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date: 08 December 2021

Platformizing Organizations: A Synthesis of the Literaturefree

Platformizing Organizations: A Synthesis of the Literaturefree

  • Pankaj Setia, Pankaj SetiaInformation Systems, Indian Institute of Management Ahmedabad
  • Franck SohFranck SohInformation Systems & Supply Chain Management, The University of North Carolina at Greensboro
  •  and Kailing DengKailing DengSchool of Accounting & Computer Information Systems, University of Tulsa


Organizations are widely building digital platforms to transform operations. Digital platforms represent a new way of organizing, as they leverage technology to interconnect providers and consumers. Using digital technologies, organizations are platformizing operations, as they open their rigid and closed boundaries by interconnecting providers and consumers through advanced application programming interfaces (APIs). Early research examined platformized development of technology products, with software development companies—such as Mozilla Foundation—leading the way. However, contemporary organizations are platformizing nontechnology offerings (e.g., ride-sharing or food delivery). With growing interest in platforms, the basic tenets underlying platformization are still not clear. This article synthesizes previous literature examining platforms, with the aim of examining what platformization is and how and why organizations platformize.


  • Business Policy and Strategy
  • Information Systems
  • Organization Theory
  • Technology and Innovation Management


How and when do organizations platformize? Digital platforms represent the use of various application programming interfaces (APIs) built over the technology and business foundations. In general, digital platforms represent digital foundations along with the business strategies and processes that enable greater interactions between providers and consumers. Platformization represents the act of shifting to digital platforms for offer products and services. Specifically, platformization is the strategy for leveraging the digital platforms—the digital and business foundations—that facilitate interactions between producers and consumers. Nambisan, Siegel, and Kenney (2018) defined platformization as “the increasing importance of digital platforms as a venue for value creation and capture” (p. 354). Recent research underlines the importance of platformization, as organizations move away from products to digital platforms, transforming organizational identity (Altman & Tripsas, 2015). Indeed, digital platforms are taking center stage in firms’ strategy (Chen, Fang, & Li, 2016; Economides & Katsamakas, 2006; Mantena & Saha, 2012; Parker & Van Alstyne, 2018; Parker, Van Alstyne, & Jiang, 2017). Therefore, how and when organizations platformize are dynamics that are less understood and that are receiving greater attention, among organizational scholars.

Initial models for platformization evolved in the technology sector, as community developers participated in technology product development (such as the development of Firefox by Mozilla Foundation, or Linux by Linux Foundation). This early approach to platformization underlines a technical strategy. Developer communities complement organizational developers, as they have unique skills and a different understanding of customer needs (Setia, Rajagopalan, Sambamurthy, & Calantone, 2012). Large developer communities supply the workforce required to develop a large number of applications, and platforms—such as Android and iOS—have leveraged them to create more than 2.46 million and 1.96 million apps, respectively (Statista, 2019). At the same time, opening up their boundaries, organizations—such as Apple or Firefox—develop novel technology offerings (products and services) by leveraging the expertise of developer communities.

Further, platform models are now being developed across mainstream organizations, with offerings that go beyond technology products. Contemporary organizations are platformizing to offer a wide range of offerings, including music, meals, taxi rides, or customer durables. For example, Uber’s platform model offers enhanced mobility, through a wide range of peer-to-peer ride-sharing services, including car-sharing or bicycle-sharing and food delivery. Platformizing operations, organizations are opening up their boundaries and increasing user and developer participation in the development of offerings, giving them access to data and applications (Eisenmann, Parker, & Van Alstyne, 2009; Parker et al., 2017). Platformization (such as that done by Uber) connects consumers with providers, using a digital platform that enables direct or quasidirect transactions between the two. Platformization has become popular among mainstream organizations, and some competitors’ survival is under duress. For example, faced with platformized competitors, such as Uber, traditional taxi companies have lost out (Angrist, Caldwell, & Hall, 2017; Cramer & Krueger, 2016), and Airbnb is putting pressure on existing hotels’ profits (Zervas, Proserpio, & Byers, 2017).

In general, many organizations are now emulating platform models across the economy, creating greater value. For example, through the platformization of healthcare, governments and lawmakers plan to more directly leverage mobile health technology for addressing the acute healthcare access problem across the United States (Khan, 2016). While it offers opportunities for creating organizational value, platformizing is not easy. Recent research discusses different facets of platformization, such as those associated with the underlying technologies and market or economic dynamics. Indeed, reviews have emphasized different aspects related to innovation, value cocreation, or exchanges in platforms (Schreieck, Wiesche, & Krcmar, 2016).

