Broad collection of consumer data by Big Tech: exclusionary or exploitative abuse?

ABSTRACT

The ability to gather and process large amounts of personal data is primarily held by a small group of companies. Some regulators, scholars, and practitioners have expressed concerns that major advertising-based platforms such as Google and Facebook may abuse their dominant position in the data market by requiring users to agree to the intensive collection of their data as a condition to the free access and use of those platforms’ core services. This raises the question of whether such broad collection of consumer data should be examined by European competition authorities as a foreclosure aiming at excluding current and potential competitors from the market of consumer data or as an excessive collection of personal data having the effect of lowering user’s privacy. This paper seeks to discuss this matter by examining the recent ruling in Meta by the European Court of Justice.

KEYWORDS:

• Big Data
• Big Tech
• advertiser-based platforms
• exclusionary abuse
• exploitative abuse
• tying
• excessive pricing
• essential facility
• personal data protection
• GDPR

Disclosure statement

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

Notes

1 OECD, ‘Big Data: Bringing Competition Policy to the Digital Era’ (2016) 14 DAF/COMP 22 <https://www.oecd.org/competition/big-data-bringing-competition-policy-to-the-digital-era.htm> accessed 1 January 2024.

2 Claudia Biancotti and Paolo Ciocca, ‘Opening Internet Monopolies to Competition with Data sharing Mandates’, Policy Brief 19-3, Peterson Institute for International Economics, April 2019 <https://www.piie.com/publications/policy-briefs/opening-internet-monopolies-competition-data-sharing-mandates> accessed 23 January 2024.

3 A consumer is defined in EU law as ‘any natural person who […] is acting for the purposes which are outside his trade, business or professions’ according to article 2, paragraph 1, b) of Directive 93/13/EEC of 5 April 1993 on unfair practices in consumer contracts, OJ 1993, 1.95, 29–34 <https://eu-lex.europa.eu/legal.content/EN/TXT/PDF/?uri=CELEX:319931.0013&qid-1543829645563&from> accessed 13 January 2024.

4 According to Andrea De Mauro and others, ‘Big Data is the Information Asset Characterized by Such a High Volume, Velocity and Variety to Require Specific Technology and Analytical Methods for Its Transformation into Value’. See Andrea De Mauro and others, ‘A Formal Definition of Big Data Based on Its Essential Features’ (2016) 65(3) Libr Rev 122–35, 129 <https://app.dimensions.ai/details/publication/pub.1018388078> accessed 16 January 2024.

5 Data analytics can be defined as the ability to design algorithms that can access and analyze vast amount of information. See Ariel Ezrachi and Maurice E Stucke, Virtual Competition: The Promise and Perils of the Algorithm-Driven Economy (Harvard University Press 2016) 15.

6 Steven Emily, ‘What is Data Analytics? A Complete Guide for Beginners’, CareerFoundry Blog <https://careerfoundry.com/> accessed 2 January 2024.

7 Definition of artificial intelligence taken from the Merriam-Webster dictionary <https://www.merriam-webster.com/dictionary/artificial%20intelligence> accessed 19 January 2024.

8 Kinza Yasar, ‘Third-Party Cookie’, TechTarget <https://www.yechtarget.com/whatis/definition/third-party-cookies> accessed 19 January 2024; Victoria HSE Robertson, ‘Excessive Data Collection: Privacy Considerations and Abuse of Dominance in the Era of Big Data’ (2020) 57 Common Market Law Review 161–90, 171.

9 Reuben Binns and Elettra Bietti, ‘Dissolving Privacy, One Merger at a Time: Competition, Data, and Third Party Tracking’ (2020) 36 Computer Law & Security Review 3 <https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3269473> accessed 8 January 2024.

10 Efficiencies of scale of large digital platforms can be defined as their ability, through the online searches of the first-party services’ clients, to collect large-scale datasets on which they can “train” at a low cost their algorithms to improve their performance and efficiency. See OECD, ‘Big Data: Bringing Competition Policy to the Digital Era’ (2016) 14 DAF/COMP, 12 October 2016, 11 <https://www.oecd.org/competition/big-data-bringing-competition-policy-to-the-digital-era.htm> accessed 15 January 2024.

