The Impact of Big Data on Innovation and Dynamic Efficiency in the Competition Process in Digital Markets

Document Type : Original Article

Authors

1 Assistant Professor, Faculty of Law, Shahid Beheshti University, Tehran, Iran

2 Ph.D. Candidate, Faculty of Law, Shahid Beheshti University, Tehran, Iran Corresponding Author Email: r_khalili@sbu.ac.i

10.48308/jlr.2025.239462.2877

Abstract

Introduction 
The transformation of digital markets in recent decades, alongside the expansion of big data, artificial intelligence, and advanced data-mining technologies, has profoundly reshaped traditional patterns of competition. In these markets, data is no longer merely an auxiliary input; rather, it functions as a strategic asset and a primary source of economic value creation and innovation. Unlike traditional competition law analyses—largely focused on indicators such as price, market share, and short-term consumer welfare—data-driven markets reveal that access to, control over, and the ability to exploit data have become decisive factors of market power. This situation may, on the one hand, enhance efficiency, improve service quality, and enable the emergence of new markets; on the other hand, through data concentration and the creation of entry barriers, it may weaken dynamic competition and innovation. This study aims to clarify the dual role of big data in fostering innovation while simultaneously generating competitive risks, and to demonstrate how data-driven capacities can be leveraged to promote competition on the merits without leading to structural market foreclosure.
Methods
This research adopts a descriptive-analytical approach grounded in comparative study. Theoretical frameworks of competition economics related to innovation, network effects, economies of scale and scope, and the role of data as an essential input are first examined. These foundations are then analyzed in light of legal instruments, enforcement practices, and decisions of competition authorities across different jurisdictions. The study of merger cases and anticompetitive conduct in digital markets, together with policy reports and economic research, provides an empirical basis for assessing the effects of data concentration on the structure of the relevant market. The methodology is qualitative and document-based, seeking to integrate legal and economic analysis in order to present a coherent account of the competitive functions of data and the regulatory challenges it entails.
Results and Discussions
The findings indicate that big data performs a dual function in digital markets. From a positive perspective, broad access to data enables service personalization, reduces information asymmetries, enhances productivity, and accelerates research and development processes. This dynamic facilitates both incremental and disruptive innovations, the creation of new business models, and improvements in consumer welfare. Data aggregation can also lower transaction costs and, through predictive analytics, enhance allocative efficiency. However, data concentration in the hands of large firms may generate cumulative advantages that competitors find difficult to replicate. Strong network effects, user lock-in, and exclusive access to behavioral data allow dominant firms not only to consolidate their market position but also to discourage the entry of potential innovators. Under such conditions, competition may be weakened—and long-term innovation harmed—even in the absence of price increases. In the context of mergers, the results reveal similarly mixed effects. Data-driven horizontal mergers between large platforms and smaller innovative firms have, in some cases, eliminated potential competition and reduced technological diversity, whereas certain vertical mergers have created efficiency gains by integrating data infrastructures and lowering development costs. The key factor distinguishing these outcomes is the extent to which rivals retain access to critical data and whether dynamic competition can emerge post-merger. The study further shows that one of the most significant barriers to innovation in these markets is the rise in entry and R&D costs resulting from lack of access to essential data. New entrants face substantial financial and temporal burdens in acquiring competitive datasets, increasing innovation risk and constraining technological investment. Consequently, data concentration may gradually shift the innovation ecosystem in favor of entrenched incumbents.
Conclusion
Overall, this research demonstrates that big data is neither inherently harmful to competition nor automatically conducive to innovation; its effects depend on how data is concentrated, controlled, and competitively utilized within market structures. While it can drive efficiency and service development, it may also reinforce scale advantages and create entry barriers that weaken dynamic competition. Safeguarding innovation therefore does not require direct, interventionist market engineering, but rather a competition policy focused on preserving the conditions for technological rivalry, preventing exclusionary conduct, and assessing the competitive use of data through analytical lenses such as innovation costs. In the context of Iranian law, moving beyond traditional approaches and reinterpreting existing legal tools in light of the realities of the data-driven digital economy is essential to maintaining competitive dynamism in digital markets.

