Women entrepreneurial intentions in subsistence marketplaces: The role of entrepreneurial orientation and demographic profiles in Zimbabwe

Abstract

Subsistence women in developing economies are largely marginalised yet their circumstances could be improved through entrepreneurship. The study sought to establish the relationship between entrepreneurial orientation on entrepreneurial intention and the moderating and direct effects of demographic profiles as an oasis of establishing a predictive model on prospective rural women entrepreneurs. Data were collected from prospective women entrepreneurs in the rural markets of Manicaland Province, Zimbabwe. A sample of 192 women was used. Data analysis was done using structural equation modeling to address the research hypotheses. Convenience sampling was applied to test the hypotheses relying on consenting women.The adequacy of the sample was tested using Kaiser-mayor-olkin and also the Bartlett’s test for sphericity. Initially, exploratory factor analysis was done using Principal Component Analysis. The rotated component matrix was also extracted. Data analysis was performed using Smartpls program. The results of analysing data show a significant relationship between innovativeness and risk-taking ability on entrepreneurial intention. However, data analysed did not confirm the hypothesised relationships between proactiveness and demographic profiles on entrepreneurial intention. It is recommended that entrepreneurship financiers, Non-Governmental Organisations and Governments should consider rural women’s innovativeness and risk-taking ability in screening potential entrepreneurs for funding and training.

Keywords:

• entrepreneurial orientation
• entrepreneurial intention
• proactiveness
• innovativeness
• risk-taking
• subsistence women

PUBLIC INTEREST STATEMENT

There are 56% people in rural areas of Africa (Worldometer, 2020) and more than half of these rural dwellers are women. More donor funds and government projects are directed towards women especially in rural markets. The purpose of this study is to prospect for a predictive model of potential women entrepreneurs for funding and training by establishing the influence of entrepreneurial orientation, entrepreneurial intention and demographic profiles in terms of level of education, family business background and age in rural markets. Innovativeness and risk-taking ability were noted as important in identifying rural women’s entrepreneurial intention. There is need to impart these elements to rural women prospective entrepreneurs to enhance entrepreneurial intention whereas demographics and proactiveness were not significant.

1. Introduction

The poor outnumber the rich in terms of population because “the bottom of the pyramid” had 3.5 billion people in 2017 (GlobalWealthReport-CreditSuisse, 2019; Prahalad & Hart, 2002). The majority of these poor people are in rural areas (subsistence marketplaces) especially in Africa where 56% live in rural areas (Worldometer, 2020). Subsistence marketplaces have illiterate consumers who are resource poor, as a result are largely ignored in most studies in entrepreneurship and business. Women in subsistence marketplaces live at the intersection of poverty, illiteracy and marketplace (Viswanathan, 2017) and they have not attracted researchers’ interest at micro-level to understand their entrepreneurial intentions. Moreso, research in such markets is geographically inconvenient (rural areas are usually far away from Universities, respondents are dispersed and do not have a research culture, as compared to data collection in urban shopping malls, streets and online surveys) and pose the extra challenge of translations of instruments to vernacular language (Brislin, 1970).

Entrepreneurship is the backbone and engine of economic development of any country. To achieve the sustainable development goals (SDGs) embraced by all United Nations member states in 2015, there is need for robust economic policies especially those related to prospective entrepreneurs’ empowerment. Entrepreneurial activities are increasing internationally and expectations from women in subsistence markets have moved to a higher level with the changing world order (Achakpa & Radović-Marković, 2018). An investigation into the link between entrepreneurial orientation of the women figure and entrepreneurial intentions is very important. The women figure is very important in every society. Her degree of entrepreneurial orientation, complemented by her age, parent’s employment and family business background as well as her level of education plays a pivotal role in determining her entrepreneurial intention (Kumar et al., 2018; Neneh & Van Zyl, 2017). It is expected that a woman should contribute to the economy and that is why more donor funds and government projects are directed towards women. It is a big loss for the country not to benefit from the women given that they are more than 50% of the population in most African countries (Worldbank, 2020). This is despite the fact that a woman is often seen as a family member who does housework, takes care of children, and spends most of her time at home. The vast benefits from entrepreneurial activities have led many nations to spearhead for a larger scale establishment of start-ups and new ventures (GEM, 2019).

There is dearth in subsistence women entrepreneurship literature on the three critical concepts of entrepreneurial orientation. Proactiveness, innovativeness and risk taking are indispensable core components of the entrepreneurial orientation construct as first discussed by Miller (1983) and extended by Lumpkin and Dess (1996). These three dimensions shape the entrepreneurial orientation as a single construct and therefore regard it as a reflective indicator. Thus, entrepreneurial orientation has been extensively publicised as an essential component of entrepreneurial intention when forming a business, goals for the business and its growth target (Neneh & Van Zyl, 2017; Panda, 2018; Quince & Whittake, 2003). In line with the institution’s theory, the huge differences in socio-cultural, infrastructural and economic environment makes it imperative to conduct empirical studies in subsistence markets despite the saturation of the concepts in terms of research in occidental and oriental markets (Burgess & Steenkamp, 2006; Meyer & Peng, 2016).

Extant entrepreneurship literature noted relations between entrepreneurial orientation and business performance measures. Findings have not been consistent, justifying the need for more studies incorporating the construct. Most previous literature on entrepreneurship examined the link between entrepreneurial orientation and organisational performance. The conclusion from the studies was that businesses with a viable entrepreneurial orientation supersedes to a larger extent those that are have nothing to do with entrepreneurial orientation (Covin & Slevin, 1986; Wiklund & Shepherd, 2003). Nevertheless, mixed results have been obtained from these researches. Alternatively, other studies show no significant or lower correlation connecting entrepreneurial orientation and achievement (Covin et al., 1994; Lumpkin & Dess, 2001). Moreso, other previous studies focused more on propensity of students’ intention to be entrepreneurs in future and it was found out that entrepreneurship education was perfectly associated with entrepreneurial intention as well as self-employment (Gatewood et al., 2004; Henderson & Robertson, 2000; Kumar et al., 2018; Parnell et al., 1995; Stohmeyer, 2007; Turker et al., 2005; Wang & Wong, 2004)

Some of the studies mainly adhered to the consequence of individual traits during the process of making choices (Brockhaus, 1980; Johnson, 1990; Krueger et al., 2000; Veciana et al., 2005). From these researches, it was discovered that there is a link between entrepreneurial intention and some individual traits like self-confidence and the desire to excel (Duygu & Senem, 2009). Therefore, lack of vast studies on the women entrepreneurship orientation and intention is evident, especially in subsistence markets.

Entrepreneurial orientation’s roots can be traced back to J. Child (1972) who advanced the emergence of entrepreneurship orientation from a critical standpoint claiming that emerging opportunities could conceivably be successfully tackled by “enthusiastic performance.” Other scholars (Mintzberg, 1973; Sorayah & Dygku, 2017) point out that entrepreneurial orientation started in policy formulation studies. Policy formulation is a companywide process that integrates designing, evaluation, resolution making, and many facets of a firm’s culture and mission (Sorayah & Dygku, 2017). Miller (1983) describes an entrepreneur, as a person who is innovative, a risky taker and has a first mover advantage which results in a competitive edge. When it comes to an entrepreneurial oriented individual, (Kuhn et al., 2010; Paul, 2013) views such an individual as one who concentrates on technological transformation (innovativeness), embarks on perilous endeavours (risk-taking), and follows favourable circumstances boldly (proactiveness).

On the other side of the coin, entrepreneurial intention is viewed as a logical characterisation of the measures to be effectuated by people to either set up original, self-sustaining ventures or to formulate latest service within the existing entities (Krueger et al., 2000; Wiklund & Shepherd, 2003). Objectives are required to make entrepreneurial motives real since they begin with inspirations. Krueger et al. (2000) point out that people form a business not as an instinctive act, but they do it with a motive behind. Since the motivation of entrepreneurship is important to revitalise development in a world which is growth sensitive (Duygu & Senem, 2009), it is important to study on mechanisms that can be put in place to heighten subsistence women’s entrepreneurial activity (Achakpa & Radović-Marković, 2018; Rosca et al., 2020; Setini et al., 2020; Siba, 2019). In the same vein, policy makers should give attention on reasons that entices some women to have a zeal for entrepreneurial career whilst others feel not interested.

1.1. Research context and background to the study

The study was done in Zimbabwe, a typical subsistence economy, with a shrinking economy and a three-digit galloping inflation (540% in 2020, according to the Reserve Bank of Zimbabwe). Almost 75% of the people in Zimbabwe survive on less than US$1 per day. Results from such a market would provide research evidence in entrepreneurship literature on poor economies which are largely ignored by scholars (Mari, 2008; Viswanathan & Rosa, 2007). There has been a rise in informal entrepreneurship in Zimbabwe largely due to failed economic policies (Ndiweni & Verhoeven, 2013) and the marginalisation of majority of the population. The rural areas have been adversely affected by the dwindling economy. Rural entrepreneurs have had challenges in securing lines of credit (Munyanyi, 2015). Ironically, the Government of Zimbabwe is working tirelessly to achieve its strategic vision of becoming an upper middle-class economy by 2030 as adopted from the global goals/sustainable development goals (SDGs) embraced by all United Nations member states in 2015.

