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‘Dữ liệu lớn’ có mang lại lợi thế cạnh tranh cho các công ty: Phân tích chống độc quyền
Tóm tắt
Nền kinh tế hiện nay đã chuyển từ cấu trúc kinh doanh truyền thống sang nền kinh tế số hóa. Nền kinh tế số hóa hoạt động nhờ vào các công cụ công nghệ, trong đó ‘dữ liệu’ được coi là công cụ quan trọng nhất trong bối cảnh hiện tại. Vấn đề trở nên cấp bách hơn với sự xuất hiện của ‘dữ liệu lớn’. Nhiều ý kiến cho rằng việc tích lũy, phân tích và sử dụng ‘dữ liệu lớn’ cho phép tạo ra nhiều hình thức rào cản gia nhập cho những người mới và sự bất cân xứng thông tin cho người tiêu dùng, điều này ảnh hưởng tiêu cực đến ‘cạnh tranh thị trường’ (Santesteban & Longpre, Tạp chí Chống độc quyền, 65(3), 459-485, 2020; Fast et al., 2021). Do đó, điều cần thiết là xem xét lại cách hiểu truyền thống về ‘cạnh tranh thị trường’ như đã quy định trong các luật chống độc quyền ở các khu vực pháp lý và cụ thể là Đạo luật Cạnh tranh Ấn Độ, 2002. Chế độ hiện tại tập trung vào lý thuyết giá neo cổ điển không đủ khả năng để hiểu các khía cạnh khác nhau của thế giới số hóa, nơi mà ‘dữ liệu’ trở thành hình thức tiền tệ mới có tác động đến quyền lực thị trường và, do đó, đến cạnh tranh thị trường. Các thị trường kỹ thuật số mang tính đa mặt và phi tuyến tính, nơi ‘dữ liệu lớn’ đóng vai trò như một chất bôi trơn cho sự hoạt động trơn tru của chúng. Câu hỏi trung tâm là liệu việc tiếp cận dữ liệu có cung cấp bất kỳ hình thức lợi thế cạnh tranh nào không. Một tài nguyên cung cấp bất kỳ hình thức lợi thế cạnh tranh nào phải rõ ràng, hiếm, không thể bắt chước, không thể thay thế và có giá trị (Barney, 1991). Nếu dữ liệu có những đặc điểm như vậy, việc thẩm thấu và sử dụng công nghệ được hỗ trợ bởi ‘dữ liệu lớn’ vào thị trường sẽ ảnh hưởng đến sự hiểu biết về những sai phạm cạnh tranh cơ bản. Các mối liên hệ tiềm năng giữa công nghệ, dữ liệu và quyền lực thị trường cũng ảnh hưởng đến sự hiểu biết về ‘sự thống trị’ như đã quy định trong luật hiện hành. Những thách thức độc đáo mà ‘dữ liệu lớn’ đặt ra không chỉ giới hạn trong chính sách cạnh tranh mà còn mở rộng đến việc thi hành pháp luật vì chúng kích hoạt các vấn đề hiến pháp chồng chéo liên quan đến quyền riêng tư. Điều này yêu cầu cần xem xét khoảng cách hiện tại giữa luật/chính sách cạnh tranh và những thách thức do ‘dữ liệu’ gây ra trong nền kinh tế số luôn phát triển này.
Từ khóa
#Dữ liệu lớn; lợi thế cạnh tranh; chính sách cạnh tranh; quyền lực thị trường; luật chống độc quyềnTài liệu tham khảo
Adomavicius, G., & Tuzhilin, A. (2015). Context-aware recommender systems. In: Ricci F, Rokach L and Shapira B (eds) Recommender systems handbook. pp.191–226, (New York: Springer).
Autorité de la concurrence and Bundeskartellamt, Franco/German Study on Competition Law and Data, (2016) <https://www.bundeskartellamt.de/SharedDocs/Publikation/DE/Berichte/Big%20Data%20Papier.pdf?__blob=publicationFile&v=2>. Accessed 18 Mar 2022.
Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1) < https://journals.sagepub.com/doi/10.1177/014920639101700108> accessed 30 March 2022.
Barney, J. (2001). Resource-based theories of competitive advantage: A ten-year retrospective on the resourcebased view. Journal of Management, 27(6), 643–650.
Baum, J. A. C. & Dobbin, F. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17.
Bezos, J. P. (1997). Letter to shareholders, AMAZON.COM, INC. <https://s2.q4cdn.com/299287126/files/doc_financials/2021/ar/Amazon-2020-Shareholder-Letter-and-1997-Shareholder-Letter.pdf> accessed 31 March 2022.
