• Title/Summary/Keyword: social investment returns

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The Effect of Real Estate Investment Factors in Investors of Sejong City on Investment Performance and Reinvestment Intention (세종시 투자자의 투자요인이 투자성과와 재투자의향에 미치는 영향)

  • Tae-Bock Park;Jaeho Chung
    • Land and Housing Review
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    • v.14 no.4
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    • pp.63-76
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    • 2023
  • Investors should understand and actively consider factors like location, future value, policies, pricing, market trends, and their income, as these elements can shift with changing local, social, economic, and policy environments. This study seeks to clarify the impact of investment factors on the performance and reinvestment intentions of Sejong City investors by surveying those who have invested in real estate. This study employs a structural equation model with confirmatory factor analysis, focusing on four aspects: value, economic and policy, psychological, and financial. We find that the investment value factor has the largest impact on investment performance, indicating that investors prioritize the investment value of real estate in Sejong City. In addition, factors increasing asset value and expected satisfaction were significant, indicating that real estate investment in Sejong City yields high returns and investor satisfaction. with a positive outlook for future reinvestment.

The research regarding the community residential welfare facilities for the Aged - Focused on instance of the United States - (지역사회 노인주거시설에 관한 연구 - 미국을 중심으로 -)

  • Cho, Cheol-Ho
    • Korean Institute of Interior Design Journal
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    • v.19 no.2
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    • pp.225-233
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    • 2010
  • At this point in time South Korea is rapidly metastasizing to a aging society. A major cause of aging can be summarized as increased life expectancy, decrease of nuclear family and birthrate, and South Korea's progress is faster than any other country. From the 1970s, western society has changed social welfare to deinstitutionalization and community care because of problems about economic reason and facilities protection, so the type of elderly social service has also changed from the facility welfare service which is accommodated old people in certain facility to community welfare service which provides various welfare services with living together. Public facilities for low income group which are supported by government are lower, 6.6%, than the United States or Japan, 50%. They are divided into private manage facilities and subscription elderly facilities. These subscription elderly residential facilities show poor administration because of focusing on development and market analysis for investment returns. Therefore, in order to vitalize the elderly welfare residential facilities in Korea, we need plans about systematic services facilities for welfare and phased medical treatments. Therefore, the purpose of this study is that (1) the types and functions of residents for community elderly residential facilities in elderly welfare policies of U.S., and supported policies are researched as a transcendental model, (2) data about operating system with the principles of the market is analyzed, and (3) basic data about welfare facility plan for community residential elderly people is provided.

Responsibility Accounting in Public Universities: A Case in Vietnam

  • LE, Oanh Thi Tu;BUI, Ngoc Thi
    • The Journal of Asian Finance, Economics and Business
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    • v.7 no.7
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    • pp.169-178
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    • 2020
  • This study examines the current situation of responsibility accounting and proposed management solutions according to responsibility centers on public universities in Vietnam. The study applies quantitative research methods, and collected data through structured questionnaires to 138 public universities in Vietnam in 2019, receiving back 55 valid questionnaires. The data was cleaned and analyzed with SPSS software. The results show that most public universities in Vietnam assigned management responsibility to their departments, but responsibility accounting was not comprehensive since many universities are not financially autonomous. The Kruskal Wallis Test was conducted to compare the current situation of responsibility accounting among universities by the degree of autonomy and by geographic area. The research found out that totally autonomous universities assigned management responsibility to responsibility centers better than semi-autonomous and non-autonomous universities did. Regarding the evaluation of management responsibility, universities in Central Vietnam rated specific quantitative criteria, residual income (RI) and returns on investment (ROI) higher than universities in the North and the South of Vietnam did. However, universities in the South of Vietnam rated the evaluation of profits by department higher than the rest. The study also suggests structure for establishing responsibility centers in accordance with public universities in Vietnam.

