ALGORITMIK NARX BELGILASH SHAROITIDA RAQOBATGA QARSHI KELISHUVLARNING ANTIMONOPOL TAHLILI
##article.subject##:
algoritmik narx belgilash, raqobatga qarshi kelishuvlar, kartel, muvofiqlashtirilgan harakatlar, hub-and-spoke, sun’iy intellekt, raqamli iqtisodiyot, antimonopol huquq, O‘zbekiston Respublikasi raqobat huquqi##article.abstract##
Mazkur maqolada algoritmik narx belgilash sharoitida yuzaga keladigan raqobatga qarshi kelishuvlarni antimonopol jihatdan kvalifikatsiya qilishning nazariy va amaliy muammolari tadqiq etiladi. Muallif algoritmik koordinatsiyaning asosiy turlarini (hub-and-spoke, parallel algorithms, predictable agent, autonomous machine learning) tahlil qiladi, kelishuv hamda muvofiqlashtirilgan harakatlarning mavjudligini aniqlashga oid doktrinal yondashuvlarni ko‘rib chiqadi, shuningdek, Amerika Qo‘shma Shtatlari, Yevropa Ittifoqi va O‘zbekiston Respublikasining huquqni qo‘llash amaliyotini taqqoslaydi. Qiyosiy-huquqiy tahlil asosida milliy antimonopol qonunchilikni takomillashtirish bo‘yicha, jumladan, narx algoritmlaridan foydalanilganda prezumpsiyalarni joriy etish va javobgar subyektlar doirasini kengaytirishga oid takliflar ilgari suriladi.
Библиографические ссылки
Закон Республики Узбекистан «О конкуренции» № 850 (в ред. от 03.07.2023 г.) // Национальная база данных законодательства Республики Узбекистан. URL: https://lex.uz/docs/6518383
Постановление Кабинета Министров Республики Узбекистан № 256 (в ред. от 01.05.2024 г.) «Об утверждении нормативных правовых актов по антимонопольному регулированию на товарном и финансовом рынках» // Национальная база данных законодательства Республики Узбекистан. URL: https://lex.uz/ru/docs/6907023#
Consolidated Version of the Treaty on the Functioning of the European Union, OJ C 326, 26.10.2012, art. 101.
Regulation (EU) 2022/1925 of the European Parliament and of the Council of 14 September 2022 on contestable and fair markets in the digital sector (Digital Markets Act), OJ L 265, 12.10.2022.
Sherman Antitrust Act of 1890, 15 U.S.C. §§ 1–7.
II. Материалы правоприменительной практики
Eturas UAB and Others v Lietuvos Respublikos konkurencijos taryba, Case C-74/14, ECLI:EU:C:2016:42, Judgment of 21 January 2016.
United States v. Topkins, No. CR 15-00201 WHO (N.D. Cal. 2015).
III. Научная и аналитическая литература
Calvano E., Calzolari G., Denicolò V., Pastorello S. Artificial Intelligence, Algorithmic Pricing, and Collusion // American Economic Review. — 2020. — Vol. 110, № 10. — P. 3267–3297.
Ezrachi A., Stucke M.E. Virtual Competition: The Promise and Perils of the Algorithm-Driven Economy. — Cambridge, MA: Harvard University Press, 2016. — 368 p.
Gal M.S. Algorithms as Illegal Agreements // Berkeley Technology Law Journal. — 2019. — Vol. 34. — P. 67–118.
Harrington J.E. Developing Competition Law for Collusion by Autonomous Artificial Agents // Journal of Competition Law & Economics. — 2018. — Vol. 14, № 3. — P. 331–363.
Mehra S.K. Antitrust and the Robo-Seller: Competition in the Time of Algorithms // Minnesota Law Review. — 2016. — Vol. 100. — P. 1323–1375.
Schwalbe U. Algorithms, Machine Learning, and Collusion // Journal of Competition Law & Economics. — 2018. — Vol. 14, № 4. — P. 568–607.
OECD. Algorithms and Collusion: Competition Policy in the Digital Age. — Paris: OECD Publishing, 2017. — 72 p.