• Asia-Pacific Journal of Business
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• v.15 no.3
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• pp.417-430
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• 2024

Purpose - This paper investigates the asymmetric capital structure adjustment toward target leverage. Our study consistently estimates heterogeneous speeds of adjustment in different regimes reflecting heterogeneity in firm characteristics. Design/methodology/approach - We collect balanced panel data on Korean listed firms over the period 2005 - 2023. In order to capture non-linearities in the speed of capital structure adjustments, this paper employs the dynamic panel threshold model that allows endogeneity in regressors and threshold variables. Findings - Using firm characteristics as proxies for adjustment costs of deviation from and adjustment to target leverage, we find asymmetric effects on the speed of capital structure adjustments. Firms of large size, with high profitability, with large cash flow and with large investment adjust capital structure faster than those with the opposite characteristics. On the other hand, firms with high growth opportunities and with high risk move slowly toward the target leverage. Research implications or Originality - This paper provides new evidence of cross-sectional asymmetries in capital structure adjustments, which calls for cautions in sample-splitting in an arbitrary manner.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.9
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• pp.315-328
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• 2020

In this study, we examined various aspects of discretionary accruals. We compared the power of Jones Model (JM), Modified Jones Model (MJM) and Performance Matched Model (PMM). Furthermore, we tested whether accruals derived from cash flow approach or balance sheet approach provide better results and we investigated the significance of country and industry control variables in models. In order to perform these tests, we constructed thirty equations. The data consists of 319 non-financial companies over five years in the GCC region. We used panel data regression models, and testing suggests us to use random effect model as the most suitable one. The results show that PMM has the highest explanatory power among models and it is followed by JM and MJM, consecutively. Secondly, results reveal that accruals derived from cash flow approach provide more accurate results. Moreover, country dummies are significant in models with cash flow approach and they lose significance in balance sheet approach. We differentiated industries due to two different classifications: the first group with higher number of industries is more precise compared to the second group with a narrower scope and lower number of industries. The model including both industrial and country-wise dummies scores highest in significance.

• Advances in nano research
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• v.16 no.3
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• pp.231-249
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• 2024

When the amplitude of the vibrations is equivalent to that clearance, the vibrations for small amplitudes will really be significantly nonlinear. Nonlinearities will not be significant for amplitudes that are rather modest. Finally, nonlinearities will become crucial once again for big amplitudes. Therefore, the concrete panel system may experience a big amplitude in this work as a result of the high temperature. Based on the 3D modeling of the shell theory, the current work shows the influences of the von Kármán strain-displacement kinematic nonlinearity on the constitutive laws of the structure. The system's governing Equations in the nonlinear form are solved using Kronecker and Hadamard products, the discretization of Equations on the space domain, and Duffing-type Equations. Thermo-elasticity Equations. are used to represent the system's temperature. The harmonic solution technique for the displacement domain and the multiple-scale approach for the time domain are both covered in the section on solution procedures for solving nonlinear Equations. An effective data-driven solution is often utilized to predict how different systems would behave. The number of hidden layers and the learning rate are two hyperparameters for the network that are often chosen manually when required. Additionally, the data-driven method is offered for addressing the nonlinear vibration issue in order to reduce the computing cost of the current study. The conclusions of the present study may be validated by contrasting them with those of data-driven solutions and other published articles. The findings show that certain physical and geometrical characteristics have a significant effect on the existing concrete panel structure's susceptibility to temperature change and GPL weight fraction. For building construction industries, several useful recommendations for improving the thermo-mechanics' behavior of structural concrete panels are presented.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.4_2
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• pp.961-972
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• 2024

As the global elderly population rapidly increases, the mental health of the elderly, particularly depression, has emerged as a significant social issue. This study analyzes the various factors influencing depression in the elderly based on the ICF model. Utilizing data from the Korea Welfare Panel Study, the study identifies the types of changes in depression among individuals aged 65 and older and examines the factors influencing these changes. This longitudinal secondary data analysis research uses the most recent three years of data (2021-2023) from the Korea Welfare Panel. The study sample consisted of 965 elderly individuals, and a latent class growth model was applied to identify the types of depression changes, while a multinomial logistic regression analysis was conducted to analyze the influencing factors. The analysis revealed that elderly depression could be categorized into four types: high-level decrease, high-level maintenance, low-level increase, and low-level maintenance. Main influencing factors included gender, age, education, poverty, social trust, social relationships, participation in economic activities, participation in religious activities, and health status. Particularly, social relationships and health status were significant factors affecting the types of depression changes. To mitigate depression in the elderly, a multifaceted approach considering both individual characteristics and social relationships and health status is required. The study suggests the development of community-based programs and trust-building activities at the community level to maintain and strengthen the social relationships of the elderly. These findings can serve as important foundational data for policies and practices aimed at improving the mental health of the elderly.

• Journal of Distribution Science
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• v.22 no.6
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• pp.1-10
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• 2024

Purpose: This study's objective is to examine the impact of firm-specific and macroeconomic factors on the business performance of non-cyclical and cyclical sectors in Indonesian listed firms. The evaluation of business performance holds paramount importance for the achievement and long-term viability of a company. Research Design Data and Methodology: The data for 61 non-cyclicals sector companies and 57 cyclicals sector companies was gathered over a 4-year period from 2018-2021. The model integrates firm size, leverage, and sales growth as firm-specific factors, with real GDP growth and inflation rate as macroeconomic variables. ROA and ROE are indicators of a firm's business performance. The regression models are estimated using the distribution of a dynamic approach with Arellano-Bond Panel Generalized Method of Moments (GMM) estimation. Results: The results of the pooled sample indicate that the historical ROA and ROE have a positive relationship with the business performance of all sectors, including both non-cyclical and cyclical industries. The ROE of non-cyclical enterprises is primarily influenced by firm-specific characteristics and macroeconomic influences. Conclusion: To ensure the successful implementation of the distribution of a dynamic approach towards enhancing corporate business performance, organizations need to take into account a combination of firm-specific factors and macroeconomic factors.

