Knowledge of entrepreneurial support and entrepreneurial intention in the rural provinces of South Africa

ABSTRACT

The purpose of this study was to investigate whether knowledge about government entrepreneurial support and entrepreneurial support institutions and their services have an influence on entrepreneurial intention and its antecedents. The study was carried out by means of a cross-sectional survey using a structured questionnaire. The sample consisted of 355 final-year commerce students from two universities located in two of South Africa’s most rural provinces, namely the Eastern Cape and Limpopo. The Statistical Package for the Social Sciences was used to analyse the data. The results indicate that the respondents could hardly access information about entrepreneurial support offered by the government and support services available, and had a very low level of knowledge about these support services. The findings revealed some significant relationships between the knowledge of entrepreneurial support and entrepreneurial intention, perceived behavioural control, subjective norms and entrepreneurial self-efficacy.

KEYWORDS:

• Rural entrepreneurship development
• entrepreneurship policy
• entrepreneurial intention
• rural provinces
• institutional support

1. Introduction

The recognition of entrepreneurship as a mechanism for economic growth and development has attracted considerable interest among researchers and policy-makers (Audet et al., 2007; Ismail et al., 2009). Policy-makers, on the one hand, are concerned with how economic growth and entrepreneurial activity can be stimulated through various policies and support programmes (Bridge et al., 2009; ECDC, 2013; SEFA, 2014; Limpopo Provincial Government, 2015). Researchers, on the other hand, are engaged with the evaluation of the effectiveness of these policies and support programmes in terms of their impact on entrepreneurial intention (Lüthje & Franke, 2003), new venture creation and growth (Bridge et al., 2009; Zanakis et al., 2012).

Entrepreneurial support as a behavioural intervention can assist both intending and existing entrepreneurs in overcoming barriers they face and facilitate their efforts to start and grow their own businesses (Ajzen, 2005). Hanlon & Saunders (2007:620) define entrepreneurial support as ‘the act of providing an entrepreneur with access to a valued resource’. The definition for entrepreneurial support in this study is the provision of information, finance, training and education programmes, infrastructural facilities, counselling and mentoring services needed by entrepreneurs to start, grow and manage their businesses effectively (Malebana, 2012, 2014a).

The high unemployment rate in South Africa of about 26.7% (Statistics South Africa, 2016) necessitates promoting and supporting entrepreneurship as an approach for stimulating job creation. Knowledge about the role of entrepreneurial support in influencing entrepreneurial intention is vital in South Africa in order to evaluate the effectiveness of government policies and interventions in encouraging individuals to start their own businesses. This knowledge is more crucial in the rural provinces of South Africa, because rural areas are characterised by a legacy of underdevelopment (Eastern Cape Provincial Government, 2004) and high poverty levels, which are currently at 74.4% in Limpopo and 69.5% in the Eastern Cape (Statistics South Africa, 2014).

Because rural areas have lower entrepreneurial activity rates than their urban counterparts (Herrington et al., 2010), targeted efforts should be aimed at enabling people in rural areas to establish new ventures and existing entrepreneurs to grow their businesses. By increasing awareness of entrepreneurial support, policy-makers could maximise the usage of their support programmes (Audet et al., 2007). This study investigates the relationship between the knowledge of government entrepreneurial support institutions and their services and entrepreneurial intention and its antecedents in the two mostly rural provinces of South Africa, the Eastern Cape and Limpopo. These provinces have a large number of their population who live in rural areas (Statistics South Africa, 2006; Limpopo Provincial Government, 2015).

Despite the numerous government support institutions that have been established and the measures that have been introduced in South Africa (DTI, 2005, 2014), the country’s total early-stage entrepreneurial activity rates and entrepreneurial intentions remain very low (Kelley et al., 2016). This situation calls for research that examines the impact of entrepreneurial support on entrepreneurial intention and activity. There is a paucity of research in South Africa on the effect of government entrepreneurial support programmes on entrepreneurial intention and its antecedents. The study advances the application of the theory of planned behaviour by assessing the impact of entrepreneurial support on entrepreneurial intention and its antecedents.

2. Theoretical framework

This study views entrepreneurial support as an intervention that can be directed at changing one or more of the antecedents of entrepreneurial intention and behaviour. The literature review focuses on the two dominant models of entrepreneurial intention, namely the theory of planned behaviour and Shapero and Sokol’s model of the entrepreneurial event. These models are valuable in shedding light on the effect of entrepreneurial support on entrepreneurial intention and its antecedents and in encouraging start-ups and the growth of new ventures. The study concludes with an overview of entrepreneurial support in South Africa.

