Strong Network Effects Research Articles

Predatory pricing in platform markets: a modified test for firms within the scope of Article 3 of the DMA and super-dominant platform firms under Article 102 TFEU

ABSTRACT The paper examines predatory pricing in the context of two-sided digital platforms, arguing that traditional tests based on Average Variable Cost (AVC) may be inadequate for these markets. While predatory pricing by dominant firms is prohibited in both EU and US competition law, the current standards may not effectively capture predatory behavior in platform markets characterized by strong network effects and low marginal costs. The paper analyses cases where cross-subsidization between platform sides had predatory elements and resulted in findings of abuse of dominant position. Given platforms' unique characteristics, it proposes a modified test under Article 102 TFEU for super-dominant platforms and those within the scope of Article 3 of Digital Markets Act's scope. The proposal extends the Akzo test by presuming prices below Average Total Cost (ATC) to be abusive, rather than using AVC, with LRAIC as a proxy for ATC. This addresses the current test's limitations for low marginal cost businesses while allowing for objective justification.

The regulator’s trilemma: On the limits of technocratic governance in digital markets

Policymakers increasingly recognise the need for regulatory intervention in the digital economy to promote competition, privacy and innovation, among other policy objectives. Much policy-focused literature presents regulation as a technical puzzle to be ‘solved’ through identification of the appropriate intervention in a particular context, though there is persistent disagreement among experts about what remedies are preferable in different digital markets. At the same time, many external observers emphasise the sheer multiplicity of public policy objectives that regulatory interventions might fulfil, claiming that conflicts between these objectives are inevitable and thus require political rather than technocratic solutions. This article attempts to bridge the gap between these perspectives through a novel theoretical analysis of digital markets characterised by strong network effects, conceptualising different markets in terms of common underlying structural characteristics. The resulting framework helps policymakers to anticipate which remedies will safeguard competition, privacy and innovation/efficiency under what circumstances, both in well-established digital markets and with respect to emerging technologies such as artificial intelligence. In so doing, it also highlights limits to the technocratic governance of digital markets, identifying circumstances in which conflicts between competing public values cannot be neatly resolved through technocratic regulatory intervention alone.

From Intel & Qualcomm to the new Art. 102 TFEU-Guidelines – Streamlining the Form- & Effects Based Approach

Abstract Rapid digital innovation has promoted a broad range of welfare aspects and created a myriad of new business models. While these benefits are uncontentious, the special characteristics of digital markets, such as strong network effects, have led to a substantial concentration of power among a few corporate actors. The increasing complexity of these market dynamics has rendered antitrust enforcement more challenging, particularly with regard to assessing the abuse of market dominance (Art. 102 TFEU). Particularly the European Commission has been confronted with criticism relating to its previously propagated “more economic approach”, which has led to a lack of timely and effective antitrust enforcement. While there is a consensus that a new approach to ascertaining the abuse of dominance is pertinent – which the Commission endorses – the underlying assessment parameters are still contentious. This article argues for a standard of dominance to notably reflect the digital transformation and include a comprehensive framework. While the predominant intervention aim must be based on sufficient innovation, a notion of economic fairness and sustainability considerations gain momentum in antitrust enforcement.

Global climate change mitigation technology diffusion: A network perspective

There is a rapidly growing number of studies on transnational climate change mitigation technology (CCMT) diffusion. Most of these studies have adopted a bilateral perspective, treating countries as primary agents driving the diffusion process. However, CCMT diffusion typically arises from the interactions between firms and involves strong network effects. In this paper, we explore the global CCMT diffusion from a network perspective, with multinational corporations (MNCs) as network makers. We first propose a methodology to construct the global CCMT diffusion networks, leveraging CCMT-related patent data, intra-firm relationships, and business scales of the selected MNCs. We then calculate the network capital for each country, utilizing it as the input for the econometric analysis to investigate the network effects on CCMT development. The network statistical analysis reveals an uneven geographical distribution of network capital, underscoring the presence of global disparities in CCMT development. Moreover, the econometric analysis identifies significant network effects originating from linkage volumes and structural positionalities within the CCMT diffusion networks.

