• Journal of Information Technology Services
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• v.16 no.3
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• pp.67-81
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• 2017

IT project teams are composed of experts from various domains with different backgrounds, such as business and technologies. Thus, enhancing knowledge sharing and increasing team social capital are critical for the success of the project. This study examines the relationship among the team social capital, team climate and team performance. A research model and hypotheses are developed from literature review and empirically validated. The research model consists of team social capital, team climate and team performance. Specifically, team social capital, as antecedents, wasconceptualized asinternal and external differentiated by team boundary, and team climate is conceptualized as innovative climate and supportive climate. Using measures adopted from previous studies, 166 data points were collected to test the research model and related hypotheses. PLS data analysis indicated that internal and external social capitalhave positive effect on innovative climate while internal social capital has a positive effect on supportive team climate. The innovative and supportive climate has significant effect on the team performance. Based on the results, we proposed several team management skills for IT project managers. Theoretical constributions are discussed at the end with limitations and further studies.

• Journal of the Korean Operations Research and Management Science Society
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• v.41 no.4
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• pp.75-93
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• 2016

This study aims at analyzing the relationship between team characteristic and innovation performance. The mediating effect of creative climate on the team characteristic and innovation performance is also measured. Based upon literature review, individual creative characteristics, team diversity, team cohesion, task characteristics are presented as antecedents of team characteristic. Creative climate affects the creative behavior and innovative performance. Creative climate is measured as the Team Climate Inventory (TCI) proposed by Anderson & West (1998) including goal, participative-autonomy and innovative-support. Data were collected from 186 survey responses (54 Teams) out of total 462 (69 teams) from the R&D department of a major ICT firm in Korea. Empirical results show the diversity, cohesion, job characteristic, individual creative characteristic have a positive effect on the creative climate and innovation performance. The participative-autonomy climate factor appears to mediate the relationship between team characteristic (diversity, cohesion, job and individual characteristics) and innovation performance. However, the mediating effects of goals and innovative-support factors were not significant statistically. It was confirmed that the organization can contribute to improve the team innovation performance by facilitating a autonomy and participative climate as well as fostering the team characteristic.

• Journal of Korean Academy of Nursing Administration
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• v.15 no.1
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• pp.72-80
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• 2009

Purpose: To investigate the influence of a team learning climate on group performance of hospital nurses. Method: The subjects were 386 nurses who have been working in six hospitals. The data were collected by a structured questionnaire from January 20 to April 30 of 2006. The data were analyzed by SAS version 8.2, including descriptive statistics, Pearson correlation coefficient, and stepwise multiple regression. Results: The mean score of group performance was 3.38 and team learning climate was 4.89. The group performance was positively correlated with team learning climate(r=.40, p<.0001). The team learning climate explained 15% of the variance in group performance. Conclusion: The findings showed that team learning climate was an important factor in enhancing group performance in nursing organization. Therefore, the nurse manager will establish the strategies to improve the team learning climate of the nurses in order to promote organizational performance.

• Atmosphere
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• v.30 no.2
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• pp.141-154
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• 2020

Seasonal forecast is growing in demand, as it provides valuable information for decision making and potential to reduce impact on weather events. This study examines how operational climate prediction systems can be reliable, producing the probability forecast in seasonal scale. A reliability diagram was used, which is a tool for the reliability by comparing probabilities with the corresponding observed frequency. It is proposed for a method grading scales of 1-5 based on the reliability diagram to quantify the reliability. Probabilities are derived from ensemble members using hindcast data. The analysis is focused on skill for 2 m temperature and precipitation from climate prediction systems in KMA, UKMO, and ECMWF, NCEP and JMA. Five categorizations are found depending on variables, seasons and regions. The probability forecast for 2 m temperature can be relied on while that for precipitation is reliable only in few regions. The probabilistic skill in KMA and UKMO is comparable with ECMWF, and the reliabilities tend to increase as the ensemble size and hindcast period increasing.

• Atmosphere
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• v.32 no.2
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• pp.87-101
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• 2022

In this paper, the performance improvement for the new KMA's Climate Prediction System (GloSea6), which has been built and tested in 2021, is presented by assessing the bias distribution of basic variables from 24 years of GloSea6 hindcasts. Along with the upgrade from GloSea5 to GloSea6, the performance of GloSea6 can be regarded as notable in many respects: improvements in (i) negative bias of geopotential height over the tropical and mid-latitude troposphere and over polar stratosphere in boreal summer; (ii) cold bias of tropospheric temperature; (iii) underestimation of mid-latitude jets; (iv) dry bias in the lower troposphere; (v) cold tongue bias in the equatorial SST and the warm bias of Southern Ocean, suggesting the potential of improvements to the major climate variability in GloSea6. The warm surface temperature in the northern hemisphere continent in summer is eliminated by using CDF-matched soil-moisture initials. However, the cold bias in high latitude snow-covered area in winter still needs to be improved in the future. The intensification of the westerly winds of the summer Asian monsoon and the weakening of the northwest Pacific high, which are considered to be major errors in the GloSea system, had not been significantly improved. However, both the use of increased number of ensembles and the initial conditions at the closest initial dates reveals possibility to improve these biases. It is also noted that the effect of ensemble expansion mainly contributes to the improvement of annual variability over high latitudes and polar regions.

