Purpose: This study aims to identify agricultural development trajectories across 25 EU member states, determine clusters with homogeneous development patterns, and analyse variations in technical efficiency levels and dynamics within these clusters. Furthermore, it evaluates the impact of Common Agricultural Policy (CAP) instruments and proposes a novel classification system to enhance the effectiveness of agricultural policy interventions. Design/methodology/approach: The analysis employs a comprehensive set of variables reflecting the agricultural production business model's characteristics. The study utilizes EUROSTAT data spanning 2007-2023. Through systematic data analysis, clusters exhibiting similar development trajectories were identified. Technical efficiency measurements within these clusters were conducted using Data Envelopment Analysis (DEA) methodology. Findings: The research reveals significant heterogeneity in European agricultural development trajectories, enabling the identification of distinct clusters with similar characteristics. These clusters demonstrate varying levels and evolutionary patterns of technical efficiency. Practical implications: The empirical findings facilitate the formulation of evidence-based recommendations aimed at enhancing and harmonizing efficiency levels across the European agricultural sector. Originality/value: This research contributes to the existing literature on EU agricultural efficiency by proposing a novel analytical clustering approach that transcends the traditional dichotomy between 'old' and 'new' EU member states. Additionally, it provides policy recommendations for future CAP developments.
Purpose: The aim of the study was to identify practical challenges, best practices, and solutions used during the deployment of agricultural machinery depending on the size of the farm Design/methodology/approach: The method of observation and risk analysis was utilized in the operation of agricultural machinery using the FMEA method to identify potential threats and develop strategies for their mitigation. Findings: Research conducted on farms has revealed significant issues such as improper maintenance, lack of safety guards, and outdated equipment. To enhance farm safety, it is recommended to adhere to maintenance schedules, replace old machinery with newer models, and use Failure Mode and Effects Analysis (FMEA) to identify and mitigate potential hazards. Research limitations/implications: Further large-scale research is needed to develop effective strategies for improving farm safety. Implementing structured safety management systems like FMEA is recommended to systematically assess and minimize risks in both individual and large-scale farms. Practical implications: Implementing recommended measures such as regular inspections and maintenance, replacing or modernizing outdated machinery, using appropriate safety guards, and participating in training sessions will help reduce the risk of machinery failures and the number of accidents. Originality/value: This article presents new research findings on agricultural machinery safety in individual and large-scale farms, identifying significant issues and proposing specific improvement measures for farmers and agricultural safety experts. These insights help farmers understand risks better and implement safety enhancements when operating machinery.
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