News aggregators have emerged as an important component of digital content ecosystems, attracting traffic by hosting curated collections of links to third-party content, but also inciting conflict with content producers. Aggregators provide titles and short summaries (snippets) of articles they link to. Content producers claim that their presence deprives them of traffic that would otherwise flow to their sites. In light of this controversy, we conduct a series of field experiments whose objective is to provide insight with respect to how readers allocate their attention between a news aggregator and the original articles it links to. Our experiments are based on manipulating elements of the user interface of a Swiss mobile news aggregator. We examine how key design parameters, such as the length of the text snippet that an aggregator displays about articles, the presence of associated images, and the number of related articles on the same story, affect a reader’s propensity to visit the content producer’s site and read the full article. Our findings suggest the presence of a substitution relationship between the amount of information that aggregators offer about articles and the probability that readers will opt to read the full articles at the content producer sites. Interestingly, however, when several related article outlines compete for user attention, a longer snippet and the inclusion of an image increase the probability that an article will be chosen over its competitors. This paper was accepted by Lorin Hitt, information systems.

Broadcasted mobile advertisements are increasingly being replaced by targeted mobile advertisements through consumer profiling. However privacy is a growing concern among consumers who may eventually prevent the advertising companies from profiling them. This paper proposes an agent-based targeting algorithm that is able to guarantee full consumer privacy while achieving mobile targeted advertising. We implemented a grocery discount-discovery application for iPhone that makes use of the new approach. We show that on modern hardware like on the iPhone, it’s feasible to run a client-based and privacy-preserving targeting algorithm with minimal additional computational overhead compared to a random advertising approach. We evaluated the targeting method by conducting a large-scale field-experiment with 903 participants. Results show that the computational overhead on user devices is well tolerated, compared to the control group with randomized advertising the targeting group showed a significantly increased application usage of 18%.

Privacy has been an enduring concern associated with commercial information technology (IT) applications, in particular regarding the issue of personalization. IT-enabled personalization, while potentially making the user computing experience more gratifying, often relies heavily on the user's personal information to deliver individualized services, which raises the user's privacy concerns. We term the tension between personalization and privacy, which follows from marketers exploiting consumers' data to offer personalized product information, the personalization--privacy paradox. To better understand this paradox, we build on the theoretical lenses of uses and gratification theory and information boundary theory to conceptualize the extent to which privacy impacts the process and content gratifications derived from personalization, and how an IT solution can be designed to alleviate privacy concerns. Set in the context of personalized advertising applications for smartphones, we propose and prototype an IT solution, referred to as a personalized, privacy-safe application, that retains users' information locally on their smartphones while still providing them with personalized product messages. We validated this solution through a field experiment by benchmarking it against two more conventional applications: a base nonpersonalized application that broadcasts non-personalized product information to users, and a personalized, nonprivacy safe application that transmits user information to a central marketer's server. The results show that (compared to the non-personalized application), while personalized, privacy-safe or not increased application usage (reflecting process gratification), it was only when it was privacy-safe that users saved product messages (reflecting content gratification) more frequently. Follow-up surveys corroborated these nuanced findings and further revealed the users' psychological states, which explained our field experiment results. We found that saving advertisements for content gratification led to a perceived intrusion of information boundary that made users reluctant to do so. Overall our proposed IT solution, which delivers a personalized service but avoids transmitting users' personal information to third parties, reduces users' perceptions that their information boundaries are being intruded upon, thus mitigating the personalization--privacy paradox and increasing both process and content gratification.

Technological advancements and market competition in the smart phone business are becoming more evident. In this article, we examine the decisional deliberation of the mobile application operating system (OS), to epitomize the development of the smart phone technology and its market. Specifically, we consider the OS vendor's market strategy, the preferences of individual and corporate buyers and the inclinations of mobile application developers in general when making decisional choices for OS adoption. It is through this analysis of the various factors and their current developments that we seek to inform organizational managers and/or individual developers on choosing the appropriate smart phone OSs. In order to evaluate the smart phone OSs we present a benchmark method based on six dimensions, namely: security, individual and organization buyer choice, market growth, ease of implementation and net revenue.