Desertification has been expanding with a remarkable speed across the Northeast Asia. Desertification in Northeast Asia significantly influences Korea's economy and environmental health conditions in recent years. For these reasons, a number of non-governmental organizations (NGOs) in Korea have carried out the reforestation projects to combat desertification in China and Mongolia. Several tree plantation projects were implemented in Mongolia and China. The objective of this study was to analyze and evaluate the performance of tree plantation aid projects carried out by Korean NGOs in Mongolia. The performance of tree plantation projects was examined through effectiveness, efficiency, equity and responsiveness of those projects. The performance was analyzed with the survival rate of planted trees and planting cost, the recognitions of Mongolian people. The analysis of the performance showed that the tree plantation cooperation projects carried out by Korean NGOs in Mongolia had comparatively high performance from a larger point of view. Especially, effectiveness and responsiveness of their projects were highly marked in spite of all the difficulties of carrying out the tree plantation. Such a high effectiveness represented the relatively higher survival rates of trees and Mongolian's positive recognition of plantation projects. Furthermore, the responsiveness also turned out to be high with a great satisfaction of the Mongolian people for plantation projects conducted by the Korean NGOs. Survey results indicated that the efficiency and equity of the projects would be increased by promoting the cooperation projects for tree planting throughout Mongolia with reinforcing infrastructures. By comparison between Korean NGOs and Mongolian Government plantation projects, confirmed the importance of sustained financial support and maintenance activities in the plantation sites.
Recently, fake news has attracted worldwide attentions regardless of the fields. The Hyundai Research Institute estimated that the amount of fake news damage reached about 30.9 trillion won per year. The government is making efforts to develop artificial intelligence source technology to detect fake news such as holding "artificial intelligence R&D challenge" competition on the title of "searching for fake news." Fact checking services are also being provided in various private sector fields. Nevertheless, in academic fields, there are also many attempts have been conducted in detecting the fake news. Typically, there are different attempts in detecting fake news such as expert-based, collective intelligence-based, artificial intelligence-based, and semantic-based. However, the more accurate the fake news manipulation is, the more difficult it is to identify the authenticity of the news by analyzing the news itself. Furthermore, the accuracy of most fake news detection models tends to be overestimated. Therefore, in this study, we first propose a method to secure the fairness of false news detection model accuracy. Secondly, we propose a method to identify the authenticity of the news using the social data broadly generated by the reaction to the news as well as the contents of the news.
This paper is an empirical analysis as a reference model that can predict up to the maximum number of elementary school student care needs in local governments across the country. This study analyzed and predicted the characteristics of the region based on machine learning to predict the demand for elementary care in a new apartment complex. For this purpose, a total of 292 variables were used, including data related to apartment structure, such as number of parking spaces per household, and building-to-land ratio, environmental data around apartments such as distance to elementary schools, and population data of administrative districts. The use of various variables is of great significance, and it is meaningful in complex analysis. It is also an empirical case study that increased the reliability of the model through comparison with the actual value of the basic local government.
As the global market environment changes, the domestic ICT industry has a growing influence on the world economy. This industry is regarded as an important driving force in the national economy from a technological and social point of view. In particular, small and medium-sized enterprises (SMEs) in the ICT industry are regarded as essential actors of domestic economic development in terms of company diversity, technology development and job creation. However, since it is small compared to large-sized enterprises, it is difficult for SMEs to survive with a differentiated strategy in an incomplete and rapidly changing environment. Therefore, SMEs must make a lot of efforts to improve their own capabilities, and the government needs to provide the desirable help suitable for corporate internal resources so that they can continue to be competitive. This study classifies the types of ICT SMEs participating in government support programs, and analyzes the relationship between resources and performance creation of each type. The data from the "ICT Small and Medium Enterprises Survey" conducted annually by the Ministry of Science and ICT was used. In the first stage, ICT SMEs were clustered based on common factors according to their experiences with government support programs. Three clusters were meaningfully classified, and each cluster was named "active participation type," "initial support type," and "soloist type." As a second step, this study compared the characteristics of each cluster through profiling analysis for each cluster. The third step carried out in this study was to find out the mechanism of R&D performance creation for each cluster through regression analysis. Different factors affected performance creation for each cluster, and the magnitude of the influence was also different. Specifically, for "active participation type", "current manpower", "technology competitiveness", and "R&D investment in the previous year" were found to be important factors in creating R&D performance. "Initial support type" was identified as "whether or not a dedicated R&D organization exists", "R&D investment amount in the previous year", "Ratio of sales to large companies", and "Ratio of vendors supplied to large companies" contributed to the performance. Lastly, in the case of "soloist type", "current workforce" and "future recruitment plan", "technological competitiveness", "R&D investment", "large company sales ratio", and "overseas sales ratio" showed a significant relationship with the performance. This study has practical implications of showing what strategy should be established when supporting SMEs in the future according to the government's participation in the startup program and providing a guide on what kind of support should be provided.
This study stereotyped the media on the basis of ideological inclinations and media types and explored the news coverage through word analysis, network analysis, and frame analysis. There was no difference between conservative media and progressive media in terms of the amount of news. The conservative mainstream media considered the THAAD rumor as an unnecessary misunderstanding and a rumor based conflict of the south-south. The progressive mainstream media mentioned much about Hwang Gyoan, external influences, and lies and highlighted the government's opinion that there was external influence that spread a vicious rumor. Conservative media mentioned on the bringing about social disturbance and in case of progressive media mentioned social disturbance, and progressive media mentioned the responsibility of government and the attitude of conservative media about the diffusion of the rumor. In conclusion the press framed the THAAD rumor on the basis of their ideological inclinations instead of the role of journalist.
