• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.95-108
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• 2017

Recently, AlphaGo which is Bakuk (Go) artificial intelligence program by Google DeepMind, had a huge victory against Lee Sedol. Many people thought that machines would not be able to win a man in Go games because the number of paths to make a one move is more than the number of atoms in the universe unlike chess, but the result was the opposite to what people predicted. After the match, artificial intelligence technology was focused as a core technology of the fourth industrial revolution and attracted attentions from various application domains. Especially, deep learning technique have been attracted as a core artificial intelligence technology used in the AlphaGo algorithm. The deep learning technique is already being applied to many problems. Especially, it shows good performance in image recognition field. In addition, it shows good performance in high dimensional data area such as voice, image and natural language, which was difficult to get good performance using existing machine learning techniques. However, in contrast, it is difficult to find deep leaning researches on traditional business data and structured data analysis. In this study, we tried to find out whether the deep learning techniques have been studied so far can be used not only for the recognition of high dimensional data but also for the binary classification problem of traditional business data analysis such as customer churn analysis, marketing response prediction, and default prediction. And we compare the performance of the deep learning techniques with that of traditional artificial neural network models. The experimental data in the paper is the telemarketing response data of a bank in Portugal. It has input variables such as age, occupation, loan status, and the number of previous telemarketing and has a binary target variable that records whether the customer intends to open an account or not. In this study, to evaluate the possibility of utilization of deep learning algorithms and techniques in binary classification problem, we compared the performance of various models using CNN, LSTM algorithm and dropout, which are widely used algorithms and techniques in deep learning, with that of MLP models which is a traditional artificial neural network model. However, since all the network design alternatives can not be tested due to the nature of the artificial neural network, the experiment was conducted based on restricted settings on the number of hidden layers, the number of neurons in the hidden layer, the number of output data (filters), and the application conditions of the dropout technique. The F1 Score was used to evaluate the performance of models to show how well the models work to classify the interesting class instead of the overall accuracy. The detail methods for applying each deep learning technique in the experiment is as follows. The CNN algorithm is a method that reads adjacent values from a specific value and recognizes the features, but it does not matter how close the distance of each business data field is because each field is usually independent. In this experiment, we set the filter size of the CNN algorithm as the number of fields to learn the whole characteristics of the data at once, and added a hidden layer to make decision based on the additional features. For the model having two LSTM layers, the input direction of the second layer is put in reversed position with first layer in order to reduce the influence from the position of each field. In the case of the dropout technique, we set the neurons to disappear with a probability of 0.5 for each hidden layer. The experimental results show that the predicted model with the highest F1 score was the CNN model using the dropout technique, and the next best model was the MLP model with two hidden layers using the dropout technique. In this study, we were able to get some findings as the experiment had proceeded. First, models using dropout techniques have a slightly more conservative prediction than those without dropout techniques, and it generally shows better performance in classification. Second, CNN models show better classification performance than MLP models. This is interesting because it has shown good performance in binary classification problems which it rarely have been applied to, as well as in the fields where it's effectiveness has been proven. Third, the LSTM algorithm seems to be unsuitable for binary classification problems because the training time is too long compared to the performance improvement. From these results, we can confirm that some of the deep learning algorithms can be applied to solve business binary classification problems.

• Asia pacific journal of information systems
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• v.20 no.4
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• pp.53-79
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• 2010

