본 연구는 점점 더 경쟁이 심화되고 있는 인터넷 의류시장에서 기업의 수익과 제품 관리에 영향을 미치는 소비자들의 반품행동에 관심을 갖고, 이들 반품에 영향을 미치는 결정요인 및 영향요인들의 경로관계를 규명하고자 하였다. 본 연구를 위해 인터넷 의류구매경험이 있는 20대 및 30대 남녀 소비자 517명에게 설문조사를 하였다. 반품행동에 영향을 미치는 요인의 영향을 알아본 결과, 반품여부에는 위험지각, 정보탐색, 충동구매, 구매경험, 연령이 정적인 영향을 미쳤으며 반품정도에는 충동구매, 구매경험, 성이 유의한 영향을 미쳤으나 위험지각, 정보탐색, 연령은 유의하지 않은 것으로 나타났다. 한편 반품의도에는 위험지각, 성, 연령의 영향은 유의하였으나 정보탐색, 충동구매, 구매경험의 영향은 유의하지 않은 것으로 나타났다. 반품행동에 영향을 미치는 요인들의 경로관계를 분석한 결과, 반품여부에는 위험지각이 정적으로 직접적 영향을 미치고 정보탐색은 직접적 영향뿐만 아니라 구매경험 및 충동구매를 통한 간접적 영향도 미치는 것으로 나타났다. 또한 반품정도에는 위험지각의 영향은 없었고 정보탐색은 구매경험과 충동구매를 매개로 한 간접적 영향을 미치는 것으로 나타났다. 본 연구는 인터넷 쇼핑몰이 반품율을 감소시키고 반품정책을 수립하는데 필요한 소비자들의 반품행동특성을 제공하였다는데 의의가 있다.
본 연구는 점점 더 경쟁이 심화되고 있는 인터넷 의류시장에서 기업의 수익과 제품 관리에 영향을 미치는 소비자들의 반품행동에 관심을 갖고, 이들 반품에 영향을 미치는 결정요인 및 영향요인들의 경로관계를 규명하고자 하였다. 본 연구를 위해 인터넷 의류구매경험이 있는 20대 및 30대 남녀 소비자 517명에게 설문조사를 하였다. 반품행동에 영향을 미치는 요인의 영향을 알아본 결과, 반품여부에는 위험지각, 정보탐색, 충동구매, 구매경험, 연령이 정적인 영향을 미쳤으며 반품정도에는 충동구매, 구매경험, 성이 유의한 영향을 미쳤으나 위험지각, 정보탐색, 연령은 유의하지 않은 것으로 나타났다. 한편 반품의도에는 위험지각, 성, 연령의 영향은 유의하였으나 정보탐색, 충동구매, 구매경험의 영향은 유의하지 않은 것으로 나타났다. 반품행동에 영향을 미치는 요인들의 경로관계를 분석한 결과, 반품여부에는 위험지각이 정적으로 직접적 영향을 미치고 정보탐색은 직접적 영향뿐만 아니라 구매경험 및 충동구매를 통한 간접적 영향도 미치는 것으로 나타났다. 또한 반품정도에는 위험지각의 영향은 없었고 정보탐색은 구매경험과 충동구매를 매개로 한 간접적 영향을 미치는 것으로 나타났다. 본 연구는 인터넷 쇼핑몰이 반품율을 감소시키고 반품정책을 수립하는데 필요한 소비자들의 반품행동특성을 제공하였다는데 의의가 있다.
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 prepar...
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.
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.
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문제 정의
to consumers. The findings of this study have a significance in having provided businesses with the consumer behavior characteristics that can be used in setting up strategies against returns. Though consumers experience dissatisfaction with online purchase, most of them do not express their dissatisfaction because of the complicated process of returns or refiinds.
This study aims to examine consumers' return behaviors in internet clothing shopping, focusing on the research questions below.
Thus, this study focuses on consumers' return behavior in online clothing shopping, and aims to find out the determinant factors on return and estimates the path models for examining casual relationship among affecting factors on return behaviors in online clothing shopping. 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.
