• Journal of Arbitration Studies
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• v.28 no.2
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• pp.249-275
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• 2018

Today's Internet environment is growing rapidly, and transactions based on it are also rapidly increasing. E-commerce allows merchants and consumers in different countries to easily trade goods across borders. However, the increase in international consumer transactions through the Internet is accompanied by an increase in disputes. International consumer transactions are characterized by a distinction among long distance, small sum, and different jurisdictions. International consumer transactions cannot be solved only by way of resolving disputes in past international transactions. The best way to resolve disputes between international carriers and consumers is through the Internet. In this regard, UNCITRAL has been preparing to enact legislation on ODR as a solution to international electronic trade disputes and, as a result, UNCITRAL adopted guidelines for operating the ODR procedure for building the ODR platform. The European Union has also increased its disputes in the European Union, which is active in the intra-regional market. Institutional improvements were made to solve this problem; therefore, the European Union (EU) has enacted the ODR Regulations for EU consumer disputes. Based on such, this study constructed the ODR platform, which is used as a way to resolve consumer disputes in the regional market.

• Convergence Security Journal
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• v.8 no.4
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• pp.9-19
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• 2008

By e-Financial Transactions Act enacted in January 2007, the financial institutions are responsible for indemnifying user's damage to ensuring security of the electronic financial transactions and to protecting financial users when suffering from electronic financial accidents. However, when occurring unauthorized financial transactions or electronic financial accidents by user's moral hazard, it is difficult to determine where the accidents happened at and whether caused by the intention or gross negligence of users. To protecting financial parties and ensuring the security and reliability of electronic financial transactions, this paper attempts to propose the means, what enhance the notification process about financial transactions and to strengthen IT regulatory compliance by using area information about electronic financial transactions, to protect risk of the financial accidents.

• Journal of Information Processing Systems
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• v.13 no.6
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• pp.1575-1584
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• 2017

As interest in big data has increased recently, NoSQL, a solution for storing and processing big data, is getting attention. NoSQL supports high speed, high availability, and high scalability, but is limited in areas where data integrity is important because it does not support multiple row transactions. To overcome these drawbacks, many studies are underway to support multiple row transactions in NoSQL. However, existing studies have a disadvantage that the number of transactions that can be processed per unit of time is low and performance is degraded. Therefore, in this paper, we design and implement a multi-row transaction system for data integrity in big data environment based on HBase, a column-based NoSQL which is widely used recently. The multi-row transaction system efficiently performs multi-row transactions by adding columns to manage transaction information for every user table. In addition, it controls the execution, collision, and recovery of multiple row transactions through the transaction manager, and it communicates with HBase through the communication manager so that it can exchange information necessary for multiple row transactions. Finally, we performed a comparative performance evaluation with HAcid and Haeinsa, and verified the superiority of the multirow transaction system developed in this paper.

• KNOM Review
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• v.22 no.1
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• pp.68-76
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• 2019

Bitcoin, based on the blockchain technology is an online crypto-currency developed by Satoshi Nagamoto. Bitcoin, which was first issued on January 3, 2009, is rapidly evolving with increasing number of transactions. However, untoward incidents are occurring due to an increase in the number of Bitcoin transactions. Predicting the number of Bitcoin transactions is important to prepare for any issues that can occur in the Bitcoin network. This paper proposes to design model for predicting the number of Bitcoin transactions by applying two machine learning algorithms and then a model for predicting the number of Bitcoin transactions through experiments.

