• Journal of Space Technology and Applications
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• v.3 no.2
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• pp.118-143
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• 2023

Space is becoming more commercialized. Despite of its delayed start-up, space activities in Korea are attracting more nation-wide supports from both investors and government. May 25, 2023, KSLV II, also called Nuri, successfully transported, and inserted seven satellites to a sun-synchronous orbit of 550 km altitude. However, Starlink has over 4,000 satellites around this altitude for its commercial activities. Hence, it is necessary for us to constantly monitor the collision risks of these satellites against resident space objects including Starlink. Here we report a quantitative research output regarding the conjunctions, particularly between the Nuri satellites and Starlink. Our calculation shows that, on average, three times everyday, the Nuri satellites encounter Starlink within 1 km distance with the probability of collision higher than 1.0E-5. A comparative study with KOMPSAT-5, also called Arirang-5, shows that its distance of closest approach distribution significantly differs from those of Nuri satellites. We also report a quantitative analysis of collision-avoiding maneuver cost of Starlink satellites and a strategy for Korea, being a delayed starter, to speed up to position itself in the space leading countries. We used the AstroOne program for analyses and compared its output with that of Socrates Plus of Celestrak. The two line element data was used for computation.

• Journal of Venture Innovation
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• v.5 no.4
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• pp.109-115
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• 2022

As the 4th industrial revolution progresses, foreign countries are promoting smart manufacturing innovation through digital transformation as a priority task early on to secure a competitive edge in the manufacturing industry. In response, the Korean government is also promoting a policy to enhance the competitiveness of small and medium-sized manufacturing companies by promoting digital transformation in the corporate sector to meet the global trend of the 4th industrial revolution era. Manufacturing powerhouses such as Germany and Japan see manufacturing as a key sector in digital transformation and are leading related policies, while emerging countries such as China are also promoting manufacturing innovation strategies such as building digital infrastructure and creating a digital innovation ecosystem. Korea is promoting the 'Korean-style smart factory dissemination and expansion strategy' by transforming Germany's manufacturing innovation strategy for smart factory supply to suit the domestic situation. However, the policy to supply smart factories so far has been conducted with support from individual companies under the leadership of the government, and most of the smart factories are at the basic level, and it is evaluated that there are limitations such as the lack of manpower to operate smart factories. In addition, while the current policy focuses on expanding the supply of smart factories in SMEs, it is necessary to establish a smart manufacturing system through linkages between large and small businesses in order to achieve the original goal of establishing a smart manufacturing system. Therefore, it can be said that from the standpoint of small and medium-sized enterprises (SMEs), who are consumers of smart factories, it can be said that the digital transformation policy can achieve the expected results only when appropriate incentives are provided for the introduction of smart factories in a situation where management resources such as funds, technology, and human resources are lacking. In addition, it is judged that the uncertainty of the performance of digital investment always exists, and as long as large and small companies are maintained as an ecosystem of delivery and subcontracting, there is very little incentive for small and medium-sized manufacturing companies to voluntarily invest in or advance digital transformation. Therefore, the digital transformation policy of small and medium-sized manufacturing companies in the future has practical significance in that it suggests that there is a need to seek ways to attract SMEs' digital-related voluntary investment.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.2
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• pp.1-20
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• 2023

