• Asia Marketing Journal
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• v.25 no.1
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• pp.37-44
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• 2023

Firm innovativeness and financing capacity are critical signals to stakeholders as they are key drivers of firm performance and competitiveness and indicate the firm's ability to fund its operations and growth initiatives. Based on signaling theory, this study investigates the signaling effect of a firm's innovativeness and creditworthiness and examines its signaling effectiveness. Using Korean innovation data and Korea Investors Service financial data for nine years, the findings indicate that a firm's technological innovation has a negative impact on its credit ratings, while non-technological innovation has a positive impact. Furthermore, a firm's credit ratings positively impact its performance. The current study contributes to the literature on signaling theory by exploring the signaling effect of a firm's innovativeness and creditworthiness. The findings provide insights for managers on how to send and monitor signals to stakeholders.

• East Asian Journal of Business Economics (EAJBE)
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• v.8 no.4
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• pp.45-65
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• 2020

Purpose - This paper is to analyze the system and the models of financial analysis in the assessment of economic consistency and the creditability of borrower. To test the process of complex express-analysis, it is utilized by the concentric matrix models by using the matrix of 5×5.. Research design, data, and methodology - The estimation of economic consistency, the creditworthiness, the complex express-analysis with application of concentric matrix models were carried out on the basis of data of the report for the 2017 of corporations POSCO and in the first half of the 2018 Daewoo Shipbuilding & Marine Engineering of South Korea. Results - This paper focused on the unbalance of the corporate financial structure (capital, receivable) and the assessment of sustainability development, taking into account the liquidity, solvency, financial sustainability and economic viability of the enterprise. Conclusions - this paper also consider the theoretical means of regulating receivables. The material is presented in the pedagogical context and appendix of the conclusion.

• Journal of Korea Port Economic Association
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• v.40 no.1
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• pp.133-149
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• 2024

According to previous studies, the key factor in determining the loan interest rate for shipping companies is the default risk premium. Therefore, this study analyzes the determinants of the risk premium of shipping loans using a multiple linear regression model. With the risk premium as the dependent variable, a total of 10 independent variables are selected, including three factors: loan characteristics, borrower's creditworthiness, and economic situation. Samples are 82 shipping loans supported by Bank A from 2014 to 2022. As a result, borrower's creditworthiness(current ratio, debt ratio, firm age) and economic situation(freight index) affect the risk premium in analysis for all samples. It is found that borrower's creditworthiness has some influence on the risk premium for container ships(current ratio, cash holding ratio, debt ratio, operating income to sales) and bulk carriers(debt ratio, firm age). Market situation affects the risk premium in gas carriers. However, in the model targeting tanker ships, unlike previous studies, all factors have no effect on the risk premium.

• International Journal of Human Ecology
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• v.15 no.2
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• pp.59-67
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• 2014

Consumer information influences purchasing behavior; however, less is known about the relationship in the credit market. Credit markets offer consumers a complex array of different products when choosing mortgages. The current study examines whether borrowers search for the very best terms when making major decisions about borrowing money or obtaining credit as well as explores the relation between consumer information seeking and the cost of credit. This study demonstrates the existence of price dispersion between those who made an extensive information seeking and those who did not. When controlling for the proxies of creditworthiness and demographics of the respondents, it is found that those who made a great deal of information seeking tend to have lower mortgage rates than those who made almost no information seeking. This study offers financial educators and policy makers suggestions on how to help consumers make better financial decisions.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2003.11a
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• pp.349-354
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• 2003

Airport facility is infrastructure that become external creditworthiness and linear measure of country competitive power. Among them, receive and supply of electric power facility of airport is very important in peculiarity, trustability, safety side of airport. In this parer, sorted domestic airline as 4 classes by code to accomplish standardization for receive and supply of electric power facility of airport. And established justice and coverage about receive and supply of electric power facility using without any standard present and analyze problem for receive and supply of electric power facility of existing airport and presents standard. Finally, present standard single-line diagram by airport grade and system grade standard of receive and supply of electric power facility of airport.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.624-626
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• 2023