In a bid to ensure the realisation of this vision, the government of Zimbabwe is pushing this agenda through the Ministry of women affairs, community, small and medium enterprises development, Ministry of youth, sports arts and recreation as well the Ministry of finance and economic development. A number of initiatives to boost the economy have been put in place by the government of Zimbabwe like the youth and women empowerment facilities. There is also the Zimbabwe Women Empowerment Bank (ZWMB) that was set up to offer financial support to Zimbabwean marginalised women entrepreneurs. Non-governmental organisations like the World Vision, Plan International, GOAL and Caritas among others are coming in to assist Zimbabwe and other nations to help in the achievement of the world SDGs. Unfortunately, regardless of such efforts to improve the Zimbabwean vision, it is surprising that women entrepreneurs are still at a small scale with very few women taking their businesses to greater magnificent levels. The entrepreneurial orientation of some of these women is questionable.

It is the purpose of this study to fill this gap and to increase the existing body of literature on women entrepreneurship. The focus of the study was on prospective women entrepreneurs in the rural areas of Manicaland province in Zimbabwe since the rural areas of Zimbabwe constitute the greatest composition of women in the country and they are the marginalised group targeted by most donors as well as the government empowerment funds. The study also aims at unveiling the fundamental factors that motivates rural women to embark on profitable and long-lasting business ventures so as to avoid wastage of donor and government funds on individuals who are not innovative, proactive or risk takers or who do not possess the right qualities for such funds. In other words, the study findings will enable efficient resource allocation for economic growth maximisation and to provide a green-light to policy makers the world over so that their policies assist in the attainment of the global goals, which is a poverty free world. Viswanathan and his colleagues emphatically indicated the essence of understanding subsistence marketplaces in their own right, so as to improve their quality of life (Venugopal et al., 2015; Weidner et al., 2010).

1.2. Women entrepreneurship studies in Zimbabwe

Entrepreneurship studies in Zimbabwe have been centered on entrepreneurship challenges and factors that motivate entrepreneurship uptake. Mazonde and Carmichael (2016), focusing on urban women, found that Zimbabwean women entrepreneurs are very good in the management of the association between their diverse social obligations and personalities. This makes these women to have a balance between family obligations and entrepreneurial roles for the improvement of their wellbeing. Women entrepreneurs are faced with difficulties in accessing financial capital, struggle between family and work obligations, acquiring of raw materials as well as inadequate knowledge and administration skills (Mauchi et al., 2014). Dumbu (2017) as well as Chikombingo et al. (2017) studied motivational aspects for women entrepreneurs. The findings were that entrepreneurship by women is a result of push factors which are on the negative side like loss of a preceding formal job, the need for the freedom associated with entrepreneurship and sufficient capital. They recommended the government to fund and support women entrepreneurs because it is a substitute for employment.

Nhuta and Mukumba (2017) had a study where they detected socio-economic features of women entrepreneurs in Zimbabwe and established the association between women empowerment in entrepreneurship and social-economic development. Chigudu (2018) had an assessment of the degree of female involvement in small and medium enterprises administration in urban Zimbabwe. The findings were that women personally had no confidence of getting involved in substantial high-risk management roles because they believe men can do better than them. Dumbu (2018) studied difficulties faced by cross border women entrepreneurs in Zimbabwe. The results of the study were that these women who are into cross border are faced with difficulties in accessing correct information on customs duty and processes, are deprived of financial knowledge and combining the family burden and entrepreneurial tasks is a big task.

To the best of our knowledge, we did not find empirical studies on subsistence women entrepreneurship in Zimbabwe or any homogeneous subsistence marketplace in Sub-Saharan Africa, which sought to establish the relationship between entrepreneurial orientation, demographic factors and entrepreneurial intention. The existence of such studies in developed markets and other markets which are completely divergent in terms of socio-cultural environment does not render this study redundant (Burgess & Steenkamp, 2006).

1.3. Statement of the problem

Governments as well as non-governmental organisations, both local and international have taken a number of initiatives to improve the livelihood of women in emerging markets. However, funds provided for subsistence women entrepreneurs have been free for all. There is no standard screening model to avoid wasting funds after giving them to women who do not possess any entrepreneurship potential. This study sought to establish the influence of entrepreneurship orientation and demographic factors on entrepreneurship intentions of subsistence women.

1.4. Objectives of the study

1. To determine the relationship between entrepreneurship orientation (innovativeness, proactiveness and the risk-taking) and entrepreneurship intention of subsistence women as prospective entrepreneurs screening variables.

2. To identify the impact (moderating and direct effects) of demographic profiles (education, family business background and age) on entrepreneurial intention of subsistence women as screening variables for entrepreneurship prospects.

This study is designed to suggest a possible detection or screening device for prospective women entrepreneurs in developing markets. The research may also be vital in ensuring that technical as well as financial support is channelled to the right recipients with entrepreneurial intentions. It focuses on how innovativeness, proactiveness and risk taking motivates a woman in a subsistence market to have an entrepreneurship intention and also how age, educational level and family business background moderates the relationship between entrepreneurship intention and orientation. The direct effects of demographic factors were also tested. The research could also be used as a preliminary instructional device to identify entrepreneurial aspects that are deficient in prospective trainee women entrepreneurs. Entrepreneurship is an indispensable ingredient for economic growth. Its value is exhibited in numerous ways such as by identifying, evaluating and making the most use of emerging prospects for businesses and driving the economy ahead through transformation (Baharudin et al., 2020; Cuervo et al., 2007; Neneh, 2018; Rosca et al., 2020; Siba, 2019). It also leads to the generation of employment and consequently, to the enhancement of an all-inclusive wellbeing of the general public (Reynolds, 1987; Zahra, 1999).

The paper unfolds as follows: the next section delves on literature review, divided into theoretical foundations and hypotheses development, followed by research methods. The logical flow takes us to presentation of results and subsequent discussions as well as conclusions, limitations and future study.

2. Literature review

2.1. Theoretical foundations

The thrust of this section is to discuss the theoretical foundations that underpin this research. The conceptual model of the study (see Figure 1) takes from the Fishbein and Ajzen (1975, p. 1985) legacy whilst the antecedents of entrepreneurial intentions were buoyed on Shapero’s entrepreneurship event model (Shapero, 1975). The liberal feminist theory brings the rural women marginalisation conceptualisation as adopted in this study.

2.1.1. The theory of planned behaviour (TPB) and entrepreneurial event model

The conceptual model of this study was based on the theory of planned behaviour (Ajzen, 1985) which was a sequel and logical development from the theory of reasoned action (Fishbein & Ajzen, 1975). The TPB is a leading model on behavioural intentions studies and it is assumed that intentions are a surrogate of actual behaviour (Taylor & Todd, 1995). Gird and Bagraim (2008) appreciate that this is a perfect model to easily understand entrepreneurial behaviour. It is the attitude-behavioural intention link which is the guiding framework of the conceptual model of this study.

The entrepreneurship event model was propounded by Shapero (1975) and highlights that certain factors are very crucial to trigger an individual to go for a business venture. Hence, according to this theory, entrepreneurial intentions are subject to three fundamental foundations which are desirability, feasibility and propensity to act (Shapero & Sokol, 1982). Prospective women who possess these characteristics or the appropriate attitude are therefore highly likely to establish a business. Ngugi et al. (2012) agrees with Shapero and Sokol (1982) by pointing out that precise desirability and perceived self-efficacy are very vital foundations for perceived desirability and feasibility.

2.1.2. Liberal feminist theory

The main women entrepreneurship theory related to this study is the liberal feminist theory. This theory originated in the 18th century arguing that men and women are basically the same since a human being is defined by the ability to be reasonable. Their difference comes from discrimination and imposed barriers like unequal access to education or social segregation. However, these barriers are not permanent and can be removed. As it underpins this research, the liberal feminist theory mainly focuses on the problems faced by individual women as well as the practical solutions to extenuate the habits and preconceptions that lead to gender inequality. These misconceptions are also prevalent with subsistence women whose entrepreneurial potential has been underrated. Broadly speaking, the liberal feminist theory focuses on the manner in which women are viewed and financed in entrepreneurial operations (Rottenberg, 2014).

From a tender age, individuals inherently adopt both socially and professionally erected gender principles. At that tender age, the young women and girls are recurrently subjected to the view that superior businesses are for men. They are therefore likely to suffer from an inferiority complex to initiate and run similar superior businesses that are commonly run by men. In fact, they believe that to run such kind of businesses is to enter the ‘men’s world’ which is a taboo, especially in subsistence markets. Due to this mentality, these prospective women entrepreneurs will display a reduced disposition towards such a type of entrepreneurship which men usually compete for (Inzlicht & Schmeichel, 2012). In addition, the women who repeatedly get subjected to prototypes and characters of women entrepreneurs as beneficiaries of small loans and owner/managers of small businesses are likely not to excel as much as men do. They may make these small business owner/managers their role models hence they will in turn develop entrepreneurial intention to start and run small business ventures. Consequently, majority of scholars concur on the notion that women have a higher aptitude to go for social as well as non-monetary oriented organisations (Inzlicht & Schmeichel, 2012; Langowitz & Minniti, 2007).

