• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.19
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• pp.224-242
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• 2003

The author believes that the main task of study in international trade usage and practice is the management of transactional risks involved in international sale of goods. They are foreign exchange risks, transportation risks, credit risk, risk of miscommunication, etc. In most cases, these risks are more serious and enormous than those involved in domestic sales. Historically, the merchant adventurers organized the voyage abroad, secured trade finance, and went around the ocean with their own or consigned cargo until around the $mid-19^{th}$ century. They did business faceto-face at the trade fair or the open port where they maintained the local offices, so-called "Trading House"(商館). Thererfore, the transactional risks might have been one-sided either with the seller or the buyer. The bottomry seemed a typical arrangement for risk sharing among the interested parties to the adventure. In this way, such organizational arrangements coped with or bore the transactional risks. With the advent of ocean liner services and wireless communication across the national border in the $19^{th}$ century, the business of merchant adventurers developed toward the clear division of labor; sales by mercantile agents, and ocean transportation by the steam ship companies. The international banking helped the process to be accelerated. Then, bills of lading backed up by the statute made it possible to conduct documentary sales with a foreign partner in different country. Thus, FOB terms including ocean freight and CIF terms emerged gradually as standard trade terms in which transactional risks were allocated through negotiation between the seller and the buyer located in different countries. Both of them did not have to go abroad with their cargo. Instead, documentation in compliance with the terms of the contract(plus an L/C in some cases) must by 'strictly' fulfilled. In other words, the set of contractual documents must be tendered in advance of the arrival of the goods at port of discharge. Trust or reliance is placed on such contractual paper documents. However, the container transport services introduced as international intermodal transport since the late 1960s frequently caused the earlier arrival of the goods at the destination before the presentation of the set of paper documents, which may take 5 to 10% of the amount of transaction. In addition, the size of the container vessel required the speedy transport documentation before sailing from the port of loading. In these circumstances, computerized processing of transport related documents became essential for inexpensive transaction cost and uninterrupted distribution of the goods. Such computerization does not stop at the phase of transportation but extends to cover the whole process of international trade, transforming the documentary sales into less-paper trade and further into paperless trade, i.e., EDI or E-Commerce. Now we face the other side of the coin, which is data security and paperless transfer of legal rights and obligations. Unfortunately, these issues are not effectively covered by a set of contracts only. Obviously, EDI or E-Commerce is based on the common business process and harmonized system of various data codes as well as the standard message formats. This essential feature of E-Commerce needs effective coordination of different divisions of business and tight control over credit arrangements in addition to the standard contract of sales. In a few word, information does not alway invite "trust". Credit flows from people, or close organizational tie-ups. It is our common understanding that, without well-orchestrated organizational arrangements made by leading companies, E-Commerce does not work well for paperless trade. With such arrangements well in place, participating E-business members do not need to seriously care for credit risk. Finally, it is also clear that E-International Commerce must be linked up with a set of government EDIs such as NACCS, Port EDI, JETRAS, etc, in Japan. Therefore, there is still a long way before us to go for E-Commerce in practice, not on the top of information manager's desk.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.221-241
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• 2018

Deep learning is getting attention recently. The deep learning technique which had been applied in competitions of the International Conference on Image Recognition Technology(ILSVR) and AlphaGo is Convolution Neural Network(CNN). CNN is characterized in that the input image is divided into small sections to recognize the partial features and combine them to recognize as a whole. Deep learning technologies are expected to bring a lot of changes in our lives, but until now, its applications have been limited to image recognition and natural language processing. The use of deep learning techniques for business problems is still an early research stage. If their performance is proved, they can be applied to traditional business problems such as future marketing response prediction, fraud transaction detection, bankruptcy prediction, and so on. So, it is a very meaningful experiment to diagnose the possibility of solving business problems using deep learning technologies based on the case of online shopping companies which have big data, are relatively easy to identify customer behavior and has high utilization values. Especially, in online shopping companies, the competition environment is rapidly changing and becoming more intense. Therefore, analysis of customer behavior for maximizing profit is becoming more and more important for online shopping companies. In this study, we propose 'CNN model of Heterogeneous Information Integration' using CNN as a way to improve the predictive power of customer behavior in online shopping enterprises. In order to propose a model that optimizes the performance, which is a model that learns from the convolution neural network of the multi-layer perceptron structure by combining structured and unstructured information, this model uses 'heterogeneous information integration', 'unstructured information vector conversion', 'multi-layer perceptron design', and evaluate the performance of each architecture, and confirm the proposed model based on the results. In addition, the target variables for predicting customer behavior are defined as six binary classification problems: re-purchaser, churn, frequent shopper, frequent refund shopper, high amount shopper, high discount shopper. In order to verify the usefulness of the proposed model, we conducted experiments using actual data of domestic specific online shopping company. This experiment uses actual transactions, customers, and VOC data of specific online shopping company in Korea. Data extraction criteria are defined for 47,947 customers who registered at least one VOC in January 2011 (1 month). The customer profiles of these customers, as well as a total of 19 months of trading data from September 2010 to March 2012, and VOCs posted for a month are used. The experiment of this study is divided into two stages. In the first step, we evaluate three architectures that affect the performance of the proposed model and select optimal parameters. We evaluate the performance with the proposed model. Experimental results show that the proposed model, which combines both structured and unstructured information, is superior compared to NBC(Naïve Bayes classification), SVM(Support vector machine), and ANN(Artificial neural network). Therefore, it is significant that the use of unstructured information contributes to predict customer behavior, and that CNN can be applied to solve business problems as well as image recognition and natural language processing problems. It can be confirmed through experiments that CNN is more effective in understanding and interpreting the meaning of context in text VOC data. And it is significant that the empirical research based on the actual data of the e-commerce company can extract very meaningful information from the VOC data written in the text format directly by the customer in the prediction of the customer behavior. Finally, through various experiments, it is possible to say that the proposed model provides useful information for the future research related to the parameter selection and its performance.

• International Commerce and Information Review
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• v.13 no.4
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• pp.51-79
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• 2011

Korea has accomplished the establishment of the National Single Window for Paperless Trade. Since 1991, it has developed Trade Automation Service System based on EDI technology. In 2003, Korean government and private sectors jointly began to set up National Paperless Trade Service( e-Trade Service) as one of the e-government projects. In 2008, they commenced the uTradeHub Service which was equipped with Internet based e-B/L and e-Nego service systems for the first time in the world To facilitate the service Korea amended its e-Trade facilitation Act and Law by 2007. At the end of 2011, Korea historically recorded its trade volume of 1 trillion US dollars and joined '$1 trillion trade club' as the 9the member country since the country had started international trade less than five decades ago. A rolling out of the e-B/L and e-Nego service will 'ally reduce the transaction costs of trading businesses and accelerate the activation e-trade services. The purposes of the study are to examine 'e-B/L Korea' service and its facilitation strategies as well as identify obstacles to utilize the 'e-B/L Korea' service. The paper reviewed and analyzed Korea's Paperless trade system and distinctive characteristics of the 'e-B/L Korea Service. Parts of the fOWld distinctive characteristics of the Korea's e-B/L service are as follows; It is well equiped with IT and legal system. It also has more that 30,000 potential users who are already uTradeHub service users. The paper indicated several weaknesses of the current system such as global KPI issues, circulation of the electronic documents not only in the domestic market but also among economies, development of the electronic Bill of Exchange. As resolution measures, the paper recommended the introduction of mutual recognition system of PKI among trade partner counties, setting up e-trade solution for small and medium companies, and special attention to raise users' awareness of the e-B/L service.