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Crowd-assisted search for price discrimination in e-commerce: first results

Published:09 December 2013Publication History

ABSTRACT

After years of speculation, price discrimination in e-commerce driven by the personal information that users leave (involuntarily) online, has started attracting the attention of privacy researchers, regulators, and the press. In our previous work we demonstrated instances of products whose prices varied online depending on the location and the characteristics of prospective online buyers. In an effort to scale up our study we have turned to crowd-sourcing. Using a browser extension we have collected the prices obtained by an initial set of 340 test users as they surf the web for products of their interest. This initial dataset has permitted us to identify a set of online stores where price variation is more pronounced. We have focused on this subset, and performed a systematic crawl of their products and logged the prices obtained from different vantage points and browser configurations. By analyzing this dataset we see that there exist several retailers that return prices for the same product that vary by 10%-30% whereas there also exist isolated cases that may vary up to a multiplicative factor, e.g., x2. To the best of our efforts we could not attribute the observed price gaps to currency, shipping, or taxation differences.

References

  1. A. Hannak, P. Sapiezynski, A. Molavi Kakhki, B. Krishnamurthy, D. Lazer, A. Mislove, and C. Wilson. Measuring personalization of web search. WWW '13, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Jakub Mikians.$heriff Browser Extension. http://pdexperiment.cba.upc.edu.Google ScholarGoogle Scholar
  3. Richard B McKenzie. Why popcorn costs so much at the movies: and other pricing puzzles. Springer, 2008.Google ScholarGoogle Scholar
  4. J. Mikians, L. Gyarmati, V. Erramilli, and N. Laoutaris. Detecting price and search discrimination on the internet. In Proc. ACM HotNets-XI, pages 79--84, New York, NY, USA, 2012. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. A Odlyzko. Privacy, economics, and price discrimination on the internet. ICEC '03. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Wired. Online Prices Not Created Equal, 2000. http://www.wired.com/techbiz/media/news/2000/09/38622.Google ScholarGoogle Scholar

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      cover image ACM Conferences
      CoNEXT '13: Proceedings of the ninth ACM conference on Emerging networking experiments and technologies
      December 2013
      454 pages
      ISBN:9781450321013
      DOI:10.1145/2535372

      Copyright © 2013 ACM

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 9 December 2013

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      CoNEXT '13 Paper Acceptance Rate44of226submissions,19%Overall Acceptance Rate198of789submissions,25%

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