2.1. Entrepreneurship as a planned behaviour

Entrepreneurship is considered a planned behaviour that is dependent on individuals’ entrepreneurial intentions (Krueger, 1993; Krueger et al., 2000). In recent years, the theory of planned behaviour and Shapero and Sokol’s model of the entrepreneurial event have become increasingly popular models of entrepreneurial intention (Krueger et al., 2000; Malebana, 2014b).

According to the theory of planned behaviour, the performance of a particular behaviour follows reasonably from an individual’s intention to perform that behaviour (Ajzen, 2005). The theory of planned behaviour suggests that intentions are determined by the attitude towards the behaviour, perceived behavioural control and subjective norms (Ajzen, 2005). The formation of entrepreneurial intention depends on how individuals evaluate the outcomes from the entrepreneurial behaviour, their judgement regarding the ease or difficulty of performing the behaviour and whether individuals perceive the social pressure to perform or not to perform the behaviour (Ajzen, 2005). The likelihood of performing the intended behaviour increases when individuals have a favourable attitude and subjective norms and believe in their own ability to perform it successfully (Ajzen, 2005).

Entrepreneurial support can play a vital role in entrepreneurship development by positively influencing entrepreneurial intention (Lüthje & Franke, 2003) and attitudes towards an entrepreneurial career, and increasing individuals’ confidence in their own ability to start a business (Malebana, 2014a; Saeed et al., 2015). Efforts aimed at increasing the knowledge of entrepreneurial support can also enhance subjective norms by developing social awareness about entrepreneurship and emphasising the importance of entrepreneurship in society (Gnyawali & Fogel, 1994; North & Smallbone, 2006). Prior research has shown that entrepreneurial support can encourage self-employment (Kim & Cho, 2009), increase the number of new business start-ups (Zanakis et al., 2012) and facilitate small business growth (Bridge et al., 2009). As a result, the theory of planned behaviour can be a valuable tool for evaluating the effectiveness of entrepreneurial support interventions in contributing to the formation of entrepreneurial intentions and in promoting entrepreneurial behaviour (Ajzen, 2005).

Perceived behavioural control originates from perceived self-efficacy (Ajzen, 2005), which is also an established determinant of entrepreneurial intention (Kickul & D’Intino, 2005). Self-efficacy is an important concept in the social cognitive theory, which is defined as ‘people’s judgements of their capabilities to organize and execute courses of action required to attain designated types of performances’ (Bandura, 1986:391). In the field of entrepreneurship it is termed entrepreneurial self-efficacy, which is defined as the degree to which individuals believe they have the ability to successfully start a new business (Brice & Spencer, 2007). Entrepreneurial support can enhance perceived entrepreneurial self-efficacy by equipping people with the right skills and can also increase the likelihood of entrepreneurial action by providing individuals with the required resources to establish new ventures (Gnyawali & Fogel, 1994). According to Bandura (1986), the possession of skills alone would not lead to action but resources should also be available to perform the behaviour adequately. On the contrary, previous research did not find a significant relationship between governmental support and entrepreneurial self-efficacy (Wang et al., 2010), attitudes and perceived behavioural control (Yurtkoru et al., 2014) and entrepreneurial intention (Ismail et al., 2009).

Shapero and Sokol’s model of the entrepreneurial event suggests that the intention to start a business derives from perceived desirability, perceived feasibility and propensity to act upon opportunities (Shapero & Sokol, 1982; Krueger et al., 2000). Perceived desirability is the degree to which an individual is attracted to the idea of starting a business. Perceived feasibility refers to an individual’s perceived capability for starting a business. Propensity to act is ‘the disposition to act on one’s decisions’ (Krueger et al., 2000:419). According to Shapero and Sokol’s model, the entrepreneurial event emerges from the interactions between situational, cultural and social variables. Shapero & Sokol (1982) view the entrepreneurial process as an event that is initiated by some sort of displacement event, such as the appearance (or acquisition) of a perceived facilitator or the removal (or avoidance) of a perceived inhibiting factor. Perceived desirability can be influenced by social and cultural factors while the availability of financial support and other forms of support can enhance perceived feasibility (Shapero & Sokol, 1982). A study by Krueger (1993) which tested Shapero and Sokol’s model of the entrepreneurial event found that entrepreneurial intentions are determined by perceived desirability, perceived feasibility and propensity to act. The study revealed that perceived desirability and perceived feasibility are positively related to prior entrepreneurial exposure.