• Journal of Korean Academy of Nursing Administration
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• v.19 no.2
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• pp.282-291
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• 2013

Purpose: The purpose of this study was to identify clusters of nursing competency, and investigate the influence of reflective thinking, team learning climate, and learning organization building according to nursing competency clusters. Methods: Participants were 244 clinical nurses who worked in 4 general hospitals in Gwangju Metropolitan City. Data were collected by self-report questionnaires during June and July, 2011. Nursing competency, levels of reflection hierarchy, team learning climate, and learning organization building were measured. Data were analyzed using frequencies, means, t-test, one-way ANOVA, Pearson correlation coefficients, and K-means cluster analysis with SPSS/WIN 20.0 version. Results: Nursing competency correlated positively with intensive reflection, reflection, team learning climate, and learning organization building (p<.001). There were three clusters of nursing competency in a clinical ladder, which were derived from cluster analysis, grouped as high, middle, and low competency. Intensive reflection, reflection, team learning climate, and learning organization building showed significant differences according to grouping of nursing competency. Conclusion: The results indicate that developing intensive reflection, reflection, team learning climate, and learning organization building would be useful strategies for enhancement of nursing competency.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.1 no.1
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• pp.68-73
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• 2020

Korean fir (Abies koreana) is an evergreen coniferous tree species that is unique to South Korea. A. koreana is found in a limited sub-alpine habitat and is considered particularly vulnerable to climate change. Identification of populations vulnerable to climate change is an important component of conservation programs. In this study, a heat stress-induced transcriptome RNA-seq dataset was used to identify a subset of six genes for assessment as candidate marker genes for ecologically vulnerable populations. Samples of A. koreana were isolated from ecologically stable and vulnerable regions of the Halla and Jiri mountains, and the expression levels of the six candidate markers were assessed using quantitative real-time polymerase chain reaction. All six of the candidate genes exhibited higher expression levels in samples from vulnerable regions compared with stable regions. These results confirm that the six high temperature-induced genes can be used as diagnostic markers for the identification of populations of A. koreana that are experiencing stress due to the effects of climate change.

• Journal of Korean Society of Rural Planning
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• v.23 no.4
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• pp.153-168
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• 2017

The main objective of this study was to assess reference evapotranspiration based on multiple GCMs (General Circulation Models) and estimation methods. In this study, 10 GCMs based on the RCP (Representative Concentration Pathway) 4.5 scenario were used to estimate reference evapotranspiration. 54 ASOS (Automated Synoptic Observing System) data were constructed by statistical downscaling techniques. The meteorological variables of precipitation, maximum temperature and minimum temperature, relative humidity, wind speed, and solar radiation were produced using GCMs. For the past and future periods, we estimated reference evapotranspiration by GCMs and analyzed the statistical characteristics and analyzed its uncertainty. Five methods (BC: Blaney-Criddle, HS: Hargreaves-Samani, MK: Makkink, MS: Matt-Shuttleworth, and PM: Penman-Monteith) were selected to analyze the uncertainty by reference evapotranspiration estimation methods. We compared the uncertainty of reference evapotranspiration method by the variable expansion and analyzed which variables greatly influence reference evapotranspiration estimation. The posterior probabilities of five methods were estimated as BC: 0.1792, HS: 0.1775, MK: 0.2361, MS: 0.2054, and PM: 0.2018. The posterior probability indicated how well reference evapotranspiration estimated with 10 GCMs for five methods reflected the estimated reference evapotranspiration using the observed data. Through this study, we analyzed the overall characteristics of reference evapotranspiration according to GCMs and reference evapotranspiration estimation methods The results of this study might be used as a basic data for preparing the standard method of reference evapotranspiration to derive the water management method under climate change.

• Journal of Information Technology Applications and Management
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• v.17 no.4
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• pp.19-38
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• 2010

This paper investigates the effect of stress on knowledge creation. The goal stress of resource inadequacy and job stress had negative influences on knowledge creation. However, the cohesion and mastery climate of team had positive influence on knowledge creation. Therefore this paper verifies the moderate role of the cohesion and mastery climate of team on the relationship between stress and knowledge creation. The model developed was tested using data collected from knowledge based industry with 375 members in 69 teams in 12 different firms. A Hierarchical Linear Model (HLM) was used to test the hypotheses generated from the model. Results show that job stress had a negative influence on knowledge creation as we expected but the goal stress didn't. The mastery climate of team affected knowledge creation positively and moderated the relationship between the goal stress and knowledge creation. Furthermore, the team cohesion had a positive influence on knowledge creation. The study provided some implications that practitioners should consider the stress when they design jobs for team members and suggest them the way to manage their job stress when they work.

• The Korean Journal of Applied Statistics
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• v.23 no.3
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• pp.559-571
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• 2010

The Demand-Control model has been one of the most popular theoretical models to explain job stress. This study extends the Demand-Control model to the team level and examines the relationship between job demand and job stress to tests the moderating effect of the `team relationship climate' on the relationship between job demand and job stress. Data were collected from 34 teams across 19 organizations and analyzed using HLM. The results showed that job demand was significantly related to job stress. Based on the team level analysis, the team relationship climate was found to moderate the relationship between job demand and job stress. In addition, the consideration behavior by the leader was significantly correlated with the team relationship climate. Finally the theoretical and practical implications and limitations of this study were discussed.