• The Journal of Small Business Innovation
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• v.19 no.4
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• pp.19-39
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• 2016

With increasing adoption of smart products and complexity, companies have shifted their strategies from stand alone and competitive strategies to business ecosystem oriented and cooperative strategies. The win-win growth of business refers to corporate efforts undertaken by companies to pursue the healthiness of business between conglomerates and partnering companies such as suppliers for mutual prosperity and a long-term corporate soundness based on their business ecosystem and cooperative strategies. This study is designed to validate a theoretical proposition that the win-win growth strategy of Samsung Electronics and cooperative efforts among companies can create a healthy business ecosystem, based on results of case studies and surveys. In this study, a level of global market access of small and mid-sized companies is adopted as the key achievement index. The foreign market entry is considered as one of vulnerabilities in the ecosystem of small and mid-sized enterprises (SMEs). For SMEs, the global market access based on the research and development (R&D) has become the critical component in the process of transforming them into global small giants. The results of case studies and surveys are analyzed mainly based on a model of a virtuous cycle of Creativity, Opportunity, Productivity, and Proactivity (the COPP model) that features the characteristics of the healthiness of a business ecosystem. In the COPP model, a virtuous circle of profits made by the first three factors and Proactivity, which is the manifestation of entrepreneurship that proactively invests and reacts to the changing business environment of the future, enhances the healthiness of a given business ecosystem. With the application of the COPP model, this study finds major achievements of the win-win growth of Samsung Electronics as follows. First, Opportunity plays a role as a parameter in the relations of Creativity, Productivity, and creating profits. Namely, as companies export more (with more Opportunity), they are more likely to link their R&D efforts to Productivity and profitability. However, companies that do not export tend to fail to link their R&D investment to profitability. Second, this study finds that companies with huge investment on R&D for the future, which is the result of Proactivity, tend to hold a large number of patents (Creativity). And companies with significant numbers of patents tend to be large exporters as well (Opportunity), and companies with a large amount of exports tend to record high profitability (Productivity and profitability), and thus forms the virtuous cycle of the COPP model. In addition, to access global markets for sustainable growth, SMEs need to build and strengthen their competitiveness. This study concludes that companies with a high level of proactivity to invest for the future can create a virtuous circle of Creativity, Opportunity, Productivity, and Proactivity, thereby providing a strategic implication that SMEs should invest time and resources in forming such a virtuous cycle which is a sure way for the SMEs to grow into global small giants.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.127-146
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• 2017

