• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.505-505
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• 2022

This study shows the first output of the three-year project (2021-2023) to develop a Smart Water City (SWC) Global Standard and Certification Scheme ley by K-water, International Water Resources Association (IWRA) and Asia Water Council (AWC). There are three major parts in the first year. In Part 1, it investigates the essential features of cities today and details the water challenges currently faced and likely to be confronted in the future. It also investigates the functions that water fulfills in the urban environment, and how ICTs can contribute to improving those functions by each Urban Water Cycle. A definition of a Smart Water City is proposed following a discussion on the meaning of "smart development". This part of the report also presents different city cases from countries around the world to illustrate the urban water challenges and the technological and non-technological solutions that cities have put in place, including national and/or local policies and strategies. In Part 2, it defines what global standards indicators and certification schemes are and identifies their characteristics. Especially, it analyses in detail eight relevant standards and certification schemes measuring sustainable development and/or water resources management in urban settings. Standards elaborated by international organizations are distinguished from those developed by the private sector, non-governmental organizations, and by academia. Finally, this study suggests the right direction to develop SWC global standard frameworks and certification schemes. And then, it shows the main tasks for the Stage 2 (second year) project. Basically, the framework for a future SWC standard (consisting three main pillars: Technical, Governance and Prospective pillars) will be fully defined in Stage 2.

• Journal of the Korean Association of Geographic Information Studies
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• v.27 no.1
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• pp.52-66
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• 2024

The purpose of this study is to identify the spatial system and characteristics of the urban center by deriving the boundaries of the urban center set in the urban basic plan for Busan Metropolitan City and diagnosing the role and status of the center. To this end, four indicators representing the characteristics of the center were selected through a review of previous studies, and the boundaries of the center were derived using spatial statistical techniques with strengths in geographical boundary analysis. Then, using the indicators of center characteristics and population potential functions, we diagnosed the influence and potential of each center in the spatial structure of Busan Metropolitan City. The analysis showed that the scale of the centers varies greatly, and the unutilized areas where commercial areas are not activated and the expansion areas that spread beyond commercial areas to residential and industrial areas are different for each urban center. The results of the potential measurement, which indicates the attractiveness of the center, also showed areas with strong and weak population potential. Therefore, systematic management and strategies based on the hierarchical characteristics and influence measurement results are needed to strengthen the function of urban centers. The results analyzed in this study can be used as a resource for responding to various urban planning needs and policy changes in the future, along with station area development plans and spatial innovation zones for building a sustainable urban growth system, balanced development, and strengthening the function of centers.

• Journal of Agricultural Extension & Community Development
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• v.21 no.4
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• pp.1191-1226
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• 2014

The purpose of this study is to develop the evaluation criteria for the maintenance preserve of agriculture and rural heritage. The major steps for this study are 1) drafting the evaluation criteria for maintenance preservation of agriculture and rural heritage 2) verifying the evaluation criteria, and 3) determining the weighting values of the confirmed evaluation criteria. First, to derive the evaluation criteria for maintenance preservation of agriculture and rural heritage, the researcher reviewed the literature on the evaluation of agriculture and rural heritage, including research on the indexes of agriculture and rural heritage, the degree of the maintain preservation of heritage. A total of 31 evaluation criteria were selected. Second, to verify the selected 5 evaluation items and 31 evaluation indexes, the Delphi Method was implemented. Using traditional 3-step Delphi Method consisting of close-ended forms, with a panel of 41 experts, the researchers verified 5 evaluation items 31 evaluation indexes, two for each evaluation area validity. The confirmed evaluation areas are 5 items of management plan, management support system, surroundings of heritage, local network, heritage utilization and 31 criteria were preservation maintenance, performance plan, resident community composition, monitoring, act of parliament fulfillment, ecosystem management, landscape harmony, restoration and transmission plan and enhancement of residents' capability, etc. in the order. Through maintenance preservation evaluation index of agriculture and rural heritage, it can be utilized as sustainable development of plural resources.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.131-138
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• 2020

In accordance with huge demand for capital to meet the expansion of steel production, there are more and more steel companies who have officially listed their stocks in HOSE and HNX. One of the key issues in successful initial public offerings and seasonal offerings for these companies is how to make stocks of steel companies become more attractive in the eyes of investors. The purpose of this research is to analyze the determinants of share prices of listed steel companies in Vietnam. This study utilized macro-economic variables, ratios and indicators representing characteristics of steel industry collected from Quarter 1/2006 to Quarter 4/2019 in association with the panel data and the feasible generalized least square (FGLS) model to evaluate the degree of these factors on the share prices. The results of the research show that ROE, Cons_rate, and CO2_rate are three main factors affecting the share prices of listed steel companies. Among which, ROE and Cons_rate have a positive effect, while CO2_rate has a negative effect on the share prices of listed steel companies. It also confirms the relationship between the environmental factor, construction industry factor and the stock prices. This lays foundations for recommendations for the future policies towards environmental protection and sustainable development.

