Determinant Factors Affecting the Technical Efficiency of Apricot Farms in Türkiye Using a Two-Stage Double-Bootstrap Data Envelopment Analysis Approach - Donmez, Rifki; Kulekci, Murat (Springer, 2025)
This study aims to reveal the efficiency of apricot-growing farms in Malatya province, T & uuml;rkiye, and the determining factors affecting the efficiency. The data were obtained from 124 surveys conducted with apricot growers in Malatya province. A two-stage double-bootstrap data envelopment analysis (DEA) was used to determine technical efficiencies and factors affecting technical efficiencies. Hypothesis testing confirmed that constant returns to scale (CRS) efficiencies would reflect the state of farms. The adjusted input oriented CRS efficiency was determined as 0.587. According to the analysis of the factors affecting the efficiencies, productivity increase, less nitrogen, potassium and diesel use, as well as a decrease in irrigation costs increase efficiency. Farms in layer I are more efficient than those in layer IV and layer V. Those with very rough lands are more efficient than those with flat lands. Those that do not receive support are more efficient than those that do. Those that do not receive credit are more efficient than those that do. Farmers who graduated from high school are more efficient than those who graduated from primary school. In addition, it was determined that the efficiencies increased as the amount of support received increased. It has been determined that apricot-growing farms can produce the same production amount by saving 32.22% in area, 33.43% in nitrogen, 30.28% in phosphorus, 36.38% in potassium, 31.59% in pesticides, 31.15% in fungicide, 31.83% in labor use, 30.93% in fuel costs, and 33.10% in irrigation cost if they use their resources effectively.
Keywords: Truncated regression; Stratified sampling method; CRS efficiency; Input oriented; Non-parametric