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Current and future demographic, geopolitical and environmental challenges have led to research focused on analysing the cost of labour in agriculture in relation to farm size, motivation and employee profile. TwoStep Cluster analysis formed: Cluster 1 - average emotional motivation of 1.1 points and financial motivation of 3.6 points formed by employees with work experience between 0 – 20 years (frq. – frequency 69.8%), farms under 500,000 SO (frq. 72.3%). Cluster 2 (24.4%) average emotional motivation of 2.8 points and financial motivation of 2.1 points: employees with experience over 40 years (frq. 97.2%), women (frq. 44.2%) and SE Development Region (frq. 58.1%). Cluster 3 (33.9%) average emotional motivation of 3.6 points and financial motivation of 1.2 points: with experience between 3 – 40 years (frq. 63.2%), financial benefits 2 – 4 euro/hour (frq. 94.3%), farms over 750,000 SO (frq. 43.4%), male (frq. 51.1). The average level of net financial benefits is 4.8 euro/hour from 2.0 euro/hour for unqualified employees to 10.3 euro/hour for highly qualified employees; from 4.7euro/hour in farms of sizes between 100,000 SO – 250,000 SO to 6.5 euro/hour in farms under 100,000 SO. Gender shows a difference of 9.1%. The average level of emotional motivation is 1.9 points and increases from 1.5 points for 0 – 10 years of experience to 2.7 points for experience over 40 years; from 1.9 points in farms between 100,000 SO – 250,000 SO to 2.4 points in farms over 750,000 SO. Gender differentiates women from men by 7.0%. Pearson analysis of motivations – employee characteristics indicates a strong and significant inverse correlation between emotional motivations and financial benefits. The inflection point is at 28 years of experience and 4.9 euro/hour. The results suggest the need for managers to recognize employees emotional motivations and manage them dynamically and individually. [ABSTRACT FROM AUTHOR]

The purpose of the research presented in this paper is to develop a specific sample model for the analysis of costs in agriculture which was done by: 1. Scientific documentation to determine the main criteria to determine the relevance of including farm size ranges in the sampling structure; 2. sensitivity analysis in order to measure the impact of each criterion on farm-specific economic performance; 3. Interviews with farmers from a representative sample for the evaluation of farms by size categories; 4. restructuring the size ranges. The field researches were carried out in the second half of 2020, on two development regions of Romania: NE and SE. The average general score obtained by the entire sample is 4.7, which resulted in a structure of agricultural farms in economic size consisting of V intervals with the following limits: 100,000 SO, 250,000 SO, 500,000 SO, 750,000 SO, 1,000,000 SO. [ABSTRACT FROM AUTHOR]