Determinants of Local Content Participation among Domestic Firms in Uganda's Oil and Gas Sector
Abstract
This study examined the determinants of local content participation among domestic firms operating in Uganda's oil and gas sector. The study adopted a mixed-methods cross-sectional research design. Data were collected from 280 firms registered on the National Supplier Database of the Petroleum Authority of Uganda. Quantitative data were collected using structured questionnaires administered to Procurement Officers, Accountants, and National Content Officers, while qualitative data were obtained through interviews with Chief Executive Officers. Quantitative data were analyzed using descriptive statistics, Pearson correlation and hierarchical regression analysis using SPSS Version 26. Qualitative data were analyzed using thematic analysis. The findings revealed that capacity building has a positive and statistically significant relationship with local content participation (r = .501, p < .01), while firm capabilities also exhibited a positive and statistically significant relationship with local content participation (r = .417, p < .01). Hierarchical regression results further showed that capacity building significantly predicts local content participation (? = .444, p < .001), while firm capabilities also exert a positive and significant influence (? = .343, p < .001). The final regression model explained 36.1% of the variation in local content participation (Adjusted R² = .361). Qualitative findings revealed that training, knowledge transfer and access to finance enhance domestic firms' ability to participate in oil and gas activities, while production capacity, infrastructure, skilled human resources and financial resources improve firms’ competitiveness and readiness to exploit procurement opportunities in the sector. The qualitative findings corroborated the quantitative results by demonstrating that capacity building and firm capabilities are critical drivers of local content participation among domestic firms.
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