This gender duality of placing men and women in separate baskets is pernicious to women who intent to grow highly profitable and growth-oriented businesses. The women will be hesitant to start businesses associated with men. This dichotomy instead, gives the men a huge advantage in business and society. In other words, the liberal feminist philosophy outlines clearly how the gender pigeonhole and the gender function prohibit women to benefit easily and in abundance from resources that are at the disposal of men. This philosophy also brings to light the remedies at personal level that extenuate these obstructions. Moving forward, this emancipation of women must be inclusive of rural women. This study sought to bridge this loophole by having a predictive model on subsistence women’s entrepreneurship orientation and intentions.

2.2. Hypotheses development

2.2.1. Entrepreneurial orientation

Entrepreneurial orientation is the degree to which an organisation or individual consistently acts entrepreneurially rather than conservatively (Covin & Wales, 2012). Entrepreneurial orientation is understood to be expounded by a list of characteristics. These features encompass the desire to take risks, innovativeness, proactiveness, independent or autonomy and determined initiative or competitive aggressiveness; which have all emanated from entrepreneurship and business blue print literary texts (Bolton & Lane, 2012). However, the current study excluded autonomy and aggressiveness. These two constructs had been dropped by Bolton and Lane (2012, p. 227) on the development of the Individual Entrepreneurial Orientation scale adapted in this study due to low Cronbach alphas. Hence the researchers decided drop the two constructs basing on the same reasons.

Rauch et al. (2009) articulate that the three facets of entrepreneurial orientation which have been occasionally applied and quoted harmoniously in the previous studies include risk-taking, innovativeness, and proactiveness. These three are described as indispensable constructs and are used together to capture the entrepreneurial intention. Awang et al. (2016) unveil that entrepreneurial orientation stands for the strategies and operations that unveils a ground for entrepreneurial choices and measures. It follows therefore, that the formulation of strategy as a process depicts a person’s entrepreneurship intention. The qualities of an entrepreneurially oriented prospective woman who should qualify for a technical and financial assistance can be compared to an entrepreneurial company which deals with markets constituting innovative and risk products (Miller, 1983). Such qualities ensure competitive advantage.

Entrepreneurial orientation is very significant in that it helps the company’s top executive to isolate the mandate of the company, maintain the business’ focus and map a way forward, to accomplish greater benefits than its rivals (Rauch et al., 2009). Hence, a prospective woman with such an orientation will equally be equipped with skills to foster the enterprise forward and to improve the welfare of the society.

2.2.1.1. Innovativeness as an entrepreneurial orientation dimension

Innovativeness is viewed as a person’s attempt to produce new products having unravelled concealed opportunities and provide novel solutions (Lumpkin & Dess, 1996, 2001; Sorayah & Dygku, 2017). This encompasses trial and inventiveness that result in the production of unique products that have features which extend consumers’ utility horizon. S. Miller and Friesen (1982) argue that such innovative firms or individuals do so occasionally while taking risks in product market formulation. On the contrary, Hansen (1997) as supported by Awang et al. (2016) opine that it is pragmatically unendurable to do similar activities and hence any new invention or idea has to be viewed as innovation.

To sustain competitive position and to survive, women entrepreneurs have to be innovative. For organisational success, innovativeness is vital and fosters entrepreneurial orientation (Hult et al., 2004). Additionally, Schumpeter (1934) as well as Galindo and Mendez-Picazo (2013) assert that innovativeness is at the very core of entrepreneurship. It is a method applied by entrepreneurs to manoeuvre through competition and exploit economic opportunities to invent new products.

Empirical studies indicate the ability of women entrepreneurs to outwit their competitors through novel solutions (Ayub et al., 2013). A study conducted by Ayub et al. (2013) on 60 women entrepreneurs in Pakistan are in tandem with the argument by Cheng et al. (2009) together with Ndubisi and Iftikhar (2012) that innovativeness is vital for the success of entrepreneurial dealings. In a separate research, in Kwazulu Natal, South Africa, government programmes and policies were assessed on women entrepreneurs (Okeke-Uzodike. et al., 2018). The research concluded that there is need for an innovative state of mind, inherent personal motivation and support from both the public and private sectors for one to be a prosperous entrepreneur. The study recommended that the South African government should intervene through empowerment programs in support of women in order to attain its vision 2030, which relate to the National Development Plan (NDP). Moreso, 274 women-owned firms were assessed by Jyoti et al. (2011), and the conclusion was that the business has to be highly innovative to gain competitive advantage.

Therefore, from the discussion, we proposed that:

H1: The innovativeness of a woman positively influences her entrepreneurial intention.

2.2.1.2. Proactiveness as an entrepreneurial orientation dimension

Proactiveness is the willingness of an entrepreneur to act, where the individual seeks opportunities and looks forward to act well ahead of competitors so as to benefit from first mover advantages be it on invention of new products and services whilst the rival is still passive (Lumpkin & Dess, 2001; Miller, 1983). In other words, proactiveness is defined as the ability to scout for concealed opportunities which may relate to current product provisions, extending to unchartered waters in terms of new products. This gives the entrepreneur an edge over competitors as they drop products that are on the decline stage (Venkatraman, 1989). Its aim is to ascertain the susceptibility to be ahead, rather than being the follower (Covin & Slevin, 1986). This line of thought moves in the same vein with Foss and Klein (2010)’s point that an entrepreneurial action enshrines holding and taking heed of profit generating chances that arises in a disjointed world. Proactiveness therefore is very crucial to an entrepreneurial orientation due to its possibility to display an optimistic outlook. This outlook moves along with an innovative activity usually associated with the entrepreneurial process (Lumpkin & Dess, 1996).

Social networking has been found to enhance proactiveness (Nziku & Struthers, 2018). This type of networking is a strong agent of behaviour influence and attitude change towards business start-up and sustenance. Wu and Wang (2011) opines that proactiveness, as a grant design of entrepreneurial activity, indicates a forecast into the time ahead and an ascertainment of market demand. According to Miles et al. (1978) as well as Wong (2012), other scholars discovered that the firm that immediately follow suit in a new market can just be as spearheading as the ground breaker and is most probably able to be a winner through being proactive. Prior researches unveiled that a proactive character is greatly linked to entrepreneurial intention amongst students as opposed to parental paradigm and gender (Baker & Sinkula, 2009; Crant, 1996). In order to take advantage of an opportunity, being the ground breaker is very predominant. This will usually result in high profits and establishment of brand recognition.

Avlonitis and Salavou (2007)’s research indicates that proactiveness is a major leader to the success of new inventions. This means that highly involved and ignorant entrepreneurs differ to a larger extent in one area of innovativeness, which is also referred to as product or service variation. Proactiveness presents a challenge in that its characteristic of introducing new products and services is closely linked to innovativeness. Morris and Paul (1987) did a research which involved twelve-items for identifying innovativeness, risk-taking and proactiveness. This research disclosed an answer to this challenge and it concluded that innovation is not a replacement of proactiveness.

Therefore, the prediction is:

H2: Proactiveness of a woman positively influences her entrepreneurial intention.

To avoid conflating innovativeness and proactiveness, their differences are succinctly explained. Innovativeness is a tendency to introduce new products or coming up with novel solutions to a problem through trials, experiments and marketing intelligence. However, proactiveness refers to the willingness to take action so as to gain first mover advantages in anticipation of a change in customer needs.

2.2.1.3. Risk taking as an entrepreneurial orientation dimension

According to Quince and Whittake (2003), risk taking is the degree to which people are different in their desire to confront and truculent to risk. Risk taking will always be an agreeable and popular scale to deal with entrepreneurial orientation (Al Mamun et al., 2017; Miller, 1983). Risk-taking means the propensity to take part in brave decisions and activities (Kumar et al., 2018; Lumpkin & Dess, 2001). While other scholars like Neneh (2014) as backed by Fatoki (2014) found out that women entrepreneurs were risk-takers, others researchers noted that some of these women have risk averse traits (Boohene et al., 2008; Wiklund & Shepherd, 2003). Risk taking encompasses partaking in audacious activities to advance into the unknown, accessing huge loans, and investing huge resources in a volatile environment (Rauch et al., 2009; Al Mamun et al. (2017). Entrepreneurs must give first preference to their risks (Ayub et al., 2013; Mozumdar et al., 2020). This is essential because of the uncertainties in the economic environment.

