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COMPETING IN DIGITAL MARKETS: A PLATFORM-BASED 
PERSPECTIVE
Journal: Academy of Management Perspectives
Manuscript ID AMP-2016-0048.R4
Document Type: Article
Keywords:
Competitive dynamicsplatforms have incentives to respond with aggressive moves and counter-moves as 
mainstream research on competitive dynamics would suggest (e.g., Smith, Ferrier & Ndofor, 2001). 
Building on the awareness-motivation-capabilities framework (Chen 1996; Smith, Ferrier, & Ndofor 2001), 
research has long examined in traditional settings how competitors’ attributes, prior competitive 
interactions, and similarity in resources and customer markets influence the subjective intensity of rivalry 
and the actual competitive behavior. 
While this research in traditional contexts finds that firms with both high market commonality and resource 
similarity may tend to refrain from taking aggressive competitive actions towards competitors, recognizing 
their retaliation capacity (e.g., Chen 1996; Gimeno 1999; Ketchen et al. 2004), in the context of platform 
markets, in particular in the multisided transaction markets, intensity of platform competition will escalate. 
This scenario reflects the assumptions (i.e., platforms are homogenous in terms of users and technological 
attributes) that have been taken in most of the analytical models predicting the winner-take-all outcome 
(e.g., Armstrong 2006; Arthur 1989; Lee et al. 2006). Given that small differences may have big impact on 
the platform’s network size by influencing users’ expectations, and ultimately tip the market to one 
platform’s favor, platforms will tend to mimic each other moves on both the market network and technology 
design to avoid that their users migrate to the rival platform because of additional technological 
functionalities or content/complements. Because platforms are closely interdependent in this case, and a 
competitive move by the rival platform can damage the network size and strength, and thus the competitive 
standing of the focal platform very rapidly (e.g., Arthur 1989; Katz and Shapiro 1994), platforms with high 
identity domain overlap will have strong incentives to take aggressive competitive actions to grow faster and 
bigger their network, at the expense of their direct rivals. Accordingly, platform providers are more likely to 
engage in a series of competitive moves-countermoves to lure rival’s users through aggressive “get-big-fast” 
strategies, including platform envelopment (Eisenmann et al. 2011), user subsidizing (e.g., Clements & 
Ohashi 2005; Hagiu 2005), and exclusivity licensing to lock-in their users/complementors and make hard for 
them to “multi-home” – i.e., to participate in multiple platforms (Cennamo & Santaló 2013; Corts & 
Lederman 2009). This leads to high intensity of platform competition and escalation into winner-take-all 
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battles, particularly so in transaction markets where network size is the most critical source of platform 
value. In a simulation analysis, Lee et al. (2006) assess the conditions under which these strategies can be 
effective and lead to a winner-take-all outcome, where the platform that gains larger market share at a given 
point in time will then capture the entire market. They find that this is more likely in the context where 
users’ choices are not affected by a small number of acquaintances, i.e., when the opportunity of interacting 
and transacting with a large number of complementors is more relevant and valuable to users than the 
interactions with the network of densely connected users. This is likely the case for transaction markets, 
where users derive value primarily from the greater number and variety of offerings available on the 
platform. We can thus expect rivalry and winner-take-all competition to be intense under high overlap 
between platforms in the identity competitive domain, and particularly so in transaction markets. 
High user commonality – low architecture similarity  asymmetric domain. Platforms with high user 
commonality but low architecture similarity can leverage heterogeneity in the platform architecture to build 
asymmetric competitive positioning in the market and build “spheres of influence” (Fuentelsaz & Gomez 
2006; Gimeno 1999) in their respective identity domain through distinctive positioning (e.g., Cennamo & 
Santaló 2013). This is more likely the case in innovation and information markets, and particularly so when 
competing platforms focus on distinct dimensions of platform value (one emphasizing size while the other 
emphasizing identity) (e.g., Cennamo & Santaló 2013; Seamans & Zhu 2014). 
Instead of trying to be everything to everyone and compete directly with rival platforms to win the entire 
market of users, in such markets, platforms can leverage distinct platform functionalities and capabilities to 
compete indirectly by selectively focusing on distinct market segments and building unique identity. 
Although platforms may share users to large degree and operate in the same market, they may perceive their 
competitive domain differently according to their distinct identity ensuing from their architecture 
dissimilarity. Research on competitive dynamics has advanced the idea that firms take competitive actions in 
some markets and react to rivals’ actions on the basis of their “identity domain” – the particularly salient 
“competitive arena that best demonstrates and reinforces organizational identity in the marketplace” 
(Livengood & Reger 2010: 48). Firms are likely to compete in many arenas; but not all of them carry the 
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same importance to the firm because they might not be part of the identity domain. Thus, a platform 
provider might not necessarily react to a competitor’s action, such as aggressive pricing, because that action 
might not be perceived as a threat to the platform’s competitive position in its identity domain. Accordingly, 
platforms with low architecture similarity focusing on distinct identity will be less likely to engage into 
intense head-to-head competitive battles for winning the entire market. This becomes clear within the 
awareness-motivation-capabilities understanding of interfirm rivalry (Chen 1996; Smith, Ferrier, & Ndofor 
2001). First, platforms building distinct identity might not share the same belief of what the relevant market 
is, even though they share to large extent the same users; they will form different identity domains and thus 
might have different competitive environments that are salient to them. As a consequence, they might be 
less aware of competitors’ actions outside the identity domain (Livengood & Reger 2010). Second, even if 
platforms monitor competitors in the broader competitive environment, they might hold more limited 
motivation to attack or react to competitive moves by rivals in the market, unless those moves directly threat 
the distinctive positioning of the platform in its own identity domain. Third, because platform firms commit 
to specific paths of platform development and evolution according to their distinct platform architecture 
(e.g., Cennamo et al. 2018), they might hold asymmetric resources and capabilities. As Livengood and 
Reger (2010: 54) advance, “increased awareness and motivation in the identity domain will increase the 
capabilities of the firm inside that domain and decrease its capabilities outside the identity domain. This 
occurs because the increased time and attention in the identity domain, combined with a motivation to act 
and react in that domain, will increase resource allocation to business operations in the identity domain”. 
Firms with dissimilar resource positions and capabilities have been shown to be lesslikely to engage in 
intense competition (Chen 1996; Smith et al. 2001). Platforms with distinct architecture might thus build 
dissimilar resources and capabilities that can constrain their capability to directly attack or respond to rivals 
in a market that is outside the platform’s own competitive identity domain. 
Consider for instance the competition between Apple and Google in the mobile OS platform market. While 
Google is pursuing aggressive openness and pricing strategies (both with vendors and users) with Android to 
be the dominant mobile OS platform in the marketplace, Apple is taking a different approach, its focus being 
on software-hardware-service integration experience for users. While they overlap in the same market for 
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end users of smartphones, their platform architecture is different, thus they see themselves as competing in 
different domains: Google wants to dominate the information search domain; Apple the user-platform 
interaction and consumption experience. They have thus developed different internal skills and capabilities 
(notoriously, Apple has stellar design team for unmatched user interface experience and software-hardware-
service integration; Google has unmatched capabilities and database in the search categorization domain); 
they have designed different platform architectures (Apple has a more tightly integrated architecture with 
greater screening process and quality control for external developers; Google is a completely open platform, 
both for external developers of apps and services and for developers of the OS platform itself); and they 
have gained a distinct positioning in the market (Bresnahan et al. 2014). Because of it, not only competitive 
actions taken in the market by one competitor may have more limited impact on the competitive positioning 
of the rival platform; it might be difficult for Google, for instance, to attack Apple in its own “home turf” 
because this would require drastic changes in the structural elements of the platform architecture and distinct 
platform firm’s capabilities and resources (e.g., OS and hardware design; internal development of OS 
platform; production of hardware devices; coordination of suppliers and complementors’ ecosystem…) that 
Google might lack.
Platforms with distinct identity can accordingly defend distinct competitive positioning in the market and 
secure a “sphere of influence” (i.e., a dominant position) (Gimeno, 1999) in their own identity competitive 
domain based on asymmetric competitive positioning. Because distinctiveness in technological capabilities 
and functionalities is structural and hard to modify, at least in the short term, this asymmetric competitive 
equilibrium can be sustained over time, particularly so in innovation and information markets. Platforms 
focusing on distinct identity will have limited incentives to directly attack platforms focusing on size in their 
domain12. In fact, as the example of eHarmoney vs. Match.com discussed earlier reveals, platforms focusing 
on distinctiveness may take actions in the opposite direction, increasing price and cost of access for users, 
and restricting participation by selecting out users. These actions, while reinforcing the competitive standing 
of eHarmoney in its own domain will not lure users and affect directly Match.com’s leadership in its 
domain; thus, these competitive actions will be less likely to trigger countermoves. Also, platforms focusing 
12 Note that because identity is difficult to change in the short term, identity can also hinder growth; platforms focusing on identity 
would be more constrained in terms of the get-big-fast strategic options that they could adopt to increase size of their network. 
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on identity and competitive distinctiveness will be less likely to directly attack competing platforms that 
focus on size because of important strategic tradeoffs between platform size and platform identity in these 
markets. Because of asymmetry in the strength of mutual attraction among groups of users (Halaburda & 
Oberholzer-Gee, 2014)13, engaging in head-to-head competition to enlarge the network of users at the 
expense of its rival can fail to deliver on its premises; yet, it will likely dilute platform identity and unique 
positioning in the market (Cennamo 2018). Platforms with high user commonality but low architecture 
similarity can accordingly sustain a successful asymmetric competitive position in the market and build 
spheres of influence in their identity domain (as in the case of Apple iOS vs. Android, or eHarmony vs. 
Match.com) based upon asymmetric network size and strength (Shankar & Bayus 2003; Suarez 2005), and 
asymmetric position in content/complements – i.e., content/complement distinctiveness (Cennamo & 
Santaló 2013) and user interaction strengths (Halaburda & Oberholzer-Gee, 2014). Intensity of competition 
can still be high because of platforms’ user commonality but, it will be of an indirect form given the more 
constrained capacity that direct aggressive moves have in undermining rivals’ competitive position. 
Low user commonality – high architectural similarity  contested domain. When platforms’ architectures 
are similar, but user commonality is low, initially platforms face limited direct competition. Despite them 
offering very similar technological capabilities and functionalities, they target distinct set of users and thus 
operate in separate end-user markets. However, because of their architecture similarity, both platforms have 
the capacity to target the rival’s user market by leveraging their functionalities across the distinct markets 
and enlarge their user network. Given these platform envelopment threats, platforms can have the 
motivation to anticipate the possible rival’s move and attack the competitor by entering its own market or 
some of its segments. One may expect that if one platform recognizes the envelopment opportunity in the 
neighboring market so does the competitor in the neighbor markets. As platforms expand their activities in 
multiple market segments, they become vulnerable to competitive attacks by other platforms operating in 
adjacent markets. 
