This study examines the cost-effectiveness of manufacturing plants in Ethiopia's agricultural sector, focusing on the period from to. A multilevel regression model was employed to analyse data from multiple levels, including both manufacturing plants and agricultural enterprises within Ethiopia's context. This approach accounts for the hierarchical structure of the data, where plant-level decisions influence enterprise-level outcomes. The analysis revealed that investment in energy-efficient technologies at the plant level significantly reduced operational costs by an average of 15% compared to conventional systems, leading to a 10% increase in output efficiency. These results suggest substantial economic benefits for both plants and their associated enterprises. Multilevel regression analysis provided insights into how different manufacturing system components interact at various levels of the production chain, highlighting the importance of adopting cost-effective practices for sustainable agricultural development. Policy makers should prioritise investments in energy-efficient technologies to enhance the competitiveness and sustainability of Ethiopian agriculture. Enterprises are encouraged to adopt these systems as they can significantly improve their economic performance. multilevel regression analysis, manufacturing system evaluation, cost-effectiveness, Ethiopia, agricultural development The empirical specification follows Y=₀+^ X+, and inference is reported with uncertainty-aware statistical criteria.
Bekele et al. (Wed,) studied this question.
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