2.2. Entrepreneurial support in South Africa

The Department of Trade and Industry has the responsibility to provide the national framework for the implementation of small, medium and micro-enterprise support in South Africa (DTI, 2005). Its agencies include the Small Enterprise Finance Agency which replaced the Khula Enteprise Finance (Khula) in April 2012, the Small Enterprise Development Agency (Seda), the National Youth Development Agency (NYDA) which replaced the Umsobomvu Youth Fund (UYF) in June 2009, the Industrial Development Corporation (IDC), the Companies and Intellectual Property Registration Office (CIPRO) which is now the Companies and Intellectual Property Commission, Land Bank, Mafisa, provincial government agencies and the National Empowerment Fund (NEF) (DTI, 2014; SEFA, 2014). The establishment of the Small Enterprise Finance Agency involved the incorporation of the activities of Khula, the South African Micro-Finance Apex Fund (SAMAF) and the IDC small business activities. Entrepreneurial support through these agencies ranges from easing the regulatory and compliance burden on small enterprises to access to finance, business development services, youth enterprise development, support for women-owned enterprises, incubation and technology acquisition and transfer services, productivity enhancement centres and sector-focused support measures. In addition to some of the national institutions that can be accessed at the provincial level, the Eastern Cape and Limpopo provinces have their own entrepreneurial support institutions, namely the Eastern Cape Development Corporation (ECDC, 2013) and the Limpopo Enterprise Development Agency which replaced the Limpopo Business Support Agency and the Limpopo Economic Development Enterprise (LIMDEV) in December 2012 (LEDA, 2013).

Bridge et al. (2009) indicate that a large number of evaluation studies tend to focus on the number of clients reached and their level of satisfaction with the support provided. This kind of evaluation ignores the role of entrepreneurial support in stimulating entrepreneurial attitudes and intentions. The impact of entrepreneurial support programmes on improving the effectiveness of the management of the assisted enterprises and the growth of these enterprises had also been overlooked. Previous research indicates that the level of awareness differed between support programmes and location, and the usage rate of support programmes among entrepreneurs was low and varied between programmes and sectors (Berry et al., 2002; Rogerson, 2004). Despite the existence of various kinds of government support, a large number of small business owners experience difficulties in accessing support mainly due to low awareness, support institutions not being visible, support programmes not being easily accessible, high costs of these programmes, limited participation of commercial banks, limited reach in rural areas and failure of programmes to cater for the needs of small and micro businesses (Berry et al., 2002; Ladzani & Netswera, 2009; Finmark Trust, 2010).

3. Research methodology

3.1. Research design

The study used a descriptive research design which followed a quantitative research approach. A cross-sectional survey was conducted among final-year commerce students in Limpopo and the Eastern Cape. The chosen research design, approach and method allowed the researchers to collect the data on the demographic characteristics, beliefs, perceptions and attitudes from a large number of respondents so that they can be analysed statistically and be used to describe the individuals studied.

3.2. Population and sample

The population comprised 814 third-year students who were registered for full-time studies in 2010 for commercial diplomas at two selected universities in Limpopo and the Eastern Cape. Although the researchers intended to use a census survey of all 814 students, only 355 students participated in the study owing to circumstances that were beyond the researchers’ control. In line with previous research on entrepreneurial intention (Liñán & Chen, 2009), this sample of students was chosen because as final-year students they were facing important career decisions upon completion of their studies, and starting their own business was a possible option. The researcher obtained permission from the heads of department at the two selected institutions to involve their lecturers and students in the research project.

About 77.7% of the respondents were from a comprehensive university in the Eastern Cape while 22.3% were from a university of technology in Limpopo. The majority (76.1%) of these respondents were aged between 18 and 24 years, 22.5% were aged between 25 and 34 years and just over 1% was aged between 35 and 64 years. Because more than 98% of the respondents fall below the age of 35 years, the respondents were an ideal group for studying the entrepreneurial intention of the youth. This suggests that the results could be helpful to policy-makers in their efforts promote youth entrepreneurship, especially the rural youth in South Africa. In terms of prior exposure to entrepreneurship, 6.6% of the respondents were running their own businesses, 26.7% had tried to start a business before, 34% were coming from the families with members who were running businesses and 28% had friends who are running businesses, while 57.8% knew other people who are entrepreneurs. With regard to employment experience, 30.8% of the respondents were previously employed.

3.3. Data collection

Data were collected using a structured questionnaire that was distributed to students during their lectures. All of the questions pertaining to entrepreneurial intention and its antecedents were adopted without alteration from Liñán & Chen’s (2009) validated entrepreneurial intention questionnaire. Although this questionnaire was initially tested on the Spanish and Taiwanese samples, it has also been validated in both developed and developing countries (e.g. Iakovleva et al., 2011; Malebana, 2012, 2014b). Questions measuring entrepreneurial intention and its antecedents in the theory of planned behaviour were based on a five-point Likert scale (1 = strongly disagree to 5 = strongly agree).

