Keywords: Gender; obstacles to entrepreneurship; financial difficulty; bureaucracy
Jel Classification: L26
Introduction
Entrepreneurs in developed and developing economies face a range of barriers when starting their business and growing it (OECD, 2011).
This has attracted a lot of attention from business people, economists, researchers and policy makers. In order to provide appropriate support in the face of these barriers it is appropriate to understand the demographic differences in the perception of barriers through empirical research (OECD, 2011). These barriers have been the major obstacles to entrepreneurship intention in all economies.
The paper is based on the theory of environmental component of perceived behavioral control developed by Ajzen (1991) Theory of Planned Behavior. The theory explains the relationship between behavioral intentions and actual behavior of an individual. According to researchers (Ahmad & Xavier, 2012; Sandhu et al., 2011; Taormina & Lao, 2007; Chowdhury, 2007; Aldrich, 2000) entrepreneurship is a function of internal psychological factors and external factors.
The psychological factors and external factors reported by the researchers are aversion to risk, fear of failure, aversion to stress and hard work, lack of social networking, lack of resources, inadequate financial support, bureaucracy, inconsistency of government policies, lack of entrepreneurial education at tertiary level, inadequacy of entrepreneurial training, political instability, corruption, inadequate infrastructural facilities, lack of education and training and inadequate financial help.
The theory by Ajzen (1991) have been used to examine empirically people’s perception of obstacles to entrepreneurship intention in relation to demographic variables such as gender, age, educational level, culture, income, employment type of parents and personality type.
The findings of the studies on demographic differences and perception of obstacles to entrepreneurship are found in the works of various researchers (Shinnar et al., 2012; World Bank, 2008; Koellinger et al., 2007; Cressy, 2006; Arenius & Minniti, 2005; Markman et al., 2005; Verheul et al., 2005; Wennekers et al., 2005; Carter, 2000; Berger & Udell, 1998; Beyer, 1998; OECD, 1998; Beyer & Bowden, 1997; Chittenden et al., 1996; Bates, 1995; Fabowale et al., 1995; Lindeman et al., 1995; Fischer et al., 1993; Brush, 1992; Scherer et al., 1990; Riding & Swift, 1990; Kalleberg & Leicht, 1991; Fagenson & Marcus, 1991; Buttner & Rosen, 1989; Evans & Jovanovic, 1989; Powell & Butterfield, 1989; Wohlers & London, 1989).
The findings in the literature have been mixed. Some studies report of significant differences (Verheul et al., 2005; Scherer et al., 1990) whereas some other researchers report of no significant differences. This calls for further studies to contribute to the debate. For example Arenius and Minniti (2005) reported of no significant gender difference between perceptual variables and entrepreneurship. Brush (1992) and Carter (2000) report that more women than men face more difficulty in getting funds for business. Other researchers (Fabowale et al., 1995; Riding & Swift, 1990; Buttner & Rosen, 1989) have reported insignificant gender differences in accessing funds for business.
Statement of problem/Justification/Significance
Researchers (Thurik, 2009; Van Praag & Versloot, 2007; Carree & Thurik (2003) have established the link both empirically and theoretically between entrepreneurship and economic growth in literature. Entrepreneurship is known to reduce employment rate and improves the welfare of people through the creation of wealth in an economy. Yet due to many obstacles, many graduates after receiving education on entrepreneurship do not start their own business or are not willing to become entrepreneurs. Researchers have reported of the moderating effect of demographic variables on the perception of obstacles to entrepreneurship effect.
The current paper examines demographic differences and the perception of barriers to entrepreneurship. According to researchers (Koellinger et al., 2007; Arenius & Minniti, 2005) individual subjective perceptions of obstacles might have more effect on intentions than the objective state of the obstacles. This call for more research on people perceived obstacles. There are scanty empirical researches on entrepreneurship in developing economies (Ahmad and Xavier, 2012; Sandhu et al., 2011; Nabi & Linan, 2011; Al-Ariss, 2010; Lan & Wu, 2010; Jamali, 2009; Kwong et al., 2009; Taormina & Lao, 2007) in the literature.
In the very knowledge of the researchers few empirical works exist in the study area and as such the current paper fills in the literature gap. The findings provide further understandings of the theory underlying the research. Policy makers are also provided with more information on how to design support policies for entrepreneurs. Future researchers will also find the findings useful as reference material since few works exist in the literature on the study area.
