• Korean Journal of Social Welfare
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• v.59 no.1
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• pp.199-221
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• 2007

This study examines the conditions and causes of income inequality and seeks assignments for mitigating income inequality. An analysis of the conditions and causes of income inequality is summarized as follows. First, income inequality, which rapidly increased after the economic crisis, increased and reduced repeatedly during 1999-2004, and remained a level in 2005 as high as that of the year directly after the economic crisis. Second, an analysis of the causes of income inequality by utilizing the long-term data(1985-2004) shows that unemployment rate, nonstandard employment rate, and the rising rate of land prices positively affect income inequality. Third, an analysis of the causes of income inequality by utilizing the data before and after the economic crisis(1995-2004) demonstrates that unemployment rate, nonstandard employment rate, and the workers' income ratio between large enterprises and small enterprises positively affect income inequality. Fourth, the rising rate of land prices which significantly affects income inequality in the data of 1985-2004 does not affect income equality in the data of 1995-2004, and the workers' income ratio between large enterprises and small enterprises which does not affect income inequality in the data of 1985-2004 significantly affect income equality in the data of 1995-2004. These results suggest several implications for mitigating income inequality. First, alternative plans to reduce unemployment rate must be prepared. Second, policies to reduce nonstandard employment rate should be established. Third, programs to stabilize or lower the land prices must be deliberated. Fourth, a master-plan to support small to medium enterprises must be carried out in order to reduce the wage differentials between large enterprises and small to medium enterprises.

• Korean Journal of Construction Engineering and Management
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• v.21 no.5
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• pp.64-73
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• 2020

The government announced a plan for fund support to the enterprises with high possibility of recovery and early restructuring for the enterprises with low recovery by objectifying credit assessment system. Such announcement of government could be extended to restructuring risk of middle standing enterprises with low financial soundness by establishing the basis to prepare prompt restructuring by reinforcing the basis for restructuring through capital market. This research analyzed financial soundness based on the financial evaluation of bank by selecting 10 middle standing construction companies which focused on housing business in 2019, based on such analysis result, it was confirmed that there was a high possibility of restructuring risk. This research determined that there would be a decrease in growth rate of construction industry on the whole in 2020 due to fall of economic growth rate and reinforced real estate regulation, accordingly, there's a big possibility for middle standing construction companies with paid-in capital ratio due to its low possibility of maintenance of stable credit rating. This research established KCSI assessment model by utilizing the material of a reliable research institute in order for middle standing construction companies to evade restructuring risk, and indicated risk ratio differentiated per each item through a working-level expert survey. Such research result could suggest credit risk reduction method to middle standing construction company management staffs, and prepare a basis to evade restructuring risk.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.1
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• pp.195-204
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• 2015

This study analyzed the normalization cases of the mutual savings bank insolvency PF (MSBIPF) to suggest the appropriate improvements according to the purpose. The results were as follows. First, the original intention to normalize the MSBIPF was unsuccessful. This may be caused by the daunting situation of the real estate market along with the complex and shared interests. On the other hand, it can be responsible for the lack of evidence and related regulations as well as the lukewarm attitude on public projects. Active institutional settings are warranted to compensate the remaining insolvent businesses to PF even today and in the future. The data related to the recognized sites as the poorest 32 PF sites was compared primarily to normalize by KAMCO and the relevant sites. The area variable was the only significant variable according to the correlation analysis and logit analysis. The direct investment, diverse PF-backed bonds and the activation of the Ritz can be suggested as alternative ways of normalization with respect to the issue of the KAMCO.

• Journal of the Korean association of regional geographers
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• v.11 no.1
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• pp.83-100
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• 2005

The Seoul Metropolitan Area's economy has undergone structural changes since the 1990s. With recent structural changes in the Korean economy in mind, this paper employs a decomposition analysis of Gross Regional Domestic Product per head and labor productivity to examine how the region's economic performance has changed relative to that of Korea since the 1900s. There are some findings. First, a strong cumulative causation process, derived from industrial linkages and agglomeration effects, has oocurred in the Seoul Metropolitan Area, widening economic disparities between the Seoul Metropolitan Area and the other regions especially since the Korean financial crisis in 1997 mainly due to Gyeonggi province's overwhelming cumulative GRDP growth relative to the national average. Second, the Seoul Metropolitan Area has begun w display good economic performance in terms of labour productivity relative w the national average since the late 1990s, with the region's industrial upgrading being implemented. Finally, manufacturing, financial intermediation and communications have made sensitive contributions to relative Seoul Metropolitan Area's labor productivity growth.

