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Barriers Towards the Development of Emerging Contractors in the Limpopo Province Lawrence Tshivhase ( DTech Student) Outline of oral presentation Introduction and background of study Objectives of study and research questions Literature review Construction Industry Development Board

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  1. Barriers Towards the Development of Emerging Contractors in the Limpopo Province Lawrence Tshivhase (DTech Student) Outline of oral presentation Introduction and background of study Objectives of study and research questions Literature review Construction Industry Development Board Study design, sample size and sampling techniques Results of data analysis Recommendations Business School

  2. Introduction and background of study A review of the literature shows that more than half of all new and emerging contractors in the construction industry in Limpopo Province fail and go out of business for various reasons (Tshivhase, 2007). Thus, they are not viable. The literature shows that over 75% of all emerging contractors in the construction industry in Limpopo Province are black, and that their market share is below 65% (Construction Industry Development Board, 2010). The study was conducted in 2010 in the 5 districts of Limpopo (Capricorn, Vhembe, Mopani, Waterberg and Sekhukhune). Objectives of study and research questions The key objective of study is to identify key barriers that adversely affect the viability and market share of emerging contractors in the construction industry in Limpopo Province. The study aims to propose feasible and suitable remedial actions that are helpful for supporting emerging contractors in the construction industry in Limpopo Province. Business School

  3. Research questions What factors affect viability in the construction business among emerging contractors? What factors affect market share in the construction business among emerging contractors? How effective is the Construction Industry Development Board (CIDB) grading system in terms of promoting emerging contractors in the Limpopo Province? Underlying theory of DTech study This research is designed to test whether or not the claim (null hypothesis) that only resources and technical skills that are relevant to construction works determine the successes of emerging contractors in the construction industry in Limpopo Province. The research will also find out how much entrepreneurial skills are important for viability and market share. Business School

  4. Dependent variables of study (Y1 and Y2) The 1st dependent (outcome) variable of study (Y1) is viability. Y1 is a dichotomous variable that has only 2 possible values (Yes, No). The financial track-records of each of the n=104 contractors were examined. The 2nd dependent (outcome) variable of study (Y2) is market share. Y2 has only 2 possible values (Moderate if market share is 0.25% or above, Low if market share is less than 0.25%). See Tshivhase (2007). Literature review Agumba (2006), Tshivhase (2007), Phaladi & Thwala (2007) and Limpopo Development Enterprises (LimDev, 2010) have reported that emerging contractors in Limpopo and in South Africa in general are not progressing well in their core business due to lack of skills and access to finance Construction Industry Development Board (Objectives) To promote strategic leadership to construction industry stakeholders, encourage sustainable growth, restructuring and development of the construction sector. Promote continue growth of the construction industry and the involvement of the emerging sector. Business School

  5. Table 1: Financial & Works Capability Requirements (Source: CIDB, 2010a) Source: CIDB (2010b) Business School

  6. Study design, sample size and sampling techniques The design of the study was cross-sectional and descriptive. A random sample of size n=104 emerging contractors was drawn from the 5 Districts of Limpopo Province based on stratification. Figure 1: Locality map of Limpopo Province Table 2: Number of participants per district Business School

  7. Results of data analysis (Cross-tab analysis, Quantitative) The Pearson chi-square test of association was used for identifying significant two-way associations among categorical variables. At the 5% level, significant associations have P-values that are smaller than 5%. Table 3: Pearson’s chi-square of associations (n=104) Business School

  8. Logistic regression analysis (Quantitative) Table 4: Odds ratios obtained from logistic regression analysis (Model 1) At the 5% level, significant odds ratios are characterized by odds ratios that are significantly different from 1, P-values that are smaller than 0.05, and 95% confidence intervals of odds ratios that do not contain 1 Business School

  9. Table 5: Odds ratios obtained from logistic regression analysis (Model 2) At the 5% level, significant odds ratios are characterized by odds ratios that are significantly different from 1, P-values that are smaller than 0.05, and 95% confidence intervals of odds ratios that do not contain 1. Business School

  10. Recommendations • There is a need to increase infrastructure investment to address the backlogs. • There is a need to review CIDB regulations requiring professionals when emerging contractors want to upgrade to grade 7. • Assess the level of entrepreneurship as a prerequisite for emerging contractors to participate in the Contractor Development Programmes. • There is a need to encourage construction entrepreneurs to invest into business operations. • It is recommended that more funds should be injected into provincial agencies that finances SMMEs • Introduce regulations that restrict unnecessary entry into the construction industry in the Limpopo Province. Business School

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