• Journal of Arbitration Studies
• /
• v.8 no.1
• /
• pp.3-33
• /
• 1998

Since the Start of WTO in 1995, world trade volume was substantially increased as much as over $250 billion by lifting the trade barriors This effect brought new problem of increasing disputes. Significantly an ever increasing atention is paid to the Question of means and procedures of settling such disputes by arbtration. The problem of arbitration has indeed become most popular with all those who take interest in legal aspects of international cooperation in various spheres. In practice arbitration seems to renovate its function to take over new disputes arising from electronic transaction such as internet trade. Looking at the actual use of arbitration, its merits than litigation should cover new aspect concerning new kind of claims caused by new type of transaction. The efficient procedure for dispute will help every country save loss of profit by the delay of settlment. This thesis aims to facilitate the appearence of more efficient arbitration procedure for dispute settlment system.

• Journal of Intelligence and Information Systems
• /
• v.21 no.1
• /
• pp.161-177
• /
• 2015

With the rapid evolution of technology, the size, number, and the type of databases has increased concomitantly, so data mining approaches face many challenging applications from databases. One such application is discovery of fraud patterns from agricultural product wholesale transaction instances. The agricultural product wholesale market in Korea is huge, and vast numbers of transactions have been made every day. The demand for agricultural products continues to grow, and the use of electronic auction systems raises the efficiency of operations of wholesale market. Certainly, the number of unusual transactions is also assumed to be increased in proportion to the trading amount, where an unusual transaction is often the first sign of fraud. However, it is very difficult to identify and detect these transactions and the corresponding fraud occurred in agricultural product wholesale market because the types of fraud are more intelligent than ever before. The fraud can be detected by verifying the overall transaction records manually, but it requires significant amount of human resources, and ultimately is not a practical approach. Frauds also can be revealed by victim's report or complaint. But there are usually no victims in the agricultural product wholesale frauds because they are committed by collusion of an auction company and an intermediary wholesaler. Nevertheless, it is required to monitor transaction records continuously and to make an effort to prevent any fraud, because the fraud not only disturbs the fair trade order of the market but also reduces the credibility of the market rapidly. Applying data mining to such an environment is very useful since it can discover unknown fraud patterns or features from a large volume of transaction data properly. The objective of this research is to empirically investigate the factors necessary to detect fraud transactions in an agricultural product wholesale market by developing a data mining based fraud detection model. One of major frauds is the phantom transaction, which is a colluding transaction by the seller(auction company or forwarder) and buyer(intermediary wholesaler) to commit the fraud transaction. They pretend to fulfill the transaction by recording false data in the online transaction processing system without actually selling products, and the seller receives money from the buyer. This leads to the overstatement of sales performance and illegal money transfers, which reduces the credibility of market. This paper reviews the environment of wholesale market such as types of transactions, roles of participants of the market, and various types and characteristics of frauds, and introduces the whole process of developing the phantom transaction detection model. The process consists of the following 4 modules: (1) Data cleaning and standardization (2) Statistical data analysis such as distribution and correlation analysis, (3) Construction of classification model using decision-tree induction approach, (4) Verification of the model in terms of hit ratio. We collected real data from 6 associations of agricultural producers in metropolitan markets. Final model with a decision-tree induction approach revealed that monthly average trading price of item offered by forwarders is a key variable in detecting the phantom transaction. The verification procedure also confirmed the suitability of the results. However, even though the performance of the results of this research is satisfactory, sensitive issues are still remained for improving classification accuracy and conciseness of rules. One such issue is the robustness of data mining model. Data mining is very much data-oriented, so data mining models tend to be very sensitive to changes of data or situations. Thus, it is evident that this non-robustness of data mining model requires continuous remodeling as data or situation changes. We hope that this paper suggest valuable guideline to organizations and companies that consider introducing or constructing a fraud detection model in the future.

• Journal of Korea Port Economic Association
• /
• v.38 no.1
• /
• pp.1-14
• /
• 2022

The change in the management environment of the logistics industry in the era of global competition is becoming an era in which customers choose companies. Differentiation from competitors through the provision of products and services suitable for customers As customers' choices change depending on their superiority, companies are constantly striving to receive or retain customers' choices. Ultimately, this competitive structure can be seen as the importance of long-term relationship building. Therefore, in this study, we examined how factors related to transaction characteristics performed by logistics companies for customer satisfaction in the transaction relationship between cargo companies and shippers affect performance and long-term transaction intentions. First, we derived the factors of logistics service, cost, logistics infrastructure, and company competency, which are transaction characteristics factors of a logistics company that must be specifically realized for customer satisfaction in transactions between logistics companies. Second, we analyzed how the transaction characteristics factors of a logistics company affect the company's performance, and finally, how the company's performance factors affect long-term transaction intentions. As a result of empirical analysis, there were no statistically significant results on the relationship between transaction characteristics and performance of logistics companies, which can be attributed to the small size of the logistics companies that were the sample. In other words, logistics companies that do not have sufficient capacity to provide services at low prices have no choice but to engage in constant bleeding competition. It can be seen that it reflects the characteristics of the industry. On the other hand, the relationship between corporate performance factors and long-term transaction intention was found to have a positive relationship. The higher the level of partnership with logistics companies and visible financial performance is, the higher the transaction will be in the future, and the more the transaction volume will be gradually increased. And even if it costs a little more, it can be seen that the intention to continue trading is greatly expressed.