Services using artificial intelligence have begun to emerge in daily life. Artificial intelligence is applied to products in consumer electronics and communications such as artificial intelligence refrigerators and speakers. In the financial sector, using Kensho's artificial intelligence technology, the process of the stock trading system in Goldman Sachs was improved. For example, two stock traders could handle the work of 600 stock traders and the analytical work for 15 people for 4weeks could be processed in 5 minutes. Especially, big data analysis through machine learning among artificial intelligence fields is actively applied throughout the financial industry. The stock market analysis and investment modeling through machine learning theory are also actively studied. The limits of linearity problem existing in financial time series studies are overcome by using machine learning theory such as artificial intelligence prediction model. The study of quantitative financial data based on the past stock market-related numerical data is widely performed using artificial intelligence to forecast future movements of stock price or indices. Various other studies have been conducted to predict the future direction of the market or the stock price of companies by learning based on a large amount of text data such as various news and comments related to the stock market. Investing on commodity asset, one of alternative assets, is usually used for enhancing the stability and safety of traditional stock and bond asset portfolio. There are relatively few researches on the investment model about commodity asset than mainstream assets like equity and bond. Recently machine learning techniques are widely applied on financial world, especially on stock and bond investment model and it makes better trading model on this field and makes the change on the whole financial area. In this study we made investment model using Support Vector Machine among the machine learning models. There are some researches on commodity asset focusing on the price prediction of the specific commodity but it is hard to find the researches about investment model of commodity as asset allocation using machine learning model. We propose a method of forecasting four major commodity indices, portfolio made of commodity futures, and individual commodity futures, using SVM model. The four major commodity indices are Goldman Sachs Commodity Index(GSCI), Dow Jones UBS Commodity Index(DJUI), Thomson Reuters/Core Commodity CRB Index(TRCI), and Rogers International Commodity Index(RI). We selected each two individual futures among three sectors as energy, agriculture, and metals that are actively traded on CME market and have enough liquidity. They are Crude Oil, Natural Gas, Corn, Wheat, Gold and Silver Futures. We made the equally weighted portfolio with six commodity futures for comparing with other commodity indices. We set the 19 macroeconomic indicators including stock market indices, exports & imports trade data, labor market data, and composite leading indicators as the input data of the model because commodity asset is very closely related with the macroeconomic activities. They are 14 US economic indicators, two Chinese economic indicators and two Korean economic indicators. Data period is from January 1990 to May 2017. We set the former 195 monthly data as training data and the latter 125 monthly data as test data. In this study, we verified that the performance of the equally weighted commodity futures portfolio rebalanced by the SVM model is better than that of other commodity indices. The prediction accuracy of the model for the commodity indices does not exceed 50% regardless of the SVM kernel function. On the other hand, the prediction accuracy of equally weighted commodity futures portfolio is 53%. The prediction accuracy of the individual commodity futures model is better than that of commodity indices model especially in agriculture and metal sectors. The individual commodity futures portfolio excluding the energy sector has outperformed the three sectors covered by individual commodity futures portfolio. In order to verify the validity of the model, it is judged that the analysis results should be similar despite variations in data period. So we also examined the odd numbered year data as training data and the even numbered year data as test data and we confirmed that the analysis results are similar. As a result, when we allocate commodity assets to traditional portfolio composed of stock, bond, and cash, we can get more effective investment performance not by investing commodity indices but by investing commodity futures. Especially we can get better performance by rebalanced commodity futures portfolio designed by SVM model.

• KDI Journal of Economic Policy
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• v.32 no.2
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• pp.93-143
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• 2010

This paper estimates the impact of Japan's economic sanction on DPRK trade in the 2000s. It conceptualizes the effects of sanction on DPRK trade, econometrically tests whether such effects exist in case of Japan's sanction using currently available DPRK trade statistics, and measures the size of the effects by correcting and reconfiguring the deficiencies of the currently available DPRK trade statistics. The main findings of the paper are as follows. First, Japan's sanction can have two different effects on DPRK trade: 'Sanction Country Effect' and "Third Country Effect.' The former means that the sanction diminishes DPRK trade with Japan while the latter refers to the effects on DPRK trade with other countries as well. The third country effect can arise not simply because the DPRK changes its trade routes to circumvent the sanction, but because the sanction forces the DPRK to readjust its major trade items and patterns. Second, currently no official DPRK trade statistics are available. Thus, the so-called mirror data referring to DPRK trading partners' statistics should be employed for the analysis of the sanction effects. However, all currently available mirror data suffer from three fundamental problems: 1) they may omit the real trade partners of the DPRK; 2) they may confuse ROK trade with DPRK trade; 3) they cannot distinguish non-commercial trade from commercial trade, whereas only the latter concerns Japan's sanction. Considering those problems, we have to adopt the following method in order to reach a reasonable conclusion about the sanction effect. That is, we should repeat the same analysis using all different mirror data currently available, which include KOTRA, IMF and UN Commodity Trade Statistics, and then discuss only the common results from them. Third, currently available mirror data make the following points. 1) DPRK trade is well explained by the gravity model. 2) Japan's sanction has not only the sanction country effect but also the third country effect on DPRK trade. 3) The third country effect occurs differently on DPRK export and import. In case of export, the mirror statistics reveal positive (+) third country effects on all of the major trade partners of the DPRK, including South Korea, China and Thailand. However, on DPRK import, such third country effects are not statistically significant even for South Korea and China. 4) This suggests that Japan's sanction has greater effects on DPRK import rather than its export. Fourth, as far as DPRK export is concerned, it is possible to resolve the abovementioned fundamental problems of mirror data and thus reconstruct more accurate statistics on DPRK trade. Those reconstructed statistics lead us to following conclusions. 1) Japan's economic sanction diminished DPRK's export to Japan from 2004 to 2006 by 103 million dollars on annual average (Sanction Country Effect). It comprises around 60 percent of DPRK's export to Japan in 2003. 2) However, for the same period, the DPRK diverted its exports to other countries to cope up with Japan's sanction, and as a result its export to other countries increased by 85 million dollars on annual average (Third Country Effect). 3) This means that more than 80 per cent of the sanction country effect was made up for by the third country effect. And the actual size of impact that Japan's sanction made on DPRK export in total was merely 30 million dollars on annual average. 4) The third country effect occurred mostly in inter-Korean trade. In fact, Japan's sanction increased DPRK export to the ROK by 72 million dollars on annual average. In contrast, there was no statistically significant increase in DPRK export to China caused by Japan's sanction. 5) It means that the DPRK confronted Japan's sanction and mitigated its impact primarily by using inter-Korean trade and thus the ROK. Fifth, two things should be noted concerning the fourth results above. 1) The results capture the third country effect caused only by trade transfer. Facing Japan's sanction, the DPRK could transfer its existing trade with Japan to other countries. Also it could change its main export items and increase the export of those new items to other countries as mentioned in the first result. However, the fourth results above reflect only the former, not the latter. 2) Although Japan's sanction did not make a huge impact on DPRK export, it might not be necessarily true for DPRK import. Indeed the currently available mirror statistics suggest that Japan's sanction has greater effects on DPRK import. Hence it would not be wise to argue that Japan's sanction did not have much impact on DPRK trade in general, simply using the fourth result above.

