
20-29	39	4.2586	0.09084	0.01455	4.2292	4.2881	4.04	4.43
30-39	56	4.2438	0.11803	0.01577	4.2122	4.2754	3.96	4.65
40-49	63	4.2595	0.10121	0.01275	4.234	4.285	4.09	4.48
50+	35	4.2534	0.07995	0.01351	4.226	4.2809	4.09	4.43
Total	193	4.2537	0.10054	0.00724	4.2394	4.2679	3.96	4.65

Table 2a Anova
Between Groups	Sum of Squares	df	Mean Square	F	Sig.
	0.009	3	0.003	0.279	0.84
Within Groups	1.932	189	0.01
Total	1.941	192

Marital Status and Business success in SMEs

Table 3 & 3a shows that there is no significant difference between the groups as the p-value is greater than the alpha level of 0.05. The multiple comparisons test using Tukey's HSD method also confirms that there are no significant differences between the groups. The mean differences between each group are very small and the confidence intervals all include zero. This suggests that, there is no evidence to suggest that marital status has a significant effect on the variable Business success.

Table 3 Descriptives
	N	Mean	Std. Deviation	Std. Error	95% Confidence Interval for Mean		Minimum	Maximum
					Lower Bound	Upper Bound
Single	71	4.2468	0.1023	0.01214	4.2226	4.271	3.96	4.43
Married	119	4.2572	0.10087	0.00925	4.2389	4.2755	4.09	4.65
Divorced	3	4.2754	0.0251	0.01449	4.213	4.3377	4.26	4.3
Total	193	4.2537	0.10054	0.00724	4.2394	4.2679	3.96	4.65

Table 3a Anova
	Sum of Squares	df	Mean Square	F	Sig.
Between Groups	0.006	2	0.003	0.308	0.735
Within Groups	1.935	190	0.01
Total	1.941	192

Tables 4 & 4a indicates that there was no significant difference in Business success scores between the education groups, with F (3, 189) = 0.645, p = 0.587 (Dragoni et al., 2014; Verhofstadt et al., 2017; Meyer, 2020). The multiple comparisons using Tukey's HSD test confirm that there were no significant differences in Business success scores between any of the education groups. All p-values were greater than 0.05. The means for each group were almost identical to those in the descriptive statistics table. The p-value for the Tukey HSD test was 0.486, indicating that there were no significant differences between the groups at a 0.05 significance level. In summary, the analysis suggests that there were no significant differences in Business success scores between the education groups. The mean scores increased with higher levels of education, but the differences were not statistically significant Zolin, Stuetzer and Watson (2013), Solesvik, Iakovleva, and Trifilova (2019) and Anderson and Ojediran (2022).

Table 4 Descriptives
	N	Mean	Std. Deviation	Std. Error	95% Confidence Interval for Mean		Minimum	Maximum
					Lower Bound	Upper Bound
Certificate	12	4.2283	0.11596	0.03348	4.1546	4.3019	4.09	4.39
Diploma	44	4.2441	0.09754	0.01471	4.2144	4.2737	3.96	4.48
Bachelor	84	4.2547	0.10502	0.01146	4.2319	4.2774	4.04	4.65
Masters	53	4.2658	0.09288	0.01276	4.2402	4.2914	4.09	4.48
Total	193	4.2537	0.10054	0.00724	4.2394	4.2679	3.96	4.65

Table 4a Anova
	Sum of Squares	df	Mean Square	F	Sig.
Between Groups	0.02	3	0.007	0.645	0.587
Within Groups	1.921	189	0.01
Total	1.941	192

Work Experience and Business success in SMEs

The results from table 5, 5a & 5b show that there is no significant difference in mean scores of business success es across different levels of "Working experience", as the p-value (Sig.) is greater than the alpha level of 0.05. The results of the multiple comparisons test (Tukey HSD) show that there are no significant differences in mean scores of Business success between any pairs of "Working experience" levels, except for the comparison between "Below 1year" and "1-2 years". The mean difference between these two groups is -0.06656, which is significant at the 0.05 level. Overall, the data suggests that there is no significant difference in mean scores of business success across different levels of working experience, except for the difference between "Below 1 year" and "1-2 years". However, as the group sizes are unequal, the researchers are cautious in interpreting the results.

