A Study on Priority of Classification System for Agro-healing Using the Analytic Hierarchy Process

Yoo, Eunha; Park, Yumin; Jeong, Sun Jin; Kim, Jae Soon; Kang, Yong Ku; Jeong, Yeo jin

doi:10.11628/ksppe.2021.24.6.663

Cited by 2 publications

(1 citation statement)

References 18 publications

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“…Therefore, this study examined the business models of care farms and surveyed the operating status of related domestic agricultural business entities (ABEs) to develop a business model that meets the times along with the increasing demand for care farming, which is newly emerging. Of those, this study aims to analyze the performance determinants that affect the operation of care farms, which were derived through review of the following previous studies (Yoo et al, 2021a;Yoo et al, 2021b;Yoo et al, 2021c;Bae et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Analysis of Performance Factors According to the Operation of Care Farms

Hong¹,

Yoo²,

Moon³

et al. 2023

J. People Plants Environ

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Background and objective: This study was conducted to understand the current status and performance factors of domestic agricultural management in order to develop a business model that meets the needs of the times along with the newly emerging demand for agro-healingMethods: An online survey was conducted on 170 care farming business entities nationwide, and the collected data were frequency-coded using SPSS Ver.25. An exploratory factor analysis was conducted to extract performance factors, and a reliability analysis was performed to verify internal consistency for each factor.Results: The factors that determine the performance of care farms, such as sales and profits, were classified into seven performance determinants (X1 to X7). Factor 1 was classified as one factor by grouping X2(excellence in use of animals/ plants), X6 (program excellence), X5(quality of facility), and X3 (size of facility) together, and Factor 2 was classified as one factor by grouping two items, X7 (governmental support) and X1(location) together, showing high internal consistency between all Cronbach’s α. The correlation between the factors determining care farm performance did not have statistically significant results between X7 (governmental support), X2 (excellence in use of animals/ plants), and X6 (excellence in program), but overall, there was a correlation between items that was statistically significant. A regression analysis was conducted to determine the variables affecting the performance factors of care farms, and at the 95% confidence level, both the location and sales of care farms were statistically significant.Conclusion: Care farms that provide care farming services were often operated on a small scale because they didn’t have a sufficient base of profit, with the exception of farms operated in connection with former rural education farms. In the future, it is considered for care farms necessary to utilize factors of regional differentiation, such as the locational environment and the characteristics of the region, or to link with multiple targets and institutions in the region.

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Section: Introductionmentioning

confidence: 99%

Analysis of Performance Factors According to the Operation of Care Farms

Hong¹,

Yoo²,

Moon³

et al. 2023

J. People Plants Environ

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Semantic Network Analysis of Newspaper Articles related to Agro-healing

Park¹,

Shin

2022

J. People Plants Environ

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Background and objective: Despite the fact that the COVID-19 pandemic has increased the demand for mental health services, access has been limited, resulting in service gaps and severance. Agro-healing, which is expected to be utilized successfully to promote mental health for both individuals and communities, could be a solution. This study was conducted to provide basic data for revitalizing policies and research related to agro-healing by analyzing the trends in big data of online news articles over the last decade.Methods: A total of 2,310 news articles related to agro-healing were collected from January 1, 2012 to December 31, 2021 by crawling Naver News. To extract nouns with practical meaning, the Okt morphological analysis of the KoNLPy module in Python 3.9 was employed. Semantic network analysis was conducted to validate degree centrality, betweenness centrality, and eigenvector centrality in order to understand the centrality and connectivity of significant keywords. The data was visualized using Gephi 0.9.2 by performing CONCOR analysis to generate clusters.Results: The keywords with the highest degree centrality were agro-healing, followed by healing, care farm, vitality, RDA, citizens, and rural tourism. Agro-healing, Healing, stress, urban, disabilities, care farm, dementia, and rural area were highest in terms of betweenness centrality. The eigenvector centrality was highest in agro-healing, followed by vitality, healing, care farm, and effect. As a result of the CONCOR analysis, four clusters were identified: ‘agro-healing characteristics’, ‘agro-healing resources’, ‘agro-healing activities’, and ‘agro-healing target and effect’.Conclusion: According to the findings, social expectations and need for agro-healing to improve public health became a significant part of the discourses. This research is expected to help determine future research and policy directions, as the vitality of agro-healing continues to provide national welfare services and seek sustainable growth in agricultural and rural areas.

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A Study on Priority of Classification System for Agro-healing Using the Analytic Hierarchy Process

Cited by 2 publications

References 18 publications

Analysis of Performance Factors According to the Operation of Care Farms

Analysis of Performance Factors According to the Operation of Care Farms

Semantic Network Analysis of Newspaper Articles related to Agro-healing

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