• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.4 no.2
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• pp.77-84
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• 2000

Black-Scholes equation arising from option pricing in the presence of cost in trading the underlying asset is derived. The transaction cost is chosen precisely and generalized to reflect the trade in the real world. Furthermore the concept of the bandwidth is introduced to obtain the better rehedging. The model with bandwidth derived in this paper can be used to calculate the more accurate option price numerically even if it is nonlinear and more complicated than the models shown before.

• Journal of Digital Convergence
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• v.14 no.5
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• pp.95-106
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• 2016

The major thrust of this research focuses on the development of phased big data distribution model based on the big data ecosystem. This model consists of 3 phases. In phase 1, data intermediaries are participated in this model and transaction functions are provided. This system consists of general control systems, registrations, and transaction management systems. In phase 2, trading support systems with data storage, analysis, supply, and customer relation management functions are designed. In phase 3, transaction support systems and linked big data distribution portal systems are developed. Recently, emerging new data distribution models and systems are evolving and substituting for past data management system using new technology and the processes in data science. The proposed model may be referred as criteria for industrial standard establishment for big data distribution and transaction models in the future.

• Journal of the Korea Safety Management & Science
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• v.21 no.4
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• pp.7-15
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• 2019

This paper proposes the FMEA-based model to avoid backdoor transactions when purchasers select suppliers for products and services. In the model, backdoor transactions consist of two categories: backdoor selling and maverick buying. Both of which influence negative effects on cost savings due to not only uncompetitive advantage but also unusable purchasing leverage by unethical and misbehavior of purchase requestors. For the risk evaluation based on FMEA, three and five risk types of backdoor selling and maverick buying are identified respectively. Current risk priority numbers(RPN) based on those risk types are calculated by three categories: occurrence, detection and severity. Six risk mitigation strategies and fourteen mitigation tactics are identified to improve current RPN. In order to validate the model, questionnaires are collected from fifteen companies and statistically analyzed. The analysis result shows that the model reduces backdoor transaction risks and has no differences in reduction of backdoor transaction risks regardless of the type of purchasing organization units and existence of purchasing procedures in the organization.

• The Journal of Industrial Distribution & Business
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• v.11 no.8
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• pp.31-38
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• 2020

Purpose: This study uses 'Autoregressive Integrated Moving Average Model' to predict the impact of a sharp drop in the base rate due to COVID-19 at the present time when government policies for stabilizing house prices are in progress. The purpose of this study is to predict implications for the direction of the government's house policy by predicting changes in house transaction prices and house rental prices after a sharp cut in the base rate. Research design, data, and methodology: The ARIMA intervention model can build a model without additional information with just one time series. Therefore, it is a time-series analysis method frequently used for short-term prediction. After the subprime mortgage, which had shocked since the global financial crisis in April 2007, the bank's interest rate in 2020 is set at a time point close to zero at 0.75%. After that, the model was estimated using the interest rate fluctuations for the Bank of Korea base interest rate, the house transaction price index, and the house rental price index as event variables. Results: In predicting the change in house transaction price due to interest rate intervention, the house transaction price index due to the fall in interest rates was predicted to change after 3 months. As a result, it was 102.47 in April 2020, 102.87 in May 2020, and 103.21 in June 2020. It was expected to rise in the short term. In forecasting the change in house rental price due to interest rate intervention, the house rental price index due to the drop in interest rate was predicted to change after 3 months. As a result, it was 97.76 in April 2020, 97.85 in May 2020, and 97.97 in June 2020. It was expected to rise in the short term. Conclusions: If low interest rates continue to stimulate the contracted economy caused by COVID-19, it seems that there is ample room for house transaction and rental prices to rise amid low growth. Therefore, In order to stabilize the house price due to the low interest rate situation, it is considered that additional measures are needed to suppress speculative demand.

