• Journal of the Korean Society of Food Science and Nutrition
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• v.46 no.7
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• pp.876-885
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• 2017

This study aimed to identify the characteristics of Home Meal Replacement (HMR) product purchases and the need for HMR product development for Hong Kong consumers in order to suggest market segmentation strategies according to consumers' dietary lifestyle. For this, an online survey was conducted on a panel of 521 Hong Kong consumers with HMR purchase experience registered at a specialized organization. Data analysis was performed using SPSS (ver. 23.0). HMR purchase characteristics of Hong Kong consumers according to dietary lifestyle showed significant differences in all items, including 'number of purchases', 'purchase location', 'cost of single purchase', and 'reason for purchase'. According to dietary lifestyle, participants were divided into three clusters: 'High interest', 'normal interest', and 'low interest'. In the case of 'high interest in dietary life group', 'low-sodium food' was the most common, followed by 'heating food', 'low sugar food', and 'low calorie food'. In the case of 'moderate interest in dietary life group', 'low-sodium food' was the most common, followed by 'low sugar food', 'low calorie food', and 'nutritious meal'. In the case of 'low interest in dietary life group', 'low sugar food' was the most common, followed by 'low-sodium food', 'various new menu', and 'easy-to-carry dehydrated food'. For the 'high interest' group, the highest proportion of consumers were male in between the ages of 20 to 29, married, and worked in an office job. The 'high interest' consumers also showed a tendency to pay '15,000 to 20,000 KRW' per single purchase. The 'normal interest' group consisted of an even proportion of male and female consumers, with the most common age range being from 30 to 39 years, and most were married. These consumers preferred to spend 'less than 10,000 KRW' or '10,000 KRW to 15,000 KRW' per single purchase, which is in the lower price range for HMR purchases. The 'low interest in dietary life group' had more females gender-wise, were unmarried, and worked in an office job, For a single purchase, the 'low interest' group chose to pay less than 10,000 KRW, which is relatively lower than the other two clusters. The results of this study can be used as baseline data for building marketing strategies for HMR product development. It can also provide basic data and directions for new HMR export products that reflect consumer needs in order to create a market segmentation strategy for industrial applications.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.149-169
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• 2020

"The Urban Renewal New Deal project", one of the government's major national projects, is about developing underdeveloped areas by investing 50 trillion won in 100 locations on the first year and 500 over the next four years. This project is drawing keen attention from the media and local governments. However, the project model which fails to reflect the original characteristics of the area as it divides project area into five categories: "Our Neighborhood Restoration, Housing Maintenance Support Type, General Neighborhood Type, Central Urban Type, and Economic Base Type," According to keywords for successful urban regeneration in Korea, "resident participation," "regional specialization," "ministerial cooperation" and "public-private cooperation", when local governments propose urban regeneration projects to the government, they can see that it is most important to accurately understand the characteristics of the city and push ahead with the projects in a way that suits the characteristics of the city with the help of local residents and private companies. In addition, considering the gentrification problem, which is one of the side effects of urban regeneration projects, it is important to select and implement urban regeneration types suitable for the characteristics of the area. In order to supplement the limitations of the 'Urban Regeneration New Deal Project' methodology, this study aims to propose a system that recommends urban regeneration types suitable for urban regeneration sites by utilizing various machine learning algorithms, referring to the urban regeneration types of the '2025 Seoul Metropolitan Government Urban Regeneration Strategy Plan' promoted based on regional characteristics. There are four types of urban regeneration in Seoul: "Low-use Low-Level Development, Abandonment, Deteriorated Housing, and Specialization of Historical and Cultural Resources" (Shon and Park, 2017). In order to identify regional characteristics, approximately 100,000 text data were collected for 22 regions where the project was carried out for a total of four types of urban regeneration. Using the collected data, we drew key keywords for each region according to the type of urban regeneration and conducted topic modeling to explore whether there were differences between types. As a result, it was confirmed that a number of topics related to real estate and economy appeared in old residential areas, and in the case of declining and underdeveloped areas, topics reflecting the characteristics of areas where industrial activities were active in the past appeared. In the case of the historical and cultural resource area, since it is an area that contains traces of the past, many keywords related to the government appeared. Therefore, it was possible to confirm political topics and cultural topics resulting from various events. Finally, in the case of low-use and under-developed areas, many topics on real estate and accessibility are emerging, so accessibility is good. It mainly had the characteristics of a region where development is planned or is likely to be developed. Furthermore, a model was implemented that proposes urban regeneration types tailored to regional characteristics for regions other than Seoul. Machine learning technology was used to implement the model, and training data and test data were randomly extracted at an 8:2 ratio and used. In order to compare the performance between various models, the input variables are set in two ways: Count Vector and TF-IDF Vector, and as Classifier, there are 5 types of SVM (Support Vector Machine), Decision Tree, Random Forest, Logistic Regression, and Gradient Boosting. By applying it, performance comparison for a total of 10 models was conducted. The model with the highest performance was the Gradient Boosting method using TF-IDF Vector input data, and the accuracy was 97%. Therefore, the recommendation system proposed in this study is expected to recommend urban regeneration types based on the regional characteristics of new business sites in the process of carrying out urban regeneration projects."