General Objective/Specific Objective
The paper contributes to the body of knowledge in the area of entrepreneurship by assessing demographic effects on perceived barriers to entrepreneurship intention among students. The paper among other things specifically;
Examine the link between demographics and perception of barriers to starting owns business.
Research Questions/Hypotheses
The research question for the paper is
how does demographic variables influence the perception of barriers to entrepreneurship
Hypotheses
The assumption underlying the paper is that demographic variables influence perception of barriers to entrepreneurship.
Limitations/Scope
The sample was based on convenient sampling method. Hence, the finding might not be able to generalise to the larger population. The findings are based on self-reported responses of the respondent. Hence, there may be respondent’s bias which might affect the reliability of the results. The paper is cross-sectional study and hence causality analyses are not discussed. The focus of the research is not on the reasons why individuals become entrepreneurs. Data are not collected from all the departments of the school but from the marketing department alone. Only students who have had entrepreneurship studies were part of the sample.
Methodology
The research is based on cross-sectional, descriptive, quantitative design and a survey research strategy using sample of 136 students of the marketing department selected through convenient sampling and purposive sampling methods. Self-designed questionnaire was used to collect primary data from the respondents during lecture hours. Primary data was analysed using frequencies, percentages, crosstabulations and chi-square.
Results and Discussions
The demographic profiles of the respondents are presented first. This is followed by the results on the link between the demographic variables and entrepreneurship intention.
Sample Characteristics
Majorities of the respondents in the survey are males 94(69.1%) and the age distribution indicates that majority 112(82.4%) respondent’s falls in the age group of 18-25. Most 39(28.7%) of the respondents are from Ashanti region. The results are shown in Table 1.
Table 1: Demographic features of respondentsDemographics differences in obstacles to entrepreneurial intention
The link between demographics and barriers to entrepreneurial intention was examined using cross-tabulations and chi-square test. The significant levels used for the discussions are: 10%; 5% and 1%. The variables used in the study are gender, age, region, religion, employment status, and father’s sector of employment, mother’s sector of employment and preferred sector of employment of respondents.
Gender
The relationship between demographics and obstacles to entrepreneurship intention was assessed in the study. There is statistical significant link between gender and obstacles to intention to start business. The obstacles are; ‘difficulty in obtaining bank loan’ (chisquare= 8.580; p=0.072); ‘lack of business skills’ (chi-square=8.984; p=0.061); ‘lack of information about any government agency that can help with funding’ (chi-square=9.482; p=0.050); ‘inability to write a business plan” (chi-square=7.941; p=0.094).
More females (76.2%) than males (71.3%) consider difficulty in obtaining bank finance as an obstacle to intention. More males (50%) than females (38.1%) consider lack of business skills as an obstacle to intention. More males (59.5%) than female (40.5%) see lack of information about any government agency that can help with funding as obstacle to intention. More males (50.6%) than females (40.5%) do not know how to write a business plan.
Age
There is statistical significant association between age and obstacles to intention to start business. The obstacles are; ‘lack of information about how to start a business’ (chisquare= 20.988; p=0.051); ‘lack of information about any government agency that can help with funding’ (chi-square=28.352; p=0.005);
‘inadequate knowledge in business management programme or entrepreneurial course’ (chisquare= 20.310; p=0.061); ‘nobody in my family has ever gone into business (chi-square=20.077; p=0.066). Very significant majority of respondents (100%) in the age group 31-35years consider lack of information about how to start a business as obstacle to intention than the other age groups. Majority of respondents (75%) in the age group 26-30years consider lack of information about any government agency that can help with funding business as obstacle to intention than the other age groups.
Very significant majority of respondents (100%) in the age group 31-35years did not do any business management programme or entrepreneurial course and that is considered as obstacle to intention than the other age groups. Majority of respondents (78.7%) in the age group 18-25years have no family members in business and more consider that as an obstacle to starting business than the other age group.
Region
There is statistical significant association between region and obstacles to intention to start business. The obstacles are ‘lack of savings’ (chi-square=63.548; p=0.003); ‘need to pay school loans’ (chi-square=54.048; p=0.027); ‘future uncertainty’ (chisquare= 51.631; p=0.044); ‘weak economic environment’ (chi-square=37.172; p=0.092). Very significant majority of respondents (100%) from Greater Accra region and Upper East perceived lack of savings as obstacle to starting own business than respondents from other regions. Very significant majority of respondents (100%) from Greater Accra region than respondents from other regions perceived the need to pay school loans as obstacle. Very significant majority of respondents from Greater Accra region (100%) than respondents from other regions consider future uncertainty as obstacle.
