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[Abstract]This study aims to segment Korean clothing consumers on the basis of their actual clothing purchasing behaviors and to investigate the differences among segmented markets in terms of shopping orientation. Consumer segmentation based on purchasing behaviors is a useful approach for developing effective clothing marketing strategies in an increasingly competitive market environment. A survey was designed to utilize a systematic probable sampling from the national population. Research assistants who visited each pre-selected household were trained to follow data collecting protocol. Individuals who represented households were asked to participate to the study.A total of 1，100 Korean consumers aged between 20 and 60 successfully answered the survey.The questionnaire consisted of measurement items for clothing shopping orientation and purchasing level.The data were analyzed through exploratory factor analysis， frequency analysis， ANOVA and Duncan’s multiple range test via the SPSS program.The results were as follows.First，on the basis of numbers of purchased clothing items and money spending on clothing purchase，consumers were segmented into seven groups：Heavy buyer（High money spending-High numbers of purchase），Moderate buyer（Middle money spending-Middle numbers of purchase），Light buyer（Low money spending-Low numbers of purchase），Mm-Hn（Middle money spending-High numbers of purchase），Mm-Ln（Middle money spending-Low numbers of purchase），Hm-Mn（High money spending-Middle numbers of purchase），and Lm-Mn（Low money spending-Middle numbers of purchase）.Second，four groups were differentiated according to shopping orientation.Third， light buyer markets differed in terms of fashion sources and purchasing diversity.Therefore，the results of this study supported the assertion that clothing purchasing behavior could be a useful tool as an effective segmentation variable.
[Key words]Consumer segmentation；Clothing purchasing behavior；Clothing shopping orientation
中圖分类号：U95 文献标识码：A 文章编号：1009-914X（2015）37-0104-09
I.Introduction
An irony exists when clothing companies suffer during recession while consumer expenditure on clothes does not diminish. Such situation is insufficient to explain the relationship of overall expenditure with the amount of clothing consumption expenditure as various factors are applied. These factors include the diversity of clothing categories， differential price policies， and individual patterns of clothing consumption. The purpose of every company is to generate revenue by satisfying the desire of consumers. The market is an aggregate of various desires of numerous consumers， and satisfying such desires is difficult. During these circumstances， analyzing the changes in the dynamism of consumer behavior is important. Consumer segmentation is one of the important steps in establishing marketing strategy. Benefit segmentation categorizes consumers according to the factors they to be deem important （Lim et al.， 2010）. Using consumer segmentation strategy reinforces customized service by developing quality， usage， and shape of the product. Adjusting to the demand of the segmented submarket strengthens the appeal of products. In addition， recognizing the large segment of potential customers can guarantee the profitability and aid in designing marketing activities for addressing marketing problems.
In terms of consumer segmentation， the preceding research segmented consumers based on geographic and demographic variables （Smith，1956）. Segmenting the market based on consumer sentiments， such as lifestyle， characteristics， and individuality of each consumer， establishes potential target markets （Wells， 1975）. However， considering that the purchasing behavior of consumers is highly related to the consumption of products， consumer segmentation based on purchasing behavior is identified as an efficient approach （Grover & Srinivasan， 1987）. Behavioral segmentation is an efficient tool in marketing， but this approach does not essentially explain the factors that influence purchasing behavior （Rhee， 2007）. Moreover， this approach is expected to lead to executable strategies because it segments consumers according to their actual consumption behavior. Furthermore， behavioral segmentation categorizes consumers into heavy and light buyers according to purchasing number and price in terms of behavior， which indicates a huge difference in the amount spent on individual clothing consumption in diversified clothing markets （Kim et al.， 2011）. In addition， strategies for reinforcing the purchasing power of the light buyer， who represents the mass market， can be determined by analyzing the differences in shopping orientation for each type of consumer and examining the purchasing behavior characteristics of light buyers.
Based on the preceding discussion， this study segments consumers based on numbers of purchased clothing items and money spending on clothing purchase to understand the actual clothing purchasing behavior. This study deduces the implications of the policies for nurturing the clothing industry and the marketing， by investigating the differences in shopping orientation for each type in terms of heavy buyers and light buyers， and understanding the purchasing behavior characteristics of light buyers. II.Theoretical Background
1.Consumer segmentation
Executing the required marketing activities to the target market after segmenting consumers into groups is imperative as the competition intensifies. Setting the target market refers to defining the market limit based on “what the desire is， and who will be satisfied，” and determining the specific part of the market that the company will address （Lee， 1999）. Companies must focus on identifying and targeting the most favorable submarket because efficiently selling to the entire market is impossible upon product launching. Hence， setting a high value on the segmentation of consumers to identify the target market among the clothing consumers and establishing specific segmentation criteria are critically important.
The criteria from prior research on consumer segmentation differ depending on product feature and researchers. Kotler （1997） suggested the criteria in terms of geographic， demographic， psychological， and behavioral factors. Lee （1999） recommended segmentation criteria in terms of demographic and psychological factors at the consumer level， as well as product planning and distribution structure factors at the product level. Rhee （2007） explained the segmentation criteria in relation to clothing characteristics. The general features of consumers can be measured objectively based on demographic and society-economic factors that are related to clothing features. These features include clothing purchasing situation response， clothing brand royalty， and clothing purchasing ratio. Moreover， the general features of consumers can be measured subjectively by including the characteristic and lifestyle factors of clothing features， as well as the attitude and preference toward clothing.
The generally accepted classification variables or consumer segmentation aspects are geographical， demographical， psychological， and behavioral. Geographical factors include region， density of population， and city size. The needs and the desires of consumers differ according to geographical variables. The segmentation is relatively easy， which ensures an efficient approach to the geographically segmented market. Demographical factors include age， gender， family size， and income. This segmentation is extensively used in practical works because it is convenient to measure and is highly correlated to the desires， preferences， and usage of consumers. Psychological factors consist of the lifestyle and characteristics of consumers. Numerous consumers with different psychological characteristics are in the same demographical segmented market. In this case， using psychological segmentation is more effective. Furthermore， behavioral segmentation includes usage， attitude， and response to the product. This study points out the behavior that is the final step in the purchase decision step as a criterion of consumer segmentation. Behavior can be the most practical and fundamental clue to explain the actual purchasing behavior that reflects the consumption level. According to Jung （2010）， consumers have a strong inclination to keep up with the existing products and services because they have already built and maintained self-justifications for their choices. In addition， clothing purchasing behavior differentiates consumer segmentation to recognize consumers with different needs and desires， and is important in establishing a suitable marketing strategy. This study also subdivides the consumer market and specifically analyzes the segmented consumers in terms of actual purchasing behavior.
The results of the preceding research the analyzed attributes of consumers by stereotyping or classifying their purchasing behavior. One study defined clothing purchasing consumption as the purchasing amount or quantity for a certain period to purchase clothes （Kim et al.， 2008）. Roh and Chung （2004） compared shopping orientation by segmentation of consumers with frequency， place， required time， or clothing purchase to understand clothing purchasing behavior. Similarly， heavy buyers refer to the group with active and high volume or purchasing amount and quantity， and this group is further classified into heavy buyers， light buyers， and non-buyers according to purchasing frequency （Twedt， 1964）. Chiou and Pan （2009） also classified consumers into heavy and light shoppers according to the purchasing frequency to define the precedence factor of satisfaction and royalty.