• Environmental and Resource Economics Review
• /
• v.21 no.1
• /
• pp.27-67
• /
• 2012

This paper analyzed the effect of transaction costs on the prices and trading volumes at the initial stage of emission markets and also examined how the size of the effect differs depending on the characteristics of the transactions. We built trading protocols modeling a recursive process to search the trading partner and make transactions with several behavioral assumptions considering the situations of early markets. The simulations results show that adding transaction costs resulted in reduction of trading volumes. Furthermore, the speed of reduction in trading volume to the increase of transaction costs is higher when there is scale economy. With a certain level of scale economy, the trading volumes abruptly fall down to almost zero as the transaction cost gets over a certain level. This suggests the possibility of a failed market. Since the scale economy is thought to be significant in the early stage of emission trading market, it is desirable to design a trading system that maximizes trading volumes and minimizes unit transaction costs at the outset. One of the alternatives to meet these conditions is to establish a centralized exchange and take measures to increase trading volumes.

• Journal of Distribution Science
• /
• v.16 no.12
• /
• pp.57-68
• /
• 2018

Purpose - The development of technologies lead the volume of sale on online market increase but an off-line shopping center is still a core component in the omni-channel strategy. It is generally thought that high-level retailtainment on brick and mortar store affects purchase intentions positively, but some previous studies dispute that and have reported that retailtainment does not affect purchase intentions. So we have studied the additional factors' effect - the nature of purchase and utility - with retailtainment. Research design, data, and methodology - There are 8 treatment groups which were assigned by the method of retailtainment (high vs. low), nature of purchase (essential vs. non-essential), and utility (acquisition vs. transaction). A total of 240 subjects (office workers = 163, 68%; undergraduates = 77, 32%; average age = 30s; female = 39%) were divided into groups and exposed to one of the eight scenarios. Participant's purchase intention was the dependent, and ANOVA and L-matrix were used to analyze for main and interactive effects between factors. Results - First, the main effect and interactive effect between retailtainment and the nature of purchase are significant. We also found that the contrast between essential and non-essential at low-level retailtainment is higher than that of high-level retailtainment. Second, in the case of retailtainment and utility, transaction utility under high-level retailtainment affects purchase intentions positively. Third, between the nature of the purchase and utility, the main effect of the nature of purchase and the interactive effect is significant, but the main effect of utility is not significant. In the case of non-essential goods, the purchase intention was high when transaction utility was provided but in the case of essential goods, acquisition utility increased purchase intentions. Finally, when transaction utility is given, purchase intentions of essential goods increase under low retailtainment, and the purchase intentions of non-essential goods increase under high retailtainment. Conclusions - When customers buy essential goods, discounts decrease purchase intentions. During the season for bargain sales, purchase intentions increase when retailtainment of essential goods is low, and retailtainment of non-essential goods is high.

• Journal of Distribution Research
• /
• v.17 no.5
• /
• pp.59-83
• /
• 2012

Agriculture is a primary industry that influenced by the weather or meterological factors more than other industry. Global warming and worldwide climate changes, and unusual weather phenomena are fatal in agricultural industry and human life. Therefore, many previous studies have been made to find the relationship between weather and the productivity of agriculture. Meterological factors also influence on the distribution of agricultural product. For example, price of agricultural product is determined in the market, and also influenced by the weather of the market. However, there is only a few study was made to find this link. The objective of this study is to investigate the effects of meterological factors on the distribution of agricultural products, focusing on the distribution of chinese cabbages. Chinese cabbage is a main ingredient of Kimchi, and basic essential vegetable in Korean dinner table. However, the production of chinese cabbages is influenced by weather and very fluctuating so that the variation of its price is so unstable. Therefore, both consumers and farmers do not feel comfortable at the unstable price of chinese cabbages. In this study, we analyze the real transaction data of chinese cabbage in wholesale markets and meterological factors depending on the variety and geography. We collect and analyze data of meterological factors such as temperatures, humidity, cloudiness, rainfall, snowfall, wind speed, insolation, sunshine duration in producing and consuming region of chinese cabbages. The result of this study shows that the meterological factors such as temperature and humidity significantly influence on the volume and price of chinese cabbage transaction in wholesale market. Especially, the weather of consuming region has greater correlation effects on transaction than that of producing region in all types of chinese cabbages. Among the whole agricultural lifecycle of chinese cabbages, 'seeding - harvest - shipment - wholesale', meterological factors such as temperature and rainfall in shipment and wholesale period are significantly correlated with transaction volume and price of crops. Based on the result of correlation analysis, we make a regression analysis to verify the meterological factors' effects on the volume and price of chines cabbage transaction in wholesale market. The results of stepwise regression analysis are shown in