KOREASCHOLAR

ASSESSING E-IMPULSE BUYING FOR FASHION PRODUCTS: THE ROLE OF BROWSING AND URGES TO BUY

Eun Joo Park, Eun Mi Kang, Yeo Jin Jung
  • LanguageENG
  • URLhttp://db.koreascholar.com/Article/Detail/271889
Global Marketing Conference
2014 Global Marketing Conference at Singapore (2014.07)
pp.1469-1471
글로벌지식마케팅경영학회 (Global Alliance of Marketing & Management Associations)
Abstract

Introduction E-retailers take advantage of apparel products which are viewed as a constantly changing experiential product rich that lead to various kinds of hedonic consumption, like impulse buying (Park and Kim, 2008). Apparel purchases are often affected by irrational and emotional attraction making them one of the most frequent impulsively purchased items online (Rhee, 2007). The e-shoppers are more spontaneous due to marketing stimuli which makes it easier to purchase impulsively and reduces risk aversion (Madhavaram and Laverie, 2004). In fact, shoppers are more likely to overspend when e-shopping because it does not feel like spending money (Dittmar, Long, and Meek, 2004). Apparel retailers need to pay special attention to converting web browsers to impulse purchasers—a capability that plays an important role in the growth of e-business. Despite the vast amount of data available online, few efforts have been made to identify the relationship among services attributes, browsing, urges to buy, and e-impulse buying of apparel products. This study explores a model of e-impulse buying for strategic e-business management in apparel products by understanding critical factors of e-store service attributes over the shopping websites and its impact on browsing and urges to buy for apparel in Korea. Specifically, the objectives of this study were to (a) identify underlying factors of online service attributes related to apparel products; (b) estimate structural equation model for causative relationship among service attributes, browsing, urges to buy, and e-impulse buying; and (c) examine mediating effect of browsing and urges to buy on e-impulse buying for apparel. By focusing on apparel products, this study will shed light on complex issues surrounding online service and provide opportunities for strategic development and promotion in fashion merchandising online. Also, this study could help mangers to identify successful global applications of e-marketing for apparel products. Methods A self-administered questionnaire was developed based on previous literatures. The instrument consisted of the main variables; e-service attributes of apparel stores, browsing, urge to buy, and e-impulse buying of apparel products. Participants responded to questions on a 5-point rating scale (1=very unlikely to 5=very likely). The questionnaire was administered during a regularly scheduled class in universities. Usable data were obtained from 319 students aged between 18 and 25 residing at the metropolitan areas in Korea. More than half of the respondents (65.5%) were 18 to 21 years old. Nearly 65.5 percent of the subjects were women, and more than half of the respondents (63.8%) were below the sophomore. For data analysis, exploratory factor analysis with varimax rotation was conducted to determine dimensions of perceived service attributes of the apparel online store. Cronbach's alpha established inter-item reliability between items. The structural equation model analysis was conducted by AMOS 18.0 using a correlation matrix with maximum likelihood approach. The overall fit of the model was assessed by various statistic indexes: chi-square (χ2), goodness of fit index (GFI), adjusted goodness of fit index (AGFI), and root mean squared residual (RMR). Results An exploratory factor analysis revealed three types of e-store service attributes: Ease of Use, Accuracy, and Reliability. The structural equation model, which was estimated to examine causal relationships among variables (i.e. three types of service attributes, browsing, urges to buy, and e-impulse buying), was relatively acceptable (chi-square value = 168.23, df = 157, p = .026; GFI = .95, AGFI = .93, RMR = .05). The model demonstrated that the two factors of service attributes (i.e. ease of use, accuracy of service) were significant variables to influence the browsing, which influence the urges to buy and e-impulse buying for apparel stores. E-impulse buying of apparel products was influenced by browsing and urges to buy. In addition, the urges to buy and browsing mediated the casual relationship between service attributes and e-impulse buying for apparel products. This result suggests that browsing and urges to buy perceived by shoppers were important predicting e-impulse buying of apparel products. Especially, urges to buy apparel products was the most important mediator to trigger e-impulse buying of apparels. Conclusions & Implication This study explores a structural equation model for understanding e-impulse buying in conjunction with browsing, urges to buy and service attributes of apparel store perceived by shoppers in Korea. The findings suggest that the browsing and urges to buy perceived by shoppers play important roles as mediators of the e-impulse buying for apparel stores. Especially, service attributes of apparel e-store perceived by shoppers had indirect effects on e-impulse buying through the browsing and urges to buy, implying that the consumers perceived the ease to use of e-store was the more browsing at e-store and then the more perceiving the urges to buy apparel products. However, the more browsing at apparel e-store was the less the e-impulse buying of apparel products and the more perceiving urges to buy at e-store is the more e-impulse buying of apparel products. This study provides retail managerial implications for stimulating e-shoppers' impulse buying of apparel products. They could increase shoppers' unplanned purchases by developing the service program for convenience (e.g. easy to use the structure of contents, wide ranges of products/service packages, various menu options of website) to stimulate the browsing at e-store.

Author
  • Eun Joo Park(Dong-A University)
  • Eun Mi Kang(Dong-A University)
  • Yeo Jin Jung(University of North Texas)