Compared with demographic analysis， marketing strategies are related to psychological factors when analyzing product usage. Demographic analysis does not work well in terms of the unbalanced usage of product ratio； this analysis distinguishes heavy from light users or non-users （Goldsmith， 2000）. Cherney （2008） investigated the effect of the quantity of consumer purchase on product selection and reported that consumers selected the product with the same quantity as their desired purchasing quantity when they could not select the preferred items. Kim （1994） examined the relationship among frequency， quantity， and selection behavior or purchasing by brand preference and price sensibility， and concluded that consumers with a high score on frequency or quantity have a higher price sensibility and tend to prefer the brands of their respective countries. Goldsmith （2000） subdivided the clothing consumer market， and indicated that heavy buyer groups set the trend， tend to be more aggressive and less sensitive to price， and are knowledgeable about new clothing trends. Similar to the aforementioned cases， several studies compared and analyzed the consumer segmentation with only one factor； meanwhile， other studies examined such segmentation by subdividing consumers into complex groups using several factors. Kim et al. （2011） investigated the differences in intention to maintain the brand relation by segmenting groups after subdividing consumers into four groups with two criteria of consumption level in terms of purchasing amount and quantity of luxury clothing brand products. To segment the complex consumers， the current study segments consumer groups by performing a crossover analysis of practical numbers of purchased clothing items and money spending on clothing purchase.
2.Clothing shopping orientation
Stone （1954） related shopping orientation to lifestyle. Darden and Howell （1987） defined shopping orientation as a specific lifestyle of shopping category， which includes shopping activities， interests， and opinions.
Clothing shopping orientation denotes the aspect of patterned clothing shopping with clothing shopping-specific lifestyle， which combines personal activity， interest， and opinion on clothing shopping. As a concept， shopping orientation with behavioral and psychological profiles appears before， during， and after shopping for clothing （Kim & Rhee， 2004）.
The criteria of clothing shopping orientation suggested by various studies are related to clothing consumer behaviors， which consist of five factors， namely， economy， characteristic， ethic， indifference， and indeterminacy （Stone， 1954）. Yang et al. （2012） explained clothing shopping orientation by segmenting this behavior into pleasure， trend， plan， characteristic， brand， economy， and showing off. Park et al. （2011） used the factors related to clothing， such as pursuit of pleasure， trend， brand， economy， and convenience.
Prior research principally considered shopping orientation as a major variation to explain purchasing behavior or suggested the marketing application plan by segmenting consumers with the attribute of shopping orientation （Chu et al.， 2013； Lee & Kim， 2008； Mokhlis， 2006）. Chu et al. （2013） examined the Generation Y consumer segments’ selection attributes and willingness to pay for the environmentally friendly clothing. They identified three different consumer segments according to their green consumption styles and attitudes toward shopping and fashion， and there was a significant difference among their willingness to pay for the environmentally friendly clothing. Lee and Kim （2008） investigated the effects of consumers’ shopping orientation on purchase behavior using multi-channels. The results showed that both confident/fashion-conscious consumers and mall shopping-oriented shoppers were more satisfied with store-based retail channels for apparel purchases， whereas non-local store-oriented shoppers and catalog/internet-oriented shoppers were more satisfied with non-store-based retail channels for their apparel purchases. Mokhlis （2006） indicated that three shopping orientation factors， namely quality conscious， impulsive shopping and price conscious were related to religiosity， suggesting that religiosity should be considered as a possible determinant of shopping orientations in consumer behavior model. Moreover， several studies examined the differences in shopping orientation by segmenting consumers based on clothing behavior level. Lim （2007） analyzed clothing involvement， shopping orientation， and clothing purchasing behavior according to the types of information source usage. According to usage of information sources， female consumers were classified into four groups： active； non-personal； personal； non-active information source usage group， and fashion involvement was the most significant involvement factor to divide four groups. Jean and Sung （2008） compared the differences in clothing shopping orientation according to the experience of Internet clothing shopping.
Clothing shopping orientation is a useful variation to understand the shopping behavior and attitude of consumers， and is highly related to clothing purchasing behavior. However， research is insufficient in terms of the differences in clothing shopping orientation by purchasing behavior because most studies have focused on the differences in shopping orientation. Hence， this study defines the differences in shopping orientation by classifying consumers based on their clothing purchasing behavior.
III.Method
1.Subject of study
This study compares and analyzes the attributes of clothing shopping orientation according to consumer groups segmented by clothing purchasing behavior from a national population. Specifically， the study：
i）Classifies consumers according to clothing purchasing behavior （numbers of purchased clothing items， money spending on clothing purchase），and
ii）Compares and analyzes the differences of shopping orientation among segmented groups.
2.Data collection
This study was conducted from May 27 to July 3， 2013， and targeted Korean consumers. Research assistants visited each pre-selected household， briefly explained the survey， and handed out the questionnaires. The completed questionnaires were immediately collected after being answered. This study selected the household population aged between 20 and 64 based on the 2010 census of population householder distribution. The study collected 1，100 questionnaires by performing prorating and probability proportion sampling according to the gender and age of citizens in 16 provinces of Korea. The data of 1，100 questionnaries came from 1，100 respondents based on six months of actual purchasing behavior. Every respondent was the householder of one house. Data were analyzed through exploratory factor analysis， frequency analysis， ANOVA， and Duncan’s multiple range test via SPSS 18.0. The results of the study were based on six months of actual purchasing data.
3.Data measurement
This study used the survey method. The questionnaire consisted of three parts， namely， （1）？clothing purchasing behavior； （2） clothing shopping orientation； （3） fashion source. The selection and the development of a measurement tool for measuring each variation were revised and complemented by the qualified questions in reliability and validity of previous studies.
（1）Measurement of clothing purchasing behavior
This study asked the respondents to describe their numbers of purchased clothing items and the clothing expenditure per month in the recent six months using a free-description approach. The 14 suggested item categories are men’s formal， women’s formal， casual， sports， outdoor， underwear， kids， fur， bag， formal shoes， casual shoes， accessories， and socks/scarf， etc. The respondents were instructed to answer the purchasing number per each category of the questions. For example， “numbers of outside clothing items” consisted of men’s formal， women’s formal， casual， sports， and outdoor.
（2）Clothing shopping orientation
The measurement items of clothing shopping orientation were revised and complemented by questionnaire used in Moye and Kincade （2003）. The measure of clothing shopping orientation are multi-item scales， devided into four variables， consists of twelve questionnaire items from previous study （Park et al.， 2012； Yang et al.， 2012）. In this study， we defined clothing shopping orientation as brand/trend， personality， convenience， and economy. Each measurement item was answered using a seven-point Likert scale （1=Strongly disagree， 7= Strongly agree）.
（3）Fashion source
The construct of fashion source can be measured with three items： “My information is mainly obtained from department store’s mail advertising，” “My information is mainly obtained from fashion magazine” and “My information is mainly obtained from celebrity dress”. All items were measured on a seven-point Likert scale （1=Strongly disagree， 7= Strongly agree）.
