Analysis of Herding on the Internet - An Empirical Investigation of Online Software Download

Online shopping often requires consumers to choose among multiple products without detailed information about the quality. Herding is common in situations where consumers infer product quality from other consumers’ choices and incorporate that information into their own decision-making process. The Internet affects the herding phenomenon in two ways. On the one hand, it provides more information about other consumers’ choices, therefore making herding more feasible. On the other hand, it provides more details about product quality, thus making herding less desirable. This paper empirically examines those two effects in the context of online software downloading. We find significant herd behavior in our analysis, and, surprisingly, the provision of professional product reviews or user reviews does not significantly influence the herding phenomenon. This study contributes to the E-Commerce and the Internet marketing research by investigating online consumer behavior. This paper also contributes to the emerging literature of studying the impact of virtual communities

Exacerbating Mindless Compliance: The Danger of Justifications during Privacy Decision Making in the Context of Facebook Applications

Online companies exploit mindless compliance during users’ privacy decision making to avoid liability while not impairing users’ willingness to use their services. These manipulations can play against users since they subversively influence their decisions by nudging them to mindlessly comply with disclosure requests rather than enabling them to make deliberate choices. In this paper, we demonstrate the compliance-inducing effects of defaults and framing in the context of a Facebook application that nudges people to be automatically publicly tagged in their friends’ photos and/or to tag their friends in their own photos. By studying these effects in a Facebook application, we overcome a common criticism of privacy research, which often relies on hypothetical scenarios. Our results concur with previous findings on framing and default effects. Specifically, we found a reduction in privacy-preserving behaviors (i.e., a higher tagging rate in our case) in positively framed and accept-by-default decision scenarios. Moreover, we tested the effect that two types of justifications—information that implies what other people do (normative) or what the user ought to do (rationale based)— have on framing- and default-induced compliance. Existing work suggests that justifications may increase compliance in a positive (agree-by-) default scenario even when the justification does not relate to the decision. In this study, we expand this finding and show that even a justification that is opposite to the default action (e.g., a justification suggesting that one should not use the application) can increase mindless compliance with the default. Thus, when companies abide by policy makers’ requirements to obtain informed user consent through explaining the privacy settings, they will paradoxically induce mindless compliance and further threaten user privacy