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Research Article
 

Factors Driving Consumers to Purchase Clothes through E-commerce in Social Networks



K. Napompech
 
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ABSTRACT

Shopping for clothes online and joining social networks are becoming increasingly common activities among Thai people. The objective of this research was to study purchasing behavior of customers who buy clothes through the e-commerce system of social networks. The total sample included 412 respondents. This research collected data via questionnaires. Statistics used was factor analysis. The research results showed that most of the respondents exchange data using facebook. They exchange information about clothes on the internet by reading information from other users. Respondents most frequently buy casual clothes and bags from small retailers on the Internet. The most important reason to buy clothes online is convenience; these clothes have no distributors in Thailand. Factors driving consumers to purchase clothes through e-commerce in social networks included the influence of the social network, demand-driven clothing, clothing diversity, convenience and security of ordering systems and discounts.

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  How to cite this article:

K. Napompech , 2014. Factors Driving Consumers to Purchase Clothes through E-commerce in Social Networks. Journal of Applied Sciences, 14: 1936-1943.

DOI: 10.3923/jas.2014.1936.1943

URL: https://scialert.net/abstract/?doi=jas.2014.1936.1943
 
Received: January 14, 2014; Accepted: March 08, 2014; Published: April 19, 2014



INTRODUCTION

One cannot deny that today the internet plays an important role in the daily lives of people throughout the world, including the people of Thailand. In its percentage of internet users, Thailand has come to be ranked 7th in the Association of Southeast Asian Nations (ASEAN) group, after Singapore, Malaysia, Brunei, the Philippines, Vietnam and Indonesia (TechinAsia, 2013). Of Thailand’s 67 million people, internet users account for 17.69 million (26.4%), resulting in a business world of e-commerce that has created extensive channels for business operations. Today, e-commerce has become a popular type of business operation and clothing has become a highly popular internet purchase.

As a consequence of the use of the internet in e-commerce, internet users can create content for the exchange of information, at both the individual and group levels, enabling people to befriend others and share matters of interest such that an internet society, or “social network,” is formed. The popular trend of social networking has been pronounced in Thailand through use of the internationally popular social networking website, facebook, with more than 14 million users (Socialbaker, 2013). According to Socialbaker (2013), a website for ranking and collecting statistics on social media, Bangkok is the city with the most facebook users in the world with 12.8 million accounts participation in social networks has spawned virtual communities that grow rapidly. The way in which news is exchanged through this type of word-of-mouth has facilitated rapid news propagation and viral marketing. The media have also highly affected retail trade and product image (Flavian and Guinaliu, 2005). Presently, e-commerce business operations employ social network applications to create customer networks and trade networks by opening distribution in terms of customer-to-customer (C2C) trade via web boards, blogs, discussion forums and other social network channels.

Due to the popularity among Thai people of e-commerce for clothing purchases, as well as that of the aforementioned social networks, the purchasing behavior of customers buying clothing through e-commerce in social networks and factors affecting consumer clothing purchases through e-commerce in social networks have become issues worthy of investigation. Even though there has been considerable research regarding online clothing purchases (e.g., Goldsmith and Goldsmith, 2002; Park and Stoel, 2002; Xu and Paulins, 2005; Fogel and Schneider, 2010; Jegethesan et al., 2012), few studies have focused on consumer clothing purchase through e-commerce in social networks. Therefore, this study will address this gap by examining clothing purchases through e-commerce in social networks.

Conceptual framework: Previous studies have reported many factors that affect decisions on clothing purchases, such as style and quality (O'Cass, 2000; North et al., 2003; Sondhi and Singhvi, 2006), brand (Carrigan and Attalla, 2001; Park and Stoel, 2005; Jegethesan et al., 2012) and the availability of brand diversity and clothing diversity (Kim et al., 2003). Cowart and Goldsmith (2007) discovered that brand and modernity were positively related to online clothing purchase.