Entrepreneurial self-efficacy was measured by asking students to indicate their level of confidence in their ability to carry out entrepreneurial tasks in the phases of the entrepreneurial life-cycle using a five-point Likert scale (1 = very low confidence to 5 = very high confidence) based on measures adopted from McGee et al. (2009), Kickul & D’Intino (2005) and Kolvereid & Isaksen (2006). Questions on entrepreneurial support measured the respondents’ level of awareness about the types of entrepreneurial support provided by the government at both the national level and the Eastern Cape and Limpopo provinces, and institutions that provide entrepreneurial support and the services they offer. These questions were derived from existing literature and previous research by Liao & Welsch (2005). Data were collected using five-point Likert type questions (1 = strongly disagree to 5 = strongly agree for general knowledge of entrepreneurial support; 1 = very low knowledge to 5 = very high knowledge for knowledge of government institutions that provide entrepreneurial support and the services they offer). The questionnaire also included demographic questions that were based on a nominal scale, which involved gender, age, province and qualifications enrolled for, prior employment experience and prior entrepreneurial exposure (whether the respondents currently own a business, have tried to start a business before, were from an entrepreneurial family background, have friends who run a business or knew other people who are entrepreneurs [1 = yes and 0 = no; 1 = male and 0 = female]). These demographic questions were used as control variables.

3.4. Data analysis

The Statistical Package for the Social Sciences was used to analyse the data. Descriptive statistics were used for the sample characteristics. Hierarchical multiple regression analysis was used to test the relationship between the knowledge of government entrepreneurial support, the knowledge of support institutions and their services and the dependent variables. Prior to data analysis, reliability analysis and factor analysis were conducted to determine the reliability and validity of the measuring instrument. The reliability of the measuring instrument was tested by means of Cronbach’s alpha. The alpha values for the variables were 0.712 for general knowledge of entrepreneurial support (five items), 0.818 for perceived behavioural control (nine items), 0.826 for subjective norms (three items), 0.872 for the attitude towards becoming an entrepreneur (six items), 0.903 for entrepreneurial intention (nine items), 0.940 for entrepreneurial self-efficacy (24 items) and 0.936 for knowledge of entrepreneurial support institutions and services (21 items). Given the high reliability scores of the constructs, the questionnaire was therefore considered to be reliable (Field, 2013).

Factor analysis was conducted to determine the convergent validity of the data (Liñán & Chen, 2009). Principal component analysis using the Varimax rotation method was used to extract the factors. The Kaiser–Meyer–Olkin measure of sampling adequacy was 0.878 and Bartlett’s Test of Sphericity was highly significant (p < 0.001). Principal component analysis extracted 16 factors with eigenvalues greater than one which accounted for 69.5% of variance. These results therefore suggest that the data were suitable for factor analysis. Data were tested for the independence of errors and multicollinearity. The values of the Durbin–Watson statistic ranged from 1.408 to 2.195, which were well within the acceptable range from one to three as suggested by Field (2013). The data therefore did not violate the assumption of independence of errors. Variance inflation factors were also highly satisfactory with values below 10, ranging from 1.054 to 7.031, indicating that multicollinearity was not a problem.

4. Results

4.1. The respondents’ knowledge of entrepreneurial support

The findings (Table 1) show that the respondents were cautiously in agreement with the general knowledge of entrepreneurial support statements. Just over 57% agreed that the government provides good support for people who want to start a business, while the different types of support that are available were known by 49.2%. Access to information about these support services seems to be difficult for the majority of the respondents because 59% of them indicated that such information is hardly accessible, while 65.8% believed that it would be difficult for them to access government support. Fifty-one per cent of the respondents were confident that it would be easier for them to receive support from the people they know than from the government, thus highlighting the importance of social capital (social support from close ones).

Table 1. Knowledge of entrepreneurial support among the respondents.