Majority of respondents from Eastern region (76.9%) consider weak economic environment as obstacle to entrepreneurship intention.
Religion
There is statistical significant relation between religion and obstacles to intention to start business. The obstacles identified are: ‘lack of savings’ (chi-square=59.768; p=0.057); ‘fear of risk’ (chi-square; p=57.873; p=0.078). Very significant majority (100%) with no religion and those with other religious faith consider lack of savings as obstacle to setting up own business. More respondents with other faith consider risk in setting up business as obstacle to starting a business.
Employment status of respondents
There is statistical significant relationship between employment status of respondents and obstacles to intention to start business. The obstacles are ‘lack of business experience’ (chisquare= 12.666; p=0.013); ‘lack of information about any government agency that can help with funding’ (chi-square=12.599; p=0.013); ‘high cost of business registration’ (chisquare= 12.945; p=0.012); ‘difficulty to find right partners (chi-square=14.137; p=0.007). More respondents who are mainly students (55.9%) consider lack of business experience as obstacle to starting own business than respondents who are students and workers (53.3%). More respondents who are only students (53.5%) consider lack of information about any government agency that can help with funding as obstacle to starting own business than respondents who are students and workers (50%).
Majority of respondents who are only students (60.2%) consider high cost of business registration as obstacle to starting own business than respondents who are students and workers (16.7%).
Most respondents who are only students (67.9%) consider difficulty to find right business partners as obstacle to starting own business than respondents who are students and workers (53.3%).
Father and mother sector of employment
The sector of employment of respondents father has statistical significant link with obstacles to starting own business. The obstacles are: ‘lack of savings’ (chi-square=17.572; p=0.025); ‘high cost of business registration (chi-square=13.455; p=0.097); ‘fear of business failure’ (chisquare= 18.545; p=0.017); ‘weak economic environment’ (chi-square=10.940; p=0.090) and lack of support from family or friends’ (chisquare= 16.745; p=0.033). Majority of respondents whose fathers are self employed (76.3%) consider lack of savings as an obstacle to starting own business than respondents whose fathers work in the public (69.8%) and private sectors (61.6%). Most respondents whose fathers are self employed (70%) consider high cost of business registration as an obstacle to starting own business than respondents whose fathers work in the public (42.8%) and private sectors (53.9%).
More respondents whose fathers are self employed (55%) consider fear of business failure as an obstacle to starting own business than respondents whose fathers work in the public (32.6%) and private sectors (42.3%). Majority of respondents whose fathers are self employed (71.2%) consider weak economic environment as an obstacle to starting own business than respondents whose fathers work in the public (45.2%) and private sectors (52%). More respondents whose fathers are self employed (66.7%) consider lack of support from family or friends as an obstacle to starting own business than respondents whose fathers work in the public (34.9%) and private sectors (46.1%).
There is significant relation between mother sector of employment and obstacles to starting up own business. The obstacle is ‘lack of business experience’ (chi-square=14.289; p=0.075). Most respondents (56.3%) whose mothers are self employed consider lack of business experience as an obstacle to starting own business than respondents whose parents work in public (45.8%) and private sector (43.7%).
Discussions
The paper has provided information regarding the different types of obstacles involved in starting a business. The findings are consistent with the findings of previous researchers which reported gender differences in perception of barriers to entrepreneurship (Shinnar et al., 2012; Verheul et al., 2005; Carter, 2000; Brush, 1992; Scherer et al., 1990). Women views on obstacles are different from that of men. Shinnar et al. (2012) reported of significant gender differences in barrier perceptions and a moderating effect of gender on the relationship between barriers and entrepreneurial intentions and also indicated that the gap is not consistent across cultures. The gender effect may positively influence women’s self-employment preferences (Verheul et al., 2011). But the results are contrary to the findings of other researchers such as Arenius and Minniti (2005) who reported of no statistical significant difference.
Conclusions and Policy implications
Demographic and socio-economic variables significantly influence the perception of barriers to entrepreneurship intention among students. There are major statistical significant differences in the way men and women perceive obstacles to start-up a business. Other variables identified are age; region; religion; employment status, and father’s sector of employment, mother’s sector of employment and preferred sector of employment of respondents.
Policies aimed at encouraging students to become entrepreneurs should focus on removing barriers by incorporating these findings since demographic-based obstacles exist. Sample size should be increased in future studies to ensure external generalisation of findings. Longitudinal studies should be done in future studies for causal analyses to be made.
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