Hugo Jonker (Open University Netherlands), Stefan Karsch (TH Koln), Benjamin Krumnow (TH Koln), Godfried Meesters (Open University Netherlands)

Online vendors typically offer different stores to sell their items, such as desktop site, mobile site, country-specific sites, etc. Online rumours and news media reports persist that item prices between such views differ. While several academic works have investigated price differentiation, to date, no systematic method for analysing this question was put forth. We devise an approach to investigate such store-based price differentiation, based on three pillars: a framework that can perform cross-store data acquisition synchronously, a method to perform cross-store item matching, and constraints to limit client-side noise factors. We test our method in an initial case study to investigate store effects on flight pricing. We gather pricing data of 824 flights from 15 stores (incl. desktop sites, mobile apps, and mobile sites) over a 38-day period. Our experiment shows that price differences occur frequently. Moreover, even in a limited run we find strong indications of store-specific pricing for certain vendors. We conclude that (i) a larger study into store-based price differentiation is needed to better gauge this effect; (ii) future research in this general domain should take store-based differences into account in their study design.

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SynthDB: Synthesizing Database via Program Analysis for Security Testing...

An Chen (University of Georgia), Jiho Lee (University of Virginia), Basanta Chaulagain (University of Georgia), Yonghwi Kwon (University of Virginia), Kyu Hyung Lee (University of Georgia)

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How to Count Bots in Longitudinal Datasets of IP...

Leon Böck (Technische Universität Darmstadt), Dave Levin (University of Maryland), Ramakrishna Padmanabhan (CAIDA), Christian Doerr (Hasso Plattner Institute), Max Mühlhäuser (Technical University of Darmstadt)

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Jens Christian Dalgaard, Niek A. Janssen, Oksana Kulyuk, Carsten Schurmann (IT University of Copenhagen)

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