General entrepreneurial support (GES)	Agree (%)	Strongly agree (%)	Total (%)
The government provides good support for people who want to start a business (GES 1)	34.8	22.6	57.4
I know different types of support that are offered to people who want to start their own business (GES 2)	36.4	12.8	49.2
It would be easy for me to access support from the government institutions (GES 3)	25.7	8.5	34.2
Information about government support for people who want to start their business is easily accessible (GES 4)	30.7	10.3	41
It would be easier for me to receive support from the people that I know than from the government (GES 5)	31.7	19.6	51.3
Entrepreneurial support institutions and services	Some knowledge (%)	Know (it) them well (%)	Total (%)
Small Enterprise Development Agency (Seda)	30.8	8.4	39.2
Business development support offered by Seda	25.3	6.1	31.4
Industrial Development Corporation (IDC)	23.5	6.1	29.6
Funding for the different sectors offered by the IDC	21.9	3.8	25.7
Khula Enteprise Finance (Khula)	21.5	4.9	26.4
Financing and non-financial support offered by Khula	18.3	5.2	23.5
Companies and Intellectual Property Registration Office (CIPRO)	14.2	7.5	21.7
Business registration services and protection of intellectual property rights offered by CIPRO	11.7	7.0	18.7
National Empowerment Fund (NEF)	16.2	4.3	20.5
Financing and non-financial support offered by NEF	14.8	2.0	16.8
South African Micro-Finance Apex Fund (SAMAF)	12.2	2.9	15.1
Financial support offered by SAMAF	9.6	5.2	14.8
Umsobomvu Youth Fund (UYF)	39.4	27.3	66.7
Financial and non-financial support offered by UYF	33.6	24.9	58.5
National Youth Development Agency (NYDA)	19.4	14.8	34.2
Limpopo Economic Development Enterprise (LIMDEV)	14.8	8.1	22.9
Enterprise development finance offered by LIMDEV	10.5	7.0	17.5
Limpopo Business Support Agency (LIBSA)	11.6	5.5	17.1
Cooperative development and support, business incubation and other non-financial support offered by LIBSA	12.2	6.4	18.6
Eastern Cape Development Corporation (ECDC)	25.3	14.2	39.5
Development finance and enterprise development services offered by the ECDC	21.1	12.6	33.7

The findings revealed an extremely low level of knowledge of government entrepreneurial support institutions and their services among the respondents. The percentages of the respondents who knew entrepreneurial support institutions and their services well ranged from as low as 2 to 27% while the percentages of those who had some knowledge about these institutions and their services varied between 9.6 and 39.4%. Generally, the majority of the respondents knew more about the UYF (66.7%) and financial and non-financial support offered by the UYF (58.5%). This is not surprising because the UYF’s focus was to provide entrepreneurial support for youth. However, this institution ceased to exist in June 2009 and was replaced with the NYDA, which was known by 34.2% of the respondents. A fair percentage of the respondents (between 31 and 39.5%) knew about Seda (39.2%) and business development support offered by Seda (31.4%), and about the ECDC (39.5%) and development finance and enterprise development services offered by the ECDC (33.7%). These findings are in line with previous research that reported a low level of awareness of entrepreneurial support in South Africa among entrepreneurs, suggesting that more efforts should be directed at remedying this situation if entrepreneurial support programmes are to achieve their intended goals.

4.2. The relationship between the knowledge of entrepreneurial support, the antecedents of entrepreneurial intention and entrepreneurial intention

The regression analysis results for the base models showed that control variables accounted for the variance of 14.1% in entrepreneurial intention (F(11, 302) = 4.522; p < 0.001), 14.7% in the attitude towards becoming an entrepreneur (F(11, 302) = 4.729; p < 0.001), 11.2% in perceived behavioural control (F(11, 302) = 3.457; p < 0.001), 7.7% in subjective norms (F(11, 302) = 2.302; p < 0.05) and 5.7% in entrepreneurial self-efficacy (F(11, 302) = 1.670; p < 0.10). The results indicate that demographic factors, with exception of previous employment experience, have a positive effect on entrepreneurial intention, the attitude towards becoming an entrepreneur, perceived behavioural control, subjective norms and entrepreneurial self-efficacy. Previous employment experience was negatively related to entrepreneurial self-efficacy.

The results of regression models that combined the knowledge of entrepreneurial support with control variables indicated an increase in the proportion of variance in the dependent variables that can be explained by the independent variables. The inclusion of the knowledge of entrepreneurial support and control variables in the regression analysis (Models 1 to 5) accounted for the variance of 28.1% in entrepreneurial intention (F(37, 240) = 2.530; p < 0.001), 23.6% in the attitude towards becoming an entrepreneur (F(37, 240) = 2.008; p < 0.01), 28.9% in perceived behavioural control (F(37, 240) = 2.639; p < 0.001), 23.7% in subjective norms (F(37, 240) = 2.010; p < 0.01) and 23% in entrepreneurial self-efficacy (F(37, 240) = 1.935; p < 0.01). The results tables for the base models and regression models that combined the knowledge of entrepreneurial support with control variables were excluded from this article because of space limitations.

