Market power,regulatory convergence,and the role of data in digital markets

The increased economic importance of digital services has profoundly changed the power structure in telecommunications and media markets. Although these services sometimes directly compete with traditional telecommunications services, the regulatory obligations for both players differ significantly. This article discusses three important areas deemed relevant in order to define a coherent regulatory framework and to account for the specific peculiarities of digital markets: First, challenges associated with assessing market power in digital markets. Second, challenges in harmonizing different regulatory obligations for digital services, and third, the vital role of data and data protection in the context of data-driven business models.     

欧盟《一般数据保护条例》对国际服务贸易规则的影响

为了保护隐私权,欧盟制定了《一般数据保护条例》(GDPR),保护个人数据和规范数据跨境流动是其两大目标。为了符合GDPR的要求,非欧盟企业客观上只有两种选择:要么撤出欧盟市场,要么将数据本地化,否则将面临巨额罚款。实际上,数据本地化构成了贸易壁垒,违反了《国际服务贸易总协定》第16和17条。为了促进数字贸易,以《全面与进步跨太平洋伙伴关系协定》(CPTPP)、《欧盟日本经济伙伴关系协定》(EPA)和《美墨加协定》(USMCA)为代表的新型区域贸易协定禁止数据中心本地化设置。为此,欧盟应设法消除任何数据本地化要求的可能性,同时应设法完善GDPR下的充分性决定机制。GDPR客观上对国际服务贸易规则产生了深远而广泛的影响。为了因应国际服务贸易规则的新发展,中国应引导与推动《服务贸易总协定》(GATS)的改进,加速构建促进个人信息保护、数据有序流动和保护公共利益相协调的新型数字贸易规则;借鉴欧盟与美国缔结的《隐私盾协议》,与欧盟开展有关数据跨境流动的双边协议谈判。     

The effect of privacy choice in cookie notices on consumers' perceived fairness of frequent price changes

Recent regulatory changes (i.e., General Data Protection Regulation of the European Union) enforce that seller (e.g., retail and service) and all other websites disclose through cookie notices which data they collect and store. At the same time, websites must allow consumers to disagree to the tracking of their browsing behavior. Despite sellers' concern about the loss of consumer insights—as consumers might disagree to the collection of their browsing data—cookie notices might also have a surprising side-effect: Consumers might accept frequent price changes (from personalized or dynamic pricing) more readily, if they agree through a cookie notice that their behavior can be tracked. Specifically, two experimental studies show that consent to the tracking of browsing behavior increases consumers internal attribution of a price change, as consumers attribute the cause of the change (here: giving up data) to themselves. This increases price fairness perceptions and, in turn, purchase intent. As a result, for online sellers of goods or services the implementation of cookie notice should no longer be thought as a matter to be avoided, but rather a trade-off decision: Loss of a part of consumer insights versus higher acceptance of data-driven marketing mix decisions, such as frequent price changes.     

Data portability effects on data-driven innovation of online platforms: Analyzing Spotify

The EU General Data Protection Regulation (GDPR) introduces a new right to data portability, which allows users to move their personal data to other platforms, potentially affecting competition between rival platforms offering similar (homogeneous/substitute) products or services within the European Union. However, it is still unclear what effects this new regulation could have on competition and, consequently, on innovation in digital markets. Therefore, this paper analyzes the effect of data portability driven by competition on the data-driven innovation response of online platforms such as Spotify, Google, and Facebook.We conduct an empirical analysis of Spotify, which is an online platform facing competition within the EU, and perform a comparison between data portability to number portability of the telecommunication sector to predict the future impact of the new regulation. Finally, we compare the observations on Spotify with Facebook and Google, which are companies in winner-takes-all markets.We argue that online platforms like Spotify, which face competition within the EU, will invest in two forms of data-driven innovation due to the effect of data portability. These types are ‘exploitation-innovation,’ by improving the existing technology, and ‘exploration-innovation’ by developing new technology. In ‘exploitation-innovation,’ firms, like Spotify, will increase investments in data-driven innovation to enhance users' engagement and retention to avoid churn. In ‘exploration-innovation,’ these firms will invest in data-driven innovation to develop new algorithms to include data from customers acquired from their competitors. On the contrary, online platforms, like Facebook or Google, which do not face real competition, will not have a substantial need to invest in data-driven innovation solely due to data portability.     

云计算和大数据时代的国家立法管辖权——数据本地化与数据全球化的大对抗？

欧洲一般数据保护规则为保障作为基本权利的个人数据,通过对领土原则和国籍原则在云计算和大数据背景下的再构建,赋予规则以广泛的适用范围。从国际法上的立法管辖权基础角度看,其表现出鲜明的数据本地化特征。规则不仅广泛规范域内数据处理,还严格限制数据向域外移送。欧盟数据本地化立法将产生怎样的影响,各国应如何应对,已经成为受到广泛关注的问题。作为云计算和大数据发达国家的美国,一方面通过与欧盟合作,确保数据能自由流通,同时又采取针对性立法,规定美国网络服务提供商有义务就其全球范围的数据依法保存和披露。这一立法尽管局限于执法机关对数据的管控和利用,但却基于数据全球化的现实,明确规定了域外适用。立法管辖权冲突也因此揭开了新的一幕。     

Marketing analytics using anonymized and fragmented tracking data

With the digitization of the retail industry, there is a growing abundance of event-based tracking data describing consumer behavior (e.g., online clickstreams and offline sensors tracking the movement of shoppers). However, stronger data privacy regulations and the growing privacy consciousness of consumers suggest that much of the data may increasingly only be available to retailers in an anonymized and fragmented form that does not identify individual consumers exactly. In response to the relative paucity of research on marketing analytics in retailing using anonymized and fragmented event-based (AFE) tracking data, this paper makes three interrelated contributions. First, we describe the relevance of AFE data in the future of retailing, contrasting it with other forms of aggregate and individual-level data. Second, we propose a methodology for analyzing AFE data, which allows us to approximately recover individual-level heterogeneity and derive meaningful variables from the raw data. Third, we validate the methodology using representative data collected by deploying sensor-enabled shelves in a field experiment within a store. We find that our approach to analyzing AFE data can help uncover interesting patterns of consumer behavior and could be applied across other online and offline retail settings in practice.