• The Korean Journal of Franchise Management
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• v.11 no.4
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• pp.7-15
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• 2020

Purpose: The purpose of this study is to clarify the role of decoupling between job characteristics, innovation behavior, and innovation resistance in order to seek ways for companies to survive and grow continuously through innovation activities in various uncertain situations. Research design, data and methodology: A total of 263 valid questionnaires were collected and used for analysis for employees working at the company. For the analysis, simple and multiple regression analysis, and 3-step mediated regression analysis were conducted using SPSS 24.0 and AMOS 24.0. Results: First, it was found that skill variety, task identity, autonomy, and feedback increase decoupling, and decoupling increases innovation resistance. In addition, it was confirmed that decoupling had a mediating effect between job characteristics and innovation resistance excluding task significance. Finally, it was found that task significance and feedback increase innovation behavior, and decoupling and task identity increase innovation resistance, but feedback can alleviate innovation resistance. Conclusions: As a result of the analysis, the fact that job characteristics excluding task importance have a positive effect on decoupling means that there are two sides of job characteristics perceived by employees. In other words, it means that the results of analysis on the jobs that the company assigns to its members may not be effective. In addition, decoupling, a phenomenon that seems to be accepting on the outside, but perceives that it is negative on the inside, means that there is a possibility to reject innovation. Therefore, prior to carrying out innovation activities, companies should give clear job specifications and meanings for the job and give them autonomy when assigning jobs to their members. In order to provide appropriate feedback, the company must design, operate, and provide feedback. It was found that there was a need to review the overall effectiveness. In addition, efforts such as strengthening corporate-level fairness, maintaining psychological contracts, and realizing authentic leadership should be preceded to reduce decoupling.

• Women's Health Nursing
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• v.26 no.4
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• pp.300-317
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• 2020

Purpose: Hysteroscopy can be used both to diagnose and to treat intrauterine pathologies. It is well known that hysteroscopy helps to improve reproductive outcomes by treating intrauterine pathologies. However, it is uncertain whether hysteroscopy is helpful in the absence of intrauterine pathologies. This study aimed to confirm whether hysteroscopy improves the reproductive outcomes of infertile women without intrauterine pathologies. Methods: We conducted a systematic review of 11 studies retrieved from Ovid-MEDLINE, Ovid-Embase, and the Cochrane Library. Two independent investigators extracted the data and used risk-of-bias tools (RoB 2.0 and ROBINS-I) to assess their quality. Results: Diagnostic hysteroscopy prior to in vitro fertilization (IVF)/intracytoplasmic sperm injection (ICSI) was associated with a higher clinical pregnancy rate (CPR) and live birth rate (LBR) than non-hysteroscopy in patients with recurrent implantation failure (RIF) (odds ratio, 1.79 and 1.46; 95% confidence interval, 1.40-2.30 and 1.08-1.97 for CPR and LBR, respectively) while hysteroscopy prior to first IVF was ineffective. The overall meta-analysis of LBR showed statistically significant findings for RIF, but a subgroup analysis showed effects only in prospective cohorts (odds ratio, 1.40 and 1.47; 95% confidence interval, 0.62-3.16 and 1.04-2.07 for randomized controlled trials and prospective cohorts, respectively). Therefore, the LBR should be interpreted carefully and further research is needed. Conclusion: Although further research is warranted, hysteroscopy may be considered as a diagnostic and treatment option for infertile women who have experienced RIF regardless of intrauterine pathologies. This finding enables nurses to educate and support infertile women with RIF prior to IVF/ICSI.

• Journal of Information Technology Services
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• v.20 no.1
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• pp.67-79
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• 2021

The advent of the 4th Industrial Revolution is also causing many changes in defense operations. Defense reform and the fourth industrial revolution promoted smart defense innovation, and attempts are being made to incorporate cutting-edge science and technology into various fields such as weapons systems and defense operations. Education and training is one of the areas in which information and intelligence are urgently needed in the spirit of defense operations. Due to the nature of defense education and training, which aims to fight against the enemy, there is no emphasis on psychological training in the field rather than informatization, but in developed countries with various experiences of modern warfare, investment and vitalization of education and training are vital. Through this, efforts are being made to foster soldiers with problem-solving skills in uncertain battlefields. The informatization and intelligence of defense education and training is no longer a matter that can be delayed, and the innovation of education and training using cutting-edge science and technology can be said to be an age-old task to improve the results of education and training in the fourth industrial revolution. The purpose of this is because the application of related technologies is not the goal itself as the 4th Industrial Revolution arrives, but it has been made possible through the rapid advancement of science and technology that has made it difficult to realize education and training, even though it has long been desired. Ultimately, education and training data will be integrated and artificial intelligence-based intelligent learning systems will maximize the performance of education and training, thereby improving the combat readiness.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.2
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• pp.163-176
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• 2022

As the business ecosystem has become more uncertain, the sources of supply chain risk have also been becoming more diverse. In particular, due to the development of informational technology in recent years, firms need to consider the emerging supply chain risk sources as well as traditional supply chain risk sources. A typical example is negative word-of-mouth by social media. Therefore, we investigated the virality of negative word-of-mouth on manufacturing firms by using YouTube as a representative social media. More specifically, we investigated how the social capital of the video creator influences the virality of negative word-of-mouth and how the emotional tone of the video affects the virality of negative word-of-mouth. In conclusion, the social capital of the video creator influenced the scale and speed of negative word-of-mouth. Furthermore, negative emotion words moderated the relation between the social capital of the video creator and the scale of negative word-of-mouth.