• Journal of Environmental Impact Assessment
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• v.13 no.6
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• pp.295-305
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• 2004

After the Rio declaration on environment and development in 1992, developed countries are undertaking "environmentally sustainable transportation (EST)" projects. To meet the needs for EST, current transportation policies in Korea are rapidly reforming and one of its concerns is modernizing and upgrading railway freight system. Planning new railroad construction projects is increasing and subsequent environmental impact assessment (EIA) demands improvements, especially in both the EIA and decision making systems. In this paper, we discuss the present status of EIA for railroad construction projects, especially, by analyzing the EIA documents for the last six years. The EIA for railroad construction projects accounts for only 4.9% of total 918 project EIAs during 1998-2003, and the portion is gradually increasing. Major environmental concerns for EIA in railroad construction projects were geomorphological and ecological changes, protection of rare organisms, air pollution, water pollution, waste management, and noise, etc. We compared characteristics of environmental impacts of railroad construction with those of vehicle road construction, based on environmental and construction-planning indicators appeared in Environmental Impact Statements. Railroad construction usually requires longer tunnels and bridges for a given length than those for vehicle road construction. In addition, the amounts of geomorphological and ecological changes (road-cutting, embankment, devegetation, etc.) in railroad construction were generally less than 50% of those in vehicle road construction. To develop environmentally friendly railway systems, monitoring studies for environmental impacts of railroads such as habitat fragmentation and road kills, dispersal of alien plants, tunnelling effects on groundwater and vegetation, and noise impacts are highly recommended.

• Asia-Pacific Journal of Business
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• v.13 no.1
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• pp.153-166
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• 2022

Purpose - ESG(Environmental, Social and Governance) rating is an indicator to predict the sustainable development and long-term value creation of enterprises, which is becoming more and more important. This study divided the ESG rating into each sector(E, S and G) to identify which ESG elements are effective in enhancing enterprise value according to the characteristics of the enterprise, which is different from previous studies. Design/methodology/approach - In this study, Bloomberg ESG Disclosure Score was used to empirically analyze the relationship between ESG ratings and corporate value by taking the listed companies of China's Shanghai Composite Index from 2017 to 2020 as the object. Findings - First, the relationship between ESG ratings and enterprise value shows a statistically significant positive correlation, which supports the results of previous studies. Second, the analysis results from the classification of ownership structure of enterprises (state-owned enterprises and non-state-owned enterprises) show that compared with state-owned enterprises, the ESG ratings of non-state-owned enterprises is more closely related to enterprise value. Third, the analysis of various industries (manufacturing and non-manufacturing) shows that compared with manufacturing, ESG scores of non-manufacturing has a more positive effect on enterprise value. Lastly, the analysis by industry type (heavy-contaminated companies, non-contaminated companies) confirmed that ESG scores of non-contaminated companies has a positive effect on corporate value than heavy-contaminated companies. Research implications or Originality - This study classified ESG evaluation grades(E, S and G) for listed companies in China and analyzed in detail how they affect corporate value according to corporate characteristics, drawing implications for what ESG indicators should be focused on to increase corporate value.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.21-28
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• 2022

The increase in the number of large cities and the size of their population sharpens attention to the new role of cities as entities to ensure a high-quality, safe and modern life of citizens, which has become significantly more active in recent years. The rapid spread of smart cities in the modern world has actualized the issue of analyzing their success and assessing the role of various factors in this. Every success of a smart city is always the result of a unique combination of the most modern technologies, environmental and social initiatives, skillful and consistent management, as well as available human potential. The purpose of the article is to analyze the success factors of smart cities based on the generalization of the results of the most famous ratings. In order to identify the impact of various factors, primarily intellectual, on the success and leadership positions of smart cities, the following ratings were consistently analyzed: Smart City Index (SCI), City in Motion Index (CIMI), Global Power City Index (GPCI), Global Cities Index (GCI), Global Cities Outlook (GCO). They have a different list of indicators and main pillars (dimensions), but all ratings take into account aspects such as: governance, ICT, mobility, functionality, human capital, etc. The highest correlation coefficient, that is, the strongest linear relationship of the CIMI index was found with such factors as: Human capital, Economy, Governance and Technologies. Summarizing the results of the TOP 20 smart cities according to different ratings allowed us to confirm that the list of leaders is very similar in all ratings. Among those cities that are in the TOP-20 in all five indexes are: London, Sydney and Singapore. There are four indices: New York, Paris, Tokyo, Copenhagen, Berlin, Amsterdam, Melbourne. Achieving leadership positions in smart city rankings is always the result of a combination and synergy of certain factors, and first of all, it is the quality of human capital. The intensity and success of the use of information and communication technologies in locality management processes, city planning and improvement of the city's living conditions depend on it.