11 Binns and Bietti (n 11) 15

12 European Data Protection Supervisor, ‘Towards a New Digital Ethics: Data, Dignity and Technology’, Opinion 4/2015, 11 September 2015 <https://edps.europa.eu/sites/edp/files/publication/15-09-11_data_ethics_en.pdf> accessed 5 January 2024.

13 Sebastian Schelter and Jerome Kunegis, ‘Tracking the Trackers: A Large-Scale Analysis of Embedded Web Trackers’ [2016] Proceedings of the ICWSM 679, 680 <https://www.google.com/search?q=Sebastian±Schelter±and±Jerome±Kunegis%2C±%E2%80%98Tracking±the±Trackers±%3A±A±Large-Scale±Analysis±of±Embedded±Web±Trackers%E2%80%99±(2016)±Proceedings±of±the±ICWSM&oq=Sebastian±Schelter±and±Jerome±Kunegis%2C±%E2%80%98Tracking±the±Trackers±%3A±A±Large-Scale±Analysis±of±Embedded±Web±Trackers%E2%80%99±(2016)±Proceedings±of±the±ICWSM&aqs=chrome..69i57.1851j0j7&sourceid=chrome&ie=UTF-8> accessed 7 January 2024.

14 Nils-Peter Schepp and Achim Wambach, ‘On Big Data and Its Relevance for Market Power Assessment’ (2016) 7(2) Journal of European Competition Law & Practice 120–24.

15 A small number of dominate third-party tracking across both the mobile and web. For app-based tracker, Alphabet/Google is the most prevalent tracker, followed by Microsoft (including LinkedIn), Facebook and X (formerly Twitter). The picture is only slightly different for web-based trackers, where Alphabet/Google is the most successful tracker, followed by Facebook and X. See Victoria HSE Robertson, ‘Excessive Data Collection: Privacy Considerations and Abuse of Dominance in the Era of Big Data’ (2020) 57 Common Market Law Review 161–90, 171; Nicholas Economides and Ioannis Lianos, ‘Restrictions on Privacy and Exploitation in the Digital Economy: A Market Failure Perspective’ [2021] Journal of Competition Law & Economics 3.

16 Big Tech are companies which through their use of Big Data and algorithms increasingly act as gateway between business users and end users and enjoy an entrenched and durable position. These businesses have proven highly profitable, allowing some attention platforms and matching algorithms to be among the top 10 most valuable companies in the world. For information on the ranking of these companies, see ‘Largest Companies by Market Cap’ <https://companiesmarketcap.com/> accessed 26 January 2024.

17 Market power is the ability of a firm or a group of firms to make decisions independently of its competitors, customers and final consumers, as set out in the European Commission’s Guidelines. See European Commission, Guidance on the Commission’s enforcement priorities in applying Article 82 of the EC Treaty to abusive exclusionary conducts by dominant undertakings, OJ 2009, C45/7 <https://eur-lexeuropa.eu/legal-content/EN/ALL/?uri=CELEX%3A52009XC0224%2801%29> accessed 17 January 2024

18 At microeconomic level, the collection and control over a very substantial amount of data enable businesses to improve the quality of their products and services by better understanding individual consumer needs, to set optimal prices that effectively respond to market changes and to optimize inventory levels. At the macro level, they allow a better allocation of resources which may provide lower prices, more competition, higher quality and a wider range of choice for consumers.

19 Ezrachi and Stucke (n 7) 15–21.

20 Robertson (n 17) 161–90; Economides and Lianos (n 17) 3.

21 OECD, ‘Abuse of Dominance in Digital Markets’ (2020) 14. <www.oecd.org/daf/competition/abuse-of-dominance-in-digital-markets-2020.pdf> accessed 21 January 2024.

22 ibid.

23 Sean Silverthorn, ‘New Research Explore Multi-Sided Market’ Harvard Business School (12 March 2006) <https://hbswk.hbs.edu/item/new-research-explores-multi-sided-markets> accessed 21 January 2024.

24 Jacques Cremer and others, ‘Competition Policy for the Digital Era’ [2019] Final Report for the European Commission, Directorate-General for Competition 21 <https://ec.europa.eu/competition/publications/reports/kd0419345enn.pdf> accessed 1 January 2024.

