지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국마케팅과학회 Journal of Global Scholars of Marketing Science(마케팅과학연구) Journal of Global Scholars of Marketing Science(마케팅과학연구) 제18권 제2호
- 발행연도
- 2008.1
- 수록면
- 81 - 101 (21page)
이용수
초록· 키워드
오류제보하기
Due to the development of digital technology, studies regarding smart wear integrating
daily life have rapidly increased. However, consumer research about perception and
attitude toward smart clothing hardly could find. The purpose of this study was to
identify innovative characteristics and perceived risk of smart clothing and to analyze the
influences of theses factors on product attitudes and intention to adopt. Specifically, five
hypotheses were established.
H1: Perceived attributes of smart clothing except for complexity would have positive
relations to product attitude or purchase intention, while complexity would be
opposite.
H2: Product attitude would have positive relation to purchase intention.
H3: Product attitude would have a mediating effect between perceived attributes and
purchase intention.
H4: Perceived risks of smart clothing would have negative relations to perceived
attributes except for complexity, and positive relations to complexity.
H5: Product attitude would have a mediating effect between perceived risks and
purchase intention.
A self-administered questionnaire was developed based on previous studies. After
pretest, the data were collected during September, 2006, from university students in Korea
who were relatively sensitive to innovative products. A total of 300 final useful questionnaire were analyzed by SPSS 13.0 program. About 60.3% were male with the
mean age of 21.3 years old. About 59.3% reported that they were aware of smart
clothing, but only 9 respondents purchased it. The mean of attitudes toward smart
clothing and purchase intention was 2.96 (SD=.56) and 2.63 (SD=.65) respectively.
Factor analysis using principal components with varimax rotation was conducted to
identify perceived attribute and perceived risk dimensions. Perceived attributes of smart
wear were categorized into relative advantage (including compatibility), observability
(including triability), and complexity. Perceived risks were identified into
physical/performance risk, social psychological risk, time loss risk, and economic risk.
Regression analysis was conducted to test five hypotheses. Relative advantage and
observability were significant predictors of product attitude (adj R2=.223) and purchase
intention (adj R2=.221). Complexity showed negative influence on product attitude. Product
attitude presented significant relation to purchase intention (adj R2=.692) and partial
mediating effect between perceived attributes and purchase intention (adj R2=.698).
Therefore hypothesis one to three were accepted.
In order to test hypothesis four, four dimensions of perceived risk and demographic
variables (age, gender, monthly household income, awareness of smart clothing, and
purchase experience) were entered as independent variables in the regression models.
Social psychological risk, economic risk, and gender (female) were significant to predict
relative advantage (adj R2=.276). When perceived observability was a dependent variable,
social psychological risk, time loss risk, physical/performance risk, and age (younger)
were significant in order (adj R2=.144). However, physical/performance risk was positively
related to observability. The more Koreans seemed to be observable of smart clothing,
the more increased the probability of physical harm or performance problems received.
Complexity was predicted by product awareness, social psychological risk, economic risk,
and purchase experience in order (adj R2=.114). Product awareness was negatively related
to complexity, meaning high level of product awareness would reduce complexity of
smart clothing. However, purchase experience presented positive relation with complexity.
It appears that consumers can perceive high level of complexity when they are actually
consuming smart clothing in real life. Risk variables were positively related with
complexity. That is, in order to decrease complexity, it is also necessary to consider
minimizing anxiety factors about social psychological wound or loss of money. Thus,
hypothesis 4 was partially accepted.
Finally, in testing hypothesis 5, social psychological risk and economic risk were
significant predictors for product attitude (adj R2=.122) and purchase intention (adj R2=.099) respectively. When attitude variable was included with risk variables as
independent variables in the regression model to predict purchase intention, only attitude
variable was significant (adj R2=.691). Thus attitude variable presented full mediating
effect between perceived risks and purchase intention, and hypothesis 5 was accepted.
Findings would provide guidelines for fashion and electronic businesses who aim to
create and strengthen positive attitude toward smart clothing. Marketers need to consider
not only functional feature of smart clothing, but also practical and aesthetic attributes,
since appropriateness for social norm or self image would reduce uncertainty of
psychological or social risk, which increase relative advantage of smart clothing. Actually
social psychological risk was significantly associated to relative advantage. Economic risk
is negatively associated with product attitudes as well as purchase intention, suggesting
that smart-wear developers have to reflect on price ranges of potential adopters. It will
be effective to utilize the findings associated with complexity when marketers in US plan
communication strategy.