• Journal of Labour Economics
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• v.26 no.3
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• pp.149-179
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• 2003

This study is analysing the factors determining individuals' behavior of selecting self-employment not only at the micro-level but also at the macro-level to put a particular emphasis on the financial constraint and unemployment rate representing business cycle. The data used in this study are "Korean Labor and Income Panal Study" of the Korea Labor Institute and "Economically Active Population Survey" of National Statistical Office. The main findings are as follows. First, human capital such as educational attainment and job experience has positive effects on male's selection of self-employment. The effects of job experience, however, changed negative for female's selection of self-employment. Second, real estate is significantly enhancing the selection probabilities of employer selection while the income from financial assets has negative effects. Third, entrepreneurial culture and environment are also raising the self-employment selection probability. Lastly, the regional unemployment rate representing the business cycle has positive effects on the self-employment selection after the financial crisis in 1997 both at the micro and macro level. Moreover, the coefficient of regional unemployment rate has changed positive in the structural model of self-employment selection controlling for selection bias and income opportunities, which means that individual's behavior of self-employment selection is rather complex when accounting for the uncertainties of income opportunities and diverse characteristics of self-employment workforce.

• Korean Journal of Construction Engineering and Management
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• v.10 no.6
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• pp.146-153
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• 2009

The year 2008 was a hard year for Korea's construction companies. The real estate downturn resulted in halting new construction and stopping existing work, and inflation of global oil prices caused price hikes in rebar and concrete materials. As a solution to reducing the budget, the newly appointed government announced plans to increase low cost bid contracts from 10 billion to 30 billion won. When such economical and political factors negatively impact the construction market, projects based on low cost contracts are the hardest hit. Many problems already inherent in low cost bid contracts become accentuated. Consequently, this provides an opportune time to actually study and analyze the issues in these projects. This paper introduces the findings made from investigating four projects struggling to make ends meet in the year 2008. Results show that flow of cash (i.e., liquidity), or lack thereof, was the root cause which in turn was hampered by failed mechanisms for design changes, material inflation. Attributing cash flow risk to the bottom of the production structure (i.e., small business subcontractors) was also a problem within the industry. Contractors need a better way to prepare against material price fluctuations, and owners need to assist in expediting payment during times of extreme downturn.

• Journal of Cadastre & Land InformatiX
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• v.50 no.2
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• pp.101-115
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• 2020

In this paper, big data analysis method was used to find out global trends in autonomous driving and to derive activate spatial information services. The applied big data was used in conjunction with news articles and patent document in order to analysis trend in news article and patents document data in spatial information. In this paper, big data was created and key words were extracted by using LDA (Latent Dirichlet Allocation) based on the topic model in major news on autonomous driving. In addition, Analysis of spatial information and connectivity, global technology trend analysis, and trend analysis and prediction in the spatial information field were conducted by using WordNet applied based on key words of patent information. This paper was proposed a big data analysis method for predicting a trend and future through the analysis of the connection between the autonomous driving field and spatial information. In future, as a global trend of spatial information in autonomous driving, platform alliances, business partnerships, mergers and acquisitions, joint venture establishment, standardization and technology development were derived through big data analysis.

• Knowledge Management Research
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• v.23 no.1
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• pp.149-164
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• 2022

This paper analyzes the independent financial advisory business that is not yet active in Korea and proposes a plan to activate the independent financial advisory business using fintech technology. A bill was enacted in 2017 for the domestic independent financial advisory business, but it has not been activated much until now for various reasons. Although existing studies have proposed solutions in various ways, there is no clear solution yet. This paper proposes a new method of revitalizing the independent financial advisory business through fintech technology using the trust system that has recently attracted attention. Digital securities fintech technology using blockchain distributed ledger technology presents new possibilities in the real estate and music copyright markets, and related fintech venture companies continue to emerge in Korea. By combining these digital securities fintech technologies and the business process of ETF, a method was derived so that independent financial advisors can have their own financial products. The proposed model is more decentralized than the existing financial product sales structure, and presents the possibility of a protocol economy through a structure close to a private blockchain while complying with the existing financial order. This paper is meaningful in that it presented new solutions to completely different markets from information convergence perspectives on two completely different markets, and we hope that more business solutions will emerge through knowledge management activities that converge various perspectives in the future.

