• Journal of Environmental Impact Assessment
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• v.20 no.6
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• pp.891-905
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• 2011

Climate vulnerability index is usually defined as a function of the climate exposure, sensitivity, and adaptive capacity, which requires adequate selection of proxy variables of each variable. We selected and used 9 proxy variables related to climate exposure in the literature, and diagnosed the adequacy of them for application in Korean peninsula. The selected proxy variables are: four variables from temperature, three from precipitation, one from wind speed, and one from relative humidity. We collected climate data over both previous year (1981~2010) and future climate scenario (A1B scenario of IPCC SERES) for 2020, 2050, and 2100. We introduced the spatial and temporal diagnostic statistical parameters, and evaluated both spatial and time variabilities in the relative scale. Of 9 proxy variables, effective humidity indicated the most sensitive to climate change temporally with the biggest spatial variability, implying a good proxy variable in diagnostics of climate change vulnerability in Korea. The second most sensitive variable is the frequency of strong wind speed with a decreasing trend, suggesting that it should be used carefully or may not be of broad utility as a proxy variable in Korea. The A1B scenario of future climate in 2020, 2050 and 2100 matches well with the extension of linear trend of observed variables during 1981~2010, indicating that, except for strong wind speed, the selected proxy variables can be effectively used in calculating the vulnerability index for both past and future climate over Korea. Other local variabilities for the past and future climate in association with climate exposure variables are also discussed here.

• Journal of Korean Academy of Nursing Administration
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• v.8 no.4
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• pp.605-614
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• 2002

Purpose : The purposes of this study is twofold: (a) to investigate the effect of job stress and organizational climate on the organizational effectiveness of hospital nurses, and (2) to examine the moderating effect of organizational climate on job stress. Method : Three organizational effectiveness variables(e .g., job satisfaction, organizational committment and group productivity) as outcomes variables were examined. The sample consisted of 602 nurses from 5 general hospitals affiliated university. Data were collected with self-administrated questionnaires and analyzed using hierarchical regression. Results : It was found that: (a) seven job stress variables(e. g., workload, role conflict, schedule, lack of knowledge, conflict with superior, conflict with other personnel and conflict with patients) have negative effect on job satisfaction and organizational committment; (b) organizational climate have positive main effects on job satisfaction and organizational committment; (c) the negative effects of job stress variables on job satisfaction and organizational committment are not moderated by organizational climate. Conclusion : Organizational climate mediates the effects of job stress on group productivity, but the size of the mediating effects was small. Various outcome variables need to be discussed further research.

• Journal of Korean Academy of Nursing Administration
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• v.12 no.4
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• pp.564-573
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• 2006

Purposes: This study was to provide basic data to explain the effect of the organizational effectiveness factor on hospital nursing, to construct an appropriate model to examine the validation and relationship with variables and to provide basic data for improving the organizational effectiveness of hospital nursing. Method: This study was a descriptive correlation research. Subjects of the study were 348 nurses, 219 patients, and 89 nurses for nursing quality. Twelve measurement variables and nine paths were established in the hypothetical model. Results: The fitness indices of the model were GFI=0.91, NFI=0.90, and PGFI=0.49. Five among the nine paths proved to be statistically significant : level of nurse manpower to organizational effectiveness, conflict to organizational effectiveness, organizational climate to organizational effectiveness, level of nurse manpower to organizational climate, and leadership to organizational climate. Level of nurse manpower and leadership influenced organizational climate. Organizational climate accounted for 43% by the predictor variables, and the level of nurse manpower, conflict, and organizational climate influenced the organizational effectiveness, which accounted for 77% by the predictor variables. Conclusion: This study identified that the level of nurse manpower, leadership, conflict, and organizational climate are important factors affecting organizational effectiveness.