25 OECD, ‘Rethinking Antitrust Tools for Multi-Sided Platforms’ [2018] <https://www.oecd.org/daf/competition/Rethinking-antitrust-tools-for-multi-sided-platforms-2018.pdf> accessed 16 January 2024.

26 Jean Charles Rochet and Jean Tirole, ‘Platform Competition in Two-Sided Markets’ (2003) 1(4) Journal of European Economic Association 990–1029.

27 OECD (n 2) 15.

28 See European Commission, ‘Discussion Paper on the Application of Article 82 of the Treaty of Exclusionary Abuses’ [2005] DG Competition 7 <www.ec.europa.eu/competition/antitrust/art82/discpaper2005.pdf> accessed 11 January 2024.

29 ibid.

30 Maurice E Stucke and Allen P Grunes, Big Data and Competition Policy (Oxford University Press 2016) 107. See also Michal S Gal and Daniel L Rubinfeld, ‘The Hidden Costs of Free Goods: Implications for Antitrust Enforcement’ (2016) 80 Antitrust Law Journal 521–62.

31 David S Evans, ‘Attention Platforms, the Value of Content and Public Policy’ (2019) 54 Review of Industrial Organization 775, 792; Gianclaudio Malgieri and Bart Custers, ‘Pricing Privacy: The Right to Know the Value of Your Personal Data’ (2018) 34 Computer Law & Security Review 289; John M Newman, ‘The Myth of Free’ (2018) 86 George Washington Law Review 513, 551–55; Gal and Rubinfeld (n 30) 522, 528; Chris Jay Hoofnagle and Jan Whittington, ‘Free Accounting for the Costs of the Internet’s Most Popular Price’ (2014) 61 UCLA Law Review 654.

32 Tamara Dinev and Paul Hart, ‘An Extended Privacy Calculus Model for E-Commerce Transactions’ (2003) 17(1) Information System Research 61 62.

33 ibid 62–68; II-Horn Hann and others, ‘Overcoming Online Information Privacy Concerns: An Information-Processing Theory Approach’ (2007) 24(2) Journal of Management Information Systems 13, 17; II-Horn Hann and others, ‘Online Information Privacy: Measuring the Cost-Benefit Trade-Off’ (International Conference of Information Systems Proceedings 2–3, Barcelona, 15–18 December 2002) <https://aisel.aisnet.org/icis2002/> accessed 11 January 2024; Joseph E Phelps, Giles D’Souza and Glen J Nowak, ‘Antecedents and Consequences of Consumer Privacy Concerns: An Empirical Investigation’ (2001) 15(4) Journal of Interactive Marketing 2, 4.

34 Dinev and Hart (n 32) 62.

35 European Data Protection Supervisor, ‘Privacy and Competitiveness in the Age of Big Data: The Interplay between Data Protection, Competition Law and Consumer Protection in the Digital Economy: Preliminary Opinion of the European Data Protection Supervisor’ (2014). Robert H Lande, ‘The Microsoft-Yahoo Merger: Yes, Privacy Is an Antitrust Concern’ (2008) University of Baltimore School of Law Legal Studies Research Paper No 2008-06 <https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1121934> accessed 7 January 2024.

36 Maurice E Stucke and Allen P Grunes, ‘No Mistake About It: The Important Role of Antitrust in the Era of Big Data’ The University of Tennessee Legal Studies Research Paper # 269 May 2015, The Antitrust Source (April 2015) <https://ssrn.com/abstract=2600051> accessed 15 January 2024.

37 Robertson (n 17) 170.

38 Directive (EU) 2018/1972 of 11 Dec. 2018 establishing the European Electronic Communications Code [2018] para 16.

39 Robertson (n 17) 170.

40 Directive (EU) 2018/1972 of 11 Dec. 2018 establishing the European Electronic Communications Code [2018] para 16.

41 Zhengmin Li, ‘The Implication of Data Concentration on EU Merger Control on EU Merger Control’ (Master Thesis Lund University faculty of law, 2020) 31 <file:///C:/Users/installuser/Documents/Sam's%20documents/%D0%9D%D0%98%D0%A1%D0%98%D0%9F%D0%9F/Merger%20control%20and%20Big%20Data/Second%20wave%20of%20articles/Li%20Implications%20of%20data%20concentrations%20in%20EU%20merger%20control.pdf> accessed 18 January 2024.