Due to the development of digital technology, studies regarding smart wear integrating daily life have rapidly increased. However, consumer research about perception and attitude toward smart clothing hardly could find. The purpose of this study was to identify innovative characteristics and perceived risk of smart clothing and to analyze the influences of theses factors on product attitudes and intention to adopt. Specifically, five hypotheses were established. H1: Perceived attributes of smart clothing except for complexity would have positive relations to product attitude or purchase intention, while complexity would be opposite. H2: Product attitude would have positive relation to purchase intention. H3: Product attitude would have a mediating effect between perceived attributes and purchase intention. H4: Perceived risks of smart clothing would have negative relations to perceived attributes except for complexity, and positive relations to complexity. H5: Product attitude would have a mediating effect between perceived risks and purchase intention. A self-administered questionnaire was developed based on previous studies. After pretest, the data were collected during September, 2006, from university students in Korea who were relatively sensitive to innovative products. A total of 300 final useful questionnaire were analyzed by SPSS 13.0 program. About 60.3% were male with the mean age of 21.3 years old. About 59.3% reported that they were aware of smart clothing, but only 9 respondents purchased it. The mean of attitudes toward smart clothing and purchase intention was 2.96 (SD=.56) and 2.63 (SD=.65) respectively. Factor analysis using principal components with varimax rotation was conducted to identify perceived attribute and perceived risk dimensions. Perceived attributes of smart wear were categorized into relative advantage (including compatibility), observability (including triability), and complexity. Perceived risks were identified into physical/performance risk, social psychological risk, time loss risk, and economic risk. Regression analysis was conducted to test five hypotheses. Relative advantage and observability were significant predictors of product attitude (adj R2=.223) and purchase intention (adj R2=.221). Complexity showed negative influence on product attitude. Product attitude presented significant relation to purchase intention (adj R2=.692) and partial mediating effect between perceived attributes and purchase intention (adj R2=.698). Therefore hypothesis one to three were accepted. In order to test hypothesis four, four dimensions of perceived risk and demographic variables (age, gender, monthly household income, awareness of smart clothing, and purchase experience) were entered as independent variables in the regression models. Social psychological risk, economic risk, and gender (female) were significant to predict relative advantage (adj R2=.276). When perceived observability was a dependent variable, social psychological risk, time loss risk, physical/performance risk, and age (younger) were significant in order (adj R2=.144). However, physical/performance risk was positively related to observability. The more Koreans seemed to be observable of smart clothing, the more increased the probability of physical harm or performance problems received. Complexity was predicted by product awareness, social psychological risk, economic risk, and purchase experience in order (adj R2=.114). Product awareness was negatively related to complexity, meaning high level of product awareness would reduce complexity of smart clothing. However, purchase experience presented positive relation with complexity. It appears that consumers can perceive high level of complexity when they are actually consuming smart clothing in real life. Risk variables were positively related with complexity. That is, in order to decrease complexity, it is also necessary to consider minimizing anxiety factors about social psychological wound or loss of money. Thus, hypothesis 4 was partially accepted. Finally, in testing hypothesis 5, social psychological risk and economic risk were significant predictors for product attitude (adj R2=.122) and purchase intention (adj R2=.099) respectively. When attitude variable was included with risk variables as independent variables in the regression model to predict purchase intention, only attitude variable was significant (adj R2=.691). Thus attitude variable presented full mediating effect between perceived risks and purchase intention, and hypothesis 5 was accepted. Findings would provide guidelines for fashion and electronic businesses who aim to create and strengthen positive attitude toward smart clothing. Marketers need to consider not only functional feature of smart clothing, but also practical and aesthetic attributes, since appropriateness for social norm or self image would reduce uncertainty of psychological or social risk, which increase relative advantage of smart clothing. Actually social psychological risk was significantly associated to relative advantage. Economic risk is negatively associated with product attitudes as well as purchase intention, suggesting that smart-wear developers have to reflect on price ranges of potential adopters. It will be effective to utilize the findings associated with complexity when marketers in US plan communication strategy.