Bork, R. H. (1967). The goals of antitrust policy, The American Economic Review, Papers and Proceedings of the Seventy-ninth Annual Meeting of the American Economic Association, 57(2), 242–253.
Botta, M., Wiedemann, K. (2020). To discriminate or not to discriminate? Personalised pricing in online markets as exploitative abuse of dominance 50 European Journal of Law and Economics 381 <http://link.springer.com/10.1007/s10657-019-09636-3> accessed 31 March 2022.
Brooke Group Ltd. (1993) . v. Brown Williamson Tobacco Corporation, 509 U.S. 209.
Candeub, A. (2014). Behavioral economics, Internet search, and antitrust SSRN Electronic Journal <http://www.ssrn.com/abstract=2414179> accessed 31 March 2022.
Cegedium v. Euris, French Competition Authority, Decision no. 14-D-06, dated08.07.2014.
Chadha, S. (2022). ‘Drivers cancelling the ride’, surge pricing top issues for consumers who book app-based taxis: Survey, Times of India < https://timesofindia.indiatimes.com/business/india-business/drivers-cancelling-the-ride-surge-pricing-top-issues-for-consumers-who-book-app-based-taxis-survey/articleshow/90718955.cms> accessed July 30, 2022.
Chen, P-Y. & Hitt, L. M. (2005). Information technology and switching costs, 9, < https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.458.1995&rep=rep1&type=pdf> accessed 31 March 2022.
Cheng, S-R. (2021) Market power and switching costs: An empirical study of online networking market. SSRN Electronic Journal <https://www.ssrn.com/abstract=3979741> accessed 31 March 2022.
Competition Act, (2002) < https://www.cci.gov.in/sites/default/files/cci_pdf/competitionact2012.pdf> accessed 20 March, 2022.
De Mauro, A., Greco, M., & Grimaldi, M. (2016), A formal definition of big data based on its essential features, Library Review, 65(3),122–135, http://www.emeraldinsight.com/doi/pdfplus/10.1108/LR-06-2015-0061 accessed 22 March, 2022.
Diebold, F. X., Cheng, X., Diebold, S., Foster, D., Halperin, M., Lohr, S., Mashey, J., Nickolas, T., Pai, M., Pospiech, M., & Schorfheide, F. (2012). A personal perspective on the origin(s) and development of “big data”: The phenomenon, the term, and the discipline, available at <https://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.297.4593> accessed on August 15, 2022.
Dini, J. (2000). Amazon losses widen but shares rise after-hours, THESTREET <http://www.thestreet.com/story/875924/1/amazon-losses-widen-but-shares-rise-after-hours.html> accessed 31 March 2022.
Douglas, E. M. (2021). The new antitrust/data privacy law interface, YALE L. J. Forum J, 647–684.
Elzinga, K. G. (1977). The goals of antitrust: Other than competition and efficiency, what else counts? 125 University of Pennsylvania Law Review 1191 <https://www.jstor.org/stable/3311439?origin=crossref> accessed 31 March 2022.
Ezrachi, A. (2018). EU competition law goals and the digital economy SSRN Electronic Journal <https://www.ssrn.com/abstract=3191766> accessed 31 March 2022.
Fast, V., Schnurr, D., & Wohlfarth, M., (2021) Regulation of data-driven market power in the digital economy: Business value creation and competitive advantages from big data, < https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3759664> accessed 01 August, 2022.
Ferdman, R. A. (2013). Amazon changes its prices more than 2.5 million times a day, QUARTZ, < https://qz.com/157828/amazon-changes-its-prices-more-than-2-5-million-times-a-day/> accessed July 21, 2022.
Foer, A., & Durst, A. (2018). The multiple goals of antitrust. The Antitrust Bulletin, 63(4), 494–508.
Fourcade, M., & Healy, K. (2017). Seeing like a market. Socio-Economic Review, 15(1), 9–29.
Fox, M. E. (2008). The efficiency paradox, in Robert Pitofsky, How the Chicago school overshot the mark (Oxford University Press) <http://www.oxfordscholarship.com/view/10.1093/acprof:oso/9780195372823.001.0001/acprof-9780195372823> accessed 31 March 2022.
Gambaro, M. (2018). Big data competition and market power, Mkt. & Competition L. Rev., 2, 99
Geradin, D., & Petit, N. (2006). Price discrimination under EC competition law: Another antitrust doctrine in search of limiting principles? 2 Journal of Competition Law & Economics 479 <http://academic.oup.com/jcle/article/2/3/479/872437/PRICE-DISCRIMINATION-UNDER-EC-COMPETITION-LAW> accessed 1 April 2022.
Google Shopping case, Cf. Commission, Decision of June 27, 2017, Case AT.39740 (para 2, 8, 5).
