• Journal of Distribution Science
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• v.15 no.11
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• pp.21-29
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• 2017

Purpose - Relationship between farm and county losses determines whether the county program provides too little, too much, or similar amount of assistance relative to the loss on an individual farm. A review of the literature finds limited analysis of the determinants of this relationship. This paper conducts such an analysis using farm-level yield data. Research design, data, and methodology - Farm-level yield data from Illinois and Kansas farm business management associations are used for to calculate the correlation between farm and county loss and the share of farm loss systemic with county loss, and also for the regression analysis. Results - Average share of farm loss systemic with the county loss lies between 42% and 68%. The correlation between farm and county yield/revenue deviation from expected value is statistically significant in all four models. The coefficient is positive, implying the higher the correlation, the larger the share of farm loss that is systemic with the county loss. Conclusions - The findings of this study are consistent with the existing literature which argues that county variability may not be closely associated with farm variability. The findings of this study thus raise questions about the efficacy of area yield and revenue insurance products in helping farmers manage their risk.

• Journal of Agricultural Extension & Community Development
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• v.24 no.1
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• pp.63-81
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• 2017

The purpose of this study is to analyze the changes of time series, the use by farm type and the causes of farm household debt. First, the mid and long term changes in farm household debt over the past 50 years have increased. Since 2010, the share of non-agricultural debt has exceeded the share of agricultural debt. Second, as a result of the analysis of the farm household debt use by farm type - full time&part time, farming type, land size, age, family members - there was a difference between the agricultural and the non-agricultural debt according to the type of farm household in a significant level of 1%. Finally, as a result of the cause analysis of the farm household debt, the related non-agricultural expenditure variables and the dummy variable of the manager's age, family member and land size has a common influence on the farm household debt increase.

• Journal of Biosystems Engineering
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• v.15 no.1
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• pp.52-60
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• 1990

The main purpose of this report is to analyse the utilization results of farm machinery, farm mechanization rate and influences on the farm household economy. These results are summarized as follows : 1) The annual working days of major farm machinery are from 34.3 to 68.8 days for power tillers and tractors ; 7.9 to 8.5 days for rice transplanters ; 3.6 to 6.9 days for binders ; and, from 18.6 to 20.6 days for combines. Also income and expenditures of the farm management reveals al surplus in major farm machinery except for binders. 2) The popularization rate of major farm machinery is currently low, reaching the level of the early 1970's in Japan and the level of the early 1980's in Taiwan for rice transplanters and harvesters respectively. 3) The farm mechanization rate is 81.7% in plowing & levelling, 66.3% in rice transplanting, 87.5% in pest and disease control, 62.1% in harvesting and 12.5% in drying. However the farm mechanization rate of rice transplanting, harvesting and drying still remains at a low level. 4) The composition rates of farm machinery and implements are 10.2% in farm management expenditures (23.6% in Japan) and 13.2% in fixed capitals (29.4% in Japan) which still reflect a low level, and below that of the 1970's in Japan. From these analysis results, farm mechanization contributes to the improvement of farm management. Nevertheless, the popularization status and mechanization rate are still at a low level in korea. Therefore, it is deemed desirable to furthure promote effective utilization methods and guide farmers in higher safety utilization and management technology.

• Korean Journal of Organic Agriculture
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• v.24 no.3
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• pp.369-383
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• 2016

Crop yield insurance program in Korea has rapidly grown not only in quantity but in quality for 15 years since it was introduced in 2001. Despite growth of Crop insurance, performance evaluation for crop yield insurance has not fully been evaluated at the farm, consumer and national level. The purpose of this study is to conduct the performance evaluation for crop yield insurance through estimating the effects of farm revenue stabilization and social welfare increase with three popular insurance items: apple, pear and sweet persimmon. Based on the analysis of social welfare effect, cost-benefit analysis of operating crop yield insurance was conducted at the national level. We found that crop yield insurance stabilizes farm revenue based on the estimated four risk indicators: Coefficient of Variation, Value at Risk, Certainty Equivalence, and Risk Premium. The result of cost-benefit analysis shows that crop yield insurance increases social net benefit by 44.1 billion won for the three items. As a result, crop yield insurance program has contributed remarkably on social welfare as well as farm management and its role will be more important in the future.