How Users Drive Value in Two-Sided Markets: Platform Designs That Matter

Extant research has popularized the perspective that strong network effects produce “winner-take-all” outcomes, which leads platforms to invest in user growth and encourages investors to subsidize these platforms. However, user growth does not necessarily imply strong user stickiness. Without user stickiness, strong network effects in the current period may fade in future periods, thus rendering a user growth strategy ineffective. By adding a time dimension to network effects, we developed a model of cross-period and within-period network effects to explain how different types of network effects drive value. We emphasize that the cross-period same-side network effect contributes to user stickiness, while the within-period cross-side network effect persists conditional on user stickiness. We propose that one reason for platforms having heterogeneous cross-period same-side network effects is because of the “product learning” mechanism: it is expected that products with higher uncertainty have a stronger cross-period same-side network effect. Based on different drivers, we extend the customer lifetime value model (CLV2) to two-sided platform markets, allowing us to measure how different interventions drive platform value. Using Groupon data, we verify our insights and discuss platform design choices that enhance user stickiness when the cross-period same-side network effect is weak.

How Users Drive Value in Two-sided Markets: Platform Designs that Matter

Extant research has popularized the perspective that strong network effects produce “winner-take-all” outcomes. This leads platforms to invest in user growth and encourages investors to subsidize them. However, without user stickiness, strong network effects in the current period may fade in future periods, so a user growth strategy is not effective. By adding a time dimension to the network effects, we develop a model of cross-period and within-period network effects to explain how different types of network effects drive value. We emphasize that the cross-period same-side network effect contributes to user stickiness while the within-period cross-side network effect persists to be conditional on user stickiness. We theorize that one reason platforms have heterogeneous cross-period same-side network effects is because of the product learning mechanism: products with higher uncertainty can expect a higher cross-period same-side network effect. Using Groupon data, we verify our theoretical insight and discuss platform design choices that enhance user stickiness when the cross-period same-side network effect is weak.

Content Quality Assurance on Media Platforms with User-Generated Content

This paper develops a duopoly model for user-generated content (UGC) platforms, which compete for consumers and content producers in two-sided markets characterized by network externalities. Each platform has the option to invest in a content quality assurance (CQA) system and determine the level of advertising. Our model reveals that network effects are pivotal in shaping the platforms’ optimal strategies and user behavior, specifically in terms of single vs. multi-homing. We find that when network effects for producers are weak, consumers tend to engage in multi-homing while producers prefer single-homing. Conversely, strong network effects lead to the opposite behavior. Furthermore, our model demonstrates that user behavior and network effects dictate whether a platform is incentivized to incorporate advertisements and/or invest in CQA. Generally, weak network effects prompt a platform to invest in a CQA system, unless both consumers and producers engage in multi-homing. Our model’s results highlight the importance for platform companies to evaluate the extent of network effects on their platform in order to anticipate user behavior, which subsequently informs the optimal CQA and advertising strategy.

The Achilles heel of interconnected user networks: Network firms and the vulnerability of rapid decline

Digital technologies have amplified firms' ability to gain and sustain competitive advantages by leveraging network effects and large user bases. They allow cheaper and better building, scaling, and operation of user networks, more efficient data collection, lower transaction costs, and ever-stronger scale advantages. Yet, the seemingly stable competitive advantage of large-scale user networks may have an “Achilles heel” that creates a strategic vulnerability. We examine this overlooked effect by studying how structural network characteristics affect the risk of rapid decline after users start to depart. We find that for user networks with small-world and scale-free properties, the departure of a few influential users can prompt strong negative network effects and accelerate the speed of a decline. To arrive at these insights, we use an analytical approach inspired by the computational networks literature to assess the impact of different structural characteristics on the likelihood of rapid collapse. Our research enriches the platform and network literature by providing fresh insights into the vulnerabilities of interconnected user networks, highlighting the risk of rapid decline. We also suggest practical implications for firms that depend on such networks for a competitive edge.