Particularly, return-related damages, return rate, and consumers' claims for remedies in clothing items are high, the study of consumers1 return behaviors in online clothing shopping will have its own significance. Thus, this study focuses on consumers' return behavior in online clothing shopping, and aims to find out the determinant factors on return and estimates the path models for examining casual relationship among affecting factors on return behaviors in online clothing shopping. 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.
in online clothing shopping. Thus, this study is designed to investigate the features of consumers' return behaviors and the determinants of return in online clothing purchase.
With concerns for consumers' return behaviors affecting internet shopping malls1 profits and product management in the internet clothing market, this study was designed to investigate determinants affecting return and path models for return behaviors. Findings are as follows.
제안 방법
Especially the latter increases knowledge of products, satisfaction from searching activities, and the possibility to be exposed to impulse buying. Based on those findings, this study tries to uncover the path model of ongoing information search affecting on return through impulse buying.
First, to find out consumers1 current return status, this study investigates whether they have ever had return experience and the frequency of return during the period of analysis in internet clothing purchase. Also the latest price range of returns and return shopping malls are questioned.
Also the latest price range of returns and return shopping malls are questioned. Next, it classifies return behaviors into three aspects of return experience(yes or no), degree of retum(retum rate), and return intention and analyzes the effect of the perceived risks, information search, impulse buying, buying experience, age, and gender on each return behaviors. Especially; the analysis of factors affecting the degree of return are limited to people with return experience.
This study analyze factors affecting return such as risk perception, information search, impulse buying, and buying experience, but future studies need the introduction of other variables enabling better explanation of return behaviors. Given the effects of consumers' risk perception on returns, studies investigating return behaviors based on each risk perception factor are needed as well since risk factors perceived through online shopping is diverse and different between consumers.
대상 데이터
were distributed to them in April 2008. A total of 517 copies are used for the final analysis with inadequate 23 copies excluded. Effective respondents are made up of female 66.
성능/효과
kr) said that consumer damage cases related to online purchase constantly increased to 5, 602 cases for 2005, 9, 694 for 2006, and 14, 223 for 2007. And the types of consumer damage recorded 27.9% for refusals to retum/refunds following agreement cancellations, 18.8% for damages from unavailable contact due to website shutdown, 7.3% for complaints against delayed deliveries, and 7.2% for frauds and swindles. The products of consumer damage recorded 27.
As shown in , in the analysis of return rate, qualified respondents were classified into a group of consumers with a low return rate of less than 30%, accounting for 75.9% of the total qualified respondents, another group of consumers with a high return rate of 70% or more, accounting for 11.0%, and the other group of consumers with intennediate return rate.
First, ones who have returned after purchasing clothing items in online shopping malls reached 63.4% of the total consumers. Of those consumers who experienced returns, ones with a low return rate of less than 30% stand at 75.
Details are as follows. First, the analysis of the influence of independent variables on consumers' return experience shows that all independent variables except gender have a significant effect on consumers' return experience. In other words, the higher risk perception is, the more ongoing information search is, the higher impulse buying tendency is, and the more buying experience is, then return experiences are occurred among consumers in 30s than in 20s.
Second, the analysis of the influence of independent variables on return rate shows that impulse buying and buying experience have a significant effect, but the perceived risks, infonnation search, age, and gender don't. In other words, among consumers with return experience, the higher impulse buying is, the higher return rate is occurred, while the more buying experience is, the less return rate is occurred.
Second, the analysis of variables affecting return shows that risk perception, information search, impulse buying, buying experience, and age have a positive effect on return experience. Meanwhile, impulse buying and buying experience turn out to have a significant effect on return rate, but risk perception, information search, age, and gender to have an insignificant effect.
Third, the analysis of independent variables on return intention shows that the perceived risks, gender, and age have a significant effect on return intention, but information search, impulse buying, and buying experience don't. That is, the higher risk perception is, male and shoppers in 30s shows than female and in 20s, the higher return intention is.
Third, the analysis of path models for return behaviors shows that the perceived risks positively has direct effects on return experience, and information search has a direct effect as well as an indirect effect through buying experience or impulse buying. It shows also that risk perception does not affect return rate, but information search has indirect effects through purchase experience or impulse buying.
후속연구
Based on many previous studies, this study intends to discover the effects of determinants on return in online clothing purchase, such as the perceived risk, information search, impulse buying, buying experience and demographic variables, which are expected to affect consumers' return.
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