• Korean Journal of Organic Agriculture
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• v.28 no.3
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• pp.315-334
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• 2020

This study was conducted to analyze factors affecting acceptance of smart farm technology. Smart farm technology is rapidly being introduced to agriculture in accordance with the progress of the 4th Industrial Revolution, but research on this is still little. Therefore, in this study, based on the unified theory of acceptance and use of technology (UTAUT), a research model reflecting the characteristics of smart farm technology was constructed. To test this, empirical analysis was performed. A survey was conducted for students in smart farm technology education and adult male and female farmers who are currently planning to operate smart farms. Valid 204 sample were used for analysis. The hypothesis test was based on multiple regression analysis using SPSS 24 statistical package. For the mediating effect and moderating effect, Process Macro 3.4 based on the regression equation was used. The results of testing the hypothesis are as follows. First, in the causal hypothesis test, it was shown that performance expectancy, social influence and price value have a significant positive effect on the intention to use smart farm technology. On the other hand, effort expectancy, facilitating conditions were not tested for a significant influence on the use of smart farm technology. As a result of analyzing the mediating effect of trust, it was found that trust plays a mediating role between performance expectancy, effort expectancy, social influence, facilitating conditions, price value and intention to use smart farm technology. In particular, the effort expectancy has not been tested for a direct significant effect on intention to use smart farm technology, but it has been shown to have an impact through trust. Trust was found to be a full mediating between the effort expectancy and the intention to use the smart farm technology. The current IT level of prospective users has been shown to play a moderating role between performance expectancy, facilitating conditions and intention to use smart farm technology. In particular, the IT level was found to strengthen the relationship between performance expectancy and intention to use smart farm technology. Based on the results of these studies, academic and practical implications were suggested.

• Journal of the Korean Home Economics Association
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• v.8 no.1
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• pp.181-197
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• 1970

Farm households consumption pattern from 1960 to 1968 was analized as follows. First, the influence of the price on the consumption pattern was observed by year for 9 years. Second, the influence of farm households and by size of the consmption pattern was analized by year for whole household and by size of the arable land. Third, the present status and problems of farm families consumption pattern was attempted to be found out compared with the pattern of all families of Seoul. Forth, the pattern of food expenditure which has the largest proportion in the living expenditure was analized. Following results and conclusions are obtained from the above analysis.1. The average nominal increase rate of all farm households has been increased gradually for 9 years, mostly due to the rise in household goods prices paid by farmers. 2. The living expenditure varies with the price and the disposal income, The influence of the latter is greater than that of the former. 3. The Engel's Coefficient of farmers. the average of which was 54.9%, recently tends to decrease gradually. The larger is the size of arable land, the lower is the Coefficient of farm households. But the Coefficient of farm households is higher than that of city families. 4. In general the proportion of food expenditure has a great influence on the consumption pattern, The average percentage of miscellaneous expenditure is 23.9% and it is next to food expenditure. The relationship between them is going reversely. Housing expenditure has usually the constant proportion. But the difference of the proportion between farm households (4.0%) and city families (17.1%) is considerable. Clothing expenditure and fuel and light expenditure have small variations. The former tends to increase with the income, and the latter tends to decrease with it or is constant. 5. Considering the food expenditure pattern, the average percentage (78.4%)of staple food of farm household is remarkably high compared with Seoul (48.3%) and other cities (54.0%). The decrease of the percentage of staple food expenditure in farm households is not so much as cities. 6. The propertion of the staple food expenditure of Farm families don't have so much differences by the size of arable land. But the rice proportion of staple foods has the tendency to increase with the income level. Subsidery food expenditure doesn't increase by year and by size of the land, while the consumption of meat and manufactured foods tends to increase with size of the land. But even big farm households don't reach to the level of cities in consumption of them. 7. Food consumption pattern may be influenced by the factors such as the knowledge of wife about nutrition, customs, consumption habits, and so on. The difference between farm households and city families in food consumption pattern is inferred from the above factors. Presently, the increasing income of the people promote the consumption of all items of living expenditure both in cities and farm households. But the Engel's Coeffcient and the proportion of the staple food expenditure is expected to decrease in farm households more than in cities.