42 Maria T Patakyova, ‘Competition Law in the Digital Era-How to define the relevant market’ (the 4th Conference on Economics and Management Proceedings, Belgrade, 3 September 2020) 175 <https://doi.org/10.31410/EMAN.2020g.171> accessed 1 January 2024.

43 Robert H Lande, ‘The Microsoft Yahoo Merger: Yes Privacy is an Antitrust Concern’ [2008] University of Baltimore School of Law Legal Studies Research Paper No 2008-06 1 <https://papers.ssrn.com/solpapers.cfm?abstract_id=1121934> accessed 12 January 2024; Natasha Just, ‘Governing Online Platforms: Competition Policy in Times of Platformization’ (2018) 42(5) Telecommunication Policy 386, 388.

44 Ariel Ezrachi and Victoria HSE Robertson, ‘Competition, Market Power and Third-Party Tracking’ (2019) 42 World Competition 5–19, 13.

45 OECD (n 2) 16.

46 OECD (n 2) 5.

47 Commission, Horizontal Merger Guidelines under the Council Regulation on the control of concentrations between undertakings (the ‘EUMR’), OJ C 31/5, 5.2.2004 (the ‘Horizontal Guidelines’) para 8; See also Commission, Guidelines on the Assessment of Non-Horizontal Mergers Under the Council Regulation on the Control of Concentrations Between Undertakings [2008] OJ C 265/07, 10.

48 European Commission, ‘Mergers: Commission Approves Acquisition of LinkedIn by Microsoft, Subject to Conditions’ IP/16/4284 (6 Dec.2016) Also referring to reduce privacy protection as a degradation in quality, see Stucke, ‘Should We be Concerned About Data-Polies?’ (2018) 2 Georgetown Law Technology Review 287.

49 Economides and Lianos (n 17) 38.

50 See Pasquale, ‘Privacy, Antitrust, and Power’ (2013) 20 George Mason Law Review 1009, 1010; Swire, ‘Protecting Consumers: Privacy Matters in Antitrust Analysis’ (19 Oct. 2007) <www.americanprogress.org/issues/economy/news/2007/10/19/3564/protecting-consumers-privacy-matters-in-antitrust-analysis/> 24 January 2024; Thanner, ‘Rethinking Competition Law for the Digital Economy’ (2018) 11 Austrian Competition Journal 79, 81; Giuseppe Colangelo and Mariateresa Maggiolino, ‘Data Accumulation and the Privacy-Antitrust Interface: Insights from the Facebook Case for the EU and the U.S’ TTLF Working Paper (No31/2018), section 4.2.

51 See, for example, Maria C Wasastjerna, ‘The Implication of Big Data and Privacy on Competition Analysis in Merger Control and the Controversial-Data Protection Interface’ (2019) 30(3) European Business Law Review 337–66, 354; Robertson (n 16) 172–83; Colangelo and Maggiolo (n 48) 369–71.

52 Stuart Thomas, ‘Too Little Too Late? An Exploration and Analysis of the Inadequacies of Antitrust Law When Regulating GAFAM Data-driven Mergers and the Potential Legal Remedies Available in the Age of Big Data’ (2021) 17 European Competition Journal 407–36.

53 Marco Botta and Klaus Wiedeman, ‘The Interaction of EU Competition, Consumer and Data Protection Law in the Digital Economy: The Regulatory Dilemna in the Facebook Odyssey (2019) 64(3) Antitrust Bulletin 428–46, 424.

54 Economides and Lianos (n 17) 24.

55 Economides and Lianos (n 17) 7.

56 Stuart (n 51) 41.

57 Yongqiang Sun and others, ‘Understanding Users’ Switching Behavior of Mobile Instant Messaging Applications: An Empirical Study from the Perspective of Push-Pull-Mooring Framework’ (2017) 75 Computers in Human Behaviour 727.

58 On switching costs, see e.g. Aaron S Edlin and Robert G Harris, ‘The Role of Switching Costs in Antitrust Analysis: A Comparison of Microsoft and Google’ (2013) 15 Yale Journal of Law and Technology 169–213.

59 OECD, ‘Non-price Effects of Mergers: Background note by the Secretariat’ [2018] DAF/COMP/ 2 <https://one.oecd.org/document/DAF/COMP(2018)2/en/pdf> accessed 4 January 2024.