Due to the development of digital technology, studies regarding smart wear integrating daily life have rapidly increased. However, consumer research about perception and attitude toward smart clothing hardly could find. The purpose of this study was to identify innovative characteristics and perceived risk of smart clothing and to analyze the influences of theses factors on product attitudes and intention to adopt. Specifically, five hypotheses were established. H1: Perceived attributes of smart clothing except for complexity would have positive relations to product attitude or purchase intention, while complexity would be opposite. H2: Product attitude would have positive relation to purchase intention. H3: Product attitude would have a mediating effect between perceived attributes and purchase intention. H4: Perceived risks of smart clothing would have negative relations to perceived attributes except for complexity, and positive relations to complexity. H5: Product attitude would have a mediating effect between perceived risks and purchase intention. A self-administered questionnaire was developed based on previous studies. After pretest, the data were collected during September, 2006, from university students in Korea who were relatively sensitive to innovative products. A total of 300 final useful questionnaire were analyzed by SPSS 13.0 program. About 60.3% were male with the mean age of 21.3 years old. About 59.3% reported that they were aware of smart clothing, but only 9 respondents purchased it. The mean of attitudes toward smart clothing and purchase intention was 2.96 (SD=.56) and 2.63 (SD=.65) respectively. Factor analysis using principal components with varimax rotation was conducted to identify perceived attribute and perceived risk dimensions. Perceived attributes of smart wear were categorized into relative advantage (including compatibility), observability (including triability), and complexity. Perceived risks were identified into physical/performance risk, social psychological risk, time loss risk, and economic risk. Regression analysis was conducted to test five hypotheses. Relative advantage and observability were significant predictors of product attitude (adj R2=.223) and purchase intention (adj R2=.221). Complexity showed negative influence on product attitude. Product attitude presented significant relation to purchase intention (adj R2=.692) and partial mediating effect between perceived attributes and purchase intention (adj R2=.698). Therefore hypothesis one to three were accepted. In order to test hypothesis four, four dimensions of perceived risk and demographic variables (age, gender, monthly household income, awareness of smart clothing, and purchase experience) were entered as independent variables in the regression models. Social psychological risk, economic risk, and gender (female) were significant to predict relative advantage (adj R2=.276). When perceived observability was a dependent variable, social psychological risk, time loss risk, physical/performance risk, and age (younger) were significant in order (adj R2=.144). However, physical/performance risk was positively related to observability. The more Koreans seemed to be observable of smart clothing, the more increased the probability of physical harm or performance problems received. Complexity was predicted by product awareness, social psychological risk, economic risk, and purchase experience in order (adj R2=.114). Product awareness was negatively related to complexity, meaning high level of product awareness would reduce complexity of smart clothing. However, purchase experience presented positive relation with complexity. It appears that consumers can perceive high level of complexity when they are actually consuming smart clothing in real life. Risk variables were positively related with complexity. That is, in order to decrease complexity, it is also necessary to consider minimizing anxiety factors about social psychological wound or loss of money. Thus, hypothesis 4 was partially accepted. Finally, in testing hypothesis 5, social psychological risk and economic risk were significant predictors for product attitude (adj R2=.122) and purchase intention (adj R2=.099) respectively. When attitude variable was included with risk variables as independent variables in the regression model to predict purchase intention, only attitude variable was significant (adj R2=.691). Thus attitude variable presented full mediating effect between perceived risks and purchase intention, and hypothesis 5 was accepted. Findings would provide guidelines for fashion and electronic businesses who aim to create and strengthen positive attitude toward smart clothing. Marketers need to consider not only functional feature of smart clothing, but also practical and aesthetic attributes, since appropriateness for social norm or self image would reduce uncertainty of psychological or social risk, which increase relative advantage of smart clothing. Actually social psychological risk was significantly associated to relative advantage. Economic risk is negatively associated with product attitudes as well as purchase intention, suggesting that smart-wear developers have to reflect on price ranges of potential adopters. It will be effective to utilize the findings associated with complexity when marketers in US plan communication strategy.
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참고문헌 (33)
참고문헌 신청
Baron,Reubern M. / 1986 / The moderator - mediator variable distinction in social psychological research: Conceptual, strategic and statistical considerations / Journal of P
Blackwell,Roger D. / 2001 / Consumer Behavior / South-Western
Fishbein,Martin / 1967 / A consideration of beliefs and their role in attitude measurement in : Reading in Attitude Theory and Measurement / John Wiley Sons : 257 ~ 286
Hawes,Jon M. / 1986 / Perceived risk and the selection of a retail patronage mode / Journal of the Academy of Marketing Science 14 (4) : 37 ~ 42
Mann,Steve / 1996 / Smart clothing: Wearable multimedia computing and personal imaging to restore the Technological balance between people and their environments / Proceedings of
Blackwell,Roger D. / 2001 / Consumer Behavior / South-Western
Fishbein,Martin / 1967 / A consideration of beliefs and their role in attitude measurement in : Reading in Attitude Theory and Measurement / John Wiley Sons : 257 ~ 286
Hawes,Jon M. / 1986 / Perceived risk and the selection of a retail patronage mode / Journal of the Academy of Marketing Science 14 (4) : 37 ~ 42
Mann,Steve / 1996 / Smart clothing: Wearable multimedia computing and personal imaging to restore the Technological balance between people and their environments / Proceedings of
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