Dangers of ‘Facebook Login’ for Mobile Apps: Is There a Price Tag for Social Information?

Social networks offer horizontal integration for any mobile platform providing app users with a convenient single sign-on point. Nonetheless, there are growing privacy concerns regarding its use. These vulnerabilities trigger alarm among app developers who fight for their user base: While they are happy to act on users’ information collected via social networks, they are not always willing to sacrifice their adoption rate for this goal. So far, understanding of this trade-off has remained ambiguous. To fill this gap, we employ a discrete choice experiment to explore the role of Facebook Login and investigate the impact of accompanying requests for different information items / actions in the mobile app adoption process. We quantify users’ concerns regarding these items in monetary terms. Beyond hands-on insights for providers, our study contributes to the theoretical discourse on the value of privacy in the growing world of Social Media and mobile web.

Forecasting Intraday Stock Price Trends with Text Mining Techniques

In this paper, we describe NewsCATS (news categorization and trading system), a system implemented to predict stock price trends for the time immediately after the publication of press releases. NewsCATS consists mainly of three components. The first component retrieves relevant information from press releases through the application of text preprocessing techniques. The second component sorts the press releases into predefined categories. Finally, appropriate trading strategies are derived by the third component by means of the earlier categorization. The findings indicate that a categorization of press releases is able to provide additional information that can be used to forecast stock price trends, but that an adequate trading strategy is essential for the results of the categorization to be fully exploited.

Do Information, Price, or Morals Influence Ethical Consumption? A Natural Field Experiment and Customer Survey on the Purchase of Fair Trade Coffee

We address ethical consumption using a natural field experiment on the actual purchase of Fair Trade (FT) coffee in three supermarkets in Germany. Based on a quasi-experimental before-and-after design the effects of three different treatments – information, 20% price reduction, and a moral appeal – are analyzed. Sales data cover actual ethical purchase behavior and avoid problems of social desirability. But they offer only limited insights into the motivations of individual consumers. We therefore complemented the field experiment with a customer survey that allows us to contrast observed (ethical) buying behavior with self-reported FT consumption. Results from the experiment suggest that only the price reduction had the expected positive and statistically significant effect on FT consumption.