Evaluating Inspiring Factors and Obstacles in the Start-Up of Owned Agri-Preneurial Businesses: Underlying Evidence from South Africa

Abstract

Contemporary economies worldwide appreciate the underlying importance of service sectors, culminating in sectorial growth and satisfactory performance of agri-preneurship. This study is premised on two simple explanations that cascaded into two hypothetical questions: (i) Are there inspiring factors for individuals to start up their own agri-preneurship business? (ii) Are there factors hindering individuals from starting up their own agri-preneurship business? These two hypothetical constructs triggered four primary arguments established in the study. This study was conducted in Mbombela local Municipality in category ‘B’, which is made up of the Ehlanzeni District, Mpumalanga South Africa. From a population of 1021 farmers, 458 samples of respondents were obtained and considered to be realistic for the study. The study embraced the mixed research approach, and the field survey was done between the months of February 2022 and June 2022. Descriptive statistics, involving the frequency count and percentages, were used to determine the motives and obstacles of starting up one’s own business. The hypothesis was assessed by employing multinominal logistic regression to determine the relationship between demographic variables and predictor variables. The findings revealed that potential agri-preneurs are affected by an array of inspiring factors in the decision-making process. Further, the results revealed that agri-preneurial spirit is inhibited by numerous challenges. In the shared view of respondents, there was a portmanteau of obstacles impeding the commencement of one’s own business. The results also showed that, in the self-realization variant, age (p < 0.035) and marital status (p < 0.033) were found to be correlated and statistically significant as an inspiration for setting up an agri-preneurship business, while the self-satisfaction variant specified marital status (p < 0.001) to be significant and to negatively (β −1.564) influence inspiration for agri-preneurship. In the independence variant category, two crucial variables, level of formal education (p < 0.005) and farm experience (p < 0.007), were found to be correlated and statistically significant in determining agri-preneurial decisions. This study has several policy propositions: the government and allied stakeholders must consider the motives that inspire potential investors in agriculture. The government must also oversee the reasons for young and old agri-preneurs leaving agri-businesses because of failure. This study underscores the need to subjectively analyze agri-preneurial inspiring factors and obstacles to performance. The contributions of agri-preneurial businesses to economic growth and poverty alleviation justify the need for a concerted effort to motivate potential investors. Another pertinent contribution of the study is highlighting the obstacles of agri-preneurs to enable the government to support and prepare responsive, innovative, and resilient agri-preneurs in South Africa. This paper recommends that starting up one’s own agri-preneurial business is a good idea for abating hunger and unemployment.

1. Introduction

Entrepreneurial prospects portend an enduring policy discourse in South Africa, which hitherto is comparable to other Sub-Saharan African countries. The outlook of farm businesses appears daunting. Nevertheless, farming businesses are pertinent to local entrepreneurship development, with farmers exhibiting laudable potential for success (Juma and Spielman 2014). The inspiring drive to unlock agri-preneurship is critical for food security, poverty reduction, economic growth, and sustainable development (Díaz-Pichardo et al. 2012). However, given the multiple dimensions and ideas of scholars about the concept of entrepreneurship, a plethora of definitions has emerged over time, implying that there is a need for the further analysis of theories appropriate to the concept. There is no single acceptable definition of entrepreneurship (Maluleke 2016), let alone agri-preneurship, and this highlights the subjective multidimensionality of the concept (Frese and Gielnik 2014). In relation to agriculture, entrepreneurship is often denoted as “agri-preneurship”, which simply suggests the application of conventional entrepreneurship principles and practices to agriculture (Wale and Chipfupa 2021; Mukembo and Edwards 2016). Therefore, from the viewpoint of the authors in this study, two explanations have emerged and become pertinent. One is that agri-preneurship is considered a business venture related to agriculture for survival. Secondly, it is the coordination and putting into effective use of all farm operations from production, distribution of farm supplies, processing, and marketing. Therefore, our study is premised on these two remarkably simple explanations that cascade into two hypothetical questions:

(i) Are there inspiring factors for individuals to start up their own agri-preneurship business? (ii) Are there factors hindering individuals from starting up their own agri-preneurship business?

These two hypothetical constructs triggered four primary arguments established in this study.

Firstly, the argument here is how important is agri-preneurial business. In Sub-Saharan Africa, agri-business contributes towards alleviating poverty 2–4 times more than other sectors of the economy. The importance of agri-preneurship to the economy of South Africa is remarkable, providing income for rural households, employment generation, and raw materials for industries. In South Africa, the role of agri-preneurship is central given the increase to prominence over inequality, poverty, and food security. However, the agri-business sector accounts for less than 2.5% of the national GDP and contributes about 4.6% to labor (Ogujiuba et al. 2023; Statistics South Africa 2015). Current economies worldwide appreciate the underlying importance of service sectors culminating in sectorial growth and satisfactory performance in agri-preneurship. The contributions of agri-preneurial businesses to economic growth, poverty alleviation, and foreign exchange justify the need for a concerted effort to motivate potential investors. As noted by Abisuga-Oyekunle et al. (2019), while mirroring the contributions of SMEs to poverty alleviation, income creation, and investment growth, the authors asserted that about 17% of small and medium enterprises (SMEs) had access to funds in variance to 70% demand, implying a potential obstacle in the sector. Similar studies (Al-Tit et al. 2019; Ogujiuba et al. 2021) opined that start-up funds remain the basis for SME entrepreneurial success. Therefore, entrepreneurial orientation that encompasses the imbibing of innovation, risk management, and other initiative-taking activities to gain a competitive advantage in agri-preneurship investment must be encouraged primarily for poverty alleviation and the creation of services (Dai and Si 2018; Wang et al. 2016; Qodriah et al. 2021).

The second argument is that entrepreneurship accounts for a larger proportion of numerous existing ventures. SMEs are the driver of industrialization for both developed and developing countries. About 2.6 million SMEs exist in South Africa and about 37% are presumed to be formal, while 54% are micro-enterprises with 15% thriving in rural communities (OECD 2022). Nevertheless, SMEs account for over 95% of all businesses in developing countries, signifying their pertinent role in livelihoods and investment success (Fjose et al. 2010). Hitherto, SMEs provide about 53% of USA’s GDP, while in the UK, they provide almost 62% of total employment and contribute to over 25% of GDP (Baldacchino and Fairbairn 2006; Day 2000). Also, in China, the contribution of SMEs accounts for at least 80% of employment and 60% of GDP (Sham 2014).

