• International Area Studies Review
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• v.13 no.1
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• pp.123-143
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• 2009

This paper investigates the determinants of total factor productivity(TFP) growth in Korean logistics industry such as market share, ownership structure, age of firm, firm size and debt ratio. Using financial data on individual firms in Korean logistics industry, we first estimate firm-level TFP growth rate and then, regress the estimated TFP growth rate on individual firms market power and structural characteristics. Our empirical results show that logistics firms market share is negatively correlated with their TFP growth rate. Also, we find that older or larger firms are more likely to have higher TFP growth rate.

• Structural Monitoring and Maintenance
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• v.10 no.3
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• pp.207-220
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• 2023

The safety of bridges are critical in our transportation infrastructure. Bridge design and analysis require complex structural analysis procedures to ensure their safety and stability. One common method is to calculate the maximum moment in the girders to determine the appropriate bridge section. Girder distribution factors (GDFs) provide a simpler approach for performing this analysis. A GDF is a ratio between the response of a single girder and the total response of all girders in the bridge. This paper explores the significance of GDFs in bridge analysis and design, including their importance in the evaluation of existing bridges. We utilized Bridge Weigh-in-motion (B-WIM) measurements of five simple supported girder bridge in Indonesia to develop a simple GDF provisions for the Indonesia's bridge design code. The B-WIM measurements enable us to know each girder strain as a response due to vehicle loading as the vehicle passes the bridge. The calculated GDF obtained from the B-WIM measurements were compared with the code-specified GDF and the American Association of State Highway and Transportation Officials (AASHTO) Load and Resistance Factor Design (LRFD) bridge design specification. Our study found that the code specified GDF was adequate or conservative compared to the GDF obtained from the B-WIM measurements. The proposed GDF equation correlates well with the AASHTO LRFD bridge design specification. Developing appropriate provisions for GDFs in Indonesian bridge design codes can provides a practical solution for designing girder bridges in Indonesia, ensuring safety while allowing for easier calculations and assessments based on B-WIM measurements.

• Journal of the Korea Society of Computer and Information
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• v.29 no.2
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• pp.179-195
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• 2024

The technological innovation of high-tech enterprises plays a positive driving role in operational performance. Investigating the factors influencing the operational performance of high-tech enterprises and the effects of technological innovation on operational performance is a targeted approach to promoting the growth of economic benefits and enhancing the foundation of enterprise efficiency. Additionally, it holds positive significance for the increase in market share of high-tech enterprises. This paper, considering the characteristics of high-tech enterprises, selects three influencing factors: research and development (R&D) investment intensity, the number of authorized patents, and the increment of intangible assets. Theoretical analysis is conducted on the impact mechanism and effects of these factors on operational performance. Based on this, empirical analysis is performed using relevant data of Chinese high-tech enterprises from 2011 to 2019. The study indicates that R&D investment intensity has a significant positive promoting effect on operational performance, the number of authorized patents also positively influences operational performance significantly, while the asset-liability ratio of high-tech enterprises has a notable inhibitory effect on operational performance. Finally, relevant recommendations are proposed.

• Nuclear Engineering and Technology
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• v.56 no.2
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• pp.463-471
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• 2024

Average and local convective heat transfer coefficients of nitrogen are measured experimentally in an electrically heated circular tube for a range of Reynolds number from 1.08 × 10⁴ to 3.60 × 10⁴, and wall-to-bulk temperature ratio from 1.01 to 1.77. The exit Mach number is up to 0.17, and the heat flux is up to 46 kW·m^-2. The molybdenum test section has a 62 diameters heated section with an inside diameter of 5 mm and a 30 diameters entrance section to ensure the fully-developed flow. Uncertainty of Nusselt number is less than 1.6 % in this study. The results indicate that the average heat transfer correlations evaluated by both the bulk and the modified film Reynolds numbers agree well with the experimental data. The local heat transfer results based on bulk properties are compared with previous empirical correlations. New prediction correlations are recommended which are significantly affected by the property variation and heated length. The comparison between the proposed correlations and experimental points shows that 88 % of experimental data fall into an error of 10 %, and almost all data are within an error of 20 %.

