• Journal of Korea Port Economic Association
• /
• v.34 no.4
• /
• pp.53-68
• /
• 2018

This paper analyzes comparatively business performance indicators and determinants of small and medium sized shipping logistics companies in Korea, using 2015 economic census data. For this purpose, this study estimates various business performance indicators according to 2015 small and medium sized companies classification standards, including operating income to sales and gross value-added to sales. In addition, this study analyzes determinants of business performance using generalized least squares models. The results indicate that average sales, operating income and value-added, sales and operating income per worker, operating income to sales, and material cost to sales of large sized companies are higher than those of small and medium sized companies. The business performance indicators differ by industry and size. Moreover, the determinants of business performance are analyzed in terms of the unemployment rate (-), number of employees (-), sales (+), labor cost ratio (+), and labor cost per employee (-) and the impacts of the individual explanatory variables based on elasticity are different. Finally, this quantitative information could be used to improve the business performance of domestic shipping logistics companies.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.44 no.6
• /
• pp.1-10
• /
• 2007

This paper presents a direct nonlinear multivariable self-tuning PID controller using neural network which adapts to the changing parameters of the nonlinear multivariable system with noises and time delays. The nonlinear multivariable system is divided linear part and nonlinear part. The linear controller are used the self-tuning PID controller that can combine the simple structure of a PID controllers with the characteristics of a self-tuning controller, which can adapt to changes in the environment. The linear controller parameters are obtained by the recursive least square. And the nonlinear controller parameters are achieved the through the Back-propagation neural network. In order to demonstrate the effectiveness of the proposed algorithm, the computer simulation results are presented to adapt the nonlinear multivariable system with noises and time delays and with changed system parameter after a constant time. The proposed PID type nonlinear multivariable self-tuning method using neural network is effective compared with the conventional direct multivariable adaptive controller using neural network.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.17 no.7
• /
• pp.237-244
• /
• 2016

The workability of mortar determines its construction performance in a structure showing its designed resistance to external loads. Measuring the rheological properties of mortar is one way of quantifying its workability, but its field-applications are limited due to economical and spatial issues. The robustness of the slump flow test allows its use for evaluating the workability of mortar, even though it is a rather qualitative test method. This paper proposes a channel flow test and develops a correlation between its result and the rheological properties of mortar. The volume-of-fluid simulation for the channel flow test was accomplished, and a numerical database for the correlation was composed. A correlation model to estimate the rheological properties of mortar using the results of the channel flow test as inputs is proposed.

• Proceedings of the KOR-KST Conference
• /
• 2002.02a
• /
• pp.17-42
• /
• 2002

전통적인 OD조사에 의한 OD추정의 여러 문제점들로 인해 링크관측교통량과 기존OD를 결합해 OD를 추정하고자 하는 연구들이 제시되고 있다. Yang(1995)은 일반화최소자승법을 풀기 위한 IEA와 SAB 알고리즘을 제시하였다. 그러나 두 알고리즘의 문제점은 첫째 실제 OD를 알기가 어렵기 때문에 기존 OD를 중요한 추정기준으로 설정한다는 것으로, 이러한 추정의 종속성으로 인해, 기존 OD와 실제 OD의 차이가 큰 경우 정확한 해를 도출하지 못한다. 두 번째 문제는 통행패턴 추정시 선형근사화를 가정하기 때문에 게임이론적 측면에서 전제로 설정한 완전한 Stackelberg 상황을 구현하지 못한다는 것이다. 이러한 문제점을 피하기 위해서는 기존 OD나 관측교통량의 오차에 일관적인 해도출 기법이 필요하다. OD추정 문제는 본질적으로 비선형이고 비볼록하여 전역해 탐색기법이 필요하기 때문에 전역최적화가 가능한 유전알고리즘을 이용한 OD추정모형(GAM)을 개발하였다. 사례네트워크 분석결과, GAM은 기존 OD의 오차에 대해 크게 종속적이지 않으며 OD구조가 변하는 경우에도 추정이 가능하여, 일반적으로 실제 OD를 알 수 없는(기존OD의 오차가 어느 정도인지를 알 수 없는) 도시부 네트워크에서 신뢰성있는 추정력을 보였다. 또한 기존 OD 추정모형은 비교적 용이하게 차종별로 관측할 수 있는 링크교통량을 차종구분 없이 단일차종으로 이용함으로써, 정보의 손실을 초래하여 결과적으로 모형의 추정력을 저하시켰다. 그렇지만 다차종 링크관측교통량으로부터 다차종 OD 추정연구는 거의 없었으며, 그 결과가 단일차종에 대한 추정결과와 어떻게 다른지에 대한 연구도 전무하였다. 본 연구에서는 유전알고리즘을 이용한 OD 추정모형을 다수단 OD 추정모형(GAMUC)으로 확대하였다. 사례 분석 결과 단일차종 OD추정기법은 심각한 추정오류를 범할 수 있으며, 그 적용성도 낮다는 것을 보였다. 다차종 OD 추정기법이 단일차종 OD 추정기법보다 양호한 추정력을 보였으며, 다차종 기법 중에서는 GAMUC가 IEAMUC보다 우수한 추정력을 보였다.