Google/Android case, (AT.40099 – Google Android), (2018) < https://ec.europa.eu/competition/antitrust/cases/dec_docs/40099/40099_9993_3.pdf> accessed 23 March, 2022.
Google/Double Click merger case, Google/DoubleClick FTC File No. 071–0170, Statement by Federal Trade Commission < https://www.ftc.gov/system/files/documents/public_statements/418081/071220googledc-commstmt.pdf> accessed 28 March 2022.
Grunes, A. P. & Stucke, M. E. (2015). No mistake about it: The important role of antitrust in the era of big data, University of Tennessee Legal Studies Research Paper No. 269 <http://ssrn.com/abstract=2600051> accessed March 31, 2022.
Hagiu, A. & Wright, J. Data-enabled learning, network effects and competitive advantage < http://andreihagiu.com/wp-content/uploads/2021/06/Data-enabled-learning-May-2021.pdf> accessed 21 March 2022.
Harbour P. J. & Koslov, T. I. (2010). Section 2 in a Web 2.0 World: An expanded vision of relevant product markets, 76 ANTITRUST L.J. 785.
hiQ v. LinkedIn, 938 F.3d 985 (9th Cir. 2019).
Hoy, J. (2019). ‘Google ads vs Microsoft advertising: Which is better for my business?, Thee Digital < https://www.theedigital.com/blog/google-ads-vs-microsoft-advertising> accessed 30 March, 2022
Hu, H. et al. (2014). Toward scalable systems for big data analytics: A technology tutorial, 2 IEEE Access, accessed 14 March 2022.
ICN. (2020). Unilateral Conduct Working group, Survey report on substantial market power in digital market https://www.internationalcompetitionnetwork.org/wp-content/uploads/2020/07/UCWG-Report-on-dominance-in-digital-markets.pdf accessed 31 March 2022.
Katz, M. L. (2019). Multisided platforms, big data, and a little antitrust policy. 54 Review of Industrial Organization 695 <http://link.springer.com/10.1007/s11151-019-09683-9> accessed 31 March 2022.
Khan, L. M. (2017). Amazon’s antitrust paradox, 126 YALE L. J. 710.
Khan, L. (2014). Why you might pay more than your neighbor for the same bottle of salad dressing, QUARTZ < https://qz.com/168314/why-you-might-pay-more-than-your-neighbor-for-the-same-bottle-of-salad-dressing/ > accessed 05 August, 2022.
Kitchin, R., & McArdles G. (2016). What makes big data, big data? Exploring the ontological characteristics of 26 datasets, Bog Data & Society, 3(1).
Klishina, N. (2011). PPC Search: Google AdWords vs. Microsoft AdCenter (Bing), CallFire. http://www.callfire.com/blog/2011/01/07/ppc-search-google-adwords-vs-microsoft-adcenter-bing/.
Kubina, M., Varmus, M., & Kubinova, I. (2015). Use of big data for competitive advantage of company. 26 Procedia Economics and Finance, 561.
Lambrecht, A. & Tucker, C. (2015) Can big data protect a firm from competition? SSRN Electronic Journal <http://www.ssrn.com/abstract=2705530> accessed 31 March 2022.
Lande, R. H. (1989). Chicago’s false foundation: Wealth transfers (not just efficiency) should guide antitrust. Antitrust Law Journal, 58(2), 631–644.
Lianos, I. (2018). The poverty of competition law: The long story, centre for law, economics and society, Research Paper Series No. 2/2018 www.ucl.ac.uk/cles/sites/cles/files/cles_2-2018.pdf accessed 29 March 2022.
Longman, P. (2019). Big tech is spying on your wallet < https://washingtonmonthly.com/2019/04/07/big-tech-is-spying-on-your-wallet/> accessed 25 March, 2022.
Marty, F. (2020). Is the consumer welfare obsolete? A European Union competition law perspective GREDEG Working Paper No. 2020–13, <https://ideas.repec.org/s/gre/wpaper.html> accessed 31 March 2022.
Matrimony.com Limited v. Google LLC and others, Case No. 07 of 2012.
Mazzeo, M., & McDevitt, R. (2014). Business strategy and antitrust policy (Roger D Blair and D Daniel Sokol eds, Oxford University Press) <http://oxfordhandbooks.com/view/10.1093/oxfordhb/9780199388592.001.0001/oxfordhb-9780199388592-e-011> accessed 31 March 2022.
Microsoft Corp. v. Commission, Case T-201/04, September 17, 2007.
Ministry of Corporate Affairs. (2019). Government of India, The report of Competition Law Review Committee <https://www.ies.gov.in/pdfs/Report-Competition-CLRC.pdf> accessed March 31, 2022.