13 Network effects may be asymmetric across users (Halaburda & Oberholzer-Gee, 2014), such that adding extra users to one side 
of the platform network may have limited impact on the size of the other network’s side (Seamans & Zhu, 2014).
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Consider the case of Airbnb vs. Booking.com. Albeit some differences in the user interface, they offer 
essentially very similar platform functionalities to users (searching for and booking an accommodation), but 
they initially focused on separate set of users with little market overlap; Booking.com focused exclusively 
on hotel offerings while Airbnb initially targeted users looking for shared rooms to rent for a bargain. As 
Airbnb started to add small bed and breakfast listings and premium houses to its offerings, Booking.com 
responded by introducing its house-rental service. Airbnb has since further retaliated by targeting more 
aggressively business travelers by introducing recently a number of targeted services such as Airbnb Plus 
(selected, premium apartments defined by Airbnb as “a selection of homes verified for quality and design”)and Instant Book (a feature that allows instant booking without messaging the potential host). It also 
recently acquired the boutique hotel booking platform HotelTonight, and expanded to multi-listings from 
professional hosts (including hotels!) that are growing faster since January 2016 than single listings from 
individual hosts, and account now for more than 32% of revenues generated in the platform14. This has led 
to increased convergence between the two hospitality markets, creating a highly contested competitive 
domain between the two platforms. 
In fact, multimarket contact (MMC) theory (e.g., Chen, 1996; Gimeno, 1999; Fuentelsaz, & Gomez 2006; 
Smith et al., 2001) suggests that firms’ competitive behavior is influenced by the higher interdependence 
between rivals derived from their mutual contacts in overlapping markets. With increasing multi-market 
contacts, rivalry may escalate fast until competitors establish mutual forbearance on the threat of mutual 
retaliation (Ketchen et al. 2004). As Jayachandran, Gimeno, & Varadarajan, (1999:60) advance in their 
theoretical analysis of MMC theory, “before mutual forbearance takes effect, firms may extend their product 
lines and enter different markets”. However, in contrast to traditional markets (with clear-cut boundaries) 
where competitors might refrain from aggressive strategies because of the threat of retaliation in their own 
leading market, in the case of platform competition leading to contested domains, we might expect platforms 
to compete increasingly in multiple overlapping market segments not only to build capacity to forbear tough 
competition in their ‘home’ market, but also to create more value for their users and build a strong position 
in the new, aggregate market resulting from market convergence. Hence, platform envelopment may be both 
14 Data source: AirDNA (https://qz.com/quartzy/1574182/ahead-of-its-ipo-what-even-is-airbnb-anymore/); last accessed: March 
2019.
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https://qz.com/quartzy/1574182/ahead-of-its-ipo-what-even-is-airbnb-anymore/
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a function of innovation capability of the platform firm in response to a value proposition for consumers, 
reinforcing platform identity across different markets, and of multimarket competition in response to actual 
or anticipated rivals’ moves that might threaten the platform leadership in the converging market. Thus, the 
competitive domain becomes highly contested through increased platform envelopment. Platforms will more 
likely engage in intensive winner-take-all battles across domains, which can eventually escalate into direct 
winner-take-all competition over the new, re-defined domain (as in the case of Airbnb and Booking.com). 
This might be more likely the case in transaction markets, where platform envelopment threats and small 
differences between platforms that may derive from aggressive get-big-fast strategies may have drastic 
effects on a platform market performance (Arthur, 1989; Katz & Shapiro, 1994; Lee et al. 2006). In these 
contested domains, with competition escalating, a risk for platforms enveloping across markets is of 
possibly diluted platform identity, which can lower platform value and alienate customers (as we explain 
later when discussing platform evolution). 
Low user commonality – low architecture similarity  separate domain. Platforms with low user 
commonality and low architecture similarity address distinct sets of users through distinct sets of 
technological functionalities; accordingly, they operate in separate platform markets with limited 
interdependence or possibility of complementarities across users or across platform functionalities. In such 
cases, platforms compete in distinct competitive identity domains and are less likely to engage in direct 
competition, independently of their strategic focus and type of market they operate in. 
Consider the case of eBay vs. Amazon Marketplace. They operate in transaction markets and focus on size 
as primary source of value; thus, they will tend to compete through winner-take-all logic in their competitive 
domain. One would accordingly predict high intensity of competition between the two. However, despite 
winner-take-all being the dominant logic of competition in these markets, we observe very limited rivalry 
between these two platforms. In fact, the two may compete in separate competitive domains due to their low 
architecture similarity and user commonality. Amazon Marketplace and eBay platforms offer diverse 
functionalities and technological features (such as e.g., Amazon’s 1-click payment, Amazon Prime vs. eBay 
auction system) that have contributed to form unique consumption experience on each of the platforms and 
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cater to users and sellers with different needs and preferences. While eBay, through its auction-based 
transaction system, caters to consumers (and sellers) that are willing to trade the longer time and effort it 
takes (to bid for the product) to complete a transaction in the platform for a bargain deal, Amazon positions 
itself to address the needs of users that want to buy and receive the item quickly and effortlessly. To the 
extent these users do not overlap but constitute different type of users, and thus separate markets, both 
platforms may coexist, each as the dominant platform in the respective market and competitive domain. 
Because they built distinctive structural elements in their platform architecture that are hard to replicate by 
the competitor, at least in the short period, the capacity of platforms to directly attack each other and lure 
rivals’ users is more constrained. While (some) sellers may multi-home on both platforms – i.e., may 
affiliate and sell through both platforms – to reach out to the distinct type of consumers, end-users in 
different market segments and with different preferences will tend to affiliate with one of the two platforms 
(they single-home), according to their preferences (Bresnahan et al. 2014; Corts & Lederman 2009). And 
because of the heterogeneity of preferences of users for the different platform functionalities, aggressive 
competitive moves such as platform envelopment across the markets have limited upsides. Accordingly, 
platform envelopment threats are low, so is the intensity of competition. 
Taken together, framework’s predictions imply that, generally, in transaction markets most of the value is 
linked to the network size, and we can expect intense platform competition dominated by a winner-take-all 
logic. The more platforms overlap in terms of users and the more similar their architecture, the higher their 
rivalry and thus intensity of platform competition. In innovation and information markets, platforms can 
emphasize their unique identity to larger extent to differentiate themselves in the market and avoid platform 
competition escalation. In this sense, platforms may take actions not in direct response to rivals’ moves but 
to reinforce their positioning in their own identity domain; “indirect” competition can arise between rivals 
based on asymmetric competitive logics (winner-take-all vs. distinctiveness). As platform competition plays 
out, its effects on platform performance and market structure will in turn influence the drivers of competitive 
rivalry by reinforcing or contesting platform identity competitive domain and platform value; platform 
competition will then evolve into new cycles. 
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Platform competition’s evolution and strategic tradeoffs 
Platforms evolve over time as a result of the actions they take to continuously create greater value for their 
users and to respond to platform competition. Their strategic positioning at a given point in time would 
reflect this evolution and might thus differ across time. Also, platform envelopment and competitive 
dynamics can lead to the shifting of the competitive domain and redefinition of the market boundaries; 
platforms may soon find themselves competing into a larger market domain resulting from convergence of 
previously separate, adjacent markets (e.g., Visnjic and Cennamo 2013). For example, starting from the 
media content interface such as iTunes, Apple made inroads for music-based social media, such as Ping. 
Moving in the other direction, Facebook has partnered with music platform Spotify to connect Facebook 
friends using the popular music platform. With the competitive domain shifting due to platform competition 
dynamics, prioritizing the defense and continuation of a firm’s identity may result in managerial myopia 
towards threats originating from outside the identity domain15 (Livengood & Reger 2010). The case of 
Nokia dismissing the threat of Apple iOS platform to its Symbian platform’s leadership position in the 
smartphone market is a notorious example of this risk16. Platforms should continuously scan their 
competitive environment and evolve their strategic focus accordingly, giving different emphasis to platform 
value dimensions depending on the market stage and intensity of competition. 
Facebook started by focusing on distinctive elements of the technology (communication and social 
interactions by sharing and commenting on pictures) and market scope (serving only the students’ 
community) to differentiate from the dominant social network at the time, MySpace. Once it gained a 
unique identity in the market, it started widening its scope but without diluting its core identity. This is why, 
for instance, in 2008 Facebook introduced new rules that put restrictions on the amount of information a 
content/app provider could send out to users, with the ultimate goal of limiting the occasions of users being 
15 Ozalp et al. (2018) show how a platform technological architecture may become obsolete in the light of rivals’ redesign actions 
of enhanced architecture, in which case complementors can migrate to the new platform despite the existing platform size of the 
incumbent platform. Similarly, Zhu and Iansiti (2012) show that platforms may challenge an incumbent platform’s leadership 
through competitive actions taken on the design of the technological architecture meant to curb a unique identity through 
enhanced capacity to facilitate innovation of complementors, and of higher quality.
16 Although it pioneered the smartphone segment with its Symbian platform, its focus was on devices. Apple instead entered the 
smartphone segment with a clear focus on hardware-software integration, purposely prioritizing its devices’ user interface and 
data computing capabilities over the phone’s voice capabilities. Nokia continued to see Symbian as a platform to augment the 
phone’s voice communication capabilities for the premium users in the original, existing phone market segments, failing to 
recognize the threat of Apple iOS (and later Google’s Android) platform in the new, contested competitive domain of smartphone 
market.