Quality Strategies in Network Markets

This paper studies network market problems in which firm(s)/platform(s) sets quality in addition to price. A well-established result in the network economics literature is that a profit-maximizing firm concerns only how quality is valued by the marginal consumer but not by inframarginal consumers, aka the Spence effect/distortion. For markets with strong network effects under which multiple market-tipping equilibria exist, I show that the validity of the previous result depends on the choice of the equilibrium selection criterion. Precisely, I show that all criteria commonly used in this literature give rise to the Spence effect, whereas the well-justified risk dominance criterion in game theory and its generalizations do not. Novel quality strategies are derived based on the latter criteria. This paper was accepted by Joshua Gans, business strategy.

Co-Opetitive Strategy Optimization for Online Video Platforms with Multi-Homing Subscribers and Advertisers

In the two-sided market for online streaming content, the platform’s co-opetitive strategy has been wildly discussed, where the platforms cooperate in sharing the broadcasting right of content and meanwhile compete for both subscribers and advertisers. Although platform co-opetition in practice can be easily captured, the impacts of cross-side network effects on pricing strategy are contingent upon the participation decision of both sides, including single-homing and multi-homing. Therefore, we examine the optimal co-opetitive strategy of duopoly platforms using a Hotelling model to capture user behaviors and investigate the equilibriums of pricing decisions and profits in three scenarios: single-single, multi-single, and multi-multi. The main findings are: (1) Advertisers choose multi-homing only when subscribers are also multi-homing, and the broadcasting cost is relatively low. (2) With single-homing advertisers, the primary broadcasting platform earns more profit than the re-broadcasting one. (3) With multi-homing advertisers, the primary broadcasting platform’s profit increases with the broadcasting rights cost. (4) Platforms should focus on building strong cross-side network effects with multi-homing advertisers. Alternatively, they would be better off contracting with single-homing advertisers if the effects are relatively low.

From monocle to spectacles: competition for data and “data ecosystem building”

ABSTRACT “Data ecosystem” companies on the digital market are unique in that they attain market power through their combination of personal data across many markets. Due to strong network effects of personal data, exploited on a conglomerate level, competition has moved beyond competition on the market and even beyond competition for the market: there is now competition for data. Consequently, we must reconsider not only the traditional concept of market power and market definition, but even the competitive analysis of alleged abuses. Therefore, the Commission’s singular focus on anti-competitive foreclosure does not do justice to the complex competitive effects of data ecosystems’ conduct. Only by fundamentally integrating competitive assessment with personal data protection can we understand data ecosystems and their role in the digital landscape. In order to fully capture the anti-competitive effects and harm done to consumer welfare, we must consider “data ecosystem building” as its own theory of harm.

Комплексное влияние сетевых эффектов, критической массы и стандартизации на конкуренцию на рынке операционных систем

The competition policy mechanisms in specific sectors of the economy work out, provided that balanced protection tools are used, and incentives are maintained to launch a new product or technology onto the market. However, strong network effects lead to the presence of a small number of manufacturers or even a single player, which hinders the spread of alternative products and contributes to a single product network formation. The relevance of this research is driven by the need to competition analysis in the software market affected by the network effects. The purpose of this review article is to justify the need for a compound impact analysis of network effects, critical mass and standardization as an assessment optimization tool of the competition state in the two- sided software market, specifically in the operating systems markets. The object of the research is an operating system itself, and the subject is the influence of network effects, critical mass and standardization on competitive processes in the operating systems market. The following issues were performed: the results systematization of theoretical studies and approaches to econometric modeling of network externalities, the strategies identification for analysis of standards and installed base of users and sales, introduction of the operating system and software concepts, the development of recommendations for analysis of the phenomenon of network effects with an emphasis on the standardization process in the furtherance of competition and industrial policy. Analysis of the examined phenomena impact shows that the introduction of a generally accepted network effects definition at the legislative level, distinction between the direct and indirect network effects, consideration of this phenomenon as a barrier to entry into the market, and concord of the network effects and standard setting theory can decrease the possibility of type I and II errors in the law enforcement practice.