• Journal of Advanced Research in Ocean Engineering
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• v.3 no.2
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• pp.83-101
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• 2017

In this study, the added resistances of the large container ship in head and oblique seas are evaluated using a time-domain Rankine panel method. The mean forces and moments are computed by the near-field method, namely, the integration of the second-order pressure directly on the ship surface. Furthermore, a weakly nonlinear approach in which the nonlinear restoring and Froude-Krylov forces on the exact wetted surface of a ship are included in order to examine the effects of amplitudes of waves on ship motions and added resistances. The computation results for various advance speeds and heading angles are validated by comparing with the experimental data, and the validation shows reasonable consistency. Nevertheless, there exist discrepancies between the numerical and experimental results, especially for a shorter wave length, a higher advance speed, and stern quartering seas. Therefore, the accuracies of the linear and weakly nonlinear methods in the evaluation of the mean drift forces and moments are also discussed considering the characteristics of the hull such as the small incline angle of the non-wall-sided stern and the fine geometry around the high-nose bulbous bow.

• Earthquakes and Structures
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• v.23 no.6
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• pp.549-580
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• 2022

This paper assesses the influences of modeling assumptions and uncertainties on the performance of the non-linear finite element (FE) model updating procedure and model clustering method. The results of a shaking table test on a four-story steel moment-resisting frame are employed for both calibrations and clustering of the FE models. In the first part, simple to detailed non-linear FE models of the test frame is calibrated to minimize the difference between the various data features of the models and the structure. To investigate the effect of the specified data feature, four of which include the acceleration, displacement, hysteretic energy, and instantaneous features of responses, have been considered. In the last part of the work, a model-based clustering approach to group models of a four-story frame with similar behavior is introduced to detect abnormal ones. The approach is a composition of property derivation, outlier removal based on k-Nearest neighbors, and a K-means clustering approach using specified data features. The clustering results showed correlations among similar models. Moreover, it also helped to detect the best strategy for modeling different structural components.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.4
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• pp.297-305
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• 2010

Employment number by areas is composed of various factors for groups and time series. In this paper, we use the panel data for finding various variables and using this, we analyzed the factors that is major influence to employment number by areas. For analysis we looked at employment number by areas, the region for analysis consist of seven groups, that is, the metropolitan city(such as Busan, Daegu, Incheon, Gwangiu, Daejeon, Ulsan.) and Seoul. Analyzing period be formed over a 63 time points(2005.01.- 2010.03). We examined the data in relation to the employment number by occupational job, unemployment rate, monthly household income, preceding business composite index, consumer price index, composite stock price index. In looking at the factors which determine employment number by areas job, evidence was produced supporting the hypothesis that there is a significant negative relationship between unemployment rate and monthly household income the consumer price index. The consumer price index and composite stock price index are significant positive relationship, preceding business composite index is positive relationship, it are not significant variables in terms of employment number by areas job.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.12
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• pp.95-105
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• 2021

A prerequisite of a sound financial system is effective channeling of financial resources to efficient users; hence maximizing economic and societal welfare. To that end, the prevalence of bad loans in banks in emerging economies is a major policy concern. In an attempt to add to the growing body of literature explaining the interrelationship between macroeconomic and firm-specific factors, and non-performing loans (NPL), this paper examines data from 24 scheduled commercial banks in Bangladesh from 2008 to 2019. Macroeconomic factors as well as firm-specific factors related to profitability, capital strength, and efficiency are considered. Panel data regression analysis is performed to estimate pooled OLS, fixed effects, and random effects models. Following the necessary testing, it was found that the fixed effects model with robust standard error is appropriate. Results show that return on assets and inflation have a negative influence on NPL, but GDP growth has a favorable impact. The paper concludes by asserting that the evidence supports similar findings from studies both in Bangladesh and elsewhere and it is noted that a combination of these macroeconomic and firm-specific factors explains only a small portion of the total variation in NPL.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.12
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• pp.117-127
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• 2021

This study was conducted to comprehensively identify factors that potentially influence corporate investment behavior, including micro, macro, and sectoral variables. Furthermore, investment behavior was studied across nations based on their participation in the global value chain (GVC), which was evaluated based on commodities, limited manufacturing, advanced manufacturing, and innovative activities. The study uses the dynamic panel data analysis and Generalized Method of Moment (GMM) estimation for a sample of 800 corporations, with data spanning over 2000-2019. The study result shows that in all types of countries, the coefficient lag indicator of capital expenditure statistically has a significant effect on capital expenditure. Sales growth, exchange rate, and GDP have a significant positive effect on corporate investment growth, while DER has a negative effect. In commodity countries, corporate investment is influenced by sales growth, exchange rate, and FCI. The variables that influence corporate investment in manufacturing countries are the FCI, exchange rate, sales growth, GDP, and DER. In innovative countries, variables that significantly affect capital expenditure are DER, GDP, and Tobin Q. In each type of country, the interaction terms between exchange rate and commodity price are positive and statistically significant.