Thirdly is the existence of ‘Death Valley’ syndrome for new SMEs. Death Valley is the time between initial business start-up and when the business begins to generate stable revenue. Although young agri-preneurs receive support from friends, relatives, and the government, only a small number achieve success in their first four years of operation owing to a mirage of challenges. In South Africa, for instance, around 70% of SMEs collapse in their first 5–7 years of operation, which suggests that SMEs in South Africa are basically nascent and emerging in nature (Bushe 2019). The low ratio of SME survival portrays potential constraints in regenerating the business economy to cushion the impact of unemployment and inequality in South Africa.

Fourthly, there are a plethora of arguments about the high rate of potential agri-preneurs totting up courage to invest in agriculture. In South Africa, about 4.4% of businesses have a direct form of access to credits compared to 20% in Sub-Saharan Africa. In addition, the Venture Capital (VC) investment subsidy also increased from 70 million in 2019 to 82 million in 2020, with 74% of these subsidies and investment in the hands of new and young investors (OECD 2022). Considering these four arguments, this study addresses the inspiring factors and obstacles to starting up an agri-preneurship business in South Africa.

This study underscores the need to subjectively analyze agri-preneurial inspiring factors and obstacles to performance. In South Africa, the contributions of SMEs account for over 2 million of existing industries and constitute 98% of total businesses. Though SMEs have experienced a two-digit growth and provided less than a third of formal jobs in the passing years, their performance in ameliorating unemployment is substantial. Worthy of note is the initiative-taking of entering into agri-businesses by individuals driven by unemployment. This unguided entrance has prompted the majority to remain as an informal sector and kept an exceptionally low business aspiration with an abysmal rate of failure.

Another pertinent contribution of the study is the highlighting of obstacles, profiling solutions to the government to support and prepare responsive, innovative, and resilient agri-preneurs in South Africa. Nevertheless, youth joblessness is alarming and unabated, culminating in poverty and inequality that hitherto has been exacerbated by the COVID-19 pandemic. Therefore, starting up one’s own business is a panacea to abating hunger and unemployment. In South Africa, agri-preneurial spirit is inhibited by an array of challenges encompassing inadequate access to funds, formal markets, inadequate marketing channels, improper product branding skills, unstable infrastructure, as well as insufficient administrative skills and training (UNCTAD 2023). According to (Wale and Chipfupa 2021; Herrington and Kew 2017), the global entrepreneurship monitors’ report indicated that only 10.1% of South Africans have an entrepreneurial plan, with only 2.9% capable of starting up an agri-preneurial business. Although this report is bleak and worrisome, it emphasizes the relevance of conducting more cutting-edge research on agri-preneurial improvement in South Africa. Smith and Beasley (2011) recognized numerous constraining factors: inadequate business knowledge, minimal support from the government, inadequate finance, and a lack of experience. However, establishing a business is fundamentally dependent on the personal initiatives of a potential entrepreneur. It is conventionally conceded that the reasons individuals start-up businesses are primarily economic reasons, while other inspirational factors are overlooked. On the contrary, this common perception is flawed because the reasons for starting up one’s own business are not only for money or economic motive (Carsrud and Brännback 2009; Wagner and Ziltener 2008). Thus, if starting up one’s own business is a product of personal desire, it will be very fascinating for this study to further investigate the subjective perception, as well as inspiring factors and obstacles, in the start-up of an owned agri-preneurial business in South Africa. In addition, this study adds to existing knowledge by highlighting inspiring factors for the start-up of one’s own business, analyzing obstacles and the profile solution of the government towards responsive and resilient agri-preneurs in South Africa.

Against this backdrop, this study examined the critical inspiring factors for individuals to start up an agri-preneurship business and educed the obstacles impeding agri-preneurship in South Africa.

Theoretical Framework

According to the economic theory, motivation is the primary driver of entrepreneurial initiatives since entrepreneurs are rational and willing to redistribute resources in response to the level of incentives received (Schultz 1980). This theory explains how entrepreneurs restore equilibrium and maximize profit by adding value to products, with the aim of gathering a competitive advantage over other actors in the market (Baumol 1990). Numerous empirical studies (Brownlee 2007; Hausfeld et al. 2020) in development economics have supported the deficiency of neoclassical economics to justify entrepreneurial behavior in making decisions. However, the aim of entrepreneurs is to diversify and adapt strategic decision-making processes to achieve their set goals. Furthermore, Hausfeld et al. (2020) suggested three flexible but robust approaches to decision making. But this approach did not completely address the decision needs of entrepreneurs. Hence, the economic theory appears to be one of the theories that elucidates the limited investment activities in agri-preneurship.

The resource-based theory of entrepreneurship encapsulates the sustainable livelihood framework, as postulated by Chambers and Conway (1992). Studies by Barney (1991) and Alvarez and Busenitz (2001) found that access to or lack of material and non-material assets, as well as the policy environment, assist in promoting and enhancing entrepreneurial drive. The resource-based theory focused on heterogeneousness because of variations in natural endowment influencing entrepreneurial intention. As noted by Carter and May (1999), the challenges of making use of endowed factors vary, particularly in a rural context.

The opportunity-based theory resonates in the recognition of opportunities and resources that are either neglected or under-exploited within the business environment. The two-way process of entrepreneurship encompasses the identification and creation of opportunities, and the final exploitation of identified opportunities (Alsos et al. 2011). However, entrepreneurs are not agents of change but only apply the principles of change for the exploitation of opportunities that accompany change (Singh et al. 2013). Any unsatisfied market gap creates an entrepreneurial opportunity recognized as a motivation for action. The inadequate entrepreneurial drive amongst SMEs is due to a lack of visible opportunities and insufficient motivation. In some instances, opportunities may be identified by entrepreneurs, but the small size of their existing operations and the lack of resources often pose a hindrance to taking advantage of such opportunities.

The subsistence theory explains the instinct and drive for the survivalist enterprise in the informal economy. Subsistence entrepreneurs, although marginalized, engage in activities that strive to give services to underprivileged societies to make ends meet. These categories of entrepreneurs are disposed to serving the poor and, by doing so, contribute to the formal economy (Ratten et al. 2019). These categories of entrepreneurs are also often found at the bottom of the pyramid with meagre resources but are engulfed in entrepreneurial pursuits to address and answer basic survival questions in response to meeting the needs of people. The subsistence theorist exhibits the characteristics of survivalist enterprise by contributing to poverty alleviation on a local level (Viswanathan et al. 2014; Berner et al. 2012). Ironically, subsistence entrepreneurs accept an optimum level of performance as the growth potential into mainstream entrepreneurs is limited by numerous factors.

