• Journal of Digital Convergence
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• v.17 no.6
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• pp.193-200
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• 2019

This study analyzes the current status and performance of regional industrial policy in the face of the weakening industrial competitiveness under the global trend of the 4th industrial revolution and suggests the policy direction that regional industrial policy as a new national growth strategy. This study focuses on the suggestion of new regional industrial policy framework under new policy environment based on literature review. We propose a new industrial policy framework that simultaneously pursues equality between regions and efficiency within the region at the same time. As a core policy recommendation, we suggest first, establishing the region-centered industrial policy governance, second, strengthening planning function of local government through human resource development and institutionalized national government consulting, and the third, constructing lifestyle industry-ecosystem based on cultural asset and identity of region, fourth, utilizing Smart City, as a platform for participatory innovation, entrepreneurial and capital attraction, and cultivating new industry based on public procurement and data. Main suggestions of this study would be a new guideline coping with the declining industrial competitiveness and the Fouth Industrial Revolution. Details would be necessary.

• Journal of Digital Convergence
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• v.16 no.12
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• pp.175-183
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• 2018

This study analyzes determinants of bond returns in terms of systematic risk versus idiosyncratic risk by examining relationship among those factors. First we examined the cross-sectional determinants of corporate bond returns with Korean bond market data from 2001 to 2014. This paper uses term factor and default factor for systematic risk, and duration factor and credit rating factor for idiosyncratic risk. The empirical result shows that systematic risk can explain cross-sectional differences of bond returns rather than idiosyncratic risk which is the same result in advanced markets(US or Europe). This result is different from the previous Korean studies which showed that idiosyncratic risk is more important than systematic risk in Korean bond market. The reason for the different result may be the longer sample period which includes the most recent period. It is insisted that Korean bond market is getting more synchronized with the advanced bond market. In conclusion, this empirical result implies that Korean bond portfolio managers should focus on systematic risk, which is contrary to current system in Korean asset management industry.

• Korean Journal of Heritage: History & Science
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• v.42 no.4
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• pp.50-73
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• 2009

Recently old stone walls were designated as registered cultural properties that meant an extension of categories about cultural properties from a spot area to whole area. Moreover given the changing situation of residential pattern, which is due to rapid social change, this designation can be seen as a significant measure to keep as intact as possible traditional landscapes in agricultural and fishing villages. In this paper, I analyze the symbol system and meaning of old stone walls and attempt to pick out the cultural elements which are related to them. These days we have made efforts to various aspects for which make traditional cultural resources into cultural contents. But many studies had done before emphasized aspects for beauty only. Especially existing studies about an old stone wall was mainly focused on architectural interpretation and tourist route. So we need to build a plot around oral research and need a creative approach for sharing with tourists. Cultural contents combine the original form, potential and capabilities with media by detecting original form of culture and finding out the worth and meaning. In this paper examined the probability of using by investigating a stone wall in Sang-hak Village that is related with recovering of places to live in contemporary society and finding cultural contents. I suggest more creative ways to make cultural properties into tourist resources by considering the possibilities of place marketing using storytelling, based on an analysis of data gathered.

• The Journal of the Korea Contents Association
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• v.22 no.9
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• pp.194-204
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• 2022

This study examined the social capital and geographical gaps of local television stations using web data gathered through website crawling. URLs for 16 local MBC websites were collected. MBC is an abbreviation for Munhwa Broadcasting Corporation, one of South Korea's largest television and radio broadcasters. Munhwa is a Sino-Korean term that means "culture." It initially determined which institutions local broadcasting stations were linked to using a Web Impact Report. To investigate the specific connection type, URL information was classified using the n-tuple helix model, followed by 2-mode network analysis. The n-tuple helix model is an analysis method that extends the standard university-business-government triple-helix model by including a new network innovation originator. As a result, local broadcasting stations relied heavily on activities like as festivals, performances, and exhibitions to engage the local community. Local stations in Daegu-Gyeongbuk area and the Busan-Ulsan-Gyeongnam area were identified as having the most diverse connections to the local population among other regions.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.1
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• pp.57-69
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• 2023

