Computational antitrust tools can support competition authorities in the detection of antitrust infringements. However, these tools require the availability of suitable data sets in order to produce reliable results. The present proof-of-concept study focuses on the understudied area of resale price maintenance, that is, the fixing of retail prices between manufacturers and retailers. By applying web scraping to price data for washing machines in Austria from a publicly accessibly price comparison website, we compiled a comprehensive data set for a period of nearly three months. Visualised with the help of interactive dashboards, this data was then analysed using various benchmarks in order to determine whether individual washing machine manufacturers and their retailers may be engaging in resale price maintenance. We conclude that the availability of data is a strong driver for research into and the application of computational antitrust tools. If market data were publicly accessible and provided in a more structured format, researchers and competition enforcers could develop ever more refined computational antitrust applications and screens that would, ultimately, help safeguard competition in markets.
Jan Amthauer a,1, Jürgen Fleiß a,*,2, Franziska Guggi b,c,d, Viktoria H.S.E. Robertson b,c,d
a Business Analytics and Data Science-Center, University of Graz, Austria
b Institute for Corporate and International Commercial Law, University of Graz, Austria
c Competition Law and Digitalization Group, Vienna University of Economics and Business, Austria
d The Competition Law Hub, Austria