The psychological theory expresses the behavioral theory of the firm, which postulates that behavior is learned through interaction with the environment. In the case of entrepreneurs, the environment where they operate influences their actions and decisions. Action in this instance denotes behavior in response to a stimulus, such as opportunities. According to the theory of planned behavior (Ajzen 1991), intention foretells human behavior, and is contingent on the belief held by an individual towards an identifiable behavior. Additionally, studies (Agholor 2019; Forouzanfar et al. 2016) have observed that some socio-demographic variables were associated with the adoption behavior of farmers in the use of innovative practices. The purpose of the psychological theory of entrepreneurship is to illustrate the behavioral factors that provoke or inspire individuals to become entrepreneurs (Zimmerman and Chu 2013), focusing on the rationale for achievement, pride of ownership, disposition, and willingness to take risk (Kerr et al. 2018).

The social theory gives an insight into the settings and nature of societal relationships and the factors that influence human behavior. The theory explains the context of entrepreneurship from an individual cultural perspective, which includes relationships, social networks, and ethnicity (Reynolds 1992). The theory considers a set of shared values that permits individuals to function together as a group with mutual trust to achieve a common goal. The relationship embedded in the social theory benefits individuals within a social group and adds value that an individual within a group cannot achieve on their own (Fairhead and Leach 2005).

In conclusion, all theoretical ideology expressed in context has only examined entrepreneurs and entrepreneurship based on perception and individual theorist observation and, therefore, may only provide limited views that do not entirely justify entrepreneurial phenomena. There is no one theory that is universally accepted as meeting the needs of agri-preneurs because there are multi-dimensional factors that determine investment drive. The synopsis of the theoretical framework is indicated below (

Table 1. Synopsis of theoretical framework.

1	Economic theory deals with motivation as the primary driver of entrepreneurial initiatives
2	The resource-based theory focuses on heterogeneousness because of variations in natural endowment influencing entrepreneurial intention.
3	The opportunity-based theory resonates as a recognition of opportunities and resources that are either neglected or under-exploited within the business environment.
4	The subsistence theory articulates the instinct and drive for the survivalist enterprise in the informal economy.
5	The psychological theory expresses the behavioral theory of the firm, which postulates that behavior is learned through interaction with the environment.
6	The social theory considers a set of shared values that permits individuals to function together as a group with mutual trust to achieve a common goal.

).

2. Literature Review

The existence of SMEs in all sectors of the economy exemplify their critical role in driving development, even though little is known in the literature about the immeasurable contributions of SMEs to economic growth (Fjose et al. 2010). The inadequate information, or lack thereof, could be linked to the invisibility and spread of SMEs in every sphere of the economy, thereby becoming a challenge to single them out from large or commercialized businesses. In Sub-Saharan Africa, informal micro-enterprises and agri-businesses are seen everywhere, contributing to the Gross Domestic Product (GDP) of each country (Benzing and Chu 2012). The contributions of SMEs to economic development cannot be overestimated, coupled with the fact that they assist in locating new and potential markets, thus utilizing them to their full advantage. SMEs remain pivotal in the discovery of new enterprises, culminating in income generation for millions of citizenries in Sub-Saharan Africa (Santarelli and Vivarelli 2007). In addition, SMEs are the basis of rural wealth creation and subsistence by accelerating demand for trade, investment, and goods and services (Amorós and Bosma 2014; Santarelli and Vivarelli 2007). The incubation of current ideas, inventing of innovative ideas, and marketing of new products within the supply chain is another vital role of SMEs in Sub-Saharan Africa.

A further role played by SMEs is the origination of latest ideas, risk detection, ceasing opportunities, and revolving them into fertile and realistic products (Longenecker et al. 2012; Rwigema and Venter 2004). Economic development can only be achieved in Sub-Saharan Africa if the appropriate business environment is established. Re-echoing the purposive contributions of SMEs in Sub-Saharan Africa, Fjose et al. (2010) in Muriithi (2017) asserted that SMEs from the informal sector account for only 20% of GDP in contrast to a 60% contribution to GDP in advanced nations of the world.

Failure of Agri-Preneurship Businesses

Research into the prospects and success of SMEs in Sub-Saharan Africa has been explored extensively, with only a few studies mirroring the obstacles experienced by agri-preneurs. Many SMEs in Sub-Saharan Africa are burdened with numerous challenges that have daunted their growth, and South Africa is not an exception (Kamunge et al. 2014).

According to Adcorp (2014), the failure rate of businesses in Saharan Africa is alarming, with five out of seven new businesses collapsing in their first year of start-up. For example, in Uganda, one-third of new businesses do not completely survive their first year of operation, while in South Africa about 75% fail to develop into reliable enterprises (Yeboah 2015; Husson et al. 2010). Inadequate capital for small businesses in South Africa has been expressed as one of the main causes of failure (Makina et al. 2015). The harsh conditions put in place by banks and other leading agencies, such as business strategies and approach, credit arrangement and the worthiness principle, and collateral and credit score, have been recognized as impeding factors to SMEs’ access to finance. According to Gebreslasie et al. (2011), training support and subsidies granted by the government to aid businesses in South Africa are grossly inadequate. In support of this assertion, Lekhanya (2015) emphasized that one of the obstacles prevalent in a high percentage of SME failure is attributable to insufficient training support.

The study by Ranhumise 2017 opined that the use of obsolete technologies in running businesses contributes to inefficiency, culminating in undue delay and, subsequently, failure. The application and use of modern technology, according to him, is vital in attaining a competitive advantage. Most recent technologies are not within the reach of entrepreneurs and are hardly ever used when available because of limited expertise. Institutional regulations are another obstacle to SME development, as these regulations are flexible and change over time in South Africa (Eze and Lose 2023). In support of this affirmation, Smulders and Naidoo (2013) also asserted that businesses are encumbered by the burden of compliance with government regulations in the form of byelaws and sometimes payments of dues and fines. Moreover, SMEs sometimes encounter excessive costs in the form of licensing and registration requirements, which add up to the start-up cost of a business (Kamara 2017). Another aching problem is the dearth of and inadequate infrastructure. For instance, an erratic power supply is discouraging and may increase the cost of running a business in South Africa. Sustainable economic growth must be supported by good infrastructure to promote SMEs and agri-preneurs (Arimah 2017).

