• Journal of Digital Convergence
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• v.17 no.4
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• pp.95-105
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• 2019

The failure of company management that does not overcome the recession of shipping economy has negative impact on front-end and back-end industries in relation to shipping industry overall. This study aims to derive a measure of government policy support for win-win of ship owners and shippers by performing a survey with experts in ship owners, shippers, and port-related institutions. This study employed a consistent fuzzy preference relation (CFPR) method to provide the priority of government policies. The study results showed that out of all 14 policies, the policy perceived most important was "expansion of participation in share of shipping company or ships of shipper (0.102)" followed by "strengthening of national shipper-centered service quality (0.101)", and "providing a long-term transportation contract model of container cargo (0.085)". To recover the Korean shipping industry via win-win of ship owners and shipper, the policy enforcement is important through correct government policy establishment and priority selection. In this regard, this study contributed to proposing policies and priority of the policies. For the future study, detailed analysis on comparison of perception difference among stakeholders in the shipping industry is needed.

• The Korean Journal of Applied Statistics
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• v.34 no.1
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• pp.115-126
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• 2021

Central banks communicate with the market through a statement on the direction of monetary policy while implementing monetary policy. The rapid contraction of the global economy due to the recent Covid-19 pandemic could be compared to the crisis situation during the 2008 global financial crisis. In this paper, we analyzed the text data from the monetary policy statements of the Bank of Korea and Fed reflecting monetary policy directions focusing on how they were affected in the face of a global crisis. For analysis, we collected the text data of the two countries' monetary policy direction reports published from October 1999 to September 2020. We examined the semantic features using word cloud and word embedding, and analyzed the trend of the similarity between two countries' documents through a piecewise regression tree model. The visualization result shows that both the Bank of Korea and the US Fed have published the statements with refined words of clear meaning for transparent and effective communication with the market. The analysis of the dissimilarity trend of documents in both countries also shows that there exists a sense of synchronization between them as the rapid changes in the global economic environment affect monetary policy.

• Journal of Digital Convergence
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• v.19 no.6
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• pp.133-141
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• 2021

Governments of each country are actively implementing fiscal expansion policies to recover the real economy after Corona 19. In Korea, the stock market and housing market are greatly affected as liquidity in the market increases due to the implementation of disaster subsidies and welfare policies. The purpose of this study is to analyze the relationship between stock market and housing market trends and liquidity. Data were collected by the Bank of Korea and Kookmin Bank. The analysis period is from January 2000 to December 2020, and monthly data are used. For empirical analysis, the rate of change from the same month of the previous year was calculated for each variable, and numerical analysis, index analysis, and model analysis were performed. As a result of the analysis, it was found that the stock index showed a positive(+) relationship with the house price, while a negative(-) relationship with M2. Previous studies have suggested that, in general, an increase in liquidity affects the stock market and the housing market, and inflation also rises. In this study, it was found that the stock market and the housing market had an effect on each other. However, it was investigated that liquidity showed an inverse relationship with the stock market and had no relationship with the housing market. Through this, this study estimated that there is a time difference in the relationship between liquidity and the stock market & housing market.

• Journal of the Korea Society of Computer and Information
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• v.26 no.2
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• pp.213-220
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• 2021

With the continuing development of the global economy, the scale of international production and management of companies is expanding rapidly nowadays. As a result, it is increasingly important for multinational companies to establish appropriate marketing strategies for products in order to successfully enter overseas markets. When consumers evaluate the quality of products from various countries, they depend heavily on the image of the product as well as the price of the product. Therefore, this study aim to find out how the price, country image, brand image and country of origin image affect on consumer product evaluation and purchase intention. Based on these concepts, the significance of this study is helping local companies make more appropriate marketing strategies by understanding the importance of price and image of a product to companies and knowing more accurate recognition in Korea and Korean-made products of Chinese consumers. The results of this study which used AMOS model showed that 1) The country image and country of origin image for a product had a positive effects on product quality, 2) The price and country image of a product had a positive effects on service quality, 3) And evaluation of product had a positive effects on purchase intention. Based on these results, we made some proposals and presented the future research directions according to the limitations.