Comparison of Models for Stock Price Prediction Based on Keyword Search Volume According to the Social Acceptance of Artificial Intelligence (인공지능의 사회적 수용도에 따른 키워드 검색량 기반 주가예측모형 비교연구)

  • Cho, Yujung;Sohn, Kwonsang;Kwon, Ohbyung
    • Journal of Intelligence and Information Systems
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    • v.27 no.1
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    • pp.103-128
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    • 2021
  • Recently, investors' interest and the influence of stock-related information dissemination are being considered as significant factors that explain stock returns and volume. Besides, companies that develop, distribute, or utilize innovative new technologies such as artificial intelligence have a problem that it is difficult to accurately predict a company's future stock returns and volatility due to macro-environment and market uncertainty. Market uncertainty is recognized as an obstacle to the activation and spread of artificial intelligence technology, so research is needed to mitigate this. Hence, the purpose of this study is to propose a machine learning model that predicts the volatility of a company's stock price by using the internet search volume of artificial intelligence-related technology keywords as a measure of the interest of investors. To this end, for predicting the stock market, we using the VAR(Vector Auto Regression) and deep neural network LSTM (Long Short-Term Memory). And the stock price prediction performance using keyword search volume is compared according to the technology's social acceptance stage. In addition, we also conduct the analysis of sub-technology of artificial intelligence technology to examine the change in the search volume of detailed technology keywords according to the technology acceptance stage and the effect of interest in specific technology on the stock market forecast. To this end, in this study, the words artificial intelligence, deep learning, machine learning were selected as keywords. Next, we investigated how many keywords each week appeared in online documents for five years from January 1, 2015, to December 31, 2019. The stock price and transaction volume data of KOSDAQ listed companies were also collected and used for analysis. As a result, we found that the keyword search volume for artificial intelligence technology increased as the social acceptance of artificial intelligence technology increased. In particular, starting from AlphaGo Shock, the keyword search volume for artificial intelligence itself and detailed technologies such as machine learning and deep learning appeared to increase. Also, the keyword search volume for artificial intelligence technology increases as the social acceptance stage progresses. It showed high accuracy, and it was confirmed that the acceptance stages showing the best prediction performance were different for each keyword. As a result of stock price prediction based on keyword search volume for each social acceptance stage of artificial intelligence technologies classified in this study, the awareness stage's prediction accuracy was found to be the highest. The prediction accuracy was different according to the keywords used in the stock price prediction model for each social acceptance stage. Therefore, when constructing a stock price prediction model using technology keywords, it is necessary to consider social acceptance of the technology and sub-technology classification. The results of this study provide the following implications. First, to predict the return on investment for companies based on innovative technology, it is most important to capture the recognition stage in which public interest rapidly increases in social acceptance of the technology. Second, the change in keyword search volume and the accuracy of the prediction model varies according to the social acceptance of technology should be considered in developing a Decision Support System for investment such as the big data-based Robo-advisor recently introduced by the financial sector.

Determinants of Credit Default Swap Spreads: The Case of Korean Firms (한국 기업들의 신용부도스왑 스프레드에 대한 결정요인 분석)

  • Park, Yoon-S.;Kim, Han-Joon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.12 no.10
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    • pp.4359-4368
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    • 2011
  • Among several macroeconomic missteps blamed for the recent global financial crisis including the social problems of income distribution and the lack of proper financial remedies, two of them have received particular attention: the global BOP(Balance of Payment) imbalance and the misguided monetary policy. Such BOP imbalance was blamed for massive foreign exchange investment flows from Asia into the U.S., triggering the financial and real estate bubble in America. The latter refers to the excessively loose monetary policy of the U.S. Federal Reserve, which pushed financial institutions and households into reckless investment behavior in search of higher returns. Given the abuse of certain innovative financial techniques and new investment instruments that have been created in recent decades, both collateralized debt obligations (CDOs) and credit default swaps (CDS) enjoyed a symbiotic and toxic relationship prior to the financial crisis This paper is organized as follows: The first section analyzes the real causes of the recent financial crisis. The second details the role of CDOs and CDS. Then, to identify key determinants of the CDS spreads in an emerging capital market, the sample data of major Korean firms' CDS spreads are used to estimate the risk premium by utilizing the multiple regression analysis. The empirical test result indicates that Korean 3-year treasury bond rate(TYIELD), market to book value ratio(MV/BV), and assets size(INASSETS) are shown to demonstrate statistically significant influences on the changes of the CDS premium for sample firms.

