Strategic Competency and Growth of Aquaculture-Based Small Enterprises in Kenya

Purpose: This study evaluated the role of strategic competency on growth of aquaculture based small enterprises in Kenya. Methodology: The study adopted descriptive research design using mixed methods approach. The target population was 600 fish farmers in Nyeri County, Kenya. The study utilized purposive sampling to select fish farmers within Nyeri County, then cluster sampling to identify fish farmers in their various sub-counties. Simple random sampling was then utilized to select respondents for the study. A self-administered questionnaire was used to collect data from the respondents. A pilot study was conducted to test validity and reliability of the questionnaire. Data analysis was done using Statistical package for Social Scientists (SPSS). Regression analysis and chi-square were used to test for significant associations between the dependent and independent variables. The findings were presented in frequency tables, pie charts, bar graphs and scatter diagrams in the final report. Findings: The findings indicated a positive statistically significant relationship on strategic competency and its effect on growth. Further, regression analysis of the results established that strategic competency was found to account for 5.8% of the variation in the growth of aquaculture-based small enterprises in Kenya. 94.2% of variation in the growth of aquaculture based small enterprises in Kenya is explained by other factors outside the model. Unique Contribution to Theory, Practice and Policy: Based on the study findings, the sector should sustain government and NGO support by subsidizing input costs, promoting cottage industries, and employing trained extension officers. In addition, the management should facilitate knowledge sharing through farmer excursions and disseminate information on region-specific fish farming techniques. Lastly, it should develop public-private partnerships to coordinate markets and reduce post-harvest losses through a demand-driven approach.