This exploratory research focuses on variety-seeking behavior in the e-commerce (EC) apparel market. The author introduces the causes of switching behavior through exploring different attributes such as product category, price range, and brand. The author discusses the definition of variety-seeker within relatively high price, high involvement, and less frequency category. Next, the author proposes a practical methodology to find different types of variety-seekers from transaction data and customer databases. Finally, the author identifies the characteristics of variety-seekers, including mobile device behavior and psychographics of customers. Having reviewed previous research, in this study, the author focuses on: (1) research of variety-seeking that leans toward the low price, low-involvement, and high-frequency category, (2) define and distinguish variables of variety-seeking, especially in fashion and EC websites, and (3) use of mobile channels in variety-seeking. Researchers and practitioners have studied variety-seeking behavior since the latter half of the 20th century. One of the earliest studies of variety-seeking behavior is by Tucker (1964), who proposed the exploratory behavior concept. Since then, variety-seeking behavior has been extensively researched, and it is considered the antithesis of brand loyalty. As introduced by Assael (1987), in his matrix on buying behavior types, variety-seeking occurs as a low-involvement behavior and in a relatively low-priced category (e.g., Inman, 2001). Therefore, the research on variety-seeking in a higher priced category, like fashion, is a relatively novel approach, when compared to other categories of consumer goods. Meanwhile, there are many variables in general transaction data and customer databases, such as product category and group level (large, medium, and small), brand, product attribute (color, size, gender), price, time, and store. However, much of the previous research considered brand-switching as a clue for distinguishing variety-seeking. Thus, there is little research that has considered every database variable, and defined variety-seeking in the fashion category. Recently, new research focusing on the apparel industry and EC websites has been published. For example, Ko, Kim, and Lee (2009) discussed mobile shopping for fashion products, where they proposed the concept of information-seeking. However, their research was based on questionnaires. For this review, discussing and developing a methodology to analyze variety-seeking in the EC fashion industry was necessary. Distinguishing variety-seekers in this area might be useful for retailers or manufacturers for category management or line expansion (e.g., Inman 2001). This study uses transaction data from fashion EC sites obtained from the 2016 Data Analytics Competition, which was sponsored by the Joint Association Study Group of Management Science. There were over 550,000 purchasing transactions, and approximately one million records of units purchased from April 1, 2015 to March 31, 2016. The number of customers was approximately 100,000, out of which around 3,000 answered the psychographic questionnaire. Every product was classified into 24 large groups and 226 small groups. The data covered approximately 6,500 brands across 900 shops. In this study, the author conducts three analyses. First, the author introduces the types of variety-seeking behavior into the data, which produces a distribution that resembles the shape of the Pareto distribution in terms of sales or frequency. Second, the author discusses how to distinguish variety-seekers. Brand-switching is the most important criterion of variety-seeking behavior; however, the author includes concepts such as price-seeking, category expansion, and purchase interval. Finally, the author introduces characteristics of variety-seekers with demographic and psychographic variables in order to discuss the factors that determine variety-seekers. For example, using large group switching and sales, the author distinguishes the variety-seekers (over 3,000 customers, that is, 3%). From analyzing demographic and psychographic variables, the author, then, attempts to specify the reasons for variety-seeking in the fashion category. Finally, the author confirms the differences between mobile device and PC channels. In the age of customer experience management, use of mobile device has an important role. The author demonstrates the relationship between mobile device use and variety-seeking behavior. However, this research has certain limitations. First, this exploratory research does not adopt a rigorous hypothesis testing approach. The second limitation pertains to data—if the author had web access log data and real channel purchase data, other indicators could have been calculated. However, despite these limitations, this research makes theoretical and practical contributions. First, using fashion EC website data, variety-seeking behavior could be observed in relatively high price and high-involvement categories. Second, the author proposes a simple method to distinguish variety-seekers. EC sites, in general, may have similar databases; therefore, this research has application possibilities. Third, the author explains how psychographic characteristics and mobile channel usage of variety seekers could be beneficial for further research on variety-seeking behavior.

기존의 선행연구들에서 사람들의 다양성 추구행동에 미치는 요인들에 많은 관심을 가져왔음에도 불구하고, 행운과 불운 그리고 체화된 인지의 상호작용이 다양성 추구행동에 미치는 효과에 관한 연구는 없었다. 행운과 불운의 경험은 소비자의 정보처리에 영향을 미치며, 손 씻기에 의한 체화된 인지는 행운 · 불운의 경험을 역전시키는 요인으로 두 요인이 다양성 추구행동에 미치는 효과를 이해하는 것은 소비자의 선택과 제품구매를 포함한 전반적인 소비자 행동연구에 중요한 역할을 할 것이다. 이에 본 연구는 운 경험 (행운 vs. 불운)과 손 씻기 여부 (있음 vs. 없음)의 상호작용이 다양성 추구행동에 미치는 영향을 검증하였다. 참가자들은 행운과 불운을 경험한 후, 손을 씻거나, 씻지 않았고, 떠먹는 요구르트의 맛을 얼마나 다양하게 선택하는지에 대한 과제를 수행하였다. 분석 결과, 운 점화와 손 씻기의 상호작용 효과가 발견되었다. 구체적으로, 행운 조건의 경우, 손을 씻은 참가자와 손을 씻지 않은 참가자의 다양성 추구 행동에는 차이가 없었다. 반면에 불운 조건에서는 손을 씻은 참가자가 손을 씻지 않은 참가자보다 다양성 추구 행동이 더 높게 나타났다. 본 연구의 결과는 소비자심리와 마케팅 분야에 폭넓은 이론적, 실무적 시사점을 줄 것으로 기대한다.

The purpose of this study was to understand interrelationships among switching costs, customer satisfaction, and switching intent in a family restaurant. Based on a total of 427 customers obtained from empirical research, this study reviewed the reliability and fitness of the research model and verified a total of five hypotheses using the Amos program. The hypothesized relationships in the model were tested simultaneously by using a structural equation model (SEM). The proposed model provided an adequate fit to the data, χ2=137.881 (df=50); p〈 .001; CMIN/df 2.758; GFI= .947; AGFI= .919, NFI= .965; IFI= .978; TLI= .970; CFI= .978; RMR= .047; RMSEA= .064. The results showed that switching cost (β= .123) in a family restaurant had a positive (+) influence upon customer satisfaction. Further, switching cost had a significantly negative (-) effect on switching intent (β= -.414). In addition, there were moderating effects related to customer knowledge and variety seeking orientation in terms of the causal relationships between switching costs, customer satisfaction, and switching intent. Limitations and future research directions are also discussed.