• Geomechanics and Engineering
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• v.36 no.3
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• pp.259-276
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• 2024

The undrained shear strength is widely acknowledged as a fundamental mechanical property of soil and is considered a critical engineering parameter. In recent years, researchers have employed various methodologies to evaluate the shear strength of soil under undrained conditions. These methods encompass both numerical analyses and empirical techniques, such as the cone penetration test (CPT), to gain insights into the properties and behavior of soil. However, several of these methods rely on correlation assumptions, which can lead to inconsistent accuracy and precision. The study involved the development of innovative methods using extreme gradient boosting (XGB) to predict the pile set-up component "A" based on two distinct data sets. The first data set includes average modified cone point bearing capacity (q_t), average wall friction (f_s), and effective vertical stress (σ_vo), while the second data set comprises plasticity index (PI), soil undrained shear cohesion (S_u), and the over consolidation ratio (OCR). These data sets were utilized to develop XGBoost-based methods for predicting the pile set-up component "A". To optimize the internal hyperparameters of the XGBoost model, four optimization algorithms were employed: Particle Swarm Optimization (PSO), Social Spider Optimization (SSO), Arithmetic Optimization Algorithm (AOA), and Sine Cosine Optimization Algorithm (SCOA). The results from the first data set indicate that the XGBoost model optimized using the Arithmetic Optimization Algorithm (XGB - AOA) achieved the highest accuracy, with R2 values of 0.9962 for the training part and 0.9807 for the testing part. The performance of the developed models was further evaluated using the RMSE, MAE, and VAF indices. The results revealed that the XGBoost model optimized using XGBoost - AOA outperformed other models in terms of accuracy, with RMSE, MAE, and VAF values of 0.0078, 0.0015, and 99.6189 for the training part and 0.0141, 0.0112, and 98.0394 for the testing part, respectively. These findings suggest that XGBoost - AOA is the most accurate model for predicting the pile set-up component.

• Information Systems Review
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• v.25 no.2
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• pp.103-123
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• 2023

One of the valid perspectives in the e-commerce platform literature is the seller signaling strategy in the information asymmetry situation. In this study, a research model was constructed based on signaling theory and shopping goal theory to systematically explore the effects of a seller's signaling strategy on consumer decision-making. Specifically, the study examined whether the signaling effects (i.e., reputation, electronic word-of-mouth, price) provided by the seller differed based on consumers' shopping goals. For the empirical analysis, the Gaussian Copula method was employed, utilizing 26,246 data collected from Amazon, a leading e-commerce platform. The analysis revealed that the signals provided by the seller positively impacted sales, and this effect was moderated by consumers' shopping goals. Drawing on shopping goal theory, this study contributes to signaling theory and e-commerce literature by discovering differences in the effectiveness of a seller's signaling strategy based on the keywords input by consumers.

• Journal of the Health Care and Life Science
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• v.11 no.2
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• pp.425-430
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• 2023

Sleep is known to be a major factor that reduces the quality of life in the human body.This study aimed to investigate the relationship between sleep and sleep in a group that has been diagnosed with diabetes. This study used raw data from the Community Health Survey and targeted a total of 227,754 people. Data analysis used cross-tabulation and logistic regression analysis. As a result of the analysis, gender, age, diabetes experience, subjective health status, sleep time, smoking, drinking, and blood sugar awareness were different from the diabetes experience group. In the group with diabetes diagnosis experience, the odds ratio for sleep time was 1.4 times higher in the group with 5 hours of sleep than in the group with 6 to 7 hours of sleep. In the future, empirical research may be needed to determine the relationship with sleep time, and this study showed the importance of sleep time. Based on the importance of sleep time, there is a need to develop a health management program that considers the importance of sleep for those who have been diagnosed with diabetes.

• Journal of Korea Port Economic Association
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• v.33 no.2
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• pp.53-82
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• 2017

The purpose of this study is to show the clustering trend and compare empirical results, as well as to choose the clustering ports for 3 Korean ports (Busan, Incheon, and Gwangyang) by using meta-frontier DEA (Data Envelopment Analysis) and integer models on 38 Asian container ports over the period 2005-2014. The models consider 4 input variables (birth length, depth, total area, and number of cranes) and 1 output variable (container TEU). The main empirical results of the study are as follows. First, the meta-frontier DEA for Chinese seaports identifies as most efficient ports (in decreasing order) Shanghai, Hongkong, Ningbo, Qingdao, and Guangzhou, while efficient Korean seaports are Busan, Incheon, and Gwangyang. Second, the clustering results of the integer model show that the Busan port should cluster with Dubai, Hongkong, Shanghai, Guangzhou, Ningbo, Qingdao, Singapore, and Kaosiung, while Incheon and Gwangyang should cluster with Shahid Rajaee, Haifa, Khor Fakkan, Tanjung Perak, Osaka, Keelong, and Bangkok ports. Third, clustering through the integer model sharply increases the group efficiency of Incheon (401.84%) and Gwangyang (354.25%), but not that of the Busan port. Fourth, the efficiency ranking comparison between the two models before and after the clustering using the Wilcoxon signed-rank test is matched with the average level of group efficiency (57.88 %) and the technology gap ratio (80.93%). The policy implication of this study is that Korean port policy planners should employ meta-frontier DEA, as well as integer models when clustering is needed among Asian container ports for enhancing the efficiency. In addition Korean seaport managers and port authorities should introduce port development and management plans accounting for the reference and clustered seaports after careful analysis.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.157-177
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• 2022