• The KIPS Transactions:PartD
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• v.8D no.1
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• pp.10-23
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• 2001

Transactions in real-time active databases have the notion of activeness where transactions are generated by external effects and another transaction. In this paper, we propose the multi version concurrency control algorithm for real-time active transactions. A real-time active transaction has a timing constraint in the form of a deadline until which the user wants to complete the transaction, and is characterized by triggering relationships which mean that association between a transaction that triggers the execution of another transaction and the triggered transaction. The triggering relationship is an important factor to resolve data conflicts among real-time active transactions. The proposed concurrency control mechanism resolves data conflicts by considering triggering relationships between conflicting transactions as well as priorities and precedence relationships. The conflict resolution mechanism considers association types of the triggering relationship such as abort and commit dependency, and then resolves data conflicts in favor of higher priority transactions. We also present the experimental results of our algorithm comparing other real-time active concurrency control algorithms.

• Journal of KIISE:Databases
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• v.30 no.2
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• pp.184-196
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• 2003

Mobile transactions updating spatial objects are long transactions that can update independently local objects of mobile clients during disconnection. Validation based protocols that are well known to be appropriate for mobile transactions are required to abort a conflicted transaction in order to keep data consistent. Since abortion leads to cancel of all of tile updates, it is not desirable to use the abortion for resolving conflicts of mobile transactions. In this paper, we propose a reprocessing transaction model to resolve the update conflicts between mobile transactions without aborting them. We also design a mobile transaction server to support the reprocessing transaction and build a prototype of a mobile field system. The reprocessing transaction is a subtransaction of a newly committed mobile transaction and re-executes only conflicted objects with foreign conflicted objects. We also introduce a progressive reprocessing scheme to expose non-conflicted objects of the mobile transaction to other transactions in order to reduce starvation of reprocessing transactions.

• The KIPS Transactions:PartD
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• v.9D no.1
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• pp.11-20
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• 2002

We propose a new concurrency control algorithm for enhancing the degree of parallelism of the transactions in fully replicated databases designed to improve the availability and the reliability. The update transactions can be logically decomposed of a read-only transaction and a write-only transaction. In our algorithm, a set of read operations of an update transaction is treated as a read-only transaction and the read-only transaction reads data items in the site to which it is submitted. And a set of write operations of the update transaction is treated as a write-only transaction and it is submitted to all corresponding sites after the update transaction has been completed. By using the proposed update protocol, all write-only transactions can execute at all sites atomically. The proposed algorithm can have transactions execute concurrently at the site to which they are submitted and, after the completion of each transaction, the update protocol is performed for updating their data items and checking their serializability. Therefore, the degree of parallelism of the transactions can be improved. Especially, if the probability of conflict among transactions is low, we can expect the higher degree of their parallelism.

• The Journal of the Korea Contents Association
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• v.8 no.2
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• pp.57-66
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• 2008

Most concurrency control protocols have been devised for resolving data conflicts among real-time transactions of a single type. Recent real-time database systems should support various types of real-time transactions due to needs of many different types of applications and steady improvement of hardware. In this paper, we propose integrated concurrency control protocol to resolve data conflicts among hard and soft real-time transactions. Our proposed protocol, based on PCP(Priority Ceiling Protocol) for a hard real-time transactions and MVPR(Multiversion with Precedence Relationship), guarantees that hard real-time transactions meet their deadline, and decreases the deadline miss ratio of soft real-time transactions. We also proved that the proposed protocol guarantees serializable schedules and no deadlocks. The performance of the proposed protocol has been compared with other real-time concurrency protocols.

• Asia-Pacific Journal of Business
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• v.13 no.1
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• pp.103-123
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• 2022

Purpose - This study investigates the effects of earnings management, related party transactions between chaebol affiliates on earnings management and ESG score on their profitability using return on assets (ROA). Design/Methodology/Approach - We use data including ESG (Environmental, Social, and Corporate Governance) score of the Korea Corporate Governance Service(KCGS), and financial data of 10,145 firm-year observations from the Total Solution 2000 (TS 2000) and Korea Companies-Information Service (KOKOInfo), and apply the finite lagged models to investigate the long-term effects of related party transactions between chaebol affiliates of earnings management on ESG scores and corporate performance. Furthermore, to take into consideration the simultaneous mutual effects on each other of main variables, we introduce finite distributed lags of five years. Findings - First, ESG-rated firms have a higher total asset return than non-ESG-rated firms. Second, chaebol firms have a higher profitability than non-chaebol firms. Third, profit management of related party transactions between affiliates within a chaebol has a positive effect on the short-term profitability and a negative effect on the long-term profitability. Fourth, chaebol ESG firms have a lower impact on profitability due to rating up (down) than non-chaebol ESG firms. Research Implications or Originality - Based on the above results, it can be concluded that firms used related party transactions for earnings management, the effects of related party transactions change over time, and chaebol firms manipulate earnings through related party transactions and ESG scores.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.93-108
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• 2014