• Journal of the East Asian Society of Dietary Life
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• v.22 no.6
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• pp.744-757
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• 2012

This study was designed to obtain basic data for the globalization of Korean food and the expansion of food exports through contract foodservices. A survey of dietary habits and attitudes toward school foodservices was given to students in three American international schools served by a domestic contract foodservice management company located in Seoul and Gyeonggi area. The results showed an average of three meals taken daily 3.39 times for male students and 2.95 times for female students and the time required for a meal was about 24~26 minutes. The average breakfast frequency was 5.10 times(4.59 times for male students and 5.35 times for female students) and many students reported skipping breakfast due to a lack of time. The average weekly frequency of dining out was 1.78 times(2.15 times for male students and 1.60 times for female students). In all schools, irrespective of gender and grade, students responded that a desire for snacking was 'why they want to have cookies', and snacking hours were frequently listed as 'between noon and evening'. Many also responded that an unbalanced diet is the reason some snacks are 'not to their taste'. Overall, students were highly satisfied with the foodservice menu, although there was a significant difference in what was considered proper food temperature, proper food seasoning, suitable amounts of food, and freshness of food. Male and female students were specifically highly satisfied with the 'freshness of food materials' and 'variety of menu' respectively. Overall, all students were highly satisfied with the foodservice, including the 'cleanliness of tables and trays'.

• Strategy21
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• s.46
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• pp.239-276
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• 2020

The failure of early economic sanctions aimed at hurting the overall economies of targeted states called for a more sophisticated design of economic sanctions. This paved way for the advent of 'smart sanctions,' which target the supporters of the regime instead of the public mass. Despite controversies over the effectiveness of economic sanctions as a coercive tool to change the behavior of a targeted state, the transformation from 'comprehensive sanctions' to 'smart sanctions' is gaining the status of a legitimate method to impose punishment on states that do not conform to international norms, the nonproliferation of weapons of mass destruction in this particular context of the paper. The five permanent members of the United Nations Security Council proved that it can come to an accord on imposing economic sanctions over adopting resolutions on waging military war with targeted states. The North Korean nuclear issue has been the biggest security threat to countries in the region, even for China out of fear that further developments of nuclear weapons in North Korea might lead to a 'domino-effect,' leading to nuclear proliferation in the Northeast Asia region. Economic sanctions had been adopted by the UNSC as early as 2006 after the first North Korean nuclear test and has continually strengthened sanctions measures at each stage of North Korean weapons development. While dubious of the effectiveness of early sanctions on North Korea, recent sanctions that limit North Korea's exports of coal and imports of oil seem to have an impact on the regime, inducing Kim Jong-un to commit to peaceful talks since 2018. The purpose of this paper is to add a variable to the factors determining the success of economic sanctions on North Korea: preventing North Korea's evasion efforts by conducting illegal transshipments at sea. I first analyze the cause of recent success in the economic sanctions that led Kim Jong-un to engage in talks and add the maritime element to the argument. There are three conditions for the success of the sanctions regime, and they are: (1) smart sanctions, targeting commodities and support groups (elites) vital to regime survival., (2) China's faithful participation in the sanctions regime, and finally, (3) preventing North Korea's maritime evasion efforts.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.149-161
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• 2014