The study was originated from recognition that project participants' satisfaction should be Improved to raise project performance and to make progress of a successful project since the above dissatisfaction was operated as a danger factor of the project. The study selected one large-scale sample project and attempted measuring characteristics of the project, participants' satisfaction and project performance with the whole project participants. The study analyzed correlations between individual level (team members) and group level (development team), and examined what effect a sub project manager under complicated hierarchical organization of the large-scale project, namely PL (project leader)'s leadership style had on each individual project participant's satisfaction and what effect project uncertainty in organization/technology environment had on project participants' satisfaction and project performance. The study verified that development team (group) had an effect on team member (individual)-level project participants' satisfaction by disclosing that there was a significant dispersion among groups within project participants' satisfaction by each individual. It is analyzed that it is necessary to make improvement through approach by each pertinent team to raise individual-level project participants' satisfaction. The study also verified PL's ideal leadership under strict methodology and hierarchical control of the large-scale project. Based on the verification of the hypotheses, the results of the analysis were produced as follows. First, the development team affects the satisfaction level that an individual has when he/she participates in a project. This suggests that the satisfaction with project participation should be improved at the team level. In addition, the project management style and leadership orientation of the manager of a sub project who is mostly affected by the team proved to have a direct influence on the satisfaction with project participation and project performances. Second, both the performance-oriented leadership and the relationship-oriented leadership of the PL of the development team were verified to have a significant effect on the satisfaction of the team members associated with project participation. In other words, when the team members recognize that the PL of the development team shows both the performance-oriented leadership and the relationship-oriented leadership, their satisfaction with project participation increases accordingly. Third, it was verified that the uncertainty of the organizational environment significantly affects the satisfaction level when the PL of the development team exerts a relationship-oriented and performance-oriented leadership. The higher the uncertainty of the organizational environment is, the more the satisfaction with project participation decreases whereas the relationship-oriented leadership has a more positive effect on the satisfaction than the performance-oriented leadership style. Fourth, when the PL of the development team exerts the relationship-related and performance-related leadership, the uncertainty of the technological environment has a significant influence on the satisfaction level. The higher the uncertainty of the technological environment is, the more the satisfaction with project participation decreases whereas the performance-oriented leadership has a more positive effect on the satisfaction than the relationship-oriented leadership style. The result of the research on the uncertainty of the project environment suggests that when the development team leader exerts a relationship-oriented and performance-oriented leadership style, the uncertainty of the organizational environment has a significant effect on the satisfaction with project participation; the higher the uncertainty of the organizational environment, the more the satisfaction level decreases, and the relationship-oriented leadership style affects the satisfaction level more positively than the performance-oriented leadership style. In addition, when the development team leader displays a relationship-oriented and performance-oriented leadership style, the uncertainty of the technological environment has a significant effect on the satisfaction with project participation; the higher the uncertainty of the technological environment. the more the satisfaction level decreases. The performance-oriented leadership style as well affects the satisfaction level more positively than the relationship-oriented leadership style. Based on the above results, the research provides the following implications when handling multiple concurrent projects. First, the satisfaction with the participation in the multiple concurrent projects needs to be enhanced at the team (group) level. Second. the manager of the project team, particularly the middle managers should have both a performance-oriented and relationship (task and human)-oriented attitude and exert a consolidated leadership in order to improve the satisfaction of team members with project participation and their performances. Third, as the uncertainty factor of the technological and organizational environment among the characteristics factors of the project has room for methodological improvement depending on one's effort even though there are some complications, we need to continuously prevent and control the risks resulting from the uncertainties of the technological and organizational environment of the project in order to enhance the satisfaction of project participation and project performances. Fourth, the performance (task)-oriented leadership is required when there is uncertainty in a technological environment while the relationship (human)-oriented leadership is required when there is uncertainty in an organizational environment. This research has the following limitations. First, this research intended to select one large-sized sample project and measure the project characteristics, the satisfaction of all the participants associated with project participation, and their performances. Therefore, it is inappropriate to generalize and apply the result of this result onto other numerous projects. Second, as this case study entailed a survey to measure the characteristics factors and performance of the project, since the result value was based on the perception of project team members, the data may have insufficient objectivity. Third, though this research targeted on all the project participants, some development teams did not provide sufficient data and questionnaires were collected from some specific development teams among the 23 development teams, causing a significant deviation in the response rate among the development teams. Therefore, we need to continuously conduct the follow-up researches making comparisons among the multiple projects, and centering on the characteristics factors of the project and its satisfaction level.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.91-108
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• 2020

