CHARACTERISTICS OF THE SAMPLE

This section provides an account of the general characteristics of the businesses that provided information for the study. The provision of this account is considered important because it provides a basic understanding of the respondents and businesses that were studied. Thus, the descriptive statistics provide an opportunity to understand the characteristics of the sample. This is because the businesses that were studied vary in different dimensions including size, legal status, location, sector of operation and age. Additionally, the analysis in this section shows that the entrepreneurs who responded to the survey questions vary in terms of age, education, gender and working experience. Importantly, the variables that are examined here are taken from the profile variables provided in Section 6.4.3.5 of Chapter 6.

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7.2.1 Descriptive Statistics of the Sample

The statistical techniques used in the current study involved exploratory and multiple regression techniques. The exploratory technique was used to present the survey data in the form of frequency distribution tables. This allowed the researcher to compute mean and standard deviation values of the sample. The rationale behind the use of the exploratory technique was to allow for inclusion of a large number of exploratory variables in the analysis (Roper, 1998). Table 7.1 provides descriptive characteristics of the 346 businesses studied.

Table 7. 1: Descriptive Statistics of the Sample

Variable N Minimum Maximum Mean Standard

Deviation

Size (in employees) 346 4 50 17.44 10.65

Total annual Sales (in 000s of US$) 346 10.46 68,000 978.32 389.71

Founder Age (in years) 346 25 70 49.36 11.62

Firm age (in years) 346 5 50 16.78 7.75

Sales Growth Rate (%) 346 0 100 13.06 9.46

Employee Growth Rate (%) 346 0 100 13.72 9.05

The average number of full-time employees was 17 and annual turnover was UD$978,320. The businesses were growth oriented as indicated by their high average percentage growth rates (i.e. annual sale growth rate of 13.06%; annual employee growth rate of 13.72%). The Table 7.1 also showed a mean age of business was 17 years. The mean age of the entrepreneurs who responded to the survey was 49.3 years. Following Baum and Locke (2004), this study calculated prior growth rate. Prior growth rate (the percentage change in sales and employment between 2011 and 2012 = [(2011/2012)-1] was 5.11%. As has been highlighted in prior scholarly studies, the impact of size, sales, founder age, employee growth rate and prior growth influence business growth (e.g., Baum and Locke, 2004; Robson and Obeng, 2008). Indeed, most of these variables were used to account for exigencies that may influence the research model.

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7.2.2 Distribution of the Characteristics 7.2.2.1 Gender

The impact of gender on growth of small businesses has been investigated by several studies. In most studies, male owned businesses have been found to make up a greater proportion of self-employment (e.g., Sowa et al., 1992). This study’s sample seems to challenge this view in that male to female ratio in terms of self-employment is comparable in the sample. The reason may be that as result of the ‘glass ceiling’ phenomenon in formal employment sector, females tend set-up their own businesses in Ghana. Table 7.2 shows that a total of 53.5% of the entrepreneurs were males and 46.5% were females in the survey. This suggests that the male to female ratio of 185:161 could enhance comparability (See section 7.6.55 for a discussion on role of gender).

Table 7. 2: Gender of Respondents

Frequency Percent Valid Percent Cumulative Percent

Female 161 46.5 46.5 46.5

Male 185 53.5 53.5 100

Total 346 100 100

7.2.2.2Education of Entrepreneurs

A review of the literature on the relationship between educational attainment and business growth suggests a positive relationship between educational background and/ or training qualifications and business growth (e.g., Storey, 1994; Mead and Liedholm, 1998; Barringer et al., 2005; Kozan, Oksoy and Ozsoy, 2006; Robson and Obeng, 2008). Table 7.3 shows the educational qualification of the entrepreneurs.

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Table 7. 3: Education of Entrepreneurs

Level of education Frequency Percent Cumulative Percent

High school 123 35.5 35.5

HND 75 21.7 57.2

Bachelors 83 24.0 81.2

Postgraduate 65 18.8 100.0

Total 346 100.0

The education of the owner-managers was examined according to their highest qualifications. Thus, the educational qualification of the entrepreneurs was grouped into the following: (i) High school; (ii) higher national diploma; (iii) bachelor’s and (iv) postgraduate. Table 7.3 indicates that a total of 35.5% were high school graduates; 21.7% were higher national diploma graduates; 25.0% hold bachelor’s degrees and 18.8% hold postgraduate degrees.

7.2.2.3Formality/Informality

In both developed and developing economies, it is widely accepted that a large number of entrepreneurs operate wholly or partially off-the-books (ILO, 2002a; Williams, 2006b; Evans et al., 2006). To assess formability/informality of the sample, the current study used legal status of the sampled businesses. Table 7.4 below shows that legal status of the sampled businesses.

Table 7. 4: Legal Status of the Businesses

Legal Status Frequency Percent Cumulative percent

Unregistered Sole Proprietor 60 17.3 17.3

Registered Sole Proprietor 127 36.7 54.0

Limited Liability 114 32.9 87.0

Partnership 45 13.0 100.0

Total 346 100

Table 7.4 above indicates that majority of the businesses (82.7%) were formal businesses whilst only 17.3% were informal businesses. That is, 17.3% of the sample businesses were unregistered sole proprietor, 36.7% were registered sole proprietor, 32.9% were limited liability businesses and 13% were partnerships. This is in contrast with previous scholarly studies (e.g. ILO, 2002a; Williams, 2006b; Evans et al., 2006).

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7.2.2.4Sector of Operation

The current study received responses from small manufacturing businesses from eight regions in Ghana. Table 7.5 shows that in terms of the composition of the sectors in the manufacturing industry, 20.8% of the businesses were manufacturers of textiles/garment and footwear; 17.9% were manufacturers of food and beverage; 15.6% were in the wood and furniture sector; 14.5% were producers of stationery whilst 11% were soap/toiletries manufacturers. Table 7.5 depicts sector of operation of the surveyed businesses.

Table 7. 5: Sector of Operation

Sector Frequency Percent Cumulative Percent

Food/beverage 62 17.9 17.9 Textiles/garment/footwear 72 20.8 38.7 Wood/furniture 54 15.6 54.3 Paper Production 50 14.5 68.8 Soap making/toiletries 38 11.0 79.8 Technology/Electronic 36 10.4 90.2

Plastics and pipes 34 9.8 100

Total 346 100

The rest of the manufacturing businesses sampled for the current study include manufacturers of electronic gadgets (10.4%) and plastics and pipes (9.8%).

7.2.2.5Entrepreneurs’ Working Experience

Prior entrepreneurs’ working experience denotes any work related experience acquired before the respondents started their businesses (Locke, 2004). Whiles various studies showed a positive relationship between past working experience and business growth (Storey, 1994; Locke, 2004), other studies have shown no association between past working experience and business growth (Birley and Westhead, 1990). The inconsistencies research evidence on the relationship between past working experience and business growth suggest that past experience does not always lead to business growth. In the present study, past working experience was used as a control variable.

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Table 7. 6: Entrepreneurs' Past Working Experience

Response Frequency Percent Cumulative percent

Yes 188 54.3 54.3

No 158 45.7 100.0

Total 346 100.0

As can be observed from Table 7.6, 188 of the respondents representing 54.3% have gained working experience whilst 158 representing 45.7% had no working experience.