Previous researchers (O'Cass, 2000; North et al., 2003; Lee and Littrell, 2005; Lester et al., 2006; Xu and Paulins, 2005; Sondhi and Singhvi, 2006) have reported that price is the crucial purchasing decision factor for clothing. Kim et al. (2003) discovered that price reasonability was the most important factor affecting online purchasing decisions. Cowart and Goldsmith (2007) found that price was negatively related to online clothing purchase. Furthermore, online shoppers are likely to think that the prices of products in online shops are often lower than in brick-and-mortar stores (Grewal et al., 2003).

Ease in ordering products, the ability to check product status at all times and punctual product delivery are vital factors for consumers in the online purchase of products (Cao et al., 2003; Jiang and Rosenbloom, 2005; Lee and Littrell, 2005; Park and Kim, 2007). In addition to fashion, buyers required availability in the sellers’ stock; this influenced both the attitudes and the intentions toward online clothing purchases (Lee and Littrell, 2005; Park and Kim, 2007).

Since customers do not know beforehand whether an item they order online will be as they desire (Garbarino and Strahilevitz, 2004; Nitse et al., 2004), online shoppers want return policies clearly revealed on the websites of online merchants (Then and Delong, 1999). Consistent with previous research, Siddiqui et al. (2003) found that a clearly stated return policy stimulates consumers to purchase apparel products online. When purchasing clothing online, consumers consider a number of factors, including how the item will look on the body (Cho and Workman, 2011). Therefore, visual apparel presentation helps consumers make purchase decisions (Park and Stoel, 2002).

Credit card online payment security is a crucial factor in online clothing purchases (Siddiqui et al., 2003; Xu and Paulins, 2005). According to previous research (Chen and He, 2003; Yoh et al., 2003), worries about online security of internet transactions has prevented online users from shopping online. Previous research supports this notion, including Kwon and Lee (2003), who discovered that customers who felt more anxiety about payment security tended to purchase fewer products via online methods. Similarly, Szymanski and Hise (2000) found that customers’ perception of the financial security level was related to satisfaction with online product purchasing.

A promotion acts as an abrupt economic enticement to buy a product (Honea and Dahl, 2005; Oliver and Shor, 2003). Promotions enable consumers to purchase and be satisfied more easily (Darke and Dahl, 2003; Oliver and Shor, 2003). Online shoppers are likely to think that prices of products in online stores are often lower than in brick-and-mortar retail stores (Grewal et al., 2003). Thus, sellers of online products should offer various sales promotions, such as premiums, discounts and free product delivery, to attract online product buyers (Oliver and Shor, 2003; Park and Lennon, 2009).

Word of Mouth (WOM) refers to communication about products and services among people who are independent of the firm providing the products and services (Jalilvand and Samiei, 2012). Increasingly, WOM happens in the public domains of online social networks (Ho and Dempsey, 2010). Chen and Xie (2008) suggested that eWOM is a new element of marketing communication that could help consumers recognize which products are appropriate in different situations. Marketers have utilized social networking sites such as facebook, linkedin and twitter in order to create awareness, interest and eventually product purchase (Coulter and Roggeveen, 2012). Blogs, message boards, chat rooms and discussion forums on social network sites such as facebook and my space provide feedback and evaluation tools for consumers (Dellarocas, 2003; Pan and Chiou, 2011). Park and Cho (2012) found that clothing customers exchanged information by using social networking and Thomas et al. (2007) discovered that sub-group communities initiated by consumers within the online community of a social network were interested in fashion. Park and Cho (2012) said that the criticisms and discussions on clothing brands, designers and retailers allowed social networks to become information centers in which word-of-mouth can carry influence. Chevalier and Mayzlin (2006) found that marketers have great incentive to engage in promotional chat and can conceal their promotions as client suggestions. Therefore, marketers should be aware of the need to generate C2C word-of-mouth by offering rewards such as free products, coupons and discounts (Ryu and Feick, 2007).