Mechanisms for Business Ecosystem Members to Capture Value through the Strong Network Effect

Business ecosystem leaders tend to focus on their own success rather than carefully monitoring the success of business ecosystem members, and each member must find a mechanism to capture value. Rarely has business ecosystem research examined the success of business ecosystem members. This study investigates the mechanisms by which business ecosystem members capture value in the business ecosystem related to different types of storage formats and how these mechanisms contribute to the sustainability of the business ecosystem. We identify two value capture mechanisms in the storage business ecosystem. First, media manufacturers, being members of the storage business ecosystem, can capture value through strong network effect in the server backup markets. They can sell a significant amount of media for every single unit of a drive sold through the strong network effect. Second, media manufacturers can capture value by selling their media repeatedly as consumables for many years. We quantitatively confirm these mechanisms using a vector autoregressive model to measure the strength of the indirect network effect. These mechanisms help business ecosystem members in staying within the business ecosystem and also contribute to the business ecosystem’s sustainability.

Investigating the Influence of Network Effects on the Mechanism of Disruptive Innovation

Disruptive technology theory receives a lot of attention and has a significant influence on scholars and managers in approaching technology competition. Some studies have formalized the disruptive technology, investigating the mechanism and determinants of disruption. While some modern technologies are understood to be disruptive, they also exhibit increasing return to the adoption properties or network effects. However, how the network effects influence the disruption mechanism has only received little attention in the previous formal disruptive technology models. Therefore, in this study, we developed a formal model to investigate the dynamics of disruption by exploring the interaction of technology development, the consumer’s choice, firm’s decision, and structure of demand under the influence of different degrees of network effects. The model is simulated using agent-based software of the Laboratory for Simulation Development (LSD). We argue that weak network effects allow for different competitive outcomes (i.e., competitive isolation, convergence, and disruption), where the heterogeneity of the consumers’ preferences matters in determining the outcomes. Therefore, this study suggests that weak network effects enhance the likelihood of disruptive innovation, depending on the heterogeneity in customer preference. Strong network effects, however, lead to a winner-takes-all situation regardless of the heterogeneity in the consumers’ preferences.

Technology Strategy and Competition Track: Thinking Strategically about Network Effects

Many, highly valuable firms such as Alibaba, Alphabet, Amazon, Apple, Meta, and Tencent owe parts of their success to network effects. Therefore, it is unsurprising that scholars have been studying network effects and their implications for decades. However, we still know surprisingly little about (1) how to measure network effects, (2) the implications for firms trying to actively induce network effects, and (3) the competition under heterogeneous network effects. The goal of this symposium is to highlight research that deals with these issues. All four presenters illustrate novel ways to measure the strength of network effects and show how these network effects affect value creation and/or firm performance. Results show that network effects are by no means a panacea for firms as (1) they might be too weak to justify a costly merger, (2) they negatively affect firm performance when paired with incompatible strategies, (3) their strength critically depends on heterogeneous user characteristics, and (4) strong within-period network effects are not enough to achieve a dominant market position without consistently strong inter-period network effects. The four presentations will be followed by a discussion that aims to identify common themes and fruitful avenues for future research on network effects. Dog Eat Dog: Balancing Network Effects and Differentiation in a Digital Platform Merger Presenter: Chiara Farronato; Harvard Business School Network Effects by Choice: A Demand-Side Perspective on Adoption Performance for Board Games Presenter: Joe N. Ploog; UCL School of Management Online Communities on Competing Platforms: Evidence from Game Wikis Presenter: Tobias Kretschmer; LMU Munich How Users Drive Value in Two-sided Markets: Platform Designs That Matter Presenter: Marshall Van Alstyne; Boston U.

