Identifying determinants using qualitative ethnographic analysis

Kodithuwakku and Rosa (2002) document a research study, which is particularly pertinent to the present study, in that there are parallels in the nature of a ‘naturally occurring’ quasi-experimental environment. In 1984, ten years prior to the timing of the field research, the flood plain of the lower Mahaweli River in Sri Lanka had been cleared of bush, and dams and irrigation systems built. Landless families were each allocated two and a half acres (one hectare) of land, and therefore families started with the same level of economic resources in commencing their agricultural enterprises.

The basic question addressed by the researchers was why was it that some rural entrepreneurs in Sri Lanka were much more successful than others albeit within the same community, and with access to the same resources. The researchers during the course of the field research discovered that ten years after the commencement of land settlement programme a minority of rural entrepreneurs, (both male and female) had become relatively prosperous, in contrast to the majority who were still impoverished, and this minority group had an elevated social as well as economic status within the community.

The ‘opportunistic research design’ of the settlement scheme created a number of control factors detailed in Table 7.

Roy H Thompson PhD Thesis Page 52

Table 7 : Factors Controlled in the Sri Lanka Research Study Kodithuwakku et al. (2002)

Control factor Basis of equality Equal

opportunities

Entrepreneurs received the same land and resources allocated by government. All started as equally poor with few prospects

Rainfall Irrigation provided equal access to water

Social status Most were brought together as impoverished strangers Soil The village was predominantly homogeneous in soil quality Education Entrepreneurs had mostly a similar low level of education Extension Extensions services were made available equally to all

Locality Remote from any major trading or population centre but all entrepreneurs had equal access to good roads.

While there were many factors that the research design was able to control for, the researchers acknowledge that there remained what they termed ‘residual antecedent factors’. Individuals and households brought with them the ‘baggage’ of somewhat different levels of education; different family sizes; and different family networks. While few had received little formal education, some had more education than others. Family sizes would potentially allow more individuals to provide work assistance on the farm, while at the same time adding the burden of higher levels of consumption.

The study began initially with a ‘positivist’ methodological approach, whereby the researcher drew up a range of possible determinants, and constructed a semi-structured questionnaire. The researcher envisaged that a statistical analysis of carefully defined and validated dependent and independent variables would dominate the research, supported by limited qualitative data from open-ended questions. The plan was for the compilation of a sample of successful and non-successful farmers based on a pre- defined number of performance measures such as, number of employees, sales turnover, assets owned, and social standing. The researcher would then randomly select individuals within a selected rural geographical area, which contained marked differences in wealth between farmers. The pilot activity revealed problems in the original design, not the least of which was the availability of reliable data for the pre- defined performance measures.

As a result of the pilot the study moved from a positivist to a more interpretivist and phenomenological approach, which involved an extended period of time interacting with

Content removed for copyright reasons The table uses data which can be accessed at

Kodithuwakku, S. and Rosa, P. (2002) The Entrepreneurial Process and Economic Success

Roy H Thompson PhD Thesis Page 53 the study group, and consisting of a mixture of repeated interviews, direct participant observation and collection of secondary data. With the aid of key informants, the researcher was able to differentiate individuals within the study village into three groups. The first comprised those who were considered to be economically successful and increasing their asset base during the period of investigation (n=37). The second were those who were also considered successful but with a declining asset base (n=12). The latter and by far the larger group were those who were rated as economically unsuccessful non-commercial farmers whose current income derived predominantly from selling their own labour (n=268). This means that of the study participants only 12% were deemed successful and growing, 4% successful but not growing and 85% unsuccessful in that they were not operating viable enterprises, which could sustain them without recourse to selling their labour elsewhere.

The prognosis of what differentiated and polarised the relatively small number of successful entrepreneurs from the large number of unsuccessful ones, was somewhat complex. Successful entrepreneurs were able to draw upon their social networks to create opportunities both in farm and non-farm economic activities. They had typically diversified into other business ventures with an average number of 3.7 enterprises relative to a more limited (albeit unspecified) number of enterprises operated by those who were rated as being unsuccessful entrepreneurs.

Successful entrepreneurs were seen to have “creatively mobilised the resources under their control” as well as discovering opportunities for new enterprises. They operated strict control over their home consumption, and exhibited ‘delayed gratification’ in favour of re-investing in their enterprises and accumulating capital. There was another group of entrepreneurs discovered who had enjoyed initial success and had diversified their range of enterprises, but then owing to managerial inadequacies had failed to manage this expanded number of enterprises and had become unsuccessful.