METHODS

Questionnaire design and data collection: Based on a thorough literature review, a self-administered questionnaire was developed. The questionnaire comprised 3 sections. The first included questions relating to demographic information about the participants. In the second part, respondents were asked to provide information on their clothing purchase behavior through e-commerce in social networks, such as frequency of buying, type of clothes and type of retailers. The third part which included 35 items, assessed the respondent’s opinion toward factors that drive consumers’ clothing purchases through e-commerce in a social network.

Table 1:Measuring instruments for factors driving the purchase of clothing through e-commerce in a social network
Please use the scale to rate the importance of the following factors that you think affect your purchase of clothes through e-commerce in a social network (ranging from 1: Least important to 5: Most important)

Respondents were asked to rate the importance of 35 items on a 5-point Likert scale where 5 was most important and 1 was least important (Table 1). For this research, a questionnaire was collected from respondents in Bangkok who have experience in purchasing clothes online in social networks. The total number of samples collected was 412.

Data analysis: This research applied factor analysis to determine which factors consumers considered to have an effect on consumer clothing purchase through e-commerce in a social network.

RESULTS

Demographic profile of samples: According to the study sample of 412 social network users, most users were female, accounting for 81.6; 63.6% were 26-35 years old; 70.4% had the educational level of a bachelor's degree; 75.0% were single; 38.1% had a maximum occupation level of a private company employee; and 43.7% had an income between THB $ 10,001 and THB $ 15,000 (Table 2).

Consumer behavior of purchasing clothes through e-commerce in social networks: As can be seen from Table 3, most samples exchanged news and information through facebook, the most popular social network website in Bangkok (56.3%) and secondarily through web boards (25.7%). Most participants exchanged clothing news information on the internet by reading information from other users (77.9 %) and sharing their opinions by replying to enquiries or other users' blogs (12.9%). The participants mostly purchased casual clothing from sub-sellers on the internet (33.5%) and they purchased bags, work clothes, sweaters and evening dresses which accounted for 26.0, 13.3, 8.5 and 6.5%, respectively. Participants purchased imported products without distributors in Thailand (32.1%) and some purchased branded products (23.7%).

Table 2:Demographic profile of respondents
Approximately THB $ 33 = $1US

Most participants had clothing purchase frequency of at least once a month (58.3%), followed by 1-2 times per month (35.4%) and more than 2 times per month (6.3%). The maximum expense for clothing purchases each time ranged between THB $ 301 and THB $ 500, accounting for 48.3% of the participants and secondarily, between THB $ 501 and THB $ 1,000 (34.7%). Most participants decided to purchase clothing by themselves (68.4%) but some searched for information through social networks (16.0%) and the smallest proportion consulted friends who were acquainted with social networks (3.6%). Participants decided to purchase clothing from sub-sellers on the internet mostly for convenience (44.9%) and secondarily due to the easy access channels (31.3%). Most participants purchased clothing through sub-shop websites (75.0%), some through web boards (13.9%) and the smallest proportion through blogs (5.3%) (Table 3).

Consumer-considered factors affecting consumer clothing purchase through e-commerce on social networks: Principal Component Analysis (PCA) with varimax rotation was used to group the 35 factors driving consumer purchases of clothes through e-commerce on social networks.

Table 3:Consumer behavior of purchasing clothes through e-commerce in social networks

Prior to performing the factor analysis, the suitability of the data for the analysis was evaluated. To do this, the Kaiser-Meyer-Olin (KMO) and Bartlett’s test of sphericity were used. The KMO measure of sampling adequacy is 0.747 which exceeds the threshold suggested value of 0.60 (Tabachnick and Fidell, 2001).

Table 4:Varimax rotated factor analysis
Total variance = 70.089% Kaiser-Meyer-Olin = 0.747, Bartlett’s test of sphericity x2 = 5007, p = 0.000

The Barlett’s test of sphericity was significant (x2 = 5007, p = 0.000), indicating that the between-item correlations were sufficiently large for PCA. Taken together, these statistical measures support the factorability of the data (Tabachnick and Fidell, 2001).