On reflection, starting up a business is dependent on an array of reasons coupled with internal and external circumstances, with human rationality taken into consideration. In contrast to previous studies (Kamara 2017; Rankhumise 2017; Eze and Lose 2023), which merely focused on the challenges, prospects, and benefits of entrepreneurship, this study adopts a different bearing and X-rayed the inspirational factors and obstacles in the commencement of one’s own agri-preneurial business.

3. Materials and Methods

This study was conducted in Mbombela local Municipality in category B, which is made up of the Ehlanzeni District. This study embraced the mixed research approach, and the field survey was done between the months of February 2022 and June 2022. Prior to the survey, fifteen enumerators were trained to assist in data collection. We ran the pilot survey and pre-test of the questionnaire with only twenty-five farmers. This approach was pertinent to allow us to know and regulate the time spent in administering each questionnaire, and to modify areas that were ambiguous. The secrecy of respondents was assured, their rights and privileges were expressed, and they were informed of their voluntary participation. The participants’ liberty to withdrawal from the survey at any time was also carefully clarified. The ethical clearance certificate (with protocol number UMP/201740788/MAgric/2021) was obtained from the University of Mpumalanga.

3.1. Sample and Sampling Procedure

The sampled participants were farmers who had been farming for a minimum period of one year. This was pertinent to allow for the determination of interests and expressed motives for agri-preneurship. We surveyed the population of farmers in the area with the assistance of agricultural extension officers assigned to the area. In determining the sample size from a given population of 1021, the Taherdoost (2017) formular was used, while adhering to a confidence level of 95% and a margin of error 5%. Therefore, a sample size of 458 farmers was obtained and considered realistic for the study. The first section of the questionnaire displayed the demographic characteristics of the respondents; the second section covered the motives of becoming agri-preneurs and the sources of business ideas; and the last section presented the relationship between some demographic variables and motives of agri-preneurial intention, which included self-awareness and self-fulfillment, the possibility of higher returns, pride of ownership, independence in decision making, value affirmation, and social status. In determining these relationships, a multinominal regression analysis was employed. To avoid multicollinearity in the regression, a protection analysis test was conducted by applying the variance inflation factor [VIF] (Kyriazos and Poga 2023). Therefore, each predictor variable was regressed against other predictor variables, and any variable with a VIF ≥ 5 was expunged from the analysis (Vatcheva et al. 2016).

3.2. Multinominal Logistics Regression Model

The study employed the multinominal logistic regression model. The multinominal logistic regression model, which is also referred to as polytomous regression, is an expansion of the simple binomial logistic regression model. It is generally used when the dependent variable has more than two values that are nominal or unordered groupings. The study used the multinominal logistic regression analysis in determining the inspirational factors for agri-preneurship drive because the dependent variable was a dummy, with an assigned value of 1 or 0 indicating the presence or absence of an outcome. Previous studies (Liebenberg and Hoyt 2003; Van Gelderen et al. 2006) used a similar approach in evaluating the relationship for decision making. In addition, the multinominal logistic regression model provides a sufficient coefficient for the comparison of outcomes and handling of dependent variables with more groupings (Bayaga 2010).

3.3. Data Analysis

Furthermore, the Cronbach Alpha analysis, which justifies the internal consistency of instrument used, and the test-retest reliability, which shows the reliability of the questionnaire, gave acceptable values of 0.71 and 0.864 correspondingly. Data screening and cleaning, which involved editing and highlighting inadvertent errors of omission in values, were done to enhance the quality of information presented from the field survey. We used the 8-item construct to determine inspiration. Respondents were asked to choose from a list of inspiring factors with the following assigned values from 1 to 7: 1 = self-realization, 2 = self-satisfaction, 3 = the possibility of higher returns, 4 = pride of ownership, 5 = independence in decision making, 6 = social status, 7 = value affirmation, and 8 = pursuit of self-trial. In determining the obstacles besetting the starting up of one’s own business, respondents were required to select from a list of items with which they agreed. SPSS software version 28 was used for data analysis, which was separated into sections. Descriptive statistics, involving the frequency count and percentages, were used to determine the motives and obstacles of starting up one’s own business. The hypothesis was evaluated by employing a multinominal logistic regression to determine the relationship between demographic variables and predictor variables.

4. Results and Discussion

4.1. Descriptive Statistics

Descriptive statistics of demographic variables used in the study are presented in

Table 2. Descriptive statistics of demographic variables.

	Gender	Age	Level of Formal Education	Marital Status	Farm Size	Source of Income	Farm Experience	Household Size
Valid	458	458	458	458	458	458	458	458
Mean	1.6725	4.2271	1.924	1.5328	1.5153	2.4367	2.7096	1.9803
Gender
		Frequency		Percent	Valid Percent		Cumulative Percent
Valid	Male	150		31.1	32.8		32.8
	Female	308		63.9	67.2		100.0
	Total	458		95.0	100.0
Missing	System	24		5.0
	Total	482		100
Age
		Frequency		Percent	Valid Percent		Cumulative Percent
Valid	<20 years	21		4.4	4.6		4.6
	20–30 years	36		7.5	7.9		12.4
	31–40 years	58		12.0	12.7		25.1
	41–50 years	149		30.9	32.5		57.6
	51–60 years	91		18.9	19.9		77.5
	>61 years	103		21.4	22.5		100.0
	Total	458		95.0	100.0
Missing	System	24		5.0
Total		482		100.0
Level of Formal Education
		Frequency		Percent	Valid Percent		Cumulative Percent
Valid	No school	210		43.6	45.9		45.9
	Primary	94		19.5	20.5		66.4
	Secondary	133		27.6	29.0		95.4
	Tertiary	21		4.4	4.6		100.0
	Total	458		95.0	100.0
Missing	System	24		5.0
Total		482		100.0
Marital Status
		Frequency		Percent	Valid Percent		Cumulative Percent
Valid	Single	256		53.1	55.9		55.9
	Married	177		36.7	38.6		94.5
	Divorced	8		1.7	1.7		96.3
	Windowed	17		3.5	3.7		100.0
	Total	458		95.0	100.0
Missing	System	24		5.0
Total		482		100.0
Farm Size
		Frequency		Percent	Valid Percent		Cumulative Percent
Valid	<1 acre	234		48.5	51.1		51.1
	1–5 acres	212		44.0	46.3		97.4
	6–10 acres	12		2.5	2.6		100.0
	Total	458		95.0	100.0
Missing	System	24		5.0
Total		482		100.0
Source of Income
		Frequency		Percent	Valid Percent		Cumulative Percent
Valid	Salary	82		17.0	17.9		17.9
	Grant	169		35.1	36.9		54.8
	Pension	132		27.4	28.8		83.6
	Other	75		15.6	16.4		100.0
	Total	458		95.0	100.0
Missing	System	24		5.0
Total		482		100.0
Farm Experience
		Frequency		Percent	Valid Percent		Cumulative Percent
Valid	<5 years	122		25.3	26.6		26.6
	6–10 years	69		14.3	15.1		41.7
	11–15 years	87		18.0	19.0		60.7
	>16 years	180		37.3	39.3		100.0
	Total	458		95.0	100.0
Missing	System	24		5.0
Total		482		100.0

