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

• The Journal of Information Systems
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• v.15 no.4
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• pp.23-53
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• 2006

The main purpose of this paper is to setup a integrated model and verify the integrated model for a customer loyalty in the internet shopping environments. The results of a structural equation model (SEM) using AMOS and LISREL include: First, hypothesis that Internet environment characteristics in outside factors has a positive effect on satisfaction, trust and commitment is partially supported. However, mutual communication to satisfaction, community to commitment and open-ubiquity to trust did not reveal a positive effect. Second, hypothesis that Internet showing mall environment has a positive effect on satisfaction is partially supported. However, transaction to commitment and transaction to trust did not reveal a positive effect. Third, hypothesis that relational benefits has a positive effect on both satisfaction and commitment is partially supported. However, confident honest to commitment and economic honest to trust did not reveal a positive effect. Forth, satisfaction trust and commitment have a strong effect upon loyalty. Fifth, satisfaction has a positive effect on trust and commitment. However, trust did not show a positive effect on commitment. Outside factors(Internet environment characteristics, showing mall characteristics, and relational benefit) partially revealed a positive effect on satisfaction trust, and commitment. Mediating variables such as satisfaction, trust, and commitment again have positive effect on loyalty. But, the relationship for trust to commitment did not reveal the significant effect in this study while other studies revealed significant effect.

• Journal of the Economic Geographical Society of Korea
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• v.10 no.1
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• pp.44-63
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• 2007

The purpose of this study is to propose mining processes in the large trip-transaction database of the Metropolitan Seoul area and to analyze the spatial characteristics of travel behavior. For the purpose. this study introduces a mining algorithm developed for exploring trip patterns from the large trip-transaction database produced every day by transit users in the Metropolitan Seoul area. The algorithm computes trip chains of transit users by using the bus routes and a graph of the subway stops in the Seoul subway network. We explore the transfer frequency of the transit users in their trip chains in a day transaction database of three different years. We find the number of transit users who transfer to other bus or subway is increasing yearly. From the trip chains of the large trip-transaction database, trip patterns are mined to analyze how transit users travel in the public transportation system. The mining algorithm is a kind of level-wise approaches to find frequent trip patterns. The resulting frequent patterns are illustrated to show top-ranked subway stations and bus stops in their supports. From the outputs, we explore the travel patterns of three different time zones in a day. We obtain sufficient differences in the spatial structures in the travel patterns of origin and destination depending on time zones. In order to examine the changes in the travel patterns along time, we apply the algorithm to one day data per year since 2004. The results are visualized by utilizing GIS, and then the spatial characteristics of travel patterns are analyzed. The spatial distribution of trip origins and destinations shows the sharp distinction among time zones.

• Journal of the Korea Computer Industry Society
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• v.5 no.9
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• pp.973-986
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• 2004

Reports have a significant meaning In large transaction environments, such as advanced the information technology and online environment. This is due to the necessity of generating reports within a giventime limit without restraining the operation performance of large transaction environments. In order to generate reports in large transaction environments while sa!isfying time-constrained requirements, this paper proposes a model which combines the incremental operation mechanism and materialized view mechanism using triggers and stored procedures. Further, the implementation and evaluation of the proposed model provides the identification of the characteristics of the proposed model.

• Journal of KIISE:Computing Practices and Letters
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• v.6 no.2
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• pp.113-119
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• 2000

In this paper, we design and implement a query processor of real-time main memory database systems, which reflect the characteristics of main memory database systems and satisfy timing constraints. The proposed query processor manages real-time data that has timing constraint by exploiting meta database. It supports CLI in order to make application programs. It also supports extended CLI and stored CLI. The former can be expressed the Information on real-time transaction. The latter is designed to support frequently processed transaction. The proposed query processor is implemented as query processor of real-time database management systems. We Present performance evaluation results that illustrate ratio of transaction, which satisfy deadline are increased by the query processing ability of system and the efficient management of real-time data.

• Journal of the Economic Geographical Society of Korea
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• v.9 no.3
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• pp.379-395
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• 2006

The purpose of this study is to analyze the spatial characteristics of travel patterns and travel behaviors of transit users in the Metropolitan Seoul area. We apply the data mining techniques to explore the travel patterns of transit users from the T-money card database which has been produced over 10,000,000 transaction records per day. The database contains the information of locations and times of origin, transfer, and destination points for each transaction as well as the informations of transit modes taken via the transaction. We develop an data mining algorithm to explore traversal patterns from the enormous information. The algorithm determines the travel sequences of each passenger, and produce the volumes of support on each points (stops) of transportation networks in the Metropolitan Seoul area. In order to visualize the spatial patterns of travel demands for transit systems we apply GIS techniques, and attempt to investigate the spatial characteristics of travel patterns and travel demand. Subway stops located in the Gangnam area appear the highest peak for the travel origin and destination, while the CBD in the Gangbuk stands at the second position. Two or three sub-peaks appear at the densely populated residential areas developed as the high-rise apartment complex. Subway stations located along the Subway Line 2, especially from Guro to Samsung receive heavy travel demand (total support), while bus stops located at the CBD in the Gangbuk stands the highest travel demand by bus.