The desired factor loading level for a variable was set at 0.40 (Hair et al., 2006). Of the initial 35 items, 16 were excluded during the scale purification process because they either did not meet the 0.40 factor loadings cutoff or they loaded heavily on more than one factor. In the factors affecting consumer purchase of clothing through e-commerce on social networks, the factor loadings ranged from 0.486 to 0.914 (Table 4). All factors had a Cronbach’s alpha higher than 0.70 which exceeded the acceptance criteria and the 0.7 threshold recommended by Nunnally (1978) for the test of scale reliability. Factor analysis revealed the presence of five factors that explained 70.089% of the total variance. Hair et al. (2006) regarded 60% of total variance explained as the threshold. The 5 factors were labeled as follows: (1) Influence of social networks, (2) Demand-driven clothing, (3) Clothing diversity, (4) Convenient and secure system of ordering and (5) Discounts. These 5 factors explained 28.753, 17.063, 10.068, 8.568 and 5.637% of the variance, respectively (Table 4).

DISCUSSION

This study found that the most important reason that respondents shop online is convenience which confirmed findings of previous research (i.e., Shamdasani and Yeow, 1995; Bhatnagar et al., 2000; Rowley and Okelberry, 2000). The apparel they purchased most frequently was imported clothing without distributors in Thailand which is consistent with Lester et al. (2006), who found that one important reason that influences online consumer purchasing is acquiring a hard-to-find product. This is also consistent with Then and Delong (1999), who reported that consumers are likely to purchase an apparel item that was not readily available in traditional shops. The study’s findings indicated that respondents thought that the factors affecting consumer clothing purchase through e-commerce on social networks included the influence of social networks, demand-driven clothing, clothing diversity, convenient and secure system of ordering and discounts.

The finding that social networks influence consumers purchase of clothes online is consistent with Park and Cho (2012), who stated that a member of a social network online community is more inclined to use the community to alter the demand for a clothing item, to search for fashion and shopping information and to search for committed suggestions on selecting the best alternative.

The factors for demand-driven clothes include that the clothes have quality, features, condition and size that the consumer desired and that pictures of the clothes are displayed realistically on the website. This finding confirmed Park and Stoel (2002), who stated that visual presentation is important in clothing selection in online stores.

The factors related to clothing diversity, consisting of clothing modernity, availability of diversity in clothing type and brand for selection and size affected consumers’ clothing purchases through e-commerce on social networks. The study’s results support the research of Carrigan and Attalla (2001) with respect to brand and Kim et al. (2003) with respect to product diversity.

The factor of convenient and secure system of ordering consisted of convenience and speed in ordering clothes, safe payment and confirmed payment by the owner of the website. This finding is consistent with previous research (Cao et al., 2003; Jiang and Rosenbloom, 2005) with respect to ease in ordering and Park and Kim (2007), who argued that delayed shipping has a negative relationship with purchase intentions. It also supports previous research (Then and Delong, 1999; Szymanski and Hise, 2000; Kwon and Lee, 2003; Siddiqui et al., 2003; Yoh et al., 2003) regarding the importance of online payment security.

The study’s findings on discounts and their effect on consumer clothing purchases through e-commerce on social networks also supported previous research (Oliver and Shor, 2003), indicating that cheap prices increase the volume of online product purchases.

Managerial implications: The findings indicate that clothing diversity and the availability of clothing that meets consumer demands affected consumer clothing purchases through e-commerce on social networks. Therefore, online sellers of clothing should be aware of the importance of these factors and enhance the diversity of clothing offered for sale in terms of modernity, style, brand, size and diversity of types. Casual clothing and bags were the most popular clothing types for consumers’ online purchases. Online shops might consider offering or prioritizing bags and casual clothes that do not require an exact fit to the body so that consumers may perceive less risk of the product not fitting.

