Who’s afraid of Big Data?

[We’re pleased to welcome authors Massimiliano Nuccio and Marco Guerzoni of the University of Torino. They recently published an article in Competition & Change entitled “Big data: Hell or heaven? Digital platforms and market power in the data-driven economy,” which is currently free to read for a limited time. Below, they briefly describe the motivation and innovations of this research:]

What motivated you to pursue this research?

Following the 2018 scandal Facebook-Cambridge Analytica, a growing case has mounted over the abuse of personal data as a practice allegedly diffused among big tech companies, who are supposed to gain market control over the exploitation of big data. Influential opinion makers on the world press are also calling for an antitrust intervention arguing that incumbent firms can exploit market power to the detriment not only of competitors, but also of consumers and the society as a whole.

Has the growing availability of digital information around consumers reduced competition and consumer welfare? And again, to what extent do these oligopolies reduce the incentive to innovate so as not to cannibalize their products?

In what ways is your research innovative, and how do you think it will impact the field?

We recognise that the technology underlying digital transformation has triggered a process of concentration in several markets and a few global players (also called digital platforms) have typically risen by leveraging on network externalities and economies of scale. Using the toolbox of the economics of information and innovation we show that potential risks of big data champions do not necessarily lie in competition or welfare issues. In particular, we show that consumers tend to benefit from discriminating practices in online markets, since firms pursue these practices by lowering prices for the low-end markets, thus expanding the output, while leaving welfare unaltered for old consumers.

Moreover, the giant leap in both cloud computing and machine learning could have not been possible without the impressive investment in R&D by big tech companies, that reinvested large part of their extra profits. For instance, the software MapReduce by Google has become one of the most widespread standards for parallel computing and in 2016 Google’s capital expenditure in production equipment, facilities and data centers peaked at 10.9 billion dollars. Facebook has also set a new standard with the two billion-dollar “Open Compute Project” trying to redesign its software and its physical network infrastructure. Concerning the improvement in machine learning, DeepFace, the Facebook algorithm for face recognition is quickly approaching the human-level performance, and we are only scratching the surface of the possibility and value of Google’s semantic search algorithms.

Our findings are not an a-priori apologia of large incumbents in digital markets, but rather an attempt to argue that market concentration is not necessarily detrimental when it stimulates continuous innovation. Nonetheless, the concentration of power in a few global players should raise other concerns linked with the supranational nature of these firms, which can easily cherry-pick locations to exploit tax competition among countries or more favourable privacy legislation and the fair use of personal data.
Policy makers and scholars stressing the risk of market control by big data companies tend to overestimate the technological aspect over the human factor. We suggest that for any (digital) business model, the value of data is built around the capability for extracting knowledge, and not its mere acquisition and storage. Underlying solutions and innovative culture are still more important than data itself.

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