نوع مقاله : مقاله پژوهشی
نویسندگان
1 استادیار، دانشکده حقوق، دانشگاه شهید بهشتی، تهران، ایران
2 دانشجوی دکتری، دانشکده حقوق، دانشگاه شهید بهشتی، تهران، ایران ایمیل نویسنده مسئول: r_khalili@sbu.ac.ir
چکیده
تازه های تحقیق
*بهرهگیری از کلان دادهها، بسته به رویهها و شیوههای بهرهگیری به افزایش یا کاهش فرصتهای نوآوری در بازارهای دیجیتال می انجامد.
*دخالت مستقیم برای حفظ نوآوری در بازار به مصلحت نیست و مراجع رقابتی با حفظ فضای رقابت و مقابله با رفتارهای محدودکننده میتوانند به حفظ رقابت نوآورانه کمک کنند.
*بهرهگیری از نظریههایی چون نظریه «هزینههای نوآوری» در بررسیهای رقابتی، میتواند تضمینگر کارآیی پویا در بازارهای داده محور باشد.
کلیدواژهها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
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.
کلیدواژهها [English]
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