IV. Results and Discussion
1.Sample
A questionnaire survey of household respondents， all currently living in Korea， included single-person household and multi-member household. Table 1 presents the demographical analysis of the 1，100 respondents for final data analysis. For gender， women comprised 69.5%， which was more than half. For age， 50+ years accounted for 35.6%， followed by 40s （31.4%）， 30s （23.8%）， and 20s （9.2%）. The age range indicated that respondents generally belonged to the old age group. For regional distribution， Incheon/Gyeonggi （29.0%） and Seoul （21.0%） led the group， whereas other provinces were equally distributed. For education level， respondents who had higher college education were 52.6%， high school diploma accounted for 43.5%， and lower than middle school diploma was 3.8%. For marital status， married respondents comprised 86.4%， singles were at 10%， and widows， divorced， separated accounted for 0.3%. For occupation， housewives led at 26.6%， followed by owner-operators （23.7%）， white collar （23.7%）， and blue collar workers （22.5%）. For average monthly income， 3 to 4？million KRW comprised 27.5% and 4 to 5？million KRW accounted for 24.3%. For the number of household members， most respondents belonged to a four-member （43.5%）， three-member （25.9%）， two-member （14.4%）， single-member （11.1%）， and five-member household （5.1%）. 2.Reliability and validity assessments
This study investigated reliability and validity assessments. The Cronbach’s α of this study proved the reliability of the measurement items. We also performed exploratory factor analysis to verify convergent validity and discriminative validity. Principal component analysis was conducted with Varimax rotation and an Eigen value of 1 as selection criteria. Approximate value with 0.919 of factor 4 （economy） was also 1 （see Table 2）.
Shopping orientation consisted of four factors， and the factors explaining a total variance 65.385%. Factor 1 （Brand/Trend） contained questions about the trend and brand preference when respondents purchase clothing items. Factor 2 （Personality） represented the uniqueness of preferred clothing items. Factor 3 （Convenience） reflected the comfort when respondents purchase clothing items. Factor 4 （Economy） referred to the contents of price sensibility. The results were supported by previous research. Park et al. （2012） examined intention to use and word-of-mouth for clothing social network service， and reported the correlation of clothing shopping orientation with pursuit of pleasure， trend， brand， convenience， and economy. Yang et al. （2012） investigated the influences of shopping orientation on selection criteria， attitudes， and preference of collaborated clothing products， and established the correlation of shopping orientation with pursuit of pleasure， trend， plan， personality， brand， economy， and showing off.
3.Consumer segmentation based on clothing purchasing behavior
This study presents two criteria for segmenting consumers according to clothing purchasing behavior， namely， money spending on clothing purchasing and numbers of purchase clothing items. Numbers of purchased clothing items refers to the sum of purchased items of outside clothing （men’s formal， women’s formal， casual， sports， outdoor）. Money spending on clothing purchase denotes the average amount of expenditure per month in the recent six months. In addition， 1，073 respondents were used in the final analysis by categorizing， except the case of non-shoppers in the recent six months and respondents with less than 1，000？KRW for purchasing expenditure.
The results of frequency analysis of money spending on clothing purchasing and numbers of purchase clothing items to identify the consumer segmentation criteria indicated that for the numbers of purchased clothing items， the mean value was 5.61 and the median value was 5.00. For money spending on clothing purchasing， the mean value was 104，017 KRW and the median value was 71.667 KRW （see Table 3）. This study segmented purchasing into three groups： Less than 33.3% = Low； 33.3% to 66.6% = Middle； and more than 66.6% = High purchasing group， respectively. The grouping resulted in nine groups using a 3×3 matrix， with three groups in terms of money spending on clothing purchasing and numbers of purchase clothing items （see Table 4）. Two groups （Low numbers of purchase and High money spending； High numbers of purchase and Low money spending） were excluded because the respondents were extremely few in the two groups， and they posed difficulty in comparing and analyzing them with other groups. This study primarily focused on the comparison of three groups， namely， Light buyer with Low money spending and Low numbers of purchased； Moderate buyer with Middle money spending and Middle numbers of purchased； Heavy buyer with High money spending and High numbers of purchased. The study also covered the comparison analysis of four groups， namely， Mm-Hn group （Middle money spending and High numbers of purchase） and Mm-Ln group （Middle money spending and Low numbers of purchase） with the same level of expenditure and a different level of numbers， and Lm-Mn group （Low money spending and Middle numbers of purchase） and Hm-Mn group （High money spending and Middle numbers of purchase） with the same level of numbers but a different level of expenditure. Furthermore， the results also indicated a positive correlation between money spending on clothing purchasing and numbers of purchase clothing items， that is， 0.597 correlation coefficient. This finding suggests that a higher purchasing number results in a higher purchasing expenditure.
The study segmented consumers based on money spending on clothing purchasing and numbers of purchase clothing items as previously described. Table 5 presents the results of group segmentation verification through clarifying the value of numbers of purchase outside clothing items and money spending for six months. The comparison indicated significant differences. The Heavy buyer group scored the highest level of numbers of purchase and money spending， followed by the Moderate buyer group and Light buyer group. Comparing the amount of money spending， Hm-Mn group was higher than Lm-Mn group； meanwhile， the numbers of purchase of both groups was similar. Comparing the numbers of purchased clothing items， Mn-Hn group was higher than Mn-Ln group； however， both groups exhibited a similar amount of money spending.
4.Differences in household attributes based on clothing purchasing behavior
The study compared the differences among groups in terms of average monthly income of household and number of household members to clarify the differences in the attributes of each household according to clothing purchasing behavior. The comparison was conducted through one-way ANOVA analysis （Table 6）.
For household income， Heavy buyer and Hm-Mn groups earned the most， followed by the Moderate buyer， Lm-Mn， Mn-Hn， and Mn-Ln groups. The Light buyer group scored the least. The three major groups （Heavy buyer； Moderate buyer； Light buyer） indicated that a larger amount of numbers of purchased clothing items and money spending of consumers resulted from the higher average monthly income of household. In addition， when comparing the Hm-Mn and Lm-Mn groups in terms of middle number， the larger the amount of money the consumer spent， the more income the consumer earned despite similar amounts in terms of numbers of purchased clothing items. Comparing Mm-Hn and Mm-Ln groups in terms of middle money， these groups were in a similar level of household income regardless of numbers of purchased clothing items； at the same time， they had a similar amount of money spending on clothing purchase.
For the number of household members， Heavy buyer had the highest number， followed by Hm-Mn， Mn-Hn， Moderate buyer， and Lm-Mn groups. The Light buyer and Mm-Ln groups had the least number of household members. The three major groups （Heavy buyer； Moderate buyer； Light buyer） indicated that consumers with high amounts of numbers of purchased clothing items and money spending had more household members than others. In addition， when comparing Hm-Mn and Lm-Mn groups in terms of middle number， the higher amount of money the consumer spent indicated more household members even if both groups had a similar level of numbers of purchased clothing items. When comparing Mm-Hn and Mm-Ln groups in terms of middle money， the higher numbers of purchased clothing items the consumer indicated more household members of the consumer despite both groups having similar levels of money spending on clothing purchase. 5.Differences in clothing shopping orientation based on clothing purchasing behavior
The study conducted one-way ANOVA analysis to determine the differences between shopping orientations according to purchasing behavior type. The results indicated meaningful differences in terms of brand/trend， personality， convenience， and economy （see Table 7）.
In terms of the shopping orientation of trend/brand， the Heavy buyer group scored the most， followed by Moderate buyer， Hm-Mn， and Mm-Ln groups. The Light buyer， Lm-Mn， and Mm-Hn groups showed lower levels of shopping orientation for trend/brand. The major three groups （Heavy buyer； Moderate buyer； Light buyer） indicated that consumers with a higher number of purchased clothing items and money spending on clothing clothing imtes pursued the brand and the trend more. Meanwhile， consumers with a less numbers of purchse and money spending were less sensitive to brand/trend. When comparing Hm-Mn and Lm-Mn groups in terms of middle number， consumers pursued brand/trend more when they spent more with the same number of purchased clothing items. Comparing Mm-Hn and Mm-Ln groups in terms of middle money spending， consumers pursued brand/trend less when they had more numbers of purchased items with the same money spending on clothing purchase.