The U.S. Bioeconomy: Charting a Course for a Resilient and Competitive Future

The U.S. Bioeconomy: Charting a Course for a Resilient and Competitive Future

Competing on freemium: Digital competition with network effects

AbstractResearch Summary“Freemium” product strategies—where a free basic version of a product is offered alongside a full “premium” paid version—are often used by companies to attempt to increase the size of their user base and benefit from network effects. However, there is limited empirical evidence of how using freemium strategies impacts firm revenues. We empirically investigate how the strengthening of network effects on the Apple App Store influenced product sales of firms using freemium strategies, contrasting the impacts on both market leaders and followers. We find that stronger network effects did not on their own lead to greater revenues for market leaders with respect to followers. However, in settings where freemium strategies were used, network effects greatly amplified the advantage of leaders over followers.Managerial SummaryFreemium strategies are increasingly common as a way for firms to increase the number of users and benefit from network effects. However, there has not been much empirical investigation in this regard, particularly in cases where products using freemium strategies face competition. In this article, we investigate how a policy by Apple on the App Store that led to stronger network effects, impacted the performance of market leaders and followers depending on whether they used freemium or not. We find that it led to an increase in revenues of leaders over followers (effectively, market dominance) but only when freemium strategies were used. The analysis demonstrates an interplay the between business model and network effects. In addition, it shows how stronger network effects and freemium strategies only benefitted market leaders in our setting.

Social networks and internal migration in China: A spatial autoregressive model

AbstractIndividual decisions such as migration can be influenced by different types of social networks. This paper examines strong and weak network effects on internal migration in China by distinguishing between first‐time migrants and experienced migrants. Strong networks are constructed by household members, while weak networks are determined by the village in which the individual resides. By employing spatial econometrics tools, we show that strong networks have a significant positive effect on the first‐time migration decision, while weak network effects vary across home provinces and are significant and positive only for some provinces. We also classify the sample to explore the network effects within the household and find that the effects are larger among siblings, especially among siblings of the same gender. In contrast, strong networks have a smaller impact, and weak networks appear to encourage migration after people have migration experience. Similar findings also apply to the choice of destination, months worked away from home, and migration earnings.

Platform mergers and antitrust

Abstract Should internet era merger policy differ from industrial era merger policy? Platform ecosystems rely on economies of scale, data-driven economies of scope, high-quality algorithmic systems, and strong network effects that frequently promote winner-take-most markets. Their market dominance has generated competition concerns that appear difficult to assess with traditional merger policy tools. This paper examines the acquisition strategies of the five major U.S. platforms—Google, Amazon, Facebook, Apple, and Microsoft—since their inception. We discuss the main merger and acquisition theories of harm and how these operate differently than in the past. To address merger and acquisition concerns of multi-sided platforms, we develop four proposals that incorporate (i) a new ex ante regulatory framework, (ii) an update of the conditions under which the notification of mergers should be compulsory and the burden of proof should be reversed, (iii) differential regulatory priorities in investigating horizontal versus vertical acquisitions, and (iv) an update of competition enforcement tools to increase visibility into market data and trends.

BIG DATA AND DIGITAL MARKETS CONTESTABILITY: THEORY OF HARM AND DATA ACCESS REMEDIES

Abstract This article analyses the crucial role of user data for digital markets contestability and presents policy proposals devised to address growing concerns about the dominance of data-rich incumbents in digital markets. To this end, we discuss a data-driven theory of harm that would warrant ex-ante data access regulation and highlight that niche entry and growth should be the primary economic policy objective in digital markets characterized by strong data-driven network effects. We then evaluate regulatory data access remedies with respect to the involved economic trade-offs and their effectiveness for promoting niche entry and growth. Firstly, we analyse remedies that would limit the collection of user data by data-rich incumbents such as data silos and line of business restrictions. Secondly, we consider remedies that facilitate sharing of (user) data by opening up access to raw behavioural user data collected by data-rich incumbents. In particular, we propose a dual approach with two complementary types of data access remedies: bulk sharing of broad anonymized raw user data and continuous, real-time data portability of deep raw data that contain personally identifiable information. Finally, we comment on the recent proposal for a Digital Markets Act by the European Commission with respect to our findings.