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.25-38
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• 2019

Selecting high-quality information that meets the interests and needs of users among the overflowing contents is becoming more important as the generation continues. In the flood of information, efforts to reflect the intention of the user in the search result better are being tried, rather than recognizing the information request as a simple string. Also, large IT companies such as Google and Microsoft focus on developing knowledge-based technologies including search engines which provide users with satisfaction and convenience. Especially, the finance is one of the fields expected to have the usefulness and potential of text data analysis because it's constantly generating new information, and the earlier the information is, the more valuable it is. Automatic knowledge extraction can be effective in areas where information flow is vast, such as financial sector, and new information continues to emerge. However, there are several practical difficulties faced by automatic knowledge extraction. First, there are difficulties in making corpus from different fields with same algorithm, and it is difficult to extract good quality triple. Second, it becomes more difficult to produce labeled text data by people if the extent and scope of knowledge increases and patterns are constantly updated. Third, performance evaluation is difficult due to the characteristics of unsupervised learning. Finally, problem definition for automatic knowledge extraction is not easy because of ambiguous conceptual characteristics of knowledge. So, in order to overcome limits described above and improve the semantic performance of stock-related information searching, this study attempts to extract the knowledge entity by using neural tensor network and evaluate the performance of them. Different from other references, the purpose of this study is to extract knowledge entity which is related to individual stock items. Various but relatively simple data processing methods are applied in the presented model to solve the problems of previous researches and to enhance the effectiveness of the model. From these processes, this study has the following three significances. First, A practical and simple automatic knowledge extraction method that can be applied. Second, the possibility of performance evaluation is presented through simple problem definition. Finally, the expressiveness of the knowledge increased by generating input data on a sentence basis without complex morphological analysis. The results of the empirical analysis and objective performance evaluation method are also presented. The empirical study to confirm the usefulness of the presented model, experts' reports about individual 30 stocks which are top 30 items based on frequency of publication from May 30, 2017 to May 21, 2018 are used. the total number of reports are 5,600, and 3,074 reports, which accounts about 55% of the total, is designated as a training set, and other 45% of reports are designated as a testing set. Before constructing the model, all reports of a training set are classified by stocks, and their entities are extracted using named entity recognition tool which is the KKMA. for each stocks, top 100 entities based on appearance frequency are selected, and become vectorized using one-hot encoding. After that, by using neural tensor network, the same number of score functions as stocks are trained. Thus, if a new entity from a testing set appears, we can try to calculate the score by putting it into every single score function, and the stock of the function with the highest score is predicted as the related item with the entity. To evaluate presented models, we confirm prediction power and determining whether the score functions are well constructed by calculating hit ratio for all reports of testing set. As a result of the empirical study, the presented model shows 69.3% hit accuracy for testing set which consists of 2,526 reports. this hit ratio is meaningfully high despite of some constraints for conducting research. Looking at the prediction performance of the model for each stocks, only 3 stocks, which are LG ELECTRONICS, KiaMtr, and Mando, show extremely low performance than average. this result maybe due to the interference effect with other similar items and generation of new knowledge. In this paper, we propose a methodology to find out key entities or their combinations which are necessary to search related information in accordance with the user's investment intention. Graph data is generated by using only the named entity recognition tool and applied to the neural tensor network without learning corpus or word vectors for the field. From the empirical test, we confirm the effectiveness of the presented model as described above. However, there also exist some limits and things to complement. Representatively, the phenomenon that the model performance is especially bad for only some stocks shows the need for further researches. Finally, through the empirical study, we confirmed that the learning method presented in this study can be used for the purpose of matching the new text information semantically with the related stocks.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.63-83
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• 2019

