• The Journal of Asian Finance, Economics and Business
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• v.9 no.9
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• pp.75-91
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• 2022

This study assesses the Internet banking adoption tendency by existing bank customers of Bangladesh. Currently, almost all the leading banks in the country have implemented Internet banking platforms. However, the active user count remains relatively low and there hasn't been any conclusive research on the drivers and inhibitors of Internet banking. This study evaluates the reasons and quantitatively establishes the factors leading to the adoption and usage continuance of internet banking by existing bank customers. Responses from 460 bank account holders were collected via online questionnaires using a purposive sampling approach, and a core conceptual framework based on Technology Acceptance Model (TAM) and Technology Readiness Index (TRI) was used. The study concluded that internet banking adoption is significantly impacted by the ease of use, customer service, and technology familiarity. Similarly, customer satisfaction is affected by the perceived value and the perceived risk. Through regression analysis, it was found that usage continuance is 89% explained by adoption and customer satisfaction. Multi-group moderation showed significant impact by groups divided based on usage frequency, income level, and age. Perceived risk weakened the impact of perceived value and technology familiarity on usage adoption. Additionally, perceived risk reduced the impact of consumer satisfaction and usage continuance.

• Journal of Korean Association for Spatial Structures
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• v.23 no.3
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• pp.87-94
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• 2023

Chloride is one of the most common threats to reinforced concrete (RC) durability. Alkaline environment of concrete makes a passive layer on the surface of reinforcement bars that prevents the bar from corrosion. However, when the chloride concentration amount at the reinforcement bar reaches a certain level, deterioration of the passive protection layer occurs, causing corrosion and ultimately reducing the structure's safety and durability. Therefore, understanding the chloride diffusion and its prediction are important to evaluate the safety and durability of RC structure. In this study, the chloride diffusion coefficient is predicted by machine learning techniques. Various machine learning techniques such as multiple linear regression, decision tree, random forest, support vector machine, artificial neural networks, extreme gradient boosting annd k-nearest neighbor were used and accuracy of there models were compared. In order to evaluate the accuracy, root mean square error (RMSE), mean square error (MSE), mean absolute error (MAE) and coefficient of determination (R2) were used as prediction performance indices. The k-fold cross-validation procedure was used to estimate the performance of machine learning models when making predictions on data not used during training. Grid search was applied to hyperparameter optimization. It has been shown from numerical simulation that ensemble learning methods such as random forest and extreme gradient boosting successfully predicted the chloride diffusion coefficient and artificial neural networks also provided accurate result.

• Journal of Navigation and Port Research
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• v.28 no.8
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• pp.687-697
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• 2004

This paper is aimed to guide ocean-going companies to reasonable decisions and to increase the competitiveness of Korean shipping industry by clarifying the determinants of political costs of ocean-going companies, which only depend for the enormous amount of money to introduce the operating fixed assets, or the vessels, upon the supporting policy from the government or the loan from the related financial institutions. As independent variables of the political costs, 5 elements were settled such as company size(sales, total assets and market share), debit ratio, capital concentration ratio, profitability(operating profit) and marine risk(sales fluctuation). To verify the relations and the effect level between dependent variables and political costs, the Multiple Regression Analysis Model was applied The result of the analysis shows significantly positive relations between size variables and political cost of shipping industry. Moreover, debt ratio and profitability were proved significant related with political costs of shipping industry.

• Journal of Bio-Environment Control
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• v.31 no.4
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• pp.384-392
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• 2022

