• The Journal of Economics, Marketing and Management
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• v.7 no.2
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• pp.15-23
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• 2019

Purpose - This describes a comparative study about the Online banking system between developing country (Bangladesh) and developed country (South Korea). Research design, data, and Methodology - Use comparison as the descriptive situation, secondary data were used to determine the differences between both countries with respect to Online banking. And also show the representative cases of online banking, kakao bank and bKash. Result - The results showed that the data indicate that both nations are dissimilar in providing basic and additional services offered by their traditional commercial banks. And different cultures and traditions in financial industry will play a major role in the adaption and development of online banking industry among different nations. Belief on lack of effort on educating the consumers toward online banking further affected the usability of online banking in both countries. Conclusions - this comparative study provides insightful guidelines for the future development of online banking industry in developing nations and worldwide. Also, managerial and empirical implications are discussed with suggestions for future research.

• Journal of Korea Trade
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• v.25 no.1
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• pp.47-64
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• 2021

Purpose - This paper empirically analyzed the determinants of the online food market in Korea and Vietnam as representatives of the developed market and emerging market. The online food market can be regarded as having a high potential value. This study aims to suggest the appropriate implications for each developed market and emerging market by empirically comparing and analyzing customers' online food purchase determinants in the growth change of the online food market. Design/methodology - The empirical model of this study was established with the motif of the TAM+Trust model suggested by Nguyen et al.'s (2019) existing theoretical framework. Davis's (1989) TAM model was adopted to establish a framework related to the determinants that consumers would accept, for the online food purchasing method. Then, the trust variable is added to the framework which is regarded as an important effector especially in food related researches. In this study's comparative analysis, the multi-group structural equation modeling analysis was implemented. Findings - The main finding of this study can be summarized as that the moderating effect of nationality is significant. This means that there is an obvious difference between the developed online food market and the emerging online food market. In addition, as the growth of the online market changes, the significant determinants of consumers' attitudes and purchase intentions are somewhat different. However, the usefulness of online food purchasing methods and the trust of websites were analyzed as significant factors. Originality/value - Although the potential of the online food market is abundant, studies on the determinants of customer's attitude and purchase intention are insufficient. Moreover, comparative studies between countries have not been conducted in existing studies. Therefore, the research value of this paper can be explained in that it has suggested implications for the continued growth of the online food market.

• Proceedings of the Korean Nuclear Society Conference
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• 1995.10a
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• pp.333-338
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• 1995

This paper discusses the methods for building up the empirical CHF correlation, Direct Substitution Method (DSM) and Heat Balance Method (HBM). It also includes consideration on the CHF manin, which ran be expressed differently depending on the correlation types in use. Some findings an presented with exemplary calculation.

• Journal of the Korean Society of Costume
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• v.64 no.6
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• pp.161-175
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• 2014

This paper investigates the differences between characteristics of street fashions due to regional and cultural differences in southern and northern region of China. Beijing and Shenzhen were chosen as representative cities for the two areas. Empirical research and literature study were performed for this study. Empirical studies were performed by using a total of 708 images of dresses, which were collected through direct imaging. Through discussion with experts, the collected data were classified into five categories; Modern trendy, Romantic, Easy casual, Ethnic, and Classical/Traditional. The data was analyzed by using cross tabulation and frequency analysis. Content analysis for each category was also conducted. As a consequence of this study, a significant difference between Beijing and Shenzhen were observed. As a city, which puts emphasis on practicality and modernity, Beijing showed a higher frequency of modern and trendy style than the other city. On the other hand, Shenzhen showed a higher frequency of romantic style and was distinguished as a city of femininity and decorative preference of fashion style. This study intends to contribute to the academic community of Chinese fashion and to help Korean clothing companies to be launched in Chinese market in the future.

• Journal of Distribution Science
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• v.11 no.7
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• pp.47-56
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• 2013

Purpose - In the academic literature, the researches on a comparative study on purchase behaviors of the consumers from emerging and mature markets remain limited. Therefore, this empirical study is attempted to examine the effects of country of origin (COO), brand image and corporate image on the purchase behavior of Chinese consumers (as from emerging market) and Korean consumers (as from mature market). Research Design, data, methodology - In total, 615 valid questionnaires were collected from the main cities of China and Korea respectively, and a multiple group analysis was conducted to test the hypotheses with SPSS 16.0 and AMOS18.0. Results - Chinese consumers are not influenced by country-of-origin effect, whereas Korean consumers are sensitive to it. Both Chinese and Korean consumers are sensitive to brand image, whereas corporate image does appear to influence Chinese consumers but not Korean consumers. The effects of country-of-origin are not more influential in less developed market (China) than more developed market (Korea). Conclusions - According to the results of this empirical study, the country-of-origin effect does impact Korean consumers but not Chinese consumers' purchase behavior. Therefore, multinational companies are relatively free to make the decision, if Chinese consumers are the marketing targets, when choosing manufacturing sites.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.7
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• pp.111-120
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• 2021

Takaful, which is an Islamic insurance instrument, manages risks in business, according to Shariah (Islamic law) principles and offers risk protection and savings assets. The study analyzes the comparative efficiency of takaful insurance companies by implementing empirical research. The study also provides a comprehensive literature review on the efficiency analysis of the takaful industry. The empirical part presents a wide range of efficiency comparisons of 41 takaful insurance companies in 16 countries between 2009 and 2014. The data enveloping analysis technique is utilized using the rDEA package in the R environment to compute the efficiency score. In the study, the technical efficiency, overall technical efficiency, and pure technical efficiency are calculated and compared per year and per country. The findings of the study suggest that the overall average efficiency scores of takaful companies are considerably high. The study results also indicate that the excess in the consumption of inputs decreases while the deficit in achieved outputs has been declining in the covered period. The study suggests the managers of the takaful companies can use the target efficiency scores, which are calculated by using the DEA analysis, as an ideal reference benchmark for planning their inputs and outputs.

