Effects of Smart Farming on the Productivity of Korean Dairy Farms: A Case Study of Robotic Milking Systems

Yong-Geon Lee, Kwideok Han, Chanjin Chung and Inbae Ji ()
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Yong-Geon Lee: Department of Food and Agriculture Economics Research, Korea Rural Economic Institute, 601 Bitgaram-ro, Naju-si 58217, Jeollanam-do, Republic of Korea
Kwideok Han: Department of Institutional Research and Analytics, Oklahoma State University, 203 PIO Building, Stillwater, OK 74078, USA
Chanjin Chung: Department of Agricultural Economics, Oklahoma State University, 307 Agricultural Hall, Stillwater, OK 74078, USA
Inbae Ji: Department of Food Institutional Management, Dongguk University, 30 Pildong-ro 1-gil, Jung-gu, Seoul 04620, Republic of Korea

Sustainability, 2024, vol. 16, issue 22, 1-18

Abstract: The Korean agricultural sector faces increasing challenges such as an aging population, labor shortages, and the liberalization of agricultural markets. To overcome these challenges, the Korean government has striven to enhance the competitiveness of agriculture by introducing AI-based technologies to the agricultural sector, labeling this as smart farming. This study estimates farm-level benefits of adopting smart farming technologies, robotic milking systems, in Korean dairy farms. The benefits are estimated by comparing the productivity (i.e., the savings of labor input, increased calf production, and increased milk production) of adopting and non-adopting farms. Our study uses the propensity score matching method to address potential problems from confounding factors, sample selection bias, and the small number of adopters. Our results show that farms that adopted robotic milking systems produced 0.10 to 0.11 more calves per year than farms that did not adopt the system. The adopters also increased milk production by 2.44 kg to 2.88 kg per head/day, while reducing labor input by 0.15 to 0.30 per head/week. However, the reduced labor input was not statistically significant. When the analysis was extended to regard the farm characteristics, the labor input became significant from small and family-run farms. We also found that the increase in the number of calves produced per head was statically significant from small farms, family-run farms, and farms with successors. The increased milk production per head was statistically significant from large farms, farms employing hired workers, and farms with successors. Our findings suggest that the Korean government continue promoting smart farming technologies such as the robotic milking system to increase the adoption rate. The findings can also provide useful information about target markets of this technology, which can be used to increase the adoption rate and ultimately enhance the sustainability and competitiveness of the Korean dairy industry.

Keywords: dairy farm; smart farming; robotic milking system; productivity; propensity score matching; endogeneity (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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