A study was performed in Tanzania, for women involved in the food processing industry (Langevang et al., 2018). One of the findings was that women are now breaking the chains of African patriarchal mentality that reduces them to be mere consumers and home defenders who wait to be taken care of by their male counter parts. These women are now entrepreneurs with the ability to pull themselves up and even successfully compete with men in business. Women business associations (WBAs) proved to be one such platform, which is very helpful in giving support to women entrepreneurs in Tanzania. However, policies that support women to run their own businesses must be priopritised by most developing economies (Baharudin et al., 2020; Neneh, 2018)

Risk-taking has also been explained as the aptitude and eagerness of a business or person to go for well thought out and schemed golden opportunities in the business’ marketplace despite uncertainties attached to these opportunities (Lumpkin & Dess, 2001; Neneh & Van Zyl, 2017). The tag attached to risk-taking in entrepreneurial orientation can also be identified from the greater role it plays in entrepreneurial behaviour (Fatoki, 2014; Quaye & Acheampong, 2013). Risk-taking results in the going concern of SMEs (D. Miller & Friesen, 1978; Neneh, 2014). More so, risk-taking is viewed by Jalali et al. (2014) as having a strong and positive relationship to firm performance and growth. Alternatively, Wiklund and Shepherd (2003) as affirmed by Hughes and Morgan (2007) found out that risk-averse behaviours lead to poor performance due to a lack of willingness to be robust in grabbing market opportunities.

Therefore, hypothesis 3 is:

H3: Risk-taking propensity of a woman positively influences her entrepreneurial intention.

2.2.2. Effect of demographics to entrepreneurial orientation and intention

A variety of factors motivates an individual to embark on entrepreneurship. Studies on the influence of demographic factors which lead to entrepreneurial intention are sparse and findings from these studies are not consistent (Sasu & Sasu, 2015; Wang & Wong, 2004). However, there is a general consensus that demographics have an impact on entrepreneurial intention.

2.2.2.1. Family business background

Family business background has a greater impact on enticing people to start their own businesses. A person raised in a family business set up is motivated to start own business in future (Alsos et al., 2011; Botha, 2020; Chaudhary, 2017; Crant, 1996). Parents who run businesses are keen to educate and help their children to start their own businesses. As an example, Cooper et al. (1994) as corroborated by Sandberg and Hofer (1987) concur on the notion that, children whose parents are entrepreneurs use their parents as role models when operating their own businesses. This means, they copy strategies and tactics of running their business from their parents. These children channel their means of survival from establishing and running their own businesses just like their parents (Fairlie & Robb, 2007; Mcelwee & Al-Riyami, 2003). This practice is common among the Indian nationals who are highly business minded and run their own businesses. Brown (1990) conducted a study in the United Kingdom which was a training program to help university students to form their own businesses. Results from the study indicated that 38% of the students were keen to start their own businesses and it was also found out that their fathers were business owners. Their family business background may have motivated them into such a desire. Crant (1996) together with Schiller and Crewson (1997) reached the same conclusion in their studies

Therefore, from the above discussion, hypothesis proposed is:

H4a: The relationship between entrepreneurial orientation and intention is moderated by the family business background.

H4b: Family business background has direct effects on entrepreneurship intention.

2.2.2.2. Level of education

Sasu and Sasu (2015) as established by Botha (2020) opines that the time frame which an individual take in general education positively influences their level of entrepreneurship. Education is important in instilling entrepreneurial skills (Al Mamun et al., 2017; Teoh & Chong, 2008). A study conducted by Neneh (2014) concluded that a graduate from university possess a higher inclination towards entrepreneurship than a non-graduate equivalent. On the contrary, some studies argue that the link between university education and entrepreneurship is weak generally (Chaudhary, 2017; Parnell et al., 1995; Turker et al., 2005). More so, Davidsson and Honig (2003) found out that one’s education can lead to new opportunity discovery, but it does not necessarily follow that such an individual will open a new business to take advantage of that opportunity.

Therefore, hypothesis 5 is:

H5a. Level of education moderates the relationship between entrepreneurship orientation and intention.

H5b. Level of education has direct effect on entrepreneurship intention.

2.2.2.3. Age

Ancient literature has not paid much attention to age as entrepreneurial intentions prognosticate (Kazmi, 1999; Lewis & Massey, 2003; Neneh & Van Zyl, 2017; Quaye & Acheampong, 2013). Surprisingly, of late, attention to age as a variable controlling entrepreneurial intention has been given much recognition and examples of such scholars who focused on age includes Zissimopoulos and Karoly (2007), Jalali et al. (2014), De Kok et al. (2010), and Al Mamun et al. (2017). Evidence have been gathered which indicate that individuals usually think of starting a business when they are about 25 to 34 years (Choo & Wong, 2006; Delmar & Davidsson, 2000; Hughes & Morgan, 2007; Wiklund & Shepherd, 2003). Age really triggers an entrepreneurial behaviour in people (Coulthard, 2007; Stohmeyer, 2007). According to Gatewood et al. (2004) younger people possess a greater zeal to act entrepreneurially and form a business than older people.

Therefore, from the discussion, hypothesis proposed is:

H6a. Age moderates the relationship between entrepreneurship orientation and intention.

H6b. Age has direct effects on entrepreneurship intention.

2.2.3. Entrepreneurial intention

Cognitive psychology is the root of the notion of intention and helps to explain human behaviour (Fatoki, 2014). Intention is a psychological state of an individual that motivates the individual to achieve a desired goal or plan of action. According to Bird (1988) intentionality is explained as a disposition commanding a person’s thoughts, encounter and steps towards a particular objective. Hence, Indira (2014) state that entrepreneurial behaviours are also designed behaviours and intention is a forecast of entrepreneurial behaviours. Entrepreneurial intention is possessed by a person who is likely to start up an entrepreneurial venture, or becoming self-employed (Bird, 1988; Thompson, 2009; Tkachev & Kolvereid, 1999). It can generally be defined as an individual’s aim of starting a business venture in the foreseeable future. However, in some instances, some women, especially in Africa are faced with conflicting roles, where their effort is required in the society in which they live and at their entrepreneurial workstations (Hundera et al., 2019). This emanated from an Ethiopian case study of 307 female entrepreneurs. The study found out that women with conflicting roles can mitigate them by applying a number of strategies, among them compromisation, social sustenance, dedication to the entrepreneurial function or satisfaction of all roles (Hundera et al., 2019).

Indira (2014) opines that, as an intentional activity, entrepreneurship is twofold, that is, it is based on the capacity and the intention of a person seek, discover and grab an opportunity to maximise the benefits that arises hence forth. Krueger et al. (2000) produced a model in which the tendency to take risks and internal locus of control positively influences a feeling towards entrepreneurship and eventually shapes entrepreneurial intent. On top of that, Duijn (2009) identified notable findings in his empirical research that the most crucial entrepreneurial constructs influencing entrepreneurial attitude were proactiveness and risk-taking proclivity. Choo and Wong (2006) articulates that entrepreneurial intention involves hunting for vital information which is essential in achieving venture creation objectives. A variety of researches, Indira (2014), Reynolds (1987), and Krueger et al. (2000) provided empirical evidence that entrepreneurial intention is the first indicator of entrepreneurial behaviour. The overall conceptual model of this study is shown on Figure 1.

Figure 1. Conceptual model of the study.

Source: Authors’ own

3. Research method

This study sought to determine the direct effects of entrepreneurial orientation on entrepreneurial intention, the direct effects of demographic factors on entrepreneurial intention as well as the moderated effect of demographic attributes on the relationship between entrepreneurial orientation and entrepreneurial intention. This section provides a detailed analysis followed to achieve these objectives and starts from the validation of the constructs on the model.

3.1. Research design

A quantitative approach was employed in this study. Quantitative approach encompasses the investigation of a natural or social context using raw data analysed statistically. Data were collected from a survey of women entrepreneurs. The research design was basically explanatory as it sought to establish relationships between constructs.

3.2. Population and sample

The population comprises of prospective women entrepreneurs in the subsistence markets of Manicaland province, Zimbabwe. The study focused on Manicaland Province because of its strategic location and demographic advantages. Manicaland is close to Mozambique and is also a gateway to South Africa, a strong trading partner of Zimbabwe. It is one of Zimbabwe’s ten provinces with a hype of commercial activities due to its ability to support all forms of agricultural activities, ranging from those that require high rainfalls and those that needs low rainfalls. Again, Manicaland is endowed with vast natural resources qualifying it to be a centre of mining activities. As far as the population distribution is concerned, in the whole of Zimbabwe, Manicaland is the only Province with more people in the rural areas (84.6%) as compared to those in the urban areas who are 15.4% of the total people in the province, (Inter Censal Demographic Survey, 2017). Hence basing on the fact that Zimbabwe has more women than men, the researchers found it ideal to use the rural women of Manicaland province.

When it comes to the sample size, it was determined basing on a number of factors (Bryman, 2016) of which in this study; cost and poor research culture of respondents were the major factors. The sample size for the study was 192, this was optimal for variance based—Structural Equation Modeling (SEM) in lieu of covariance based-Structural Equation Modeling as this was found to be more robust for sample sizes which are below 200 (J. Hair et al., 2010).