Those who managed to accumulate resources first and sustain them tended to be the winners who were able to gain control of the larger land units. They acquired surpluses and translated these into a wider range of enterprises, which generated further surpluses by selling to the less successful within the community. The least successful were forced to lease their land to the more successful, and to sell their labour to them.

Roy H Thompson PhD Thesis Page 54 2.7. Educational Attainment and Performance

Peters and Brijlal (2011) in their study of South African entrepreneurs, using employees and sales as their performance measures, found a positive relationship between educational level and entrepreneurial performance (EP). In their study of Kenyan women SMEs, Gathenya et al. (2011) found a relationship between education and EP, using both objective measures of performance and a self-assessment rating. Their recommendation for needed remedial action involved special courses and programs for those women entrepreneurs with primary education only, although there is no specificity regarding content and approach for such initiatives. They quote Sonfield et al. (2001) in stating that “education equips women with the knowledge and skills they need to more effectively manage, be more strategic and succeed in their businesses.” Nam et al. (2010) found in their study of Vietnamese exporters that the performance of an enterprise is also considerably influenced by the human capital of the entrepreneur, including formal education.

Calvo and Garcia (2010) in their study of Spanish entrepreneurs using venture growth as their measure of entrepreneurial performance found that while general level of education of the entrepreneur was a determining factor, the entrepreneur’s previous enterprise experience had the greatest impact. Okurut (2008) found that returns in microenterprises in Uganda were positively and significantly influenced by education level. Nevertheless, within the livestock sector, despite females having higher levels of education than males they still exhibited lower levels of performance.

The approach of Swinney et al. (2006) followed that of Fasci and Valdez (1998) and Okurut (2008) in investigating within industry types, to avoid any ‘industry effect’ (refer section 2.15 on page 92). Swinney et al. (2006) investigated the gender and education level of the entrepreneur as possible influences on small firm performance within the retail and services sectors in the U.S. They concluded that while education alone was not a significant factor in EP for males, for female entrepreneurs a higher level of education did translate into improved entrepreneurial performance. Since the performance measure used was an owner self-reported subjective assessment of the enterprise, this raises additional questions concerning the relationship between

Roy H Thompson PhD Thesis Page 55 educational level and self-assessment of entrepreneurial performance, which were not fully explored in the article.

Khanka (2009) along with Fasci and Valdez (1998) find no evidence in their studies that educational level had any effect upon entrepreneurial performance (EP). Khanka explains his finding by proposing that formal education is not necessary for starting and running an enterprise, or for high levels of entrepreneurial performance, as evidenced by the success of entrepreneurs with limited education, citing some notable examples to support this assertion. Otoo et al. (2011) support this finding in their study of female entrepreneurs in both Niger and Ghana, where females with no formal education actually outperformed those with secondary education. Cowling and Taylor (2001) considered that enterprise specific training was more important than academic skills alone in influencing EP. In the case of Fasci and Valdez (1998) all entrepreneurs had a base accounting vocational training which was directly related to their enterprise, and to some extent it could be argued that educational level was a controlling rather than a determining factor in their analysis.

Chirwa (2008) in his study of micro- and small enterprises in Malawi found that education is a critical factor for the success of female-owned enterprises. Dickson et al. (2008) found strong evidence to support the relationship between levels of general education and several entrepreneurial success measures within their literature review, and this was across a range of both developed and developing countries. Bhattacharjee et al. (2008), in their econometric analysis of newly created French firms found that a higher education level for the entrepreneur was a determining factor influencing the survival rate of their enterprise, and that the extent of this positive association depended on the previous experience of the entrepreneur in the labour market. Their findings suggested that the extent of the impact of education on survival was always strongest among the sub-group who had previous experience in the sector of the enterprise they were operating. This suggests, and this is borne out by their analysis, that the impact of previous experience in the sector of enterprise choice is equally significant as their educational level.

Hietalahtil and Linden (2006) in their study of the socio-economic impacts of microcredit on women’s welfare in north-eastern South Africa found that those who were more

Roy H Thompson PhD Thesis Page 56 educated tended to have a better ‘starting point’ and were more capable of protecting themselves against vulnerability. Van der Sluis et al. (2003) estimate from their meta- analysis of a large number of developing country case studies that one year of schooling raises enterprise income by an average of five percent. Their findings indicated that returns to education tend to be higher for females and in agricultural societies where literacy rates are typically lower.