European Privacy Law and Global Markets for Data

Peukert, Christian; Bechtold, Stefan; Batikas, Michail; Kretschmer, Tobias

doi:10.5465/ambpp.2021.12506abstract

Cited by 4 publications

(4 citation statements)

References 27 publications

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“…Binns & Bietti (2019) show how the market of online third-party trackers significantly increased its concentration over time (with Alphabet firms being present in more than 70% of the analysed sample). The same trend is observed by Batikas et al, (2020) in the web provider market.…”

Section: Discussion and Existing Evidencesupporting

confidence: 79%

“…However, some recent empiric papers argue that soft privacy intervention could disproportionally harm smaller firms, increasing asymmetries in the market. Batikas et al, (2020) highlight this phenomenon in the market of web providers after implementing GDPR: the policy introduction lowered the market shares of all firms in favour of the market leader, Google. Garrett et al, (2022) also observed a similar result regarding web technology vendors (e.g.…”

Section: Discussion and Existing Evidencementioning

confidence: 98%

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The microeconomics of data – a survey

Pino

2022

J. Ind. Bus. Econ.

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In recent years, academia, institutions, and policymakers have been focusing their attention on the impact of data in digital markets. The economic literature that explicitly models data and their collection as strategic variables is growing, but most studies focus on distinct settings with specific data uses. This survey aims to organise this literature to extract general insights that hold across different models and assumptions. To do so, I identify three classes of models according to the way they model data collection. I find that each class is characterised by a specific impact of data on the market outcomes, regardless of the specific data use. First, when firms obtain data without strategic interactions, their use has a pro-competitive effect on the market. However, firms fail to fully internalise the data externalities, leading to data overuse and, in turn, privacy concerns. Second, when firms collect data from their interaction with consumers, data can facilitate market tipping, especially if firms are asymmetric in their starting positions. Third, when firms acquire data from data intermediaries, data are strategically sold to temper competition in the downstream market, allowing intermediaries to extract most of the surplus at the expense of firms and consumers. These general insights can facilitate future research and help policymakers to have a more general understanding of the competitive effects of data, depending on the situation at hand.

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Section: Discussion and Existing Evidencesupporting

confidence: 79%

Section: Discussion and Existing Evidencementioning

confidence: 98%

The microeconomics of data – a survey

Pino

2022

J. Ind. Bus. Econ.

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“…Campbell et al (2015) propose a model of how regulatory attempts to protect consumers' data privacy affect the structure of competition and find that the consent-based approach may disproportionately benefit firms that offer a larger scope of services, thus most adversely affecting small and new firms. This prediction has also been supported empirically in recent work on the EU GDPR (Batikas et al, 2020;Johnson et al, 2022). What has not been examined, however, is how such regulations affect the quality of the products and services offered by entrant firms.…”

Section: Relation To the Literaturementioning

confidence: 82%

Why generative AI can make creative destruction more creative but less destructive

Norbäck,

Persson

2023

Small Bus Econ

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The application of machine learning (ML) to operational data is becoming increasingly important with the rapid development of artificial intelligence (AI). We propose a model where incumbents have an initial advantage in ML technology and access to (historical) operational data. We show that the increased application of ML for operational data raises entrepreneurial barriers that make the creative destruction process less destructive (less business stealing) if entrepreneurs have only limited access to the incumbent’s data. However, this situation induces entrepreneurs to take on more risk and to be more creative. Policies making data generally available may therefore be suboptimal. A complementary policy is one that supports entrepreneurs’ access to ML, such as open source initiatives, since doing so would stimulate creative entrepreneurship.

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“…4 The academic literature has been generally more critical. A number of empirical studies report adverse effects of the GDPR on businesses such as a decrease in the amount of data collected (Schmitt et al, 2021;Congiu et al, 2022;Aridor et al, forthcoming) which adversely affect AI startups and data-based innovation (Bessen et al, 2020;Batikas et al, 2023), dampened incentives to invest in technology ventures (Jia et al, 2021), a decrease in the number of mobile apps (Janßen et al, 2022), reduced website pageviews and e-commerce revenue (Goldberg et al, 2022), and increased market concentration in websites and web technology services (Schmitt et al, 2021;Peukert et al, 2022;Johnson et al, forthcoming). 5 In addition, several 1 Following the GDPR, many countries enacted similar privacy laws or amended existing ones in line with the GDPR.…”

Section: Introductionmentioning

confidence: 99%