KAYNAKÇA
Affeldt, P., Kesler, R.: Big Tech Acquisitions — Towards Empirical Evidence, Journal of European Competition Law & Practice, 2021, C. 12, S. 6, s. 471-478.
Alfange Jr., D.: Jeremy Bentham and the Codification of Law, Cornell Law Review, 1969, C. 55, S. 58, s. 58-77.
Avrupa Komisyonu: 27 Mart 2017 tarihli İç Pazar ve AEA Anlaşması ile uyumlu bir yoğunlaşma ilan eden Komisyon Kararı (Case M.7932 – Dow/DuPont), C(2017) 1946, §97, 2017.
Sayfa 391
Barmash, P.: The Legal Authority of the Laws of Hammurabi, The Laws of Hammurabi: At the Confluence of Royal and Scribal Traditions, New York, 2021; online edn, Oxford Academic, 22.10.2020, s. 234, https://doi.org/10.1093/oso/9780197525401.003.0008, Erişim Tarihi: 14.09.2024.
Berry, S. T.: Estimating Discrete-Choice Models of Product Differentiation, RAND Journal of
Economics, 1994, C. 25, s. 242-262
Braunschweig, D.: Input-Process-Output Model, Programming Fundamentals, Harper College, 2021. Erişim: https://harpercollege.pressbooks.pub/programmingfundamentals/chapter/input-process-output-model/ (Erişim Tarihi: 14.09.2024).
Budzinski, O., Noskova, V.: Cartel Screening and Machine Learning, Stanford Computational Antitrust Paper Series, 2022, s. 55-68.
Chopra, R., Khan, L. M.: The Case for “Unfair Methods of Competition” Rulemaking, The University of Chicago Law Review, 2020, C. 87, S. 2, s. 357-380.
Crooke, P., Froeb, L., Tschantz, S. et al.: Effects of Assumed Demand Form on Simulated Postmerger Equilibria, Review of Industrial Organization, 1999, C. 15, s. 205-217.
Deaton, A., Muellbauer, J.: An Almost Ideal Demand System, American Economic Review, 1980, C. 70, s. 312-326.
Di Porto, F., Grote, T., Volpi, G., Invernizzi, R.: ‘I See Something You Don’t See’. A Computational Analysis of the Digital Services Act and the Digital Markets Act, Stanford Computational Antitrust, 2021, C. 6, s. 84-112.
European Commission: Mergers: Commission Clears Bayer’s Acquisition of Monsanto, Subject to Conditions, European Commission, 21.03.2018, https://ec.europa.eu/commission/presscorner/detail/en/IP_18_2282, archived at https://perma.cc/KAY5-A5T6?type=image, Erişim Tarihi: 14.09.2024.
Erevelles, S., Fukawa, N., Swayne, L.: Big Data Consumer Analytics and the Transformation of Marketing, Journal of Business Research, 2016, C. 69, S. 2, s. 897-904.
Genesereth, M.: Computational Law: The Cop in the Backseat, White Paper, CodeX—The Stanford Center for Legal Informatics, 2015, s. 1-8.
Gifford, D. J., Kudrle, R. T.: Antitrust Goals, Procedures, and Policies in the U.S. and the EU, Antitrust Bulletin, 2017, C. 62, S. 2, s. 239-253.
Sayfa 392
Goldenfein, J., Leiter, A.: Legal Engineering on the Blockchain: ‘Smart Contracts’ as Legal Conduct, Law and Critique, 2018, C. 29, s. 141-149.
Guthmann, Y., Frumence, A., Hoogterp, C.: Deploying Network Analysis in Antitrust Law, Stanford Computational Antitrust, 2023, C. 3, s. 1-21.
Harrington, J. E. Jr., Imhof, D.: Cartel Screening and Machine Learning, Stanford Computational Antitrust Paper Series, 2022, s. 140-147.
Hofmann, H. C. H., Lorenzoni, I.: Future Challenges for Automation in Competition Law Enforcement, Stanford Computational Antitrust, 2023, C. 3, s. 36-54.
Imhof, D., Karagök, Y., Rutz, S.: Screening for Bid Rigging – Does It Work?, Journal of Competition Law & Economics, 2018, C. 14, s. 235-260.
Kitapçı, İ.: Joseph Schumpeter’in Girişimcilik ve İnovasyon Anlayışı: Yaratıcı Yıkım Kavramı ve Geçmişten Günümüze Yansımaları, Journal of Empirical Economics and Social Sciences, 2019, C. 1, S. 2, s. 54-74.
Kumar, P.: Large Language Models (LLMs): Survey, Technical Frameworks, and Future Challenges, Artificial Intelligence Review, 2024, C. 57, s. 1-51.
Lianos, I. (ed.): Computational Competition Law and Economics - An Inception Report, Hellenic Competition Commission, 2021
Lim, D.: Can Computational Antitrust Succeed?, Stanford Computational Antitrust, C. 1, 2021, s. 38-51.
Mahari, R. Z., Lera, S. C., Pentland, A.: Time for a New Antitrust Era: Refocusing Antitrust Law to Invigorate Competition in the 21st Century, Stanford Computational Antitrust, C. 1, 2021, s. 52-63.
Makridis, C. A., Thayer, J.: The Big Tech Antitrust Paradox: A Reevaluation of the Consumer Welfare Standard for Digital Markets, Stanford Technology Law Review, 2024, C. 27, s. 72-130.
McCaskill, J., Elliott, E., Harrington, J., Kiel, L. D.: Antitrust Policy and Blockchain Technology: An Exploration from the Complex Systems Perspective, Stanford Computational Antitrust, 2022, C. 2, s. 118-130.
Molski, R.: Competition Law and Artificial Intelligence – Challenges and Opportunities, Teka Komisji Prawniczej PAN Oddział W Lublinie, 2022, C. 14, S. 2, s. 339-352.