Table 5 Descriptives
	N	Mean	Std. Deviation	Std. Error	95% Confidence Interval for Mean		Minimum	Maximum
					Lower Bound	Upper Bound
Below 1year	20	4.1957	0.11416	0.02553	4.1422	4.2491	4.09	4.39
1-2 years	65	4.2622	0.09991	0.01239	4.2375	4.287	4.09	4.65
3-5 years	80	4.2587	0.09483	0.0106	4.2376	4.2798	3.96	4.43
5+ years	27	4.2609	0.10161	0.01955	4.2207	4.3011	4.13	4.48
Total	192	4.2536	0.1008	0.00727	4.2393	4.268	3.96	4.65

Table 5a Anova
	Sum of Squares	df	Mean Square	F	Sig.
Between Groups	0.075	3	0.025	2.536	0.058
Within Groups	1.865	188	0.01
Total	1.941	191

Table 5b Multiple Comparisons
(I)Working experience	(J)Working experience	Mean Difference	Std. Error	Sig.	95% Confidence Interval
		(I-J)			Lower Bound	Upper Bound
Below 1year	1-2 years	-.06656*	0.02547	0.047	-0.1326	-0.0005
	3-5 years	-0.063	0.0249	0.058	-0.1276	0.0015
	5+ years	-0.0652	0.02939	0.122	-0.1414	0.011
1-2 years	Below 1year	.06656*	0.02547	0.047	0.0005	0.1326
	3-5 years	0.00351	0.01663	0.997	-0.0396	0.0466
	5+ years	0.00134	0.02281	1	-0.0578	0.0605
3-5 years	Below 1year	0.06304	0.0249	0.058	-0.0015	0.1276
	1-2 years	-0.0035	0.01663	0.997	-0.0466	0.0396
	5+ years	-0.0022	0.02217	1	-0.0596	0.0553
5+ years	Below 1year	0.06522	0.02939	0.122	-0.011	0.1414
	1-2 years	-0.0013	0.02281	1	-0.0605	0.0578
	3-5 years	0.00217	0.02217	1	-0.0553	0.0596
*. The mean difference is significant at the 0.05 level.

Conclusions and Recommendations

This study sought to explore the influence of gender, age, marital status, education level and work experience on variations of business success among owner-managers. With regards to the findings on gender, the analysis indicates no significant difference in business success between male and female respondents. Although the mean difference slightly favoured males, the effect size was negligible. This challenges stereotypes and underscores the potential for gender equality in business success as observed. They all argued that women generally face more challenges when it comes to attaining business success, though authors pointed out that woman tend to run businesses with social missions which can lead to better levels of happiness and motivation, but not necessarily financial success. Contrary to the findings of where youth in an advantage resulting from innovativeness and propensity to take risk, the analysis did not reveal significant differences in business success across age groups, the results prompt further exploration. This is further emphasised by the fact that other scholar suggesting that the lack of difference may originate from various factors such as experience level or industry dynamics, warranting deeper investigation into these potential influencers. Literature suggests a mixed result due to the fact that some believe that marriage enhances business success, while others observed it as an impediment. In this study marital status showed no significant impact on business success. The consistent mean scores across single, married, and divorced respondents suggest that personal relationship status may not be a decisive factor in business success within the context of Uganda. confirmed that research into the relationship between ownermanager education level and business success has found mixed results. Scholar such as suggest a positive influence, while authors observed the negative influence. The findings in this study indicate no significant difference in business success based on education level. Although mean scores increased with higher education, the lack of significant differences suggest that educational qualifications alone may not be a determinant of business success in the examined setting. As suggested by literature work experience plays a major role in business success. In the aspect of work experience in this study, the analysis uncovered a significant difference in business success between respondents with less than one year and those with 1-2 years of experience. This suggests that early-stage entrepreneurs might face unique challenges or exhibit distinct success metrics, warranting targeted support and investigation.