Highlights

*The use of big data, depending on the practices and methods of its utilization, may lead to either an increase or a reduction in innovation opportunities within digital markets.
*Direct intervention aimed at preserving innovation in the market is not advisable; rather, competition authorities can contribute to safeguarding innovative competition by maintaining a competitive environment and addressing restrictive practices.
*Employing theories such as the “innovation costs” theory in competition assessments can help ensure dynamic efficiency in data-driven markets.

Keywords

Main Subjects

References

References
Books
Charbit, N, Ahmad, S. (eds.). Frédéric Jenny: Standing Up for Convergence and Relevance in Antitrust – Liber Amicorum, Volume 1, Paris: Institute of Competition Law, 2019.
Ghaffari Farsani, Behnam, Competition Law and Its Civil Remedies, Tehran: Mizan, 2019. (in Persian)
Rahbari, Ebrahim and Vahid Hassani, Competition Law in the Field of Intellectual Property Rights, Volume 1, Tehran: Samt, 2019. (in Persian)
Articles
Autorité de la Concurrence and Bundeskartellamt. “Competition Law and Data”, 2016, PP 1–32, Doi: 10.2139/ssrn.3350512/ 
Bourreau. M, de Streel. A. “Digital Conglomerates and EU Competition Policy, Telecom ParisTech”, CERRE, 2019, PP 1‑35, Doi: 10.2139/ssrn.3350512/
Bourreau, M. and Krämer, J. and Buiten, M. “Interoperability In: Digital Markets”, CERRE, Report, 2022, PP 1‑48, Doi: 10.2139/ssrn.3350512/
Cheah, S. and Wang, S. “Big Data-Driven Business Model Innovation by Traditional Industries in the Chinese Economy”, Journal of Chinese Economic and Foreign Trade Studies, Volume 10, Issue 3, 2017, PP  229-251, Doi: 10.1108/JCEFTS-05-2017-0013/
CMA, “A New Pro-Competition Regime for Digital Markets Advice of the Digital Markets Taskforce”, 2020.
Condorelli, D. and Padilla, J. “Harnessing Platform Envelopment in the Digital World”, Journal of Competition Law & Economics, Volume 16, Issue 2, 2020, PP 143-187, Doi: 10.1093/joclec/nhaa006/
European Commission. “Towards a Thriving Data-Driven Economy”, COM/2014/0442 final, 2014.
Fast, V, Schnurr. D. and Wohlfarth, M. “Regulation of Data-Driven Market Power in the Digital Economy: Business Value Creation and Competitive Advantages from Big Data”, Journal of Information Technology, Volume 38, 2022, PP 122‑145, Doi: 10.1177/02683962221114394/
Fletcher, A. “Digital Competition Policy: Are Ecosystems Different? Hearing on Competition Economics of Digital Ecosystems”, OECD Competition Committee, 2020, PP 1‑37.
Jung, N. and Sinclair, E. “Innovation Theories of Harm in Merger Control”, European Competition Law Review, Volume 40, Issue 6, 2019, PP 266‑275.
Kopanakis, I; Vassakis, K. and Mastorakis, G. “Big Data in Data-Driven Innovation: The Impact in Enterprises' Performance”, Conference: 11th Management of Innovative Business, Education & Support systems International Conference, 2016, PP 12‑28.
Kraemer, J. and Schnurr, D. “Big Data and Digital Markets Contestability: Theory of Harm and Data Access Remedies”, Journal of Competition Law & Economics, Volume 18, Issue 2, 2022, PP 233‑276, Doi: 10.1093/joclec/nhab015/
Laney, D. “3D Data Management: Controlling Data Volume, Velocity and Variety”, META Group Research, Volume 949, 2001, PP 1‑12.
OECD, “Algorithms and Collusion: Competition Policy in the Digital Age”, DAF/COMP, 2017, Doi: 10.1787/258dcb14‑en/ 
OECD, “Big Data: Bringing Competition Policy to The Digital Era”, DAF/COMP, 2016, PP 1‑60, Doi: 10.1787/a1c2d55c‑en/
OECD, “Competition and Innovation - The Role of Innovation in Enforcement Cases”, DAF/COMP 12, 2023, PP 1‑42.
