• Journal of the Korean Society of Safety
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• v.27 no.5
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• pp.30-34
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• 2012

A safety helmet is a personal protective equipment to protect the head from falling and flying objects. A safety helmet has the maximum delivered impact force as shock absorption performance, the lower delivered impact force the better performance, which was not a controlled variety during manufacturing safety helmet. Accordingly there were some difficulties in establishing the standard for improved performance as there was not a clear controllable impact force for improved performance. In this study the shock absorption performance was intended to be found as coefficient of restitution related to impulse. As a research method, a coefficient of restitution during the absorption of shock was calculated using the impulse transferred to pharynx utilizing the safety helmet shock absorption performance testing device based on the theory of momentum and impulse. The estimated impulsive force curve was derived assuming that shock was not absorbed using the measured data. The sample was selected as tested goods of ABS material for safety certification available mainly in the market. As a result of study, the maximum delivered impact force of safety helmet made by a domestic safety certified a company was 735 N, and its coefficient of restitution proved to be 0.64. The smaller coefficient of restitution is, the lower maximum delivered impact force and the higher shock absorption performance. The coefficient of restitution can be used as a performance index of safety helmet.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.4
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• pp.27-35
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• 2019

The paper examines the level of disclosure on Islamic banks' performance in the United Arab Emirates (UAE). The data was collected through content analysis of annual reports and financial statements of all fully-fledged Islamic banks working in the UAE over the period 2009 to 2013. Return on Assets is used as a proxy for the performance of Islamic banks while disclosure index is used as a proxy for Islamic banks' disclosure. Also, predetermined variables are used in the study like Size, Deposits, Non-Performing Investments and Capital to Risk Weighted Assets Ratio. Two-Stage Least-Square regression method is used to check the interdependence relationships between disclosure and performance of Islamic banks in the UAE. The results show a significant relationship between performance and disclosure in the UAE Islamic banks. Our regression results show that Islamic banks with higher levels of disclosure lead to higher operating performance. Furthermore, the performance has a great impact on the level of disclosure which means Islamic banks with high performance measures will disclose more information for investors and other institutions in order to reduce the cost of equity and increase their values in the market. This study is considered as a battery for further studies in the relationship between disclosure and financial performance of Islamic banks at a global level.

• Journal of Distribution Science
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• v.16 no.9
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• pp.53-58
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• 2018

Purpose - This study aims to examine how the time variations of customer satisfaction influence retail firms' performance. Research design, data, and methodology - The study employs yearly time series customer satisfaction data of Korean retail secured from the National Customer Satisfaction Index(NCSI) for the 2011~2016 period. Our data includes a total of 90 observations of 15 retail firms in 5 different sector(department store, filling station, large discount store, open market, TV home shopping). We obtained the firm performance data from the KIS Value database. The variables for financial performance include sales and net profit. Results - The results show that customer satisfaction has dynamic effects on retail firms' performance. More specifically, the time variation of customer satisfaction has the moderating effect on the linkage between customer satisfaction and financial performance as well as direct effects on the firms' financial performance. Conclusions - Customer satisfaction has the current effect lasting over time on firm performance and changes of customer satisfaction in positive direction also impact on firm performance. Retail firms need to not only focus on improving customer satisfaction in the current term, but make efforts to continuously enhance customer satisfaction in the long term.

• East Asian Journal of Business Economics (EAJBE)
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• v.7 no.4
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• pp.41-49
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• 2019

Purpose - This paper empirically investigates what factors contribute to corporate investments under financial constraint condition in the Korean stock market. In the paper, tangible assets' growth rate and fixed assets' growth rate were employed as investment performance and total assets were also used for comparison purpose. Research design and methodology - Samples are constructed by manufacturing firms listed on the stock market of Korea as well as those who settle accounts in December from 2001 to 2018. Financial institutions are excluded from the sample as their accounting procedures, governance and regulations differ. This study adopted a fixed panel regression model to assess the sample construction including yearly and cross-sectional data. Results - This results support the literatures that major shareholders showed positive significance to investment in financially unconstrained firms and no significance to investment in financially constrained firms. ROA showed positive significance to investment in financially unconstrained and constrained firms, whereas firm size showed negative significance to investment in financially unconstrained and constrained firms. Debt showed no positive significance to investment in financially unconstrained firms and negative significance to investment in financially constrained firms. Conclusions - This paper documented evidence that ROA and firm size are important factors to investment irrespective of firms' financial constraints. And this paper also supports that major shareholders give positive impact to investments in financially unconstrained firms. This means that financial constraints itself rule corporate' investment decision in financially constrained firms.