Investors prefer to look for trading points based on the graph shown in the chart rather than complex analysis, such as corporate intrinsic value analysis and technical auxiliary index analysis. However, the pattern analysis technique is difficult and computerized less than the needs of users. In recent years, there have been many cases of studying stock price patterns using various machine learning techniques including neural networks in the field of artificial intelligence(AI). In particular, the development of IT technology has made it easier to analyze a huge number of chart data to find patterns that can predict stock prices. Although short-term forecasting power of prices has increased in terms of performance so far, long-term forecasting power is limited and is used in short-term trading rather than long-term investment. Other studies have focused on mechanically and accurately identifying patterns that were not recognized by past technology, but it can be vulnerable in practical areas because it is a separate matter whether the patterns found are suitable for trading. When they find a meaningful pattern, they find a point that matches the pattern. They then measure their performance after n days, assuming that they have bought at that point in time. Since this approach is to calculate virtual revenues, there can be many disparities with reality. The existing research method tries to find a pattern with stock price prediction power, but this study proposes to define the patterns first and to trade when the pattern with high success probability appears. The M & W wave pattern published by Merrill(1980) is simple because we can distinguish it by five turning points. Despite the report that some patterns have price predictability, there were no performance reports used in the actual market. The simplicity of a pattern consisting of five turning points has the advantage of reducing the cost of increasing pattern recognition accuracy. In this study, 16 patterns of up conversion and 16 patterns of down conversion are reclassified into ten groups so that they can be easily implemented by the system. Only one pattern with high success rate per group is selected for trading. Patterns that had a high probability of success in the past are likely to succeed in the future. So we trade when such a pattern occurs. It is a real situation because it is measured assuming that both the buy and sell have been executed. We tested three ways to calculate the turning point. The first method, the minimum change rate zig-zag method, removes price movements below a certain percentage and calculates the vertex. In the second method, high-low line zig-zag, the high price that meets the n-day high price line is calculated at the peak price, and the low price that meets the n-day low price line is calculated at the valley price. In the third method, the swing wave method, the high price in the center higher than n high prices on the left and right is calculated as the peak price. If the central low price is lower than the n low price on the left and right, it is calculated as valley price. The swing wave method was superior to the other methods in the test results. It is interpreted that the transaction after checking the completion of the pattern is more effective than the transaction in the unfinished state of the pattern. Genetic algorithms(GA) were the most suitable solution, although it was virtually impossible to find patterns with high success rates because the number of cases was too large in this simulation. We also performed the simulation using the Walk-forward Analysis(WFA) method, which tests the test section and the application section separately. So we were able to respond appropriately to market changes. In this study, we optimize the stock portfolio because there is a risk of over-optimized if we implement the variable optimality for each individual stock. Therefore, we selected the number of constituent stocks as 20 to increase the effect of diversified investment while avoiding optimization. We tested the KOSPI market by dividing it into six categories. In the results, the portfolio of small cap stock was the most successful and the high vol stock portfolio was the second best. This shows that patterns need to have some price volatility in order for patterns to be shaped, but volatility is not the best.

• The Korean Journal of Air & Space Law and Policy
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• v.32 no.1
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• pp.83-138
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• 2017