. A total of 458 participants took part in the survey. The percentage of female (67.2%) participants was more than that of male participants (32.8%), indicating that more females participated in the study. On average, farmers between the ages of 41 and 50 years recorded 32.5%, while younger farmers (≤20 years) recorded 4.4%. The majority of respondents (45.9%) had no formal education, while respondents who had primary, secondary, and tertiary education were 20.5%, 29.0%, and 4.6%, respectively. With respect to marital status, data revealed that single respondents were 55.9%, followed by married couples at 38.6%, and widowed at 3.7%. The majority of respondents (51.1%) cultivated farmland of ≤1 acre, depicting the level of subsistence farming in the area surveyed. However, other respondents who had farm sizes of 1–5 acres and 6–10 acres were 46.3% and 2.6%, correspondingly. The results also indicated that 36.9% of respondents received government grants to augment their farm income, while 28.8% depended on pension payout. Respondents with ≤5 years farm experience were 26.6%, while 6–10, 11–15, and ≥16 years were 15.1%, 19.0%, and 39.3%, respectively.

4.2. Sources of Agri-Preneurial Business Ideas

In our initial start-up of the analysis, we attempted to determine the perception of respondents about the sources of agri-preneurial ideas considered pertinent in starting up their own businesses (

Table 3. Sources of agri-preneurial business ideas.

		Frequency	Percent	Valid Percent	Cumulative Percent
Valid	Hobby	101	21.0	22.1	22.1
	Professional activities	41	8.5	9.0	31.0
	Personal dream	24	5.0	5.2	36.2
	Knowledge through research	68	14.1	14.8	51.1
	Media	39	8.1	8.5	59.6
	Friends and relatives	58	12.0	12.7	72.3
	Peers’ impression	38	7.9	8.3	80.6
	Inheritance	58	12.0	12.7	93.2
	Government programs	13	2.7	2.8	96.1
	Market survey	18	3.7	3.9	100.0
	Total	458	95.0	100.0
Missing	System	24	5.0
Total		482	100.0

). Four main sources were found to be crucial sources: hobby (22.1%), knowledge through research (14.8%), friends and relatives (12.7%), and inheritance (12.7%). Other sources of agri-preneurial business included personal dream (5.2%), media (8.5%), peers’ impression (8.3%), government programs (2.8%), and market surveys (3.9%).

4.3. Inspiration for Starting an Agri-Preneurial Business

The inspirational factors (

Table 4. Inspirational factors for starting up an agri-preneurial business.

	Inspiration	Frequency	Percent	Valid Percent	Cumulative Percent
Valid	Self-satisfaction	98	20.3	21.4	42.4
	Self-realization	96	19.9	21.0	21.0
	Social status	79	16.4	17.2	87.6
	Possibility of higher returns	56	11.6	12.2	54.6
	Pride of ownership of business	49	10.2	10.7	65.3
	Affirmation of value	30	6.2	6.6	94.1
	Pursuit of self-trial	27	5.6	5.9	100.0
	Independence in decision making	23	4.8	5.0	70.3
	Total	458	95.0	100.0

) accentuated as vital for starting up an agri-preneurial business were self-realization (21.0%), self-satisfaction (21.4%), the possibility of higher returns (12.2%), and pride of ownership (10.7%). However, factors that were less inspirational were independence in decision making (5.0%), social status (17.2%), affirmation of value (6.6), and pursuit of self-trial (5.9%).

4.4. Obstacles Hampering the Start-Up of One’s Own Agri-Preneurial Business

Reflecting on the importance of SMEs in both the economy and livelihoods, the government of South Africa produced a separate department to manage, facilitate, and organize the development of small businesses and entrepreneurship (Chimucheka and Mandipaka 2015; Eze and Lose 2023). In support of previous studies (Sharma and Madan 2013; Smith and Beasley 2011), the results of our study indicated that potential agri-preneurs who intend to start up their own businesses are exposed to several obstacles (

Table 5. Obstacles hampering the start-up of one’s own agri-preneurial business.

Obstacles	Frequency	%
Inadequate capital for start-up	61	13.3
Inadequate experience	56	12.2
Taxation and licensing	51	11.1
Fear of failure	31	6.8
Incessant changes to investment legislation	27	5.9
Unstable government and governance	26	5.7
Fear of competition	25	5.5
Inadequate assistance and advice concerning businesses	24	5.2
Unhealthy business environment and infrastructure	23	5.0
Exorbitant labor cost	21	4.6
Regulations concerning business registration	20	4.4
Psychological effects of being referred to as a farmer (a job for the dirty and poor)	19	4.1
Other	18	3.9
Inadequate business ideas	15	3.3
Inadequate market and access	14	3.1
IT knowledge and skills	14	3.1
Stereotype in farming (a job for a particular group or race)	11	2.4
Total	458	100.0

Source: Authors’ own survey.

). In the view of our respondents surveyed, the most serious obstacles were inadequate experience, inadequate capital for start-up, and fear of failure (Table 5).

Our results also indicated that fear of competition, inadequate business ideas, taxation and licensing, exorbitant labor cost, inadequate assistance and advice concerning businesses, incessant changes to investment legislation, an unhealthy business environment and infrastructure, unstable government and governance, and the psychological effects of being referred to as a farmer (a job for the dirty and poor) pose secondary challenges (Table 5). However, the obstacles in starting up one’s own agri-preneurial business remain a subject of discourse, as efforts by the South African government to ameliorate these totting challenges persist unabated.

4.5. Relationship between Demographic Characteristics and Inspirational Factors

In the processing summary to determine the relationship, the marginal percentages of each variable, as indicated in

Table 6. Case processing summary.

