• Journal of Industrial Convergence
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• v.22 no.5
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• pp.107-116
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• 2024

This study is a descriptive research study to determine the extent to which end-of-life care stress, death awareness, and prior decision-making attitudes of nurses at a hospice and palliative nursing institution have an impact on end-of-life care performance. The subjects of this study were 200 nurses working at a hospice and palliative nursing institution. Data collection for this study was conducted from August 9 to September 30, 2021, using two methods: written questionnaire and internet survey. The data analysis method used Pearson's correlation coefficient to analyze the relationship between the subjects' end-of-life care stress, death awareness, prior decision-making attitude, and end-of-life care performance. Hierarchical Regression was used to identify factors affecting the subject's end-of-life care performance. The results of this study showed a significant correlation between end-of-life care performance and death awareness (r=.22, p=.002), and end-of-life care performance and prior decision-making attitude (r=.20, p=.004). And prior decision-making attitude and death awareness had a significant impact on end-of-life care performance. As death awareness and prior decision-making attitudes increased, end-of-life care performance increased, and end-of-life care stress did not appear to be a statistically significant factor influencing end-of-life care performance. In order to improve hospice nurses' ability to provide end-of-life care, intervention that takes into account the influencing factors is required.

• Information Systems Review
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• v.24 no.3
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• pp.43-68
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• 2022

With the growing demand for online food delivery (OFD) services via Online to Offline (O2O) platforms, it is required for academic researchers to identify the success factors of OFD businesses. In line with this, this research examines the impact of the core service attributes of a restaurant (hygiene, interactivity, trust,and popularity) on business success in the OFD platform context from the perspective of information asymmetry. Furthermore, the moderating effects of hygiene factor between the core service attributes and the success of restaurants are evaluated. We utilize 1,146 restaurants registered on the largest OFD platform in Korea. The results of this study demonstrate that hygiene (certification), trust (franchise), popularity (favorite) factors have positive impacts on the success of OFD businesses. Moreover, we find that franchise restaurants with high response rates to customer reviews and inquiries achieve higher sales when they have hygiene certifications than those without the certification do. The key findings bear significant contributions to prior literature by empirically substantiating the pivotal role of service quality signals in fostering restaurant success on the OFD platforms. In addition, this study provides business implications for restaurants in O2O platform.

• Korean Journal of Environment and Ecology
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• v.38 no.1
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• pp.108-120
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• 2024

This study proposes measures for institutionalization and its inter-departmental linkages to increase the effectiveness of wind corridor forests in response to changing urban environmental issues and climate change. For this purpose, the study reviewed laws and regulations containing terms related to urban wind corridors, identified the roles and relationships of wind corridor forests required in relevant plans, and assessed high-level and basic plans for wind corridor forests to identify issues in the current establishment of wind corridor forests and derive key issues related to them. Based on these results, institutionalization measures for legislating wind corridor forests and their effectiveness methods were suggested. This study proposes 1) defining terms and establishing legal and institutional foundations and 2) establishing hierarchies with related plans and a legal basis for the basic plan for wind corridor forest as an institutional plan for legalization of wind corridor forest, and 1) establishing a legal and institutional foundation for constructing spatial data like analysis maps and 2) establishing the guidelines for the basic plan and for creating and managing wind corridor forests and their contents as an institutional plan for effective revitalization. It is expected that this study can be utilized as basic data for establishing laws and regulations related to wind corridor forests and can contribute to the institutionalization research of basic plans. It is also hoped to be used as basic data for systematically constructing wind corridor forests.

• Korean Journal of Environment and Ecology
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• v.38 no.2
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• pp.178-188
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• 2024

The dynamics of suspended sediment (SS) in forested catchments vary depending upon human or natural disturbances, including land use change, forestry activity, forest fires, and landslides. Understanding the dynamics of SS originating from the potential sources within a forested catchment is crucial for establishing an effective water quality management strategy. Therefore, to suggest a systematic method for interpreting SS dynamics, we evaluated the performance and applicability of ten methods for calculating the hysteresis index based on observed hydrological data and two calculation models (Lawler's method and Lloyd's method) with five sampling intervals (50th, 25th, 10th, 5th, and 1st percentiles). Our results showed that Lloyd's method, which used a sampling interval at the 1st percentile, had the largest number of analyzable runoff events and exhibited the best performance. The results of this study can contribute to quantifying the hysteresis in the relationship between discharge and SS and provide useful information for interpreting SS dynamics.

