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Competition Concerns in Cross- Border E-Commerce Implications for Developing Countries

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Competition Concerns in Cross- Border E-Commerce Implications for Developing Countries STUDY Competition Concerns in Cross- border E-Commerce Implications for Developing Countries Philippe Brusick Competition Concerns in Cross- border E-Commerce: Implications for Developing Countries Authored by: Philippe Brusick Published by: CUTS INTERNATIONAL, GENEVA Rue de Vermont 37-39 1202 Geneva, Switzerland www.cuts-geneva.org This paper was undertaken by Philippe Brusick, Chairperson, General Assembly, CUTS International Geneva. It is published under CUTS Internataional Geneva’s project “Keeping Pace with Trade Developments”, undertaken with funding support from the Ministry of Foreign Affairs, Sweden. Citation: BRUSICK, P. (2018). Competition Concerns in Cross-border E-Commerce: Implications for Developing Countries. Geneva: CUTS International, Geneva. Disclaimer: The views expressed in this publication represent the opinions of the author, and do not necessarily reflect the views of CUTS or its funders. Cover Photo: G.L. Barose © 2018. CUTS International, Geneva The material in this publication may be reproduced in whole or in part and in any form for education or non-profit uses, without special permission from the copyright holders, provided acknowledgment of the source is made. The publishers would appreciate receiving a copy of any publication, which uses this publication as a source. No use of this publication may be made for resale or other commercial purposes without prior written permission of the copyright holders. 2 Table of Contents Table of Contents Abstract ........................................................................................................... 4 Abbreviations .................................................................................................. 5 Glossary ........................................................................................................... 8 Introduction ................................................................................................... 11 1. E-Commerce, Main Types of Businesses Involved and Participation of Selected Developing Countries in the Digital Economy ................................ 13 2. Potential Benefits and Challenges of the Digital Economy for Smaller Developing Countries .................................................................................... 28 3. Main Issues Related to Anticompetitive Practices by Digital Economy Firms.............................................................................................................. 34 Lessons Learnt and Recommendations for Smaller Developing Countries .. 56 References..................................................................................................... 63 3 Abstract This paper looks at the rapid emergence of the In conclusion, this paper examines the main digital revolution in the world economy and the lessons learnt and draws attention to the urgent way in which developing countries, in particular need for all countries to come to grips with the smaller developing economies in Africa, Asia and anticompetitive challenges posed by the the Pacific, are getting involved in e-commerce. imminent conglomeration of the digital economy These countries are for the greatest part ill- in each and every sector of our lives. While most equipped to face the challenge posed by giant developed competition authorities (CAs) need to international e-commerce platforms and will need reach consensus on their enforcement practices to rapidly join the bandwagon of national and with regard to this type of businesses, more regional competition authorities’ efforts to come to advanced developing countries CAs should grips with this new type of business models. cooperate with smaller developing economies, to ensure they are able to enforce competition rules After looking at the characteristics of the main in a proper way, avoiding actions which might types of businesses involved in the digital stifle innovation and the spread of benefits of economy, the paper examines broadly the competition, while ensuring that they are able to potential benefits and challenges these firms control anticompetitive harm. Special bring to smaller developing countries, particularly concertation and cooperation efforts are also in Africa, Asia and the Pacific regions. It then recommended for regional competition covers the main anticompetitive practices that authorities, such as those of regional Free Trade may take place in e-commerce, including Areas, which must rapidly take the lead in collusion in hard-core cartels, vertical restraints ensuring that e-commerce is not hampered by and abuse of dominance, as well as anticompetitive practices. concentrations, whereby large businesses might eliminate small start-ups or larger competitors in domestic markets of smaller developing countries. 