Korea's famous soccer players are steadily performing well in international leagues, which led to higher interests of Korean fans in the international leagues. Reflecting the growing social phenomenon of rising interests on international leagues by Korean fans, the study examined the overall consumer perception in the consumption of uniform by domestic soccer fans and compared the changes in perception following the transfers of the players. Among others, the paper examined the consumer perception and purchase factors of soccer fans shown in social media, focusing on periods before and after the recruitment of Heung-Min Son to English Premier League's Tottenham Football Club. To this end, the EPL uniform is the collection keyword the paper utilized and collected consumer postings from domestic website and social media via Python 3.7, and analyzed them using Ucinet 6, NodeXL 1.0.1, and SPSS 25.0 programs. The results of this study can be summarized as follows. First, the uniform of the club that consistently topped the league, has been gaining attention as a popular uniform, and the players' performance, and the players' position have been identified as key factors in the purchase and search of professional football uniforms. In the case of the club, the actual ranking and whether the league won are shown to be important factors in the purchase and search of professional soccer uniforms. The club's emblem and the sponsor logo that will be attached to the uniform are also factors of interest to consumers. In addition, in the decision making process of purchase of a uniform by professional soccer fan, uniform's form, marking, authenticity, and sponsors are found to be more important than price, design, size, and logo. The official online store has emerged as a major purchasing channel, followed by gifts for friends or requests from acquaintances when someone travels to the United Kingdom. Second, a classification of key control categories through the convergence of iteration correlation analysis and Clauset-Newman-Moore clustering algorithm shows differences in the classification of individual groups, but groups that include the EPL's club and player keywords are identified as the key topics in relation to professional football uniforms. Third, between 2002 and 2006, the central theme for professional football uniforms was World Cup and English Premier League, but from 2012 to 2015, the focus has shifted to more interest of domestic and international players in the English Premier League. The subject has changed to the uniform itself from this time on. In this context, the paper can confirm that the major issues regarding the uniforms of professional soccer players have changed since Ji-Sung Park's transfer to Manchester United, and Sung-Yong Ki, Chung-Yong Lee, and Heung-Min Son's good performances in these leagues. The paper also identified that the uniforms of the clubs to which the players have transferred to are of interest. Fourth, both male and female consumers are showing increasing interest in Son's league, the English Premier League, which Tottenham FC belongs to. In particular, the increasing interest in Son has shown a tendency to increase interest in football uniforms for female consumers. This study presents a variety of researches on sports consumption and has value as a consumer study by identifying unique consumption patterns. It is meaningful in that the accuracy of the interpretation has been enhanced by using a cluster analysis via convergence of iteration correlation analysis and Clauset-Newman-Moore clustering algorithm to identify the main topics. Based on the results of this study, the clubs will be able to maximize its profits and maintain good relationships with fans by identifying key drivers of consumer awareness and purchasing for professional soccer fans and establishing an effective marketing strategy.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.141-154
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• 2019

Rapid growth of internet technology and social media is progressing. Data mining technology has evolved to enable unstructured document representations in a variety of applications. Sentiment analysis is an important technology that can distinguish poor or high-quality content through text data of products, and it has proliferated during text mining. Sentiment analysis mainly analyzes people's opinions in text data by assigning predefined data categories as positive and negative. This has been studied in various directions in terms of accuracy from simple rule-based to dictionary-based approaches using predefined labels. In fact, sentiment analysis is one of the most active researches in natural language processing and is widely studied in text mining. When real online reviews aren't available for others, it's not only easy to openly collect information, but it also affects your business. In marketing, real-world information from customers is gathered on websites, not surveys. Depending on whether the website's posts are positive or negative, the customer response is reflected in the sales and tries to identify the information. However, many reviews on a website are not always good, and difficult to identify. The earlier studies in this research area used the reviews data of the Amazon.com shopping mal, but the research data used in the recent studies uses the data for stock market trends, blogs, news articles, weather forecasts, IMDB, and facebook etc. However, the lack of accuracy is recognized because sentiment calculations are changed according to the subject, paragraph, sentiment lexicon direction, and sentence strength. This study aims to classify the polarity analysis of sentiment analysis into positive and negative categories and increase the prediction accuracy of the polarity analysis using the pretrained IMDB review data set. First, the text classification algorithm related to sentiment analysis adopts the popular machine learning algorithms such as NB (naive bayes), SVM (support vector machines), XGboost, RF (random forests), and Gradient Boost as comparative models. Second, deep learning has demonstrated discriminative features that can extract complex features of data. Representative algorithms are CNN (convolution neural networks), RNN (recurrent neural networks), LSTM (long-short term memory). CNN can be used similarly to BoW when processing a sentence in vector format, but does not consider sequential data attributes. RNN can handle well in order because it takes into account the time information of the data, but there is a long-term dependency on memory. To solve the problem of long-term dependence, LSTM is used. For the comparison, CNN and LSTM were chosen as simple deep learning models. In addition to classical machine learning algorithms, CNN, LSTM, and the integrated models were analyzed. Although there are many parameters for the algorithms, we examined the relationship between numerical value and precision to find the optimal combination. And, we tried to figure out how the models work well for sentiment analysis and how these models work. This study proposes integrated CNN and LSTM algorithms to extract the positive and negative features of text analysis. The reasons for mixing these two algorithms are as follows. CNN can extract features for the classification automatically by applying convolution layer and massively parallel processing. LSTM is not capable of highly parallel processing. Like faucets, the LSTM has input, output, and forget gates that can be moved and controlled at a desired time. These gates have the advantage of placing memory blocks on hidden nodes. The memory block of the LSTM may not store all the data, but it can solve the CNN's long-term dependency problem. Furthermore, when LSTM is used in CNN's pooling layer, it has an end-to-end structure, so that spatial and temporal features can be designed simultaneously. In combination with CNN-LSTM, 90.33% accuracy was measured. This is slower than CNN, but faster than LSTM. The presented model was more accurate than other models. In addition, each word embedding layer can be improved when training the kernel step by step. CNN-LSTM can improve the weakness of each model, and there is an advantage of improving the learning by layer using the end-to-end structure of LSTM. Based on these reasons, this study tries to enhance the classification accuracy of movie reviews using the integrated CNN-LSTM model.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.1-25
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• 2020