In a situation where digital transformation using artificial intelligence is active around the world, the growth of domestic AI companies or AI industrial ecosystems is slow. Where a large amount of government funds related to AI are being invested to overcome the difficult economic situation, systematic research on the effect is insufficient. So, this study aimed to examine the policy effectiveness of the government artificial intelligence solution voucher support project for small and medium-sized enterprises (SMEs) using Propensity Score Matching (PSM) and Difference-in-Differences (DID) on the financial performance of beneficiary companies. For empirical analysis, PSM-DID analysis was performed using sales performance since 2019 for 461 companies with a history of voucher support among the AI SMEs data released by the National IT Industry Promotion Agency. As a result of the analysis, the beneficiary companies' asset growth, salary, and R&D expenses increased overall after government support, and no significant contribution could be confirmed in terms of profits. This study suggests that the voucher policy business directly contributed to the company's growth in the short term, but it requires a certain period of time to generate profits.

• Economic Analysis
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• v.27 no.1
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• pp.67-90
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• 2021

This study found an interesting fact that the nonlinear relationship structure between volatility and trading volume changed before and after the COVID-19 pandemic according to empirical analysis using Bitcoin (BTC) market data that sensitively reflects investors' trading behavior. That is, their relationship appeared positive (+) in a stable market state before COVID-19 pandemic, as in theory based on the information flow paradigm. In a state under severe market stress due to COVID-19 pandemic, however, their dependence structure changed and even negative (-). This can be seen as a consequence of increased market stress caused by COVID-19 pandemics from a behavioral economics perspective, resulting in structural changes in the asset market and a significant impact on the nonlinear dependence of volatility and trading volume (in particular, their dependence at extreme quantiles). Hence, it should be recognized that in addition to information flows, psychological phenomena such as behavioral biases or herd behavior, which are closely related to market stress, can be a key in changing their dependence structure. For empirical analysis, this study performs a test of Ross (2015) for detecting a structural change, and proposes a Copula Regression Quantiles (CRQ) approach that can identify their nonlinear relationship structure and the asymmetric dependence in their distribution tails without the assumption of i.i.d. random variable. In addition, it was confirmed that when the relationship between their extreme values was analyzed by linear models, incorrect results could be derived due to model specification errors.

• Journal of Korean Society of Disaster and Security
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• v.15 no.4
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• pp.39-46
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• 2022

The rainfall characteristics such as heavy rains are changing differently from the past, and uncertainties are also greatly increasing due to climate change. In addition, urban development and population concentration are aggravating flood damage. Since the causes of urban inundation are generally complex, it is very important to establish an appropriate flood prevention plan. Thus, the government in Korea is establishing standards for disaster prevention performance for each local government. Since the concept of the disaster prevention performance target was first presented in 2010, the setting standards have changed several times, but the overall technology, methodology, and procedures have been maintained. Therefore, in this study, studies and technologies related to urban disaster prevention performance were reviewed using the scientometric analysis method to review them. This analysis is a method of identifying trends in the field and deriving new knowledge and information based on data such as papers and literature. In this study, papers related to the disaster prevention performance of the Web of Science for the last 30 years from 1990 to 2021 were collected. Citespace, scientometric software, was used to identify authors, research institutes, countries, and research trends, including citation analysis. As a result of the analysis, consideration factors such as the the concept of asset evaluation were identified when making decisions related to urban disaster prevention performance. In the future, it is expected that prevention performance standards and procedures can be upgraded if the keywords are specified and the review of each technology is conducted.