To support business decision making, interests and efforts to analyze and use transaction data in different perspectives are increasing. Such efforts are not only limited to customer management or marketing, but also used for monitoring and detecting fraud transactions. Fraud transactions are evolving into various patterns by taking advantage of information technology. To reflect the evolution of fraud transactions, there are many efforts on fraud detection methods and advanced application systems in order to improve the accuracy and ease of fraud detection. As a case of fraud detection, this study aims to provide effective fraud detection methods for auction exception agricultural products in the largest Korean agricultural wholesale market. Auction exception products policy exists to complement auction-based trades in agricultural wholesale market. That is, most trades on agricultural products are performed by auction; however, specific products are assigned as auction exception products when total volumes of products are relatively small, the number of wholesalers is small, or there are difficulties for wholesalers to purchase the products. However, auction exception products policy makes several problems on fairness and transparency of transaction, which requires help of fraud detection. In this study, to generate fraud detection rules, real huge agricultural products trade transaction data from 2008 to 2010 in the market are analyzed, which increase more than 1 million transactions and 1 billion US dollar in transaction volume. Agricultural transaction data has unique characteristics such as frequent changes in supply volumes and turbulent time-dependent changes in price. Since this was the first trial to identify fraud transactions in this domain, there was no training data set for supervised learning. So, fraud detection rules are generated using outlier detection approach. We assume that outlier transactions have more possibility of fraud transactions than normal transactions. The outlier transactions are identified to compare daily average unit price, weekly average unit price, and quarterly average unit price of product items. Also quarterly averages unit price of product items of the specific wholesalers are used to identify outlier transactions. The reliability of generated fraud detection rules are confirmed by domain experts. To determine whether a transaction is fraudulent or not, normal distribution and normalized Z-value concept are applied. That is, a unit price of a transaction is transformed to Z-value to calculate the occurrence probability when we approximate the distribution of unit prices to normal distribution. The modified Z-value of the unit price in the transaction is used rather than using the original Z-value of it. The reason is that in the case of auction exception agricultural products, Z-values are influenced by outlier fraud transactions themselves because the number of wholesalers is small. The modified Z-values are called Self-Eliminated Z-scores because they are calculated excluding the unit price of the specific transaction which is subject to check whether it is fraud transaction or not. To show the usefulness of the proposed approach, a prototype of fraud transaction detection system is developed using Delphi. The system consists of five main menus and related submenus. First functionalities of the system is to import transaction databases. Next important functions are to set up fraud detection parameters. By changing fraud detection parameters, system users can control the number of potential fraud transactions. Execution functions provide fraud detection results which are found based on fraud detection parameters. The potential fraud transactions can be viewed on screen or exported as files. The study is an initial trial to identify fraud transactions in Auction Exception Agricultural Products. There are still many remained research topics of the issue. First, the scope of analysis data was limited due to the availability of data. It is necessary to include more data on transactions, wholesalers, and producers to detect fraud transactions more accurately. Next, we need to extend the scope of fraud transaction detection to fishery products. Also there are many possibilities to apply different data mining techniques for fraud detection. For example, time series approach is a potential technique to apply the problem. Even though outlier transactions are detected based on unit prices of transactions, however it is possible to derive fraud detection rules based on transaction volumes.