60 OECD, ‘Geographic Market Definition across National Borders: Background note by the Secretariat’ [2016] DAF/COMP/WP3 <https://one.oecd.org/document/DAF/COMP/WP3(2016)5/en/pdf> accessed 5 January 2024.

61 OECD, ‘Practical Approaches to Assessing Digital Platform Markets for Competition Law Enforcement: Background Note by the Secretariat for the Latin American and Caribbean Competition Forum’ (2019) 2 DAF/COMP/LACF 21 <https://one.oecd.org/document/DAF/COMP/LACF(2019)3/en/pdf> accessed 22 January 2024.

62 The Bundeskartellamt (German Competition Authority), ‘The Market Power of Platforms and Networks, Executive Summary’, June 2016, 67 <https://www.bundeskartellamt.de/SharedDocs/Publikation/EN/Berichte/Think-Tank-Breicht-Zusammenfassung.pdf?_blob=publicationFile&v=4>.

63 OECD, ‘Big Data: Bringing Competition Policy to the Digital Era’ (n 1) para 48.

64 Anwar Aridi and Urška Petrovĉiĉ, ‘Big Tech, Small Tech and the Data Economy: What Role for EU Competition Law?’ [2019] The World Bank Working Papers 19 <https://openknowledge.worldbank.org/handle/10986/33124> accessed 2 July 2021.

65 ibid.

66 Data portability is the ability of users to transfer elsewhere the data that a platform has collected about them. See Cremer, ‘Competition Policy for the Digital Era’ (n 25) 6.

67 Multi-homing is the method of configuring one computer, called the host, with more than one network connection and IP address. The multi-homed method provides enhanced and reliable Internet connectivity without compromising efficient performance. See ‘What is Multi-Homing?’ (F5 Glossary, 2021) <https://www.f5.com/services/resources/glossary/multi-homing> accessed 28 June 2021.

68 Cremer, ‘Competition Policy for the Digital Era’ (n 26) 57.

69 Sunk costs are costs that cannot be recovered if a firm exits a market, which can dissuade entry. See OECD, ‘Abuse of Dominance in Digital Markets’ (n 23) 17.

70 Google Search (Shopping) (Case AT.39740) Commission Decision C (2017) 4444 [2017] <https://ec.europa.eu/competition/antitrust/cases/dec_docs/39740/39740_14996_3.pdf> accessed 25 May 2021.

71 ibid paras 185, 286 et seq.

72 Bundestagsdrucksache 18/10207, p. 51 in the context of § 18(3a) GWB: ‘Relevant für mögliche Wettbewerbsvorteile können aber auch die Fähigkeiten und Möglichkeiten eines Unternehmens zur Datenauswertung bzw. –verarbeitung sein’.

73 OECD, ‘Big Data: Bringing Competition Policy to the Digital Era’ (n 2) 11.

74 Google Search (Shopping) Commission Decision [2017] (n 69) paras 287 et seq.

75 § 18(3a) GWB.

76 R Shyam Khemani and Daniel Shapiro, ‘Glossary of Industrial Organization, Economics and Competition Law’ [1993] OECD 9 <https://oecd.org/regreform/sectors/2376087.pdf> accessed 13 January 2024.

77 Pinar Akman, ‘Exploitative Abuse in Article 82 EC: Back to Basics?’ [2008] University of East Anglia, ESRC Center for Competition Policy Working Paper No.09-1 <https://competitionpolicy.ac.uk/documents/107587/1.105848!wp09-1_exploitative_abuse_in_article82EC_PA.pdf> accessed 13 January 2024.

153 Adapted from Frances Dethmers and Jonathan Blondeel, ‘EU Enforcement Policy on Abuse of Dominance: Some Statistics and Facts’ (2017) 38(4) Eur Compet Law Rev 151.

78 Where EU competition law considers harm to consumers, it consistently refers to both final consumers and consumers at the intermediate level, e.g. manufacturers who use a product as an input or distributors of a good or service. See EU Commission, Guidance on the Commission’s enforcement priorities in applying Article 102, OJ 2009, C 45/7, para 19 <https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:52009XC0224(01)&from=EN> accessed 19 January 2024.