Credit scoring is a technique used by financial institutions to assess the creditworthiness of potential borrowers. This involves evaluating a borrower's credit history to predict the likelihood of defaulting on a loan. This paper presents an ensemble of two Transformer based models within a framework for discriminating the default risk of loan applications in the field of credit scoring. The first model is FinBERT, a pretrained NLP model to analyze sentiment of financial text. The second model is FT-Transformer, a simple adaptation of the Transformer architecture for the tabular domain. Both models are trained on the same underlying data set, with the only difference being the representation of the data. This multi-modal approach allows us to leverage the unique capabilities of each model and potentially uncover insights that may not be apparent when using a single model alone. We compare our model with two famous ensemble-based models, Random Forest and Extreme Gradient Boosting.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.69
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• pp.239-259
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• 2016

An increasing number of transactions in the bilateral trade between Korea and China rely on collection and remittance, resulting in an increase in exporters' demand for trade financing. Therefore, there is a need to vitalize forfaiting transactions using drafts or promissory notes, which are based on the collections. In the forfaiting transactions, exporters transfer a payment claim to forfaiters on a non-recourse basis through a without recourse endorsement. However, forfaiters do not know importers' creditworthiness and ability to repay drafts or promissory notes; thus, they need a bank aval as a means of credit support. In forfaiting using aval, the drafts or promissory notes are transferred internationally. However, there is no internationally unified law that regulates drafts and promissory notes, and the governing laws related to such drafts and promissory notes do not accept the "principle of party autonomy." Therefore, there is no other choice but to apply the laws of a certain country, in the event of any dispute relating to such drafts or promissory notes. This paper examined forfaiting using aval from the comparative law perspective, focusing on the "Law of China on Negotiable Instruments." The results of this study may to provide businesses involved in international trade with practical guidance and assistance when using forfaiting with aval, especially in trade with China.

• The Journal of Information Systems
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• v.14 no.1
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• pp.41-65
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• 2005

The credit ration is a significant area of financial management which is of major interest to practitioners, financial and credit analysts. The components of credit rating are identified decision models are developed to assess credit rating an the corresponding creditworthiness of firms an accurately ad possble. Although many early studies demonstrate a priori which of these techniques will be most effective to solve a specific classification problem. Recently, a number of studies have demonstrate that a hybrid model integration artificial intelligence approaches with other feature selection algorthms can be alternative methodologies for business classification problems. In this article, we propose a hybrid approach using rough set theory as an alternative methodology to select appropriate attributes for case-based reasoning. This model uses rough specific interest lies in lthe stable combining of both rough set theory to extract knowledge that can guide dffective retrevals of useful cases. Our specific interest lies in the stable combining of both rough set theory and case-based reasoning in the problem of corporate credit rating. In addition, we summarize backgrounds of applying integrated model in the field of corporate credit rating with a brief description of various credit rating methodologies.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.1241-1248
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• 2021

This study employs data from CRSP/Compustat files for the period from 2003 to 2017 and applies a panel data analysis. The results of this study show a positive relationship between trade credit and the firm's market value, however, the results show a negative relationship if we test the impact of financial credit on the firm's market value. The results have direct policy implications for investors, the firm's management, and financial strategy. An implication of our study is that using trade credit as a source of financing may give a positive signal of the firm's creditworthiness and increase the firm's market value. Also, the results of our study indicate that the benefits of using trade credit may outperform the cost of using it as a source of finance. Prior studies examine the impact of financial leverage on the firm's value, however, this study contributes to the existing studies that examine the factors that affect the firm's market value by examining the impact of using trade credit finance on the firm's market value. The main limitation of this study is that the results are based on listed firms, using data from unlisted firms is not available.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.8
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• pp.89-97
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• 2022

The e-commerce market faces significant credit risks due to the complexity of the industry and information asymmetries. Therefore, credit risk has started to stymie the growth of e-commerce. However, there is no reliable system for evaluating the creditworthiness of e-commerce companies. Therefore, this paper constructs a credit risk evaluation index system that comprehensively considers the online and offline behavior of online retail enterprises, including 15 indicators that reflect online credit risk and 15 indicators that reflect offline credit risk. This paper establishes an integration method based on a fuzzy integral support vector machine, which takes the factor analysis results of the credit risk evaluation index system of online retail enterprises as the input and the credit risk evaluation results of online retail enterprises as the output. The classification results of each sub-classifier and the importance of each sub-classifier decision to the final decision have been taken into account in this method. Select the sample data of 1500 online retail loan customers from a bank to test the model. The empirical results demonstrate that the proposed method outperforms a single SVM and traditional SVMs aggregation technique via majority voting in terms of classification accuracy, which provides a basis for banks to establish a reliable evaluation system.