Invisible market for online personal data: An examination
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RESEARCH PAPER
Invisible market for online personal data: An examination David Agogo 1 Received: 22 June 2020 / Accepted: 20 August 2020 # Institute of Applied Informatics at University of Leipzig 2020
Abstract Despite the widespread knowledge that corporations collect and exchange user online personal data (OPD) between themselves in a market for OPD, there have been few attempts to systematically understand the nature and structure of these markets or answer basic questions about the behavior of parties in these markets. This paper addresses these questions using records of data sharing behavior by 218 websites across eight economic sectors. Two datasets, collected 4 years apart, are analyzed using social network analysis (SNA). Findings indicate linear preferential attachment is the most likely coordinating mechanism in the OPD market. Further, this market has a much higher number of brokers (intermediary corporations that facilitate exchange between other corporations) than comparable markets. Building on these findings, implications for research and practice are presented along with future research directions. Keywords Online personal data . Social network analysis . Cookie-syncing . Personal data markets . Third-party tracking JEL classification M15 . L10
Introduction The data produced when individuals use the internet has become a critical resource that can create a significant imbalance of power in favor of today’s corporations, who appear to have a limitless capacity to collect and use this information (Cadogan 2004; Greenstein 2015). Broadly referred to as online personal data (OPD), such data consists of websites visited, actions performed on each website, time spent, apps downloaded, games played, and so on. This “exhaust of the information age” (Schneier 2015), despite being generated unintentionally and incidentally by users, has become an essential resource for marketing departments in the endless quest for new and repeat customers. OPD has even been dubbed “the new oil” (Spiekermann and Korunovska 2017; Stojanovic et al. 2016). However, for a single corporation, the value of this data is limited if they can use only first party OPD (i.e. data they collect directly from visitors to their online properties). Rather, by obtaining and processing additional
* David Agogo [email protected] 1
Information Systems and Business Analytics, College of Business, Florida International University, 11200 SW 8th Street, University Park, Miami 33199, FL, USA
OPD from other corporations’ websites and even offline datasets, corporations can unlock remarkable and powerful insights about internet users (Kohavi et al. 2002). As such, there is an economic incentive for corporations within and across economic sectors to figure out ways to generate and utilize OPD, or to seek to work with other corporations who do – directly or through intermediaries (Grover and Teng 2001). The growth in spending on programmatic advertising, a multi-billion-dollar industry, is evidence of the immense value that comes from mastering the us
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