• Fashion & Textile Research Journal
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• v.25 no.3
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• pp.280-290
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• 2023

As consumers are increasingly shopping online for fashion products, their return behavior is also increasing. Regarding the factors affecting return behavior, this study explores the effect of the purchasing orientation considering returns that are derived from bracketing purchase behavior, monetary lenient return policies, and non-monetary lenient return policies. Additionally, this study examines the effect of monetary/non-monetary lenient return policies on return behavior, mediated by the purchasing orientation considering returns. This study was conducted through an online survey and 238 data were collected and used for analysis. Two research models were designed for each independent variable of monetary lenient return policies, and non-monetary lenient return policies, and the path of the research model was analyzed using Process Macro 4.0. The study found that the sub-dimensions of return policy - monetary or non-monetary return policies - had different effects on return behavior through purchasing orientation considering returns. Monetary lenient return policies had a positive direct effect on return behavior, and purchasing orientation considering returns mediated the effect of the monetary lenient return policies on return behavior. However, the non-monetary lenient return policies only positively and significantly directly affected return behavior. The findings of this study contribute to understanding consumers' purchasing orientation considering returns. Furthermore, from the effect of the return policy on return behavior, the results are valuable as they can help fashion marketers establish a return strategy.

• Fashion & Textile Research Journal
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• v.11 no.1
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• pp.41-47
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• 2009

The purpose of this study was to investigate the main factors of return and consumers' return behavior types and also to find out the characteristics of consumer's purchasing behavior according to consumer's return behavior type. The Questionnaires was administered 315 males and females, who had experience of clothing purchase and return in internet shopping mall. The results were as follows. First, the factors of return were classified into quality of product, delivery, service, consumer's change of mind, and impulse buying. Second, 4 types of consumer's return behavior were categorized into habitual, dissatisfaction in product quality, dissatisfaction in delivery, and impulse buying. Third, Consumer's return behavior types were not significantly related to the frequency of purchase, information search. However there were significant differences in satisfaction of return process, dissatisfaction after return, and negative word of mouth according to the consumer's return behavior types.

• Fashion & Textile Research Journal
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• v.12 no.6
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• pp.745-754
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• 2010

This study is to find return factors when modern consumers purchase goods from an internet shopping mall and then to analyze the characteristics of complaints act and information search behavior. Subjects of research are 245 men and women, who have experience with more than one return in internet fashion shopping mall, in their twenties. The data were analyzed by using Factor analysis, Cronbach's analysis, one-way ANOVA, Duncan test as a post identification, Pearson's correlation analysis and multiple regression analysis. The results of this study are that male and female consumers in their 20s are mainly aware of the return factors: impulse buying, product status, deliver service, service after purchase, hype and comfortableness. And complains behavior often conduct public action, private action, nonaction. Information search behaviors for risk reduction when they purchase are product comparison, oral information search, neutral marketing information search, and service information search. The return factor from the internet fashion shopping had the greatest impact on public action and deliver services factor was a big complaint. In addition, impulse buying & Hype affect private action and non-action is influenced by impulse purchase. The consumer types by the return factors in internet fashion shopping mall are classified into the return group by deliver service, the return group by complex factors, and the return group by product status. Furthermore, there are significant differences in complaining behavior among these groups. In the information search behavior for reduction of risk factors, the return group by complex factors did more active information search behavior than the other groups. The return group by deliver service searched oral information and the return group by product status explored the neutral marketing information.

• Fashion & Textile Research Journal
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• v.10 no.6
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• pp.917-925
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• 2008

The purpose of this study was to find out the relationship between consumer's perceived risks and return behavior on internet clothing shopping. Questionnaires were distributed to the consumers, total 517, males and females, aged from 20 to 39, who had experience of clothing purchasing through internet shopping malls. The results showed that consumer's return factors related to the perceived risks on internet shopping process. The results were as follows. First, factors of perceived risks in internet clothing shopping were categorized into product performance, account-related, delivery, economic, and social psychological risk. 5 consumer types of perceived risk were segmented by low-perceived risk group, product performance/delivery-perceived risk group, account related-perceived risk group, harmony with oneself/account related-perceived risk group, and harmony with others/economic-perceived risk group. Second, the consumer's perceived risks on internet shopping process affected one's return behavior. The factors of return was differentiated on the types of consumer's perceived risk. The relation between consumer's perceived risks and return behavior on internet clothing shopping was significant. Therefore company had better draw various strategies to manage consumer's perceived risk, in order to reduce the returns and improve consumer's satisfaction.

• The Korean Journal of Financial Studies
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• v.3 no.1
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• pp.179-211
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• 1996

This study examines whether trading mechanisms or market microstructures of markets have an effect on the integration issue of the international equity market. If the international equity market is integrated, identical stocks listed on different international stock exchanges should have the same rates of return, the same characteristics of stock price behavior and similar distributions of return. If different market microstructures, or trading mechanisms cause differences in characteristics of stock price behavior, those can lead to different rates of return because of different liquidity risk for the same stocks between markets. This study proposes international asset pricing with liquidity risk related to trading mechanisms. Systematic risk by itself cannot predict the sign of expected rate of return difference for the same stocks between international markets. Liquidity risk factors related to market microstructure provide explanations for the sign of rate of return differences between markets, However, liquidity risk factors related to market microstructure do not have a significant effect on the rate of return differences and sensitivity of return differences between markets, Trading mechanisms or market microstructures might not have a significant effect on the interpretation of the international equity market integration studies, if trading volume or other factors are controlled.