Sentiment Analysis (SA) is a Natural Language Processing (NLP) task that analyzes the sentiments consumers or the public feel about an arbitrary object from written texts. Furthermore, Aspect-Based Sentiment Analysis (ABSA) is a fine-grained analysis of the sentiments towards each aspect of an object. Since having a more practical value in terms of business, ABSA is drawing attention from both academic and industrial organizations. When there is a review that says "The restaurant is expensive but the food is really fantastic", for example, the general SA evaluates the overall sentiment towards the 'restaurant' as 'positive', while ABSA identifies the restaurant's aspect 'price' as 'negative' and 'food' aspect as 'positive'. Thus, ABSA enables a more specific and effective marketing strategy. In order to perform ABSA, it is necessary to identify what are the aspect terms or aspect categories included in the text, and judge the sentiments towards them. Accordingly, there exist four main areas in ABSA; aspect term extraction, aspect category detection, Aspect Term Sentiment Classification (ATSC), and Aspect Category Sentiment Classification (ACSC). It is usually conducted by extracting aspect terms and then performing ATSC to analyze sentiments for the given aspect terms, or by extracting aspect categories and then performing ACSC to analyze sentiments for the given aspect category. Here, an aspect category is expressed in one or more aspect terms, or indirectly inferred by other words. In the preceding example sentence, 'price' and 'food' are both aspect categories, and the aspect category 'food' is expressed by the aspect term 'food' included in the review. If the review sentence includes 'pasta', 'steak', or 'grilled chicken special', these can all be aspect terms for the aspect category 'food'. As such, an aspect category referred to by one or more specific aspect terms is called an explicit aspect. On the other hand, the aspect category like 'price', which does not have any specific aspect terms but can be indirectly guessed with an emotional word 'expensive,' is called an implicit aspect. So far, the 'aspect category' has been used to avoid confusion about 'aspect term'. From now on, we will consider 'aspect category' and 'aspect' as the same concept and use the word 'aspect' more for convenience. And one thing to note is that ATSC analyzes the sentiment towards given aspect terms, so it deals only with explicit aspects, and ACSC treats not only explicit aspects but also implicit aspects. This study seeks to find answers to the following issues ignored in the previous studies when applying the BERT pre-trained language model to ACSC and derives superior ACSC models. First, is it more effective to reflect the output vector of tokens for aspect categories than to use only the final output vector of [CLS] token as a classification vector? Second, is there any performance difference between QA (Question Answering) and NLI (Natural Language Inference) types in the sentence-pair configuration of input data? Third, is there any performance difference according to the order of sentence including aspect category in the QA or NLI type sentence-pair configuration of input data? To achieve these research objectives, we implemented 12 ACSC models and conducted experiments on 4 English benchmark datasets. As a result, ACSC models that provide performance beyond the existing studies without expanding the training dataset were derived. In addition, it was found that it is more effective to reflect the output vector of the aspect category token than to use only the output vector for the [CLS] token as a classification vector. It was also found that QA type input generally provides better performance than NLI, and the order of the sentence with the aspect category in QA type is irrelevant with performance. There may be some differences depending on the characteristics of the dataset, but when using NLI type sentence-pair input, placing the sentence containing the aspect category second seems to provide better performance. The new methodology for designing the ACSC model used in this study could be similarly applied to other studies such as ATSC.