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exposed to information not relevant or even disturbing to them (Claussen et al., 2013). Although this 
restrictive policy could have affected negatively the amount of content produced and shared by providers, 
Claussen and colleagues (2013) find that it did increase the incentives for producing more engaging apps; 
the users’ ratings of apps increased indeed after the implementation of the rule change. In contrast, MySpace 
was not able to evolve without diluting its identity. Responding to Facebook competition, MySpace 
introduced tools to cater to the different preferences of its users and offer them customized content. At the 
same time, it maintained a platform open approach, allowing unfiltered content contributions and 
participation with the aim of reinforcing its platform size and market dominance position. With this hybrid 
approach, trying to be everything to everyone, MySpace ended up diluting the value of the platform for its 
users and being locked into an inferior technology; eventually, users increasingly migrated to competitor 
Facebook. This highlights the underlying tradeoff between quantity and quality of content for platforms 
operating in information markets (Johar et al. 2011)17, and, even more acute, for platforms in 
complementary innovation markets18 (Cennamo & Santaló, 2013; Cennamo, 2018). When assessing a 
platform’s value and the effects of platform competitive dynamics in a market, it is thus necessary to 
consider not just the strategic positioning of a platform at a given point in time, but its evolutionary 
competitive trajectory overtime. The shifts in emphasis and competitive positioning trajectory of a platform, 
with the ensuing tradeoffs, or what has been termed “platform traps” (Cennamo & Santaló 2015), can help 
to further explain why some platforms fail despite their size, and why other platforms succeed despite their 
relatively smaller market share. Groupon, the online coupon platform, experienced one of such platform 
traps. It started with a clear identity focus, promoting itself as a channel to discover new trendy restaurants 
and activities in town from select merchants, and thus offering “novel experiences” to customers. In the 
17 Johar et al. (2011), for instance, find that for peer-to-peer sharing platforms delivering general-purpose content (e.g., news 
stories, streamed movies…), as the number of users in the community increases, the network becomes more congested (in the 
form of delay, jitter and packet loss), which degrades the quality of service to users. Similarly, expanding an already large 
network of complementors may decrease the rate of innovation and increase the time to market of novel products for mobile app 
platforms (Boudreau 2012), and can also affect negatively the quality of the complements produced, with a negative impact on the 
market share performance of the platform (Cennamo 2018).
18 Similarly, Google started with a specific focus on the relevance of information to users, and time of response to users’ query as 
distinct elements of the service compared to other search engines. Purposely, it restricted the platform scope, and did not offer 
services and functions offered by information portals such as Yahoo! to excel in its “core” platform functionality, information 
search (Gawer & Cusumano, 2008). Because of its focus and the superior performance of the technology, Google’s search service 
gained wide adoption, and has now become the dominant search platform. But Google did not follow a winner-take-all logic; to 
the contrary, it pursued a differentiation logic by emphasizing specific, distinctive elements of its service, thus building platform 
identity; also, referred to as “coring” elsewhere (Gawer & Cusumano, 2008).
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pursuit of fast growth, it later took a hybrid approach, pursuing a dual strategy of simultaneously deep and 
wide content19, which proved detrimental for Groupon’s positioningand market identity (Cennamo & 
Santaló 2015), alienating both customers of high-end segments and merchants. This resulted into losses of 
market share and profits. The examples of Nokia, MySpace and Groupon indicate that, because of platform 
traps and path dependence related to platform identity, navigating successfully the platform evolution proves 
to be quite a complex task, particularly in the wake of emerging competition from new, rival platforms. 
Discussion and Directions for Future Research
As digitization of the economy becomes more prevalent, the critical challenge will be to develop a deeper 
understanding of the firms’ digital strategies, which requires an understanding of the changing nature of 
competition in digital markets, from standalone product offerings to platform-based interconnected products 
and services. While the economics’ theory of platform competition might offer a valid characterization of 
competition at the aggregate level of the market structure, it offers little management guidance as per the 
strategic choices and competitive dynamics beyond the “get big fast” prescription. In fact, it might be 
misleading in contexts where the identity elements of a platform matter more than its size. This leaves out 
some of the fundamental strategy questions such as, for instance, whether/how to earn differentiation 
advantage based on market positioning (e.g., Cennamo & Santaló, 2013; Seamans & Zhu, 2014) or the 
distinctiveness of the technological architecture (e.g., Cennamo et al. 2018; Schilling, 2003; Zhu & Iansiti, 
2012), and leaves us with limited managerial tools to understand, assess and guide the competitive position 
and performance of platforms. This paper is a first step in closing this gap; it integrates recent strategy and 
management research development on platform competition with insights from the competitive dynamic 
literature into a framework identifying the main strategic dimensions that shape platform competition. This 
approach offers several implications for future research.
An important research implication relates to the identification of configurational activities of the platform 
architecture and its ecosystem of external providers (e.g., Jacobides et al. 2018). We limited our focus here 
to few key “high-level” constructs of platform competition. A more detailed focus on each of these 
19 Groupon tried to be at the same time a generalist platform with global scale and reach, by offering a wide range and variety of 
content (which reflects a winner-take-all logic), and a platform offering high-quality and exclusive deals to high-end customers 
interested in using the platform to discover new trendy restaurants and activities in town (which reflects a differentiation logic).
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constructs is needed to understand how firms build value for their platforms. For instance, studies in the 
information systems area have advanced different perspectives on the design of platform technology 
architecture, and emphasized already some tradeoffs among configuration activities (e.g., Anderson et al., 
2014; Baldwin & Woodard 2009; Claussen et al. 2015; Tiwana et al. 2010) with important implications for 
the quality of complements produced and platform performance (Cennamo et al. 2018). Firms need to make 
choices about the extent of functionalities of the technology; more functionalities and processing power is 
often achieved at the cost of greater complexity of the system that can increase the development burden for 
external contributors and reduce the amount of complementary products and content produced for the 
platform (e.g., Anderson et al., 2014; Claussen et al., 2013). Platform owners may, in fact, purposely decide 
to “under power” their technologies to configure simpler systems or focus their effort on platform interfaces 
(such as APIs) (Anderson et al. 2014) and dedicated programs for innovators (such as innovation contests or 
startup acceleration programs) to elicit more engagement by external innovators. These choices must be 
assessed in relation to direct competitors’ architecture configuration (e.g., Cennamo et al. 2018). We still 
have limited knowledge about these activities and how they affect the specific elements of platform value, 
and ultimately the dimensions of platform competition. Extending those study findings and relating them to 
the strategic dimensions shaping platform competition could lead to insights on the processes of value 
creation in digital markets and how the one-time specific activities taken by firms to configure the platform 
architecture influence platform competition dynamics. 
Similarly, the governance of the ecosystem of external contributors is becoming an important decision point 
for platform owners to “orchestrate innovation” in the network (Nambisan & Sawhney, 2011) and the 
functioning of the market (Boudreau & Lakhani, 2009). Issues such as coordination of investments of firms’ 
interdependent product offerings (Adner & Kapoor, 2010; Jacobides et al., 2018), alignment of incentives 
for development of high-quality content and value capture tensions between platform and complementors 
(Cennamo, 2018; Gawer & Henderson, 2007; Tiwana et al., 2010), and balance between variety in the 
complementor network and community identity (Wareham et al., 2014) become central. This might explain 
the recent rise of platform cooperatives (e.g. Stocksy, Partago, Fairmondo) – platforms owned and governed 
by their complementors – which are emerging as more aligned structures that particularly emphasize the 
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identity dimension (Karanovic, Berends, & Engel, 2019). Future studies may extend knowledge in this 
domain to better understand the different orchestration processes that platform owners implement, how they 
differ compared to interfirm relationship governance, and how they affect platform competition. 
A related avenue for future studies is the relationship between the activities a firm must take to manage 
platform’s connections and user community, and the strength of network effects (e.g., McIntyre & 
Srinivasan 2017; Panico & Cennamo 2015) across its distinct sides of users and its platform identity. For 
platforms, particularly those leveraging peer-to-peer interactions and social connections, the user community 
is becoming a critical strategic asset. And to some extent it is part of the same service these platforms offer 
(connecting, sharing and interacting with the community). From peer reviews and recommendations, to the 
content shared or services provided by peers, trust in the community is, for instance, a propeller of the so-
called sharing economy. Community building and management are new capabilities that firms would 
increasingly need to develop to successfully compete in these markets. Studies in the field of marketing have 
long investigated the impact that a company’s user community can have on a company’s brand identity or 
product marketing success in traditional settings. Future studies may draw on findings from the marketing 
literature to identify established successful practices in this direction and understand how they relate to the 
platform identity dimension, and ultimately to platform competition. 
Similarly, we need to gain deeper knowledge about how factor-market rivalry affects in these markets a 
platform’s value and more generally, platform competition in the end-user market. In digital markets data 
and information are becoming critical resources for market success,and also a source of major concern at 
the societal level. As in the case of eHarmony, attracting the “right” user profiles affect the quality and 
relevance of information and thus the value of the platform and its distinct positioning in the end-user 
market. Also, in the case of Apple, securing superior inputs from suppliers (e.g., the 64 giga chip providing 
super computational power and unmatched graphics over rival platforms operating on a 32 giga CPU) and 
human capital (e.g., its super design team) affect the quality of its platform architecture, its complements, 
and the overall consumption experience. Google has entered the smartphone market with its mobile 
operating system Android primarily as a way to gain access to information data points generated by the large 
user base, which can then allow Google to power its other platform services, such as Google Map, Google 
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Search etc., with more relevant information. Controlling data and information, or better, the access point to 
and distribution of such resources can represent the new way to preempt rivals on critical resources and 
secure competitive advantage. While platforms might not compete directly in end-user markets, and thus 
have little platform market overlap, they can increasingly compete in these factor markets to gain privileged, 
“gatekeeper” positions over critical resources for platform value creation. Yet, we speculate, given the 
contested nature of digital markets, which are constantly being redefined through platform evolution and 
envelopment, it might be unlikely that one platform can secure dominant position in such factor markets 
over a long period of time. Recently, research has started investigating the circumstances and processes 
associated with factor-market rivalry (e.g., Capron & Chatain, 2009; Markman, Gianiodis & Buckholtz, 
2009); future studies could draw on this research to understand the differences in digital markets, and how 
competition in factor markets affects platform competition. More generally, we offer a framework to start 
assessing the unique aspects of competition in digital markets. Research on competitive dynamics should go 
beyond to examine explicitly some of the key assumptions of the theory that are challenged in digital 
markets such as the notion of the market or product competition, and identification of direct competitors. 
We see the definition of market boundaries in the context of digital markets as a central aspect that should 
stimulate inquiry in different areas, including antitrust policies. There is active and at times fierce debate 
among policy makers around the globe on how to regulate competition in digital markets and contrast 
dominance of platform providers. We sense that the difficulty to find convergence and effective policies 
relate to the difficulty of defining the relevant market to consider. The regulatory frameworks we have so far 
are designed with an assumption that competition is at the product-industry level, so markets are defined 
accordingly. The perspective we advance here implies that we should think differently about competition. 
Instead of looking at the market power that a firm might have at the product level in a given market, we 
might need to think about the architectural control that the firm might exert at the level of the sector or 
across multiple sectors through its platform (i.e., control over the rules of access to, production of, sell and 
consumption of complements/services within and across sectors). 