3.2.1. KMO and Bartlett’s test

Pallant (2013) argues the need to test for sampling adequacy prior to any application of EFA, as well as the testing of the homogeneity of variance between the test and identity matrices of the data. To achieve this, Kaiser-Mayor-Olkin (KMO)’s test of sampling adequacy as well as the Bartlett’s test for sphericity were computed. J. Hair et al. (2010) and Pallant (2013) recommend that the optimal KMO statistic should be greater than 0.5, while the Bartlett’s test must be significant at p < 0.05. These assumptions were tested and the results are shown below Table 1:

The KMO statistic was 0.801 > 0.50 and with respect to the Bartlett’s test, χ²(253) = 3129.303; p = 0.000 < 0.05. From the foregoing, the outcomes for KMO were both greater than 0.5 and both outcomes for the Bartlett p-values were less than 0.05, thereby confirming the validity of the use of factor analysis. To achieve the exploratory factor analysis, the researchers considered the Principal Component Analysis (PCA) as the extraction method. This decision was made on the understanding that it was more robust as compared with other extraction methods such as the image factoring, alpha factoring, principal axis factoring, unweighted or generalized least squares (Harrington, 2009; Yong & Pearce, 2013). To further improve the extraction robustness, rotation was applied and because the constructs were expected to be uncorrelated or negligibly correlated, the orthogonal varimax rotation method was chosen in lieu of the direct oblimin rotation methods (Field, 2016; Hair et al., 2014).

3.3. Variable and measurement

The study had the following independent variables:

1. innovativeness

2. proactiveness

3. risk-taking

Individual orientation sub-constructs of innovativeness, proactiveness and risk taking were measured using Bolton and Lane (2012) individual entrepreneurship orientation scale. Individual entrepreneurial intention was measured using items adapted from Linan and Chen (2009) and Thompson (2009) individual entrepreneurship intention scales. Reverse items were avoided because they are least understood in subsistence markets (Steenkamp & Burgess, 2002). Demographic profiles were theorized to have moderating effects as well as direct effects. The demographics were education, family business background and age whereas the dependent variable was entrepreneurial intention (see Figure 1). A questionnaire of 23-items was developed to collect data from subsistence women excluding demographic questions. The English version was translated into Shona, the vernacular language of rural women respondents in the eastern province of Zimbabwe (Manicaland) and back-translated in line with translation best practice (Brislin, 1970). Pilot testing of the questionnaire was done before data collection. Only those women who are not yet entrepreneurs were considered. The questionnaire comprised of items about the level of entrepreneurial capability of the women, their level of innovativeness, proactiveness and risk-taking. Questions on age, education and family business background were also included to enable testing moderating and direct effects of these demographic profiles on entrepreneurial intentions. We used convenience sampling to test the hypotheses. Similar to Marshall et al. (2006)’s sampling strategy, data were collected from consenting women in line with the Helsinki declaration on ethical data collection and also to enhance respondent’s honesty.

In other words, the study used structural equation modeling to address the research hypotheses. These hypotheses comprised of both direct relationships between latent variables as well as demographic attributes which measured both the direct and moderated relationships. To better handle the latent variables, scholars do concur that structural equation modeling is more robust in lieu of other multivariate regression techniques (Hair et al., 2018). Using standard regression tests failed to accommodate the latent effect in both the independent and dependent variables (Field, 2016). Aggregating the items was inaccurate as they failed to accommodate the inter-item discrepancies (Hair et al., 2011). To this effect, the researchers embraced structural equation modeling (SEM). Since the sample size used was less than 200, SmartPLS, a variance-based SEM tool was used in lieu of the covariance-based statistical tools such as IBM SPSS Amos v26.

3.3.1. Exploratory factor analysis

The research comprised of two broad constructs, that is, entrepreneurial orientation (EO) and entrepreneurial intention (EI) and each of these two constructs comprised of several items. According to Kline (2005), it is vital to explore and uncover the underlying structure among the set of items for each of the constructs. Lee (2007) as affirmed by Schmitt (2011) recommend the use of exploratory analysis, citing that this is a multivariate dimension reduction technique that seeks to establish the principal dimensions emerging from the data.

3.4. Data collection method

The data were collected using a questionnaire. The data collection was carried out from June to August 2019. From the questionnaire, 23 of the items were gauged on five-point Likert scale ranging from 1 = strongly disagree to 5 = strongly agree. The collected data were then tabulated and a validity and reliability test performed.

3.4.1. Construct validation

With a view to validating the research constructs prior to structural equation modeling, Carden et al. (2019) recommend the need to conduct validity testing of the extracted dimensions. For the construct validity, the researcher considered the use of the Confirmatory Factor Analysis (CFA) as prescribed by Tabachnick and Fidell (2007) and affirmed by Hair et al. (2018). Two key tests were done and include convergent and discriminant validity.

3.4.2. Convergent validity

For the assessment of the convergent validity, Byrne (2004), Kline (2005) together with J. Hair et al. (2010) prescribe a minimum path coefficient of 0.6. The results are presented on Appendix 4:

From the foregoing discussion, with respect to entrepreneurial orientation, the least observed statistic was 0.464, and because this was less than the prescribed minimum 0.60, this was dropped. For innovativeness, proactiveness and risk-taking, none of these had path coefficients that were less than the prescribed minimum, and thus for these, none of the items were dropped.

3.4.3. Discriminant validity

With respect to discriminant validity, both J. Hair et al. (2010) and Byrne (2004) recommend a maximum Heterotrait-Monotrait Ratio (HTMT) covariance of 0.85 between any of the constructs. The respective discriminant validity results are presented in Table 2. The HTMT between innovativeness and entrepreneurial intention was 0.386, and 0.103 with proactiveness, while with risk-taking this was 0.131. On the other hand, for risk-taking, the HTMT with entrepreneurial intention was 0.240, while with proactiveness this was 0.102. Lastly, the HTMT between proactiveness and entrepreneurial intention was 0.078.

Table 1. KMO and Bartlett’s Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy.		.801
Bartlett’s Test of Sphericity	Approx. Chi-Square	3129.303
	df	253
	Sig.	.000

Table 2. HTMT Discriminant Validity Results

	Entrepreneurial Intention	Innovativeness	Proactiveness
Entrepreneurial Intention
Innovativeness	0.386
Proactiveness	0.078	0.103
Risk-Taking	0.240	0.131	0.102

Table 3. SEM Results—Entrepreneurial Orientation Sub-Constructs on Intention

	Sample Mean (M)	Standard Deviation (STDEV)	T Statistics (|O/STDEV|)	P Values
Innovativeness -> Entrepreneurial Intention	0.337	0.076	4.813	0.000
Proactiveness -> Entrepreneurial Intention	0.039	0.208	0.374	0.354
Risk-Taking -> Entrepreneurial Intention	0.168	0.071	2.331	0.010

Table 4. SEM Results Demographics moderation between EO and EI

	Sample Mean (M)	Standard Deviation (STDEV)	T Statistics (|O/STDEV|)	P Values
Age -> EI	−0.107	0.073	1.585	0.057
EO -> EI	0.446	0.080	4.578	0.000
Education -> EI	−0.034	0.066	0.468	0.322
Family -> EI	−0.034	0.073	0.421	0.336
Moderating Effect Age -> EI	−0.025	0.076	0.118	0.450
Moderating Effect Education -> EI	0.051	0.078	0.792	0.206
Moderating Effect Family -> EI	−0.007	0.097	0.021	0.491

EO: Entrepreneurial Orientation EI: Entrepreneurial intention

Table 5. Model Fit Results

	SEM Model 1		SEM Model 2
	Saturated Model	Estimated Model	Saturated Model	Estimated Model
SRMR	0.067	0.067	0.054	0.054
d_ULS	0.342	0.342	0.306	0.306
d_G	0.100	0.100	0.189	0.189
Chi-Square	115.665	115.728	226.055	226.055
NFI	0.916	0.914	0.943	0.943

From the results, the maximum HTMT observed was 0.386 and because this was less than 0.85, this meant that discriminant validity was not violated.

3.5. Analysis method

Data analysis was performed using the Smart PLS program and three stages were carried out, that is the evaluation of measurement models, structural models, followed by the testing of research hypotheses.

4. Results and discussion

4.1. Evaluation of the measurement models

4.1.1. Communalities

Upon running the PCA, according to Field (2016), the first criteria of cleaning up the outcome was the consideration of the communalities. These communalities help determine the degree of correlation between an item and the aggregated items, and they show the common variance explained. Under optimal conditions, the common variance explained ought to be greater than 0.4 (Costello & Osborne, 2005; Field, 2016). The key findings are presented are shown in Appendix 1

Three communalities were below the minimum acceptable threshold of 0.40, and these were for the items I would like to start my own venture (0.304), Among various options, I would rather be an entrepreneur (0.381) and I am determined to create a firm in the future (0.370). These were all for the construct entrepreneurial intention and were dropped from the analysis.