In terms of the shopping orientation of personality， Heavy buyer groups scored the most， followed by Hm-Mn， Moderate buyer， and Mm-Ln groups. Light buyer and Mm-Hn groups showed a similar level， whereas Lm-Mn group showed a lower level of shopping orientation for personality. The major three groups （Heavy buyer； Moderate buyer； Light buyer） indicated that consumers with a higher numbers of purchased clothing items and money spending on clothing pruchase pursued personality more， whereas consumers with a less numbers of purchased clothing items and money spending were less sensitive to the personality. When comparing Hm-Mn and Lm-Mn groups in terms of middle number， consumers pursued personality more when they spent more with the same numbers of purchased clothing items. Comparing Mm-Hn and Mm-Ln groups in terms of middle money， Mm-Hn group spent less but pursued personality more， whereas Mm-Ln group spent a larger amount.
In terms of the shopping orientation of convenience， the Light buyer group scored the most， followed by Heavy buyer， Hm-Mn， Mm-Hn， and Mm-Ln. The Moderate buyer and Lm-Mn groups showed lower levels of shopping orientation for convenience. The major three groups （Heavy buyer； Moderate buyer； Light buyer） indicated that consumers with numbers of purchased clothing items and money spending on clothing pruchase pursued convenience more. When comparing Hm-Mn and Lm-Mn groups in terms of middle number， consumers pursued convenience more when they spent more with same numbers of purchased clothing items. Comparing Mm-Hn and Mm-Ln groups in terms of middle money， they showed similar level. In terms of the shopping orientation of economy， the Heavy buyer and Mm-Ln groups scored the most， followed by Moderate buyer and Light buyers as well as Hm-Mn. The Light buyer and Mm-Hn groups had similar levels， whereas the Hm-Mn and Lm-Mn groups presented a lower level of shopping orientation for economy. The three major groups （Heavy buyer； Moderate buyer； Light buyer） indicated that consumers with a higher numbers of purchased clothing items and money spending on clothing pruchase pursued economy more， whereas consumers with a less numbers of purchased clothing items and money spending on clothing pruchase were less sensitive to the economy. When comparing Hm-Mn and Lm-Mn groups in terms of middle number， consumers pursued the economy less when they spent more despite having the same numbers of purchased clothing items. Comparing Mm-Hn and Mm-Ln groups in terms of middle money， the Mm-Ln group， which bought with a less amount， pursued economy more than the Mm-Ln group， which bought more with a larger amount.
6.Differences in fashion source in terms of lower level purchasing behavior groups
One-way ANOVA analysis was conducted to define the differences in clothing sources in terms of passive consumer groups. The Moderate buyer and Light buyer groups as well as the Mm-Ln and Lm-Mn groups had smaller numbers of purchased clothing itmes and money spending than the Heavy buyer group. The analysis revealed the differences in terms of “Department store’s mail advertising，” “Fashion magazine” and “Celebrity dress” （see Table 8）.
In terms of “Department store’s mail advertising” as a fashion source when buying clothing items， the Moderate buyer group tended to depend on the source more than the Light buyer and Lm-Mn groups did. The result indicated that consumer groups with higher amount of money spending on clothing purchase with the same numbers of purchase made use of department store’s mail advertising more.
In terms of “Fashion magazines” as a fashion source， the Moderate buyer， Mm-Ln， and Lm-Mn groups depended on the source more than the Light buyer group did. This finding indicated that groups with a lower level of purchasing depended on “Fashion Magazines” when they had smaller numbers of purchased clothing items and money spending.
In terms of “Celebrity dress” as a fashion source， the Moderate buyer group made the most use of this channel， followed by the Mm-Ln， Light buyer， and Lm-Mn groups. Groups with a lower level of purchasing indicated that consumer groups with more money spending on clothing purcahse and numbers of purchase referred to “Celebrity dress” more. Groups with an extremely low level of money spending were not influenced by the source， and groups with an extremely low level of numbers of purchase used “Celebrity dress” more as they spent more. V.Conclusion and Suggestion
To understand the rapidly changing clothing market， this study segmented consumers in terms of purchasing behaviors， as well as compared and analyzed the differences in the shopping orientation of categorized groups. The results of the study were based on six months of actual purchasing data.
Consumers were segmented into nine groups based on clothing purchasing behavior （numbers of purchase clothing items； money spending on clothing purchase）. Seven groups were analyzed， but two groups were not. These groups included one with small money spending and high numbers of purchase， and the other with high money spending and small number of purchase. The differences between money spending and numbers of purchase of segmented groups to verify the consumer segmentation were identified. The Heavy buyer group had a higher level of clothing item purchase expenditure and number. By contrast， the Light buyer group had a lower level of clothing item purchase expenditure and number. These results are aligned with proceding research on differences in shopping orientation by segmenting consuers based on clothing behavior level （Lim， 2007； Jean & Sung， 2008）.
The study further compared and analyzed the differences in the clothing shopping orientation of the segmented seven groups. The differences in the fashion sources of four lower level or purchasing groups were determined. The results and implications of the major three groups （Heavy buyer； Moderate buyer； Light buyer） are discussed below：
First， Heavy buyers have the highest amount of money spending and numbers， and comprise the most active group for clothing item purchasing behavior. （1） In terms of household attribute， household income and number of household have the highest figures. Hence， motivating the group with the items for the family， such as family sets， is easier. （2） In terms of clothing shopping orientation， the group has the strongest tendency to pursue the brand/trend， personality， and economy. Hence， a continuous relationship is required to strengthen strategies for marketers and emphasize certain items to highlight such behavior of consumers.
Second， Moderate buyers are within the middle range in terms of clothing item purchasing expenditure and number. （1） In terms of the attributes of household， the group with higher level of money spending with similar numbers of purchased clothing items has more income and household members. The group with higher level of numbers of purchase with similar money spending on clothing purchase has more household members； meanwhile， the income is unrelated to the scores. （2） In terms of clothing shopping orientation， the group with higher amounts of money spending with similar numbers of purchased clothing items according to the middle number has a stronger clothing orientation in four categories. The group with lower amounts of numbers of purchase with a similar money spending according to middle money has a stronger tendency to pursue the trend/brand and economy； at the same time， the group is unaffected by the pursuit of personality and convenience. Third， Light buyers in this study comprise the passive purchasing behavior group. This group tends to spend less in terms of numbers of purchased clothing items and money spending on lcothing purchase. Moreover， Light buyers have lower amounts of income and household number， and prioritize convenience in shopping orientation. To clarify the consumer attributes of the mass market， the study analyzed the differences in fashion sources according to the passive consumer groups， namely， Moderate buyers and Light buyers， Mm-Ln group， and Lm-Mn group. In terms of fashion source， stimulating consumption is required. Opportunities can be created and increased through department store mail advertising， fashion magazines， and celebrity fashion， among other modes. The study indicated that consumers use fashion sources more when they have a higher tendency to spend on purchases. In addition， money spending on clothing purchase is more important than numbers of purchased clothing items as the Mm-Ln group considers the fashion source more than the Lm-Mn group does.