• Journal of Korean Society of Transportation
• /
• v.25 no.6
• /
• pp.141-157
• /
• 2007

This paper evaluates the effects of privatization and deregulation on the firm-specific efficiency and total factor productivity (TFP) growth in the Korean and Japanese railways. Using a stochastic frontier approach and a generalized translog functional form, the paper specifies the equation system consisting of a multiproduct variable cost function and input share equations which is estimated with Zellner's iterative seemingly unrelated regression and the corrected least squares method. The Korean and Japanese railway firms are assumed to produce three outputs (Shinkansen passenger-kilometers, incumbent railway passenger-kilometers, ton-kilometers of freight) using three input factors (labor, fuel, maintenance and rolling stock). A monetary value of the ways and fixed installations held by the railroad firm is also included as a quasi-fixed input. The empirical results indicate that the average estimate of cost inefficiency is 2.57% for the total sample and on the average, JNR and JR Kyushu are found to be worst efficient while the most efficient railway firm in the sample is JR West. Also the cost efficiency levels of seven JRs have been improved after the reform and privatization of JNR. The findings also indicate that TFP growth of the privately-owned JRs are higher than those of the government-owned KNR and JNR. Three-island JRs and JR Freight have slightly higher TFP growth than Honshu JRs as well. Thus, the results suggest that managerial autonomy and increased competition via deregulation have improved efficiency and TFP growth.

• Journal of Korean Society of Transportation
• /
• v.19 no.6
• /
• pp.89-102
• /
• 2001

Using a multiproduct translog cost function model, this paper examines the existence or absence of scale and scope economies in Seoul's urban bus industry. The Paper then conceptualizes that the bus firm produces three outputs (city, seat and local bus-kilometers) using low input factors(labor, capital, fuel and maintenance). Using 1996 annual observations for 81 Seoul's bus firms, the equation system consisting of a cost function and three input share equations is estimated with the nonlinear iterative Zellner method. The findings show that the cost function corresponding to a non-homothetic production technology with separability between local bus outputs and inputs adequately represents the structure of cost for Seoul's bus firms, and that the demand lot all input factors is quite inelastic with respect to their own price. On the other hand, nearly all firms experience mild overall economies or scale, but rather marked product-specific economies of scale with respect to all the three outputs. In addition, there appear to be substantial economies or scope associated with the joint production of city and seat bus services, while considerable diseconomies of scope associated with that of city and local bus services. These results indicate that the merger of smaller firms into larger firms with a fleet of approximately 200 buses would result in more cost-efficient bus services.