Case Processing Summary
	Inspiration for Starting Up an Agri-Preneurial Business		N (482)	Marginal Percentage
	Self-satisfaction		98	21.4%
	Self-realization		96	21.0%
	Social status		79	17.2%
	Possibility of higher returns		56	12.2%
	Pride of ownership of business		49	10.7%
	Affirmation of value		30	6.6%
	Pursuit of self-trial		27	5.9%
	Independence in decision making		23	5.0%
Valid			458	100.0%
Missing			24
Total			482
Sub-population			88 a
a. * The dependent variable has only one value observed in 5 (5.7%) sub-populations.
Model Fitting Information
Model	Model Fitting Criteria	Likelihood Ratio Tests
	−2 Log Likelihood	Chi-Square	df	Sig.
Intercept Only	1209.946
Final	1096.902	113.044	56	<0.001
Goodness-of-Fit
		Chi-Square	df	Sig.
Pearson		919.622	553	0.001
Deviance		803.114	553	0.001
Pseudo R-Square
Cox and Snell			0.219
Nagelkerke			0.223
McFadden			0.063
Likelihood Ratio Tests
Effect	Model Fitting Criteria	Likelihood Ratio Tests
	−2 Log Likelihood of Reduced Model	Chi-Square	df	Sig.
Intercept	1108.169	11.267	7	0.127
Gender	1104.081	7.179	7	0.410
Age	1128.716	31.813	7	0.001
Level of formal education	1109.808	12.906	7	0.074
Marital status	1128.366	31.464	7	0.001
Farm size	1101.388	4.486	7	0.722
Source of income	1098.993	2.091	7	0.955
Farm experience	1116.778	19.876	7	0.006

* Significance at 0.05, 0.001, and 0.01 for all independent variables. The chi-square statistic is the difference in −2 log-likelihoods between the final model and the reduced model. The reduced model is formed by omitting an effect from the final model. The null hypothesis is that all parameters of that effect are 0.

, were self-realization 21.0%, self-satisfaction 21.4%, the possibility of higher returns 12.2%, pride of ownership of business 10.7%, independence in decision making 5.0%, social status 17.2%, affirmation of value 6.6%, and pursuit of self-trial 5.9%. These useable observations were found in each of the outcome variable groups. The valid column, as indicated in the table, shows the number of observations in the data set with a sub-population of 88a (Bruin 2011).

Further, in our data analysis (Table 6), to determine the suitability of the multinominal logistic model employed in the study, findings show that the goodness-of-fit tests for both Pearson and Deviance residuals were ≤0.001, while Pseudo R-Square were Cox and Snell (0.219), McFadden (0.223), and Nagelkerke (0.063). These results suggest that the model adopted for the study fitted the data correctly. Previous studies (Allison 2014; Cox and Snell 1989; Hosmer et al. 2013) observed that Pearson and Deviance residuals, Pseudo R-Square (Cox and Snell; McFadden and Nagelkerke) with a value between 0 and 2, indicated that the model employed appropriately predicted the response variables. In this study, we therefore set the threshold for determining significance at 0.05, 0.001, and 0.01 for all independent variables.

4.6. Relationship between Independent Variables and Inspirational Factors

In this section, we evaluated the relationship between independent variables (gender, age, level of formal education, farm size, household size, source of income, and farm experience) and inspiration. The results show that in the self-realization variant, age (p < 0.035) and marital status (p < 0.033) were found to be correlated and were statistically significant as inspiration for setting up an agri-preneurship business (

Table 7. Self-realization.

Parameter Estimates
Inspiration for Starting Up an Agri-Preneurial Business a		B	Std. Error	Wald	df	Sig.	Exp.B.	95% Confidence Interval for Exp(B)
								Lower Bound	Upper Bound
Self-realization	Intercept	−0.210	1.837	0.013	1	0.909
	Gender	−0.066	0.530	0.016	1	0.900	0.936	0.331	2.644
	Age	0.573	0.271	4.466	1	0.035 *	1.774	1.042	3.020
	Level of formal education	0.442	0.312	2.007	1	0.157	1.556	0.844	2.868
	Marital status	0.740	0.346	4.563	1	0.033 *	0.477	0.242	0.941
	Farm size	−0.040	0.457	0.008	1	0.930	0.961	0.392	2.353
	Household size	−0.118	0.356	0.109	1	0.741	0.889	0.442	1.787
	Source of income	0.028	0.262	0.011	1	0.916	1.028	0.615	1.719
	Farm experience	−0.091	0.258	0.123	1	0.726	0.913	0.551	1.514

* Threshold for determining significance level is at 0.05, 0.001, and 0.01.

), while the self-satisfaction variant specified marital status (p < 0.001) to be significant and to negatively (β −1.564) influence inspiration for agri-preneurship (Table 7).

The self-realization variant (age and marital status) with a p < 0.035 and p < 0.035, respectively, was found to be significant and positively related to setting up an agri-preneurship business (Table 7). This result is corroborated by the study of Kerr et al. (2018), which found that self-assurance was a rationale for achievement and willingness to take risk (Kerr et al. 2018). In the present dispensation and with the economic atmosphere, there are gaps in investment decision making between men, women, and age. In addition, wealth creation is traditionally lower in women than men for numerous reasons, including social, emotional, and gender disparity (Rana and Sharma 2019). Also of concern is the marital status of both men and women, and being single, married, a widow, a widower, and divorced has a significant effect on financial decision making at the household level. Our findings lend credence to the studies of Rana and Sharma (2019), Kannadas and Shah (2021), who found that investment decisions were informed by family members (wives and husbands) and friends.

In the self-satisfaction category (

Table 8. Self-satisfaction.

Parameter Estimates
Inspiration for Starting Up an Agri-Preneurial Business a		B	Std. Error	Wald	df	Sig.	Exp.B.	95% Confidence Interval for Exp(B)
								Lower Bound	Upper Bound
Self-satisfaction	Intercept	0.294	1.852	0.025	1	0.874
	Gender	0.371	0.536	0.479	1	0.489	1.449	0.507	4.139
	Age	0.146	0.259	0.318	1	0.573	1.158	0.696	1.925
	Level of formal education	0.511	0.309	2.747	1	0.097	1.668	0.911	3.053
	Marital status	−1.564	0.409	14.610	1	0.001 *	0.209	0.094	0.467
	Farm size	0.236	0.464	0.259	1	0.611	1.266	0.510	3.142
	Household size	−0.096	0.361	0.071	1	0.790	0.908	0.448	1.843
	Source of income	0.126	0.259	0.238	1	0.626	1.135	0.683	1.886
	Farm experience	0.275	0.257	1.145	1	0.285	1.316	0.796	2.178

* Threshold for determining significance at 0.05, 0.001, and 0.01.