79 International Competition Network, ‘Report on the Results of the ICN Survey on Dominance/Substantial Market Power in Digital Markets’ (Unilateral Conduct Working Group, July 2020) 4 <https://www.internationalcompetitionnetwork.org/wp-content/uploads/2020/07/UCWG-Report-on-dominance-in-digital-markets.pdf> accessed 27 January 2024

80 For an overview of tying, see Case 3/37.792, Microsoft Corp., Commission Decision (Apr. 21, 2004). For American cases, see Jefferson Parish Hosp. District No. 2 v Hyde, 466 U.S. 2, 1 (1984); United States v Microsoft Corp., 253 F.3d 34 (D.C. Cir. 2001). Though the U.S. seemed to adopt the rule of reason after Illinois Tool Works Inc. v Independent Ink, Inc., 547 U.S. 28 (2006), ‘the general per se rule for tying arrangements when market power is present very likely still survives’, per Herbert Hovenkamp, ‘The Rule of Reason’ (2018) 70 Fla L Rev 81, 96. For more on bundling, see Nicholas Economides and Ioannis Lianos, ‘Elusive Antitrust Standard on Bundling in Europe and in the United States in the Aftermath of the Microsoft Cases’ (2012) 76 Antitrust LJ 483.

81 Economides and Lianos (n 17) 9.

82 ibid.

83 For an in-depth analysis of this question, see the Australian Competition and Consumer Commission (henceforth, the ‘ACCC’, ‘Digital Platforms Inquiry’ (2019) Final Report 8–10 and 89–99 <https://www.accc.gov.au/about-us/publications/digital-platforms-inquiry-final-report> accessed 8 January 2024.

84 OECD (2020), ‘Abuse of Dominance in Digital Markets’ (n 23) 55.

85 OECD, ‘Big Data: Bringing Competition Policy to the Digital Era’ (n 2) 21

86 David A Balto and Mathew Lane, ‘Monopolizing Water in a Tsunami: Finding Sensible Antitrust Rules for Big Data’ (2016) <https://ssrn.com/abstract=2753249> 9 January 2024; Andres V Lerner, ‘The Role of “Big Data” in Online Platform Competition’ <https://papers.ssrn.com/sol/papers.cfm?abstract_id=2482780> 4 January 2024; David D Sokol and Roisin E Comerford, ‘Does Antitrust Have a Role to Play in Regulating Big Data?’ in Cambridge Handbook of Antitrust, Intellectual Property and High Tech (Cambridge University Press 2016) 5.

87 See, e.g. Anja Lambrecht and Catherine E Tucker, ‘Can Big Data Protect a Firm From Competition?’ [2017] CPI ANTITRUST CHRONICLE 11, 12.

88 See Darren S Tucker and Hill B.Wellford, ‘Big Mistakes Regarding Big Data’ THE ANTITRUST SOURCE, December 2014, 13, 14–15.

89 ibid 13.

90 Sokol and Comerford (n 87) 5.

91 Darren and Wellford (n 89) 13.

92 Holles de Peyer Ben, ‘EU Merger Control and Big Data’ (2018) 13(4) Journal of Competition Law & Economics 767–90, 773.

93 See Competition & Markets Authority, The Commercial Use of Consumer Data, at 44 (June 2015) <https://www.gov.uk/governement/uploads/system/uploads/attachement_data/file/435817/The_commercial_use_of_consumer_data.pdf> accessed on 12 January 2024.

94 Where EU competition law considers harm to consumers, it consistently refers to both final consumers and consumers at the intermediate level, e.g. manufacturers who use a product as an input or distributors of a good or service. See EU Commission, Guidance on the Commission’s enforcement priorities in applying Article 102, OJ 2009, C 45/7, para 19 <https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:52009XC0224(01)&from=EN> accessed 19 January 2024.

95 Anne C Witt, ‘Excessive Data as Anticompetitive Conduct: The German Facebook Case’ (2019) 8(19) Jean Monnet Working Paper 3 <https://ssrn.com/abstract=3671445> accessed 12 January 2024.

