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Abstract. Consumer surveys demonstrated that privacy statements on the web are ineffective in alleviating users' privacy concerns. We propose a new user interface design approach in which the privacy practices of a website are explicated in a contextualized manner, and users' benefits in providing personal data clearly explained. To test the merits of this approach, we conducted a user experiment that compared two versions of a personalized web store: one with a traditional global disclosure and one that additionally provides contextualized explanations of privacy practices and personalization benefits. We found that subjects in the second condition were significantly more willing to share personal data with the website, rated its privacy practices and the perceived benefit resulting from data disclosure significantly higher, and also made considerably more purchases. We discuss the implications of these results and point out open research questions.

Analysis of consumer-related and consumer-generated data is a very important way to measure the success of on-line retailing. The software packages for data analysis have two major shortcomings: (1) solutions are not offered as a service reachable by standard procedures over the Internet, but as isolated standalone applications or ERP system modules; (2) privacy restrictions need to be integrated into a framework of business analytics for Web retailers. The first aspect can be addressed with standardized developer software for Web services, but the second must consider privacy legislation, privacy specifications on Web sites (P3P), and data reidentification problems. These shortcomings are addressed by a proposed formal model of these problems and an implementation of the model as a declarative specification of privacy constraints, expressed as an extension of P3P. The constraints are complemented by a logic identifying the elements in a given set of Web analytics that might lead to data reidentification and therefore violate implicit privacy constraints. A Web-based service is presented that uses these components to automatically adapt the set of available Web analytics to an on-line retailer's P3P policy. The system was tested on a large data set from a major European multichannel retailer.

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Retailers with multiple distribution channels are increasingly gaining market shares compared to Internet-only retailers. However, a lack of research explaining consumers' purchasing behavior in a multi-channel context can be identified.This paper discusses examples of multi-channel strategies and describes in detail the case of an online retailer who aims at measuring the interrelation between the sales channel Internet and a physical branch network. Based on the analysis of the retailer's transaction data and a literature review, we derive hypotheses to explain consumer purchasing behavior. A questionnaire is presented to further test the hypotheses.