Purchasing behavior as a consumer behavior variance has not been studied with the limitation of measurement， although this factor is a major variation that is directly related to marketing revenue. From this study， purchasing behavior is a major criterion for segmenting consumers. The study revealed the differences in shopping orientation according to purchasing behavior and presented knowledge on the passive purchasing behavior group. Moreover， the Heavy buyer group is important in consumer segmentation， and marketers should continuously strengthen consumer relationships. Given that consumers in the mass market consider economy and convenience， consumption should be stimulated based on price competition and the strategy of shop approaching.
Despite the results， follow-up research is required. These findings are limited by the clothing purchasing behavior of the household so that they do not provide individual purchasing pattern. This study was also carried out only in Korea； thus， consumer segmentation could be further investigated in terms of countries， business districts， and ages of respondents.
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[Key words]Consumer segmentation；Clothing purchasing behavior；Clothing shopping orientation
中圖分类号：U95 文献标识码：A 文章编号：1009-914X（2015）37-0104-09
I.Introduction
An irony exists when clothing companies suffer during recession while consumer expenditure on clothes does not diminish. Such situation is insufficient to explain the relationship of overall expenditure with the amount of clothing consumption expenditure as various factors are applied. These factors include the diversity of clothing categories， differential price policies， and individual patterns of clothing consumption. The purpose of every company is to generate revenue by satisfying the desire of consumers. The market is an aggregate of various desires of numerous consumers， and satisfying such desires is difficult. During these circumstances， analyzing the changes in the dynamism of consumer behavior is important. Consumer segmentation is one of the important steps in establishing marketing strategy. Benefit segmentation categorizes consumers according to the factors they to be deem important （Lim et al.， 2010）. Using consumer segmentation strategy reinforces customized service by developing quality， usage， and shape of the product. Adjusting to the demand of the segmented submarket strengthens the appeal of products. In addition， recognizing the large segment of potential customers can guarantee the profitability and aid in designing marketing activities for addressing marketing problems.
In terms of consumer segmentation， the preceding research segmented consumers based on geographic and demographic variables （Smith，1956）. Segmenting the market based on consumer sentiments， such as lifestyle， characteristics， and individuality of each consumer， establishes potential target markets （Wells， 1975）. However， considering that the purchasing behavior of consumers is highly related to the consumption of products， consumer segmentation based on purchasing behavior is identified as an efficient approach （Grover & Srinivasan， 1987）. Behavioral segmentation is an efficient tool in marketing， but this approach does not essentially explain the factors that influence purchasing behavior （Rhee， 2007）. Moreover， this approach is expected to lead to executable strategies because it segments consumers according to their actual consumption behavior. Furthermore， behavioral segmentation categorizes consumers into heavy and light buyers according to purchasing number and price in terms of behavior， which indicates a huge difference in the amount spent on individual clothing consumption in diversified clothing markets （Kim et al.， 2011）. In addition， strategies for reinforcing the purchasing power of the light buyer， who represents the mass market， can be determined by analyzing the differences in shopping orientation for each type of consumer and examining the purchasing behavior characteristics of light buyers.
Based on the preceding discussion， this study segments consumers based on numbers of purchased clothing items and money spending on clothing purchase to understand the actual clothing purchasing behavior. This study deduces the implications of the policies for nurturing the clothing industry and the marketing， by investigating the differences in shopping orientation for each type in terms of heavy buyers and light buyers， and understanding the purchasing behavior characteristics of light buyers. II.Theoretical Background
1.Consumer segmentation
Executing the required marketing activities to the target market after segmenting consumers into groups is imperative as the competition intensifies. Setting the target market refers to defining the market limit based on “what the desire is， and who will be satisfied，” and determining the specific part of the market that the company will address （Lee， 1999）. Companies must focus on identifying and targeting the most favorable submarket because efficiently selling to the entire market is impossible upon product launching. Hence， setting a high value on the segmentation of consumers to identify the target market among the clothing consumers and establishing specific segmentation criteria are critically important.
The criteria from prior research on consumer segmentation differ depending on product feature and researchers. Kotler （1997） suggested the criteria in terms of geographic， demographic， psychological， and behavioral factors. Lee （1999） recommended segmentation criteria in terms of demographic and psychological factors at the consumer level， as well as product planning and distribution structure factors at the product level. Rhee （2007） explained the segmentation criteria in relation to clothing characteristics. The general features of consumers can be measured objectively based on demographic and society-economic factors that are related to clothing features. These features include clothing purchasing situation response， clothing brand royalty， and clothing purchasing ratio. Moreover， the general features of consumers can be measured subjectively by including the characteristic and lifestyle factors of clothing features， as well as the attitude and preference toward clothing.
The generally accepted classification variables or consumer segmentation aspects are geographical， demographical， psychological， and behavioral. Geographical factors include region， density of population， and city size. The needs and the desires of consumers differ according to geographical variables. The segmentation is relatively easy， which ensures an efficient approach to the geographically segmented market. Demographical factors include age， gender， family size， and income. This segmentation is extensively used in practical works because it is convenient to measure and is highly correlated to the desires， preferences， and usage of consumers. Psychological factors consist of the lifestyle and characteristics of consumers. Numerous consumers with different psychological characteristics are in the same demographical segmented market. In this case， using psychological segmentation is more effective. Furthermore， behavioral segmentation includes usage， attitude， and response to the product. This study points out the behavior that is the final step in the purchase decision step as a criterion of consumer segmentation. Behavior can be the most practical and fundamental clue to explain the actual purchasing behavior that reflects the consumption level. According to Jung （2010）， consumers have a strong inclination to keep up with the existing products and services because they have already built and maintained self-justifications for their choices. In addition， clothing purchasing behavior differentiates consumer segmentation to recognize consumers with different needs and desires， and is important in establishing a suitable marketing strategy. This study also subdivides the consumer market and specifically analyzes the segmented consumers in terms of actual purchasing behavior.
The results of the preceding research the analyzed attributes of consumers by stereotyping or classifying their purchasing behavior. One study defined clothing purchasing consumption as the purchasing amount or quantity for a certain period to purchase clothes （Kim et al.， 2008）. Roh and Chung （2004） compared shopping orientation by segmentation of consumers with frequency， place， required time， or clothing purchase to understand clothing purchasing behavior. Similarly， heavy buyers refer to the group with active and high volume or purchasing amount and quantity， and this group is further classified into heavy buyers， light buyers， and non-buyers according to purchasing frequency （Twedt， 1964）. Chiou and Pan （2009） also classified consumers into heavy and light shoppers according to the purchasing frequency to define the precedence factor of satisfaction and royalty.
Compared with demographic analysis， marketing strategies are related to psychological factors when analyzing product usage. Demographic analysis does not work well in terms of the unbalanced usage of product ratio； this analysis distinguishes heavy from light users or non-users （Goldsmith， 2000）. Cherney （2008） investigated the effect of the quantity of consumer purchase on product selection and reported that consumers selected the product with the same quantity as their desired purchasing quantity when they could not select the preferred items. Kim （1994） examined the relationship among frequency， quantity， and selection behavior or purchasing by brand preference and price sensibility， and concluded that consumers with a high score on frequency or quantity have a higher price sensibility and tend to prefer the brands of their respective countries. Goldsmith （2000） subdivided the clothing consumer market， and indicated that heavy buyer groups set the trend， tend to be more aggressive and less sensitive to price， and are knowledgeable about new clothing trends. Similar to the aforementioned cases， several studies compared and analyzed the consumer segmentation with only one factor； meanwhile， other studies examined such segmentation by subdividing consumers into complex groups using several factors. Kim et al. （2011） investigated the differences in intention to maintain the brand relation by segmenting groups after subdividing consumers into four groups with two criteria of consumption level in terms of purchasing amount and quantity of luxury clothing brand products. To segment the complex consumers， the current study segments consumer groups by performing a crossover analysis of practical numbers of purchased clothing items and money spending on clothing purchase.