• Korean Journal of Social Welfare Studies
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• v.42 no.3
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• pp.233-265
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• 2011

Material hardship measures have been used to supplement the traditional income-based poverty measures. Recently poverty researchers have increasingly used measure of material hardship to examine the well-being of low income families. Measuring the material hardship might be useful to a better understanding of the multi-dimensions of the poverty in Korea. Using the data of the Korea Welfare Panel Study(the fourth wave), I examine incidences of material hardship across quintiles of the income distributions and the factors that might affect the experience of material hardship among the poor families. Major findings are as follows. Descriptive results show that nearly one-fifth of all families had experienced at least one of the five material hardships in the year. Those in the bottom quintiles and the poor families are more likely to experience material hardship than the other quintiles and non-poor families. But, incidences of the material hardship in the middle income quintiles and low income families are not a few(18 percent and 37 percent). Logistic regression results show that family-consumption related variables, income other economic resources(asset and public assistance), and household's employment status affect the experience of material hardship among the poor families. But, material hardship among the poor families is not significantly related with family income. These results indicate that material hardship measures are the useful indicators to understanding the multi-dimensions of the poverty in Korea. And they suggest that an extensive reform of the public assistance policy is necessary to relieve the material hardships of the poor in Korea.

• Journal of Industrial Convergence
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• v.22 no.2
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• pp.1-12
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• 2024

This study investigates what decisions have an impact on bank performance. A panel regression analysis was conducted using data from the financial statements of banks located in the United States from 2013 to 2022, and the effects of explanatory variables were examined through hierarchical panel regression analysis divided into financial decision-making and management decision-making. In addition, by analyzing performance separately from the creditor and shareholder perspectives (hereinafter referred to as overall) and from the shareholder perspective alone, it suggests which elements should be utilized and how to improve performance from each perspective. When a panel regression analysis was performed using only liquidity and stability, dependency on deposits and the interest coverage ratio had a statistically significant impact from the perspective of overall performance, and the debt ratio also had a statistically significant impact from the perspective of shareholder performance. When adding non-technical factors, only the labor cost ratio among non-technical factors was found to be statistically significant from the overall performance perspective, and although the non-technical factors were not statistically significant from the shareholder performance perspective, the cash ratio was found to have a statistically significant impact. Lastly, when adding technical innovation elements, the intangible asset ratio was not statistically significant from the overall performance perspective, but was significant from the shareholder performance perspective. The significance and implications of this study are that there are differences in factors that can affect the performance of overall or shareholder and that various decision-making factors can affect a bank's performance.

• Journal of Technology Innovation
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• v.24 no.4
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• pp.277-307
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• 2016

Since 2011, DCF(Discounted Cash Flow) method has been used initiatively for valuating R&D technology assets in the agricultural food industry and recently technology valuation based on royalties comparison among technology transfer transactions has been also carried out in parallel when evaluating the technology assets such as new seed development technologies. Since the DCF method which has been known until now has many input variables to be estimated, sophisticated estimation has been demanded at the time of technology valuation. In addition, considering more similar trading cases when applying sales transaction comparison or industry norm method based on information of technology transfer royalty, it is an important issue that should be taken into account in the same way in the Agri-Food industry. The main input variables used for technology valuation in the Agri-Food industry are life cycle of technology asset, the financial information related to the Agri-Food industry, discount rate, and technology contribution rate. The latest infrastructure building and data updating related to technology valuation has been carried out on a regular basis in the evaluation organization of the Agri-Food segment. This study verifies the key variables that give the most important impact on the results for the existing technology valuation in the Agri-Food industry and clarifies the difference between the existing valuation result and the outcome by referring the support information that is derived through the latest input information applied in DCF method. In addition, while presenting the scheme to complement fragment information which the latest input data just influence result of technology valuation, we tried to perform comparative analysis between the existing valuation results and the evaluated outcome after the latest of reference data for making a decision the input values to be estimated in DCF. To perform these analyzes, it was first selected the representative cases evaluated past in the Agri-Food industry, applied a sensitivity analysis for input variables based on these selected cases, and then executed a simulation analysis utilizing the key input variables derived from sensitivity analysis. The results of this study is to provide the information which there are the need for modernization of the data related to the input variables that are utilized during valuating technology assets in the Agri-Food sector and for building the infrastructure of the key input variables in DCF. Therefore it is expected to provide more fruitful information about the results of valuation.