Financial Performance of M&A: Focusing on E-commerce Companies in China (M&A 기업성과: 중국 전자상거래 기업을 중심으로)

  • Zhang, Cong;Jin, Shanyue
    • Journal of Digital Convergence
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    • v.20 no.4
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    • pp.119-126
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    • 2022
  • With the rise and rapid development of the "Internet+" economic model, the internet is deeply integrated with the social economy and penetrates every corner of life. Compared with expanding the scale of business operations through internal investment and capital accumulation, e-commerce companies are more inclined to directly gain control of other companies through efficient merger and acquisition (M&A). The purpose of this study is to analyze changes in financial performance before and after M&A of Alibaba, China's largest e-commerce company in the Internet era. To present the impact of M&A events on Alibaba's stock price and shareholder wealth more intuitively, this study selected the market model in the event study method to measure abnormal returns. The results show that an M&A event led to a reduction in Alibaba's shareholder wealth in the short term. This study presents the theoretical basis for the M&A performance of e-commerce companies.

Mediating Roles of Attachment for Information Sharing in Social Media: Social Capital Theory Perspective (소셜 미디어에서 정보공유를 위한 애착의 매개역할: 사회적 자본이론 관점)

  • Chung, Namho;Han, Hee Jeong;Koo, Chulmo
    • Asia pacific journal of information systems
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    • v.22 no.4
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    • pp.101-123
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    • 2012
  • Currently, Social Media, it has widely a renown keyword and its related social trends and businesses have been fastly applied into various contexts. Social media has become an important research area for scholars interested in online technologies and cyber space and their social impacts. Social media is not only including web-based services but also mobile-based application services that allow people to share various style information and knowledge through online connection. Social media users have tendency to common identity- and bond-attachment through interactions such as 'thumbs up', 'reply note', 'forwarding', which may have driven from various factors and may result in delivering information, sharing knowledge, and specific experiences et al. Even further, almost of all social media sites provide and connect unknown strangers depending on shared interests, political views, or enjoyable activities, and other stuffs incorporating the creation of contents, which provides benefits to users. As fast developing digital devices including smartphone, tablet PC, internet based blogging, and photo and video clips, scholars desperately have began to study regarding diverse issues connecting human beings' motivations and the behavioral results which may be articulated by the format of antecedents as well as consequences related to contents that people create via social media. Social media such as Facebook, Twitter, or Cyworld users are more and more getting close each other and build up their relationships by a different style. In this sense, people use social media as tools for maintain pre-existing network, creating new people socially, and at the same time, explicitly find some business opportunities using personal and unlimited public networks. In terms of theory in explaining this phenomenon, social capital is a concept that describes the benefits one receives from one's relationship with others. Thereby, social media use is closely related to the form and connected of people, which is a bridge that can be able to achieve informational benefits of a heterogeneous network of people and common identity- and bonding-attachment which emphasizes emotional benefits from community members or friend group. Social capital would be resources accumulated through the relationships among people, which can be considered as an investment in social relations with expected returns and may achieve benefits from the greater access to and use of resources embedded in social networks. Social media using for their social capital has vastly been adopted in a cyber world, however, there has been little explaining the phenomenon theoretically how people may take advantages or opportunities through interaction among people, why people may interactively give willingness to help or their answers. The individual consciously express themselves in an online space, so called, common identity- or bonding-attachments. Common-identity attachment is the focus of the weak ties, which are loose connections between individuals who may provide useful information or new perspectives for one another but typically not emotional support, whereas common-bonding attachment is explained that between individuals in tightly-knit, emotionally close relationship such as family and close friends. The common identify- and bonding-attachment are mainly studying on-offline setting, which individual convey an impression to others that are expressed to own interest to others. Thus, individuals expect to meet other people and are trying to behave self-presentation engaging in opposite partners accordingly. As developing social media, individuals are motivated to disclose self-disclosures of open and honest using diverse cues such as verbal and nonverbal and pictorial and video files to their friends as well as passing strangers. Social media context, common identity- and bond-attachment for self-presentation seems different compared with face-to-face context. In the realm of social media, social users look for self-impression by posting text messages, pictures, video files. Under the digital environments, people interact to work, shop, learn, entertain, and be played. Social media provides increasingly the kinds of intention and behavior in online. Typically, identity and bond social capital through self-presentation is the intentional and tangible component of identity. At social media, people try to engage in others via a desired impression, which can maintain through performing coherent and complementary communications including displaying signs, symbols, brands made of digital stuffs(information, interest, pictures, etc,). In marketing area, consumers traditionally show common-identity as they select clothes, hairstyles, automobiles, logos, and so on, to impress others in any given context in a shopping mall or opera. To examine these social capital and attachment, we combined a social capital theory with an attachment theory into our research model. Our research model focuses on the common identity- and bond-attachment how they are formulated through social capitals: cognitive capital, structural capital, relational capital, and individual characteristics. Thus, we examined that individual online kindness, self-rated expertise, and social relation influence to build common identity- and bond-attachment, and the attachment effects make an impact on both the willingness to help, however, common bond seems not to show directly impact on information sharing. As a result, we discover that the social capital and attachment theories are mainly applicable to the context of social media and usage in the individual networks. We collected sample data of 256 who are using social media such as Facebook, Twitter, and Cyworld and analyzed the suggested hypotheses through the Structural Equation Model by AMOS. This study analyzes the direct and indirect relationship between the social network service usage and outcomes. Antecedents of kindness, confidence of knowledge, social relations are significantly affected to the mediators common identity-and bond attachments, however, interestingly, network externality does not impact, which we assumed that a size of network was a negative because group members would not significantly contribute if the members do not intend to actively interact with each other. The mediating variables had a positive effect on toward willingness to help. Further, common identity attachment has stronger significant on shared information.