• Journal of Korean Society of Transportation
• /
• v.22 no.6
• /
• pp.159-173
• /
• 2004

Using a generalized translog multiproduct cost function model, this paper examines economies of scale and scope in the vertically-integrated Korean railway industry. The paper then conceptualizes that the Korea National Railroad (KNR) produces four outputs (passenger-kilometers, ton-kilometers of freight, average length of passenger trips, and average length of freight haul) using three input factors(labor, fuel and maintenance, and rolling stock and capital). Using time series data collected from the KNR's annual records for the years from 1977 to 2002, the simultaneous equation system consisting of a cost function and two input share equatins is estimated with the Zellner's iterative seemingly unrelated regression. The findings show that the cost function corresponding to a non-Cobb-Douglas, non-homothetic, and non-homogeneous production technology adequately represents the KNR's cost structure. On the other hand, the Korean railway industry experiences sizeable overall scale economies, which result from substantial product-specific scale economies associated with passenger-kilometers and freight ton-kilometers and from scope economies associated with their joint production. In addition, the magnitude of economies of scope is influenced largely by the ratio of passenger trips, and has increased over time as the former has increased while the latter has decreased.

• 한국체육학회지인문사회과학편
• /
• v.54 no.4
• /
• pp.329-345
• /
• 2015

Our study examines the relationship between coach turnover and professional sport team performance using the evidences of Korean professional soccer teams. We collected panel dataset of 304 team-year observations and 96 coaches from Korean professional soccer league during the period of 1983-2013. Among them, our final sample is comprised of 226 observations and 81 coaches manifested for fixed-effect generalized least square (GLS) regression analysis. Drawing on sport management literatures and organizational learning theory, we argue that it takes time for a new head coach to take charge of the team in which the new leader who secure more time to interact with organization members is better able to remodel and improve team performance. Our empirical findings reveal that off-season coach turnover has a positive impact while turnover during the season has its negative influences on team performance. In addition, we find that subsequent team performance in association of off-season coach turnover is comparably better than that of on-season succession. The results show that coach succession rendered from inside the professional soccer team mediates the relationship between coach turnover and team performance. Our findings imply that coach turnover in professional sport teams is a significant factor affecting team performance.

• Journal of Korean Society of Transportation
• /
• v.24 no.2 s.88
• /
• pp.65-78
• /
• 2006

This paper investigates the cost structure ot the Korea and Japan railroad industry with respect to density, scale and scope economies as well as productivity growth rate using a generalized trans)og multiproduct cost function model. The paper then assumes that the Korea and Japan railway companies pi·educe three outputs (incumbent railway passenger-kilometers. Shinkansen passenger-kilometers, ton-kilometers of freight) using four input factors (labor, fuel, maintenance, rolling stock and capital). The specified cost function includes foul other independent variables: track lengths to reflect network effects, two dummies to reflect nation and ownership effects, and time trend as a proxy for technical change. The simultaneous equation system consisting of a cost function and three input share equations is estimated with the Zellner's iterative seemingly unrelated regression. The unbalanced panel data used in the paper, a total of 154 observations. are collected from the annual records of the Korea National Railroad (KNR) for the yews $1977{\sim}2003$, Japan National Railways (JNR) for the years $1977{\sim}1984$. seven Japan Railways (JR's) for the years $1987{\sim}2003$. The findings show that the Korean and Japanese railways exhibit product-specific and overall economies of density but product-specific diseconomies of scale with respect to incumbent railway passenger-kilometers, Shinkansen-kilometers and ton-kilometers. However, the railways experience mild overall economies of scale which result from economies of scope associated with the joint production of incumbent railway/Shinkansen and feight, freight/incumbent railway and Shinkansen except Shinkansen/incumbent railway and freight. In addition, the economies of density and scale in the KNR, JR east, JR central, and JR west companies at the point of the years $1990{\sim}2003$ average is generally analogous to the above results at the point of sample average. There also appear to be economies of ssope associated with the joint Production of the incumbent railway and Shinkansen in JR central but diseconomies of scope in JR East and JR West. The findings also indicate that the productivity growth rate of the privately-owned JR's is larger than that of the government-owned KNR.