• Journal of Powder Materials
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• v.29 no.4
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• pp.303-308
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• 2022

The plastic deformation behavior of additively manufactured anisotropic structures are analyzed using the finite element method (FEM). Hill's quadratic anisotropic yield function is used, and a modified return-mapping method based on dual potential is presented. The plane stress biaxial loading condition is considered to investigate the number of iterations required for the convergence of the Newton-Raphson method during plastic deformation analysis. In this study, incompressible plastic deformation is considered, and the associated flow rule is assumed. The modified return-mapping method is implemented using the ABAQUS UMAT subroutine and effective in reducing the number of iterations in the Newton-Raphson method. The anisotropic tensile behavior is computed using the 3-dimensional FEM for two tensile specimens manufactured along orthogonal additive directions.

• Journal of the Korean Society of Clothing and Textiles
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• v.30 no.6 s.154
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• pp.961-970
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• 2006

This study attempted to understand post-purchase consumer return experiences which had not received much attention in consumer behavior research. As a first step to understand return experiences from consumers' viewpoint, the study took an exploratory approach and identified themes and patterns from subjective consumer experiences. Whenever possible, attribution theory was applied to interpret the identified patterns. A total of 99 cases were collected from an open-ended questionnaire and analyzed based on a qualitative method. The reasons of product return was classified into five groups: changing mind; product defects; unsuitable products; products not expected; and for a better deal. External attribution was observed for return decisions caused by consumers' changed mind as well as by product defects. Dissatisfaction with defected products seemed to be intensified or reduced by service failure or success in the post-purchase service encounter. Consumer expectation and situations seemed to affect this process. Overall, the study supported attribution theory in the post-purchase return experience, and insights for research questions were proposed.

• Journal of the Korea Fashion and Costume Design Association
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• v.10 no.3
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• pp.149-161
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• 2008

Internet shopping provides convenience to consumers, however, in recent years the consumer's return rate and return-related disputes continue to increase. This article examines the characteristics of return behavior through return experiences of internet clothing purchases. For an empirical study, questionnaires were handed out to 317 undergraduate male and female students, in which the results had been used for data analysis. Data were analyzed through SPSS 12.0 software, descriptive statistics, factor analysis, t-test, ANDVA analysis, Duncan test, and $x^2-test$. The results are the following: The analysis of consumers' return factor for clothes in Internet shopping showed there are five factors: product and quality, delivery, impulse buying, change of mind, and service. There is a significant difference in product quality of return factors depending on the availability of the return experience. Thus, consumers with return experience showed more return tendency owing to product quality factor than consumers without return experience. The availability of consumer's return experience was significantly related to information search. Consumers with return experience showed more consistent information search than consumers without return experience. There were significant differences in perceived risks depending on the availability and degree of consumer's return experience. In other words, consumers with return experience perceived more account related risk than consumers without return experience. Moreover, the more return experience the consumer has, the more risks consumers perceived in product performance.

• Proceedings of the Korea Concrete Institute Conference
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• 2006.11a
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• pp.349-352
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• 2006

According to current bridge design code cable supported bridges are designed generally against 1000-year-return-period earthquake. Considering its importance, however, it may be desirable to design against 2400-year-return-period earthquake. But the seismic behavior of cable supported bridges under higher seismicity is not investigated fully. In this study, several cable supported bridges were analyzed under higher seismicity and then the response forces in prime members were compared with those analyzed under current design earthquake.

• Journal of the Korean Society of Clothing and Textiles
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• v.32 no.12
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• pp.1891-1902
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• 2008

With concerns for consumers' return behaviors affecting internet shopping malls' profits and product management in the internet clothing market, this study is designed to investigate determinants affecting return and path models for return behaviors. For an empirical study, questionnaires are prepared and respondents in their 20s and 30s with internet clothing purchase experience are selected using the convenience sampling. A total of 517 questionnaires are used for the final analysis. Data are analyzed by using SPSS 12.0 software and descriptive statistics, $x^2$-test, discriminant analysis, regression analysis, and path analysis is conducted. The results are as follows. First, ones who have returned after purchasing clothing items in internet shopping reached 63.4% of the total consumers. Respondents returned items with price at 50 thousand won or less stood at 67.2%, and the most frequent return shopping malls are open markets with their return rate at 51.1%. Second, variables such as risk perception, information search, impulse buying, buying experience, and age have a positive effect on return experience. Impulse buying and buying experience turn out to have a significant effect on the degree of return, but risk perception, information search, age, and gender to have an insignificant effect. Return intention is significantly affected by risk perception, gender, and age. Third, the analysis of path model for return experience shows that perceived risk has a positively effect, and information search has a direct effect as well as an indirect effect through buying experience or impulse buying. The analysis of path model for the degree of return shows that risk perception does not have effect, but information search has indirect effect through buying experience or impulse buying. This study is thought to find consumers' return behavior characteristics in online shopping, and help businesses operating online shopping malls to efficiently manage returns and set up strategies against returns.