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A Study on the Effects of National Forest Management on the Local Community (국유림경영이 지역사회에 미치는 영향에 관한 연구)

  • Youn, Yeo Chang;Son, Cheol Ho;Lee, Jin Kue
    • Journal of Korean Society of Forest Science
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    • v.83 no.1
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    • pp.38-49
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    • 1994
  • To investigate the effects of national forest management on the regional community, the inter-relationship between the local communities and neighbouring forest owned by the state was surveyed in the three locations, namely pyungchang-gun, Bonghwa-gun, and Kwangyang-gun, which have a large area of national forest. The effect of national forest management on the local community was different depending upon the relationship between the local community and the national forest, the resource base and infrastructure and facilities installed within the national forest. The major contribution of the national forest to regional society is the provision of land resources, forest products, employment opportunities, and social functions of forest. The supply of land resource from the national forest has been increasing steadily due to the increase in demand for public facilities. About one quarter of household income in the forest villages surveyed came out of the sales of forest products, mainly non-timber products. Due to the low level of forest operations for timber production, there are very limited opportunities of employment provided by the national forest. And the use of forest roads by local residents was also to a limited extent. Therefore, it is suggested that the national frosts should be managed such that help to revive the economy of local communities which are disadvantaged in the national investment priority due to the low economic returns.

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Review of change and response strategies for ESG management (ESG 경영을 위한 변화 및 대응 전략 검토)

  • Choe Yoowha
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.3
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    • pp.75-79
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    • 2023
  • ESG management means to thoroughly consider the investor's perspective when evaluating corporate value, and environmental, social, and governance issues are continuous and strategic monitoring issues in identifying risk and opportunity factors related to corporate management activities. In other words, the perspective of value creation is reflected in business relationships. The fundamental purpose of ESG management is continuous business value creation and thorough management of investment risks and business transactions in contractual relationships. It is also a requirement of linked investors. The field that Korean companies are currently experiencing the most is the recognition that 'ESG information collection is necessary and maintenance must be prioritized' in investor IR and global sales and marketing departments, and the primary need for this is emerging. In addition, as the legal affairs office, environmental safety department, and human resources department, which conduct compliance management, carry out related tasks, clarity at the organizational level must precede in order to properly establish an information integration and management system. It covers the scope of securing new market opportunities such as management, disclosure and communication. Therefore, in regard to the newly emerging ESG management and response methods, it is necessary to review and implement it repeatedly so that sustainable exchange profits can be created by simultaneously managing non-financial risks as well as efforts to enhance corporate value for financial returns.