Korea-China FTA entered into force on the 20th of December 2015, and one year elapsed after its effectuation as the FTA with China, our country's largest trading partner. Therefore, this study looks at the trends of air transport trade between Korea and China, and examines the contents of concessions to the air transport services sector in Korea-China FTA, and analyzes the impact on the air transport sector by Korea-China FTA, and proposes our country's aviation policy direction in order to respond to such impact. In 2016 the trends of air transport trade between Korea and China are as follows : The export amount of air transport trade to China was 40.03 billion dollars, down by 9.3% from the last year, and occupied 32.2% of the total export amount to China. The import amount of air transport trade from China was 24.26 billion dollars, down by 9.1% from the last year, and occupied 27.7% of the total import amount from China. The contents of concessions to the air transport services sector in Korea-China FTA are as follows : China made concessions to the aircraft repair and maintenance services and the computer reservation system services with limitations on market access and national treatment in the air transport services sector of the China Schedule of Specific Commitments of Korea-China FTA Chapter 8 Annex. Korea made concessions to the computer reservation system services, selling and marketing of air transport services, and aircraft repair and maintenance without limitations on market access and national treatment in the air transport services sector of the Korea Schedule of Specific Commitments of Korea-China FTA Chapter 8 Annex. The impact on the air transport sector by Korea-China FTA are as follows : As for the impact on the air passenger market, in 2016 the arrival passengers of the international flight from China were 9.96 million, up by 20.6% from the last year, and the departure passengers to China were 9.90 million, up by 34.8% from the last year. As for the impact on the air cargo market, in 2016 the exported goods volumes of air cargo to China were 105,220.2 tons, up by 6.6% from the last year, and imported goods volumes from China were 133,750.9 tons, up by 12.3% from the last year. Among the major items of exported air cargo to China, the exported goods volumes of benefited items in the Tariff Schedule of China of Korea-China FTA were increased, and among the major items of imported air cargo from China, the imported goods volumes of benefited items in the Tariff Schedule of Korea of Korea-China FTA were increased. As for the impact on the logistics market, in 2016 the handling performance of exported air cargo to China by domestic forwarders were 119,618 tons, down by 2.1% from the last year, and the handling performance of imported air cargo from China were 79,430 tons, down by 4.4% from the last year. In 2016 the e-commerce export amount to China were 109.16 million dollars, up by 27.7% from the last year, and the e-commerce import amount from China were 89.43 million dollars, up by 72% from the last year. The author proposes the aviation policy direction of Korea according to Korea-China FTA as follows : First, the open skies between Korea and China shall be pushed ahead. In June 2006 Korea and China concluded the open skies agreement within the scope of the third freedom and fourth freedom of the air for passenger and cargo in Sandong Province and Hainan Province of China, and agreed the full open skies of flights between the two countries from the summer season in 2010. However, China protested against the interpretation of the draft of the memorandum of understanding to the air services agreement, therefore the further open skies did not take place. Through the separate aviation talks with China from Korea-China FTA, the gradual and selective open skies of air passenger market and air cargo market shall be pushed ahead. Second, the competitiveness of air transport industry and airport shall be secured. As for the strengthening methods of the competitiveness of Korea's air transport industry, the support system for the strengthening of national air carriers' competitiveness shall be prepared, and the new basis for competition of national air carriers shall be made, and the strategic network based on national interest shall be built. As for the strengthening methods of the competitiveness of Korea's airports, particularly Incheon Airport, the competitiveness of the network for aviation demand creation shall be strengthened, and the airport facilities and safety infrastructure shall be expanded, and the new added value through the airport shall be created, and the world's No.1 level of services shall be maintained. Third, the competitiveness of aviation logistics enterprises shall be strengthened. As for the strengthening methods of the competitiveness of Korea's aviation logistics enterprises, as the upbringing strategy of higher added value in response to the industry trends changes, the new logistics market shall be developed, and the logistics infrastructure shall be expanded, and the logistics professionals shall be trained. Additionally, as the expanding strategy of global logistics market, the support system for overseas investment of logistics enterprises shall be built, and according to expanding the global transport network, the international cooperation shall be strengthened, and the network infrastructure shall be secured. As for the strengthening methods of aviation logistics competitiveness of Incheon Airport, the enterprises' demand of moving in the logistics complex shall be responded, and the comparative advantage in the field of new growth cargo shall be preoccupied, and the logistics hub's capability shall be strengthened, and the competitiveness of cargo processing speed in the airport shall be advanced. Forth, in the subsequent negotiation of Korea-China FTA, the further opening of air transport services sector shall be secured. In the subsequent negotiation being initiated within two years after entry into force of Korea-China FTA, it is necessary to ask for the further opening of the concessions of computer reservation system services, and aircraft repair and maintenance services in which the concessions level of air transport services sector by China is insufficient compared to the concessions level in the existing FTA concluded by China. In conclusion, in order to respond to the impact on Korea's air passenger market, air cargo market and aviation logistics market by Korea-China FTA, the following policy tasks shall be pushed ahead : Taking into consideration of national air carriers' competitiveness and nation's benefits, the gradual and selective open skies shall be pushed ahead, and the support system to strengthen the competitiveness of air transport industry and airport shall be built, and entry into aviation logistics market by logistics enterprises shall be expanded, and the preparations to ask for the further opening of air transport services sector, low in the concessions level by China shall be made.

