• Asia pacific journal of information systems
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• v.13 no.1
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• pp.1-22
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• 2003

This study describes how the weights of performance measures varies depending on business strategy types, such as defenders, prospectors, analyzers, and reactors. A Balanced Scorecard has been widely used for measuring a corporate performance to incorporate financial and non-financial measures simultaneously. Because such performance measurements are related to the compensation and promotion of employees, research of weights of performance measures would be instrumental. Our test results demonstrate that the weights of the business performance measures differ in the four perspectives-financial, customer, internal process, and learning and growth. Furthermore, there is evidence that the weights of performance measures vary depending on business strategy. Our study results can be used for enhancing the quality of performance measurement systems.

• Management & Information Systems Review
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• v.25
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• pp.321-337
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• 2008

The house price rise suddenly is not only Economic stability but economic, mental state of a heavy burden to people. This paper is a house finance environment analyzed in this research about the rise factor of the house price and the result to present the plan to the natural disposition. The financial institute has an influence on the disguised demand extension of the house and The mortgage Lending in commercial Banks with the earnings as the stability high than the industry loaning. A house finance environment changes and will go from economic factor of the variety of the life style, the housing conditional according to the income level, a children education condition, and the population structure many this little. The disposition of the house need changes according to this and will have an influence on the house price. Necessary for a house market environment house policy of the market need which the consistency reflects so that we are suitable and is desired.

• Journal of Information Processing Systems
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• v.16 no.4
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• pp.935-958
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• 2020

The core value of finance is credit. It can be said that without credit, there can be no finance. The distributed structure of the blockchain and the low-cost trust-building mechanism based on mathematical algorithms provide a new solution and path for solving and optimizing related problems in the financial field. The blockchain technology is applied in the development of the financial industry through consensus mechanisms, smart contracts, and distributed networks. In this research, a comprehensive survey of the blockchain technology is proposed in the development of financial services including equity crowdfunding and credit investigations in inclusive finance, cross-border remittance, Internet financial payment, P2P lending, supply chains finance, and the application of blockchain in the field of anti-money laundering. This paper discusses the role of blockchain in solutions to different issues in the financial field. It also discusses the architectures in different financial service application scenarios from the perspective of the financial trust mechanism and the perspective of the technology and rule change of blockchain participation in financial innovation. Finally, the problems and challenges of blockchain in financial services are discussed, and corresponding solutions are proposed.

• Industrial Engineering and Management Systems
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• v.12 no.4
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• pp.406-415
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• 2013

The present study examines a set of financial ratios in predicting the up or down movements of stock prices in the context of a securities law, the Sarbanes-Oxley Act of 2002 (SOA), controlling for macroeconomic variables. Using the logistic regression with proxy betas to alleviate the incompatibility problem between the firm-specific financial ratios and macroeconomic indicators, we report evidence that financial ratios are meaningful predictors of stock price changes, which subdue the influence of macroeconomic indicators on stock returns, and more importantly that the SOA truly improves the stock price predictability of financial ratios for the markup sample. The empirical results further suggest that industry and time effects exist and that for the markdown sample the SOA actually deteriorates the predictive power of financial ratios.

• Journal of Information Technology Applications and Management
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• v.23 no.4
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• pp.25-39
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• 2016

Asset prices decline sharply and stock markets collapse when financial crisis happens. Recently we have encountered more frequent financial crises than ever. 1998 currency crisis and 2008 global financial crisis triggered academic researches on early warning systems that aim to detect the symptom of financial crisis in advance. This study proposes a risk recovery index for detection of good opportunities from financial market instability. We use SVM classifier algorithms to separate recovery period from unstable financial market data. Input variables are KOSPI index and V-KOSPI200 index. Our SVM algorithms show highly accurate forecasting results on testing data as well as training data. Risk recovery index is derived from our SVM-trained outputs. We develop a trading system that utilizes the suggested risk recovery index. The trading result records very high profit, that is, its annual return runs to 121%.

• The Journal of Information Systems
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• v.23 no.4
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• pp.75-91
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• 2014

The effective supply chain management(SCM) is a matter of survival in many firms because successful supply chains will effectively coordinate their processes, focus on delivering customer value, eliminate unnecessary costs in key functional areas, and create performance measurement systems. The balanced scorecard(BSC) is widely used to measure the performance of the SCM. The BSC framework suggests that balance is obtained by adopting performance measures from four different areas. In this study, we analyzed the causal relationship of SCM performance based on BSC framework. First, we reviewed the nested causal relationships among four different perspective of the BSC, namely, business process perspective, customer perspective, financial perspective, and innovation and learning perspective. Then, we used the chi-square difference test to identify the best model to fit the causal relationship of SCM performance. Of the 800 questionnaires posted, a total of 265 questionnaires were returned after one follow-up. A total of 66 questionnaires were eliminated due to largely missing values. The major finding says alternative model 3 is dominant to other models to fit causal relationships among four different perspective of the BSC. Innovation and learning perspective positively influence on customer perspective, business process perspective, and financial perspective. Business process perspective also positively influence on customer perspective and financial perspective whereas customer perspective does not influence on financial perspective significantly.

