Methodological Evaluation of Manufacturing Plant Systems Efficiency in Kenyan Agriculture Using Bayesian Hierarchical Models

Manufacturing plants in Kenya's agriculture sector are crucial for productivity and efficiency gains. However, there is a need to evaluate their performance systematically. The methodology involves a comprehensive search and analysis of relevant studies, focusing on methodologies employed for measuring efficiency. A Bayesian hierarchical model is proposed as a robust framework for evaluating these systems. Findings indicate that the use of a Bayesian hierarchical model significantly improves the accuracy in estimating efficiency gains across different agricultural settings in Kenya. The review underscores the potential of Bayesian hierarchical models to enhance the understanding and management of manufacturing plant efficiencies within Kenyan agriculture. Recommendation is made for further empirical studies using this methodological approach to validate its effectiveness in diverse agricultural contexts. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.