Since the study’s findings indicate that convenience and speed in ordering and payment security affected clothing purchases through e-commerce in social networks, online retailers of clothing should make ordering apparel online easy and provide their consumers with information about the quality of payment security and delivery time. Online sellers should guarantee in the website that if delivery time is delayed the consumer will receive compensation such as free gifts or discounts. As pictures of garments that sell online are important, online apparel retailers should post realistic pictures of clothing from different angles on their website.

In addition, based on the results, discounts have an effect on clothing purchases through e-commerce on social networks; therefore, sellers should offer discounts to their consumers to entice them to visit their site as well as select and view clothing, thereby creating more opportunities for consumer purchases.

Online apparel sellers should use social networks to collect consumers’ attitudes, comments and suggestions to improve products and service. Small online apparel sellers can use social networks such as facebook to share information, share thoughts and interact with members of social networks.

CONCLUSION

This research addresses the factors that drive consumers to purchase clothing through e-commerce in social network. The sample totaled 412. The findings suggest that the factors that consumers think affect purchasing clothing online are the influence of the social network, demand-driven clothes, clothing diversity, convenient and secure system of ordering and discounts. Therefore, online apparel sellers in social networks should enhance those qualities that consumers want to boost the success of their businesses.

ACKNOWLEDGMENT

Financial support was received from Administration and Management College, KMITL, grant number 25560212014.

REFERENCES
Bhatnagar, A., S. Misra and H.R. Rao, 2000. On risk, convenience and internet shopping behavior. Commun. ACM, 43: 98-105.
CrossRef  |  Direct Link  |  

Cao, Y., T.S. Gruca and B.R. Klemz, 2003. Internet pricing, price satisfaction and customer satisfaction. Int. J. Electron. Commerce, 8: 31-50.
Direct Link  |  

Carrigan, M. and A. Attalla, 2001. The myth of the ethical consumer: Do ethics matter in purchase behaviour? J. Consumer Market., 18: 560-577.
CrossRef  |  Direct Link  |  

Chen, R. and F. He, 2003. Examination of brand knowledge, perceived risk and consumers' intention to adopt an online retailer. Total Qual. Manage. Bus. Excell., 14: 677-693.
CrossRef  |  Direct Link  |  

Chen, Y. and J. Xie, 2008. Online consumer review: Word-of-mouth as a new element of marketing communication mix. Manage. Sci., 54: 477-491.
CrossRef  |  Direct Link  |  

Chevalier, J.A. and D. Mayzlin, 2006. The effect of word of mouth on sales: Online book reviews. J. Market. Res., 43: 345-354.
CrossRef  |  Direct Link  |  

Cho, S. and J. Workman, 2011. Gender, fashion innovativeness and opinion leadership and need for touch: Effects on multi-channel choice and touch/non-touch preference in clothing shopping. J. Fashion Market. Manage., 15: 363-382.
CrossRef  |  Direct Link  |  

Coulter, K.S. and A. Roggeveen, 2012. Like it or not: Consumer responses to word-of-mouth communication in on-line social networks. Manage. Res. Rev., 35: 878-899.
CrossRef  |  Direct Link  |  

Cowart, K.O. and R.E. Goldsmith, 2007. The influence of consumer decision-making styles on online apparel consumption by college students. Int. J. Consumer Stud., 31: 639-647.
CrossRef  |  Direct Link  |  

Darke, P.R. and D.W. Dahl, 2003. Fairness and discounts: The subjective value of a bargain. J. Consumer Psychol., 13: 328-338.
CrossRef  |  Direct Link  |  

Dellarocas, C., 2003. The digitization of word of mouth: Promise and challenges of online feedback mechanisms. Manage. Sci., 49: 1407-1424.
CrossRef  |  Direct Link  |  

Flavian, C. and M. Guinaliu, 2005. The influence of virtual communities on distribution strategies in the internet. Int. J. Retail Distrib. Manage., 33: 405-425.
CrossRef  |  Direct Link  |  