4 Abbreviations Abbreviations ACCC Australian Competition and Consumer Commission. ACFTA ASEAN-China Free Trade Area. AI Artifitial intelligence (see in Glossary). ASEAN Association of Southeast Asian Nations. BATX Bandu, Alibaba, Tencent, Xiaomi (Chinese platforms, equivalents to GAFAs). CAs Competition authorities CCCS Competition and Consumer Commission of Singapore. CCI Competition Commission of India. CMA Competition and Markets Authority (UK). CMS Content Management System. COFECE Federal Economic Competition Commission of Mexico. COMESA Common Market for Eastern and Southers Africa. CCOPOLC Competition and Consumer Policy and Law Committee, established in 2009 to implement the SADC cooperation in competition & consumer policy. COMCO Swiss competition commission. CUTS Consumer Unity & Trust Society CPTPP Comprehensive and Progressive Agreement for Trans-Pacific Partnership. DoJ US Department of Justice (US antitrust watchdog, togetherwith USFTC) EAC East African Community. EACCA EAC Competition Authority. EC European Commission (EU’s competition authority). ECA Egyptian Competition Authority. ECOWAS Economic Community of West African States. 5 EEA European Economic Area. Includes EU member States plus Iceland, Lichtenstein and Noeway. ERCA ECOWAS Regional Competition Authority. ETLS ECOWAS Trade Liberalisation Scheme. EU European Union FTA Free Trade Association. ICT Information and Communication Technologies. INDECOPI Instituto Nacional de Defensa de la Competencia y de la Propiedad Intellectual (Peru’s competition authority). IPRs Intellectual Property Rights. JFTC Japan Fair Trade Commission (Japan’s CA). KCA Kenyan Competition Authority. KPPU Indonesia’s competition authority. GAFAM Google, Amazon, Facebook, Apple, Microsoft. LDC Lease Developed Countries. M&As Mergers and acquisitions; M&As, including takeovers and joint ventures result in “Concentrations”. MFN please see in Glossary MSME Micro, Small and Medium Enterprises OECD Organisation for Economic Cooperation and Development. OTCC Office of Trade Competition Commission (Thailand’s competition authority). PCW Price comparison website RPM Resale (or Retail) Price Maintenance. US DOJ US Department of Justice (US antitrust body). US FTC US Federal Trade Commission UNCTAD United Nations Conference on Trade and Development. SAARC South Asian Association for Regional Cooperation. 6 Abbreviations SADC Southern African Development Community. VCCA Vietnam Competition and Consumer Authority. WAEMU West African Economic and Monetary Union (UEMOA in French). 7 Glossary Algorithms : represent a sequence of logic Brokers: they bring buyers and sellers together commands executed very rapidly by a computer and facilitate transactions. Brokers play a frequent to carry out a given task, such as solving a role in business-to-business (B2B), business-to- mathematical problem. One can distinguish consumer (B2C), or consumer-to-consumer between ordinary, « non-learning algorithms » (C2C) markets. Usually a broker charges a fee or and « deep-learning algorithms » : (i) A « non- commission for each transaction it enables. The learning algorithm » is one where the user defines formula for fees can vary. Brokerage models the relevant parameters and the formula applied ; include: (ii) A « deep-learning algorithm », which is part of artificial intelligence (AI), is able to make Auction Broker : a platform that conducts decisions to a large extent independently from auctions for sellers (individuals or pre-set rules and parameters. merchants). The broker may charge the seller a listing fee and/or a commission as Artificial intelligence (AI) : The output which deep a share of the value of the transaction. learning algorithms produce over time can be Some brokers provide their services for hard to predict or steer even for those who have free, charging advertisers, the other side developed or implemented them. Not only are the of the platform (e.g. Amazon, Alibaba programs much faster and more efficient in subsidiary Taobao in China). identifying patterns and corresponding strategies than human brains, they can also find patterns a Transaction Broker : provides a third- human brain could not detect. Moreover, deep- party payment mechanism for buyers and learning algorithms may present themselves as sellers to settle a transaction (e.g. Pay Pal, “black boxes” the workings and interactions of ApplePay, TWINT, etc.) which are hard or impossible to decipher. Bundling can be either pure or mixed : Barriers to market entry : costs borne by a firm Pure bundling occurs when products are that seeks to enter a market, but is not borne by sold jointly in fixed proportions, while firms already in the market. mixed bundling (also referred to as multi- Black
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