• The Journal of the Korea Contents Association
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• v.21 no.8
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• pp.356-366
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• 2021

The high-tech industry, a leader in the national economy, has a larger investment cost compared to general buildings, a shorter construction period, and requires continuous investment. Therefore, accurate construction cost prediction and quick decision-making are important factors for efficient cost and process management. Overseas, the construction information classification system has been standardized since 1980 and has been continuously developed, improving construction productivity by systematically collecting and utilizing project life cycle information. At domestic construction sites, attempts have been made to standardize the classification system of construction information, but it is difficult to achieve continuous standardization and systematization due to the absence of a standardization body and differences in cost and process management methods for each construction company. Particular, in the case of the high-tech industry, the standardization and systematization level of the construction information classification system for high-tech facility construction is very low due to problems such as large scale, numerous types of work, complex construction and security. Therefore, the purpose of this study is to construct a construction information classification system suitable for high-tech facility construction through collection, classification, and analysis of related project data constructed in Korea. Based on the WBS (Work Breakdown Structure) and CBS (Cost Breakdown Structure) classified and analyzed through this study, a code system through hierarchical classification was proposed, and the cost model of buildings by linking WBS and CBS was three-dimensionalized and the utilized method was presented. Through this, an information classification system based on inter-relationships can be developed beyond the one-way tree structure, which is a general construction information classification system, and effects such as shortening of construction period and cost reduction will be maximized.

• The Journal of the Korea Contents Association
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• v.22 no.10
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• pp.703-722
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• 2022

The concentration of local businesses in the capital region promotes a decrease in the local population and polarization between the capital region and non-capital regions. It affects the competitiveness of local industries and creates a vicious cycle throughout the local economy, society and culture. Therefore, this study classified the companies in the capital region and non-capital regions by group and examined the effect of the innovation capability factors of companies on the creation of business performance. We analyzed the effects of R&D capabilities, which are elements of innovation capability, and open innovation and convergence capabilities on business performance. Smart PLS 3.0 was used for analysis including direct and indirect mediating and moderating effects, multi-group analysis, and structural equation model analysis. As a result, R&D capability did not have a significant effect on business performance, but it has a positive influence towards business performance through convergence capability and open innovation. However, the effectiveness of open innovation in non-capital regions and convergence capabilities in capital region were not statistically significant. In particular, in terms of open innovation, as the difference between groups is statistically clear, follow-up measures are suggested especially in non-capital regions.

• Knowledge Management Research
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• v.23 no.3
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• pp.129-152
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• 2022

As a key infrastructure for digital transformation, the spread of data, network, artificial intelligence (D.N.A.) fields and the emergence of promising industries are laying the groundwork for active digital innovation throughout the economy. In this study, by applying the text mining methodology, major topics were derived by using the abstract, publication year, and research field of the study corresponding to the SCIE, SSCI, and A&HCI indexes of the WoS database as input variables. First, main keywords were identified through TF and TF-IDF analysis based on word appearance frequency, and then topic modeling was performed using g-DMR. With the advantage of the topic model that can utilize various types of variables as meta information, it was possible to properly explore the meaning beyond simply deriving a topic. According to the analysis results, topics such as business intelligence, manufacturing production systems, service value creation, telemedicine, and digital education were identified as major research topics in digital transformation. To summarize the results of topic modeling, 1) research on business intelligence has been actively conducted in all areas after COVID-19, and 2) issues such as intelligent manufacturing solutions and metaverses have emerged in the manufacturing field. It has been confirmed that the topic of production systems is receiving attention once again. Finally, 3) Although the topic itself can be viewed separately in terms of technology and service, it was found that it is undesirable to interpret it separately because a number of studies comprehensively deal with various services applied by combining the relevant technologies.