Based on the findings presented in this study, it can be concluded that the investigated demographic factors (gender, age, marital status, education level, and work experience), do not show significant differences in relation to business success, as measured by the Business success scores. The results of Levene's Test and subsequent t-tests for gender reveal no substantial variance between male and female groups. The same is true for analyses across different age groups, marital status, education levels, and work experience levels suggesting no statistically significant difference in business success scores. Although some mean differences exist, they are small in size and lack statistical significance, especially regarding age, marital status, and education level. The exception lies in the comparison between individuals with less than one year and 1-2 years of work experience, where a statistically significant difference in business success scores was observed. However, the caution is warranted due to unequal group sizes. At the core, these findings suggest a broad homogeneity in business success scores across varied demographic categories within the studied population, suggesting the need for a comprehensive understanding of business success that goes beyond these demographic variables.

Though this study provides quality insights into the relationship between owner-manager demographics and business success, there is more to be explore. This is due to the fact that the findings suggest that there are no variations in business success on the basis of the demographic characteristics of owner-managers. To enrich the understanding of the complexities between owner-manager demographics and business success, this study recommends a multifaceted approach. Qualitative studies should be conducted to investigate aspects, such as personal experiences and industry-specific challenges, which quantitative measures like that of this study may overlook. It is also recommended that longitudinal studies to track the entrepreneurial journey over time, offering insights into evolving success (or lack of) and the impact of changing demographics

References

Abbas, M. K., Osunsan, O. K., & Kibuuka, M. (2020). Social norms and entrepreneurial intent of graduating university students in north west Nigeria. European Journal of Business and Management Research, 5(2).

Indexed at, Google Scholar, Cross Ref

Al Mamun, A., Fazal, S. A., & Muniady, R. (2019). Entrepreneurial knowledge, skills, competencies and performance: A study of micro-enterprises in Kelantan, Malaysia. Asia Pacific Journal of Innovation and Entrepreneurship, 13(1), 29-48.

Indexed at, Google Scholar

Anderson, A., & Ojediran, F. (2022). Perspectives, progress and prospects; researching women’s entrepreneurship in emerging economies. Journal of Entrepreneurship in Emerging Economies, 14(2), 292-315.

Indexed at, Google Scholar, Cross Ref

Bullough, A., Guelich, U., Manolova, T. S., & Schjoedt, L. (2022). Women’s entrepreneurship and culture: gender role expectations and identities, societal culture, and the entrepreneurial environment. Small Business Economics, 58(2), 985-996.

Indexed at, Google Scholar, Cross Ref

Cardella, G. M., Hernández-Sánchez, B. R., & Sanchez Garcia, J. C. (2020). Entrepreneurship and family role: a systematic review of a growing research. Frontiers in psychology, 10, 2939.

Indexed at, Google Scholar, Cross Ref

Dickson, P. H., Solomon, G. T., & Weaver, K. M. (2008). Entrepreneurial selection and success: does education matter?. Journal of small business and enterprise development, 15(2), 239-258.

Indexed at, Google Scholar, Cross Ref

Haykir, Ö., & Çelik, M. S. (2018). The effect of age on firm’s performance: evidence from family-owned companies. Ömer Halisdemir Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 11(2), 129-137.

Indexed at, Google Scholar, Cross Ref

Isaga, N. (2015). Owner-managers' demographic characteristics and the growth of Tanzanian Small and medium enterprises. International Journal of Business and Management, 10(5), 168.

Google Scholar, Cross Ref

Kautonen, T., Luoto, S., & Tornikoski, E. T. (2010). Influence of work history on entrepreneurial intentions in ‘prime age’and ‘third age’: A preliminary study. International small business journal, 28(6), 583-601.

