• Journal of the Korea Fashion and Costume Design Association
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• v.13 no.2
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• pp.47-62
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• 2011

The purpose of this study was to investigate the knitwear preferences and purchase behaviors of university students. The subjects were 493 university students in Daejeon and Chungnam Provinces. The method of this study was a survey and measurement instruments were 34 stimuli which were manipulated pullover patterns and shapes and self-administrated questionnaire with knitwear design preference items and knitwear purchase behavior items. Data were analyzed by factor analysis, frequency analysis, Cronbach'${\alpha}$, t-test, ANOVA and $Sch{\acute{e}}ffe$ test using SPSS program. The results of the study were as follows. First, university students most preferred achromatic colors, pastel tones, solid patterns, and 100% cotton. Second, as for knitwear purchase behaviors, university students considered the esthetical factor to be most important among 4 dimensions (comfortable, esthetical, economical, and conspicuous factors) as important purchase criteria, and they used internet web sites for knitwear purchases. Third, there were significant differences in preferred pullover shape depending on neckline shape, neck depth, sleeve shape and clothing length. University students preferred the classic pullover design with V neckline, normal neck depth, set-in sleeves and normal length. Fourth, university students preferred the cloud motif and riding man motif among the 9 Baekje traditional motifs and one point small pattern on the left chest and crosswise bending pattern for pattern arrangement.

• The Research Journal of the Costume Culture
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• v.32 no.2
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• pp.199-214
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• 2024

Until now, research on consumers' purchasing behavior has primarily focused on psychological aspects or depended on consumer surveys. However, there may be a gap between consumers' self-reported perceptions and their observable actions. In response, this study aimed to investigate consumer purchasing behavior utilizing a big data approach. To this end, this study investigated the purchasing patterns of fashion items, both online and in retail stores, from a data-driven perspective. We also investigated whether individual consumers switched between online websites and retail establishments for making purchases. Data on 516,474 purchases were obtained from fashion companies. We used association rule analysis and K-means clustering to identify purchase patterns that were influenced by customer loyalty. Furthermore, sequential pattern analysis was applied to investigate the usage patterns of online and offline channels by consumers. The results showed that high-loyalty consumers mainly purchased infrequently bought items in the brand line, as well as high-priced items, and that these purchase patterns were similar both online and in stores. In contrast, the low-loyalty group showed different purchasing behaviors for online versus in-store purchases. In physical environments, the low-loyalty consumers tended to purchase less popular or more expensive items from the brand line, whereas in online environments, their purchases centered around items with relatively high sales volumes. Finally, we found that both high and low loyalty groups exclusively used a single preferred channel, either online or in-store. The findings help companies better understand consumer purchase patterns and build future marketing strategies around items with high brand centrality.

• Journal of the Korea Society of Computer and Information
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• v.26 no.5
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• pp.141-148
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• 2021

The purpose of this study is to explore the interaction of virtual reality consumption pattern under the background of virtual reality, and the influence of such interaction on consumers' purchase intention. In this paper, we selected three independent variables (including content interaction, function interaction and service interaction) and two mediating variables (including perceived quality and perceived value) to explore the relationship between them and consumers' purchase intention, used SPSS24.0 and AMOS24.0, made the analysis of reliability and validity, constructed the structural equation model, and tested the hypotheses. The findings show that: fourteen hypotheses are all true, and the perceived value of virtual reality has a positive influence on consumers' purchase intention. In addition, we find that the perceived value has a mediating effect in this study.

• The Research Journal of the Costume Culture
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• v.12 no.3
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• pp.369-378
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• 2004

The objectives of this study were to measure the preference and purchase intention on Korean traditional motifs and to investigate the relationship among preference, purchase intention, and sensibility. The subjects consisted of 217 male and 351 female US undergraduate students. The experimental materials used in this study were 48 stimuli and a questionnaire, composed of 7-point semantic differential scales of 17 bi-polar adjectives. The data were analyzed by ANOVA, Duncan's multiple range test, Regression, and t-test. The major findings were as follows; First, interpretation type and application object had significant effects on the preference, while category and interpretation type had significant effects on the purchase intension. The application of Korean traditional motifs for pattern design was preferred to their application for clothing design. Decorative type was found to be more related to the preference and purchase intention than the other interpretation types of realistic, stylized and abstract types. The purchase intention on crain motif was lower than the other categories of lotus and cloud motifs. Second, in overall, the preference on Korean traditional motifs was higher than purchase intention. Third, the preference and purchase intention were affected mainly by 'Quality' image, a component of sensibility, followed by 'Cheerfulness' image, but not affected by 'Simplicity' and 'Modernity' image.