• Journal of Labour Economics
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• v.29 no.1
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• pp.75-98
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• 2006

This study shows a theoretical model, based on transaction cost theory, for the choice of alternative work arrangement, Suppose that standard labor contract (permanent and full-time) is a typical labor contract of within-organization transaction and alternative labor contracts of variety are in the spectrum between market and within-organization transaction, the type and size of the market transaction cost for a specific labor would determine the appropriate labor contract. Firm-specificity and level of skill, scope and uncertainty of tasks, and duration of contract are the major determinants of transaction cost which, in turn, determines the type of labor contract. This theoretical model implies that there will be occupational segregation between standard and alternative work arrangements and that the legal regulations for protecting employment and wage of non-standard workers might not be so effective as expected.

• The Journal of Information Technology
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• v.5 no.1
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• pp.113-131
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• 2002

The purpose of this study is to investigate the influences of transaction information and reputation about alliance partner on opportunism and alliance performance. In this study, a structural model and several hypotheses were developed regarding the relationships between transaction term, transaction records, reputation of alliance partner, opportunism, and alliance performance. Based on the collected data, the structural model was analyzed with Lisrel 8.12. The results can be summarized as follows. First, the longer the transaction term, the lower the opportunism and the higher the perceived alliance performances. Second, the better the transaction records, the lower the opportunism and the higher the perceived alliance performances. Third, the reputation of alliance partner company has not any influence on the opportunism and the perceived alliance performances. Finally, the lower the opportunism of alliance partner, the higher the perceived alliance performances. At the end of the paper, managerial implications and future research directions are discussed.

• Journal of KIISE:Databases
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• v.32 no.2
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• pp.142-150
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• 2005

A shared disks (SD) cluster couples multiple computing nodes, and every node shares a common database at the disk level. A great deal of research indicates that the SD cluster is suitable to high performance transaction processing, but the aggregation of SD cluster with real-time processing has not been investigated at all. A real-time transaction has not only ACID properties of traditional transactions but also time constraints. By adopting cluster technology, the real-time services will be highly available and can exploit inter-node parallelism. In this paper, we first develop an experiment model of an SD-based real-time database system (SD-RTDBS). Then we investigate the feasibility of real-time transaction processing in the SD cluster using the experiment model. We also evaluate the cross effect of real-time transaction processing algorithms and SD cluster algorithms under a wide variety of database workloads.

• The Korean Journal of Applied Statistics
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• v.23 no.4
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• pp.739-745
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• 2010

This paper computes the repurchase index based on statistical modeling. Using the transaction record of a certain product, the repurchase index is obtained by fitting the Poisson regression model. The customers are classified into 5 groups based on the index giving the information about the propensity to repurchase.

• 한국디지털정책학회:학술대회논문집
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• 2003.12a
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• pp.45-57
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• 2003

In recent years, the number of digital content transaction has increased dramatically, in main, owing to the innovation of IT technology. At the same time, it creates new problems which have never been found in traditional transactions. Especially, due to the easy-copy characteristics of digital content, the illegal usage of digital content proliferates. Also the conflicts between seller an d buyer in digital content transactions on cyberspace market take place frequently because contracts were made without face-to-face discussion. The increase of illegal usage and conflict in digital content market would diminish motivation of creators for their work, furthermore break down digital content market on cyberspace. Digital content transaction authentication system would play an important role in creating sound digital content market. Especially, it would make big contribution to reducing the number of conflict between seller and buyer. In this context, the main objective of this study is to suggest operational model of digital content transaction authentication and to explain critical success factors in organizing digital content transaction authentication system.

• Management & Information Systems Review
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• v.26
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• pp.1-26
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• 2008

Since Capital Asset Pricing Model(CAPM) was proposed in the early 1960s by William Sharpe(1964) and John Lintner(1965) researchers have investigated the validity of the model. The results of empirical researches do not show that expected returns of stocks seem to be determined solely by systematic risk of the stocks as precicted by CAPM. In this paper the relationship between transaction volume and expected returns of stocks was investigated. Empirical cross-sectional analysis about the data collected from Stock Market of Korea Exchange shows transaction volume and variability of stock returns play an important role in pricing assets. The well-known variables which were used traditionally to explain the differences of expected returns among stocks such as the size and beta of a stock seems to be unimportant in pricing assets.