Ministry of Road Transport and Highways. (2020). Motor vehicle aggregator guidelines issued to regulate shared mobility and reducing traffic congestion and pollution, Press Information Bureau <https://pib.gov.in/Pressreleaseshare.aspx?PRID=1676403 > accessed July 30, 2022.
Ministry of Road Transport and Highways, Government of India, (2020). Motor vehicles aggregator guidelines, <https://morth.nic.in/sites/default/files/notifications_document/Motor%20Vehicle%20Aggregators27112020150046.pdf> accessed 25 March 2022.
Nuccio, M., & Guerzoni, M. (2019). Big data: Hell or heaven? Digital Platforms and Market Power in the Data-Driven Economy, Competition & Change, 23(3), 312–328.
Ohlhausen, M. K. & Okuliar, A. P. (2015). Competition, consumer protection, and the right [approach] to privacy, 80 ANTITRUST L.J. 121, 123.
Organization for Economic Co-operation and Development (OECD). (2016). Big data: Bringing competition policy to the digital era <https://one.oecd.org/document/DAF/COMP(2016)14/en/pdf#:~:text=Definition%20of%20Big%20Data,-5.&text=According%20to%20De%20Mauro%20et,for%20its%20transformation%20into%20value.%E2%80%9D> accessed 31 March 2022.
PeopleBrowsr, Inc., And PeopleBrowsr Pty., Ltd., v. Twitter, Inc. (n.d) Case No. 3:12-cv-06120-EMC.
Peteraf, M. A., & Barney, J. B. (2003). Unravelling the resource-based tangle. Managerial & Decision Economics, 24(4), 309–323.
Pitofsky, R. (1979). The political content of antitrust, 127 U. Pa. L. Rev. 1051–1075.
Posner, R. A. (1979). The Chicago school of antitrust analysis. 127 University of Pennsylvania Law Review, 925 <https://www.jstor.org/stable/3311787?origin=crossref> accessed 30 March 2021.
Samir Agrawal v. Competition Commission of India & Ors., Competition Commission of India in Case No. 37 of 2018.
Santesteban, C., & Longpre, S. (2020). How big data confers market power to big tech: Leveraging the perspective of data science. The Antitrust Bulletin, 65(3), 459–485.
Sadowski, J. (2019). “When data is capital: datafication, accumulation, and extraction”, big data & society 16(1).
Satyen Narendra Bajaj v. PayU Payments Private Limited & Anr., Competition Commission of India, Case No. 23 of 2019.
Shan, S., Luo, Y., Zhou, Y., & Wei, Y. (2019). Big data analysis adaptation and enterprises’ competitive advantages: The perspective of dynamic capability and resource-based theories. Technology Analysis & Strategic Management, 31(4), 406–420.
Sokol D. D. & Comerford, R. (2016). Antitrust and regulating big data, 23 Geo. Mason L. Rev. 1129.
Streitfeld, D. (2013). As Competition Wanes, Amazon cuts back discounts, N.Y. TIMES, <https://www.nytimes.com/2013/07/05/business/as-competition-wanes-amazon-cuts-back-its-discounts.html> accessed 20 March 2022.
Stucke, M. E. & Grunes, A. P., (2015). Debunking the myths over big data and antitrust (2) CPI Antitrust Chronicle <http://ssrn.com/abstract=2612562> accessed March 31, 2022.
Suo Moto Case No. 01 of 2021.
Suo moto case against WhatsApp Inc. LLC and Facebook Inc., Suo Moto Case No. 01 of 2021.
United States Department of Justice & Federal Trade Commission. (n.d). Horizontal merger guidelines <https://www.justice.gov/atr/horizontal-merger-guidelines-08192010 > accessed 28 March 2022.
Vaheesan, S. (2019). The Profound Nonsense of Consumer Welfare Antitrust”, p. 1- 16, The Antitrust Bulletin.
Vallabhaneni, A. K., & Geetha SP Entertainment LLP (2019) Competition Commission of India, Case No. 17.
Vinod Kumar Gupta v. (2016). WhatsApp Inc., Case No. 99.
Working Paper No. 2020–13, <https://ideas.repec.org/s/gre/wpaper.html> accessed 31 March 2022.
Yao, S., & Mela, C. F. (2011). A dynamic model of sponsored search advertising. Marketing Science, 30(3), 447–468.
Zettelmeyer, F. (2018). The economics of big data and personal information, presentation at the Federal Trade Commission, FTC HEARING 6, SESSION 2, Nov. 6, 2018, https://www.ftc.gov/news-events/audio-video/video/ftc-hearing-6-nov-6-session-2-economics-big-data-personalinformation. Accessed 28 Mar 2022.
Zuboff, S. (2020). The age of surveillance capitalism: The fight for a human future at the new frontier of power. PublicAffairs.