The purpose of this study is to identify the unique entrepreneurial behavioral attributes of social enterprises that are distinct from for-profit enterprises at the organizational level, derive a social entrepreneurship model that reflects the unique characteristics of social enterprises as strategic decision-making and organizational behavioral tendencies. In order to effectively achieve the purpose of this study, previous studies were reviewed, and qualitative studies were conducted using the grounded theory method based on this. In this study, social entrepreneurship was identified as five sub-factors through a series of analysis processes, and 'Social value orientation; Innovativeness; Pro-activeness; Risk taking; Cooperation orientation' was newly proposed. It also proposed a new social entrepreneurship framework that integrates and explains the multidimensional model of social entrepreneurship by reviewing and connecting the relationships between each sub-factor of the research model. The 'social entrepreneurship framework' classified the social entrepreneurship model into 'pro-social motivation', 'pro-social behavior', and 'entrepreneurial behavior' attributes and explained them by linking them with each sub-factor that constitutes social entrepreneurship. The most remarkable difference between this study and previous studies is that it identified and added 'Cooperation orientation' as a sub-factor constituting social entrepreneurship from the organizational-level behavioral point of view. Through this study, 'Cooperation orientation' was identified as a major behavioral tendency for social enterprises to materialize pro-social motivation, strengthen the economic foundation of business activities, and improve the efficiency of business operations. 'Cooperation orientation' is a major behavioral tendency that strengthens the legitimacy of business activities between pro-social motivation and profit-seeking of social enterprises, improves the performance of social value creation activities, and overcomes the difficulties of resource constraints through cooperation with the outside and improves operational efficiency. In addition, it was confirmed that 'Cooperation orientation' is a major behavioral tendency of social enterprises that is manifested simultaneously in social value-oriented activities and entrepreneurial activities pursuing profit. The 'Cooperation orientation' newly identified in the study supplements the previous research, increases the explanatory power of the theory of social entrepreneurship, and provides the basis for theoretical expansion to subsequent researchers.

• Journal of Venture Innovation
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• v.5 no.1
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• pp.107-127
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• 2022

Global challenges such as the corona pandemic, climate change and the war-on-tech ensure that the demand who the technologies of the future develops and monitors prominently for will be on the agenda. Development of, and applications in, agrifood, biotech, high-tech, medtech, quantum, AI and photonics are the basis of the future earning capacity of the Netherlands and contribute to solving societal challenges, close to home and worldwide. To be like the Netherlands and Europe a strategic position in the to obtain knowledge and innovation chain, and with it our autonomy in relation to from China and the United States insurance, clear choices are needed. Brainport Eindhoven: Building on Philips' knowledge base, there is create an innovative ecosystem where more than 7,000 companies in the High-tech Systems & Materials (HTSM) collaborate on new technologies, future earning potential and international value chains. Nearly 20,000 private R&D employees work in 5 regional high-end campuses and for companies such as ASML, NXP, DAF, Prodrive Technologies, Lightyear and many others. Brainport Eindhoven has a internationally leading position in the field of system engineering, semicon, micro and nanoelectronics, AI, integrated photonics and additive manufacturing. What is being developed in Brainport leads to the growth of the manufacturing industry far beyond the region thanks to chain cooperation between large companies and SMEs. South-Holland: The South Holland ecosystem includes companies as KPN, Shell, DSM and Janssen Pharmaceutical, large and innovative SMEs and leading educational and knowledge institutions that have more than Invest €3.3 billion in R&D. Bearing Cores are formed by the top campuses of Leiden and Delft, good for more than 40,000 innovative jobs, the port-industrial complex (logistics & energy), the manufacturing industry cluster on maritime and aerospace and the horticultural cluster in the Westland. South Holland trains thematically key technologies such as biotech, quantum technology and AI. Twente: The green, technological top region of Twente has a long tradition of collaboration in triple helix bandage. Technological innovations from Twente offer worldwide solutions for the large social issues. Work is in progress to key technologies such as AI, photonics, robotics and nanotechnology. New technology is applied in sectors such as medtech, the manufacturing industry, agriculture and circular value chains, such as textiles and construction. Being for Twente start-ups and SMEs of great importance to the jobs of tomorrow. Connect these companies technology from Twente with knowledge regions and OEMs, at home and abroad. Wageningen in FoodValley: Wageningen Campus is a global agri-food magnet for startups and corporates by the national accelerator StartLife and student incubator StartHub. FoodvalleyNL also connects with an ambitious 2030 programme, the versatile ecosystem regional, national and international - including through the WEF European food innovation hub. The campus offers guests and the 3,000 private R&D put in an interesting programming science, innovation and social dialogue around the challenges in agro production, food processing, biobased/circular, climate and biodiversity. The Netherlands succeeded in industrializing in logistics countries, but it is striving for sustainable growth by creating an innovative ecosystem through a regional industry-academic research model. In particular, the Brainport Cluster, centered on the high-tech industry, pursues regional innovation and is opening a new horizon for existing industry-academic models. Brainport is a state-of-the-art forward base that leads the innovation ecosystem of Dutch manufacturing. The history of ports in the Netherlands is transforming from a logistics-oriented port symbolized by Rotterdam into a "port of digital knowledge" centered on Brainport. On the basis of this, it can be seen that the industry-academic cluster model linking the central government's vision to create an innovative ecosystem and the specialized industry in the region serves as the biggest stepping stone. The Netherlands' innovation policy is expected to be more faithful to its role as Europe's "digital gateway" through regional development centered on the innovation cluster ecosystem and investment in job creation and new industries.