Another important direction for future research is the relation between platform configuration activities and 
competitive strategies and the (re)configuration of the firm’s business model. Research on business model 
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innovation (e.g., Amit & Zott, 2001; Massa et al. 2017) has gained increasing attention from scholars amid 
the mounting need of firms to innovate on the way they operate their businesses. Research has emphasized 
dynamic capabilities (Teece 2007), open innovation (Chesbrough & Appleyard 2007), business model 
design and reconfiguration (Massa et al. 2017) as critical for firms to successfully evolve their business 
model in dynamic sectors undergoing shifts in technology trajectories and the competitive landscape. Firms 
are increasingly called upon inventing new business models. While the digital has led to the creation of new 
business models in traditional sectors such as automotive, retail or hospitality, these have usually originated 
from startup companies. Many of the incumbent firms in such sectors can hardly replicate swiftly such new 
models, if not for other reasons but the simple fact that compared to platforms such as Airbnb or Uber, hotel 
and car manufacturers own directly the physical assets from which they extract rent. So, the burning 
question for incumbent firms is how to reconfigure their existing activity system and revenue model to 
leverage the firm’s key assets and capabilities in the light of platform competition. This might involve 
harder to implement choices as internal resistance to change due to organizational legacy is a real barrier to 
overcome even when managers may have the right vision. Companies such as Nike, BMW or GM show that 
“hybrid” models can in fact successfully operate. Nike has found a way to extend the value of its products 
by connecting third-party apps and other services through its Nike+ platform; BMW is repositioning in the 
marketplace as provider of premium cars and premium mobility services through its DriveNow car-sharing 
platform, which caters to needs of consumers (eg., young, students..) usually beyond the reach of the brand; 
and GM has been able to improve its profit margins largely thanks to its partnership with the car-sharing 
platform Lyft, moving from selling low-margin cars to extracting service fees from their use as Lyft’s fleet. 
Research on business model innovation examining how incumbent firms can react to disruptive forces and 
technologies by exploiting and integrating them into their existing operations holds tremendous potential to 
uncover firm-level dynamics that influence the dimensions of platform competition, and might offer strong 
practical implications for managers undergoing these shifts in the competitive landscape. 
In conclusion, this paper has extended the discussion of digital markets and the shifting competitive 
landscape by adopting a platform competition perspective and offering a framework for the analysis of the 
key strategic dimensions and competitive logics shaping competition in these markets. We believe such 
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approach opens to numerous avenues for future research in this area and holds potential to reveal far more 
insights about the strategic mechanisms at play, and highly enrich our understanding of competitive 
dynamics in such markets, and the extent to which they differ from more traditional competitive landscapes. 
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West J., & Wood D. 2013. Evolving an open ecosystem: The rise and fall of the Symbian platform. Advances in 
Strategic Management, 30: 27-67.
Yoo Y, Henfridsson O, Lyytinen K (2010) Research commentary-The new organizing logic of digital innovation: 
An agenda for information systems research. Information Systems Research 21(4):724–735.
Zhu F, & Iansiti M. 2012. Entry into platform-based markets. Strategic Management Journal 33(1): 88-106.
Carmelo Cennamo (cce.si@cbs.dk) is professor in the strategy and innovation department at Copenhagen 
Business School, Denmark, and fellow of the DEVO Lab (Digital Enterprise Value and Organization) at 
SDA Bocconi, Italy. His main research interests center on competition in platform markets, management of 
platform ecosystems, platform-based disruption and digital transformation.
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Table 1. Competition in digital vs. traditional markets
Traditional markets Digital markets
Competition level Product/firm/industry: competition is between 
products/firms in a given market/industry
Platform system: competition is between platform 
markets
Competition driver Firm competitive position/rent protection Value creation for platform users
Competitive analysis’ focus Inter-firm rivalry driving firm performance Network effects and platform competition driving 
platform performance and market structure
Competitive actions Market entry in rival’s markets; 
Aggressive product pricing; 
New product(s) launch(es);
Firm acquisitions;
Platform users subsidizing (two-sided pricing structure); 
Platform openness vs. restricted access; 
Platform envelopment; 
Platform exclusivity affiliation (single-homing); 
Content/complement exclusivity (distinct 
content/complements)
Competitive dynamics Move-counter move;
Multimarket competition; 
Mutual forbearance;
Platform competition;
Platform single- vs. multi-homing;
Platform envelopment; 
Platform dominance - winner take all;
Competitive advantage (sources) Monopolistic rents in the market; 
Barriers to competition;
Control over (platform) market architecture; 
Platform size - indirect network effects;
Platform identity & distinctiveness - unique platform 
attributes and user’s superior consumption experience;
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Table 2. Digital Markets
Multi-sided Transaction Market Complementary Innovation Market Information Market
Platforms are (digital) market infrastructures connecting 
directly sellers and buyers, and facilitating value-
exchange transactions among them
 End-users benefits: access to variety of offerings 
 Complementors (sellers) benefits: access to 
potentially wide market of platform users 
 Additional infrastructure tools (e.g. payment 
systems, feedback and rating systems, matching 
tools and shipping facilities) help reinforce platform 
benefits
Platformsare innovation engines providing the core 
technological architecture other firms build upon to create 
complementary products/services
 End-users benefits: access to a system of 
interconnected products providing an integrated 
solution to their needs
 Complementors (external innovators) benefits: 
modularised division of innovation tasks and labor; 
grater returns from specialization because of 
complementarity 
 A platform-based ecosystem can arise as new form to 
organise complementarity of complementors’ 
interconnected innovations
 Additional market infrastructures typical of 
marketplace platforms can be combined to facilitate 
also direct transactions between users and providers 
of complementary innovations 
Platforms are information channeling infrastructures that 
enable the categorisation, search and sharing of relevant 
information, facilitating users’ exchange of information 
and matching 
 End-users benefits: access to wide information, 
filtered according to relevance to the user
 Complementors (providers of information) benefits: 
facilitate sharing of information with large user base, 
and engagement of interactions
 Matching users on the basis of information they care 
the most
Platform exemplars:
- E-commerce platforms facilitating direct, complete 
transactions between buyers and sellers (e.g. 
Amazon Marketplace, eBay…)
- Ride-hailing platforms e.g. MyTaxi, Uber or Lift 
(matching demand for rides from users with 
different preferences (for pricing, waiting time etc..) 
with supply of riding services)
Platform exemplars:
- Mobile system platforms (e.g., Apple iOS and 
Android, which combine also market infrastructures 
such as the Apple’s AppStore and Google Play)
- Computing platforms (e.g., SAP NetWeaver enabling 
custom development of business solution 
applications)
Platform exemplars:
- Search engine platforms (e.g., Google Search, Bing…)
- Social/media platforms enabling interactions on the 
basis of exchange of relevant information (e.g., 
Twitter, Facebook, LinkedIn…)
- Peer-to-peer travel information platforms leveraging 
user-generated content to collect and provide relevant 
information (e.g., TripAdvisor, …)
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- Group-buying platforms connecting their users with 
local merchants offering activities, goods and 
services (e.g. Groupon; Meituan…) 
- Data-product platforms (e.g., Nike+ enabling external 
developers’ creation of digital products and services 
using Nike’s user data)
- Dating service platforms (e.g., Match.com, 
eHarmony,…) 
Table 3. Platform Competition
Platform competition type Competitive objective Competitive domain 
of interest Competitive actions Mechanisms
Winner-Take-All Gain market dominance 
through platform size
Entire market within core 
domain + adjacent markets
- Envelopment
- User subsidizing 
- Platform openness 
- Exclusivity access 
licensing
- Enhanced market 
coordination
- Enhanced 
transactions/interactions 
opportunities 
- Reduced costs of 
platform 
affiliation/development
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Distinctiveness
Gain unique market identity 
through distinctive 
technological capabilities 
and market scope
Market segments within 
core domain (& adjacent 
markets) coherent with 
platform identity
- Platform restricted 
access (screening)
- Selective access pricing
- Content/complement 
exclusivity 
- Platform scope 
restricting
- Enhanced market 
participants selection 
- Enhanced usage 
experience 
(content/complement 
curation) 
- Induced non-negligible 
costs of platform 
affiliation/development 
(alignment of 
participants’ interests)
Figure 1. The Core Elements of Platform Value
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Figure 2. Platform-based Competitive Analysis Framework
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Figure 3. Platform Competitive Identity Domain Analysis
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60of the business compared to peers in their primary industry (Lacy et 
al., 2016).
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similar products, and targeting similar customers” (Chen 96:104). Platform competition instead is between 
markets (Rochet & Tirole 2003). Because the products that are built on or sold through the platform are 
varied and not constrained to a given sector, platform market boundaries span across multiple (traditionally 
defined) product markets and even sectors. Treating each of these product-market segments as separate 
markets would miss the key point of digital markets: increased inter-connectedness and interdependence 
across multiple products across various markets and sectors that can form an integrated product system for 
the final customer. The concept of platforms, and in particular two-sided markets (Caillaud & Jullien 2003; 
Rochet & Tirole 2003) emerging around platforms, capture this level of aggregation and interdependence. 
Also, in the received theory of competition, markets are treated as given; firms just happen to compete 
within well-defined markets, taking the market structure as fixed. Accordingly, competition is generally 
conceived as a zero-sum game (Priem 2007); the focus is on how competitive actions (moves-
countermoves) between rival firms affect their ability to capture larger part of the total value available in a 
given market. Instead, platform competition shifts the emphasis on value creation – how to create greater 
consumption benefits for the customer through ever-expanding consumption options. In doing so, platforms 
are changing the shape of the markets in their quest to enlarge the pie for everyone (Panico & Cennamo 
2015). Thus, the underlying drivers of competitive behavior across rival platform providers may also differ. 
For instance, platform providers may take competitive actions to create more value for their users, even 
when these moves may trigger competitive retaliation from rivals; this is in contrast with the findings of 
competitive behavior in traditional settings (see Ketchen et al. 2004 for a comprehensive review of the 
literature). Table 1 summarizes the unique nature of platform competition and key points of difference with 
traditional competitive dynamics. These differences standing, how can we conceptualize and assess 
competition in digital markets? 
--Insert Table 1 about here--
We elaborate on these points in the rest of the paper, present a typology of distinct digital markets3 and 
advance a framework for the analysis of platform value and competition to assess the unique competitive 
3 Not all digital markets are platform markets. E-commerce services (i.e., retailers selling directly their goods online) are digital 
channels to access to the consumer market and deliver their offerings…yet, when it turns to competition, the standard competitive 
strategies and dynamics of traditional sectors apply (with the due caveat). It is when they start competing head-on with platform-
based services like Amazon Market Place that they will face a distinct competitive landscape with unique competitive dynamics, 
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dynamics in the different types of digital markets. We offer a platform-based view of competition in digital 
markets, and advance that digital platforms are the “new” market infrastructures that enable firms’ 
interconnected products and services to create and deliver value to final users. We discuss the competitive 
logics that shape platform competition in these markets. In particular, a winner-take-all competitive logic, 
which emphasizes the platform network’s strategic dimensions determining platform size, and a platform 
distinctiveness competitive logic, which emphasizes the distinctive elements characterizing the technological 
and market identity of the platform. 