4.1.2. Total variance explained

The Guttman-Kaiser criterion (D. Child, 2006) was used to establish the number of optimal components, and according to this criterion, only components with eigenvalues which are greater than 1.0 ought to be selected. From the scree plot in Figure 2, six components had an eigenvalue that was greater than the minimum threshold 1.0. The highest eigenvalue was 5.335 (variance explained = 17.841%). The second component explained a variance of 13.610% (Eigenvalue = 4.092), while the third explained a variance of 12.561% (Eigenvalue = 2.278). The fourth component had a variance explanation of 10.274% (Eigenvalue = 2.152), while the fifth explained 9.160% (Eigenvalue = 1.274) and the last component explained 6.736% and had the least eigenvalue of 1.011. The cumulative total variance explained by the six components was 70.183%, and being greater than the prescribed minimum of 50.0% (J. Hair et al., 2010), the findings do confirm that the six extracted components were all valid.

Figure 2. Scree Plot.

The respective total variance explained is presented on Appendix 2.

4.1.3. Rotated component matrix

The rotated component matrix was extracted and according to Dugard et al. (2010), the optimal threshold for item inclusion in each of the components was 0.5. However, scholars such as Field (2016) argue that even 0.4 would be tolerable for exploratory studies, while for confirmatory studies, 0.7 would be ideal. The resultant rotated component matrix is presented on Appendix 3.

From the outcome above, six components were extracted using the inclusion criteria defined earlier, that is, factor loadings greater than 0.50, the first and fourth components comprised of four items while the second, third and fifth components comprised of three items. Only the sixth component had two items. Ultimately, four of the items were dropped as they had factor loadings that were less than 0.50 and these included: I am ready to do anything to be an entrepreneur, I am determined to create a firm in the future, I would like to start my own venture and among various options, I would rather be an entrepreneur.

Moreso, according to Field (2016) together with Carden et al. (2019), the general standard threshold for the assessment of reliability is 0.7, however, alpha loadings as low as 0.6 are still considered to be reliable while those above 0.7 are considered to be the most desirable (Sweet & Grace-Martin, 2012). From the above results, the least observed alpha statistic was 0.350 for the sixth component and this was less than 0.70, while the second least was the fifth component (0.497), again, less than 0.70. The rest of the other components were all greater than 0.70, with the highest being 0.992. In this regard, components 1, 2, 3 and 4 were retained, while components 5 and 6 which failed to meet the mark were discarded off (J. Hair et al., 2010).

4.1.4. Naming the components

The last stage for EFA was the attribution stage which entailed the assignment of names to the extracted components.

Component 1: Entrepreneurial Orientation -Proactiveness

The first component comprised of:

• I favour experimentation and original approaches to problem solving rather than using methods others generally use for solving their problems.

• I prefer to step-up and get things going on projects rather than sit and wait for someone else to do it.

I tend to plan ahead on projects.

I usually act in anticipation of future problems, needs or changes.

Experimentation, stepping-up, planning and acting in anticipation, all resonated with the proactiveness aspect of entrepreneurial orientation.

Component 2: Entrepreneurial Orientation—Innovativeness

The following items constituted the second component:

I often like to try new and unusual activities that are not typical but not necessarily risky.

• I prefer to try my own unique way when learning new things rather than doing it like everyone else does.

• In general, I prefer a strong emphasis in projects on unique, one-of-a-kind approaches rather than revisiting tried and true approaches used before.

Trying new and unusual activities, trying unique ways, as well as unique and one-of-a-kind approaches, all tended to reflect the attributes of being innovative.

Component 3: Entrepreneurial Orientation—Risk taking

For component 3, the respective items were:

I am willing to invest a lot of time and/or money on something that might yield a high return.

I like to take bold action by venturing into the unknown.

I tend to act boldly in situations where risk is involved.

Willing to invest a lot of time, taking a bold action and acting boldly, all reflected the risk-taking attitude.

Component 4: Entrepreneurial Intention

The fourth component comprised of entrepreneurial intention-related items and these were:

I have very seriously thought of starting a firm.

I will make every effort to start and run my own firm.

Being an entrepreneur would entail great satisfactions for me.

I have a strong intention to start a firm someday.

4.2. Hypothesis tests

Having confirmed the convergent validity and discriminant validity, the researchers sought next to evaluate the relationships between the research constructs and this was to be achieved through structural equation modeling. In this light, researchers classify structural equation modeling techniques into either the covariance based structural equation modeling (CB-SEM) or the variance based structural equation modeling (VB-SEM), otherwise known as the partial least squares’ structural equation modeling (PLS-SEM) technique (Hair et al., 2018; Schmitt, 2011; Tabachnick & Fidell, 2007). However, the main factor considered was the sample size and since the sample size for the study was 192, this was optimal for VB-SEM in lieu of CB-SEM as this was found to be more robust for sample sizes less than 200 (J. Hair et al., 2010). In this respect, the researchers considered the use of the SmartPLS over CB-based SEM techniques. Standardised bootstrapped SEM was done with 500 sub-samples and the respective model is for the first three hypotheses is presented in Figure 3:

H₁: Innovativeness of a woman positively influences her entrepreneurial intention.

H₂: Proactiveness of a woman positively influences her entrepreneurial intention.

H₃: Risk-taking of a woman positively influences her entrepreneurial intention.

Figure 3. SEM—Entrepreneurial Orientation Sub-Constructs.

The respective path coefficient and p-values are presented in Table 3:

From the foregoing, the highest t-statistic was 4.813 (p = 0.000 < 0.05) and was observed for the relationship between innovativeness and entrepreneurial intention, and this was an indication that entrepreneurial orientation played the largest role towards entrepreneurial intention than the rest of the other entrepreneurial orientation dimensions. With the p-value being less than 0.05, the null hypothesis was rejected and the researcher confirmed that there was a significant relationship between innovativeness and entrepreneurial orientation. The second most significant entrepreneurial orientation dimension was risk-taking and the path coefficient was 2.331 (p = 0.010 < 0.05). Again, with the p-value being less than 0.05, the null hypothesis was rejected and the researcher confirmed that there was enough statistical evidence at the 95% confidence level that risk-taking had a significant influence on entrepreneurial intention.

Nevertheless, with respect to proactiveness, the t-statistic was 0.0374 (p = 0.374 > 0.05). In this regard, the p-value was greater than 0.05, it meant that there was not enough statistical evidence to support the hypothesised significance of the relationship between proactiveness and entrepreneurial intention. Effectively, the null hypothesis was not rejected. Further modeling the direct and moderating role of the demographic attributes, that is, employment status, family entrepreneurial history, age and education were also tested. The corresponding hypothesis tested included:

H_4a:Family business background moderates the relationship between female entrepreneurial orientation and entrepreneurial intention.

H_4b Family business background has direct effects on entrepreneurial intention.

H_5a:Highest level of education moderates the relationship between female entrepreneurship orientation and entrepreneurial intention.

H_5b: Education has direct effects on entrepreneurial intention.

H_6a:Age moderates the relationship between female entrepreneurship orientation and entrepreneurial intention.

H_6b: Age has direct effects on entrepreneurial intention.

To achieve the above hypotheses, again, standardised bootstrapping was done using 500 sub-samples in SmartPLS and the results are presented in Table 4 and Figure 4:

From the above outcome, only the direct relationship between entrepreneurial orientation and entrepreneurial intention was statistically significant with a high t-statistic of 4.578 > 1.96 and a p-value of 0.000 < 0.05. In this regard, the null hypothesis was rejected for the fourth research hypothesis and the researchers confirmed that there existed a statistically significant positive influence of entrepreneurial orientation on entrepreneurial intention. None of the demographic variables had a statistically significant direct effect or a statistically significant moderation effect as also shown below:

Figure 4. SEM—Moderation Effect between EO and EI.

For the direct effect of family entrepreneurial background on the women’s entrepreneurial intention, the path coefficient was 0.421 (p = 0.336 > 0.05), and for the direct effect of age, this was 1.585 (p = 0.057 > 0.05) while for the highest level of education the path coefficient was 0.468 (p = 0.322 > 0.05). Effectively, none of the demographic factors had a statistically significant direct effect on entrepreneurial intention. In this regard, the researchers failed to reject the null hypothesis for all the direct relationships tested Table 5.

With respect to the moderation effect of the demographic variables on the relationship between entrepreneurial orientation and entrepreneurial intention, for family entrepreneurial background, the moderation effect path coefficient was 0.021 (p = 0.491 > 0.05), for the moderation effect of age, the computed path coefficient was 0.118 (p = 0.457 > 0.05) and for the moderation effect of the highest level of education, the respective path coefficient was 0.792 (p = 0.206 > 0.05). Again, none of the demographic factors had a statistically significant moderation effect on entrepreneurial intention and in this light, the researchers failed to reject the null hypothesis for all the moderation effect relationships tested.