• Asia Marketing Journal
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• v.14 no.1
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• pp.25-51
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• 2012

Researches about the relationship between SST(Self Service Technology) and TRI(Technology Readiness Index) have been carried out after TRI was developed by Parasuraman and his colleagues(2000). We hypothesize Consumer Readiness can also influence consumer's motivation, attitude, and intent to use SST. Currently, there has been no research on this subject. In this study, we investigated the relationship between TR, Consumer Readiness and SST Core Attitudinal Model which Dabholkar & Bagozzi(1994) proposed. The researchers also investigated moderating effects of consumer traits and situational factors to verify the acceptance of such forms of service delivery by all kinds of consumers and under different situational contexts. Self consciousness, the need for interaction with an employee, and the technology anxiety were used as consumer trait variables. Perceived waiting time and perceived crowding were used as situational variables. 380 questionnaires were distributed to a sample group of people in their 20's and 30's, and the data were analyzed with structural equation model using AMOS 18.0 program. All of Cronbach's alpha values representing reliabilities were satisfactory. The values of Composite Reliability(CR) and Average Variance Extracted(AVE) also showed the above criteria, thus providing evidence of convergent validity. To confirm discriminant validity among the constructs, confirmatory factor analysis and correlations among all the variables were examined. The results were satisfactory. The results of this study are summarized as follows. 1. Optimism and innovativeness of TR partially influenced the motivation to use SST. People who tend to be optimistic use SST because of ease of use and fun. The innovative however, usually use SST due to its performance. However, consumer readiness of role clarity, ability and self-efficacy influence all the components of motivation to use SST, ease of use, performance and fun. The relative effect of consumer readiness on the motivation to use SST was much stronger and more significant than that of TR. No other previous studies have examined the effects of Consumer Readiness on SST usage motivation, attitude and intention. It is academically meaningful that the researchers verified that Consumer Readiness is the important precedent construct influencing the self service technology core Attitudinal Model. Our findings suggest that marketers should consider fun and ease of use attributes to promote the use of self service technology. In addition, the SST usage frequency will rise rapidly when role clarity, ability, and self-efficacy which anybody can easily handle SST is assured. If the SST usage rate is increased, waiting times for customers could be decreased. Shorter waiting time could lead to higher customer satisfaction. It may also result in making a long-term profit owing to the reduced number of employees. Thus, presentation of using SST by employees or videos showing how to use it will promote the usage attitude and intent. 2. In SST core attitudinal model, performance and fun factors among SST usage motivation affected attitudes of using SST. The attitude of using SST highly influenced intent to use SST. This result is consistent with previous researches that dealt with the relationship between motivation, attitude and intention. Expectation of using SST could result in good performance just like the effect of ordering menu to service employees and to have fun since fun during its use could promote more SST usage rate. 3. In the relationship among motivation, attitude and intent in SST core attitudinal model, the moderating effect of consumer traits(self-consciousness, need for interaction with service employees and technology anxiety) and situational factors(perceived crowding and perceived waiting time) were tested. The results also supported the hypothesized moderating effects except perceived crowding. The highly self-conscious tended to form attitudes to use SST because of its fun compared to those who were less self-conscious because of its performance. People who had a high need for interaction with service employees tended to use SST for its performance. This result indicates that if ordering results are assured, SST is easily accessible to even consumers who have a high need for interaction with a service employee. When SST is easy to use, attitudes strengthen intent among people who had a high level of anxiety of technology. People who had low technology anxiety formed attitudes to use SST because of its performance. Service firms must ensure their self service technology is designed to be easy to use for those who have a high level of technology anxiety. Shorter perceived waiting times strengthened the attitude to use self service technology because of its fun. If the fun aspect is assured, people willing to use self service technology even perceive waiting time to be shorter than it actually is. Greater perceived waiting times form higher level of intent to use self service technology than those of shorter perceived waiting times. This implies that people view self service technology as a faster alternative to ordering service employees. The fun aspect of self service technology will attract a higher rate of usage for self service technology. 4. It has been proven that ease of use, performance and fun aspects are very important factors in motivation to form attitudes and intent to use self service technology regardless of the amount of perceived waiting time, self-consciousness, need for interaction with service employees, and technology anxiety. Service firms must consider these motivation aspects(ease of use, performance and fun)strongly in their promotion to use self service technology. Ease of use, assuring absolute performance compared to interaction with service employees', and adding a fun aspect will positively strengthen consumers' attitudes and intent to use self service technology. Summarizing the moderating effects, fun is the most valuable factor triggering SST usage attitude and intention. Therefore, designing self service technology to be fun will be the key to its success. This study focused on the touch screen self service technology in fast food restaurant. Although it has its limits due to the fact that it is hard to generalize the results to any other self service technology, the conceptual framework of this study can be applied to future research of any other service site.