The regression analysis results (Table 2) indicate that the general knowledge about the availability of entrepreneurial support and the knowledge of government entrepreneurial support institutions and their services have a significant relationship with entrepreneurial intention (p < 0.05), perceived behavioural control (p < 0.001), subjective norms (p < 0.01) and entrepreneurial self-efficacy (p < 0.01). Knowledge of entrepreneurial support accounted for 13.8% of variance in entrepreneurial intention in Model 1 (F(26, 284) = 1.744; p < 0.05). Entrepreneurial intention had a significant relationship with entrepreneurial support factors which include the perception that the government provides good support for people who want to start a business (β = −0.129, t = −1.755, p < 0.10), knowledge of the different types of support offered by the government to start a business (β = 0.136, t = 1.891, p < 0.10), the perception that it would be easier for the respondents to receive support from the people they know than from the government institutions (β = 0.115, t = 1.957, p < 0.10), and knowledge of financial support offered by SAMAF (β = 0.166, t = 1.736, p < 0.10). The findings suggest that, on the one hand, the perception that the government provides good support for people who want to start a business has a negative relationship with entrepreneurial intention. On the other hand, the perception that it would be easier for the respondents to receive support from the people they know than from the government institutions and knowledge of financial support offered by SAMAF have a positive effect on entrepreneurial intention.

Table 2. Relationship between independent variables and dependent variables.

Independent variable	Dependent variable
	Entrepreneurial intention	Attitude towards becoming an entrepreneur	Perceived behavioural control	Subjective norms	Entrepreneurial self-efficacy
	β
	Model 1	Model 2	Model 3	Model 4	Model 5
General entrepreneurial support (GES)
GES 1	−0.129^†	−0.002	−0.083	−0.034	0.017
GES 2	0.136^†	0.034	−0.009	0.164*	0.106
GES 3	0.079	0.135^†	0.250**	0.058	0.105
GES 4	0.040	−0.035	0.067	0.035	−0.029
GES 5	0.115^†	0.049	0.035	−0.003	0.000
Entrepreneurial support institutions and services
Seda	0.093	0.101	−0.004	0.028	0.247*
Business development support offered by Seda	0.057	0.011	0.178^†	0.011	0.010
IDC	−0.175	−0.215^†	−0.113	−0.111	−0.129
Funding for the different sectors offered by the IDC	0.167	0.226*	0.147	0.040	0.078
Khula	0.073	−0.023	0.032	−0.093	−0.133
Financing and non-financial support offered by Khula	−0.076	0.020	−0.081	0.106	0.030
CIPRO	−0.088	−0.041	0.002	0.134	−0.095
Business registration services and protection of intellectual property rights offered by CIPRO	0.136	0.090	0.112	−0.036	0.216^†
NEF	−0.148	0.005	−0.123	−0.130	0.251^†
Financing and non-financial support offered by NEF	0.101	0.026	0.071	0.055	−0.233^†
SAMAF	−0.142	−0.250*	−0.037	−0.085	−0.241*
Financial support offered by SAMAF	0.166^†	0.157	0.072	0.187*	0.137
UYF	−0.083	−0.072	0.126	−0.065	−0.048
Financial and non-financial support offered by UYF	−0.003	0.057	0.040	0.120	0.125
NYDA	0.060	0.024	0.020	0.047	0.094
LIMDEV	−0.056	−0.006	0.041	0.046	−0.040
Enterprise development finance offered by LIMDEV	0.071	−0.043	−0.174	−0.241^†	−0.071
LIBSA	−0.004	0.003	−0.104	0.007	−0.067
Business support offered by LIBSA	−0.064	−0.028	0.177	0.180	0.088
ECDC	0.040	0.249^†	−0.023	−0.034	0.012
Development finance and enterprise development services offered by the ECDC	0.037	−0.095	0.004	0.158	−0.016
Multiple R	0.371	0.333	0.462	0.417	0.415
R-square (R^2)	0.138	0.111	0.213	0.174	0.172
ΔAdjusted R^2	0.059	0.029	0.141	0.098	0.096
ΔF-ratio	1.744	1.362	2.961	2.293	2.271
Significance of F	0.016*	0.117	0.000***	0.001**	0.001**

Notes: Seda = Small Enterprise Development Agency; IDC = Industrial Development Corporation; Khula = Khula Enteprise Finance; CIPRO = Companies and Intellectual Property Registration Office; NEF = National Empowerment Fund; SAMAF = South African Micro-Finance Apex Fund; UYF = Umsobomvu Youth Fund; NYDA = National Youth Development Agency; LIMDEV = Limpopo Economic Development Enterprise; LIBSA = Limpopo Business Support Agency; ECDC = Eastern Cape Development Corporation.

