Proceedings of the Korean Institute of Navigation and Port Research Conference
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2002.03a
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pp.39-51
/
2002
Online exchange is a cost-effective approach to trade goods and information among multiple sellers and buyers. Shipping industry includes lots of global entities such as shippers, liners, ship owners and shipping agents. Marine insurance companies and ship repairers and many other groups are also supporting the industry. However, international shipping exchanges are located on few cities in the world. Its our motivation that a shipping market can be online so that market participants do the dealing while sitting where they are with more efficient manner, preferable price and larger pool of candidates of trading partners. This paper presents Korean governmental project of building a cyber shipping exchange. The exchange covers ship sale and purchase, charter, insurance, freight futures, repairs, supplying of ships oil and database service. The workflows of each business were analyzed and designed to fit for online environment. The project includes design of trading mechanism, online documents, data flow, data storage and security. Online match making and trading mechanisms such as auction, reverse auction, bid are used. The whole trading process involves multiple organizations and business processes. So, this Paper focuses on how each organization would play their roles so that users can complete transactions with integrated and transparent view. The online exchange selves also as maritime portal site that links to other sites for cooperation vertically or horizontally, and serves database and information in global perspective. This paper also issues and discusses the justification of an online shipping exchange
In this study, we tried to examine the effect of service quality on the current industrial product B2B trading market on the degree of sustainable purchase for employees engaged in industrial product B2B trading market. We gathered data from questionnaires from employees who worked in the industrial product B2B trading market for this research. Empirical analysis is carried out through the collected questionnaire materials and finally the research model is finally verified using reliability analysis, validity analysis, discrimination validity analysis, and structural equation model fitness test, and finally Analysis of differences between cooperating companies and vendor, analysis of differences between companies engaged in purchasing industrial materials and developers. The results of the research analysis did not positively influence the quality of the relationship with relativity satisfaction with ease of information exchange and adaptability did not have a positive influence on the quality of the relationship. However, product service exchange, product development cooperation, adaptability, correspondence, reliability had a positive influence on the quality of relationship with relation satisfaction. Relationship of parameters The satisfaction has a positive influence on the quality of the relationship, the degree of sustainable purchase, and eventually the quality of the relationship has a positive influence on each successive purchase. By using the results of this research it is possible to confirm the factors which directly or indirectly influence the strengthening of the relationship between suppliers and purchasers in the industrial material B2B trading market and provide the basis for strategy to B2B trading companies It seems to be meaningful to offer.
By the continued island-mainland bridging works, increased consumer demand for seashore regions and fundamental improvement of accessibility to metropolitan areas, rural service industries in the island areas has been rapidly developed in the past decades, and also, their functions differentiated geographically. In most island areas, catering and accommodation sectors have been expanded, while traditional trading sector decreasing. And the dominant power of public sectors has been increased but private ones decreased. So, the overall development trends of service industries in island areas would be considered as unhealthy for rural economic sustainability. As a tentative solution, it may be proposed that through the functional specialization/differentiation and efficient linking/networking of rural service industries with multifunctionality of countryside capitals, their spatial cohesion would be strengthened.
Journal of the Korea Society of Computer and Information
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v.17
no.7
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pp.175-184
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2012
The purpose of this study is to investigate the home trading system (HTS) of the security companies in order to examine the critical factors of HTS service quality and the effect of these factors on HTS customer satisfaction and loyalty. The results show : (1) the quality factors of HTS are assurance, reliability, tangible, responsiveness, and empathy, (2) and these quality factors significantly affect customer satisfaction on HTS and customer satisfaction and loyalty to the security company. (3) Also, customer satisfaction on HTS plays an important role in improving customer satisfaction and loyalty to the security company.
This study quantifies the dynamic interrelationship between the KOSPI index return and search query data derived from the Naver DataLab. The empirical estimation using a bivariate GARCH model reveals that negative contemporaneous correlations between the stock return and the search frequency prevail during the sample period. Meanwhile, the search frequency has a negative association with the one-week- ahead stock return but not vice versa. In addition to identifying dynamic correlations, the paper also aims to serve as a test bed in which the existence of profitable trading strategies based on big data is explored. Specifically, the strategy interpreting the heightened investor attention as a negative signal for future returns appears to have been superior to the benchmark strategy in terms of the expected utility over wealth. This paper also demonstrates that the big data-based option trading strategy might be able to beat the market under certain conditions. These results highlight the possibility of big data as a potential source-which has been left largely untapped-for establishing profitable trading strategies as well as developing insights on stock market dynamics.
Competitive and reliable maritime transport services benefit the economy as a whole, and are key efficiency factors for the production of both goods and services. Although maritime transport sector is very liberalized compared to many other service sectors, certain obstacles must be overcome before full liberalization of the maritime transport can be realized. Particularly, maritime transport services in Northeast Asia are regulated by a complicated and outdated system. To remove these barkers two approaches can be used: a regional trading arrangement approach and a multilateral approach via WTO. However, multilateral efforts are not likely to be successful in achieving any concrete progress towards maritime transport liberalization in the short- to medium-term in Northeast Asia. Consequently, it may be the best to take the following two progressive approaches and to make them work towards liberalization of the maritime transport market: a bilateral approach and a trilateral approach. A gradual process of liberalization would expand the market, help operators achieve economies of scale, promote the international division of labor and specialization, enhance the effective management of shipping services, and promote the long-term interests and welfare of the user by improving service quality and diversifying services. A liberalized and integrated maritime transport market in Northeast Asia should achieve both of these long-run policy objectives by benefiting both the transport service users and the transport service providers. In order to move the maritime transport liberalization programs as quickly as possible, it is desirable to establish a "Regional Maritime Transport Liberalization Committee." We suggest it to be a Tripartite (China, Japan and Korea) Committee initially, which can later expand its membership to include other Northeast Asian countries.