96 Maurice Stucke, ‘Should We be Concerned about Data-Opolies?’ (2018) 2 Georgetown Law Technology Review 284.

97 European Data Protection Supervisor, ‘Privacy and Competitiveness in the Age of Big Data: The Interplay Between Data Protection, Competition Law and Consumer Protection in the Digital Economy’ (March 2014) 29. See also Bania, ‘The Role of Consumer Data in the Enforcement of EU Competition law’ (2018) 14 European Competition Journal 63 et seq.

98 Robertson (n 17) 173.

99 For methods of calculating the value of personal data, see OECD, ‘Exploring the Economics of Personal Data: A Survey of Methodologies for Measuring Monetary Value’ OECD Digital Economy Papers No 220 (2 April 2013); Gianclaudio Malgieri and Bart Custers, ‘Pricing Privacy-The Right to Know the Value of Your Personal Data’ (2018) 34 Computer Law & Security Review 289, 296 et seq.

100 Harri Kalimo and Klaudia Mejcher, ‘The Concept of Fairness: Linking EU Competition and Data Protection Law in the Digital Marketplace’ (2017) 42 EL Rev 210, 230 et seq.; Konstantina Bania, ‘The Role of Consumer Data in the Enforcement of EU Competition Law’ (2018) 14 European Competition Journal 63 et seq.

101 Robertson (n 17) 174.

102 Sokol and Comerford (n 86) 5.

103 On this see Wolfgang Körber, ‘Konzeptionelle Erfassung digitaler Plattform and adequate Regulierungsstrategien’ (2017) 21 Zeitschrift für Urheber-und Medienrecht 93, 96.

104 Robertson (n 17) 174.

105 ibid.

106 Case 27/76 United Brands v Commission, ECLI:EU:C:1978:22

107 ibid para 252.

108 ibid. For further cases on excessive prices, see Case 26/75, General Motors Continental v Commission, EU:C:1975:150; Case C-177/16, Latvian Copyright Society, EU:C:2017:689; Deutsche Post AG (Case COMP/C-1/36.915); Commission Decision 2001/892/EC, O.J 2001, L331/40.

109 C-52/07 Kanal 5 and TV 4, EU:C:2008:703, para 28. In AKKA/LAA, the Court held that another way of establishing whether the price was excessive would be to compare the prices applied in the Member State concerned with those applied in other Member States (C-177/16 AKKA/LAA, ECLI:EU:C:2017:689, para 38).

110 This is merely an intermediate step; Scandlines Sverige v Port of Helsinborg (Case COMP/36.568). Commission Decision of 23 July 2004, para 150.

111 Robertson (n 17) 175.

112 Case 27/76, United Brands, para 252.

113 Scandlines Sverige v Port of Helsingborg (Case COMP/36.568), Commission Letter of July 2004, para 217.

114 Bania, ‘The Role of Consumer Data in the Enforcement of EU Competition Law’ (2018)14 European Competition Journal 67.

115 ibid.

116 Judgment of 14 March 2013, Allianz Hungária, C-32/11, EU: C: 2013:160, paragraphs 46 and 47. See, however, also Judgment of 6 December 2012, AstraZeneca v Commission, C-457/10 P, EU: C: 2012:770, paragraph 132.

117 Bundeskartellamt, Facebook Decision (6 February 2019), B6-22/16.

118 ibid 10.

119 Brian X Chen, ‘I Downloaded the Information That Facebook Has on Me. Yikes’ New York Times (11 April 2018).

120 Witt (n 96).

121 Bundeskartellamt, Facebook Decision (6 February 2019), B6-22/16.

122 Wolfgang Kerber and Karsten K Zolna, ‘The German Facebook Case: The Law and Economics of the Relationship Between Competition and Data Protection Law’ [2022] European Journal of Law and Economics 2, 220.

123 See Bundesgerichtshof Order of 23 June 2020 in Case KVR 69/19.

124 ibid 239.

125 ibid.

126 For a legal analysis on the decision of the Bundesgerichtshof, see Rupprecht Podszum, ‘Der Verbraucher als Marktakteur: Kartellrecht und Datenschutz in der “Facebook”-Entscheidung des BGH’ [2020] GRUP 1268–76.

127 Judgment of the European Court of Justice, 4 July 2023, Meta Platforms Inc. and others v Bundeskartellamt, ECLI: EU: C: 2023: 537, recital 35.