• International journal of advanced smart convergence
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• v.8 no.2
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• pp.132-139
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• 2019

We address the problem about forecasting the direction of stock price movement in the Korea market. Recently, the deep neural network is popularly applied in this area of research. In deep neural network systems, proper parameter initialization reduces training time and improves the performance of the model. Therefore, in our study, we propose a novel parameter initialization technique and apply this technique for the stock price movement prediction model. Specifically, we design a framework which consists of two models: a base model and a main prediction model. The base model constructed with LSTM is trained by using the large data which is generated by a large amount of the stock data to achieve optimal parameters. The main prediction model with the same architecture as the base model uses the optimal parameter initialization. Thus, the main prediction model is trained by only using the data of the given stock. Moreover, the stock price movements can be affected by other related information in the stock market. For this reason, we conducted our research with two types of inputs. The first type is the stock features, and the second type is a combination of the stock features and the Korea Composite Stock Price Index (KOSPI) features. Empirical results conducted on the top five stocks in the KOSPI list in terms of market capitalization indicate that our approaches achieve better predictive accuracy and F1-score comparing to other baseline models.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.308-314
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• 2013

Although global construction spending has experienced slow growth due to consecutive economic crises, global contractors have consistently attempted to expand their overseas market share, leading to more intense competition among contractors in the international construction market. In this market environment, owners, clients and financial institutions require reasonable and systematic criteria to effectively assess the business capabilities of international construction firms. However, the existing evaluation methods for construction firms rarely consider overseas-focused business capabilities. To address this problem, this study proposes a quantitative approach to assessing the overseas business capabilities of international construction firms. The limitations of existing approaches are reviewed, and the capabilities required to perform overseas businesses are analyzed through expert interviews. Finally, 18 evaluation indices are suggested in four categories: technology resources, project management, experience and performance, and sustainability. The relative weight of each index is determined according to the Analytical Hierarchy Process (AHP) method, and a preliminary investigation of 11 Korean construction firms is conducted. The proposed method is expected that it will provide the rational criteria for international owners, clients, and financial institutions for decision-making and for evaluating international contractors.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.25-39
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• 2021

This purpose of this study is to investigate the association among mutual funds (MFs) risk measures and return parameters, evaluate mutual fund performance and also explore the best appropriate mutual fund performance measure for investment in Pakistan. Therefore, thirty-five mutual funds have been selected for the period 2007-2015. The Sharpe, Treynor, Jensen Alpha, Information ratio and Fama's Net Selectivity measures has been used to analyze MF performance. Our study findings show significant positive relation exist between Sharpe and Jenson alpha & information ratio (IR); Treynor ratio is negatively correlated to Jenson alpha and Jenson alpha is positively allied with IR. Moreover, association among performance measures, Fama's net selectivity is a major driver in leading to other measures but Sharpe and IR lead to Treynor ratio as well. Furthermore, performance measures are ranked in accordance standard deviation with the arrangement of Fama's net selectivity at top, Jenson Alpha at second, Sharpe ratio at third, IR at fourth and Treynor ratio at fifth position according to risk parameters in Pakistan. Overall, Jensen Alpha measure appears to be the best suitable mutual fund performance measure in Pakistan due to its practical nature. Finally, the Pakistani stock market index KSE100 (as benchmark) performs better than MF industry of Pakistan.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.127-146
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• 2017