4.2.1. Model fit

With a view to validating the structural equation model results, Schmitt (2011) and Hair et al. (2018) recommend the use of goodness-of-fit tests. There are two main categories that are considered in PLS-SEM and these include the Standardized Root Mean Square Residual (SRMR) as well as Normed Fit Index (NFI) and this is supported by Hair et al. (2018). The SRMR was tested and the threshold considered was 0.08 (Hair et al., 2018). The results are presented below:

From the foregoing, the SRMR was 0.067 < 0.08 for the first model and 0.054 < 0.08 for the second model and being less than the maximum threshold, it followed that the SRMR was valid. Further, with respect to NFI, the computed statistic was 0.914 for the first model and 0.943 for the second model, and this was greater than 0.85 (Dijkstra & Henseler, 2015). Hence, the above results indicate that none of the model fit tests was violated and, in this regard, the researcher confirms that the research model used was valid.

4.3. Discussion

The first hypothesis (H₁) predicted that the innovativeness of a woman positively influences her entrepreneurial intention. This hypothesis was accepted (the highest t-statistic was 4.813 (p = 0.000 < 0.05, the p-value being less than 0.05). The implication is that there is a greater significant relationship between innovativeness and entrepreneurial intention even for subsistence prospective entrepreneurs in rural areas. Schumpeter (1934) as well as Galindo and Mendez-Picazo (2013) discovered the same results as they concluded that innovativeness is at the very core of entrepreneurship. More so, the findings of this study are in tandem with the argument by Cheng et al. (2009) together with Ndubisi and Iftikhar (2012) who discovered that innovativeness is a key success factor of every entrepreneurial activity. Jyoti et al. (2011)’s resting point was that the business has to be highly innovative to gain competitive advantage meaning to say that innovativeness and entrepreneurial orientation are positively related. Innovativeness components should be trained to trainee rural women entrepreneurs to enhance their entrepreneurial intentions. These innovativeness facets are creativity and the tendency to experiment with new ideas rather than waiting for things to be tried and tested by others. Rural women also need to be equipped with technology skills so that they could use such technology in research and development of context specific new products to provide local solutions to subsistence marketplace problems and make money.

The third hypothesis (H₃) which predicted that the risk-taking behaviour of a woman positively influences her entrepreneurial intention became the second most significant entrepreneurial orientation dimension. The path coefficient was 2.331 (p = 0.010 < 0.05, with the p-value being less than 0.05). This means the null hypothesis was rejected and the researchers confirmed that there was enough statistical evidence at the 95% confidence level that risk-taking had a significant influence on entrepreneurial intention. The same results were obtained by Teoh and Chong (2008) as well as Fatoki (2014) who confirmed that women entrepreneurs, who are risk takers, goes for well-thought out and organised business opportunities in the market, despite the fact that the outcomes from such opportunities will be unpredictable. Another study by Rauch et al. (2009) found out that people who possess a strong entrepreneurial orientation are associated with a high-risk behaviour. Even in the context of subsistence marketplaces, boldness to venture into the unknown is a prerequisite for entrepreneurial intention. Rural women about to start own business need to be trained in taking calculated risks especially considering that risk taking includes the guts to borrow funds for the venture. Women who are deficient of the risk taking attribute need to be hypnotised into risk taking behaviour.

Subsistence women had a different characteristic on proactiveness (H₂). When it comes to proactiveness, the t-statistic was 0.0374 (p = 0.374 > 0.05). Since the p-value was greater than 0.05, it meant that there was not enough statistical evidence to support the hypothesized significance of the relationship between proactiveness and entrepreneurial intention. Effectively, the null hypothesis was not rejected. This is a unique result as compared to previous research on proactiveness (Avlonitis & Salavou, 2007). Just like the findings by Morris and Paul (1987), proactiveness was also acknowledged as a distinct sub-construct of entrepreneurial orientation after exploratory factor analysis.

The moderating and direct effect of demographic variables on entrepreneurial orientation and entrepreneurial intention were tested (H_4a, H_4b, H_5a H_5b, H_6a, H_6b) and none of them had a statistically significant direct effect or a statistically significant moderating effect. Basically, the researchers’ results indicated that for the direct effect of family entrepreneurial background on the women’s entrepreneurial intention, the path coefficient was 0.421 (p = 0.336 > 0.05). This means there was no statistically significant direct effect of family entrepreneurial background on entrepreneurial intention. Nguyen (2018) also reached the same conclusion when he noted that the statistical evidence available is not adequate to support the idea that any individual whose parents own businesses portrays a higher entrepreneurial intention than the one whose parents did not own a business. Alsos et al. (2011) together with Chaudhary (2017) noted different findings by stating that a family business plays a greater function in strengthening the growth of entrepreneurship among members of that family. Chaudhary (2017) further states that family background associated with self-employment will have a positive relationship towards entrepreneurial intent.

When it comes to the highest level of education the path coefficient was 0.468 (p = 0.322 > 0.05). It did not have a statistically significant direct effect on entrepreneurial intention. These findings are also consistent with the study of Davidsson and Honig (2003) who are of the view that the connection between educational level in general and entrepreneurship is not very strong and contested. These researchers opine that education can possibly help an individual to identify new opportunities even though it does not necessarily decide whether such an individual will form a new business to utilise the opportunity. On the other hand, education is found to have a greater role to play in instilling entrepreneurial skills (Al Mamun et al., 2017; Neneh, 2014; Sasu & Sasu, 2015).

In terms of age as a moderator of the relationship between entrepreneurship orientation and intention, the researchers found out that it was not significant. For the direct effect of age on entrepreneurial intention, it was 1.585, p = 0.057 > 0.05. This means that there is no statistically significant direct effect of age on entrepreneurial intention. Nguyen (2018) also indicated that there is no relationship between age and entrepreneurial intention. However, the results are not consistent with Coulthard (2007); Hughes and Morgan (2007) together with Wiklund and Shepherd (2003) who concluded that indeed, age is a triggering factor of entrepreneurial behaviour and that younger people are bolder to take steps toward acting entrepreneurially and establish a business than older people.

The insignificance of all demographic profiles in terms of their moderating and direct effects in subsistence marketplaces of Zimbabwe may actually mirror the economic outlook of the economy. Ndiweni and Verhoeven (2013) noted the rise of informal entrepreneurs across the country. These were prompted by economic hardships regardless of a person’s family business background, level of education and age. The employment population rate in Zimbabwe in 2019 (Zimstat, 2019, Labour force and child labour survey) was 36% and the rest of the population was unemployed. The informal sector in 2019 was much bigger than the formal sector (Zimstat, 2019). The rural sector would actually be worse off. These characteristics clearly exhibit the justification of the rural women entrepreneurial responses on the lack of moderating and direct effects of demographic profiles between entrepreneurial orientation and entrepreneurial intention.

5. Conclusion, limitations and future research

5.1. Conclusion

The main purpose of the study was to identify the propinquity between entrepreneurial orientation on entrepreneurial intention and the moderating and direct effects of demographic profiles as an oasis of establishing a predictive model on prospective rural women entrepreneurs. The results suggested that innovativeness and risk-taking as pointers to identify prospective women’s entrepreneurial intention were found to be the most appropriate. On the contrary, proactiveness was found to have no evidence to support that it has an effect to a rural prospective woman’s entrepreneurial intention.

It can be established that despite the challenges that most women in developed countries are faced with, being innovative will increase their chances of business success. The same conclusion was reached in a study which was carried out on Bangladeshi women by Mozumdar et al. (2020). The same study also indicated risk-taking as having the same effect on entrepreneurial intention as innovativeness. This basically means that before embarking on an entrepreneurial activity, these prospective women entrepreneurs should be ready to be associated with innovativeness and risk-taking.

In other words innovativeness and risk taking should be taken as characteristics or traits that should be possessed by any woman who intent to be a successful entrepreneur in a subsistence marketplace. This conclusion also support the conclusion reached by Neneh and Van Zyl (2017) who determined that innovativeness is very crucial for an entrepreneur. Additionally, the higher the levels of innovativeness and risk-taking in these prospective women entrepreneurs, the higher the chances of being successful. In simple words and in short, since it is always said that high risk will result in high returns, it is most probable that those women with a very high level of risk-taking propensity will stand a chance of yielding higher returns in their businesses.

Entrepreneurship attributes may also be affected or be determined by economic circumstances of respondents in an economy. This entails that risk-taking and innovativeness alone may not suffice to bring out a successful entrepreneur. There is need for technical, financial, and social support to enable these prospective entrepreneurs to positively contribute to the economic development of their nations. Policy making agents of the developing countries where these women are based are supposed to shoulder this responsibility.

When it comes to demographic attributes, (family entrepreneurial history, age and level of education), they do not necessarily help as they are insignificant in terms of moderation effect and direct effect on the relationship between female entrepreneurial orientation and entrepreneurial intention. This conclusion was also arrived at by Nguyen (2018) who identified an insignificant relationship when it comes to moderation effect and direct effect on the relationship between female entrepreneurial orientation and entrepreneurial intention. The deduction is that the prospective women entrepreneurs’ age, family business background and educational background is irrelevant when it comes to their entreprenerial intention.