• Journal of Korea Entertainment Industry Association
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• v.15 no.8
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• pp.19-31
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• 2021

This study tried to identify the characteristics of college students' entrepreneurial intentions in the entertainment industry, focusing on existing literature studies. Based on this, it was intended to suggest realistic educational alternatives for university student start-ups and implications for start-up management to university start-up officials and those in charge of national start-up support policy. Therefore, the implications of this study are as follows. First, technology(item) for idea creation education, which is an essential element in the entertainment industry, how to connect ideas and products, technology methods that can increase content value, and user characteristics education within the entertainment industry will need to be continued. In addition, along with the idea education, it is necessary to increase the understanding of start-up business management such as financing, human resource management, marketing, and operation management, and furthermore, confidence education should be provided so that the possibility of success in an entertainment start-up and a sense of adventure in a new job can be developed. Second, the space and equipment necessary for start-up (club room, student start-up room, entertainment-related equipment, etc.) should be provided centering on the opinion survey of students who are interested in starting a business, and various regulations of universities and government for student start-up should be relaxed. will have to In addition, education for the formation of entrepreneurial knowledge inside and outside of the school, special lectures and consultations by experts, and on-the-spot education, etc., should be made to create more practical entrepreneurial knowledge. something to do. Third, for students wishing to start a business in the entertainment industry, it is necessary to inform their families about the field situation of the entertainment industry accurately so that their children can develop a positive perception rather than a negative perception when choosing a business field. In addition, by promoting various successful cases of college students to their families after starting a business, families should be encouraged so that their children can develop a challenging spirit about starting a business. Fourth, it should be possible to form continuous clubs or gatherings with friends who wish to start a business in the entertainment industry, and furthermore, an opportunity to listen to the opinions of friends who actually started a business through these meetings should be provided. In addition, the meeting and the formation of friends should create a place for discussion about writing a business plan, how to succeed in starting a business, and management of startups, and psychological stimulation activities should be conducted so that each other's will to start a business arises. Fifth, various knowledge related to start-up (methods for securing funds, management of start-up organizations, grasping information about the market in which they want to start a business, etc.) should be cultivated, and how to write a business plan for the various entertainment industry fields they want to start up. You will also need to train them to be practical. Also, based on this knowledge formation, students themselves should be able to respond to risks and changes that may occur in entrepreneurship. Lastly, it is necessary to increase the understanding of business start-up management, and various psychological stimulation activities are needed to make the confidence and fear of starting a business disappear.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.6
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• pp.58-69
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• 2022

This study compares and analyses the impacts of holding domestic garden expos that will be fundamental for holding garden expos in the future. Satisfaction with the three sites of the 2013 Suncheon Bay International Gardening Expo, 2015 Seoul Gardening Expo, and 2022 Goyang International Flower Fair, as well as factors affecting the satisfaction in economic, social/cultural, environment/ecology, and operation aspects, were analyzed. As a result of the study, the satisfaction level of all three sites was high, with a value of 3.5 or higher. In particular, satisfaction with the 2013 Suncheon Bay International Gardening Expo was the highest. It was found that there was a difference between the satisfaction level of the 2013 Suncheon Bay International Gardening Expo and the 2015 Seoul Gardening Expo. As a regional festival, the 2013 Suncheon Bay International Garden Expo has acquired a high status due to the 'Suncheon Bay Garden' being designated as the first National Garden. It is thought that great satisfaction was obtained because economic, social, cultural, and environmental revitalization was achieved by matching the values of citizen participation and ecological conservation. As a result of the comparison of perception types affecting the satisfaction by garden fair, satisfaction at the 2013 Suncheon Bay International Gardening Expo and the 2015 Seoul Gardening Expo, it was found that both affected all four aspects. The 2022 Goyang International Flower Fair did not affect satisfaction in the operational aspect. This seems to be because the Goyang International Flower Fair is already a fixed local brand. As a result of analyzing the detailed factors of perception that affect satisfaction, the three target sites were commonly analyzed, including social and cultural factors, which attract cultural events, improve pride and affection for the region, and help educate children. In terms of environmental and ecological factors were analyzed as an inconvenience in life due to traffic congestion. It can be seen that it has the same meaning as the comparative analysis of the difference in factors on the satisfaction of the target site. There is no difference in the effect on satisfaction in terms of social·cultural, and environmental·ecological aspects, but there are differences in terms of economy and operation. Based on the analysis results of this study, to hold a domestic garden expo in the future, it is necessary to properly utilize "environmental" and "ecological" garden aspects that have potential values according to the region's characteristics to develop sustainable, eco-friendly tourism resources. In addition, values will be more apparent when cultural and artistic programs are planned to establish a differentiated identity in the host area and are appropriately used as a marketing means for a local fair. A well-planned local festival through communication with local residents can affect the image of the region and lead to the revitalization of the local communities by securing urban competitiveness along with the establishment of urban brands, so it can be said that local residents' participation and national or local organizations' cooperation is essential.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.77-110
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• 2017