• Journal of Korea Trade
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• v.25 no.3
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• pp.21-47
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• 2021

Purpose - Offshoring has emerged as one of the major trends in international trade and has become one of the strategies for achieving competitiveness in the global market. In spite of this, the expected gains of offshoring can be offset by hidden costs and risks, such as those associated with the COVID-19 pandemic, the trade war between the USA and China, and the ongoing trade dispute between Korea and Japan. To obviate such business failure and prevent critical business blunders, offshoring strategies that efficiently consider both risk elements and potential wealth creation are urgently need. The first purpose of this study is to contribute to the development of more advanced offshoring strategies to help host countries select the best locations to manage supply chain risks and create unique value. The second purpose is to specifically analyze the current status of Korea and provide Korean companies with implications to be considered when deciding whether to offshore or re-shore. Design/methodology - A Network DEA model was applied to measure the comparative location efficiency of national competencies for offshoring strategy from perspectives of wealth creation opportunities (profitability and marketability) and supply chain risk management. The location efficiencies are compared among a total 70 countries selected from the Global Competitiveness Index (GCI) and globally attractive locations outlined by Kearney (2017). For the secondary analysis of efficiency, a t-test examining the nature of competitive advantage and the level of sophistication in production processes was implemented in three divisions. We then analyzed differences in offshoring performance in terms of the identified national traits. Moreover, Tobit regression analysis is conducted to investigate the correlation between value-added business activities and each divisional efficiency, seeking to determine how each degree of value-added business activity influences the increase in offshoring productivity. Findings - Regarding overall location efficiency for offshoring performance, only the USA and Italy were identified as being efficient as host countries for offshoring, under circumstances of advanced development, such as productivity and risk management. Korea ranks 13th among 70 countries. The determinants of national competitiveness depend on national traits (the nature of competitive advantage and business sophistication). Countries with labor/resource advantages and labor-intensive industries are more competitive in terms of marketability than others. In contrast, countries with strong technology-intensive industries benefit offshoring companies, particularly in the technology sector, with the added advantage of supply chain risk management. As the perception of a value chain is broader in a country, it can achieve both production sophistication and competitive advantages such as marketability and SCRM. Originality/value - Existing studies focus on offshoring effectiveness from a company perspective. This paper contributes to comparing country efficiency in producing core competencies related to an offshoring strategy and also segments countries into three performance-based considerations associated with the global offshoring market. It also details Korea's position as an offshoring location according to national efficiency and competency.

• Korean small business review
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• v.42 no.1
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• pp.107-133
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• 2020

Many researchers conducted studies on the relationship between entrepreneur's characteristic, capability, strategy and performance of new venture. However, the development of scientific technique and the complexity of the business environment have stimulated entrepreneurial teams rather than individuals. Therefore, the necessity of theoretical and practical study on the effect of the characteristics of an entrepreneurial team on the new venture companies was suggested. Initial research on entrepreneurial team diversity has primarily addressed the impact of demographic diversity on performance. In order to verify the research model of this study, 287 delegates of new venture companies that participated in the projects at the 18 Centers for Creative Economy & Innovation in 17 regions of the country conducted validity and reliability test based on the questionnaire to which they answered. The result shows that only gender diversity among demographic diversity affected non-financial performance. Information diversity influenced career diversity on financial performance and diversity in education on non-financial performance. Also, the higher the previous sharing experience, the better the financial performance. Value diversity has negative effect on both financial and non-financial performance. Based on the results, theoretical and practical implications are derived. Also suggested are methodological limitations and future research directions.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.4
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• pp.163-180
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• 2022

Real estate data can be big data. Because the amount of real estate data is growing rapidly and real estate data interacts with various fields such as the economy, law, and crowd psychology, yet is structured with complex data layers. The existing Relational Database tends to show difficulty in handling various relationships for managing real estate big data, because it has a fixed schema and is only vertically extendable. In order to improve such limitations, this study constructs the real estate data in a Graph Database and verifies its usefulness. For the research method, we modeled various real estate data on MySQL, one of the most widely used Relational Databases, and Neo4j, one of the most widely used Graph Databases. Then, we collected real estate questions used in real life and selected 9 different questions to compare the query times on each Database. As a result, Neo4j showed constant performance even in queries with multiple JOIN statements with inferences to various relationships, whereas MySQL showed a rapid increase in its performance. According to this result, we have found out that a Graph Database such as Neo4j is more efficient for real estate big data with various relationships. We expect to use the real estate Graph Database in predicting real estate price factors and inquiring AI speakers for real estate.