• The Journal of Asian Finance, Economics and Business
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• v.5 no.4
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• pp.35-44
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• 2018

The study is aimed at investigating the main factors that affect the interest rate yields, in the long-term. In addition, the study surveys the theories and literature relating to the determinants of interest rate. The importance of which is essential not only for governments, but also for banks and corporate financial risk management decisions, including risk exposures in banks and capital markets. Interest rate influences corporate profit as well as growth. For this purpose, the study examines the impact of budget deficit, risk-free rate, capital inflows, money supply and business cycles on real interest rate in Jordan. These factors are based upon well-established theories and straightforward practical view as interest rate determinants. Using data for (1990-2015), the study employed Johansen's co-integrating test, which takes into consideration the long-term unsynchronized relationships. The data is tested for normality, symmetric correlations, covariance diagonal and unit root. The results show that the government budget deficit, short-term risk-free interest rate, capital inflows, money supply and business cycle are long-term determinants of the real interest rate in Jordan. The coefficients of government budget deficit, short-term risk-free rate, money supply and business cycle all are inversely affecting the real interest rate, while capital inflows has a positive impact on the real interest rate.

• Industrial Engineering and Management Systems
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• v.9 no.1
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• pp.41-53
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• 2010

An existing risk diagnosing methodology (RDM) diagnoses corporate risk for product-innovation projects. However, it cannot evaluate and compare the risk levels of multiple alternatives in the product development stage. This paper proposes a modified risk diagnosis method to fill the gap of risk evaluation in selections of innovative product alternatives and the application of the method will be also illustrated by a case problem on alternative selections in electrical dimmer designs. With RDM as the foundation, a modified RDM (MRDM) is proposed to deal with the problem of selecting innovative project alternatives during the early stages of product development. The Bayesian network; a probabilistic graphical model, is adopted to support the risk pre-assessment stage in the MRDM. The MRDM is proposed by incorporating the risk pre-assessment stage into the foundation. By evaluating the engineering design risks in two electrical dimmer switches, an application of the MRDM in product innovation development is successfully exemplified. This paper strengthens the existing methodology for RDM in innovative product development projects to accommodate innovative alternatives. It is advantageous for companies to identify and measure the risks associated in product development so as to plan for appropriate risk mitigation strategies.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.980-985
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• 2005

Since the 1980s, Build-Operate-Transfer and its variations have become a common approach to develop large-scale infrastructure projects. Despite the slight variations in contractual settings, the key issue for all parties concerned is to assess the risks and uncertainties inherent in a project. The risk factors studied and highlighted by past researchers are very diverse. This paper starts with an objective to compare the risk factors in different sectors of infrastructure, and then categorize them into two kinds: general and specific. Following this classification, risk mitigation strategies should be adopted differently at the corporate and project levels. A few short cases have also been used to illustrate the flexible measures or "options" that some project participants have designed to address risks and uncertainties at the two levels.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.136-144
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• 2021

This study focuses on the necessity of MOT methods in companies, especially the utilization level. Based on the analysis structure of the previous study (2012), this study was conducted to compare the results with the previous results. We investigated the settlement level of MOT, the degree of necessity for MOT methods, the degree of actual use, and the Product Realization Process (PRP) for MOT-related researchers in electronic companies (n=184). It was confirmed that the higher the demand for MOT methods in the corporate field, the higher the utilization level (ratio). In particular, the need for and utilization of techniques such as Environmental Analysis, Business Opportunity Analysis, Project Feasibility Review, Roadmap, Risk Management was high. These methods were beneficial along with cost management and quality management techniques. The most challenging part of using MOT methods was the lack of systematic use, the absence of experts, and the difficulty in selecting suitable techniques. The necessity of opening subjects such as Creative Thinking, Communication, Teamwork, and Professional Ethics was high among the PRP subjects. Furthermore, the necessity of opening courses in Cost and Safety Design and Applied Statistics was higher than in the previous study.

• Journal of Information Technology Applications and Management
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• v.14 no.2
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• pp.151-168
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• 2007

The corporate credit rating represents an assessment of the relative level of risk associated with the timely payments required by the debt obligation. In this study, the corporate credit rating model employs artificial intelligence methods including Neural Network (NN) and Case-Based Reasoning (CBR). At first we suggest three classification models, as partitioned neural networks, all of which convert multi-group classification problems into two group classification ones: Ordinal Pairwise Partitioning (OPP) model, binary classification model and simple classification model. The experimental results show that the partitioned NN outperformed the conventional NN. In addition, we put to use CBR that is widely used recently as a problem-solving and learning tool both in academic and business areas. With an advantage of the easiness in model design compared to a NN model, the CBR model proves itself to have good classification capability through the highest hit ratio in the corporate credit rating.

