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The motor vehicle assembly industry is crucial for industrial development, job creation, and economic growth. However, Kenya’s motor vehicle sector has seen a decline in local market share, revenue, and competitiveness due to strategic stagnation, weak innovation, and operational inefficiencies. This study therefore examined the effect of competitor elimination strategy on the performance of motor vehicle assemblers in Kenya. The study was anchored on the Resource-Based View (RBV) theory. It adopted a descriptive and explanatory design. The target population comprised all 21 licensed and operational motor vehicle assembly firms in Kenya and the 202 employees directly involved in strategy and operations at three management levels across these firms. A census approach was used, and primary data were collected using a semi-structured questionnaire. Three firms were purposively used for the instrument pretest, after which the main study was conducted among the remaining 18 firms. Construct validity was assessed through factor analysis, and reliability was assessed using Cronbach’s Alpha (≥ 0.70). Descriptive statistics provided foundational insights, while inferential analysis included Pearson’s Product-Moment Correlation and simple linear regression; thematic analysis was used for the qualitative data. The study found that competitor elimination strategy had a positive and statistically significant effect on the organisational performance of motor vehicle assemblers in Kenya (R² = 0.340, β = 0.451, p = 0.000). Policymakers in Kenya should promote innovation, product differentiation, and strategic positioning through R&D incentives, first-mover support, and cross-industry collaboration to enable effective competitor elimination. Motor vehicle assemblers should implement product bundling, differentiated offerings, strategic alliances, and innovation initiatives to create unique market space, reduce direct competition, attract new customers, increase market share, and enhance overall performance and sustainability. This study provides insights to guide strategic innovation and competitiveness in Kenya’s motor vehicle assembly industry, contributing to the realisation of the Sustainable Development Goals, Africa’s Agenda 2063, and Kenya Vision 2030.

This study finds that green loans and green mortgages are positively and statistically significantly associated with CO₂ emissions in Nigeria, contrary to their intended role in climate mitigation. Using annual time-series data from 2012 to 2024 obtained from the Central Bank of Nigeria (CBN) Statistical Bulletin and the World Bank World Development Indicators (WDI), the study examines the effect of loan-based climate finance on carbon dioxide (CO₂) emissions, with gross domestic product per capita included as a control variable. The Autoregressive Distributed Lag (ARDL) framework is employed due to its suitability for small samples and mixed orders of integration. The Pesaran et al. (2001) bounds testing approach confirms the existence of a long-run relationship, and the model is re-specified as an error-correction model (ECM) to capture short-run dynamics and long-run adjustment. The results show that green loans and green mortgages increase emissions in the long run, while short-run effects are weak and largely insignificant. The error-correction term is negative and statistically significant, indicating adjustment toward the long-run equilibrium. These findings suggest that existing green credit instruments in Nigeria have not yet translated into measurable emissions reduction, reflecting weaknesses in credit targeting and monitoring. The study highlights the need for clearer classification standards, stronger regulatory oversight, and improved monitoring frameworks to ensure that climate finance effectively supports emissions reduction objectives.

The motor vehicle assembly industry is crucial for industrial development, job creation, and economic growth. However, Kenya’s motor vehicle sector has seen a decline in local market share, revenue, and competitiveness due to strategic stagnation, weak innovation, and operational inefficiencies. This study therefore examined the effect of competitor elimination strategy on the performance of motor vehicle assemblers in Kenya. The study was anchored on the Resource-Based View (RBV) theory. It adopted a descriptive and explanatory design. The target population comprised all 21 licensed and operational motor vehicle assembly firms in Kenya and the 202 employees directly involved in strategy and operations at three management levels across these firms. A census approach was used, and primary data were collected using a semi-structured questionnaire. Three firms were purposively used for the instrument pretest, after which the main study was conducted among the remaining 18 firms. Construct validity was assessed through factor analysis, and reliability was assessed using Cronbach’s Alpha (≥ 0.70). Descriptive statistics provided foundational insights, while inferential analysis included Pearson’s Product-Moment Correlation and simple linear regression; thematic analysis was used for the qualitative data. The study found that competitor elimination strategy had a positive and statistically significant effect on the organisational performance of motor vehicle assemblers in Kenya (R² = 0.340, β = 0.451, p = 0.000). Policymakers in Kenya should promote innovation, product differentiation, and strategic positioning through R&D incentives, first-mover support, and cross-industry collaboration to enable effective competitor elimination. Motor vehicle assemblers should implement product bundling, differentiated offerings, strategic alliances, and innovation initiatives to create unique market space, reduce direct competition, attract new customers, increase market share, and enhance overall performance and sustainability. This study provides insights to guide strategic innovation and competitiveness in Kenya’s motor vehicle assembly industry, contributing to the realisation of the Sustainable Development Goals, Africa’s Agenda 2063, and Kenya Vision 2030.

This study finds that green loans and green mortgages are positively and statistically significantly associated with CO₂ emissions in Nigeria, contrary to their intended role in climate mitigation. Using annual time-series data from 2012 to 2024 obtained from the Central Bank of Nigeria (CBN) Statistical Bulletin and the World Bank World Development Indicators (WDI), the study examines the effect of loan-based climate finance on carbon dioxide (CO₂) emissions, with gross domestic product per capita included as a control variable. The Autoregressive Distributed Lag (ARDL) framework is employed due to its suitability for small samples and mixed orders of integration. The Pesaran et al. (2001) bounds testing approach confirms the existence of a long-run relationship, and the model is re-specified as an error-correction model (ECM) to capture short-run dynamics and long-run adjustment. The results show that green loans and green mortgages increase emissions in the long run, while short-run effects are weak and largely insignificant. The error-correction term is negative and statistically significant, indicating adjustment toward the long-run equilibrium. These findings suggest that existing green credit instruments in Nigeria have not yet translated into measurable emissions reduction, reflecting weaknesses in credit targeting and monitoring. The study highlights the need for clearer classification standards, stronger regulatory oversight, and improved monitoring frameworks to ensure that climate finance effectively supports emissions reduction objectives.