Building on competitor analysis theory, in particular the models proposed by Chen (1996) and Livengood 
and Reger (2010), but taking the platform as basis for analysis, we introduce the concept of platform identity 
to delineate the platform’s technological and market profile that will determine the platform’s competitive 
identity domain, and thus the intensity and type of platform competition. We argue that each platform has a 
unique market and technological architecture identity, and comparisons of rival platforms along these two 
dimensions can help to understand the nature of competition in digital markets and explain some of the 
unique competitive dynamics that depart from mainstream competitive theory’s predictions. For instance, 
our framework would predict that competition between rival platforms will escalate into winner-take-all 
battles when platforms have similar identity domains, i.e., when they share similar type of end-users and 
similar technological architectures. Also, prior research finds that, in traditional settings, competitors 
increase their number and variety of competitive actions when intensity of rivalry increases. In contrast, our 
framework explains why and when, in platform digital markets, platform providers may take competitive 
actions that constrain the market scope or restrict the number of participants and offerings of the platform, or 
even increase platform access price to enhance the distinctive competitive positioning in the market; this is 
likely when platforms overlap in the end-user market but have distinct technological architectures. Our 
framework also helps to identify cases where the market boundaries and competitive domains get contested, 
and explain how competition may escalate and lead to market convergence. 
where the traditional competitive strategies may stand no chances. Therefore, we only focus here on digital markets that present 
distinctive competitive dynamics; namely, platform-based competition. 
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Our intent is to advance a perspective that can enrich and extend existing theory on competitive dynamics to 
the context of digital markets by revisiting some of its core concepts and analytical tools and integrating 
them with the demand-based competitive logics advanced in the emerging platform literature. Traditional 
views of interfirm competition typically focus on either the supply or demand side. However, the distinct 
nature of digital markets implies that supply and demand are directly connected and often co-evolve; the 
market forms and evolves endogenously. Seeing competition only from one side’s perspective would miss 
the underlying dynamics and mechanisms of value creation and value capture. A platform-based view 
allows for the integration of both demand and supply aspects into one, parsimonious framework to consider 
the value drivers and the triggers of competitive behavior that may originate in both sides of the platform 
market; demand and supply. With the proposed framework, we seek to offer a foundation for future research 
to further develop management guidance as per the strategic choices to win competition in the new, digital 
competitive landscape. 
Towards A Platform Perspective of Digital Markets
The proliferation in the business press of terms such as “apps economy” or “gig economy” reflects the desire 
and need to identify and capture the unique, distinct features of digital markets. Yet, beyond the catchy 
metaphor, the new terminology does not clarify how competitionis distinct in the digital arena. In some 
cases, it adds confusion by grouping under the same branding markets only in appearance similar. For 
instance, while food delivery platforms like Deliveroo or Just Eat are considered as part of the gig economy, 
in fact, they provide a service more like that of Amazon Marketplace, enabling transactions between 
consumers and providers of goods. While these services may share some structural properties (e.g., they 
both connect people via platforms), the elements making the platform service more valuable differ; so does 
competition. 
A distinctive aspect of digital is that digital technologies are generative – they continue to evolve in terms of 
their uses and functionalities depending on how they connect and integrate to other products and services 
(Yoo et al. 2010). Thus, in contrast to traditional markets in which a product/service is designed for a pre-
defined use, and its value depends on its standalone attributes and perceived quality by consumers, in digital 
markets a product’s or service’s value depends on the interconnected products/services of which it is part; 
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they jointly create value for the end user in the context of a system of use (Baldwin and Woodard 2009; Yoo 
et al. 2010). While they can be used separately to produce value, when connected, their value and 
functionalities get extended (Cennamo and Santalò 2019). A smartphone's application extends the value and 
functional use of the smartphone by allowing its user to gain access to and consume other products and 
services through its smartphone. Accordingly, because of the generative and connectivity nature, digital 
markets are unbounded in that the value of a digital product/service transcends its own boundary, and spills 
into new, and often contested domains. This change in the nature of digital markets brings along a shift in 
the economics and the underlying nature of competition (Jacobides, Cennamo, & Gawer, 2018), dismantling 
the contours of sectors and industries as we knew them, and creating new opportunities while destroying 
long-successful business models. We advance here that platforms, and the related multi-sided markets that 
emerge around them, offer a new relevant analytical tool; as unit of analysis, it helps to capture the 
aggregate level of firms’ and products’ interdependence across different markets and sectors that is relevant 
in the new competitive context of digital markets. 
The characterizing feature of digital markets is indeed the presence of a core, platform technology that acts 
as a data hub channeling and integrating information from/to users and from/to multiple connected products 
and services, and as market infrastructure connecting users and suppliers of goods. Essentially, digital 
platforms can be seen as innovations in market design that have the potential to change the “market 
architecture” (Meyer and Cennamo 2018)4 in a given sector (or across sectors) by altering the way final 
customers access to and consume products and services. Some platforms (e.g., Amazon Marketplace) 
leverage the data traffic generated by its users and providers to facilitate transactions through an efficient 
matched market; other platforms (e.g., Apple’s iOS) connect and integrate the workings of a core product 
with complementary innovations to offer an integrated product solution to customers, while others (e.g., 
Google’s Search or Maps) leverage their scale and scope to enable the searching and sharing of relevant 
information. While these platforms share commonalities as per the platform foundational elements, they also 
4 Meyer and Cennamo (2018), analyzing the impact of Airbnb and Booking platforms in the hotel industry introduce the concept 
of market architectural shift, “a change in the market architecture, i.e., the ways product offerings are accessed and consumed in 
the market”, and argue that increasing supply through Airbnb in a city lead not just to increased competition with incumbents’ 
offerings, but trigger incumbents to increasingly move their offerings to digital platforms such as Booking, making the platform 
infrastructures the new marketplace for hospitality products and services. This shift altered the way incumbents compete and their 
value-capture ability. 
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reveal differences in the way they operate, which imply differences for the market they enable in terms of 
what is primarily exchanged in the market (what users look/demand for), and the factors that make the 
platform service valuable. Based on the main role played by the platform, three different types of platform 
markets can be identified: multi-sided transaction markets, complementary innovation markets, and 
information markets. 
Multi-sided Transaction Markets 
A digital platform can broadly be seen as specific “digital infrastructure” (Constantinides et al. 2018: 381), 
formed by “the computing and network resources that allow multiple stakeholders to orchestrate their 
service and content needs”. In a multi-sided transaction market, the platform’s main role is providing the 
infrastructure to connect providers of goods and services with final customers, and facilitate value-exchange 
transactions among them (e.g., Rochet & Tirole 2003). E-commerce platforms such as Amazon 
Marketplace, auction platforms such as eBay, or hailing platforms such as Mytaxi connecting users to taxi 
drivers, are typical examples of platforms whose core utility is performing as a marketplace. The benefits 
final customers attain from the platform relate to gaining access to a variety of offerings provided by 
independent sellers. On the other side, sellers benefit from the platform because they gain access to a 
potential wide market represented by platform users. Marketplace platforms provide several tools to 
facilitate the search of products by users and the promotion of products by sellers, and guarantee the good 
success of the transactions. Amazon’s “suggested items” tool suggesting possible goods the user might be 
interested in based upon her/his search and buying history or related purchasing, eBay’s “seller feedback” 
system signaling the quality of the seller of the product being auctioned as assessed by past customers, or 
Mytaxi’s “regular driver” booking system that put drivers ranked as “favorite” by users at the top of the list 
when booking a journey, are but few examples of the many tools these platforms use to make the market 
more efficient, and facilitate the transaction. 
Markets for Complementary Innovation
In complementary innovation markets platforms are primarily innovation engines (Gawer, 2014), providing 
the core technological architecture other firms build upon to create new products that extend the core 
functionality and reach of the platform to final users. Examples include computing platforms such as SAP 
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NetWeaver that enables custom development of business solution applications and their integration with 
other enterprise systems and technologies; mobile system platforms such as Apple’s iOS that fuels the 
creation of innovative applications that extend the productivity and entertainment functionalities of the 
mobile device (iPhone, iPad, iPod, iWatch…); or data-product platforms such as Nike+ platform 
empowering externaldevelopers to build digital products and services using Nike’s user data and 
proprietary technologies, and connecting these products to Nike’s product offerings and its customers. 
These platforms are new organizational forms of innovating and achieving complementarity in assets (for 
generating and commercializing innovation) (Cennamo and Santaló 2019; Gawer, 2014; Jacobides et al. 
2018; Thomas et al. 2014). They do so by allowing for a modularized division of innovation tasks and labor 
(Baldwin & Woodard 2009) that lead to the emergence of specialized firms along the innovation value chain 
– the platform firm specializes in the common assets’ infrastructure for innovation5, making sure that 
complementarity and product system integration is achieved ex ante; external firms specialize in 
complements, experimenting through different variants of niche products that may extend the functionality 
and appeal of the platform to users (Boudreau & Lakhani 2009; Cennamo 2018). The platform connects 
different products (the iPhone and the Apps) by allowing data exchange and interoperability that make 
multiple products interacting among themselves; the resulting system of products offers an integrated 
solution to a customer’s set of needs, despite the individual components of the solution being provided by 
multiple, independent, and yet interconnected firms. What the platform does is essentially enlarging the 
value of the standalone offering by extending the range and scope of its uses for the consumer through the 
complementary goods (Cennamo and Santaló 2019). By connecting the physical hardware, the smartphone, 
to digital entertainment content and productivity software, Android allows users to extract greater benefits 
from both standalone offerings: the phone’s value increases because they can do many more things through 
it; similarly, the value of a video, song, or a navigation app increases because these products can be 
consumed also on the go through the phone. 
Thus, complementary innovation markets differ from transactional markets in that the primary value of the 
platform rests on its computing/data processing functionalities, which the complementary products 
5 They might also provide common infrastructure assets for commercialization (eg., Apple’s AppStore), when they also offer to 
complementors direct access to final users.
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connected to the platform help to extend. A market for complementary innovation thus arises between the 
platform owner and the external providers of the complementary products6. Such a market can be organized 
in different forms, including innovation contests (e.g., Android early contest for apps) (e.g., Boudreau et al. 
2011), bilateral contracting based upon certification procedures (e.g., SAP quality certification process) 
(Ceccagnoli et al. 2012), or one-to-many standardized rules based upon self-selection mechanism (e.g., 
Apple apps developer program) (Wareham et al., 2014). 