^†p < 0.10.

*p < 0.05.

**p < 0.01.

***p < 0.001.

Knowledge of entrepreneurial support institutions and the services they offer did not predict the attitude towards becoming an entrepreneur in Model 2. However, some significant relationships were found between the attitude towards becoming an entrepreneur and the perceived ease of accessing support from the government institutions (β = 0.135, t = 1.719, p < 0.10), knowledge of the IDC (β = −0.215, t = −1.855, p < 0.10) and funding offered by the IDC (β = 0.226, t = 1.982, p < 0.05), and knowledge of SAMAF (β = −0.250, t= −2.372, p < 0.05) and the ECDC (β = 0.249, t = 1.949, p < 0.10). The findings indicate that the perceived ease of accessing support from the government institutions, the knowledge of funding offered by the IDC and knowledge of the ECDC were positively related to the attitude towards becoming an entrepreneur, whereas knowledge of the IDC and SAMAF had a negative effect on the attitude towards becoming an entrepreneur.

As shown in Models 3 and 5, the knowledge of government entrepreneurial support institutions and their services explained 21.3% of variance in perceived behavioural control (F(26, 284) = 2.961; p < 0.001) and 17.2% of variance in entrepreneurial self-efficacy (F(26, 284) = 2.271; p < 0.01). Perceived behavioural control was significantly related to the perceived ease of accessing support from the government institutions (β = 0.250, t = 3.396, p < 0.01) and knowledge of business development support offered by Seda (β = 0.178, t = 1.835, p < 0.10). Entrepreneurial support factors that had a significant relationship with entrepreneurial self-efficacy include knowledge of Seda (β = 0.247, t = 2.257, p < 0.05), business registration services and protection of intellectual property rights offered by CIPRO (β = 0.216, t = 1.734, p < 0.10), knowledge of the NEF (β = 0.251, t = 1.851, p < 0.10) and financing and non-financial support offered by the NEF (β = −0.233, t = −1.696, p < 0.10) and SAMAF (β = −0.241, t = −2.368, p < 0.05). The findings suggest that the perceived ease of accessing support from the government institutions, knowledge of Seda and business development support offered by Seda, business registration services and protection of intellectual property rights offered by CIPRO and the NEF, financing and non-financial support offered by the NEF and knowledge of SAMAF enhance perceived capability for starting a business. As a source of the skills, infrastructure facilities, counselling and mentoring services and funding, entrepreneurial support can increase individuals’ confidence in their ability to start a business.

The results (from Model 4) show that the knowledge of government entrepreneurial support institutions and their services accounted for 17.4% of variance in subjective norms (F(26, 284) = 2.293; p < 0.001). Subjective norms had a significant relationship with the knowledge of the different types of support offered by the government to start a business (β = 0.164, t = 2.338, p < 0.05), financial support offered by SAMAF (β = 0.187, t = 1.989, p < 0.05) and enterprise development finance offered by LIMDEV (β = −0.241, t = −1.884, p < 0.10). The findings indicate that the general knowledge which individuals have about government support for starting a business and knowledge of financial support offered by SAMAF had a positive effect on subjective norms, whereas enterprise development finance offered by LIMDEV was negatively related to subjective norms.

5. Discussion of findings

The purpose of this study was to establish the level of knowledge about entrepreneurial support that is offered by the South African government and to determine whether this knowledge is significantly related to entrepreneurial intention and its antecedents among final-year commerce students in the Eastern Cape and Limpopo. Despite the fact that over 57% of the respondents agreed that the government provides good support for starting a business, their knowledge about the different types of support that are offered was below 50% and they had little knowledge about the majority of government institutions that provide entrepreneurial support and their services, which varied between 2 and 39.5%. The respondents had more knowledge about the UYF (66.7%) and its services (58.5%). The results indicate that the respondents could hardly access information about the various types of government support and the services offered by government institutions. Given the little knowledge of these government entrepreneurial support institutions and their services among the respondents, it is highly unlikely that maximum usage of small business support programmes would be realised in rural areas. This in turn limits the impact of small business support programmes on job creation, and poverty alleviation, and negatively affects the number of new start-ups that could improve low rural entrepreneurial activity rates. The fact that over 51% of the respondents perceived that it would be easier for them to receive support from the people they know than from the government suggests the inaccessibility of entrepreneurial support in rural areas.