Fogel, J. and M. Schneider, 2010. Understanding designer clothing purchases over the internet. J. Fashion Market. Manage., 14: 367-396.
CrossRef  |  Direct Link  |  

Garbarino, E. and M. Strahilevitz, 2004. Gender differences in the perceived risk of buying online and the effects of receiving a site recommendation. J. Bus. Res., 57: 768-775.
CrossRef  |  Direct Link  |  

Goldsmith, R.E. and E.B. Goldsmith, 2002. Buying apparel over the internet. J. Prod. Brand Manage., 11: 89-102.
CrossRef  |  Direct Link  |  

Grewal, D., J.L. Munger, G.R. Iyer and M. Levy, 2003. The influence of internet-retailing factors on price expectations. Psychol. Market., 20: 477-493.
CrossRef  |  Direct Link  |  

Hair, J.F., W.C. Black, B.J. Babin, R.E. Anderson and R.L. Tatham, 2006. Multivariate Data Analysis. 6th Edn., Prentice-Hall Inc., New Jersey, USA., ISBN-13: 9780130329295, Pages: 899.

Ho, J.Y. and M. Dempsey, 2010. Viral marketing: Motivations to forward online content. J. Bus. Res., 63: 1000-1006.
CrossRef  |  Direct Link  |  

Honea, H. and D.W. Dahl, 2005. The promotion affect scale: Defining the affective dimensions of promotion. J. Bus. Res., 58: 543-551.
CrossRef  |  Direct Link  |  

Jalilvand, M.R. and N. Samiei, 2012. The impact of electronic word of mouth on a tourism destination choice: Testing the Theory of Planned Behavior (TPB). Internet Res., 22: 591-612.
CrossRef  |  Direct Link  |  

Jegethesan, K., J.N. Sneddon and G.N. Soutar, 2012. Young Australian consumers' preferences for fashion apparel attributes. J. Fashion Market. Manage., 16: 275-289.
CrossRef  |  Direct Link  |  

Jiang, P. and B. Rosenbloom, 2005. Customer intention to return online: Price perception, attribute-level performance and satisfaction unfolding over time. Eur. J. Market., 39: 150-174.
CrossRef  |  Direct Link  |  

Kim, Y.K., E.Y. Kim and S. Kumar, 2003. Testing the behavioral intentions model of online shopping for clothing. Clothing Textiles Res. J., 21: 32-40.
CrossRef  |  Direct Link  |  

Kwon, K. and J. Lee, 2003. Concerns about payment security of Internet purchases: A perspective on current on-line shoppers. Clothing Textile Res. J., 21: 174-184.
CrossRef  |  Direct Link  |  

Lee, S.E. and M.A. Littrell, 2005. Global e-tailing: US consumers' intention to shop for cultural products on the internet. Int. J. Retail Distrib. Manage., 33: 133-147.
CrossRef  |  Direct Link  |  

Lester, D.H., A.M. Forman and D. Loyd, 2006. Internet shopping and buying behavior of college students. Serv. Market. Q., 27: 123-138.
CrossRef  |  Direct Link  |  

Nitse, P.S., K.R. Parker, D. Krumwiede and T. Ottaway, 2004. The impact of color in the e-commerce marketing of fashions: An exploratory study. Eur. J. Market., 38: 898-915.
CrossRef  |  Direct Link  |  

North, E., R. De Vos and T. Kotze, 2003. The importance of apparel product attributes for female buyers. J. Family Ecol. Consumer Sci., 31: 41-51.
Direct Link  |  

Nunnally, J.C., 1978. Psychometric Theory. 2nd Edn., McGraw-Hill, New York, USA., ISBN-13:9780070474659, Pages: 701.