5.2. Theoretical contribution

This study brings rural women entrepreneurship into the general women entrepreneurship literature which has mainly focused on urban women entrepreneurship. Whilst there have been a lot of studies on entrepreneurship orientation and intention, we extend these studies into subsistence markets which pose a unique socio-cultural setting. Innovativeness and risk taking entrepreneurship orientation has been noted to relate to entrepreneurship intention but the insignificance of demographic profiles in terms of age, education and family business background are surprising and points for consideration in subsistence women entrepreneurship literature.

The study validated entrepreneurial orientation and intention scales items in a subsistence market in Sub-Saharan Africa. A rigorous quantitative approach using partial least squares structural equation modeling was done. Original entrepreneurial orientation scale items developed by Bolton and Lane (2012) were confirmed after exploratory factor analysis to be valid in rural markets. However, only four items remained on the entrepreneurial intention scale items picked from Linan and Chen (2009) as well as Thompson (2009).

5.3. Practical contribution

When screening rural women prospective entrepreneurs, it critical to take into consideration potential women’s entrepreneurial innovativeness and risk-taking attitudes. The donors should administer measurement scale items for these two constructs but may not worry about proactiveness items and demographic profiles since these do not have any predictive power on identifying successful women entrepreneurs in subsistence markets. There is no need to read much on age, level of education and family business background when screening subsistence women to get successful entrepreneurs who may effectively utilise seed capital usually provided by donors. Financial institutions may do not need also to read much on these demographic profiles when evaluating potential rural women entrepreneurs’ potential to utilise advances and loans so as to minimise bad debts. Governments, may also follow suit and consider innovativeness and risk-taking attitudes to identify rural women to benefit from revolving funds provided to rural start-ups.

5.4. Limitations and future research

This study was conducted only on women prospective entrepreneurs, so the results cannot be generalised to male or girls and boys who desire to be entrepreneurs. Further studies on the relationship between entrepreneurial orientation of the women figure and entrepreneurial intentions using different methodology for example, ethnography is required especially on demographic variables because the results of this research are inconsistent with prior researches which stated that demographic variables has an impact on entrepreneurship intention (Chaudhary, 2017; Coulthard, 2007; Hughes & Morgan, 2007; Wiklund & Shepherd, 2003).

Moreso, further research needs to be conducted interrogating entrepreneurial orientation and intention with cultural variables such as values (see, Schwartz (1992) theory of human values to postulate a complete model for rural women entrepreneurs. Furthermore, personality variables may also be integrated to produce a comprehensive model to identify entrepreneurial intention in rural women.

Additional information

Funding

Authors received no direct funding for this research.

Notes on contributors

Lucia Mandongwe

Lucia Mandongwe is a lecturer at Manicaland State University of Applied Sciences (Zimbabwe) in the Faculty of Agribusiness and Commerce, department of Accounting. Her research interests are in business management, entrepreneurship, accounting and auditing.

Divaries C. Jaravaza

Divaries C. Jaravaza is a tenured full-time lecturer at Bindura University of Science Education (Zimbabwe). His research interests are in transformative consumer research, consumer behaviour in subsistence marketplaces, entrepreneurship and accounting.

Appendices

Appendix 1. Communalities of items

Table

	Initial	Extraction
I would like to work for myself	1.000	.576
I would like to start my own venture	1.000	.304
Being an entrepreneur implies more advantages than disadvantages to me	1.000	.597
A career as entrepreneur is attractive for me	1.000	.589
If I had the opportunity and resources, I would like to start a firm	1.000	.554
Being an entrepreneur would entail great satisfactions for me	1.000	.520
Among various options, I would rather be an entrepreneur	1.000	.381
I am ready to do anything to be an entrepreneur	1.000	.436
My professional goal is to become an entrepreneur	1.000	.413
I will make every effort to start and run my own firm	1.000	.682
I am determined to create a firm in the future	1.000	.370
I have very seriously thought of starting a firm	1.000	.747
I have a strong intention to start a firm some day	1.000	.448
I often like to try new and unusual activities that are not typical but not necessarily risky	1.000	.947
In general, I prefer a strong emphasis in projects on unique, one-of-a-kind approaches rather than revisiting tried and true approaches used before	1.000	.912
I prefer to try my own unique way when learning new things rather than doing it like everyone else does	1.000	.918
I favour experimentation and original approaches to problem solving rather than using methods others generally use for solving their problems	1.000	.985
I usually act in anticipation of future problems, needs or changes	1.000	.978
I tend to plan ahead on projects	1.000	.983
I prefer to step-up and get things going on projects rather than sit and wait for someone else to do it	1.000	.983
I like to take bold action by venturing into the unknown	1.000	.931
I am willing to invest a lot of time and/or money on something that might yield a high return	1.000	.958
I tend to act boldly in situations where risk is involved	1.000	.928
Extraction Method: Principal Component Analysis.

Appendix 2.

Total Variance Explained

Table

Component	Initial Eigenvalues			Extraction Sums of Squared Loadings			Rotation Sums of Squared Loadings
	Total	% of Variance	Cumulative %	Total	% of Variance	Cumulative %	Total	% of Variance	Cumulative %
1	5.335	23.196	23.196	5.335	23.196	23.196	4.104	17.841	17.841
2	4.092	17.790	40.987	4.092	17.790	40.987	3.130	13.610	31.451
3	2.278	9.903	50.890	2.278	9.903	50.890	2.889	12.561	44.012
4	2.152	9.358	60.249	2.152	9.358	60.249	2.363	10.274	54.287
5	1.274	5.539	65.788	1.274	5.539	65.788	2.107	9.160	63.447
6	1.011	4.395	70.183	1.011	4.395	70.183	1.549	6.736	70.183
7	.967	4.203	74.386
8	.913	3.967	78.353
9	.840	3.652	82.005
10	.761	3.307	85.312
11	.728	3.164	88.476
12	.680	2.956	91.433
13	.559	2.431	93.864
14	.465	2.024	95.887
15	.357	1.551	97.438
16	.271	1.180	98.618
17	.103	.447	99.065
18	.098	.426	99.491
19	.051	.221	99.712
20	.032	.138	99.850
21	.018	.079	99.929
22	.010	.044	99.973
23	.006	.027	100.000

Extraction Method: Principal Component Analysis.

Appendix 3.

Rated Component Matrix

Table

	Component
	1	2	3	4	5	6
I favour experimentation and original approaches to problem solving rather than using methods others generally use for solving their problems	.989	.043	.044	−.029	−.009	.034
I prefer to “step-up” and get things going on projects rather than sit and wait for someone else to do it	.989	.026	.056	−.016	−.007	.029
I tend to plan ahead on projects	.989	.033	.052	−.046	.003	.016
I usually act in anticipation of future problems, needs or changes	.986	.043	.054	−.005	−.001	.038
I often like to try new and unusual activities that are not typical but not necessarily risky	.068	.941	.094	.136	.104	.136
I prefer to try my own unique way when learning new things rather than doing it like everyone else does	.060	.939	.077	.108	.095	.084
In general, I prefer a strong emphasis in projects on unique, one-of-a-kind approaches rather than revisiting tried and true approaches used before	.000	.932	.131	.099	.062	.114
I am willing to invest a lot of time and/or money on something that might yield a high return	.053	.112	.962	.073	.073	.087
I like to take bold action by venturing into the unknown	.070	.105	.948	.075	.075	.079
I tend to act “boldly” in situations where risk is involved	.068	.092	.941	.108	.091	.098
I have very seriously thought of starting a firm	−.087	.233	.053	.814	.121	−.072
I will make every effort to start and run my own firm	−.055	.096	.018	.652	.430	.243
Being an entrepreneur would entail great satisfactions for me	−.028	.334	.073	.572	.033	.272
I have a strong intention to start a firm some day	−.104	−.028	.140	.550	.333	.062
I am ready to do anything to be an entrepreneur	.242	−.114	.099	.496	−.055	.324
A career as entrepreneur is attractive for me	.120	.076	.163	.159	.719	−.010
I would like to work for myself	−.003	.379	.113	−.275	.587	.011
My professional goal is to become an entrepreneur	−.135	−.030	−.050	.195	.508	.309
I am determined to create a firm in the future	−.170	−.065	.009	.265	.487	.173
I would like to start my own venture	.165	.231	.058	.251	.390	−.074
Being an entrepreneur implies more advantages than disadvantages to me	.017	.121	.164	.124	−.075	.731
If I had the opportunity and resources, I’d like to start a firm	.062	.130	−.037	.035	.405	.605
Among various options, I would rather be an entrepreneur	.065	.170	.162	.212	.268	.452
Mean	3.94	4.28	3.65	4.21	4.17	4.08
Cronbach’s Alpha	.992	.979	.973	.710	.497	.350

Appendix 4.

Convergent Validity Results

Table

	Entrepreneurial Intention	Innovativeness	Proactiveness	Risk-Taking
INT06	0.808
INT10	0.715
INT12	0.736
INT13	0.464
INV01		0.989
INV02		0.976
INV03		0.973
PRO01			0.996
PRO02			0.984
PRO03			0.997
PRO04			0.993
RSK01				0.973
RSK02				0.979
RSK03				0.971