Since 2020, the GuangXi government of China has focused on the deep integration of tea industry with leisure and cultural tourism, popular science education, health care and elderly care industries. Among the output value targets of the tertiary industry, the GuangXi government plans to achieve 25 billion yuan, and the tea industry is developing rapidly. Through questionnaire survey, field research and interview, this paper studies the differences of demand behavior and selection attributes of tea products among consumers in different years, and finally studies the evolution pattern of service mode of tea industry in GuangXi. The results show that there are obvious differences in life and work style, shopping habits, service design, user experience, social needs and personality needs of each generation consumers in different years. Based on the analysis of demand and behavior habits of tea products, the evolution pattern of service mode of tea industry in GuangXi is studied. Based on the above results, according to the differences of consumers' choice of tea products in different years, the service mode of tea industry in GuangXi is improved The development of tea industry in service design, user experience level is worthy of in-depth attention.
Smart rural construction is an important direction for the Chinese government to promote the cause of "Rural Revitalization". In this paper, in the Xikou village project of the "future community" smart rural demonstration development project proposed by the local government of Zhejiang Province, China, the researcher participated in the design of the intellectualization of the smart rural life circle from the perspective of UX design and through qualitative and quantitative research methods. Through field investigation, understand the users' needs for intelligent design of smart countryside, and on this basis, design the maximum space of the region as a cognitive smart rural demonstration park, and quantitatively analyze the user experience feedback after the completion of the project. Before and after the actual design and application of the "Xikou village" in the demonstration area, chapters 3 and 4 are the symbols that can remember the rural era, the Rural Cultural Exchange Square. In the intelligent office space and living space, the user needs are composed of the design results. In order to reduce the anxiety of residents and tourists caused by the intelligent environment, the artificial manual service part is also designed. Now, as a case of intelligent rural space design, resident residence is developing continuously.
Asia-Pacific Journal of Business Venturing and Entrepreneurship
/
v.16
no.6
/
pp.43-55
/
2021
Recently, as the domestic job problem has become serious, government ministries are investing a lot of budgets to encourage startups by prospective entrepreneurs. What is important to the success of startups is the recognition of various startup opportunities before starting a startup, and the experience through trial. However, in reality, prospective entrepreneurs recognize and seek various startup opportunities through support such as startup education and initial commercialization funds through various government supported projects, but it is difficult to actually start a business. Previous studies have revealed that the recognition of entrepreneurial opportunities affects entrepreneurial intentions by various variables such as gender, but research is insufficient on what kind of black box exists between the recognition of entrepreneurial opportunities and entrepreneurial intentions. The purpose of this study is to emphasize the importance of positive psychological capital as a major method for improving the entrepreneurial intention, and to analyze exploratorily whether positive psychological capital plays a mediating role between the recognition of entrepreneurial opportunities and the entrepreneurial intention. As a result of the study, it was confirmed that the recognition of startup opportunities affects the intention to start a business, and positive psychological capital has a mediating effect between the recognition of the startup opportunity and the intention to start a business. This means that positive psychological capital is important in order to lead to actual entrepreneurial intentions after recognizing a startup opportunity. Therefore, in order to revitalize the startups of prospective entrepreneurs in the current startup ecosystem, it is necessary to prepare a plan to improve the recognition of startup opportunities and positive psychological capital.
Transactions of the Korean Society of Mechanical Engineers B
/
v.38
no.9
/
pp.721-729
/
2014
A hybrid desiccant cooling system (HDCS) that uses a heat pump driven by district heating instead of a sensible rotor can provide an increased energy efficiency in summer. In this paper, the summer operation costs and initial costs of both the HDCS and traditional systems are analyzed using annual equal payments, and national benefits are found from using the HDCS instead of traditional systems. In the analysis results, the HDCS reduces the operation cost by 30 compared to the traditional systems, and each HDCS unit has 0.079 TOE per year of primary energy savings and 0.835 $TCO_2$ per year of $CO_2$ emission reduction more than the traditional systems. If HDCSs were to be installed in 680,000 households by 2020, this would produce a replacement power effect of 463 MW. Despite this savings effect, HDCSs require a government subsidy before they can be supplied because the initial cost is higher than that of traditional systems. Thus, this paper calculates suitable subsidies and suggests a supply method for HDCSs considering the national benefits.
The entire tourism industry is being hit hard by the COVID-19 as a global pandemic. Accommodation sharing services such as Airbnb, which have recently expanded due to the spread of the sharing economy, are particularly affected by the pandemic because transactions are made based on trust and communication between consumer and supplier. As the pandemic situation changes individuals' perceptions and behavior of travel, strategies for the recovery of the tourism industry have been discussed. However, since most studies present macro strategies in terms of traditional lodging providers and the government, there is a significant lack of discussion on differentiated pandemic response strategies considering the peculiarity of the sharing economy centered on peer-to-peer transactions. This study discusses the marketing strategy for individual hosts of Airbnb during COVID-19. We empirically analyze the effect of changes in listing descriptions posted by the Airbnb hosts on listing performance after COVID-19 was outbroken. We extract nine aspects described in the listing descriptions using the Attention-Based Aspect Extraction model, which is a deep learning-based aspect extraction method. We model the effect of aspect changes on listing performance after the COVID-19 by observing the frequency of each aspect appeared in the text. In addition, we compare those effects across the types of Airbnb listing. Through this, this study presents an idea for a pandemic crisis response strategy that individual service providers of accommodation sharing services can take depending on the listing type.
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