• The Journal of Asian Finance, Economics and Business
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• v.4 no.1
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• pp.5-18
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• 2017

Total debt in the People's Republic of China surged to nearly 290% as a ratio to GDP by the second quarter of 2016, mostly on account of non-financial corporate debt. The outpouring of credit to stem the impact of the global financial crisis accentuated industrial overcapacity in traditional sectors, such as steel, cement, and energy, while feeding asset bubbles in the property, equity and bond markets. At the Chinese corporate level, this has translated into weakened fundamentals and a fall in industrial profits, particularly of SOEs. As debtors struggle to service interest payments, non-performing loans (NPLs) have been on the rise. This paper assesses the financial fragility of the Chinese economy by looking at risk factors in the non-financial sector. We apply quantile regressions to a dataset containing all Chinese listed companies in Standard & Poor's IQ Capital database. We find higher sensitivity over time of corporate leverage to some of its key determinants, particularly for firms at the upper margin of the distribution. In particular, profitability increasingly acts as a curb on corporate leverage. At a time of falling profitability across the Chinese non-financial corporate sector, this eases the brake on leverage and may contribute to its continuing increase.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.8
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• pp.1-12
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• 2021

Altman's Z-score is used to measure a company's financial health and to predict the probability that a company will collapse within 2 years. It is proven to be very accurate to forecast bankruptcy in a wide variety of contexts and markets. The goal of this study is to use Altman's Z-score model to forecast insolvency in non-financial publicly traded enterprises. Non-financial firms are a significant industry in Malaysia, and current trends of consolidation and long-term government subsidies make assessing the financial health of such businesses critical not just for the owners, but also for other stakeholders. The sample of this study includes 84 listed companies in the Kuala Lumpur Stock Exchange. Of the 84 companies, 52 are considered high risk, and 32 are considered low-risk companies. Secondary data for the analysis was gathered from chosen companies' financial reports. The findings of this study show that the Altman model may be used to forecast a company's financial collapse. It dispelled any reservations about the model's legitimacy and the utility of applying it to predict the likelihood of bankruptcy in a company. The findings of this study have significant consequences for investors, creditors, and corporate management. Portfolio managers may make better selections by not investing in companies that have proved to be in danger of failing if they understand the variables that contribute to corporate distress.

• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.1
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• pp.105-128
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• 2005

The Purpose of the current study is to identify the differences between Samsung and Hyundai Group and the causes why the differences occurred. The study focuses on the founders of the two group as a main source of the differences, especially brain preference of the two founders. Two steps were employed to perform the study. Firstly, the two founders' characteristics were analyzed by using archival research. It was implicitly hypothesized that Group founders' characteristics explained the differences of the two Groups. It was found that the founder of Samsung Group, the late president Lee emphasized rationality, analysis, and cause/effect relationship and low risk taking, suggesting that he had left-brain preference. In contrast. the late president Chung, the founder of Hyundai Group, emphasized intuition, wholeness, contextual meaning, and risk taking, showing that he had right-brain preference. Secondly, a comparison between the two groups was performed in terms of business and financial risk in corporate portfolio, and management system. It was found that Hyundai Group was pursuing higher risk than Samsung Group. And it was observed that Samsung Group put more emphasis on formality in decision making and systematic control, and less emphasis on risk taking than Hyundai Group. From the two step research relationship between brian preference and management was reasoned. Research implications and limitations were discussed at the end of the study.

• The Journal of Information Systems
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• v.18 no.4
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• pp.41-57
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• 2009

Although financial information is a great influence upon determining of the group which use them, detection of management fraud and earning manipulation is a difficult task using normal audit procedures and corporate credit evaluation processes, due to the shortage of knowledge concerning the characteristics of management fraud, and the limitation of time and cost. These limitations suggest the need of systemic process for !he effective risk of earning manipulation for credit evaluators, external auditors, financial analysts, and regulators. Moot researches on management fraud have examined how various characteristics of the company's management features affect the occurrence of corporate fraud. This study examines financial characteristics of companies engaged in fraudulent financial reporting and suggests a model and system for detecting GAAP violations to improve reliability of accounting information and transparency of their management. Since the detection of management fraud has limited proven theory, this study used the detecting method of outlier(upper, and lower bound) financial ratio, as a real-field application. The strength of outlier detecting method is its use of easiness and understandability. In the suggested model, 14 variables of the 7 useful variable categories among the 76 financial ratio variables are examined through the distribution analysis as possible indicators of fraudulent financial statements accounts. The developed model from these variables show a 80.82% of hit ratio for the holdout sample. This model was developed as a financial outlier detecting system for a financial institution. External auditors, financial analysts, regulators, and other users of financial statements might use this model to pre-screen potential earnings manipulators in the credit evaluation system. Especially, this model will be helpful for the loan evaluators of financial institutes to decide more objective and effective credit ratings and to improve the quality of financial statements.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.9
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• pp.249-261
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• 2022

Globally, COVID-19 has significantly impacted many different organizations and people. From the banks' perspective, this pandemic has affected banks' corporate and retail customers. Also, banks had to adjust to distributed workforce model. This paper analyses the lessons learned from the COVID-19 pandemic, which can be effectively used to rebuild banks' Operational Risk Management capabilities. The present study used the survey research methodology, which includes structured questionnaires completed by senior banking professionals to analyze the learnings from COVID-19 and understand the distributed workforce model and remote working effectiveness. Findings: The Pandemic accelerated the pace of digital transformation. The lockdown imposed due to the pandemic led to employees working remotely, which has been effective because of enhanced digital capabilities. However, enhanced monitoring is required to prevent data-related issues, and action needs to be taken to address challenges faced in having a remote distributed workforce model, like negative impact on on-the-job learning, data-related risks, and employee wellbeing. COVID-19 is an unprecedented event that could not have been predicted in any scenario analysis. This crisis has highlighted various systemic drawbacks that need to be addressed. Banks can apply the lesson learned from this Pandemic to become more robust in the future.