2.Clothing shopping orientation
Stone （1954） related shopping orientation to lifestyle. Darden and Howell （1987） defined shopping orientation as a specific lifestyle of shopping category， which includes shopping activities， interests， and opinions.
Clothing shopping orientation denotes the aspect of patterned clothing shopping with clothing shopping-specific lifestyle， which combines personal activity， interest， and opinion on clothing shopping. As a concept， shopping orientation with behavioral and psychological profiles appears before， during， and after shopping for clothing （Kim & Rhee， 2004）.
The criteria of clothing shopping orientation suggested by various studies are related to clothing consumer behaviors， which consist of five factors， namely， economy， characteristic， ethic， indifference， and indeterminacy （Stone， 1954）. Yang et al. （2012） explained clothing shopping orientation by segmenting this behavior into pleasure， trend， plan， characteristic， brand， economy， and showing off. Park et al. （2011） used the factors related to clothing， such as pursuit of pleasure， trend， brand， economy， and convenience.
Prior research principally considered shopping orientation as a major variation to explain purchasing behavior or suggested the marketing application plan by segmenting consumers with the attribute of shopping orientation （Chu et al.， 2013； Lee & Kim， 2008； Mokhlis， 2006）. Chu et al. （2013） examined the Generation Y consumer segments’ selection attributes and willingness to pay for the environmentally friendly clothing. They identified three different consumer segments according to their green consumption styles and attitudes toward shopping and fashion， and there was a significant difference among their willingness to pay for the environmentally friendly clothing. Lee and Kim （2008） investigated the effects of consumers’ shopping orientation on purchase behavior using multi-channels. The results showed that both confident/fashion-conscious consumers and mall shopping-oriented shoppers were more satisfied with store-based retail channels for apparel purchases， whereas non-local store-oriented shoppers and catalog/internet-oriented shoppers were more satisfied with non-store-based retail channels for their apparel purchases. Mokhlis （2006） indicated that three shopping orientation factors， namely quality conscious， impulsive shopping and price conscious were related to religiosity， suggesting that religiosity should be considered as a possible determinant of shopping orientations in consumer behavior model. Moreover， several studies examined the differences in shopping orientation by segmenting consumers based on clothing behavior level. Lim （2007） analyzed clothing involvement， shopping orientation， and clothing purchasing behavior according to the types of information source usage. According to usage of information sources， female consumers were classified into four groups： active； non-personal； personal； non-active information source usage group， and fashion involvement was the most significant involvement factor to divide four groups. Jean and Sung （2008） compared the differences in clothing shopping orientation according to the experience of Internet clothing shopping.
Clothing shopping orientation is a useful variation to understand the shopping behavior and attitude of consumers， and is highly related to clothing purchasing behavior. However， research is insufficient in terms of the differences in clothing shopping orientation by purchasing behavior because most studies have focused on the differences in shopping orientation. Hence， this study defines the differences in shopping orientation by classifying consumers based on their clothing purchasing behavior.
III.Method
1.Subject of study
This study compares and analyzes the attributes of clothing shopping orientation according to consumer groups segmented by clothing purchasing behavior from a national population. Specifically， the study：
i）Classifies consumers according to clothing purchasing behavior （numbers of purchased clothing items， money spending on clothing purchase），and
ii）Compares and analyzes the differences of shopping orientation among segmented groups.
2.Data collection
This study was conducted from May 27 to July 3， 2013， and targeted Korean consumers. Research assistants visited each pre-selected household， briefly explained the survey， and handed out the questionnaires. The completed questionnaires were immediately collected after being answered. This study selected the household population aged between 20 and 64 based on the 2010 census of population householder distribution. The study collected 1，100 questionnaires by performing prorating and probability proportion sampling according to the gender and age of citizens in 16 provinces of Korea. The data of 1，100 questionnaries came from 1，100 respondents based on six months of actual purchasing behavior. Every respondent was the householder of one house. Data were analyzed through exploratory factor analysis， frequency analysis， ANOVA， and Duncan’s multiple range test via SPSS 18.0. The results of the study were based on six months of actual purchasing data.
3.Data measurement
This study used the survey method. The questionnaire consisted of three parts， namely， （1）？clothing purchasing behavior； （2） clothing shopping orientation； （3） fashion source. The selection and the development of a measurement tool for measuring each variation were revised and complemented by the qualified questions in reliability and validity of previous studies.
（1）Measurement of clothing purchasing behavior
This study asked the respondents to describe their numbers of purchased clothing items and the clothing expenditure per month in the recent six months using a free-description approach. The 14 suggested item categories are men’s formal， women’s formal， casual， sports， outdoor， underwear， kids， fur， bag， formal shoes， casual shoes， accessories， and socks/scarf， etc. The respondents were instructed to answer the purchasing number per each category of the questions. For example， “numbers of outside clothing items” consisted of men’s formal， women’s formal， casual， sports， and outdoor.
（2）Clothing shopping orientation
The measurement items of clothing shopping orientation were revised and complemented by questionnaire used in Moye and Kincade （2003）. The measure of clothing shopping orientation are multi-item scales， devided into four variables， consists of twelve questionnaire items from previous study （Park et al.， 2012； Yang et al.， 2012）. In this study， we defined clothing shopping orientation as brand/trend， personality， convenience， and economy. Each measurement item was answered using a seven-point Likert scale （1=Strongly disagree， 7= Strongly agree）.
（3）Fashion source
The construct of fashion source can be measured with three items： “My information is mainly obtained from department store’s mail advertising，” “My information is mainly obtained from fashion magazine” and “My information is mainly obtained from celebrity dress”. All items were measured on a seven-point Likert scale （1=Strongly disagree， 7= Strongly agree）.
IV. Results and Discussion
1.Sample
A questionnaire survey of household respondents， all currently living in Korea， included single-person household and multi-member household. Table 1 presents the demographical analysis of the 1，100 respondents for final data analysis. For gender， women comprised 69.5%， which was more than half. For age， 50+ years accounted for 35.6%， followed by 40s （31.4%）， 30s （23.8%）， and 20s （9.2%）. The age range indicated that respondents generally belonged to the old age group. For regional distribution， Incheon/Gyeonggi （29.0%） and Seoul （21.0%） led the group， whereas other provinces were equally distributed. For education level， respondents who had higher college education were 52.6%， high school diploma accounted for 43.5%， and lower than middle school diploma was 3.8%. For marital status， married respondents comprised 86.4%， singles were at 10%， and widows， divorced， separated accounted for 0.3%. For occupation， housewives led at 26.6%， followed by owner-operators （23.7%）， white collar （23.7%）， and blue collar workers （22.5%）. For average monthly income， 3 to 4？million KRW comprised 27.5% and 4 to 5？million KRW accounted for 24.3%. For the number of household members， most respondents belonged to a four-member （43.5%）， three-member （25.9%）， two-member （14.4%）， single-member （11.1%）， and five-member household （5.1%）. 2.Reliability and validity assessments
This study investigated reliability and validity assessments. The Cronbach’s α of this study proved the reliability of the measurement items. We also performed exploratory factor analysis to verify convergent validity and discriminative validity. Principal component analysis was conducted with Varimax rotation and an Eigen value of 1 as selection criteria. Approximate value with 0.919 of factor 4 （economy） was also 1 （see Table 2）.