Recently, the diversification and individualization of consumption patterns through the web and mobile devices based on the Internet have been rapid. As this happens, the efficient operation of the offline store, which is a traditional distribution channel, has become more important. In order to raise both the sales and profits of stores, stores need to supply and sell the most attractive products to consumers in a timely manner. However, there is a lack of research on which SKUs, out of many products, can increase sales probability and reduce inventory costs. In particular, if a company sells products through multiple in-store stores across multiple locations, it would be helpful to increase sales and profitability of stores if SKUs appealing to customers are recommended. In this study, the recommender system (recommender system such as collaborative filtering and hybrid filtering), which has been used for personalization recommendation, is suggested by SKU recommendation method of a store unit of a distribution company that handles a homogeneous brand through a plurality of sales stores by country and region. We calculated the similarity of each store by using the purchase data of each store's handling items, filtering the collaboration according to the sales history of each store by each SKU, and finally recommending the individual SKU to the store. In addition, the store is classified into four clusters through PCA (Principal Component Analysis) and cluster analysis (Clustering) using the store profile data. The recommendation system is implemented by the hybrid filtering method that applies the collaborative filtering in each cluster and measured the performance of both methods based on actual sales data. Most of the existing recommendation systems have been studied by recommending items such as movies and music to the users. In practice, industrial applications have also become popular. In the meantime, there has been little research on recommending SKUs for each store by applying these recommendation systems, which have been mainly dealt with in the field of personalization services, to the store units of distributors handling similar brands. If the recommendation method of the existing recommendation methodology was 'the individual field', this study expanded the scope of the store beyond the individual domain through a plurality of sales stores by country and region and dealt with the store unit of the distribution company handling the same brand SKU while suggesting a recommendation method. In addition, if the existing recommendation system is limited to online, it is recommended to apply the data mining technique to develop an algorithm suitable for expanding to the store area rather than expanding the utilization range offline and analyzing based on the existing individual. The significance of the results of this study is that the personalization recommendation algorithm is applied to a plurality of sales outlets handling the same brand. A meaningful result is derived and a concrete methodology that can be constructed and used as a system for actual companies is proposed. It is also meaningful that this is the first attempt to expand the research area of the academic field related to the existing recommendation system, which was focused on the personalization domain, to a sales store of a company handling the same brand. From 05 to 03 in 2014, the number of stores' sales volume of the top 100 SKUs are limited to 52 SKUs by collaborative filtering and the hybrid filtering method SKU recommended. We compared the performance of the two recommendation methods by totaling the sales results. The reason for comparing the two recommendation methods is that the recommendation method of this study is defined as the reference model in which offline collaborative filtering is applied to demonstrate higher performance than the existing recommendation method. The results of this model are compared with the Hybrid filtering method, which is a model that reflects the characteristics of the offline store view. The proposed method showed a higher performance than the existing recommendation method. The proposed method was proved by using actual sales data of large Korean apparel companies. In this study, we propose a method to extend the recommendation system of the individual level to the group level and to efficiently approach it. In addition to the theoretical framework, which is of great value.

• 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.