• KDI Journal of Economic Policy
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• v.13 no.4
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• pp.91-116
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• 1991

Market liberalization progressing simultaneously with high and rapidly rising domestic wages has created an adverse business environment for domestic firms. Korean firms are losing their international competitiveness in comparison to firms from LDC(Less Developed Countries) in low-tech industries. In high-tech industries, domestic firms without government protection (which is impossible due to the liberalization policy and the current international status of the Korean economy) are in a disadvantaged position relative to firms from advanced countries. This paper examines the division of roles between the private sector and the government in order to achieve a successful structural adjustment, which has become the impending industrial policy issue caused by high domestic wages, on the one hand, and the opening of domestic markets, on the other. The micro foundation of the economy-wide structural adjustment is actually the restructuring of business portfolios at the firm level. The firm-level business restructuring means that firms in low-value-added businesses or with declining market niches establish new major businesses in higher value-added segments or growing market niches. The adjustment of the business structure at the firm level can only be accomplished by accumulating firm-specific managerial assets necessary to establish a new business structure. This can be done through learning-by-doing in the whole system of management, including research and development, manufacturing, and marketing. Therefore, the voluntary cooperation among the people in the company is essential for making the cost of the learning process lower than that at the competing companies. Hence, firms that attempt to restructure their major businesses need to induce corporate-wide participation through innovations in organization and management, encourage innovative corporate culture, and maintain cooperative labor unions. Policy discussions on structural adjustments usually regard firms as a black box behind a few macro variables. But in reality, firm activities are not flows of materials but relationships among human resources. The growth potential of companies are embodied in the human resources of the firm; the balance of interest among stockholders, managers, and workers of the company' brings the accumulation of the company's core competencies. Therefore, policymakers and economists shoud change their old concept of the firm as a technological black box which produces a marketable commodities. Firms should be regarded as coalitions of interest groups such as stockholders, managers, and workers. Consequently the discussion on the structural adjustment both at the macroeconomic level and the firm level should be based on this new paradigm of understanding firms. The government's role in reducing the cost of structural adjustment and supporting should the creation of new industries emphasize the following: First, government must promote the competition in domestic markets by revising laws related to antitrust policy, bankruptcy, and the promotion of small and medium-sized companies. General consensus on the limitations of government intervention and the merit of deregulation should be sought among policymakers and people in the business world. In the age of internationalization, nation-specific competitive advantages cannot be exclusively in favor of domestic firms. The international competitiveness of a domestic firm derives from the firm-specific core competencies which can be accumulated by internal investment and organization of the firm. Second, government must build up a solid infrastructure of production factors including capital, technology, manpower, and information. Structural adjustment often entails bankruptcies and partial waste of resources. However, it is desirable for the government not to try to sustain marginal businesses, but to support the diversification or restructuring of businesses by assisting in factor creation. Institutional support for venture businesses needs to be improved, especially in the financing system since many investment projects in venture businesses are highly risky, even though they are very promising. The proportion of low-value added production processes and declining industries should be reduced by promoting foreign direct investment and factory automation. Moreover, one cannot over-emphasize the importance of future-oriented labor policies to be based on the new paradigm of understanding firm activities. The old laws and instititutions related to labor unions need to be reformed. Third, government must improve the regimes related to money, banking, and the tax system to change business practices dependent on government protection or undesirable in view of the evolution of the Korean economy as a whole. To prevent rational business decisions from contradicting to the interest of the economy as a whole, government should influence the business environment, not the business itself.