• Journal of Korean Society on Water Environment
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• v.28 no.3
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• pp.444-452
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• 2012

This study aims at assessing vulnerability of water quality and aquatic ecosystem to climate change by using proxy variables. Vulnerability to climate change is defined as a function of exposure to climate, sensitivity, and adaptive capacity. Detailed proxy variables were selected considering availability and then standardized by re-scaling concept. After adequate weights were assigned to standardized proxy variables by Delphi technique, vulnerability index was calculated. As results, vulnerability of adjacent regions to coastal areas include water quality and aquatic ecosystem is relatively higher than that of inland areas, and especially adjacent region to the western and southeast seas, and Jeju show high vulnerabilities. Vulnerability in the future was performed based on A1B scenario (IPCC, 2000). Temporally, the increase of vulnerability from 2050s to 2100s may be larger than the increase from 2000s to 2050s. Because vulnerability index was estimated through the relationship among various proxy variables, it is important to consider characteristics of local region with measurements and policies for reduction of sensitivity and enhancement of adaptive capacity on climate change. This study is expected to be useful in planning adaptation measures and selecting priority to the policy on climate change.

• Journal of Korean Society for Atmospheric Environment
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• v.28 no.1
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• pp.22-38
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• 2012

Adaptation of climate change is necessary to avoid unexpected impacts of climate change caused by human activities. Vulnerability refers to the degree to which system cannot cope with impacts of climate change, encompassing physical, social and economic aspects. Therefore the quantification of climate change impacts and its vulnerability is needed to identify vulnerable regions and to setup the proper strategies for adaptation. In this study, climate change vulnerability is defined as a function of climate exposure, sensitivity, and adaptive capacity. Also, we identified regions vulnerable to ozone due to climate change in Korea using developed proxy variables of vulnerability of regional level. 18 proxy variables are selected through delphi survey to assess vulnerability over human health sector for ozone concentration change due to climate change. Also, we estimate the weighting score of proxy variables from delphi survey. The results showed that the local regions with higher vulnerability index in the sector of human health are Seoul and Daegu, whereas regions with lower one are Jeollanam-do, Gyeonggi-do, Gwangju, Busan, Daejeon, and Gangwon-do. The regions of high level vulnerability are mainly caused by their high ozone exposure. We also assessed future vulnerability according to the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) A2, A1FI, A1T, A1B, B2, and B1 scenarios in 2020s, 2050s and 2100s. The results showed that vulnerability increased in all scenarios due to increased ozone concentrations. Especially vulnerability index is increased by approximately 2 times in A1FI scenarios in the 2020s. This study could support regionally adjusted adaptation polices and the quantitative background of policy priority as providing the information on the regional vulnerability of ozone due to climate change in Korea.

• Journal of Fisheries and Marine Sciences Education
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• v.21 no.1
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• pp.121-133
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• 2009

This study tested the relations of schools organizational climate and teachers' job stresses, perceived by 913 teachers from 45 elementary, junior- and senior-high schools. Pearson's correlation analysis for the relations between the sub-factors of both organizational climate and job stresses and cannonical correlation analysis for the relative contribution of individual variable of organizational climate upon job stress were applied for the test. The results of Pearson's correlation analysis showed that while 'intimacy', 'esprit', 'considerations', and 'production emphasis' climate had negative correlations with job stress sub-factors, 'disengagement' and 'aloofness' climate had positive correlation. 'Student guidance', a sub-factor of job stresses, did not have statistically significant correlation with any sub-factors of organizational climate. Findings from cannonical correlation analysis showed 2 significant cannonical functions to explain the relations between the sets of variables. 'Disengagement' from organizational climate positively contributed with 'authority forfeiture' and 'dissention and conflict' of the job stresses variables.

• Journal of The Korean Society of Agricultural Engineers
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• v.55 no.1
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• pp.31-38
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• 2013

The purpose of this study was to evaluate climate change vulnerability over the agricultural infrastructure in terms of flood and drought using principal component analysis. Vulnerability was assessed using vulnerability resilience index (VRI) which combines climate exposure, sensitivity, and adaptive capacity. Ten flood proxy variables and six drought proxy variables for the vulnerability assessment were selected by opinions of researchers and experts. The statistical data on 16 proxy variables for the local governments (Si, Do) were collected. To identify major variables and to explain the trend in whole data set, principal component analysis (PCA) was conducted. The result of PCA showed that the first 3 principal components explained approximately 83 % and 89 % of the total variance for the flood and drought, respectively. VRI assessment for the local governments based on the PCA results indicated that provinces where having the relatively large cultivation areas were categorized as vulnerable to climate change.