• Journal of the Korea Society of Computer and Information
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• v.29 no.5
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• pp.155-164
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• 2024

This study proposes an unsupervised learning-based clustering model to estimate the ESG ratings of domestic public institutions. To achieve this, the optimal number of clusters was determined by comparing spectral clustering and k-means clustering. These results are guaranteed by calculating the Davies-Bouldin Index (DBI), a model performance index. The DBI values were 0.734 for spectral clustering and 1.715 for k-means clustering, indicating lower values showed better performance. Thus, the superiority of spectral clustering was confirmed. Furthermore, T-test and ANOVA were used to reveal statistically significant differences between ESG non-financial data, and correlation coefficients were used to confirm the relationships between ESG indicators. Based on these results, this study suggests the possibility of estimating the ESG performance ranking of each public institution without existing ESG ratings. This is achieved by calculating the optimal number of clusters, and then determining the sum of averages of the ESG data within each cluster. Therefore, the proposed model can be employed to evaluate the ESG ratings of various domestic public institutions, and it is expected to be useful in domestic sustainable management practice and performance management.

• The Journal of Engineering Geology
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• v.34 no.1
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• pp.107-115
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• 2024

This study assesses forest fire susceptibility in Gangwon-do, South Korea, which hosts the largest forested area in the nation and constitutes ~21% of the country's forested land. With 81% of its terrain forested, Gangwon-do is particularly susceptible to wildfires, as evidenced by the fact that seven out of the ten most extensive wildfires in Korea have occurred in this region, with significant ecological and economic implications. Here, we analyze 480 historical wildfire occurrences in Gangwon-do between 2003 and 2019 using 17 predictor variables of wildfire occurrence. We utilized three machine learning algorithms—random forest, logistic regression, and support vector machine—to construct wildfire susceptibility prediction models and identify the best-performing model for Gangwon-do. Forest and soil map data were integrated as important indicators of wildfire susceptibility and enhanced the precision of the three models in identifying areas at high risk of wildfires. Of the three models examined, the random forest model showed the best predictive performance, with an area-under-the-curve value of 0.936. The findings of this study, especially the maps generated by the models, are expected to offer important guidance to local governments in formulating effective management and conservation strategies. These strategies aim to ensure the sustainable preservation of forest resources and to enhance the well-being of communities situated in areas adjacent to forests. Furthermore, the outcomes of this study are anticipated to contribute to the safeguarding of forest resources and biodiversity and to the development of comprehensive plans for forest resource protection, biodiversity conservation, and environmental management.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.12
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• pp.3218-3241
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• 2023

Financial fraud undermines the sustainable development of financial markets. Financial statements can be regarded as the key source of information to obtain the operating conditions of listed companies. Current research focuses more on mining financial digital data instead of looking into text data. However, text data can reveal emotional information, which is an important basis for detecting financial fraud. The audit opinion of the financial statement is especially the fair opinion of a certified public accountant on the quality of enterprise financial reports. Therefore, this research was carried out by using the data features of 4,153 listed companies' financial annual reports and audits of text opinions in the past six years, and the paper puts forward a financial fraud detection model integrating audit opinions. First, the financial data index database and audit opinion text database were built. Second, digitized audit opinions with deep learning Bert model was employed. Finally, both the extracted audit numerical characteristics and the financial numerical indicators were used as the training data of the LightGBM model. What is worth paying attention to is that the imbalanced distribution of sample labels is also one of the focuses of financial fraud research. To solve this problem, data enhancement and Focal Loss feature learning functions were used in data processing and model training respectively. The experimental results show that compared with the conventional financial fraud detection model, the performance of the proposed model is improved greatly, with Area Under the Curve (AUC) and Accuracy reaching 81.42% and 78.15%, respectively.