• Journal of Agricultural Extension & Community Development
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• v.18 no.4
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• pp.983-1010
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• 2011

The purpose of this study was to examine the implication for the return farm and rural training program through the analyzed trainees' satisfaction and general characteristics. This study polled 89 trainees who presented the Return farm and rural training program by Jeju Agricultural Research and Extension Service. and the results of analysis are as follows. First, trainees' general characteristics appeared very various at an age structure, stage and type of return farm and rural. Second, the overall satisfaction level for the training program was normal but it was different according to the trainees' general characteristics, stage and type of Return farm and rural. This result was due to the unilateral training program. Consequently, it required a lot of efforts for the improvement of satisfaction through reflecting the trainees' properties in the training plan.

• Agribusiness and Information Management
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• v.1 no.2
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• pp.23-42
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• 2009

As technology develops, more advanced technologies involving GPS, GIS, RFID and sensor networks have been adopted in agriculture sector for u-Farm. However, technology adoptions have been evaluated as ineffective. Farmers and agri-business have low level of understanding on technology so it is not efficiently utilized. This study introduces a case of RFID/sensor networks of mushroom farm as a u-Farm case study, focusing on developing a framework for analysis of u-Farm investment returns. RFID and sensor networks improve real-time production control, processing management, and traceability. Integration of RFID and sensor networks leads to innovation into the mushroom farm, reducing labor cost, increasing productivity, and improving quality of the mushroom. The ROI which is used as an indicator of performance indicator is 413%.

• Korean Journal of Rural Living Science
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• v.7 no.2
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• pp.139-152
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• 1996

The objectives of this study are : (1) to measure the level of economic stress perception in Korean farm households. (2) to identify the effects of related variables such as socio-demographic variables and economic stability. The data from 505 farm households' wives was analyzed using statistical methods such as frequency, correlation, oneway ANOVA, lease significant difference test, and stepwise multiple regression. The major findings are as follows : The mean value of economic stress perception on the 505 wives was 33.5 points out of a possible 100. Among 3 subsectors, income stress perception had highest score. Socio- demographic variables such as family size, type of farm household, financial manager, debt, credit . grant assistant, wife's age, and educational level of the wife had a significant difference on the economic stress perception of wives in the ANOVA analysis. So did the objective and subjective evaluation of economic stability. As a result of multiple regression analysis, economic stability, debt presence, and wife age were verified explaining 23% of the variance of economic stress perception. Therefore, it can be said that farm wives had relatively high economic stress perception in the case of low economic stability, getting into debt and low age.

• Journal of Families and Better Life
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• v.8 no.2
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• pp.87-100
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• 1990

This study was carried out in an attempt to establish a preliminary scale for measuring $\boxDr$Quality of Life$\boxUl$ of Korean farm households, Data from randomly selected 318 farm households through our the country were analysis. The main results of this study were summarized as follows; 1) The objective levels of living conditions were relatively low in dietary life, healthy & sanitation, and financial stability and were relatively high in family relationship, household work and housing environment. 2) The subjective satisfaction level was lowest in leisure and were relatively high in family relationship and health & sanitation. 3) A comparison of objective level of living conditions and subjective satisfaction level suggested th score of the latter were higher than the former in dietary life and health & sanitation. In the contrary to this, the scores of the former were higher than the latter in housing environment, household work, child education, leisure and family relationship. In particular, the score of the subjective satisfaction level were much higher in housing environment and household work.