The results indicate some significant relationships between demographic factors and entrepreneurial intention, the attitude towards becoming an entrepreneur, perceived behavioural control, subjective norms and entrepreneurial self-efficacy. Demographic factors alone explained between 5.7 and 14.7% of variance in the dependent variables, whereas the knowledge of entrepreneurial support accounted for the variance of between 13.8 and 21.3% in the dependent variables. Knowledge of entrepreneurial support combined with demographic factors explained between 23 and 28.9% of variance in the dependent variables.

In line with previous research, the results suggest that entrepreneurial support could play a vital role in promoting rural entrepreneurship by stimulating entrepreneurial intention and impacting positively on the antecedents of entrepreneurial intention (Lüthje & Franke, 2003; Malebana, 2014a; Saeed et al., 2015). Entrepreneurial support is valuable in creating an environment that enhances entrepreneurial abilities and intentions and can become a tool for changing societal values about the entrepreneurial career. The findings indicate that the formation of entrepreneurial intention is dependent on the supportiveness of the environment. They concur with previous research that highlighted the importance of a supportive environment in stimulating entrepreneurial activity and enhancing the entrepreneurial potential (Gnyawali & Fogel, 1994). The findings contradict earlier research that could not find a relationship between entrepreneurial support and entrepreneurial intention (Ismail et al., 2009), entrepreneurial self-efficacy (Wang et al., 2010), attitudes and perceived behavioural control (Yurtkoru et al., 2014).

Because perceived availability of and access to entrepreneurial support can facilitate the establishment of new ventures (Zanakis et al., 2012) and enhance the growth of existing enterprises (Bridge et al., 2009), more efforts should be directed at increasing awareness of and access to entrepreneurial support in rural areas. These efforts would impact positively on entrepreneurial intention and stimulate rural entrepreneurial activity, which in turn would create jobs and improve rural economies (Malebana, 2014a, 2014b).

In line with Ajzen’s (2005) view, the findings demonstrate the value of the theory of planned behaviour as a tool for evaluating the effectiveness of entrepreneurial support programmes with regard to their impact on entrepreneurial intention and its antecedents. The originality of this study lies in it being the first in a South African context to test the relationship between the knowledge of government entrepreneurial support and entrepreneurial intention and its antecedents.

6. Conclusion

Given the low level of knowledge about support institutions and their services among the respondents, the government should intensify its campaigns to raise awareness of and access to entrepreneurial support programmes, especially in rural areas where these programmes are inaccessible. These efforts, in turn would enhance perceived behavioural control, subjective norms and entrepreneurial self-efficacy. By publicising the available entrepreneurial support programmes and highlighting the importance of entrepreneurship, the government would generate supportive societal norms and values that favour entrepreneurship, which in turn would increase the perceived social pressure on individuals to pursue entrepreneurship as a career. The more knowledgeable individuals are about the different types of support and perceive them to be easily accessible, the greater would be their likelihood of entering self-employment (Kim & Cho, 2009).

The South African government should include the impact of support programmes on entrepreneurial intention in its evaluation criteria because entrepreneurial intention precedes entrepreneurial behaviour. By so doing, policy-makers would know whether support programmes achieve the desired effects on entrepreneurial intention and the antecedents of entrepreneurial intention. The stronger the effects of entrepreneurial support on entrepreneurial intention, perceived behavioural control and entrepreneurial self-efficacy, the greater will be the likelihood of new start-ups – mainly due to increased access to entrepreneurial support which facilitates the performance of the behaviour (Bandura, 1986; Ajzen, 2005). Partnerships between higher education and government institutions should be established to make resources available for students to experiment with their ideas and to put the theory into practice. This would enhance confidence in the acquired skills, which in turn would increase the likelihood of the efforts to translate intentions into new ventures (McGee et al., 2009).

While this study had shed light on the role of the knowledge of entrepreneurial support in the formation of entrepreneurial intention, future research should examine the impact of awareness of and access to entrepreneurial support on new venture creation, growth intention and small business growth (Malebana, 2014a, 2014b). There is also a need for more knowledge about the types of support required by intending entrepreneurs to implement their entrepreneurial intentions.

This study has its own limitations, which include its cross-sectional nature and the use of student samples. Owing to the use of convenience samples the results cannot be generalised to all students in the rural provinces of South Africa. While the study established the relationship between knowledge of entrepreneurial support and entrepreneurial intention and its antecedents, these results do not necessarily mean that this knowledge would translate into behaviour. There could be other intervening factors that could negatively impact on the efforts of translating such intentions into new ventures which were not the focus of this study.

Acknowledgements

The authors would like to thank Professor Francisco Liñán for the permission to use the Entrepreneurial Intention Questionnaire.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This study was partially funded by the National Research Foundation under Thuthuka funding [grant number TTK2008062200004].