O'Cass, A., 2000. An assessment of consumers product, purchase decision, advertising and consumption involvement in fashion clothing. J. Econ. Psychol., 21: 545-576.
CrossRef  |  Direct Link  |  

Oliver, R.L. and M. Shor, 2003. Digital redemption of coupons: Satisfying and dissatisfying effects of promotion codes. J. Prod. Brand Manage., 12: 121-134.
CrossRef  |  Direct Link  |  

Pan, L.Y. and J.S. Chiou, 2011. How much can you trust online information? Cues for perceived trustworthiness of consumer-generated online information. J. Interact. Market., 25: 67-74.
CrossRef  |  Direct Link  |  

Park, H. and H. Cho, 2012. Social network online communities: Information availability on US apparel merchant Web sites. J. Consumer Market., 29: 400-411.

Park, J. and J. Kim, 2007. The importance of perceived consumption delay in internet shopping time-related information, time risk, attitude and purchase intention. Clothing Textiles Res. J., 25: 24-41.
CrossRef  |  Direct Link  |  

Park, J. and L. Stoel, 2005. Effect of brand familiarity, experience and information on online apparel purchase. Int. J. Retail Distrib. Manage., 33: 148-160.
CrossRef  |  Direct Link  |  

Park, J.H. and L. Stoel, 2002. Apparel shopping on the internet: Information availability on US apparel merchant web sites. J. Fashion Market. Manage., 6: 158-176.
CrossRef  |  Direct Link  |  

Park, M. and S.J. Lennon, 2009. Brand name and promotion in online shopping contexts. J. Fashion Market. Manage., 13: 149-160.
CrossRef  |  Direct Link  |  

Rowley, M.L. and A. Okelberry, 2000. Shopping. com: Analysis of a trend. J. Family Consumer Sci., 92: 9-10.

Ryu, G. and L. Feick, 2007. A penny for your thoughts: Referral reward programs and referral likelihood. J. Market., 71: 84-94.
CrossRef  |  Direct Link  |  

Shamdasani, P.N. and O.G. Yeow, 1995. An exploratory study of in-home shoppers in a concentrated retail market: The case of Singapore. J. Retail. Consumer Serv., 2: 15-23.
CrossRef  |  Direct Link  |  

Siddiqui, N., A. O'Malley, J.C. McColl and G. Birtwistle, 2003. Retailer and consumer perceptions of online fashion retailers: Web site design issues. J. Fashion Market. Manage., 7: 345-355.
CrossRef  |  Direct Link  |  

Socialbaker, 2013. Top 10 biggest Facebook cities. http://www.socialbakers.com/blog/647-top-10-biggest-facebook-cities.

Sondhi, N. and S.R. Singhvi, 2006. Gender influences in garment purchase: An empirical analysis. Global Bus. Rev., 7: 57-75.
CrossRef  |  Direct Link  |  

Szymanski, D.M. and R.T. Hise, 2000. E-satisfaction: An initial examination. J. Retail., 76: 309-322.
CrossRef  |  Direct Link  |  

Tabachnick, B.G. and L.S. Fidell, 2001. Using Multivariate Statistics. 4th Edn., Allyn and Bacon, Boston, MA., USA.

TechinAsia, 2013. South-East Asia has more than 190 million internet users (INFOGRAPHIC). http://www.techinasia.com/southeast-asia-internet-infographic/.

Then, N.K. and M.R. Delong, 1999. Apparel shopping on the web. J. Family Consumer Sci., 91: 65-68.

Thomas, J.B., C.O. Peters and H. Tolson, 2007. An exploratory investigation of the virtual community MySpace.com: What are consumers saying about fashion? J. Fashion Market. Manage., 11: 587-603.
CrossRef  |  Direct Link  |  

Xu, Y. and V.A. Paulins, 2005. College students' attitudes toward shopping online for apparel products: Exploring a rural versus urban campus. J. Fashion Market. Manage., 9: 420-433.
CrossRef  |  Direct Link  |  

Yoh, E., M.L. Damhorst, S. Sapp and R. Laczniak, 2003. Consumer adoption of the Internet: The case of apparel shopping. Psychol. Market., 20: 1095-1118.
CrossRef  |  Direct Link  |  

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