The export of domestic public services to overseas markets contains many potential obstacles, stemming from different export procedures, the target services, and socio-economic environments. In order to alleviate these problems, the business incubation platform as an open business ecosystem can be a powerful instrument to support the decisions taken by participants and stakeholders. In this paper, we propose an ontology model and its implementation processes for the business incubation platform with an open and pervasive architecture to support public service exports. For the conceptual model of platform ontology, export case studies are used for requirements analysis. The conceptual model shows the basic structure, with vocabulary and its meaning, the relationship between ontologies, and key attributes. For the implementation and test of the ontology model, the logical structure is edited using Prot$\acute{e}$g$\acute{e}$ editor. The core engine of the business incubation platform is the simulator module, where the various contexts of export businesses should be captured, defined, and shared with other modules through ontologies. It is well-known that an ontology, with which concepts and their relationships are represented using a shared vocabulary, is an efficient and effective tool for organizing meta-information to develop structural frameworks in a particular domain. The proposed model consists of five ontologies derived from a requirements survey of major stakeholders and their operational scenarios: service, requirements, environment, enterprise, and county. The service ontology contains several components that can find and categorize public services through a case analysis of the public service export. Key attributes of the service ontology are composed of categories including objective, requirements, activity, and service. The objective category, which has sub-attributes including operational body (organization) and user, acts as a reference to search and classify public services. The requirements category relates to the functional needs at a particular phase of system (service) design or operation. Sub-attributes of requirements are user, application, platform, architecture, and social overhead. The activity category represents business processes during the operation and maintenance phase. The activity category also has sub-attributes including facility, software, and project unit. The service category, with sub-attributes such as target, time, and place, acts as a reference to sort and classify the public services. The requirements ontology is derived from the basic and common components of public services and target countries. The key attributes of the requirements ontology are business, technology, and constraints. Business requirements represent the needs of processes and activities for public service export; technology represents the technological requirements for the operation of public services; and constraints represent the business law, regulations, or cultural characteristics of the target country. The environment ontology is derived from case studies of target countries for public service operation. Key attributes of the environment ontology are user, requirements, and activity. A user includes stakeholders in public services, from citizens to operators and managers; the requirements attribute represents the managerial and physical needs during operation; the activity attribute represents business processes in detail. The enterprise ontology is introduced from a previous study, and its attributes are activity, organization, strategy, marketing, and time. The country ontology is derived from the demographic and geopolitical analysis of the target country, and its key attributes are economy, social infrastructure, law, regulation, customs, population, location, and development strategies. The priority list for target services for a certain country and/or the priority list for target countries for a certain public services are generated by a matching algorithm. These lists are used as input seeds to simulate the consortium partners, and government's policies and programs. In the simulation, the environmental differences between Korea and the target country can be customized through a gap analysis and work-flow optimization process. When the process gap between Korea and the target country is too large for a single corporation to cover, a consortium is considered an alternative choice, and various alternatives are derived from the capability index of enterprises. For financial packages, a mix of various foreign aid funds can be simulated during this stage. It is expected that the proposed ontology model and the business incubation platform can be used by various participants in the public service export market. It could be especially beneficial to small and medium businesses that have relatively fewer resources and experience with public service export. We also expect that the open and pervasive service architecture in a digital business ecosystem will help stakeholders find new opportunities through information sharing and collaboration on business processes.