• Nuclear Engineering and Technology
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• v.54 no.7
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• pp.2367-2375
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• 2022

In this work, we propose a new mechanistic model for the treatment of helium behaviour at the grain boundaries in oxide nuclear fuel. The model provides a rate-theory description of helium inter-granular behaviour, considering diffusion towards grain edges, trapping in lenticular bubbles, and thermal resolution. It is paired with a rate-theory description of helium intra-granular behaviour that includes diffusion towards grain boundaries, trapping in spherical bubbles, and thermal re-solution. The proposed model has been implemented in the meso-scale software designed for coupling with fuel performance codes SCIANTIX. It is validated against thermal desorption experiments performed on doped UO₂ samples annealed at different temperatures. The overall agreement of the new model with the experimental data is improved, both in terms of integral helium release and of the helium release rate. By considering the contribution of helium at the grain boundaries in the new model, it is possible to represent the kinetics of helium release rate at high temperature. Given the uncertainties involved in the initial conditions for the inter-granular part of the model and the uncertainties associated to some model parameters for which limited lower-length scale information is available, such as the helium diffusivity at the grain boundaries, the results are complemented by a dedicated uncertainty analysis. This assessment demonstrates that the initial conditions, chosen in a reasonable range, have limited impact on the results, and confirms that it is possible to achieve satisfying results using sound values for the uncertain physical parameters.

• The Journal of the Korea Contents Association
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• v.22 no.6
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• pp.701-711
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• 2022

This study tried to examine the relationship between superior leadership and emotional support from co-workers on task performance through performance evaluation fairness and self-efficacy in order to find factors that affect the task performance of a company in an uncertain market environment. For this purpose, 500 copies of questionnaire data were collected from corporate employees, and the research hypothesis was verified using Smart PLS 3.0. As a result of the study, superior leadership and emotional support from co-workers showed a positive (+) effect individually on the fairness of employee performance evaluation, Performance evaluation fairness showed a positive (+) effect on self-efficacy. Through this study, it was found that the fairness and self-efficacy of the performance evaluation accepted by employees affects work performance, providing a theoretical foundation for subsequent researchers. Practical implications are suggested to inspire employees to take on a challenge by managing them properly. In future research, based on the results of this study, various studies are needed on the factors that an organization must have for task performance.

• Journal of Korea Trade
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• v.24 no.6
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• pp.1-18
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• 2020

Purpose - This study investigates whether a listing effect exists in cross-border M&As and whether the effect can be attributed to the uncertainty of the GDP growth rate in the target firm's home country. We apply a joint variable analysis using M&A announcement data from the Korea Exchange (KRX), Shanghai Stock Exchange (SSE), and the Taiwan Stock Exchange (TWSE) from 2004 to 2013. We also conduct an event study using the measure of the uncertainty of the GDP growth rate (based on IMF statistics) in 55 target countries. Design/methodology - We measure the abnormal return (AR) using the market-adjusted model. We test the significance of the AR and the cumulative abnormal return (CAR) using a one-sample t-test. We examine the characteristics of the CARs depending on whether the target company is listed by applying a difference analysis using CAR as a test variable. In addition, we set CAR (-5, +5) as a dependent variable to identify the cause of the listing effect, and test both the financial characteristic variables of the acquirer and the collective characteristic variables of the merger as independent variables in the multiple regression analysis. Findings - First, we find the listing effect of cross-border M&As in the KRX, SSE, and TWSE, which represent the capital markets in Korea, China, and Taiwan, respectively. This listing effect persists during the global financial crisis and has a negative effect on the wealth of acquiring shareholders, especially when the target countries are emerging markets. Second, greater uncertainty regarding the target countries' economic growth in cross-border M&As has a negative effect on the wealth of acquiring firms' shareholders. Third, our empirical analysis demonstrates that the listing effect is attributable to the fact that firms listed in a target country with greater uncertainty of economic growth are more directly and greatly exposed to uncertain capital markets through stock markets, than are unlisted firms. Originality/value - This study is significant in that it presents a new strategic perspective in the study of cross-border M&As by demonstrating empirically that the listing effect is attributable to the uncertainty regarding the economic development of the target firms' home countries.