• 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.

• Archives of design research
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• v.18 no.4 s.62
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• pp.53-64
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• 2005

The emergence of new communication media, digital, is something of a wonder, as well as a cultural tension. The industrial technologies that dramatically expand human abilities are being developed much faster than the speed of adaptation by humans. Without an exception, it creates new contents and form of the culture by shaking the very foundation of the notion about human beings. Korean broadcasting environment has stepped into the era of multi-media, multi-channel as the digital technology separated the media into network, cable, satellite and internet. In this digital culture, broadcasting, as a medium of information delivering and communication, has bigger influence than ever. Such changes in broadcasting environment turned the TV viewers into new consumers who participate and play the main role in active communication by choosing and using the media. This study is trying to systemize the question about the core identity of broadcasting through brand as the consumers stand in the center of broadcasting with the power to select channel. The story schema theory can be applied as a cognitive psychological tool to approach the active consumers in order to explain the cognitive processes that are related to information processing. It is a design with stories, which comes up as a case of a brand's story telling. The range of this study covers the current issue and educational programs in network TV during the period of May and August of year 2005. The cases of Korean and foreign programs were compared by the station each program is broadcasted. This study concludes that it is important to take the channel identity into the consideration in the brand strategy of each program. Especially, the leading programs of a station must not be treated as a separate program that has nothing to do with the station's identity. They must be treated to include the contents and form that builds the identity of the channel. Also, this study reconfirmed that building a brand of the anchor person can play as an important factor in the identity of the program's brand.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.1-23
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• 2014

Market forecasting aims to estimate the sales volume of a product or service that is sold to consumers for a specific selling period. From the perspective of the enterprise, accurate market forecasting assists in determining the timing of new product introduction, product design, and establishing production plans and marketing strategies that enable a more efficient decision-making process. Moreover, accurate market forecasting enables governments to efficiently establish a national budget organization. This study aims to generate a market growth curve for ICT (information and communication technology) goods using past time series data; categorize products showing similar growth patterns; understand markets in the industry; and forecast the future outlook of such products. This study suggests the useful and meaningful process (or methodology) to identify the market growth pattern with quantitative growth model and data mining algorithm. The study employs the following methodology. At the first stage, past time series data are collected based on the target products or services of categorized industry. The data, such as the volume of sales and domestic consumption for a specific product or service, are collected from the relevant government ministry, the National Statistical Office, and other relevant government organizations. For collected data that may not be analyzed due to the lack of past data and the alteration of code names, data pre-processing work should be performed. At the second stage of this process, an optimal model for market forecasting should be selected. This model can be varied on the basis of the characteristics of each categorized industry. As this study is focused on the ICT industry, which has more frequent new technology appearances resulting in changes of the market structure, Logistic model, Gompertz model, and Bass model are selected. A hybrid model that combines different models can also be considered. The hybrid model considered for use in this study analyzes the size of the market potential through the Logistic and Gompertz models, and then the figures are used for the Bass model. The third stage of this process is to evaluate which model most accurately explains the data. In order to do this, the parameter should be estimated on the basis of the collected past time series data to generate the models' predictive value and calculate the root-mean squared error (RMSE). The model that shows the lowest average RMSE value for every product type is considered as the best model. At the fourth stage of this process, based on the estimated parameter value generated by the best model, a market growth pattern map is constructed with self-organizing map algorithm. A self-organizing map is learning with market pattern parameters for all products or services as input data, and the products or services are organized into an $N{\times}N$ map. The number of clusters increase from 2 to M, depending on the characteristics of the nodes on the map. The clusters are divided into zones, and the clusters with the ability to provide the most meaningful explanation are selected. Based on the final selection of clusters, the boundaries between the nodes are selected and, ultimately, the market growth pattern map is completed. The last step is to determine the final characteristics of the clusters as well as the market growth curve. The average of the market growth pattern parameters in the clusters is taken to be a representative figure. Using this figure, a growth curve is drawn for each cluster, and their characteristics are analyzed. Also, taking into consideration the product types in each cluster, their characteristics can be qualitatively generated. We expect that the process and system that this paper suggests can be used as a tool for forecasting demand in the ICT and other industries.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.187-201
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• 2011