• Journal of the Korean Society of Clothing and Textiles
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• v.21 no.1
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• pp.82-92
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• 1997

The purpose of this study is to segment an infant's wear market on the base of housewife's fashion life-style for satisfaction of varied needs and high efficiency of marketing activity. This study was used 183 questionnaires (20∼30 generation housewife in Seoul) for statistical analysis. This study was used factor analysis and cluster analysis to group same respondents and frequency analysis, x2_analysis, ANOVA, duncan-test to analyze characteristics of demographics, clothing purchase pattern for each segmented group. The respondents were divided into 4 groups of differnt housewife's fashion life-style matte tons according to the results of analysis. The findings of the research on each groups are summarized as follows: 1) Subdividing market was classified such as a fashion-seeking/shoping-oriented group, personality-seeking group, practical/planning group, traditional conservative group. 2) According to characteristics of demographics in Subdividing market, there were significant difference in their school career, family monthly income, existence of job. 3) According to clothing purchase pattern in Subdividing market, there were significant difference in housewife's fashion life-style. But there were only partly significant difference in characteristics of demographics. In this study, housewife's fashion life-style segmentation in infant's wear market has purpose that marketing managers are given these infornations and various wants of consumers can be satisfied.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.11a
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• pp.29-32
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• 2006

In this paper, we propose a customer personalized system that presents the web pages to users which are customized to their individuality. It analyzes the action of users who visit the shopping mall, and preferentially supplies the necessary information to them. When they actually buy some items, it forecasts the users' access pattern to web site and their following purchasable items and improves their web pare on the bases of their individuality. It reasons the relation among the web documents and among the items by using the log data of web server and the purchase information of DB. For reasoning it employs Rough Set, which is a method that searches the association rule and offers most suitable cases by reduces cases. It reasons the web pages by considering the users' access pattern and time by using the web log and reasons the users' purchase pattern by using the purchase information of DB. On the basis of the relation among them, it appends the related web pages to link of users' web pages and displays the inferred goods on users' web pages.

• Journal of Multimedia Information System
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• v.5 no.3
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• pp.195-200
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• 2018

Recently, as the sensor and big data analysis technology have been developed, there have been a lot of researches that analyze the purchase-related data such as the trajectory information and the stay time. Such purchase-related data is usefully used for the purchase pattern prediction and the purchase time prediction. Because it is difficult to find periodic patterns in large-scale human data, it is necessary to look at actual data sets, find various feature patterns, and then apply a machine learning algorithm appropriate to the pattern and purpose. Although existing papers have been used to analyze data using various machine learning methods, there is a lack of statistical analysis such as finding feature patterns before applying the machine learning algorithm. Therefore, we analyze the purchasing data of Songjeong Maeil Market, which is a data gathering place, and finds some characteristic patterns through statistical data analysis. Based on the results of 1, we derive meaningful conclusions by applying the machine learning algorithm and present future research directions. Through the data analysis, it was confirmed that the number of visits was different according to the regional characteristics around Songjeong Maeil Market, and the distribution of time spent by consumers could be grasped.

• The Korean Journal of Food And Nutrition
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• v.32 no.4
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• pp.385-394
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• 2019

This study was designed as the precedent research to develop improve the HMR type flavored cooked rice, by analyzing the consumer perception and purchase pattern. This will in turn provide base data to that will help in the development of products that meet consumer's convenience and quality demands. An online survey of 247 people (63.5%) in the age of 20 to 60 was conducted on January 2019. For the primary reason of buying those products, the survey respondents chose a convenience of 71.7%. They are likely to buy 1~2 times a month (40.5%) in hypermarkets (63.6%). The channel choice showed meaningful difference between segments (p<0.01). 89.1% of respondents replied that they are willing to purchase frozen flavored cooked rice in the future. The Key Purchasing factor appeared to be the flavor (5.80), while nutrition (4.89) was chosen as the least important factor. For flavor preference, sea food received the highest score (5.05), while radish kimchi flavor received the lowest (4.02) with a meaningful difference by gender and age (p<0.01). Consumers who sought nutrition, convenience and adventure in HMR products had higher willingness to re-purchase. Developing healthy, flavorful, sensory, and enjoyable HMR products will be critical in the fulfillment of diverse consumer needs.

• The Research Journal of the Costume Culture
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• v.18 no.2
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• pp.304-321
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• 2010

The purpose of this study was to investigate the sensation seeking tendency and knitwear purchase behaviors of high school girls. The data were obtained from 475 high school girls at 6 high schools located in Daejeon. The method of study is a survey consisted of sensation seeking tendency items, knitwear purchase behavior items and demographic attribution. Data were analyzed by frequency, variance, crosstabs, and correlation analysis using SPSS WIN 17.0 program. The results of study are as follows. First, high school girls generally liked knitwears by reason of comfort and activity. Most girls purchased the knitwears to wear ordinary casual wear(81.5%). They usually thought sweater and cardigan to be representative of knitwears. Also, they mostly purchased the knitwears of simple and active design, achromatic color, 100% cotton, and solid or simple stripe pattern. The design and price were considered as important evaluation criteria in knitwear purchase. The information sources used by them were store display, friends, and internet. Second, the knitwear purchase behaviors of high school girls showed the difference between groups with high- and low-sensation seeking tendency. The most important factor of knitwear purchase was an unique and characteristic design in high group and a simple and active design in low group. In conclusion, high school girls liked knitwears and had different knitwear purchase behaviors according to the sensation seeking tendency.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.143-146
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• 2004

With the rapid growth of e-commerce, marketers are able to observe not only purchasing behavior on what and when customers purchased, but also the individual Web usage behavior that affect purchasing. The richness of this information has the potential to provide marketers with an in-depth understanding of customer. Using commonly available Web log data, this paper examines Web usage behaviors at the individual level. By decomposing the buying process into a pattern of visits and purchase conversion at each visit, we can better understand the relationship between Web usage behavior and purchase decision. This allows us to more accurately forecast a shopper's future purchase decision at the site and hence determine the value of individual customers to the siteAccording to our research, not only information seeking behavior but also visiting duration of a customer and participative behavior such as participation in event should be considered as important predicators of purchase decision of customer in a cosmetic internet shopping mall.