OECD, “Theories of Harm for Digital Mergers”, DAF/COMP, 2023, PP 1‑55, Doi: 10.1787/0099737e‑en/
Prüfer, J. and Schottmüller, C. “Competing with Big Data”, Journal of Industrial Economics, Wiley Blackwell, Volume 69, Issue 4, 2021, PP 967‑1008. Doi: 10.1111/joie.12259/
Rahbari, Ebrahim, “A Reflection on the Relationship between Big Data and Market Power in Platform Markets from the Perspective of Recent Developments in Competition Law.” Private Law Studies Quarterly, Volume 53, Issue 2, 2023, PP 205-228. (in Persian) Doi: 10.22059/jlq.2023.347799.1007709
Rahbari, Ebrahim, “Algorithmic Price Collusion: A Comparative Study in U.S., EU, and Iranian Competition Law”, Comparative Law Studies Quarterly, Volume 14, Issue 1, 2023, PP 286–287. (in Persian) DOI: 10.22059/jcl.2023.345558.634394
Rahbari, Ebrahim. “Competitive Assessment Standards for Mergers Involving Intellectual Property Rights”, Private Law Studies Quarterly, Volume 48, Issue 1, 2018, PP 59-76. (in Persian) Doi: 10.22059/jlq.2018.215114.1006784
Shahid, U. and Sheikh, N. “Impact of Big Data on Innovation, Competitive Advantage, Productivity, and Decision Making: Literature Review”, Open Journal of Business and Management, 2021, PP 32‑57, Doi: 10.4236/ojbm.2021.92032/
Sokol. D., Comerford. D. and Roisin E. “Antitrust and Regulating Big Data”, George Mason Law Review 119, University of Florida Levin College of Law, Research Paper, Volume 23, Issue 5, 2016, PP 987‑1020, Doi: 10.1017/9781316671313.016/
Stucke. M. and Grunes. A. “Debunking the Myths Over Big Data and Antitrust, CPI Antitrust Chronicle”, University of Tennessee Legal Studies, Research Paper, Issue 276, 2015, PP 1–24, Doi: 10.2139/ssrn.2612562/
US House Judiciary Subcommittee on Antitrust, “Commercial and Administrative Law, Investigation of Competition in Digital Markets”, 2020, PP 1‑74.
Van de Waerdt, P. “From Monocle to Spectacles: Competition for Data and Data Ecosystem Building”, European Competition Journal, Volume 19, Issue 2, 2023, PP 191‑225, Doi: 10.1080/17441056.2023.2169366/
Thesis
Vejtasa, Martin. “Big Data and Competition Law”, Master Thesis, Masaryk University, Department of Commercial Law, 2019.
Cases
Case No. 8955 Takeda/Shire, EC decision, 2018.
Case No. AT.8084, Bayer / Monsanto, EC decision, 2018.
Case No. C-4439, Nielsen Holdings N.V. and Arbitron INC, FTC Decision, 2016.
Case No. M.10188Ilumina/Grail, EC decision, 2022.
Case No. M.7932, Merger of Dow/Dupont, EC decision, 2017.
Case No.2:23-cv-01495-JHC, Federal Trade Commission v. Amazon.com, Inc., Federal Court, 2022.
Case T-691/14, Servier SAS and Others v European Commission, Judgment of the General Court (Ninth Chamber, Extended Composition), 2018.
CMA v. Facebook Inc (now Meta Platforms Inc) / Giphy, Inc merger inquiry, 2022.
Council of Competition, “Complaint by Niyak Technology Developers Co. and Azma Information Structures Co. regarding the monopolistic process of using the LIMS Software in Laboratories for Food, Beverage, Cosmetic, and Hygiene Control”, Decision No 522, 2022. (in Persian)
Council of Competition, Complaint by the Association of Research and Knowledge-Based Companies in Oil, Gas, Petrochemical and Refining Industries (APNA) against the Ministry of Oil and its four main subsidiaries, Decision No 466, 2021. (in Persian)
Sites
www.assets.publishing.service.gov.uk  
www.bundeskartellamt.de
www.penfriend.ai

Files

History

  • Receive Date: 12 April 2025
  • Revise Date: 14 October 2025
  • Accept Date: 23 November 2025

Share

How to cite

Statistics