KOSPI200 index is the Korean stock price index consisting of actively traded 200 stocks in the Korean stock market. Its base value of 100 was set on January 3, 1990. The Korea Exchange (KRX) developed derivatives markets on the KOSPI200 index. KOSPI200 index futures market, introduced in 1996, has become one of the most actively traded indexes markets in the world. Traders can make profit by entering a long position on the KOSPI200 index futures contract if the KOSPI200 index will rise in the future. Likewise, they can make profit by entering a short position if the KOSPI200 index will decline in the future. Basically, KOSPI200 index futures trading is a short-term zero-sum game and therefore most futures traders are using technical indicators. Advanced traders make stable profits by using system trading technique, also known as algorithm trading. Algorithm trading uses computer programs for receiving real-time stock market data, analyzing stock price movements with various technical indicators and automatically entering trading orders such as timing, price or quantity of the order without any human intervention. Recent studies have shown the usefulness of artificial intelligent systems in forecasting stock prices or investment risk. KOSPI200 index data is numerical time-series data which is a sequence of data points measured at successive uniform time intervals such as minute, day, week or month. KOSPI200 index futures traders use technical analysis to find out some patterns on the time-series chart. Although there are many technical indicators, their results indicate the market states among bull, bear and flat. Most strategies based on technical analysis are divided into trend following strategy and non-trend following strategy. Both strategies decide the market states based on the patterns of the KOSPI200 index time-series data. This goes well with Markov model (MM). Everybody knows that the next price is upper or lower than the last price or similar to the last price, and knows that the next price is influenced by the last price. However, nobody knows the exact status of the next price whether it goes up or down or flat. So, hidden Markov model (HMM) is better fitted than MM. HMM is divided into discrete HMM (DHMM) and continuous HMM (CHMM). The only difference between DHMM and CHMM is in their representation of state probabilities. DHMM uses discrete probability density function and CHMM uses continuous probability density function such as Gaussian Mixture Model. KOSPI200 index values are real number and these follow a continuous probability density function, so CHMM is proper than DHMM for the KOSPI200 index. In this paper, we present an artificial intelligent trading system based on CHMM for the KOSPI200 index futures system traders. Traders have experienced on technical trading for the KOSPI200 index futures market ever since the introduction of the KOSPI200 index futures market. They have applied many strategies to make profit in trading the KOSPI200 index futures. Some strategies are based on technical indicators such as moving averages or stochastics, and others are based on candlestick patterns such as three outside up, three outside down, harami or doji star. We show a trading system of moving average cross strategy based on CHMM, and we compare it to a traditional algorithmic trading system. We set the parameter values of moving averages at common values used by market practitioners. Empirical results are presented to compare the simulation performance with the traditional algorithmic trading system using long-term daily KOSPI200 index data of more than 20 years. Our suggested trading system shows higher trading performance than naive system trading.