Shopping orientation consisted of four factors， and the factors explaining a total variance 65.385%. Factor 1 （Brand/Trend） contained questions about the trend and brand preference when respondents purchase clothing items. Factor 2 （Personality） represented the uniqueness of preferred clothing items. Factor 3 （Convenience） reflected the comfort when respondents purchase clothing items. Factor 4 （Economy） referred to the contents of price sensibility. The results were supported by previous research. Park et al. （2012） examined intention to use and word-of-mouth for clothing social network service， and reported the correlation of clothing shopping orientation with pursuit of pleasure， trend， brand， convenience， and economy. Yang et al. （2012） investigated the influences of shopping orientation on selection criteria， attitudes， and preference of collaborated clothing products， and established the correlation of shopping orientation with pursuit of pleasure， trend， plan， personality， brand， economy， and showing off.
3.Consumer segmentation based on clothing purchasing behavior
This study presents two criteria for segmenting consumers according to clothing purchasing behavior， namely， money spending on clothing purchasing and numbers of purchase clothing items. Numbers of purchased clothing items refers to the sum of purchased items of outside clothing （men’s formal， women’s formal， casual， sports， outdoor）. Money spending on clothing purchase denotes the average amount of expenditure per month in the recent six months. In addition， 1，073 respondents were used in the final analysis by categorizing， except the case of non-shoppers in the recent six months and respondents with less than 1，000？KRW for purchasing expenditure.
The results of frequency analysis of money spending on clothing purchasing and numbers of purchase clothing items to identify the consumer segmentation criteria indicated that for the numbers of purchased clothing items， the mean value was 5.61 and the median value was 5.00. For money spending on clothing purchasing， the mean value was 104，017 KRW and the median value was 71.667 KRW （see Table 3）. This study segmented purchasing into three groups： Less than 33.3% = Low； 33.3% to 66.6% = Middle； and more than 66.6% = High purchasing group， respectively. The grouping resulted in nine groups using a 3×3 matrix， with three groups in terms of money spending on clothing purchasing and numbers of purchase clothing items （see Table 4）. Two groups （Low numbers of purchase and High money spending； High numbers of purchase and Low money spending） were excluded because the respondents were extremely few in the two groups， and they posed difficulty in comparing and analyzing them with other groups. This study primarily focused on the comparison of three groups， namely， Light buyer with Low money spending and Low numbers of purchased； Moderate buyer with Middle money spending and Middle numbers of purchased； Heavy buyer with High money spending and High numbers of purchased. The study also covered the comparison analysis of four groups， namely， Mm-Hn group （Middle money spending and High numbers of purchase） and Mm-Ln group （Middle money spending and Low numbers of purchase） with the same level of expenditure and a different level of numbers， and Lm-Mn group （Low money spending and Middle numbers of purchase） and Hm-Mn group （High money spending and Middle numbers of purchase） with the same level of numbers but a different level of expenditure. Furthermore， the results also indicated a positive correlation between money spending on clothing purchasing and numbers of purchase clothing items， that is， 0.597 correlation coefficient. This finding suggests that a higher purchasing number results in a higher purchasing expenditure.
The study segmented consumers based on money spending on clothing purchasing and numbers of purchase clothing items as previously described. Table 5 presents the results of group segmentation verification through clarifying the value of numbers of purchase outside clothing items and money spending for six months. The comparison indicated significant differences. The Heavy buyer group scored the highest level of numbers of purchase and money spending， followed by the Moderate buyer group and Light buyer group. Comparing the amount of money spending， Hm-Mn group was higher than Lm-Mn group； meanwhile， the numbers of purchase of both groups was similar. Comparing the numbers of purchased clothing items， Mn-Hn group was higher than Mn-Ln group； however， both groups exhibited a similar amount of money spending.
4.Differences in household attributes based on clothing purchasing behavior
The study compared the differences among groups in terms of average monthly income of household and number of household members to clarify the differences in the attributes of each household according to clothing purchasing behavior. The comparison was conducted through one-way ANOVA analysis （Table 6）.
For household income， Heavy buyer and Hm-Mn groups earned the most， followed by the Moderate buyer， Lm-Mn， Mn-Hn， and Mn-Ln groups. The Light buyer group scored the least. The three major groups （Heavy buyer； Moderate buyer； Light buyer） indicated that a larger amount of numbers of purchased clothing items and money spending of consumers resulted from the higher average monthly income of household. In addition， when comparing the Hm-Mn and Lm-Mn groups in terms of middle number， the larger the amount of money the consumer spent， the more income the consumer earned despite similar amounts in terms of numbers of purchased clothing items. Comparing Mm-Hn and Mm-Ln groups in terms of middle money， these groups were in a similar level of household income regardless of numbers of purchased clothing items； at the same time， they had a similar amount of money spending on clothing purchase.
For the number of household members， Heavy buyer had the highest number， followed by Hm-Mn， Mn-Hn， Moderate buyer， and Lm-Mn groups. The Light buyer and Mm-Ln groups had the least number of household members. The three major groups （Heavy buyer； Moderate buyer； Light buyer） indicated that consumers with high amounts of numbers of purchased clothing items and money spending had more household members than others. In addition， when comparing Hm-Mn and Lm-Mn groups in terms of middle number， the higher amount of money the consumer spent indicated more household members even if both groups had a similar level of numbers of purchased clothing items. When comparing Mm-Hn and Mm-Ln groups in terms of middle money， the higher numbers of purchased clothing items the consumer indicated more household members of the consumer despite both groups having similar levels of money spending on clothing purchase. 5.Differences in clothing shopping orientation based on clothing purchasing behavior
The study conducted one-way ANOVA analysis to determine the differences between shopping orientations according to purchasing behavior type. The results indicated meaningful differences in terms of brand/trend， personality， convenience， and economy （see Table 7）.
In terms of the shopping orientation of trend/brand， the Heavy buyer group scored the most， followed by Moderate buyer， Hm-Mn， and Mm-Ln groups. The Light buyer， Lm-Mn， and Mm-Hn groups showed lower levels of shopping orientation for trend/brand. The major three groups （Heavy buyer； Moderate buyer； Light buyer） indicated that consumers with a higher number of purchased clothing items and money spending on clothing clothing imtes pursued the brand and the trend more. Meanwhile， consumers with a less numbers of purchse and money spending were less sensitive to brand/trend. When comparing Hm-Mn and Lm-Mn groups in terms of middle number， consumers pursued brand/trend more when they spent more with the same number of purchased clothing items. Comparing Mm-Hn and Mm-Ln groups in terms of middle money spending， consumers pursued brand/trend less when they had more numbers of purchased items with the same money spending on clothing purchase.