The objective of this study was to estimated nitrogen content and chlorophyll using RGB, Hyperspectral sensors to diagnose of nitrogen nutrition in apple tree leaves. Spectral data were acquired through image processing after shooting with high resolution RGB and hyperspectral sensor for two-year-old 'Hongro/M.9' apple. Growth data measured chlorophyll and leaf nitrogen content (LNC) immediately after shooting. The growth model was developed by using regression analysis (simple, multi, partial least squared) with growth data (chlorophyll, LNC) and spectral data (SPAD meter, color vegetation index, wavelength). As a result, chlorophyll and LNC showed a statistically significant difference according to nitrogen fertilizer level regardless of date. Leaf color became pale as the nutrients in the leaf were transferred to the fruit as over time. RGB sensor showed a statistically significant difference at the red wavelength regardless of the date. Also hyperspectral sensor showed a spectral difference depend on nitrogen fertilizer level for non-visible wavelength than visible wavelength at June 10th and July 14th. The estimation model performance of chlorophyll, LNC showed Partial least squared regression using hyperspectral data better than Simple and multiple linear regression using RGB data (Chlorophyll R²: 81%, LNC: 81%). The reason is that hyperspectral sensor has a narrow Full Half at Width Maximum (FWHM) and broad wavelength range (400-1,000 nm), so it is thought that the spectral analysis of crop was possible due to stress cause by nitrogen deficiency. In future study, it is thought that it will contribute to development of high quality and stable fruit production technology by diagnosis model of physiology and pest for all growth stage of tree using hyperspectral imagery.

• Korean Journal of Social Welfare
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• v.57 no.4
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• pp.67-90
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• 2005

The purpose of this study is to analyze factors to affect low fertility and to investigate its implications to social welfare. For the purpose, I surveyed 360 married women and men in Gyeongnam province, and employed multi-regression, logistic regression model to process the data. I analyzed factors to influence low fertility in three aspects: demographic feature, socio-economic status, and personal sense of value. The results of analysis can be summarized as follows: (1) the period of marriage in demographic feature, income level in social economic status, and the necessity of children in personal sense of value are important factors to affect the current fertility level, (2) period of marriage, total numbers of children, gender of the first child are determining the future childbirth in demographic feature. Secondly, income level is interrelated to the future childbirth in socio-economic status. Thirdly, in the aspect of personal values, how much one needs to get married, how much one prefers son to daughter, how much one relies on one's children to realize one's dream are interrelated to the future childbirth, (3) the cost of bringing up a child as well as he expense of private education, lacking of a day nursery, and economic difficulty are causes to make people to postpone or give up childbirth. These results suggest that development of population policy to promote women's social participation and to strengthen family welfare as well as social welfare is necessary. These also implicates that if we pursue integrated policies on women, childcare, and education, we can get much more effective population welfare policy.

• Journal of the Korea Safety Management & Science
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• v.16 no.1
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• pp.53-68
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• 2014

The purpose of this study is to verify the relationships among innovative behavior, turnover intention, and job security. An additional purpose was to examine partial mediating effects on psychological ownership. The baseline of analyzing those relationships in this study is that the role of psychological ownership will be a mediator between job security and turnover intention as well as innovative behavior in the organization. To accomplish these purposes, a model was built among job security as predictor variable, the psychological ownership as mediating variable and turnover intention, and innovative behavior as criteria variables based on the studies conducted in the various areas. The 248 questionnaires surveyed from the area of DaeGu and Kyungbuk were used in the statistical analyses. The detail statistical techniques are such as descriptive analysis, reliability analysis, factor analysis, correlation analysis, and multi regression analysis. The results of the study show that job security had positively significant effect on turnover intention and innovative behavior. In addition, only the psychological ownership of organization-level thinking have partial mediating effects between job security and innovative behavior also job security and turnover intention. The results may indicate that the psychological ownership of organization-level thinking be a key factor to alleviate the turnover intention of employees and to encourage the innovative behavior during their works for the small-medium size companies showing the unstable job security.

• Journal of Korean Public Health Nursing
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• v.35 no.2
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• pp.254-267
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• 2021

Purpose: This study aimed at identifying the factors affecting the service satisfaction of urban elderly, focusing on the outreach community health service in Seoul, and suggesting policy directions for the successful implementation of community care. Method: Individuals aged 65 and 70 who used the outreach community health service from July 2017 to June 2019 were eligible for the survey. A total of 2,028 people were sampled using a proportional allocation method for each autonomous district in the survey which covered 25 districts. A multi-level logistic regression analysis was conducted, taking into account the individual's socioeconomic level, health status, type of service provided, and the healthcare-related environment and service provision period of the autonomous district. Result: The results revealed that the health status of the urban elderly, the type of services provided (health screening, linkage to community health center and clinic/hospital, medical checkup results counseling, frailty evaluation), and personal experience of the service were the major factors associated with the satisfaction with the outreach health services. Conclusion: The development of customized health services based on the close relationship between visiting nurses and the elderly may be considered to promote a sustainable community health care model.

