Tomato cultivation holds significant importance in the Al Jabal Al Akhdar region, yet the varied input utilization among farmers has led to discrepancies in technical efficiency. This study addresses the need to assess the efficiency of tomato farming in the region, aiming to identify input limitations and facilitate improvement processes to minimize resource consumption. Utilizing primary data collected in 2023 via a closed questionnaire distributed among 100 randomly selected farmers, the study employs Data Envelopment Analysis (DEA) in its input-oriented form, utilizing win4DEAP software. The results reveal that while pure technical efficiency surpasses technical efficiency, there’s a notable discrepancy between the flexible frontier of the Variable Returns to Scale (VRS) model and the Constant Returns to Scale (CRS) model. Specifically, the VRS model indicates a slightly lower input reduction of 11.3%, emphasizing the importance of considering both models in decision-making processes. Farm-specific projections clarify that some are well-managed and serve as benchmarks, while others require improvement to achieve 100% efficiency scores. Key observations highlight the potential for cost reduction through input streamlining, with DEA proving to be an effective and user-friendly method for farm management enhancement. Its accessibility benefits both researchers and farmers, enabling informed decision-making to optimize profits while maintaining performance standards. The estimation results underscore the necessity for input reduction among tomato farms in Libya, particularly regarding variable capital costs, emphasizing the importance of tighter control over cultivation expenses.

Tomato cultivation holds significant importance in the Al Jabal Al Akhdar region, yet the varied input utilization among farmers has led to discrepancies in technical efficiency. This study addresses the need to assess the efficiency of tomato farming in the region, aiming to identify input limitations and facilitate improvement processes to minimize resource consumption. Utilizing primary data collected in 2023 via a closed questionnaire distributed among 100 randomly selected farmers, the study employs Data Envelopment Analysis (DEA) in its input-oriented form, utilizing win4DEAP software. The results reveal that while pure technical efficiency surpasses technical efficiency, there’s a notable discrepancy between the flexible frontier of the Variable Returns to Scale (VRS) model and the Constant Returns to Scale (CRS) model. Specifically, the VRS model indicates a slightly lower input reduction of 11.3%, emphasizing the importance of considering both models in decision-making processes. Farm-specific projections clarify that some are well-managed and serve as benchmarks, while others require improvement to achieve 100% efficiency scores. Key observations highlight the potential for cost reduction through input streamlining, with DEA proving to be an effective and user-friendly method for farm management enhancement. Its accessibility benefits both researchers and farmers, enabling informed decision-making to optimize profits while maintaining performance standards. The estimation results underscore the necessity for input reduction among tomato farms in Libya, particularly regarding variable capital costs, emphasizing the importance of tighter control over cultivation expenses.