• Journal of Korean Clinical Nursing Research
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• v.28 no.3
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• pp.299-307
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• 2022

Purpose: The purpose of this study was to understand the effects of infection control fatigue and social support on burnout among nurses during the Coronavirus Disease 2019 (COVID-19) pandemic. Methods: This study is a descriptive survey study designed to confirm the effects of nurses' infection control fatigue and social support on burnout among nurses during the COVID-19 pandemic. The collected data were analyzed using frequency, percentage, mean, standard devia analyzed using frequency, percentage, mean, standard deviation, independent t-test, One-way ANOVA, Scheffe test, Pearson's correlation coefficient, and stepwise multiple regression analysis using SPSS Statistics 26.0. Results: An analysis of the correlations between fatigue from infection control, social support, and burnout showed a positive correlation between burnout and fatigue from infection control (r=.39, p<.001), and a negative correlation between burnout and social support (r=-.29, p<.001). Conflict and lack of support due to uncertain circumstances (β=.51, p<.001), support from supervisor's (β=-.22, p<.001), and experience of infection management education during the previous 1year (β=-.15, p=.007) were identified as the factors that influenced burnout among nurses, and explained 39.0% of the variance in burnout. Conclusion: The results of this study demonstrate that fatigue from infection control and social support influence burnout levels among nurses, which suggests the need to establish a new kind of work culture. Additionally, the findings call for the development and implementation of interventional programs that can reduce fatigue from infection control and increase social support for nurses.

• Journal of Oriental Neuropsychiatry
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• v.33 no.4
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• pp.401-424
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• 2022

Objectives: As effective treatments for dementia are lacking in Western medicine, complementary and alternative medicine (CAM) is considered a useful option. While the quality of life (QoL) is a vital outcome for patients with dementia, the QoL of patients receiving CAM for dementia remains ambiguous. This study aimed to determine the effect of CAM on QoL outcomes in dementia patients. Methods: A search was performed using the keywords "dementia," "Alzheimer's," "cognitive impairment," "Chinese," "Korean," "oriental," "herbal," "acupuncture," and "quality of life". All quantitative data were synthesized using R version 4.1.1. Results: Twenty-five randomized controlled trials (RCTs), 16 pre-post trials, and two cohort studies were selected for the systematic review. QoL in Alzheimer's disease (QOL-AD) (n=11, 25.6%) and geriatric QoL in dementia (GQOL-D, n=9, 20.9%) were the most utilized QoL instruments. Significant benefits in QoL were observed after receiving mind, body, combined mind and body, nursing, oriental medicine, and acupuncture therapies. In the meta-analysis, the combined effect was shown to significantly increase QOL-AD compared to before CAM interventions (standardized mean difference, SMD: 0.507; 95% confidence interval (CI), 0.191~0.824; p<0.01). The overall synthesized estimates in the GQOL-D showed a significantly improved QoL (SMD: 0.537, 95% CI: 0.238~0.837 p<0.01; one group; SMD: 1.465, 95% CI: 0.934~1.996, p<0.01). The seven studies assessing the cost-effectiveness of CAM reported uncertain outcomes. Conclusions: This study showed that CAM interventions benefited patients with dementia by improving their QoL. While additional standardized research is required, CAMs are suggested as effective clinical management for patients with dementia. They are also suggested as complementing therapies for these patients.

• Journal of the Korean Society of Systems Engineering
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• v.18 no.2
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• pp.75-93
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• 2022

Machine learning (ML) data-driven meta-model is proposed as a surrogate model to reduce the excessive computational cost of the physics-based model and facilitate the real-time prediction of a nuclear power plant's transient response. To forecast the transient response three machine learning (ML) meta-models based on recurrent neural networks (RNNs); specifically, Long Short Term Memory (LSTM), Gated Recurrent Unit (GRU), and a sequence combination of Convolutional Neural Network (CNN) and LSTM are developed. The chosen accident scenario is a control element assembly withdrawal at power concurrent with the Loss Of Offsite Power (LOOP). The transient response was obtained using the best estimate thermal hydraulics code, MARS-KS, and cross-validated against the Design and control document (DCD). DAKOTA software is loosely coupled with MARS-KS code via a python interface to perform the Best Estimate Plus Uncertainty Quantification (BEPU) analysis and generate a time series database of the system response to train, test and validate the ML meta-models. Key uncertain parameters identified as required by the CASU methodology were propagated using the non-parametric Monte-Carlo (MC) random propagation and Latin Hypercube Sampling technique until a statistically significant database (181 samples) as required by Wilk's fifth order is achieved with 95% probability and 95% confidence level. The three ML RNN models were built and optimized with the help of the Talos tool and demonstrated excellent performance in forecasting the most probable NPP transient response. This research was guided by the Systems Engineering (SE) approach for the systematic and efficient planning and execution of the research.