• The Journal of Industrial Distribution & Business
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• v.11 no.3
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• pp.39-50
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• 2020

Purpose: Agriculture, which is heavily influenced by climate conditions, is one of the industries most affected by climate change. In this respect, various studies on the impact of climate change on the agricultural market have been conducted. Since climate change is a long-term phenomenon for more than a decade, long-term projections of agricultural prices as well as climate variables are needed to properly analyze the impact of climate change on the agricultural market. However, these long-term price projections are often major constraints on studies of climate changes. The purpose of this study is to analyze the impacts of climate changes on the Korean onion market using ex-post analysis approach in order to avoid the difficulties of long-term price projections. Research design, data and methodology: This study develops an annual dynamic partial equilibrium model of Korean onion market. The behavioral equations of the model were estimated by OLS based on the annual data from 1988 to 2018. The modelling system is first simulated to have actual onion market conditions from 2014 to 2018 as a baseline and then compared it to the scenario assuming the climatic conditions under RCP8.5 over the same period. Scenario analyses were simulated by both comparative static and dynamic approach to evaluate the differences between the two approaches. Results: According to the empirical results, if the climate conditions under RCP8.5 were applied from 2014 to 2018, the yield of onion would increase by about 4%, and the price of onion would decrease from 3.7% to 17.4%. In addition, the average price fluctuation rate over the five years under RCP8.5 climate conditions is 56%, which is more volatile than 46% under actual climate conditions. Empirical results also show that the price decreases have been alleviated in dynamic model compared with comparative static model. Conclusions: Empirical results show that climate change is expected to increase onion yields and reduce onion prices. Therefore, the appropriate countermeasures against climate change in Korean onion market should be found in the stabilization of supply and demand for price stabilization rather than technical aspects such as the development of new varieties to increase productivity.

• Geomechanics and Engineering
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• v.30 no.1
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• pp.11-26
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• 2022

One of the most important issues in tunneling, is the squeezing phenomenon. Squeezing can occur during excavation or after the construction of tunnels, which in both cases could lead to significant damages. Therefore, it is important to predict the squeezing and consider it in the early design stage of tunnel construction. Different empirical, semi-empirical and theoretical-analytical methods have been presented to determine the squeezing. Therefore, it is necessary to examine the ability of each of these methods and identify the best method among them. In this study, squeezing in a part of the Alborz service tunnel in Iran was estimated through a number of empirical, semi- empirical and theoretical-analytical methods. Among these methods, the most robust model was used to obtain a database including 300 data for training and 33 data for testing in order to develop a machine learning (ML) method. To this end, three ML models of Gaussian process regression (GPR), artificial neural network (ANN) and support vector regression (SVR) were trained and tested to propose a robust model to predict the squeezing phenomenon. A comparative analysis between the conventional and the ML methods utilized in this study showed that, the GPR model is the most robust model in the prediction of squeezing phenomenon. The sensitivity analysis of the input parameters using the mutual information test (MIT) method showed that, the most sensitive parameter on the squeezing phenomenon is the tangential strain (ε_θ^α) parameter with a sensitivity score of 2.18. Finally, the GPR model was recommended to predict the squeezing phenomenon in tunneling projects. This work's significance is that it can provide a good estimation of the squeezing phenomenon in tunneling projects, based on which geotechnical engineers can take the necessary actions to deal with it in the pre-construction designs.

• Earthquakes and Structures
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• v.22 no.6
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• pp.609-623
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• 2022

To study the empirical seismic fragility of a reinforced concrete girder bridge, based on the theory of numerical analysis and probability modelling, a regression fragility method of a rapid fragility prediction model (Gaussian first-order regression probability model) considering empirical seismic damage is proposed. A total of 1,069 reinforced concrete girder bridges of 22 highways were used to verify the model, and the vulnerability function, plane, surface and curve model of reinforced concrete girder bridges (simple supported girder bridges and continuous girder bridges) considering the number of samples in multiple intensity regions were established. The new empirical seismic damage probability matrix and curve models of observation frequency and damage exceeding probability are developed in multiple intensity regions. A comparative vulnerability analysis between simple supported girder bridges and continuous girder bridges is provided. Depending on the theory of the regional mean seismic damage index matrix model, the empirical seismic damage prediction probability matrix is embedded in the multidimensional mean seismic damage index matrix model, and the regional rapid prediction matrix and curve of reinforced concrete girder bridges, simple supported girder bridges and continuous girder bridges in multiple intensity regions based on mean seismic damage index parameters are developed. The established multidimensional group bridge vulnerability model can be used to quantify and predict the fragility of bridges in multiple intensity regions and the fragility assessment of regional group reinforced concrete girder bridges in the future.

• Journal of Labour Economics
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• v.21 no.2
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• pp.17-46
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• 1998

In this paper, I pursue an empirical analysis of different patterns of employment and wage adjustments to demand changes for the US and Japan. Analyzed are the data in the 70's and 80's, the period that the two countries are believed to show most conspicuous diverging patterns. Using the framework of cointegration and error correction, I establish that in the US it is employment level, while in Japan it is wages, that is more responsive to output fluctuations both in the long run and the short run. All the comparisons on the long run relationships are estimated and tested based on the system cointegrating regressions, and the transition from the short run to the long run responses are investigated using impulse response analysis of the error correction models. I also study differences across genders and establishment sizes within each country. For males and females in Japan, the adjustments are significantly different both in the long run and the short run, but for the firms of different sizes they diverge only in the short run. In contrast to some of the earlier work, the gender effect turns out to be insignificant in the US.