), the results indicate that marital status is also significant (p < 0.001) with β −1.564. The implication here, is that though marital status is significant, it negatively impacts the decision to start-up an agri-preneurial business as shown by the negative coefficient. This result suggests that an increase in rapport with family members, friends, and relatives will cause a decrease in the possibility of investment decisions, provided all antecedent variables remain constant (Ahuvia et al. 2018).

In

Table 9. Possibility of higher returns.

Parameter Estimates
Inspiration for Starting Up an Agri-Preneurial Business a		B	Std. Error	Wald	df	Sig.	Exp.B.	95% Confidence Interval for Exp(B)
								Lower Bound	Upper Bound
Possibility of higher returns	Intercept	−0.399	2.001	0.040	1	0.842
	Gender	−0.134	0.566	0.056	1	0.813	0.875	0.289	2.652
	Age	0.172	0.282	0.372	1	0.542	1.188	0	2.064
	Level of formal education	0.772	0.329	5.487	1	0.019 *	2.164	1.134	4.127
	Marital status	−0.539	0.378	2.036	1	0.154	0.583	0.278	1.223
	Farm size	0.214	0.490	0.190	1	0.663	1.238	0.474	3.235
	Household size	−0.274	0.383	0.513	1	0.474	0.760	0.359	1.611
	Source of income	−0.084	0.274	0.094	1	0.759	0.919	0.537	1.574
	Farm experience	0.203	0.277	0.535	1	0.465	1.225	0.712	2.107

* Threshold for determining significance at 0.05, 0.001, and 0.01.

, the possibility of higher returns variant (level of education) was found to be statistically significant (p < 0.019), an inspiring factor in commencing agri-preneurship. This result implies that, for any additional training received, there is a corresponding increase in the inspiration and yearnings of an agri-preneurship investment decision, provided all variables in the study remain constant. This result agrees with the study by (Agholor et al. 2023; Oduro-Ofori et al. 2015), which found that an increase in farmers’ level of education enhanced the acceptance of a climate resilience approach aimed at increasing production.

Furthermore, the data indicate that the pride of ownership variant (level of education with p < 0.024) is correlated and significantly influences motivation to start-up an agri-preneurial business (

Table 10. Pride of ownership.

Parameter Estimates
Inspiration for Starting Up an Agri-Preneurial Business a		B	Std. Error	Wald	df	Sig.	Exp.B.	95% Confidence Interval for Exp(B)
								Lower Bound	Upper Bound
Pride of ownership of business	Intercept	−2.398	2.104	1.299	1	0.254
	Gender	−0.001	0.582	0.000	1	0.998	0.999	0.319	3.125
	Age	0.554	0.304	3.323	1	0.068	1.740	0.959	3.158
	Level of formal education	0.777	0.343	5.127	1	0.024 *	2.176	1.110	4.264
	Marital status	−0.549	0.368	2.227	1	0.136	0.577	0.281	1.188
	Farm size	0.130	0.496	0.069	1	0.793	1.139	0.431	3.013
	Household size	−0.171	0.388	0.195	1	0.659	0.843	0.394	1.802
	Source of income	−0.017	0.288	0.004	1	0.952	0.983	0.558	1.730
	Farm experience	0.113	0.286	0.156	1	0.692	1.120	0.639	1.962

* Threshold for determining significance at 0.05, 0.001, and 0.01.

). Consistent with previous studies (Decrop and Derbaix 2010; Ahuvia et al. 2018), pride of ownership is interconnected with consumers’ ability to conceptualize the optimistic identity of a product to purchase.

In the independence decision making category, two crucial variables, level of formal education (p < 0.005) and farm experience (p < 0.007), were found to be correlated and statistically significant in determining agri-preneurial decisions (

Table 11. Independence in decision making.

Parameter Estimates
Inspiration for Starting Up an Agri-Preneurial Business a		B	Std. Error	Wald	df	Sig.	Exp.B.	95% Confidence Interval for Exp(B)
								Lower Bound	Upper Bound
Pride of ownership of business	Intercept	−2.398	2.104	1.299	1	0.254
	Gender	−0.001	0.582	0.000	1	0.998	0.999	0.319	3.125
	Age	0.554	0.304	3.323	1	0.068	1.740	0.959	3.158
	Level of formal education	0.777	0.343	5.127	1	0.024 *	2.176	1.110	4.264
	Marital status	−0.549	0.368	2.227	1	0.136	0.577	0.281	1.188
	Farm size	0.130	0.496	0.069	1	0.793	1.139	0.431	3.013
	Household size	−0.171	0.388	0.195	1	0.659	0.843	0.394	1.802
	Source of income	−0.017	0.288	0.004	1	0.952	0.983	0.558	1.730
	Farm experience	0.113	0.286	0.156	1	0.692	1.120	0.639	1.962

* Threshold for determining significance at 0.05, 0.001, and 0.01.

). This finding is corroborated by the study of Al-Hadrami et al. (2020), which found that independence and competence had a significant influence on investment decision making.

The social status variant was investigated, and the findings indicate that the social status variant, (farm experience) recorded p < 0.051, (

Table 12. Social status.

Parameter Estimates
Inspiration for Starting Up an Agri-Preneurial Business a		B	Std. Error	Wald	df	Sig.	Exp.B.	95% Confidence Interval for Exp(B)
								Lower Bound	Upper Bound
Social status	Intercept	0.877	1.880	0.217	1	0.641
	Gender	−0.117	0.545	0.046	1	0.829	0.889	0.306	2.588
	Age	−0.316	0.264	1.435	1	0.231	0.729	0.435	1.223
	Level of formal education	0.422	0.313	1.819	1	0.177	1.525	0.826	2.816
	Marital status	−0.092	0.340	0.073	1	0.787	0.912	0.469	1.774
	Farm size	0.430	0.459	0.877	1	0.349	1.537	0.625	3.780
	Household size	−0.433	0.361	1.438	1	0.231	0.648	0.319	1.316
	Source of income	−0.031	0.262	0.014	1	0.906	0.969	0.580	1.621
	Farm experience	0.521	0.267	3.798	1	0.051 *	1.684	0.997	2.843

* Threshold for determining significance at 0.05, 0.001, and 0.01.