• Information Systems Review
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• v.25 no.1
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• pp.111-128
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• 2023

With the development of artificial intelligence technology, interest in data-based product preference estimation and personalized recommender systems is increasing. However, if the recommendation is not suitable, there is a risk that it may reduce the purchase intention of the customer and even extend to a huge financial loss due to the characteristics of the financial product. Therefore, developing a recommender system that comprehensively reflects customer characteristics and product preferences is very important for business performance creation and response to compliance issues. In the case of financial products, product preference is clearly divided according to individual investment propensity and risk aversion, so it is necessary to provide customized recommendation service by utilizing accumulated customer data. In addition to using these customer behavioral characteristics and transaction history data, we intend to solve the cold-start problem of the recommender system, including customer demographic information, asset information, and stock holding information. Therefore, this study found that the model proposed deep learning-based collaborative filtering by deriving customer latent preferences through characteristic information such as customer investment propensity, transaction history, and financial product information based on customer transaction log records was the best. Based on the customer's financial investment mechanism, this study is meaningful in developing a service that recommends a high-priority group by establishing a recommendation model that derives expected preferences for untraded financial products through financial product transaction data.

• The KIPS Transactions:PartD
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• v.13D no.3 s.106
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• pp.293-298
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• 2006

Many data are stored in database. For getting any information from many data, we use the query sentences. These information is basic and simple. Data mining method is various. In this paper, we manage clustering and association rules. We present a method for finding the better association rules, and we solve a problem of the existing association rules. We propose and apply a new clustering method to fit for association rules. It is not clustering of the existing distance basis or category basis. If we find association rules of each clusters, we can get not only existing rules found in all transaction but also rules that will be characteristics of clusters. Through this study, we can expect that we will reduce the number of many transaction access in large databases and find association of small group.

• Journal of Digital Convergence
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• v.19 no.6
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• pp.259-264
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• 2021

Recently, as the number of used trading sites supporting used trading increases, users want to search for a variety of information in real time. This new change has enabled a new type of C2C (Commerce to Commerce) transaction in the e-commerce base. However, since each used trading site has its own characteristics, it is difficult to standardize the whole. Therefore, in this paper, we studied a system that provides the transaction data used by the user in real time and provides the desired information quickly. In this paper, we researched the crawler system necessary for the development of the integrated trading system for used goods through Internet e-commerce, and made it possible to provide information in the web environment desired by the user through the defined morpheme analyzer. Therefore, in this study, we designed a system that provides information desired by users without accessing various used goods sites.

• Journal of Korea Trade
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• v.24 no.7
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• pp.73-92
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• 2020

Purpose - The letter of credit has been playing a major role to diminish overall risks which exist among concerned parties even though there are differences such as language, culture, law, and distance. This paper reviews essence of the letter of credit and its transaction principles, as well as overall practical questions based on the L/C transaction principle. It also investigates the risk of fraud occurrences in L/C transactions and the importance of fraud prevention and preventive measures in international L/C transactions, including the Fraud Rule, which is a major topic to consider in business transactions. Design/methodology - It is considered that an importing country's concerned parties and an exporting country's concerned parties face different situations. This study employs the existing framework to identify liability, responsibility, and obligation for all concerned parties across countries. Using a quite direct measurement of principles in the letter of credit, such as principle of independence, principle of abstraction, and principle of strictness and coincidence, we studied these differences. Findings - Our main findings can be summarized as follow. The paper enhances the efficiency of the L/C payment method to provide fraud generated from L/C transactions, presentation of a theoretical framework about fraud and fraud prevention, which international trading companies should acknowledge in a material way based on fraud risk resulting from taking advantage of L/C transaction principles. Originality/value - Existing studies focus on fraud accidents in L/C transactions by taking bad advantage of the characteristics of the letter of credit without suggesting risks of fraud. This paper attempts to evaluate and provide preventive measures as a solution for fraud and risky international business in a letter of credit transaction. This area of trade studies is underexplored, both empirically and theoretically, although the issue has long been important to Korean and world community foreign trade.