Google Scholar, Cross Ref

Kolstad, I., & Wiig, A. (2015). Education and entrepreneurial success. Small Business Economics, 44, 783-796.

Indexed at, Google Scholar, Cross Ref

Mahmood, R., Zahari, A. S. M., Ibrahim, N., Jaafar, N. F. H. N., & Yaacob, N. M. (2021). The impact of entrepreneur education on business performance. Asian Journal of University Education, 16(4), 171-180.

Google Scholar, Cross Ref

Makhbul, Z. M., & Hasun, F. M. (2011). entrepreneurial success: An exploratory study among entrepreneurs. International journal of business and management, 6(1), 116.

Google Scholar

Mallinguh, E., Wasike, C., & Zoltan, Z. (2020). The business sector, firm age, and performance: The mediating role of foreign ownership and financial leverage. International Journal of Financial Studies, 8(4), 79.

Indexed at, Google Scholar, Cross Ref

Meyer, N. (2020). The impact of work experience on selected entrepreneurial factors. Polish Journal of Management Studies, 22(2), 247-260.

Indexed at, Google Scholar, Cross Ref

Osunsan, O. K., Kinyatta, S., Baliruno, J. B., & Kibirige, A. R. (2015). Age and performance of small business enterprises in Kampala, Uganda. International Journal of Social Science and Humanities Research, 3(1), 189-196.

Indexed at, Google Scholar

Peter, P. W., & Munyithya, H. M. (2015). The gender factor influence on entrepreneurial successin Kitui County, Kenya. International Journal of Education and Research, 3(7), 13-32.

Google Scholar

Peters, R. M., & Brijlal, P. (2011). The relationship between levels of education of entrepreneurs and their business success: a study of the province of KwaZulu-Natal, South Africa. Industry and higher education, 25(4), 265-275.

Indexed at, Google Scholar, Cross Ref

Rossi, M. (2016). The impact of age on firm performance: A literature review. Corporate Ownership & Control, 13(2), 217-223.

Google Scholar

Sarasvathy, D. K., Simon, H. A., & Lave, L. (1998). Perceiving and managing business risks: Differences between entrepreneurs and bankers. Journal of economic behavior & organization, 33(2), 207-225.

Indexed at, Google Scholar

Shane, S., & Venkataraman, S. (2000). The promise of entrepreneurship as a field of research. Academy of management review, 25(1), 217-226.

Google Scholar, Cross Ref

Solesvik, M., Iakovleva, T., & Trifilova, A. (2019). Motivation of female entrepreneurs: a cross-national study. Journal of Small Business and Enterprise Development, 26(5), 684-705.

Indexed at, Google Scholar, Cross Ref

Suresh, J., & Ramraj, R. (2012). Entrepreneurial ecosystem: Case study on the influence of environmental factors on entrepreneurial success. European Journal of Business and Management, 4(16), 95-101.

Google Scholar

Wach, D., Stephan, U., Gorgievski, M. J., & Wegge, J. (2020). Entrepreneurs’ achieved success: developing a multi-faceted measure. International Entrepreneurship and Management Journal, 16, 1123-1151.

Indexed at, Google Scholar, Cross Ref

Wennberg, K., & DeTienne, D. R. (2014). What do we really mean when we talk about ‘exit’? A critical review of research on entrepreneurial exit. International Small Business Journal, 32(1), 4-16.

Indexed at, Google Scholar, Cross Ref

Zolin, R., Stuetzer, M., & Watson, J. (2013). Challenging the female underperformance hypothesis. International Journal of Gender and Entrepreneurship, 5(2), 116-129.

Indexed at, Google Scholar, Cross Ref

Received: 21-Apr-2024, Manuscript No. AEJ-24-145875; Editor assigned: 24-Apr-2024, PreQC No. AEJ-24-145875 (PQ); Reviewed: 09- Apr-2024, QC No. AEJ-24-145875; Revised: 14-May-2024, Manuscript No. AEJ-24-145875 (R); Published: 21-May-2024