) with a positive significant relationship for agri-preneurship investment decision making. Furthermore, the results affirmed that personal decision making is characterized by the perspectives of intimate family, peers, and friends belonging to the same social cycle, as well as relatives (Akhtar et al. 2018).

Value affirmation assists in reinforcing individual integrity, an assurance of self-worth in an investment environment, and the ability to take independence decision. Individuals with low self-esteem are seldom able to make proactive decisions (Agholor 2019). Although the affirmation value did not indicate a positive relationship for agri-preneurial investment decision making, it is worth noting that self-affirmation assists entrepreneurs to conquer some business hurdles (

Table 13. Affirmation of value.

Parameter Estimates
Inspiration for Starting Up an Agri-Preneurial Business a		B	Std. Error	Wald	df	Sig.	Exp.B.	95% Confidence Interval for Exp(B)
								Lower Bound	Upper Bound
Affirmation of value	Intercept	−2.602	2.399	1.177	1	0.278
	Gender	0.831	0.684	1.478	1	0.224	2.296	0.601	8.765
	Age	0.185	0.324	0.326	1	0.568	1.203	0.637	2.272
	Level of formal education	0.653	0.372	3.085	1	0.079	1.922	0.927	3.983
	Marital status	−0.646	0.434	2.214	1	0.137	0.524	0.224	1.227
	Farm size	0.367	0.553	0.442	1	0.506	1.444	0.489	4.267
	Household size	−0.247	0.427	0.334	1	0.563	0.781	0.338	1.805
	Source of income	−0.141	0.323	0.190	1	0.663	0.869	0.461	1.636
		0.250	0.313	0.634	1	0.426	1.284	0.694	2.373
	Farm experience	0.250	0.313	0.634	1	0.426	1.284	0.694	2.373

Threshold for determining significance at 0.05, 0.001, and 0.01. The Table 13 shows the affirmation of values for parameter estimates.

).

5. Conclusions

This study underscores the need to subjectively analyze certain factors that inspire agri-preneurs, obstacles to performance, sources of agri-preneurial ideas, and the relationship between dependent and demographic characteristics of respondents. Our findings revealed that potential agri-preneurs are affected by an array of inspiring factors in the decision-making process. The inspirational factors that were noted as vital for starting up an agri-preneurial business were self-realization, self-satisfaction, the possibility of higher returns, and pride of ownership. However, other factors were independence in decision making, social status, affirmation of value, and pursuit of self-trial. The inspirational factors identified in our study are supported by the classes of entrepreneurial motives, as expressed by Hefer et al. (2015). It is pertinent to understand that the inspirational factors enunciated in this study are both ‘pull factors’ (internal) and ‘push factors’ (external). In light of this, it is possible for potential agri-preneurs to be inspired by either the pull or push factor in the decision-making process.

Further, in the shared views of surveyed respondents, there was a portmanteau of obstacles impeding the commencement of one’s own business. The consequence was that most potential agri-preneurs lack experience, capital, and fear of failure and competition portend more problems in the start-up of one’s own business. According to Bushe (2019), 40% of new enterprises in South Africa fail beyond their first year of start-up, 60% fail within their second year of operation, and 90% abandon their business within their first 10 years of commencement. The unfortunate survival rate of new enterprises lends credence to the obstacles indicated in our findings. The sources of agri-preneurial business appear to be many, as highlighted in our survey. However, decision-making processes interplay amongst these identified sources. According to Agholor and Ogujiuba (2021), a credible behavior is premised on antecedents, such as intention and propensity to perform. The sources of information do not necessarily determine aptitude to invest and become an agri-preneur.

In addition, the study evaluated the relationship between gender, age, level of formal education, farm size, household size, source of income, and farm experience and inspiration. The results show that, in the self-realization variant, age (p < 0.035) and marital status (p < 0.033) was found to be correlated and statistically significant as inspiration for setting up an agri-preneurship business, while the self-satisfaction variant specified marital status (p < 0.001) to be significant and to negatively (β −1.564) influence inspiration for agri-preneurship (Table 7). The possibility of higher returns variant was found to be statistically significant (p < 0.019), an inspiring factor in commencing agri-preneurship. Further, the data indicate that pride of ownership correlated and significantly (p < 0.024) influences motivation to start-up an agri-preneurial business (Table 9). In the independence in decision making category, two crucial variables, level of formal education (p < 0.005) and farm experience (p < 0.007), were found to be correlated and statistically significant in determining agri-preneurial decisions (Table 10). The findings also indicate that, in the social status variant, farm experience (p < 0.051) influences the decision to start up an agri-preneurial business. Consistent with other studies (Charles and Kasilingam 2013; Ansari 2019), we found that age influenced the pattern of investment and decision making. As indicated in our survey, farm experience was another relevant determinant of agri-preneurial investment decision making process.

In summary, the position of agri-preneurship in South Africa must not be underrated since the national development plan has been identified as one of the panaceas for achieving socio-economic imperatives. Notwithstanding the substantial efforts employed by the government of South Africa to enhance entrepreneurial business, more must still be done to ameliorate the obstacles of investment. This study carries policy propositions: the government and allied stakeholders must consider the motives that inspire potential investors in agriculture. The government must also oversee the reasons for young and old agri-preneurs exiting agri-businesses to pursue other occupations.

6. Limitations and Future Research

Firstly, all theoretical ideology expressed in context has only examined entrepreneurs and entrepreneurship based on the perception and individual theorist observation and, therefore, may only provide limited views that do not entirely justify entrepreneurial phenomena. Secondly, there is no one theory that is universally accepted as meeting the needs of agri-preneurs because there are multi-dimensional factors that determine investment drive. Thirdly, this study used only multinominal regression to determine relationship, but other models could be employed. Additionally, this study is limited to Mbombela, South Africa, but may be considered for other areas.

Our study answered the following questions: (i) Are there inspiring factors for individuals to start up their own agri-preneurship business? (ii) Are there factors hindering individuals from starting up their own agri-preneurship business? These two hypothetical constructs triggered four primary arguments established in the study. Future research should investigate the various sources of finance that exist to help new agri-preneurs to start up their own business. Finance-based advisory programs and partnership for investors should be considered as areas to form part of the future research niche for developing agri-preneurs. Unlocking agri-business incubators and affiliating with relevant stakeholders should also be the focus for further research. Furthermore, this study employed only a multinominal logistic regression model to determine relationships, but future research should articulate the use of other models relevant for determining relationships. Research into the quality of human capital is vital for agri-preneurship success and must considered in future research.