The Transactions of the Korea Information Processing Society
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v.7
no.4
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pp.1050-1061
/
2000
This paper presents a new object model, LOM(Lightweight Object Model) and an implementation method for the distributed trader in heterogeneous distributed computing environment including mobile network. Trader is third party object that enables clients to find suitable servers, which provide the most appropriate services to client in distributed environment including dynamic reconfiguration of services and servers. Trading service requires simpler and more specific object model than genetic object models which provide richer multimedia data types and semantic characteristics with complex data structures. LOM supports a new reference attribute type instead of the relationship, inheritance and composite attribute types of the general object oriented models and so LOM has simple data structures. Also in LOM, the modelling step includes specifying of the information about users and the access right to objects for security in the mobile environment and development of the distributed storage for trading service. Also, we propose and implementation method of the distributed trader, which integrates the LOM-information object model and the OMG (object Management Group) computational object model.
Machine learning is a field of artificial intelligence. It refers to an area of computer science related to providing machines the ability to perform their own data analysis, decision making and forecasting. For example, one of the representative machine learning models is artificial neural network, which is a statistical learning algorithm inspired by the neural network structure of biology. In addition, there are other machine learning models such as decision tree model, naive bayes model and SVM(support vector machine) model. Among the machine learning models, we use SVM model in this study because it is mainly used for classification and regression analysis that fits well to our study. The core principle of SVM is to find a reasonable hyperplane that distinguishes different group in the data space. Given information about the data in any two groups, the SVM model judges to which group the new data belongs based on the hyperplane obtained from the given data set. Thus, the more the amount of meaningful data, the better the machine learning ability. In recent years, many financial experts have focused on machine learning, seeing the possibility of combining with machine learning and the financial field where vast amounts of financial data exist. Machine learning techniques have been proved to be powerful in describing the non-stationary and chaotic stock price dynamics. A lot of researches have been successfully conducted on forecasting of stock prices using machine learning algorithms. Recently, financial companies have begun to provide Robo-Advisor service, a compound word of Robot and Advisor, which can perform various financial tasks through advanced algorithms using rapidly changing huge amount of data. Robo-Adviser's main task is to advise the investors about the investor's personal investment propensity and to provide the service to manage the portfolio automatically. In this study, we propose a method of forecasting the Korean volatility index, VKOSPI, using the SVM model, which is one of the machine learning methods, and applying it to real option trading to increase the trading performance. VKOSPI is a measure of the future volatility of the KOSPI 200 index based on KOSPI 200 index option prices. VKOSPI is similar to the VIX index, which is based on S&P 500 option price in the United States. The Korea Exchange(KRX) calculates and announce the real-time VKOSPI index. VKOSPI is the same as the usual volatility and affects the option prices. The direction of VKOSPI and option prices show positive relation regardless of the option type (call and put options with various striking prices). If the volatility increases, all of the call and put option premium increases because the probability of the option's exercise possibility increases. The investor can know the rising value of the option price with respect to the volatility rising value in real time through Vega, a Black-Scholes's measurement index of an option's sensitivity to changes in the volatility. Therefore, accurate forecasting of VKOSPI movements is one of the important factors that can generate profit in option trading. In this study, we verified through real option data that the accurate forecast of VKOSPI is able to make a big profit in real option trading. To the best of our knowledge, there have been no studies on the idea of predicting the direction of VKOSPI based on machine learning and introducing the idea of applying it to actual option trading. In this study predicted daily VKOSPI changes through SVM model and then made intraday option strangle position, which gives profit as option prices reduce, only when VKOSPI is expected to decline during daytime. We analyzed the results and tested whether it is applicable to real option trading based on SVM's prediction. The results showed the prediction accuracy of VKOSPI was 57.83% on average, and the number of position entry times was 43.2 times, which is less than half of the benchmark (100 times). A small number of trading is an indicator of trading efficiency. In addition, the experiment proved that the trading performance was significantly higher than the benchmark.
When existing trade creates a product, a series of processes is terminated when a seller or a buyer subscribes for transportation insurance and is guided through customs procedures according to the terms of the sales contract and then receives payment for it. Training practical Trade kowhow is also educated focusing on the procedures of these contracts. A new paradigm of the fourth industrial revolution was launched in the development of information communication technology and computer technology. Also, due to the Xinhuo tradeism triggered by the United States, the risk of commodity trading is further increasing. Currently, trade practical education of university and industry is carried out for most lecture and discussion. Since 2014, the curriculumof the department of trade has been increasingly managed by the NCS process. The curriculumof the department of trade department has the advantage of being managed in consideration of the characteristics of the company that wishes to find employment and the level of work content. Standardized, the curriculumcan faithfully reflect the characteristics of the company and the level of the work content. In the new era, a new educational method that reflects the trend of the 4th industrial revolution era is necessary. In this research, we propose that service trade practical education should be educated mainly on contracts, not on procedural basis as with traditional commodity trade education.
As volume of international trade is growing importance for service business and service trade are also increasing. Increasing importance of service trade in Korea is also a reflection of such international trading. In this treatise this writer did not address various topics in relation to international trade arising from service trade. But confined the topic to study of concept of service and concept and patterns of service trade. Depending on scholars concept of service may be varied and this holds true also with concept of service trade which also lends itself to various classification. Among them if the focus is concentrated to tax standard in international trade then it can be classified into service transaction. In other words classification can be made according to service trade separated from commodities transaction with embodiment of service and service trade accompanying commodities transaction. In this treatise this writer confined the topic to introduction of international service trade but issues arising in relation to such trade internationally are varied. For this reason more study on such topics will be required in future.
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