• The Journal of Information Systems
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• v.29 no.2
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• pp.1-26
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• 2020

Purpose This study empirically investigates the impact of information technology(IT) investments on the financial and non-financial performance of a manufacturing firm. We examined the interaction effects of IT investments and strategic applications levels of information systems(IS). This study also demonstrated the three-way interaction effects of IT investments, levels of IS strategic applications, and perceived environmental uncertainty(PEU). Design/methodology/approach For this study, empirical data were collected from 98 manufacturing firms with the structured questionnaires. The data were analyzed with multiple regression models, and partial derivatives were utilized to identify the directions of the impact. Findings From the empirical results, it was found that when both the levels of IS strategic applications and the degrees of IT investments are high, the ratios of the costs of goods sold to total sales(RCGS) and the labor costs to total sales(RLCS) are decreased, as it were, the performance of a firm is improved. However, it was observed that when the levels of strategic IS are low, the high degrees of IT investments do not contribute to the improvement of a performance. The results showed that when the levels of strategic IS are high, the high degrees of IT investments incur the high RSAE not low RSAE. When PEU is considered, the empirical results showed that under the low degrees of PEU, the IT investments under high levels of strategic IS applications (strategic IT investments) improve the performance, as it were, low RCGS, and high degrees of perceived financial and non-financial performance. However, under high PEU, it was observed that high degrees of strategic IT investments do not increase the performance. When PEU is high, the strategic IT investments reduce RSAE, and under low PEU, RSAE is increased.

• Management & Information Systems Review
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• v.30 no.4
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• pp.175-193
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• 2011

This paper tests a correlation between degrees of operating leverage(DOL) and financial leverage(DFL). For an empirical analysis, this paper extracted information from financial statements of manufacturing companies listed in the Korea Stock Exchange. Data extend from 1990 to 2009. The DOL continued to increase until 1997, but decreased dramatically after the IMF financial crisis. However, the DOL has been at a higher level than companies of other countries such as USA and Japan. The DFL has been maintained at a much higher level, as expected. The empirical results indicate a positive correlation between the DOL and the DFL. To further investigate, we divide the whole sample into subgroups according to such management elements as asset size, IMF crisis. The results for sub-samples are different from those of whole sample. This indicates we need to incorporate specific managerial factors in order to correctly explain financial decision processes.

• International Journal of Computer Science & Network Security
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• v.24 no.3
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• pp.1-11
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• 2024

Payment systems are evolving, and this study examines how blockchain and AI improve online transactional security and service quality. The study examines micro and macro payment systems, compares online, and offline methods all over the world. The study also examines how blockchain and AI affect payment system security, privacy, and efficiency globally and rapidly digitizing economy. Digital payment methods are growing all over the world with high literacy and digital engagement, but they face challenges. The research highlights cybersecurity threats and the need to balance user convenience and security. It suggests blockchain and AI improve online payment services, supporting the policies for different countries. In this extensive research survey, we compare and evaluate the strengths and weaknesses of various payment systems, their practicality, and their robustness. This study also examines how technological innovations and payment systems interact to reveal how blockchain and AI could transform the financial sector. It seeks to understand how technology-enhancing service quality can boost customer satisfaction and financial stability in the digital age. The findings should help policymakers, financial institutions, and technology developers optimize online payment systems for a more secure and efficient digital economy.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.3
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• pp.79-87
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• 2024

Recently, the importance of pre-trained language models (PLM) has been emphasized for natural language processing (NLP) such as text classification, sentiment analysis, and question answering. Korean PLM shows high performance in NLP in general-purpose domains, but is weak in domains such as finance, medicine, and law. The main goal of this study is to propose a language model learning process and method to build a financial-specific language model that shows good performance not only in the financial domain but also in general-purpose domains. The five steps of the financial-specific language model are (1) financial data collection and preprocessing, (2) selection of model architecture such as PLM or foundation model, (3) domain data learning and instruction tuning, (4) model verification and evaluation, and (5) model deployment and utilization. Through this, a method for constructing pre-learning data that takes advantage of the characteristics of the financial domain and an efficient LLM training method, adaptive learning and instruction tuning techniques, were presented.