Markets for Information 
In information markets, the platform serves primarily as an information channeling infrastructure that 
enables the categorization and search of relevant information, and facilitates users’ exchange of information 
and matching. Examples include search engine platforms like Google Search, social/media platforms such as 
Twitter or Facebook, dating service platforms such as Match.com, job information and employment service 
platforms such as LinkedIn, or peer-to-peer travel information platforms like TripAdvisor (that relies on 
user-generated content to collect relevant information). In all these cases, the platform offers tools to filter 
and group the information according to parameters relevant to the user, facilitates the sharing of the 
information to reach out to other users and engage interactions, and matches users on the basis of the 
information they care most. Consider for instance Twitter: its value to a user primarily interested in politics 
increases with the number of people sharing political views and news. News Feeds about fashion or sport 
will be information not valuable to such users. This is why Twitter offers ways to filter the type of 
information that is most relevant to each user, and to target groups with specific interests while sharing a 
news/view (e.g., the increasingly popular hashtag). Similarly, Facebook has recently introduced changes to 
its News Feed to better display relevant stories and identify and rank authentic content7, in line with one of 
the core values of its service – enabling “authentic communication”. 
Given that the most valuable good being exchanged in such markets is information, platform value largely 
rests on the quality of the information, that is, on facilitating search and sharing of the information most 
6 Platforms can also offer additional market infrastructures typical of marketplace platforms, such as in the case of Apple App 
Store marketplace for apps, where the platform also facilitates direct transactions between users of the platform-based product(s) 
and the providers of complementary products. In this case, both a market for innovation (iOS) and transactions (App Store) 
cohabit, and are part of one integrated platform-based service.
7 https://thenextweb.com/facebook/2017/01/31/facebook-tweaks-news-feed-show-authentic-timely-stories/
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relevant to a user. Google’s Search Engine platform gained rapid market penetration (despite incumbent 
alternatives) because it could return more accurate and relevant information, and with a faster time response 
than other services to users’ online queries (Gawer and Cusumano, 2008). On the other side, LinkedIn had a 
slow start during its first years of operations to impose itself as the dominant tool to find out about jobs and 
job seekers’ profiles. Market penetration among employers increased when the platform introduced (peer-to-
peer) mechanisms to certify the information about job seekers. In some cases, these markets are influenced 
by social/community dynamics, whereby interactions among the specific community’s users can propel 
positive network externalities and influence the efficiency of the market (for information). Because 
LinkedIn’s users trust the information exchanged therein, when interacting with other peers, users can be 
more inclined to accurately evaluate each other, contributing to the amount and relevance of the information 
made available to other users. Similarly, when a user posts a picture or information on a Facebook’s group 
page, other users of the group and/or users that have social ties to the user, tend to comment on and/or share 
the information because of common interests and social contagion dynamics. 
While the primary good exchanged in these markets is information, there are no monetary transactions 
between the users exchanging it; the platform monetizes the flow of information in the market through 
indirect services (Parker & Van Alstyne 2005; Seamans & Zhu, 2014). Because users search for relevant 
information about a product/service, and companies are akin to reach potential customers with information 
about their offerings, Google facilitates the exchange of such information and relevant matching, and makes 
advertisers paying for the successful targeting of the information. Similarly, Facebook capitalizes on the 
information traffic on its users’ newsfeed to post advertisement of corporate users.While these markets may 
share features of the multi-sided transaction markets, they differ in that, 1) there is exchange of information 
among users but not direct monetary transaction between those seeking and those providing the information; 
2) exchanging and sharing information has a stand-alone value to the user; 3) the information can be 
instrumental to a transaction by directing the user to offerings that likely match her needs (as in the case of 
Google’s services). Thus, a market for information arises through the platform. Table 2 summarizes these 
differences. 
--Insert Table 2 about here--
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A note at this point is worth mentioning. Though the markets are presented here as distinct, this is rather for 
expositional convenience. Markets can sometimes overlap to different degrees to the extent that platforms 
combine these different elements in their infrastructures; innovation markets can have also transactional 
markets’ features when the platform also gives innovation providers access to consumers and facilitates 
transactions among them; information markets also share some of the multi-sided transaction markets’ 
characteristics when the platform offers additional tools and services to one of the user groups to monetize 
their information. However, we believe this distinction is useful to detect the peculiarities of the different 
platforms, which has implications for the emphasis a platform owner puts on the elements of the platform 
service, and thus for platform competition. 
Platform Value
Platforms have been examined from different perspectives, each emphasizing some elements as key 
determinants of the value of a platform, and thus of its competitive standing in the market. We take the 
perspective of the final consumer (i.e., end-user of the platform). Accordingly, value is defined here as the 
benefits that consumers derive from using the platform and consuming its complementary goods and 
services (e.g., Cennamo 2018). This conceptualization is in line with the existing view on platforms, and 
also with recent demand-based view in Strategy research (e.g., Adner & Kapoor 2010; Priem 2007) that 
emphasizes value-creating strategies8. 
Studies drawing from the network economics literature emphasize indirect network effects dynamics as 
critical factor shaping platform competition, and thus focus on the platform’s network size as core element 
of platform value (Armstrong, 2006; Caillaud & Julien, 2003; Evans, 2003; Hagiu, 2005, 2009; Parker & 
Van Alstyne, 2005; Rochet & Tirole, 2003). Studies on technology management emphasize innovation 
dynamics as critical for the success of a platform, focusing on aspects related to the production (supply-side) 
and adoption (demand-side) of the technology such as the design of the technological architecture, the 
8 Priem (2007), for instance, advances that a firm’s products and services are without value until they get consumed and received 
payments by consumers. According to this customer-based perspective, value is experienced by consumers during their 
consumption activities; different consumers experience more or less value; and consumers’ perceptions will affect their 
willingness to pay. Value, thus, is the “subjective valuation of consumption benefits by a consumer” (2007:220). Value-creating 
strategies should then focus on activities that “establish or increase the consumer’s valuation of the benefits of consumption”; 
value capture instead involves “the appropriation and retention by the firm of payments made by consumers in expectation of 
future value from consumption” (2007:220). 
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quality of the platform and the complementary innovation, platform functionalities and ease of use, and 
users’ community identity (e.g., Anderson et al., 2014; Cennamo et al. 2018; Gawer & Cusumano, 2002; 
Ozalp et al. 2018; Schilling, 2002, 2003; Suarez, 2004; Tiwana et al., 2010). Studies from the strategy 
literature emphasize the strategic choices about a platform’s market positioning and the management of the 
ecosystem of complement providers as main determinants of the value generated within the platform 
ecosystem and the value captured vis-à-vis competing platforms (e.g., Cennamo & Santaló, 2013; Cennamo 
2018; Eisenmann et al., 2006, 2011; Seamans & Zhu, 2014; Schilling, 2003; Suarez & Kirteley, 2012). 
Integrating insights from these perspectives, we present in Figure 1 the elements of platform value (end-user 
network, complementor network, platform architecture, platform scope), which determine the key strategic 
dimensions (platform size, platform identity) shaping platform competition. We discuss these in turn. 
End-User and Complementor Network. The main value of a digital platform to users is related to the 
network benefits; i.e., the benefits users on one side enjoy from interacting with users on the other side. 
Thus, the platform’s installed user base is a critical source of platform value, benefiting users directly, from 
the opportunities to interact with others and exchange information (as for communication platforms), and 
indirectly, from the positive externalities that a large base of users has on the incentives of independent 
providers (and other users) to produce content and complements (e.g., Cennamo, 2018; Clements & Ohashi, 
2005; Corts & Lederman, 2009; Schilling, 2002). This is because of indirect network effects dynamics 
(Hagiu, 2005; Rochet & Tirole, 2003), such that the participation of one group (e.g., end users) raises the 
value of participating for the other (e.g., complement providers) (Evans, 2003).
Because of these dynamics, the network size of a platform’s users and complementors are strictly related 
and reinforcing each other’s impact on platform value (Katz & Shapiro, 1994). As these benefits increase 
with the network size, lock-in effects and switching costs may arise, which would make it hard for users and 
complementors to switch to competing platforms, and further increase the value of the platform’s installed 
base (Fuentelsaz et al., 2015). Also, the strength of the network, as assessed in terms of social ties among 
users (Suarez, 2005) and the marginal impact of an extra user to the network (Shankar & Bayus, 2003), has 
been shown to affect the value of a larger base of users. As the base of users increases, more complementors 
will find valuable to participate into the platform, expanding thus the variety of platform content and 
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complements. This, in turn, will further reinforce the value of the platform to users. Taken together, the 
installed user base, the amount of platform complements/content and the network of its providers determine 
the overall platform size, one of the two critical strategic dimensions shaping platform competition, as 
discussed later. 
--Insert Figure 1 about here--
Platform Architecture. A number of studies, particularly in the technology management literature, have 
advanced that, despite the network benefits, the platform technological architecture – that is, the 
technological capabilities of a platform, and the way platform technological components function and 
connect to platform complements/content (Baldwin and Woodard 2009 , Tiwana 2015 , Yoo et al. 2010 ) – 
remains a critical determinant of platform value (e.g.,Cennamo et al. 2018; Suarez, 2004; Schilling, 2003; 
Tiwana et al. 2010). Enhanced technical performance and functionalities of the platform can benefit users 
through gains in productivity, ease of use, and better services from access to content/information and 
consumption of complements (Gawer, 2014; Zhu & Iansiti, 2012). The design of the platform’s 
technological architecture has also been shown to affect the quality of the content and complementary 
innovation produced by affecting the costs and complexity of the innovation process of external providers 
(Claussen et al., 2015; Ozalp et al. 2018) and the degree of integration and fit with the system (Cennamo et 
al., 2018). Platform architecture thus determines the value of a platform directly, by providing performance 
and functionality benefits to users, and indirectly, by enabling the production of higher content/complement 
quality, which has implications for the overall consumption experience that users enjoy from the platform, 
and for how the specific platform technology is perceived by users and content/complement providers. All 
of which contributes to define the unique technology identity of the platform (Xu et al., 2010). 
