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Articles

Regulating the digital economy: explaining heterogenous business preferences in data governance

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Pages 1902-1926 | Received 18 Oct 2022, Accepted 13 Feb 2023, Published online: 22 Mar 2023
 

ABSTRACT

As part of its European Data Strategy, the EU wants to create a market for non-personal data and unlock the sharing of industrial data between companies. This theory-building case study suggests that businesses’ data governance preferences are determined by their position in the data value chain and thus whether firms monetise data as data holders (producers) in the upstream or as data reusers (access seekers) in the downstream segment. While the latter favour legal rules for governing data sharing, the former prefer only contractual agreements. The data value chain theory draws on concepts of the role of data in value creation in the digital economy and on case evidence from the automotive and financial sectors, which are typical cases of digital disruption. The theory helps to better understand coalition building in business lobbying activities, the potential dynamics between private self-regulation and public policies, and the probable feedback effects of digital policies on corporate power sources.

Acknowledgements

I would like to thank the members of the Comparative Political Economy Research Group at the Cologne Center of Comparative Politics (CCCP) for their valuable comments on an earlier version of this paper and the reviewers and editors of this journal for their concise advice.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 The difference between personal and non-personal data is not easy to define in practice. In legal terms, personal data are ‘any information relating to an identified or identifiable natural person (data subject)’ (Tombal, Citation2022, p. 16). Non-personal data are data that were never personal (e.g., machine-generated) or personal data which have been anonymised (Tombal, Citation2022, pp. 16–18).

2 The following four consultation processes were selected for this analysis: Building a European Data Economy (2017), the European Strategy for Data (2020), the Digital Finance Strategy (2020), and the Data Act and amended rules on the legal protection of databases (2021).

3 ‘The International Accounting Standards (IAS) define intangible assets as “an identifiable non-monetary asset without physical substance” [IAS 38]’ (Birch et al., Citation2021, p. 3).

4 It is important to note, however, that studies on private politics have argued that voluntary actions by firms result from social or political pressure, that is from activists’ campaigns or mass public demand to constrain markets by social, consumer or environmental standards (Haufler, Citation2001; Werner, Citation2012). Given that, to date, unlike personal data regulation, non-personal data-sharing governance in the B2B context is not an issue for activists, mass public demand for state intervention is non-existent, and regulation is not about constraining the market but rather promoting it, it seems likely that firms’ preferences are more rooted in the economic dimensions of their data value chain position than in politics. However, another question is whether in the (immediate) future the EU may use company-based self-regulation as a proxy for state regulation to set standards for data sharing, as Mattli and Büthe (Citation2005) have shown for other areas of commercial activity. The conclusion returns to this aspect. We would like to thank one of the reviewers of an earlier version of this study for drawing our attention to this point.

5 Application Programming Interfaces are software programs that serve as an important control mechanism in governing data flows and data access (OECD, Citation2020, p. 16).

6 These dynamics of data value chains play out in other sectors as well, including the health industry, agriculture, chemical sector, aviation and aerospace, transport, retail, the energy sector and telecommunications (Deloitte, Citation2018b, Annex 2).

8 In public debate, the term Big Tech encompasses the five large US tech companies Meta, Amazon, Apple, Microsoft and Alphabet. In order to include tech companies which hold industrial data (and not only personal data) and to not exclude European firms, this article defines Big Tech more broadly, adding major cloud computing firms, telecommunication and internet service providers, software companies and chip producers (and their lobbying associations).

9 See their answer to the question ‘data sharing purely by contract’, .

10 For this and the following statements, see how they explained their answers to the question ‘data sharing purely by contract’, .

12 SMEs = small and medium-sized enterprises.

13 See the representatives’ answers to the open question ‘Question 26’; Consultation on a new Digital Finance Strategy for Europe/Fintech Action Plan; https://ec.europa.eu/info/consultations/finance-2020-digital-finance-strategy_en.

14 See EBF’s answer to the open question: ‘Have you had difficulties in using data from other companies?’ ‘What was the nature of such difficulties?’; consultation on the European Strategy for Data; https://ec.europa.eu/digital-single-market/en/news/summary-report-public-consultation-european-strategy-data.

15 For this and the following statements, see the representatives’ answers to the open question ‘Question 26’; consultation on a new Digital Finance Strategy for Europe/Fintech Action Plan; https://ec.europa.eu/info/consultations/finance-2020-digital-finance-strategy_en.

16 Although Facebook, CCIA, CISPE and AmCham were neutral.

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