• Human Ecology Research
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• v.61 no.4
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• pp.599-613
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• 2023

This study investigated female consumers' attitudes toward the general and fashion-specific climate environments and analyzed the relations between the attitudes and the variables such as values, knowledge, and climate cognition. The data was collected from a sample of 450 women in their 20s, 30s, and 40s via quota sampling from a selfreported online survey in 2023. The measurement comprised the attitudes toward the general and fashion-specific climate environments, Rokeach's 18 terminal values, Holbrook's 8 consumer values regarding fashion products, climate environmental knowledge related to fashion, the cognition concerning the climate crisis, and several demographic variables. Descriptive statistics, factor analysis, reliability analysis, and correlations were applied to the data using SPSS. As a result, two factors were determined for the attitudes toward the general and fashion-specific climate environments, respectively: social and personal. Family security, happiness, and self-respect were identified as important terminal values. Quality, efficiency, aesthetics, and ethics were considered important when the current sample group purchased fashion products. The mean score of climate environmental knowledge related to fashion was lower than neutral; however the cognition of the climate crisis was considerably high. Attitudes toward the general and fashion-specific climate environments showed positive relations with values, knowledge, and climate cognition. The results were discussed to provide some insight and suggestions to carbon neutrality and the related studies.

• Journal of Animal Science and Technology
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• v.63 no.2
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• pp.339-353
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• 2021

This study aimed to assess the causality of different climate variables on the production of whole crop maize (Zea mays L.; WCM) in the central inland region of the Korea. Furthermore, the effect of these climate variables was also determined by looking at direct and indirect pathways during the stages before and after silking. The WCM metadata (n = 640) were collected from the Rural Development Administration's reports of new variety adaptability from 1985-2011 (27 years). The climate data was collected based on year and location from the Korean Meteorology Administration's weather information system. Causality, in this study, was defined by various cause-and-effect relationships between climatic factors, such as temperature, rainfall amount, sunshine duration, wind speed and relative humidity in the seeding to silking stage and the silking to harvesting stage. All climate variables except wind speed were different before and after the silking stage, which indicates the silking occurred during the period when the Korean season changed from spring to summer. Therefore, the structure of causality was constructed by taking account of the climate variables that were divided by the silking stage. In particular, the indirect effect of rainfall through the appropriate temperature range was different before and after the silking stage. The damage caused by heat-humidity was having effect before the silking stage while the damage caused by night-heat was not affecting WCM production. There was a large variation in soil surface temperature and rainfall before and after the silking stage. Over 350 mm of rainfall affected dry matter yield (DMY) when soil surface temperatures were less than 22℃ before the silking stage. Over 900 mm of rainfall also affected DMY when soil surface temperatures were over 27℃ after the silking stage. For the longitudinal effects of soil surface temperature and rainfall amount, less than 22℃ soil surface temperature and over 300 mm of rainfall before the silking stage affected yield through over 26℃ soil surface temperature and less than 900 mm rainfall after the silking stage, respectively.

• Journal of the Korean Data and Information Science Society
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• v.27 no.4
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• pp.969-977
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• 2016

Climate change affects the growth of crops which were planted especially in fields, and it becomes more important to use climate data to predict the yields of the major vagetables. The variation of the crop products caused by climate change is one of the significant factors for the discrepancy of the demand and supply, and leads to the price instability. In this paper, using a panel regression model, we predicted the garlic yields with the weather conditions of different regions. More specifically we used the panel data of the several climate variables for 15 main garlic production areas from 2006 to 2015. Seven variables (average temperature, average maximum temperature, average minimum temperature, average surface temperature, cumulative precipitation, average relative humidity, cumulative duration time of sunshine) for each month were considered, and most significant 7 variables were selected from the total 84 variables by the stepwise regression. The random effects model was chosen by the Hausman test. The average maximum temperature (January), the cumulative precipitation (March, October), the cumulative duration time of sunshine (April, October) were chosen among the variables as the significant climate variables of the model