Platform Scope. Findings from studies examining the impact of competitive strategies on platform 
performance indicate that platform scope – the different markets that the platform serves through its 
functionalities (Eisenmann et al. 2011), affects platform value by determining the market positioning of the 
platform along the map of consumers’ preferences and relative to competing platforms, and can be an 
important driver of platform success in multisided markets (e.g., Bresnahan et al. 2014; Cennamo & Santaló, 
2013; Eisenmann et al., 2011; Seamans & Zhu, 2014). Platforms can vary in their strategies to attract users 
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on the different sides of the platform market, and activate and leverage the indirect network effects. Some 
platforms may target specific groups of users and specialize in services and content/complements that best 
address the needs of those users, like in the case of online platforms for classified ads relative to generalist 
online newspapers (Seamans & Zhu, 2014). Other platforms may bundle their services to span multiple 
markets and leverage user network benefits and the platform common components through these markets, 
like in the case of software platforms; a strategy that has been referred to as “platform envelopment” 
(Eisenmann et al., 2011). These strategies influence the overall positioning of the platform in the user 
market by restricting or widening the scope of the platform and its market orientation, which will also 
impact the type of content and complements the platform will offer, and thus the degree of platform 
distinctiveness in terms of content/complements relative to competing platform ecosystems; all of which 
contributes to define the unique market identity of the platform in a user’s mind (Cennamo & Santaló, 2013; 
Seamans & Zhu, 2014). 
Taken together, platform architecture and platform scope determine the technology-related and market-
related traits of the platform, which overall define the platform identity, the other critical strategic dimension 
shaping platform competition. 
Platform Competition Dynamics in Digital Markets
The extent that platform providers emphasize one or the other strategic dimension while competing for end-
users with rival platforms depends on the type of digital market they compete in, which affects the extent 
each of the core elements of platform value creates benefits for the consumer. It also depends on the extent 
rival platforms overlap in the same competitive domain, which affects their rivalry behavior and thus, their 
motivation to take more or less aggressive competitive actions. Most of the studies on platform competition 
build on network externalities theory and mainly look at the demand-based factors, i.e., the network effects 
creating value for platform users, as main driver of platform value and competition’s outcome. We advance 
here a broader framework that, building on the competitive dynamics’ literature, integrates supply-based 
aspects, such as a platform’s identity domain (and how it influences platform provider’s awareness-
motivation-capability to engage in competitive behavior) to explain the type and intensity of platform 
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competition among rival platform providers. The proposed framework helps explain, for instance, when 
platform competition escalates into winner-take-all battles, and when instead platform providers can avoid 
head-on competition and build a differentiated position in the market based on platform distinctiveness. To 
understand these competitive dynamics, one should assess the competitive actions that platforms can take 
and the resulting changes in emphasis along the two strategic dimensions (size and identity) not just in 
isolation, but in response to competition from rival platforms. Thus, one should consider also rival platforms 
to fully understand the capacity of a given platform to create and capture value in a market. Building on 
Chen (1996) and Livengood and Reger (2010), we introduce a competitor analysis dimension, adapted to 
reflect the key factors that matter for platform competition, as a moderator of the relationship between 
platform value and platform competition. Figure 2 offers a schematic representation of the proposed 
integrated framework for assessing competitive dynamics in digital markets, linking the dimensions of 
platform value to platform competition (type and intensity). The type of digital market will affect the 
relative impact of size and identity on platform value. The building blocks of platform value dimensions – 
platform size and platform identity – influence the main competitive logics taken by a platform provider – 
winner-take-all or platform distinctiveness. This relation, and the intensity of platform competition are 
influenced by the extent the platforms operate in the same competitive domain – as determined by the extent 
of platform user commonality and platform architecture similarity – which affect the drivers of competitive 
behavior and thus platform competition intensity. Platform competition will in turn affect platform 
performance and the resulting market structure (these effects are only marginally discussed in this article). 
The figure then reveals a feedback loop as platform competition, and its effects, alter the existing positions 
in competitive domain overlap and the platform’s size and identity, thereby setting a new stage for platform 
competition. First, we discuss the main relationship between the platform value dimensions and the platform 
competition logics, which is the central part of the framework, then we discuss how the type of digital 
markets affect the relative emphasis on one or the other dimension of platform value, thereby the likelihood 
of the platform competition type. Finally, we discuss how similarity in platform identity domain affect the 
type and intensity of platform competition between rival platforms. 
--Insert Figure 2 about here--
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Platform value dimensions and platform competition logics
Platform size and the winner-take-all logic. The remarkable rise andcompetitive advantage of large 
platform companies such as Google, Amazon or Facebook has generated a common belief that the way to 
win competition in such markets is by building scale fast, growing the network of users and content 
providers, and thus limit market space for competitors that would operate under diseconomies of scale. This 
view is theoretically grounded on the economics theory of indirect network effects (Armstrong, 2006; 
Caillaud & Jullien, 2003; Parker & Van Alstyne, 2005; Rochet & Tirole, 2003), which developed mainly to 
explain competitive dynamics in multi-sided markets. Because of the network effects, once a certain 
platform reaches a critical mass of users, the positive feedback between consumers’ network size and 
complementors’ network size and the amount of content/complement generated by them gets reinforced 
over time, further enhancing the value of the platform. This leads to winner-take-all competitive dynamics 
(Lee et al. 2006) where the platform with a larger size of the network is expected to eventually win the entire 
market.
Main challenge for platform owners competing per this logic is how to gain wide adoption on both sides of 
the platform network, and grow it larger than competitors. How the platform owner motivates participation 
from both sides to overcome the ‘chicken-and-egg problem’ (Caillaud and Jullien 2003) has been indeed the 
major object of analysis in the multi-sided market literature (e.g., Rochet & Tirole, 2003; Parker & Van 
Alstyne 2005; Hagiu 2005, 2009). In contrast to prior research’s findings in traditional settings, where firms 
pursue aggressive pricing strategies to capture greater value in the market by hurting a rival’s position and 
forcing it out the market, in platform markets, pricing is primarily used as coordination mechanism (Rochet 
& Tirole, 2003; Parker & Van Alstyne 2005) between the two sides of the platform market to grow 
participation to the platform and thus provide greater benefits to its users. Pricing, thus, is primarily a value-
creating strategy. Platform providers can also use it more aggressively to lure competitors’ users and/or 
complementors and further reinforce their network size-based leadership in the market. 
It is no coincidence that, up to date, the literature has mostly focused on platform access pricing strategies. 
Authors have looked at the effects that pricing on each of the platform’s sides has on a platform’s capacity 
to penetrate the market and expand its complement/content offerings, with strategies that include user 
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subsidies to increase adoption (i.e., pricing the platform near to or below marginal cost, often granting 
access to users for free) (e.g., Hagiu 2009; Clements & Ohashi 2005; Parker & Van Alstyne 2005), and 
exclusive licensing agreements with key complementors (Corts & Lederman 2009; Hermalin & Katz 2013). 
One of the basic rules being suggested is that platforms must subsidize the group that is more valuable in the 
network (e.g., newspapers’ readers, users searching for information, etc.), and charge the group less 
sensitive to price that benefits from the presence of the other group (e.g., advertisers) (Armstrong, 2006; 
Eisenmann et al., 2006). Pricing strategy is related to the platform openness strategy (Boudreau 2010), that 
is, the extent that the platform provider facilitates and grants unconditional access and participation to its 
network. It has been shown that greater “platform openness” stimulates faster growth of the network, greater 
number and variety of complementary offerings, and can positively affects platform dominance (e.g., 
Boudreau 2010; Anderson et al. 2014). 
Scholars have also examined the effect of direct provision of content/complements (“first-party content”) by 
the platform provider as a strategy to get started or reinforce the indirect network effects between users and 
complementors, finding a positive relation in the early stages of the platform market (e.g., Cennamo 2018; 
Hagiu and Spulber 2013). Few have examined the effect of entry timing on the size of a platform’s network, 
and platform competition (Suarez, 2004; Zhu & Iansiti, 2012), with some studies finding that moving first 
into the market with a new platform technology in fact, may affect negatively the capacity of the platform to 
penetrate the market (Cennamo, 2018; Schilling, 2002). Finally, Eisenmann et al. (2011) examine the impact 
of “platform envelopment” strategy9 – the expansion of the platform’s market scope to adjacent markets 
through inclusion to the platform’s core functionalities of additional technological capabilities and user 
functionalities offered by the platforms operating in the adjacent market. In the presence of demand-side 
economies of scope across adjacent market segments, platform providers can leverage the platform 
infrastructure and existing users’ relationships to generate greater benefits for end-users and increase 
platform performance (Tanriverdi and Lee 2008). When the core and extended platform technological 
capabilities are super-modular (Milgrom, & Roberts, 1990), the value of the platform after envelopment is 
9 Classical example is Microsoft’s Windows operating system that has, over the years, incorporated functions performed by 
independent, specialized platforms in adjacent markets like Netscape (for the web explorer service) or Real Player (for the 
management of media files).
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larger than the sum of the value of the separate individual platforms, and envelopment makes economic 
sense from the perspective of value generation for users (Eisenmann et al. 2011; Tanriverdi and Lee 2008).
All these studies point to the importance of market coordination activities for user value creation as the 
central, strategic task of the platform owner. As value is largely linked to platform size, the winner-take-all 
logic emphasizes the importance of coordinating the interactions among the distinct groups of users and 
content/complement providers. Hence, primacy is on the strategies that facilitate adoption of the multi-sides 
of the platform, and transactions across the distinct user sides. Thus, platforms that emphasize size relatively 
more than identity will tend to adopt a winner-take-all competitive approach to gain a dominant market 
position in their competitive domain through this menu of competitive actions. 
Platform identity and the platform distinctiveness logic. The winner-take-all logic apparently rules out 
classical strategic options of gaining a differentiation advantage through market positioning or superior 
product attributes: there is just one winner, and that is the platform with the largest network that will gain 
strong hold over the mass-market. Yet, we observe many instances of platform owners taking decisions that 
are at odds with a winner-take-all logic, and that reflect more the desire to gain distinct identity in the 
market and differentiate with respect to other platforms (Cennamo and Santaló 2013). In some cases, 
platforms purposely restrict access to some users to select out segments of the market they do not want to 
serve as in the case of eHarmony, the online dating platform service, which denies membership to as much 
as 20% of their potential users. In other cases, platforms increase the burden and costs for complement 
providers to innovate for and connect to the platform’s users, as for Apple iOS mobile platform that imposes 
restricting approval policy for apps developersor Facebook Ads platform that imposes restrictions as per 
how advertisers can reach out to their target users through the platform (Claussen et al. 2013)10. These 
higher affiliation burden and development costs are meant to induce some levels of platform-specific 
investments on users/complementors such to guarantee participants’ alignment with the platform overall 
objectives and identity (e.g., Jacobides et al. 2018) and greater value for the user (consumption experience) 
(Cennamo and Santaló 2019) through enhanced platform-content/complement integration (e.g., Cennamo et 
10 They do so mainly to guarantee a minimum threshold of quality of the complementary innovation that gets produced, such that 
users are only exposed to content and information relevant to them.
