• Title/Summary/Keyword: Showrooming

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An Empirical Study on Influencing Factors of Switching Intention from Online Shopping to Webrooming (온라인 쇼핑에서 웹루밍으로의 쇼핑전환 의도에 영향을 미치는 요인에 대한 연구)

  • Choi, Hyun-Seung;Yang, Sung-Byung
    • Journal of Intelligence and Information Systems
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    • v.22 no.1
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    • pp.19-41
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    • 2016
  • Recently, the proliferation of mobile devices such as smartphones and tablet personal computers and the development of information communication technologies (ICT) have led to a big trend of a shift from single-channel shopping to multi-channel shopping. With the emergence of a "smart" group of consumers who want to shop in more reasonable and convenient ways, the boundaries apparently dividing online and offline shopping have collapsed and blurred more than ever before. Thus, there is now fierce competition between online and offline channels. Ever since the emergence of online shopping, a major type of multi-channel shopping has been "showrooming," where consumers visit offline stores to examine products before buying them online. However, because of the growing use of smart devices and the counterattack of offline retailers represented by omni-channel marketing strategies, one of the latest huge trends of shopping is "webrooming," where consumers visit online stores to examine products before buying them offline. This has become a threat to online retailers. In this situation, although it is very important to examine the influencing factors for switching from online shopping to webrooming, most prior studies have mainly focused on a single- or multi-channel shopping pattern. Therefore, this study thoroughly investigated the influencing factors on customers switching from online shopping to webrooming in terms of both the "search" and "purchase" processes through the application of a push-pull-mooring (PPM) framework. In order to test the research model, 280 individual samples were gathered from undergraduate and graduate students who had actual experience with webrooming. The results of the structural equation model (SEM) test revealed that the "pull" effect is strongest on the webrooming intention rather than the "push" or "mooring" effects. This proves a significant relationship between "attractiveness of webrooming" and "webrooming intention." In addition, the results showed that both the "perceived risk of online search" and "perceived risk of online purchase" significantly affect "distrust of online shopping." Similarly, both "perceived benefit of multi-channel search" and "perceived benefit of offline purchase" were found to have significant effects on "attractiveness of webrooming" were also found. Furthermore, the results indicated that "online purchase habit" is the only influencing factor that leads to "online shopping lock-in." The theoretical implications of the study are as follows. First, by examining the multi-channel shopping phenomenon from the perspective of "shopping switching" from online shopping to webrooming, this study complements the limits of the "channel switching" perspective, represented by multi-channel freeriding studies that merely focused on customers' channel switching behaviors from one to another. While extant studies with a channel switching perspective have focused on only one type of multi-channel shopping, where consumers just move from one particular channel to different channels, a study with a shopping switching perspective has the advantage of comprehensively investigating how consumers choose and navigate among diverse types of single- or multi-channel shopping alternatives. In this study, only limited shopping switching behavior from online shopping to webrooming was examined; however, the results should explain various phenomena in a more comprehensive manner from the perspective of shopping switching. Second, this study extends the scope of application of the push-pull-mooring framework, which is quite commonly used in marketing research to explain consumers' product switching behaviors. Through the application of this framework, it is hoped that more diverse shopping switching behaviors can be examined in future research. This study can serve a stepping stone for future studies. One of the most important practical implications of the study is that it may help single- and multi-channel retailers develop more specific customer strategies by revealing the influencing factors of webrooming intention from online shopping. For example, online single-channel retailers can ease the distrust of online shopping to prevent consumers from churning by reducing the perceived risk in terms of online search and purchase. On the other hand, offline retailers can develop specific strategies to increase the attractiveness of webrooming by letting customers perceive the benefits of multi-channel search or offline purchase. Although this study focused only on customers switching from online shopping to webrooming, the results can be expanded to various types of shopping switching behaviors embedded in single- and multi-channel shopping environments, such as showrooming and mobile shopping.

A Design and Implementation of Needs Analysis System in Internet Shopping Mall (인터넷 쇼핑몰 니즈 분석 시스템의 설계 및 구현)

  • Park, Sung-hoon;Kim, Jindeog
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.19 no.9
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    • pp.2073-2080
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    • 2015
  • Even though users choose goods they want to buy in on-line shopping malls, real purchase is often performed in off-line shopping malls. It is called reverse showrooming. It means that users' analysis of goods based on images and description of internet shopping malls has limitation. Thus, large-scale online shopping malls provide a customized shopping information. However, in that case, the provided information is a simple list of goods users bought or retrieved. Thus, a system to analyze various needs of users and apply the result into on-line shopping mall is necessary. In this paper, an analysis system is proposed. The system contains a module to analyze user defined preference and a module to analyze users' reviews. The former designates two goods and collects preferences of individual users. the latter analyzes reviews about purchased goods based on database dictionary stored in advance for analyzing reviews. The system implemented shows that it is possible to recommend some goods that meet each users's needs