Services using artificial intelligence have begun to emerge in daily life. Artificial intelligence is applied to products in consumer electronics and communications such as artificial intelligence refrigerators and speakers. In the financial sector, using Kensho's artificial intelligence technology, the process of the stock trading system in Goldman Sachs was improved. For example, two stock traders could handle the work of 600 stock traders and the analytical work for 15 people for 4weeks could be processed in 5 minutes. Especially, big data analysis through machine learning among artificial intelligence fields is actively applied throughout the financial industry. The stock market analysis and investment modeling through machine learning theory are also actively studied. The limits of linearity problem existing in financial time series studies are overcome by using machine learning theory such as artificial intelligence prediction model. The study of quantitative financial data based on the past stock market-related numerical data is widely performed using artificial intelligence to forecast future movements of stock price or indices. Various other studies have been conducted to predict the future direction of the market or the stock price of companies by learning based on a large amount of text data such as various news and comments related to the stock market. Investing on commodity asset, one of alternative assets, is usually used for enhancing the stability and safety of traditional stock and bond asset portfolio. There are relatively few researches on the investment model about commodity asset than mainstream assets like equity and bond. Recently machine learning techniques are widely applied on financial world, especially on stock and bond investment model and it makes better trading model on this field and makes the change on the whole financial area. In this study we made investment model using Support Vector Machine among the machine learning models. There are some researches on commodity asset focusing on the price prediction of the specific commodity but it is hard to find the researches about investment model of commodity as asset allocation using machine learning model. We propose a method of forecasting four major commodity indices, portfolio made of commodity futures, and individual commodity futures, using SVM model. The four major commodity indices are Goldman Sachs Commodity Index(GSCI), Dow Jones UBS Commodity Index(DJUI), Thomson Reuters/Core Commodity CRB Index(TRCI), and Rogers International Commodity Index(RI). We selected each two individual futures among three sectors as energy, agriculture, and metals that are actively traded on CME market and have enough liquidity. They are Crude Oil, Natural Gas, Corn, Wheat, Gold and Silver Futures. We made the equally weighted portfolio with six commodity futures for comparing with other commodity indices. We set the 19 macroeconomic indicators including stock market indices, exports & imports trade data, labor market data, and composite leading indicators as the input data of the model because commodity asset is very closely related with the macroeconomic activities. They are 14 US economic indicators, two Chinese economic indicators and two Korean economic indicators. Data period is from January 1990 to May 2017. We set the former 195 monthly data as training data and the latter 125 monthly data as test data. In this study, we verified that the performance of the equally weighted commodity futures portfolio rebalanced by the SVM model is better than that of other commodity indices. The prediction accuracy of the model for the commodity indices does not exceed 50% regardless of the SVM kernel function. On the other hand, the prediction accuracy of equally weighted commodity futures portfolio is 53%. The prediction accuracy of the individual commodity futures model is better than that of commodity indices model especially in agriculture and metal sectors. The individual commodity futures portfolio excluding the energy sector has outperformed the three sectors covered by individual commodity futures portfolio. In order to verify the validity of the model, it is judged that the analysis results should be similar despite variations in data period. So we also examined the odd numbered year data as training data and the even numbered year data as test data and we confirmed that the analysis results are similar. As a result, when we allocate commodity assets to traditional portfolio composed of stock, bond, and cash, we can get more effective investment performance not by investing commodity indices but by investing commodity futures. Especially we can get better performance by rebalanced commodity futures portfolio designed by SVM model.

• Journal of Korean Institute of Industrial Engineers
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• v.34 no.1
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• pp.108-121
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• 2008

Dispatching rule for parallel machines with multi product is proposed in this paper, In current market,customer's request for higher quality is increasing, In accordance with such demand, manufacturers are focusingon improving the quality of the products. Such shift in production objective is risky. The possibility ofneglecting another important factor in customer satisfaction increases, namely due dates. From the aspect ofimproving quality, frequency of product assignment to limited number of high performance machines willincrease. This will lead to increased waiting time which can incur delays, In the case of due date orientedproduct dispatch, Products are assigned to machines without consideration for quality. Overall deterioration ofproduct quality is inevitable, In addition, Poor products will undergo rework process which can increase delays.The objective of this research is dispatching products to minimize due date delays while improving overallquality. Quality index is introduced to provide means of standardizing product quality. The index is used toassure predetermined quality level while minimizing product delays when dispatching products. Qualitystandardization method and dispatching algorithm is presented. And performance evaluation is performed withcomparison to various dispatching methods.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.6
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• pp.45-52
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• 2022

This research has the purposes of analyzing and proving empirically, such as: To investigate the effect of good corporate governance (GCG) on financial performance at banks in Indonesia through the mediating role of corporate asset growth. Theoretically, the study's results were expected to enrich and complete the repertoire of understanding in the financial management area, specifically with those phenomena related to banking financial performance and factors which influenced it. The population of this research was a bank that had a Corporate Governance Perception Index (CGPI) rating from 2011 to 2020. The type of sampling used was saturated sampling; thus, the whole population is sample members. Current data analysis used SEM. GCG has a direct or indirect impact on banking financial performance, according to the findings of this study. Improved GCG results in increased public confidence, which is reflected in an increase in total assets, as well as improved banks' financial performance. As a result, it can be stated that corporate asset increase largely mitigated the impact of GCG on bank financial performance in Indonesia. Through this rapid growth from corporate assets, Bank can maximize the market expansion which is ultimately able to improve banking financial performance.