• Environmental and Resource Economics Review
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• v.31 no.4
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• pp.801-824
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• 2022

Recently, United Nations found that 38% of global carbon emissions are generated in the building sector, surpassing other industries (32%) and transportation (23%), and ESG is actively used as a way to reduce carbon emissions in the building sector, led by overseas advanced countries. In Korea, as the National Pension Service announced "Consider ESG with more than 50% of investment assets" this year, the move to introduce ESG in the building sector is accelerating, centering on construction companies and asset management companies. However, as the domestic ESG evaluation system is still mainly focused on corporate governance and social responsibility, interest in the environmental sector is lagging behind that of advanced countries. As ESG in the building sector is expected to grow rapidly over the next 10 years, I would like to suggest the following development directions. The first is the expansion of the incentive system. In order for the government to successfully implement policies related to ESG in the building sector, incentive system such as tax reduction and building standards should be expanded further than now in addition to negative systems such as rent restrictions and punishment taxes due to regulatory violations. Second, standardized ESG standards are established. Rather than creating an independent Korean ESG standard that is far from global standards, it is necessary to organize the common parts of global standards and evaluation methods and create and provide guidelines in the form of standard textbooks that can be used equally by all stakeholders. Third, it is an effort to link ESG in the building sector with Digital Transformation(DX). This is because actual energy savings and carbon emission reduction can be realized only when the operation method of the building sector, which is operated mainly by manpower, is digitalized and converted to an intelligent way.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.93-111
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• 2013

As Internet and information technology (IT) continues to develop and evolve, the issue of big data has emerged at the foreground of scholarly and industrial attention. Big data is generally defined as data that exceed the range that can be collected, stored, managed and analyzed by existing conventional information systems and it also refers to the new technologies designed to effectively extract values from such data. With the widespread dissemination of IT systems, continual efforts have been made in various fields of industry such as R&D, manufacturing, and finance to collect and analyze immense quantities of data in order to extract meaningful information and to use this information to solve various problems. Since IT has converged with various industries in many aspects, digital data are now being generated at a remarkably accelerating rate while developments in state-of-the-art technology have led to continual enhancements in system performance. The types of big data that are currently receiving the most attention include information available within companies, such as information on consumer characteristics, information on purchase records, logistics information and log information indicating the usage of products and services by consumers, as well as information accumulated outside companies, such as information on the web search traffic of online users, social network information, and patent information. Among these various types of big data, web searches performed by online users constitute one of the most effective and important sources of information for marketing purposes because consumers search for information on the internet in order to make efficient and rational choices. Recently, Google has provided public access to its information on the web search traffic of online users through a service named Google Trends. Research that uses this web search traffic information to analyze the information search behavior of online users is now receiving much attention in academia and in fields of industry. Studies using web search traffic information can be broadly classified into two fields. The first field consists of empirical demonstrations that show how web search information can be used to forecast social phenomena, the purchasing power of consumers, the outcomes of political elections, etc. The other field focuses on using web search traffic information to observe consumer behavior, identifying the attributes of a product that consumers regard as important or tracking changes on consumers' expectations, for example, but relatively less research has been completed in this field. In particular, to the extent of our knowledge, hardly any studies related to brands have yet attempted to use web search traffic information to analyze the factors that influence consumers' purchasing activities. This study aims to demonstrate that consumers' web search traffic information can be used to derive the relations among brands and the relations between an individual brand and product attributes. When consumers input their search words on the web, they may use a single keyword for the search, but they also often input multiple keywords to seek related information (this is referred to as simultaneous searching). A consumer performs a simultaneous search either to simultaneously compare two product brands to obtain information on their similarities and differences, or to acquire more in-depth information about a specific attribute in a specific brand. Web search traffic information shows that the quantity of simultaneous searches using certain keywords increases when the relation is closer in the consumer's mind and it will be possible to derive the relations between each of the keywords by collecting this relational data and subjecting it to network analysis. Accordingly, this study proposes a method of analyzing how brands are positioned by consumers and what relationships exist between product attributes and an individual brand, using simultaneous search traffic information. It also presents case studies demonstrating the actual application of this method, with a focus on tablets, belonging to innovative product groups.