• Information Systems Review
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• v.22 no.4
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• pp.21-39
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• 2020

Recently, deep learning has shown high performance in various applications such as pattern analysis and image classification. Especially known as a difficult task in the field of machine learning research, stock market forecasting is an area where the effectiveness of deep learning techniques is being verified by many researchers. This study proposed a deep learning Convolutional Neural Network (CNN) model to predict the direction of stock prices. We then used the feature selection method to improve the performance of the model. We compared the performance of machine learning classifiers against CNN. The classifiers used in this study are as follows: Logistic Regression, Decision Tree, Neural Network, Support Vector Machine, Adaboost, Bagging, and Random Forest. The results of this study confirmed that the CNN showed higher performancecompared with other classifiers in the case of feature selection. The results show that the CNN model effectively predicted the stock price direction by analyzing the embedded values of the financial data

• Journal of the Korean Society of Radiology
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• v.18 no.2
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• pp.171-177
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• 2024

In this study, two general X-ray device, CT, and MRI inspection devices were selected from general hospitals in the Daejeon area and an experiment was conducted to predict the level of infection by measuring the surface contamination of the inspection devices at different times and to use it as basic data for infection prevention. As a result, the surface contamination level by time zone for general X-ray devices and MRI examination devices was in the order of 13H > 8H > 16H, and for CT examination devices, it was 13H > 16H > 8H, which appeared to be influenced by the number of tests. In addition, the surface contamination results for each part of the test device showed that the highest ATP contamination value was found on the stand bucky handle for the general X-ray device, the headrest for the CT examination device, and the operation switch for the MRI examination device, which was closely related to the number of contacts. As a result of comparing before and after disinfection, all devices showed a significant decrease after disinfection. Based on the results of the experiment, it is believed that it can be used as basic data to identify the level of contamination in radiology laboratories and prevent infectious diseases.

• Information Systems Review
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• v.22 no.4
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• pp.185-203
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• 2020

With the advent of 4th industrial revolution, the manufacturing industry is converging with ICT and changing into the era of smart manufacturing. In the smart factory, all machines and facilities are connected based on ICT, and thus security should be further strengthened as it is exposed to complex security threats that were not previously recognized. To reduce the risk of security incidents and successfully implement smart factories, it is necessary to identify key security factors to be applied, taking into account the characteristics of the industrial environment of smart factories utilizing ICT. In this study, we propose a 'hierarchical classification model of security factors in smart factory' that includes terminal, network, platform/service categories and analyze the importance of security factors to be applied when developing smart factories. We conducted an assessment of importance of security factors to the groups of smart factories and security experts. In this study, the relative importance of security factors of smart factory was derived by using AHP technique, and the priority among the security factors is presented. Based on the results of this research, it contributes to building the smart factory more securely and establishing information security required in the era of smart manufacturing.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.2
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• pp.1-11
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• 2024

In the midst of the current turbulent global economy, traditional investment metrics are undergoing a metamorphosis, signaling the onset of what's often referred to as an "Investment cold season". Early-stage startups, despite their boundless potential, grapple with immediate revenue constraints, intensifying their pursuit of critical investments. While financial indicators once took center stage in investment evaluations, a notable paradigm shift is underway. Organizational culture, once relegated to the sidelines, has now emerged as a linchpin in forecasting a startup's resilience and enduring trajectory. Our comprehensive research, integrating insights from CVF and OCAI, unveils the intricate relationship between organizational culture and its magnetic appeal to investors. The results indicate that startups with a pronounced external focus, expertly balanced with flexibility and stability, hold particular allure for investment consideration. Furthermore, the study underscores the pivotal role of adhocracy and market-driven mindsets in shaping investment desirability. A significant observation emerges from the study: startups, whether they secured investment or failed to do so, consistently display strong clan culture, highlighting the widespread importance of nurturing a positive employee environment. Leadership deeply anchored in market culture, combined with an unwavering commitment to innovation and harmonious organizational practices, emerges as a potent recipe for attracting investor attention. Our model, with an impressive 88.3% predictive accuracy, serves as a guiding light for startups and astute investors, illuminating the intricate interplay of culture and investment success in today's economic landscape.

• Information Systems Review
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• v.22 no.2
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• pp.25-41
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• 2020

Along with the expectation about 5G network commercialization, interests in realistic and immersive media industries such as virtual reality (VR) are increasing. However, most of studies on VR still focus on video technologies instead of factors for popularity and consumption. Thus, the main objective of this research is to identify meaningful factors, which affect the view counts of VR videos and to provide business implications of the content strategies for VR video creators and service providers. Using a regression analysis with 700 VR videos, this study tries to find major factors that affect the view counts of VR videos. As a result, user assessment factors such as number of likes and sicknesses have a strong influence on the view counts. In addition, the result shows that both general information factors (video length and age) and content characteristic factors (series, one source multi use (OSMU), and category) are all influential factors. The findings suggest that it is necessary to support recommendation and curation based on user assessments for increasing popularity and diffusion of VR video streaming.

• Industry Promotion Research
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• v.9 no.2
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• pp.95-102
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• 2024

This study aims to compare the role of the public sector in the U.S. and Korean medical security systems and study response measures in the social risk situation of the COVID-19 virus. The COVID-19 pandemic was a typical case of a 'disaster' that spread across the world across borders in a short period of time and caused serious social welfare losses by increasing the annual number of deaths by approximately 4% in 2020. Threats to health security, such as changes in social order, unpredictable endings, prolonged control of daily life, and deepening inequality, affected the economy, politics, and environment as a whole, and people had to experience anxiety and confusion due to mental and physical stress. Furthermore, developed countries failed to provide help to low-income countries in the face of global disasters. In this situation, the country's disaster management capacity to minimize harm and secure resilience, especially disaster response capacity in the health and medical field, is inevitably very important. Therefore, this study compares how the health insurance system, which is a system to guarantee citizens' right to life, differs from the United States, a liberal health care country, and raises the need to strengthen the role of the public sector.