In terms of the shopping orientation of personality， Heavy buyer groups scored the most， followed by Hm-Mn， Moderate buyer， and Mm-Ln groups. Light buyer and Mm-Hn groups showed a similar level， whereas Lm-Mn group showed a lower level of shopping orientation for personality. The major three groups （Heavy buyer； Moderate buyer； Light buyer） indicated that consumers with a higher numbers of purchased clothing items and money spending on clothing pruchase pursued personality more， whereas consumers with a less numbers of purchased clothing items and money spending were less sensitive to the personality. When comparing Hm-Mn and Lm-Mn groups in terms of middle number， consumers pursued personality more when they spent more with the same numbers of purchased clothing items. Comparing Mm-Hn and Mm-Ln groups in terms of middle money， Mm-Hn group spent less but pursued personality more， whereas Mm-Ln group spent a larger amount.
In terms of the shopping orientation of convenience， the Light buyer group scored the most， followed by Heavy buyer， Hm-Mn， Mm-Hn， and Mm-Ln. The Moderate buyer and Lm-Mn groups showed lower levels of shopping orientation for convenience. The major three groups （Heavy buyer； Moderate buyer； Light buyer） indicated that consumers with numbers of purchased clothing items and money spending on clothing pruchase pursued convenience more. When comparing Hm-Mn and Lm-Mn groups in terms of middle number， consumers pursued convenience more when they spent more with same numbers of purchased clothing items. Comparing Mm-Hn and Mm-Ln groups in terms of middle money， they showed similar level. In terms of the shopping orientation of economy， the Heavy buyer and Mm-Ln groups scored the most， followed by Moderate buyer and Light buyers as well as Hm-Mn. The Light buyer and Mm-Hn groups had similar levels， whereas the Hm-Mn and Lm-Mn groups presented a lower level of shopping orientation for economy. The three major groups （Heavy buyer； Moderate buyer； Light buyer） indicated that consumers with a higher numbers of purchased clothing items and money spending on clothing pruchase pursued economy more， whereas consumers with a less numbers of purchased clothing items and money spending on clothing pruchase were less sensitive to the economy. When comparing Hm-Mn and Lm-Mn groups in terms of middle number， consumers pursued the economy less when they spent more despite having the same numbers of purchased clothing items. Comparing Mm-Hn and Mm-Ln groups in terms of middle money， the Mm-Ln group， which bought with a less amount， pursued economy more than the Mm-Ln group， which bought more with a larger amount.
6.Differences in fashion source in terms of lower level purchasing behavior groups
One-way ANOVA analysis was conducted to define the differences in clothing sources in terms of passive consumer groups. The Moderate buyer and Light buyer groups as well as the Mm-Ln and Lm-Mn groups had smaller numbers of purchased clothing itmes and money spending than the Heavy buyer group. The analysis revealed the differences in terms of “Department store’s mail advertising，” “Fashion magazine” and “Celebrity dress” （see Table 8）.
In terms of “Department store’s mail advertising” as a fashion source when buying clothing items， the Moderate buyer group tended to depend on the source more than the Light buyer and Lm-Mn groups did. The result indicated that consumer groups with higher amount of money spending on clothing purchase with the same numbers of purchase made use of department store’s mail advertising more.
In terms of “Fashion magazines” as a fashion source， the Moderate buyer， Mm-Ln， and Lm-Mn groups depended on the source more than the Light buyer group did. This finding indicated that groups with a lower level of purchasing depended on “Fashion Magazines” when they had smaller numbers of purchased clothing items and money spending.
In terms of “Celebrity dress” as a fashion source， the Moderate buyer group made the most use of this channel， followed by the Mm-Ln， Light buyer， and Lm-Mn groups. Groups with a lower level of purchasing indicated that consumer groups with more money spending on clothing purcahse and numbers of purchase referred to “Celebrity dress” more. Groups with an extremely low level of money spending were not influenced by the source， and groups with an extremely low level of numbers of purchase used “Celebrity dress” more as they spent more. V.Conclusion and Suggestion
To understand the rapidly changing clothing market， this study segmented consumers in terms of purchasing behaviors， as well as compared and analyzed the differences in the shopping orientation of categorized groups. The results of the study were based on six months of actual purchasing data.
Consumers were segmented into nine groups based on clothing purchasing behavior （numbers of purchase clothing items； money spending on clothing purchase）. Seven groups were analyzed， but two groups were not. These groups included one with small money spending and high numbers of purchase， and the other with high money spending and small number of purchase. The differences between money spending and numbers of purchase of segmented groups to verify the consumer segmentation were identified. The Heavy buyer group had a higher level of clothing item purchase expenditure and number. By contrast， the Light buyer group had a lower level of clothing item purchase expenditure and number. These results are aligned with proceding research on differences in shopping orientation by segmenting consuers based on clothing behavior level （Lim， 2007； Jean & Sung， 2008）.
The study further compared and analyzed the differences in the clothing shopping orientation of the segmented seven groups. The differences in the fashion sources of four lower level or purchasing groups were determined. The results and implications of the major three groups （Heavy buyer； Moderate buyer； Light buyer） are discussed below：
First， Heavy buyers have the highest amount of money spending and numbers， and comprise the most active group for clothing item purchasing behavior. （1） In terms of household attribute， household income and number of household have the highest figures. Hence， motivating the group with the items for the family， such as family sets， is easier. （2） In terms of clothing shopping orientation， the group has the strongest tendency to pursue the brand/trend， personality， and economy. Hence， a continuous relationship is required to strengthen strategies for marketers and emphasize certain items to highlight such behavior of consumers.
Second， Moderate buyers are within the middle range in terms of clothing item purchasing expenditure and number. （1） In terms of the attributes of household， the group with higher level of money spending with similar numbers of purchased clothing items has more income and household members. The group with higher level of numbers of purchase with similar money spending on clothing purchase has more household members； meanwhile， the income is unrelated to the scores. （2） In terms of clothing shopping orientation， the group with higher amounts of money spending with similar numbers of purchased clothing items according to the middle number has a stronger clothing orientation in four categories. The group with lower amounts of numbers of purchase with a similar money spending according to middle money has a stronger tendency to pursue the trend/brand and economy； at the same time， the group is unaffected by the pursuit of personality and convenience. Third， Light buyers in this study comprise the passive purchasing behavior group. This group tends to spend less in terms of numbers of purchased clothing items and money spending on lcothing purchase. Moreover， Light buyers have lower amounts of income and household number， and prioritize convenience in shopping orientation. To clarify the consumer attributes of the mass market， the study analyzed the differences in fashion sources according to the passive consumer groups， namely， Moderate buyers and Light buyers， Mm-Ln group， and Lm-Mn group. In terms of fashion source， stimulating consumption is required. Opportunities can be created and increased through department store mail advertising， fashion magazines， and celebrity fashion， among other modes. The study indicated that consumers use fashion sources more when they have a higher tendency to spend on purchases. In addition， money spending on clothing purchase is more important than numbers of purchased clothing items as the Mm-Ln group considers the fashion source more than the Lm-Mn group does.
Purchasing behavior as a consumer behavior variance has not been studied with the limitation of measurement， although this factor is a major variation that is directly related to marketing revenue. From this study， purchasing behavior is a major criterion for segmenting consumers. The study revealed the differences in shopping orientation according to purchasing behavior and presented knowledge on the passive purchasing behavior group. Moreover， the Heavy buyer group is important in consumer segmentation， and marketers should continuously strengthen consumer relationships. Given that consumers in the mass market consider economy and convenience， consumption should be stimulated based on price competition and the strategy of shop approaching.
Despite the results， follow-up research is required. These findings are limited by the clothing purchasing behavior of the household so that they do not provide individual purchasing pattern. This study was also carried out only in Korea； thus， consumer segmentation could be further investigated in terms of countries， business districts， and ages of respondents.
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