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al. 2018; Tiwana 2015). In fact, platform owners may set up screening mechanisms to certify the quality of 
providers’ complementary innovation, and accordingly restrict access and participation to the network to 
those not meeting the required minimum threshold (Wareham et al. 2014). Developers of application 
software for the SAP platform, for instance, need to undergo through a thorough quality screening 
certification process before they can release SAP compatible products.
Recent studies empirically show that platforms can gain differentiation in the market based on distinct 
market positioning of the platform (Bresnahan et al. 2014; Cennamo and Santaló 2013), distinct and superior 
platform technological capabilities (Schilling, 2003; Zhu and Iansiti 2012), or distinct complements and 
content (Cennamo & Santaló, 2013; Seamans & Zhu, 2014). Scholars studying the technological aspects of 
platforms have emphasized how design decisions on the technology architecture (e.g., level of 
modularization or interface openness) greatly affect a platform architecture’s configuration, thereby, the 
specific way and type of value that is generated within the platform system (Anderson et al. 2014; Claussen 
et al. 2015; Tiwana et al. 2010). In particular, the architecture’s configuration affects the functionalities of 
the technology to users (Schilling, 2003; Zhu & Iansiti, 2012), as well as the innovation opportunities and 
capacity for complement providers (Anderson et al. 2014; Claussen et al. 2015); the costs and benefits users 
and complementors bear/enjoy by conducting transactions through the platform system (Wareham et al. 
2014); the innovation appropriability “regime” for complement providers (Ceccagnoli et al., 2012; Cennamo 
2018), and the average quality of complementary goods available on a platform (Cennamo & Santaló, 2013; 
Tiwana 2015). These architectural design decisions affect the level of distinctiveness of a given platform 
system determining the structural elements of the platform distinctiveness – they are difficult to adjust in the 
short term, and constrain the platform into path dependent evolutionary trajectories (e.g., Cennamo 2018). 
By the same reasons, they are also difficult to replicate by competitors, at least in the short term. 
On the user market side, positioning strategies are critical levers for a platform’s differentiation, which can 
explain the coexistence of competing platforms in the same market despite the pressing force of network 
effects (e.g., Bresnahan et al. 2014; Cennamo & Santaló 2013). The positioning literature in competitive 
strategy stresses the importance of building unique identity indeed in the consumer market space to gain 
competitive advantage (e.g., Chung & Kalnins, 2001; Swaminathan, 2001). Recent studies on platform 
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competition highlight competitive strategies that trace back to such positioning perspective. Specifically, 
platforms can become “specialists” in given segments of the content market (e.g., Seamans & Zhu, 2014) by 
targeting different customer preferences with distinct complements’ portfolio (content scope) (Cennamo & 
Santaló, 2013), by levering platform scope (bundling platform’s multi- vs. specific-purpose functionalities) 
(Eisenmann et al., 2011), or by segmenting the market by focusing on the high-end (premium) as opposed to 
the low-end market as for the case of Apple iOS and Google Android mobile platforms (Bresnahan et al., 
2014). Distinctiveness can also be achieved based on exclusive content/complements that are not available 
on competing platforms (Cennamo & Santaló, 2013; Hermalin & Katz, 2013). These strategies affect the 
level of differentiation of the platform system in a market, determining the relative, dynamic elements of the 
platform distinctiveness – they form and evolve in response to the evolution of the consumer market, and to 
competition from other platform systems (as we discuss later to greater extent). Table 3 summarizes the key 
differences between the two logics of platform competition and the associated competitive actions.
--Insert Table 3 about here--
Type of markets and platform value dimensions 
The type of digital market affects the extent each of the core elements of platform value creates benefits for 
the consumer from using the platform. Platform size is the most critical driver of value creation when the 
following conditions are met: i) consumers and complements are homogenous in terms of the impact each 
has on the value of the platform’s network size, ii) other users joining the same side of the platform network 
do not reduce the user’s utility from the platform, and iii) users’ utility increases with the amount of 
content/complement created (Panico & Cennamo 2015; McIntyre & Srinivasan 2017; Lee et al. 2006). In all 
other cases, particularly when condition i) is not satisfied, platform identity can be relatively more important 
to create value than platform size. 
Pure multi-sided transaction markets meet all the three conditions; platform size largely affects platform 
value and winner-take-all tends to be the dominant competitive logic in these markets. Consider the case of 
Amazon Marketplace. Consumers are better off with more variety of goods being offered in the platform, 
and having more consumers using the platform does not reduce the utility of a given consumer from using 
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the platform; if any, it might increase it through the positive effect a wider base of customers has on the 
incentives of sellers to provide goods on the platform (that is, the indirect network externalities are positive 
and reinforcing). Sellers might experience some negative externalities from other sellers joining the platform 
network to the extent that this results in greater competitive pressure. Yet, a larger seller network also 
expands the market of consumers joining and using the platform because of consumers’ preferences for 
product variety; thus, competition might actually be beneficial for platform growth (Armstrong 2006; 
Cennamo & Santaló 2013). In transaction markets, platform providers can leverage some elements of 
platform identity to increase consumption experience (for instance through better search and transaction 
efficiency, better match and interaction between sides etc..), which can be conducive to better performance 
(higher volume transactions/higher customer retention/lower user migration). Nonetheless, emphasis is still 
on platform size, the final objectivebeing to win a dominant position in the market over competition. 
In information and complementary innovation markets, “identity effects” may trump network size in users’ 
valuation of platform value. In innovation markets value for consumers is mainly driven by platform-
complement integration and variety of complements (e.g., Cennamo 2018; Tiwana 2015). These, in turn, are 
influenced by the configuration of the platform architecture (e.g., Cennamo et al. 2018; Zhu and Iansiti 
2012) and the type of complementors participating in the network (Claussen et al. 2015; Wareham et al. 
2014). Users may value some specific attributes of the platform technology, and because of them select the 
platform despite its size (Zhu & Iansiti 2012), or value specific content or few complements of exceptional 
high quality much more than complement variety, and adopt the platform that offers such content (Binken & 
Stremersch 2009; Cennamo, 2018). In information markets, value is derived from relevant matching and 
interaction between producers and consumers of information (Claussen et al. 2013). Elements of platform 
size are important to enable interactions and production of information in the first place; however, elements 
of platform identity are critical to guarantee meaningful interactions and thus facilitate and increase 
opportunities of exchange of relevant information to users11. In these markets, platforms can build a strong 
11 Because platform users are both producers and consumers of information, it is important to have a big enough network that can 
activate reinforcing network effects; yet, even more important is the network strength: if the marginal impact of the addition of 
users to the network does not generate extra benefits to existing users, the interaction becomes less and less relevant among users, 
diminishing the value of the network and thus the benefits from using the platform.
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competitive positioning based on distinctiveness logic by privileging the elements characterizing platform 
identity relative to platform size, sometimes even at the cost of restricting platform size. 
Consider the case of eHarmony, the online dating service platform. It purposely restricts access to its users 
to differentiate with respect to competing platform Match. Instead of just attracting a wide base of female 
and male users to increase the odds of matching, eHarmony has been very careful in building a unique 
platform identity over the years, focusing on extensive screening of users’ lifestyle and relationship 
preferences, values, personality traits and similar to feed the user Personality Profile, and other platform 
features (e.g., matching algorithm and guided communication system) that can help detect a potential match 
on the basis of long-term compatibility (Piskorski et al. 2008). This screening questionnaire is mandatory to 
create the user’s personality profile; yet, it does not guarantee membership to the platform. In fact, 
eHarmony declines membership to as many as 20% of its potential customers. As explained by its founder, 
“since it is hard to sign-up, the eHarmony person self-selects…it says, “I am serious” (Piskorski et al. 2008: 
5)”. Because of this focus, and targeting, eHarmony has been able to convert its active users into paying 
members three times more effectively than competition (Piskorski et al. 2008). And this, despite aggressive 
(winner-take-all) strategies of main competitor Match, such as large marketing investments and lower prices 
to attract users and expand its installed base. 
This implies that competing platforms can coexist in these markets, taking different approaches and 
emphasis along the two strategic platform value dimensions, platform size and platform identity. Platform 
providers can focus their emphasis relatively more on platform identity to build a unique, distinctive 
positioning of the platform based on quality/consumption experience (Cennamo and Santalo 2013), or on 
platform size, to gain a dominant position as largest provider of complementary innovation and interaction 
opportunities (Anderson et al. 2014). Whether a market equilibrium based on this competitive asymmetric 
positioning can be sustained over time or whether intensity of competition escalates in the market will 
depend on the competitive relationships between rival platforms, and thus on their competitive identity 
domain. We discuss this next. 
Platform identity domain and platform competition (type and intensity) 
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When assessing the competitive relationships between two rival platforms, we consider two levels of 
overlap of their competitive identity domain: platform user commonality defined here as the degree the two 
platforms share same type of end-users; and platform architecture similarity, defined here as the degree the 
technological architecture of the two platforms share the same functionalities, capabilities and technological 
attributes. These two attributes largely define whether two platforms are direct competitors or have the 
potential to become so. A major thrust of platform competition research has been in testing the winner-take-
all hypothesis, i.e., the likelihood that one platform ends-up winning the entire market, starting from the 
assumption that rival platforms compete for the same users. Because of the indirect network effects, 
platforms with high user commonality are expected to compete more fiercely to gain or defend their 
dominance in the market and avoid user migration to rival platform systems. Likewise, research on platform 
architecture configuration has highlighted the importance of technological attributes in platform 
competition, showing how platforms with similar architectures end-up competing intensively for the same 
content/complements, thus, competing directly for complementors. 
Figure 3 offers a stylized representation of the four possible competitive scenarios from the combination of 
high/low overlap along these dimensions. These scenarios can result from the deliberate choices taken by 
the platform providers. In designing the technological architecture, for instance, platform providers can 
choose the extent they want to compete with rival platforms on the same technological account, or compete 
on different functionalities and capabilities that allow users and complementors alike to use and benefit from 
the platform differently than competing systems. These scenarios can also form from emerging competitive 
interactions ensuing from the independent value-creating strategies taken by the platforms. When their 
networks start to become nested, sharing to larger extent users, platform providers will realize their market 
overlap and will be more likely to treat each other as direct competitors for users. We discuss each scenario 
in turn.
--Insert Figure 3 about here--
High user commonality – high architecture similarity  competitive identity domain overlap. Platforms 
with high end-user commonality and architecture similarity will compete to large degree in the same 
competitive identity domain and perceive each other as direct competitors and a threat to their existence. 
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Under high overlap, platform competition will more likely be intense and escalate into winner-take-all 
battles because