Electronic copy available at: http://ssrn.com/abstract=1732759 1 How is the Mobile Internet Different? Ranking Effects and Local Activities * Anindya Ghose New York University aghose@stern.nyu.edu Avi Goldfarb University of Toronto agoldfarb@rotman.utoronto.ca Sang Pil Han City University of Hong Kong sangphan@cityu.edu.hk November 2011 Abstract We explore how internet browsing behavior varies between mobile phones and personal computers. Smaller screen sizes on mobile phones increase the cost to the user of reading information. In addition, a wider range of offline locations for mobile internet usage suggests that local activities are particularly important. Using data on user behavior at a (Twitter-like) microblogging service, we exploit exogenous variation in the ranking mechanism of posts to identify the ranking effects. We show (1) Ranking effects are higher on mobile phones: Links that appear at the top of the screen are especially likely to be clicked on mobile phones and (2) The benefit of searching for geographically close matches is higher on mobile phones: Stores located in close proximity to a user are much more likely to be clicked on mobile phones. Thus, the mobile internet is somewhat less “internet-like”: search costs related to ranking effects are higher and distance matters more. Our results also suggest a possible exception: while ranking effect- related search costs are higher in a mobile phone, recency-related search costs (the cost of acquiring timely information) appear to be lower on a mobile phone than on a PC. We speculate on how these changes may affect the future direction of internet commerce. Keywords: Mobile Internet, Ranking Effects, Primacy Effects, Recency Effects, Local Commerce, Microblogging, Social Media, User Behavior, Hierarchical Bayesian. * We thank the Wharton Interactive Media Initiative for support, and Ramayya Krishnan, Vandana Ranachandran, Raghuram Iyengar and seminar participants at SICS 2011, Marketing Science Conference 2011, Second Annual Searle Center Conference on Internet Search and Innovation 2011, SCECR 2011, WISE 2010, INFORMS-CIST 2010, and the MSI-WIMI Conference on Crossplatform and Multichannel Customer Behavior for helpful comments. Support was provided by an NSF CAREER Award IIS-0643847 and a MSI-WIMI research grant. All opinions and errors are ours alone.