• Journal of the Korean earth science society
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• v.38 no.4
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• pp.283-292
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• 2017

In this study, the empirical models were established to estimate the concentrations of surface-level $PM_{2.5}$ over Seoul, Korea from 1 January 2012 to 31 December 2013. We used six different multiple linear regression models with aerosol optical thickness (AOT), ${\AA}ngstr{\ddot{o}}m$ exponents (AE) data from Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Terra and Aqua satellites, meteorological data, and planetary boundary layer depth (PBLD) data. The results showed that $M_6$ was the best empirical model and AOT, AE, relative humidity (RH), wind speed, wind direction, PBLD, and air temperature data were used as input data. Statistical analysis showed that the result between the observed $PM_{2.5}$ and the estimated $PM_{2.5}$ concentrations using $M_6$ model were correlations (R=0.62) and root square mean error ($RMSE=10.70{\mu}gm^{-3}$). In addition, our study show that the relation strongly depends on the seasons due to seasonal observation characteristics of AOT, with a relatively better correlation in spring (R=0.66) and autumntime (R=0.75) than summer and wintertime (R was about 0.38 and 0.56). These results were due to cloud contamination of summertime and the influence of snow/ice surface of wintertime, compared with those of other seasons. Therefore, the empirical multiple linear regression model used in this study showed that the AOT data retrieved from the satellite was important a dominant variable and we will need to use additional weather variables to improve the results of $PM_{2.5}$. Also, the result calculated for $PM_{2.5}$ using empirical multi linear regression model will be useful as a method to enable monitoring of atmospheric environment from satellite and ground meteorological data.

• Journal of agricultural medicine and community health
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• v.44 no.2
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• pp.73-81
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• 2019

This study aimed to assess the level of awareness on safe abortion among adolescent girls in rural area of Mahottari district of Nepal. A community based cross-sectional study was conducted in rural areas of Mahottari district of Southern Nepal between January and March 2019.A sample of 412 adolescent girls was selected using multi-stage cluster sampling. Multivariable logistic regression model was adapted to explore level of awareness among adolescent girls. This study found that 45.6% of adolescent girls had high awareness regarding safe abortion. The odds of awareness among the married adolescents was higher (AOR=2.16; 95% CI: 1.01-4.87) than unmarried adolescent whereas the odds of awareness among the adolescents who had education of secondary level and more had higher (AOR=2.21; 95%CI: 1.13-3.04) than those who had primary or lower secondary level of education. Similarly, the adolescents who had monthly family income of Nepalese Rupees (NRs.), 10,000-20,000 and more than NRs. 20,000 were respectively, 2.33 times (AOR = 2.33; 95% CI: 1.07-3.55) and 3.17 times (AOR = 3.17; 95% CI: 2.19-8.94) more likelihood to have high awareness regarding safe abortion than those their counterparts. The study showed that overall level of knowledge towards safe abortion was found low. Socio-demographic factors like marital status, level of education, and family income were the factors independently associated with level of awareness on safe abortion. Therefore, efforts should be exerted towards arising and improving the awareness of abortion care which may reduce unwanted pregnancy, abortion and other complications related to abortion.

• Journal of Digital Convergence
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• v.13 no.4
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• pp.115-125
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• 2015

The purpose of this study is to empirically examines the effects of corporate sustainable management activities(social activity, economic activity, environmental activity) on the innovation activities(managerial innovation, technical innovation) in the convergence era. To accomplish these purposes, their relationships were modeled based on the previous studies conducted in the various areas. A total of 500 questionnaires were distributed to the employees working at the small & medium size companies. The statistical techniques such as descriptive analysis, reliability analysis, factor analysis, correlation analysis, multi regression analysis were used to evaluate the research model. The results of multi regression analysis show that all three aspects of corporate sustainable management activities have positively significant effects on the two factors of innovation. That is, if each activities of sustainable management works properly, it leads to create innovation. In addition, enterprises are needed to develop training programs or action planning that make the employees understands sustainable management well. Thus, the advanced level of corporate sustainability is expected if various sustainable management activities are performed in harmony with their innovation activities.