The purpose of this study is to provide comparative information that can help to measure efficiency and select appropriate benchmarking targets of inefficient farms by securing homogeneity with the characteristics of farms in efficiency analysis. The farm income data of apple and pear farms obtained...
The purpose of this study is to provide comparative information that can help to measure efficiency and select appropriate benchmarking targets of inefficient farms by securing homogeneity with the characteristics of farms in efficiency analysis. The farm income data of apple and pear farms obtained from Rural Development Administration(RDA) were analyzed using Stochastic Frontier Analysis (SFA) model and Data Envelopment Analysis (DEA) model, which are representative methods of efficiency analysis. For the analysis, fertilizer, pesticide, material, labor and fixed costs were selected as input factors. and total income was selected as the output factor. In addition, we divided the farms into several groups with different practice types to secure homogeneity in each crop. First, the result of the SFA estimation showed that both pear farms and apple farms had technical inefficiency. As for the pear farms, the material cost and labor cost were statistically significant in all groups. Pesticide costs were also found to be significant in some groups with their own practice types. Apple farms had statistically significant material and labor costs. As a result of farmhouse analysis by cultivation type, fixed costs were also significant. There are differences in efficiency values due to methodological differences between SFA efficiency and DEA efficiency. In both methods, the more efficient the farms were, the more they were classified into varieties and cultivation types. Although there were differences among the analysis groups, pear and apple farms were caused by Pure Technical Efficiency (PTE) because of the inefficiency of most farms. Result of over-investment and benchmarking of inefficient farms according to DEA analysis results, According to the characteristics of the farmhouse, the more the group analysis, It was clear that over-injection factors that required savings by farms. It can also be seen that the benchmark target reference set and reference rank are different. Finally, as a result of efficiency analysis by group, a comparison of farm efficiency and ranking showed, how farm efficiency varied. Both pear farms and apple farms showed differences in efficiency as they were segmented based on the homogeneity of analysis group. The more the farm characteristics are segmented, the higher the farm efficiency. This suggests that farming techniques among homogeneous farms are leveled.
The purpose of this study is to provide comparative information that can help to measure efficiency and select appropriate benchmarking targets of inefficient farms by securing homogeneity with the characteristics of farms in efficiency analysis. The farm income data of apple and pear farms obtained from Rural Development Administration(RDA) were analyzed using Stochastic Frontier Analysis (SFA) model and Data Envelopment Analysis (DEA) model, which are representative methods of efficiency analysis. For the analysis, fertilizer, pesticide, material, labor and fixed costs were selected as input factors. and total income was selected as the output factor. In addition, we divided the farms into several groups with different practice types to secure homogeneity in each crop. First, the result of the SFA estimation showed that both pear farms and apple farms had technical inefficiency. As for the pear farms, the material cost and labor cost were statistically significant in all groups. Pesticide costs were also found to be significant in some groups with their own practice types. Apple farms had statistically significant material and labor costs. As a result of farmhouse analysis by cultivation type, fixed costs were also significant. There are differences in efficiency values due to methodological differences between SFA efficiency and DEA efficiency. In both methods, the more efficient the farms were, the more they were classified into varieties and cultivation types. Although there were differences among the analysis groups, pear and apple farms were caused by Pure Technical Efficiency (PTE) because of the inefficiency of most farms. Result of over-investment and benchmarking of inefficient farms according to DEA analysis results, According to the characteristics of the farmhouse, the more the group analysis, It was clear that over-injection factors that required savings by farms. It can also be seen that the benchmark target reference set and reference rank are different. Finally, as a result of efficiency analysis by group, a comparison of farm efficiency and ranking showed, how farm efficiency varied. Both pear farms and apple farms showed differences in efficiency as they were segmented based on the homogeneity of analysis group. The more the farm characteristics are segmented, the higher the farm efficiency. This suggests that farming techniques among homogeneous farms are leveled.
주제어
#Stochastic Frontier Analysis (SFA) Data Envelopment Analysis (DEA) Homogeneity Efficiency
학위논문 정보
저자
정선화
학위수여기관
충북대학교
학위구분
국내석사
학과
농업경제학과 농업경영전공
지도교수
서상택
발행연도
2020
총페이지
viii,97 p.
키워드
Stochastic Frontier Analysis (SFA) Data Envelopment Analysis (DEA) Homogeneity Efficiency
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