128 Alessia D’Amico, ‘Meta ECJ Judgment’, the Digital Market Research Hub, 18 October 2023 <https://www.youtube.com/watch?v=SxQRM799lHc> accessed 24 January 2024.

129 Judgment of the European Court of Justice, 4 July 2023, Meta Platforms Inc. and others v Bundeskartellamt, ECLI: EU: C: 2023: 537, recital 36.

130 Judgment of the European Court of Justice, 4 July 2023, Meta Platforms Inc. and others v Bundeskartellamt, ECLI: EU: C: 2023: 537, recital 49.

131 ibid.

132 Judgment of the European Court of Justice, 4 July 2023, Meta Platforms Inc. and others v Bundeskartellamt, ECLI: EU: C: 2023: 537, recitals 46–49.

133 Kerber and Zolna (n 123) 220.

134 Bundesgerichtshof Order of 23 June 2020 in Case KVR 69/19, recital 239.

135 On see point, the opinions of Alessia D’Amico, Renato Nazzini and Thomas Höppner concur. See ‘The Meta ECJ judgment’, the Digital Market Research Hub, 18 October 2023 <https://www.youtube.com/watch?v=SxQRM799lHc> accessed 24 January 2024

136 ibid.

137 Alessia D’Amico, ‘Meta ECJ Judgment’, the Digital Market Research Hub, 18 October 2023 <https://www.youtube.com/watch?v=SxQRM799lHc> accessed 24 January 2024.

138 Judgment of the European Court of Justice, 4 July 2023, Meta Platforms Inc. and others v Bundeskartellamt, ECLI: EU: C: 2023: 537, recital 50.

139 Judgment of the European Court of Justice, 4 July 2023, Meta Platforms Inc. and others v Bundeskartellamt, ECLI: EU: C: 2023: 537, recital 27.

140 Judgment of the European Court of Justice, 4 July 2023, Meta Platforms Inc. and others v Bundeskartellamt, ECLI: EU: C: 2023: 537, recital 51.

141 Renato Nazzini, ‘Meta ECJ judgment’, the Digital Market Research Hub, 18 October 2023 <https://www.youtube.com/watch?v=SxQRM799lHc> accessed 24 January 2024.

142 Judgment of 14 March 2013, Allianz Hungária, C-32/11, EU: C: 2013:160, paragraphs 46 and 47. See, however, also Judgment of 6 December 2012, AstraZeneca v Commission, C-457/10 P, EU: C: 2012:770, paragraph 132.

143 Judgment of the European Court of Justice, 4 July 2023, Meta Platforms Inc. and others v Bundeskartellamt, ECLI: EU: C: 2023: 537, recital 47.

144 Opinion of the Advocate General Rantos delivered on 20 Sept. 2022 in case C-252/21 Meta Platforms Inc., formerly Facebook Inc., Meta Platforms Ireland Limited, Formerly Facebook Ltd; Facebook Deutschland GmbH v Bundeskartellamt, recital 24.

145 Judgment of the European Court of Justice, 4 July 2023, Meta Platforms Inc. and others v Bundeskartellamt, ECLI: EU: C: 2023: 537, recital 54g.

146 Judgment of the European Court of Justice, 4 July 2023, Meta Platforms Inc. and others v Bundeskartellamt, ECLI: EU: C: 2023: 537, recital 56.

147 Judgment of the European Court of Justice, 4 July 2023, Meta Platforms Inc. and others v Bundeskartellamt, ECLI: EU: C: 2023: 537, recital 59.

148 Judgment of the European Court of Justice, 4 July 2023, Meta Platforms Inc. and others v Bundeskartellamt, ECLI: EU: C: 2023: 537, recital 63.

149 Thomas Höppner, ‘Meta ECJ Judgment’, the Digital Market Research Hub, 18 October 2023 <https://www.youtube.com/watch?v=SxQRM799lHc> accessed 24 January 2024.

150 Renato Nazzini, ‘Meta ECJ judgment’, the Digital Market Research Hub, 18 October 2023 <https://www.youtube.com/watch?v=SxQRM799lHc> accessed 24 January 2024.

151 ibid.

152 Alessia D’Amico, ‘Meta ECJ judgment’, the Digital Market Research Hub, 18 October 2023 <https://www.youtube.com/watch?v=SxQRM799lHc> accessed 24 January 2024.