• Journal of Distribution Research
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• v.17 no.4
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• pp.81-101
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• 2012

A franchise system develops competitive products for a franchise store through the system established by the franchise head office. Therefore, it has advantages of expanding the marketing effect since the risk of failure is reduced for a founder and the franchise head office supports the overall sales, advertisement and promotional activities. Also, a franchise store has advantages of fulfilling necessary facilities and tools on advantageous terms, reducing expenses by purchasing in bulk, and getting a supply of products with stable qualities. However, aside from such advantages, franchise head offices are forcing franchise stores to make unnecessary investments in equipments and remodel the interior. Also, franchise business operators are being made to share the cost of marketing and multiple franchise stores are being approved within the same business district, and franchise business operators are suffering damages. Therefore, cases of shutting down a franchise store or not renewing the contract are frequent. From the position of a franchise head office, profits that are generated from franchise fees, interior remodeling fees and supplying facilities and materials will increase as the number of new franchise stores increases. However, franchise stores are faced with difficulties due to excessive competitions between similar types of businesses and the overlapping of business districts that come from increases in the number of stores, and they eventually end up shutting down. Therefore, in order for a franchise business operator and franchise head office to grow and develop continuously, opening new stores is important, but successfully renewing the contract by maintaining a relationship with an existing franchise business operator is desirable. In this aspect, a study that examines the elements that can affect the relationship between a franchise business operator and franchise head office is believed to be important for the development of the franchise industry and creating safe jobs for the public. With an emphasis on the relationship between a franchise head office and franchise store, this study attempted to examine the effect of characteristics of a franchise head office and franchise business operator on the bilateral relationship such as the faith and immersion, and wished to review the effects of such faith and immersion on the satisfaction of a franchise store, including an intention of renewing the contract. In particular, in the current situation of great uncertainties in the market, this study also wished to examine how uncertain market elements will affect the relationship between the characteristics of a franchise head office and franchise business operator, and the faith and immersion. The study revealed that among the characteristics of a franchise head office, the standardization management of a franchise head office hinders a franchise store's faith and immersion in a franchise head office. Also, a franchise head office's support was shown to increase a franchise store's faith and immersion. However, it was revealed that a franchise head office's regulation and incentive policies for a franchise store do not affect a franchise store's faith and immersion. Among characteristics of a franchise business operator, a franchise store's healthy financial status and entrepreneur spirits were shown to enhance the faith and immersion in a franchise head office. However, it was shown that excellent business abilities of a franchise business operator actually reduce the immersion for a franchise head office. Also, the faith and immersion in a franchise head office were shown to enhance the intention of renewing the contract by increasing the satisfaction for a franchise head office. In addition, it was originally believed that the effects of a franchise business operator's characteristics on the faith and immersion in a franchise head office will vary depending on the market uncertainty, but the effect of a franchise business operator's characteristics depending on the recognition of uncertainties was shown to be insignificant. Such findings show that instead of making a franchise store pay for equipment investments and marketing and obtaining profits by force, a franchise head office should actively support a franchise store so that a franchise store's business activities can be conducted well, which will bring profits to a franchise store and ultimately to a franchise head office. This is a more desirable direction for the development of both parties. Implications of such findings are summarized as follows. First, it was shown that a franchise head office's standardization management actually reduces a franchise store's faith and immersion. Therefore, it is believed that instead of conducting standardization managements for regulating and managing franchise stores, measures should be developed so that franchise stores can actually participate voluntarily. For this, a head office should put in efforts to develop and provide standardized manuals, and make sure that a self-review system takes root. Second, a franchise head office's incentives did not have significant effects on the faith and immersion, but the support was shown to be effective. Therefore, it can be seen that instead of taking post-measures for a franchise store, taking pre-measures of actively supporting is more effective in maintaining a franchise store. Third, among characteristics of a franchise head office, it was shown that a franchise store's healthy financial status increased the faith and immersion in a franchise head office. Therefore, when selecting a franchise business operator, instead of thoughtlessly opening up franchise stores for the profit of a head office, it is believed that reviewing a franchise business operator's financial firepower and credit status is necessary. As for academic implications, previous studies examined the relationship by focusing on the characteristics of a franchise head office and franchise store, but this study focused on the characteristics of a franchise business operator. Therefore, this study dealt with the importance of a franchise business operator's competence, and is significant because it revealed the fact that a franchise business operator's excellent commercialization ability can become an element that hinders the immersion in a franchise head office. It was originally believed that a franchise store's characteristics will have different effects on the faith and immersion depending on the market uncertainty, but it was shown that the effect of a franchise store's characteristics depending on the recognition of uncertainties was insignificant, and that is the limitation of this study.