Investors are trading stocks by keeping a close watch on the order information submitted by domestic and foreign investors in real time through Limit Order Book information, so-called price current provided by securities firms. Will order information released in the Limit Order Book be useful in stock price prediction? This study analyzes whether it is significant as a predictor of future stock price up or down when order imbalances appear as investors' buying and selling orders are concentrated to one side during intra-day trading time. Using classification algorithms, this study improved the prediction accuracy of the order imbalance information on the short-term price up and down trend, that is the closing price up and down of the day. Day trading strategies are proposed using the predicted price trends of the classification algorithms and the trading performances are analyzed through empirical analysis. The 5-minute KOSPI200 Index Futures data were analyzed for 4,564 days from January 19, 2004 to June 30, 2022. The results of the empirical analysis are as follows. First, order imbalance information has a significant impact on the current stock prices. Second, the order imbalance information observed in the early morning has a significant forecasting power on the price trends from the early morning to the market closing time. Third, the Support Vector Machines algorithm showed the highest prediction accuracy on the day's closing price trends using the order imbalance information at 54.1%. Fourth, the order imbalance information measured at an early time of day had higher prediction accuracy than the order imbalance information measured at a later time of day. Fifth, the trading performances of the day trading strategies using the prediction results of the classification algorithms on the price up and down trends were higher than that of the benchmark trading strategy. Sixth, except for the K-Nearest Neighbor algorithm, all investment performances using the classification algorithms showed average higher total profits than that of the benchmark strategy. Seventh, the trading performances using the predictive results of the Logical Regression, Random Forest, Support Vector Machines, and XGBoost algorithms showed higher results than the benchmark strategy in the Sharpe Ratio, which evaluates both profitability and risk. This study has an academic difference from existing studies in that it documented the economic value of the total buy & sell order volume information among the Limit Order Book information. The empirical results of this study are also valuable to the market participants from a trading perspective. In future studies, it is necessary to improve the performance of the trading strategy using more accurate price prediction results by expanding to deep learning models which are actively being studied for predicting stock prices recently.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.35 no.2
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• pp.23-32
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• 2023

Probabilistic and deterministic analyses are implemented for the armor units of rubble foundation mound of composite breakwaters which is needed to protect the upright section against the scour of foundation mounds. By a little modification and incorporation of the previous empirical formulas that has commonly been applied to design the armor units of foundation mound, a new type formula of stability number has been suggested which is capable of taking into account slopes of foundation mounds, damage ratios of armor units, and incident wave numbers. The new proposed formula becomes mathematically identical with the previous empirical formula under the same conditions used in the developing process. Deterministic design have first been carried out to evaluate the minimum weights of armor units for several conditions associated with a typical section of composite breakwater. When the slopes of foundation mound become steepening and the incident wave numbers are increasing, the bigger armor units more than those from the previous empirical formula should be required. The opposite trends however are shown if the damage ratios is much more allowed. Meanwhile, the reliability analysis, which is one of probabilistic models, has been performed in order to quantitatively verify how the armor unit resulted from the deterministic design is stable. It has been confirmed that 1.2% of annual encounter probability of failure has been evaluated under the condition of 1% damage ratio of armor units for the design wave of 50 years return period. By additionally calculating the influence factors of the related random variables on the failure probability due to those uncertainties, it has been found that Hudson's stability coefficient, significant wave height, and water depth above foundation mound have sequentially been given the impacts on failure regardless of the incident wave angles. Finally, sensitivity analysis has been interpreted with respect to the variations of random variables which are implicitly involved in the formula of stability number for armor units of foundation mound. Then, the probability of failure have been rapidly decreased as the water depth above foundation mound are deepening. However, it has been shown that the probability of failure have been increased according as the berm width of foundation mound are widening and wave periods become shortening.