The Influence of Avatars on Online Consumer Shopping Behavior

Holzwarth, Martin; Janiszewski, Chris; Neumann, Marcus M.

doi:10.1509/jmkg.70.4.019

Cited by 319 publications

(306 citation statements)

References 55 publications

Supporting

Mentioning

257

Contrasting

Unclassified

Order By: Relevance

“…The more this feature is used, the greater the likelihood of a click-out. This implies the importance of Downloaded by [University of Nebraska, Lincoln] at 04:53 13 April 2015 30 OlbRICH and HOlsIng price within the purchasing process. Accordingly, our hypotheses regarding the direct shopping features (H5(a)-(g)) are supported for six of the seven direct shopping features.…”

Section: Results Of Logit Modelingmentioning

confidence: 99%

“…We also found that community members are more likely to make a click-out than ordinary users. This implies that community members are more profitable.KEY WORDS AND PHRASES: Clickstream data, online consumer purchasing behavior, social shopping, user-generated content, virtual community.Parallel to the increasing importance of the Internet as a shopping channel [30,77], the advent of Web 2.0 is rapidly moving the online landscape into a truly consumer-driven era [8,19,75]. Web 2.0 provides consumers with many methods of creating and sharing user-generated content (UGC) [23,58,80].…”

mentioning

confidence: 99%

“…Parallel to the increasing importance of the Internet as a shopping channel [30,77], the advent of Web 2.0 is rapidly moving the online landscape into a truly consumer-driven era [8,19,75]. Web 2.0 provides consumers with many methods of creating and sharing user-generated content (UGC) [23,58,80].…”

mentioning

confidence: 99%

See 2 more Smart Citations

Modeling Consumer Purchasing Behavior in Social Shopping Communities with Clickstream Data

Olbrich

Yang

2011

International Journal of Electronic Commerce

228

129

View full text Add to dashboard Cite

Social shopping communities (SSCs) evolve from a linkage of social networking and online shopping. Apart from direct shopping features in shopbots (e.g., search fields), SSCs additionally offer user-generated social shopping features. These include recommendation lists, ratings, styles (i.e., assortments arranged by users), tags, and user profiles. Purchases can be made by following a link to a participating online shop ("clickout"). SSCs are experiencing high growth rates in consumer popularity (e.g., Polyvore attracts more than 6 million unique visitors per month). Thus, this business model has received considerable venture capital in recent years. By analyzing clickstream data, we investigate which factors, especially social shopping features, are significant for predicting purchasing behavior within SSCs. Our logit model includes about 2.73 million visiting sessions and shows that social shopping features exert a significant impact, both positive and negative. Tags and high ratings have a positive impact on a click-out. In contrast, the more lists and styles used, the less likely the user is to make a click-out. Yet, lists and styles seem to enhance site stickiness and browsing. Moreover, the more direct shopping features that are used, the less likely the user is to conduct a click-out. Increasing transaction costs and information overload could be potential reasons. We also found that community members are more likely to make a click-out than ordinary users. This implies that community members are more profitable.KEY WORDS AND PHRASES: Clickstream data, online consumer purchasing behavior, social shopping, user-generated content, virtual community.Parallel to the increasing importance of the Internet as a shopping channel [30,77], the advent of Web 2.0 is rapidly moving the online landscape into a truly consumer-driven era [8,19,75]. Web 2.0 provides consumers with many methods of creating and sharing user-generated content (UGC) [23,58,80]. Therefore, social media such as blogs, message boards, and content-sharing platforms are growing rapidly [8,54]. In particular, consumers increasingly communicate and exchange information in social networks, such as Facebook [58,79].In the area of e-commerce, this results in a linkage of online shopping and social networking, initiating a new form of e-commerce, that of social shopping [78,80]. In general, social shopping is about connecting consumers and shopping together [75], which is also the focus of social shopping communities (SSCs), which can be defined as follows: An SSC is an online shopping service that connects consumers and lets them discover, share, recommend, rate, and purchase products [21,38]. In contrast to traditional e-commerceThe authors thank an anonymous collaborating company for providing the clickstream data used in this article. Furthermore, the authors thank SAS Institute Germany for providing SAS Enterprise Miner™ Software. Finally, the authors are especially grateful to two anonymous IJEC reviewers for their helpful and insightful comments.

show abstract

Section: Results Of Logit Modelingmentioning

confidence: 99%

mentioning

confidence: 99%

See 1 more Smart Citation

Modeling Consumer Purchasing Behavior in Social Shopping Communities with Clickstream Data

Olbrich

Yang

2011

International Journal of Electronic Commerce

228

129

View full text Add to dashboard Cite

show abstract

“…these designs have also been evaluated in various application contexts, such as computer-aided learning [31] and electronic commerce [49,55,77]. a summary of empirical evaluations of anthropomorphic interfaces is provided in appendix a.…”

mentioning

confidence: 99%

“…this design may have also undermined the validity of the results because people may have very different experiences when actually interacting with an agent to perform a real shopping task. In a recent study by Holzwarth et al [49], participants were asked to interact with and evaluate humanoid agents designed to deliver product information in an online shopping Web site. However, these agents only helped shoppers customize a product rather than recommended what to buy.…”

mentioning

confidence: 99%