• Journal of Intelligence and Information Systems
• /
• v.23 no.2
• /
• pp.107-122
• /
• 2017

Volatility in the stock market returns is a measure of investment risk. It plays a central role in portfolio optimization, asset pricing and risk management as well as most theoretical financial models. Engle(1982) presented a pioneering paper on the stock market volatility that explains the time-variant characteristics embedded in the stock market return volatility. His model, Autoregressive Conditional Heteroscedasticity (ARCH), was generalized by Bollerslev(1986) as GARCH models. Empirical studies have shown that GARCH models describes well the fat-tailed return distributions and volatility clustering phenomenon appearing in stock prices. The parameters of the GARCH models are generally estimated by the maximum likelihood estimation (MLE) based on the standard normal density. But, since 1987 Black Monday, the stock market prices have become very complex and shown a lot of noisy terms. Recent studies start to apply artificial intelligent approach in estimating the GARCH parameters as a substitute for the MLE. The paper presents SVR-based GARCH process and compares with MLE-based GARCH process to estimate the parameters of GARCH models which are known to well forecast stock market volatility. Kernel functions used in SVR estimation process are linear, polynomial and radial. We analyzed the suggested models with KOSPI 200 Index. This index is constituted by 200 blue chip stocks listed in the Korea Exchange. We sampled KOSPI 200 daily closing values from 2010 to 2015. Sample observations are 1487 days. We used 1187 days to train the suggested GARCH models and the remaining 300 days were used as testing data. First, symmetric and asymmetric GARCH models are estimated by MLE. We forecasted KOSPI 200 Index return volatility and the statistical metric MSE shows better results for the asymmetric GARCH models such as E-GARCH or GJR-GARCH. This is consistent with the documented non-normal return distribution characteristics with fat-tail and leptokurtosis. Compared with MLE estimation process, SVR-based GARCH models outperform the MLE methodology in KOSPI 200 Index return volatility forecasting. Polynomial kernel function shows exceptionally lower forecasting accuracy. We suggested Intelligent Volatility Trading System (IVTS) that utilizes the forecasted volatility results. IVTS entry rules are as follows. If forecasted tomorrow volatility will increase then buy volatility today. If forecasted tomorrow volatility will decrease then sell volatility today. If forecasted volatility direction does not change we hold the existing buy or sell positions. IVTS is assumed to buy and sell historical volatility values. This is somewhat unreal because we cannot trade historical volatility values themselves. But our simulation results are meaningful since the Korea Exchange introduced volatility futures contract that traders can trade since November 2014. The trading systems with SVR-based GARCH models show higher returns than MLE-based GARCH in the testing period. And trading profitable percentages of MLE-based GARCH IVTS models range from 47.5% to 50.0%, trading profitable percentages of SVR-based GARCH IVTS models range from 51.8% to 59.7%. MLE-based symmetric S-GARCH shows +150.2% return and SVR-based symmetric S-GARCH shows +526.4% return. MLE-based asymmetric E-GARCH shows -72% return and SVR-based asymmetric E-GARCH shows +245.6% return. MLE-based asymmetric GJR-GARCH shows -98.7% return and SVR-based asymmetric GJR-GARCH shows +126.3% return. Linear kernel function shows higher trading returns than radial kernel function. Best performance of SVR-based IVTS is +526.4% and that of MLE-based IVTS is +150.2%. SVR-based GARCH IVTS shows higher trading frequency. This study has some limitations. Our models are solely based on SVR. Other artificial intelligence models are needed to search for better performance. We do not consider costs incurred in the trading process including brokerage commissions and slippage costs. IVTS trading performance is unreal since we use historical volatility values as trading objects. The exact forecasting of stock market volatility is essential in the real trading as well as asset pricing models. Further studies on other machine learning-based GARCH models can give better information for the stock market investors.