Bankruptcy Forecasting Model using AdaBoost: A Focus on Construction Companies (적응형 부스팅을 이용한 파산 예측 모형: 건설업을 중심으로)

  • Heo, Junyoung;Yang, Jin Yong
    • Journal of Intelligence and Information Systems
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    • v.20 no.1
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    • pp.35-48
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    • 2014
  • According to the 2013 construction market outlook report, the liquidation of construction companies is expected to continue due to the ongoing residential construction recession. Bankruptcies of construction companies have a greater social impact compared to other industries. However, due to the different nature of the capital structure and debt-to-equity ratio, it is more difficult to forecast construction companies' bankruptcies than that of companies in other industries. The construction industry operates on greater leverage, with high debt-to-equity ratios, and project cash flow focused on the second half. The economic cycle greatly influences construction companies. Therefore, downturns tend to rapidly increase the bankruptcy rates of construction companies. High leverage, coupled with increased bankruptcy rates, could lead to greater burdens on banks providing loans to construction companies. Nevertheless, the bankruptcy prediction model concentrated mainly on financial institutions, with rare construction-specific studies. The bankruptcy prediction model based on corporate finance data has been studied for some time in various ways. However, the model is intended for all companies in general, and it may not be appropriate for forecasting bankruptcies of construction companies, who typically have high liquidity risks. The construction industry is capital-intensive, operates on long timelines with large-scale investment projects, and has comparatively longer payback periods than in other industries. With its unique capital structure, it can be difficult to apply a model used to judge the financial risk of companies in general to those in the construction industry. Diverse studies of bankruptcy forecasting models based on a company's financial statements have been conducted for many years. The subjects of the model, however, were general firms, and the models may not be proper for accurately forecasting companies with disproportionately large liquidity risks, such as construction companies. The construction industry is capital-intensive, requiring significant investments in long-term projects, therefore to realize returns from the investment. The unique capital structure means that the same criteria used for other industries cannot be applied to effectively evaluate financial risk for construction firms. Altman Z-score was first published in 1968, and is commonly used as a bankruptcy forecasting model. It forecasts the likelihood of a company going bankrupt by using a simple formula, classifying the results into three categories, and evaluating the corporate status as dangerous, moderate, or safe. When a company falls into the "dangerous" category, it has a high likelihood of bankruptcy within two years, while those in the "safe" category have a low likelihood of bankruptcy. For companies in the "moderate" category, it is difficult to forecast the risk. Many of the construction firm cases in this study fell in the "moderate" category, which made it difficult to forecast their risk. Along with the development of machine learning using computers, recent studies of corporate bankruptcy forecasting have used this technology. Pattern recognition, a representative application area in machine learning, is applied to forecasting corporate bankruptcy, with patterns analyzed based on a company's financial information, and then judged as to whether the pattern belongs to the bankruptcy risk group or the safe group. The representative machine learning models previously used in bankruptcy forecasting are Artificial Neural Networks, Adaptive Boosting (AdaBoost) and, the Support Vector Machine (SVM). There are also many hybrid studies combining these models. Existing studies using the traditional Z-Score technique or bankruptcy prediction using machine learning focus on companies in non-specific industries. Therefore, the industry-specific characteristics of companies are not considered. In this paper, we confirm that adaptive boosting (AdaBoost) is the most appropriate forecasting model for construction companies by based on company size. We classified construction companies into three groups - large, medium, and small based on the company's capital. We analyzed the predictive ability of AdaBoost for each group of companies. The experimental results showed that AdaBoost has more predictive ability than the other models, especially for the group of large companies with capital of more than 50 billion won.