Focusing on the technology dynamics, Tiwana (2015) and Tiwana, Konsynski, and Bush (2010) examined the technical design of platforms, highlighting key characteristics, such as modularity, compatibility, and standardization. Studies in this domain may focus on boundary resources, including data and toolkits (Eaton, Elaluf-Calderwood, Sorensen, & Yoo, 2015; Ghazawneh & Henfridsson, 2013). Another body of research examines market dynamics, using economic perspectives, such as network effects. Research in this domain may focus on pricing and revenue creation while exploring competition among platforms for market creation (Anderson, Parker, & Tan, 2014; Bakos & Katsamakas, 2008; Mantena & Saha, 2012). Researchers have also highlighted the socioeconomic impact of digital platforms. Greenwood and Agarwal (2016) and Greenwood and Wattal (2017) highlighted serious health-related consequences—such as HIV incidence and alcohol-related motor vehicle fatalities—of matching platforms and ride-sharing platforms, respectively.1

While the idea of platformization is enticing practitioners and scholars, literature unraveling its dynamics is in the formative stages, and the core tenets for platformizing are unclear for mainstream organizations. Platformizing represents a new way of organizing. Understanding this new way is essential for creating appropriate and efficient platforms within organizations, a requirement for firm survival (Parker et al., 2017). Therefore, this article reviews and synthesizes previous research to answer three questions: What is platformization? How do organizations platformize? Why do organizations platformize?

A New Business Model: What Is Platformizing?

Organizations process inputs from (upstream) providers and (downstream) consumers, enabling the exchange between the two (Lee, Padmanabhan, & Whang, 1997; Vachon & Klassen, 2006). For mainstream organizations, providers and consumers have typically been suppliers and customers, respectively. Also, ordinarily, organizations separately interact with providers and consumers, with little direct interface between the two. However, platformizing entails transforming these exchange dynamics. Organizations choosing to platformize underline the recognition of enhanced value created by others’ (complementors’) innovations rather than their product offerings (Altman & Tripsas, 2015). Beyond the new entrants’ (such as Uber and Airbnb) transforming industry (e.g., taxis and hotels, respectively) dynamics, established incumbents are also platformizing operations. For example, CitiBank released several banking APIs in 2016 to create a banking ecosystem and to accelerate digital innovation by third-party developers.

Notably, platformization requires enhancing the directness of exchanges between providers and consumers, as the organization takes on the role of an intermediary (Table 1; see also Helmond, 2015; Nieborg & Helmond, 2019). Previous research highlighted that the platformization of organizations transforms their identity, as it underlines new value creation and appropriate mechanisms. The organizational emphasis may shift from a stand-alone product-based business model to a platform-based business model (Altman & Tripsas, 2015). Across different industry sectors, platformized organizations may take different forms that differ in the ways they create value. Notably, the organizational offerings may be information, goods/services, or innovation, and the platform itself may manifest as an information market (e.g., Google search, Twitter), a multisided transaction market (e.g., Amazon Marketplace, eBay), or a complementary innovation market (e.g., SAP NetWeaver; Apple’s iOS; Cennamo, 2019).

Table 1. Platformization of Organizations



Exchange Between or Among Providers and Consumers

Platformized Organizations

Economides and Katsamakas (2006), Tiwana (2015)

Add-ons to the web browser or core modules of the operating systems.

External developers contribute skills and get recognition and web browsers’ users download the add-ons. Similar dynamic for developing core modules of PC operating systems (OS).

Mozilla Foundation, Linux Foundation

Kapoor and Agarwal (2017)

Mobile operating systems

Mobile users and independent application developers create complementary apps, and iOS or Android users download the apps.

Apple Inc., Google LLC

Chen et al. (2016)


Third parties sell their products and services to consumers.

eBay Inc., Alibaba Group

Greenwood and Agarwal (2016)

Online dating service

Men and women exchange information and seek relationships.

Craigslist, Inc.

Greenwood and Wattal (2017)

Online ride-share service

Independent drivers offer their cars and services to riders when and where they want.

Uber Technologies, Inc.

The platformization of the organizational model enhances openness and is in stark contrast to the traditional model that centralizes operations with closed organizational boundaries. Platformization reduces organizational decision-rights ownership and control over the creation of offerings (products and services), as it represents a distributed or decentralized model for production, distribution, or both. For example, Economides and Katsamakas (2006) and Fitzgerald (2006), respectively, discussed Linux and Mozilla Firefox’s open strategies, wherein the core of the product is open-sourced, allowing external contributors to enhance the product. Kapoor and Agarwal (2017) highlighted mobile apps’ provisioning, wherein third-party developers provide mobile apps to Apple users via iOS—a mobile platform.

Platformization involves clear identification of providers and consumers of offerings, as the organization becomes an intermediary to facilitate exchange between or among the two. Further, the exchange model represents the blueprint of transactions between providers and consumers. To create platforms, organizations define the exchange model, identifying and managing transactions between providers and consumers (Hagiu, 2007; Hagiu & Wright, 2014; Thomas, Autio, & Gann, 2014). Prior platform research has differentiated exchange models based on the type of platforms, offerings, or markets where the organization operates (Zhu & Iansiti, 2012). For example, the creation of technological products often requires providers with IT skills, although nondevelopers (e.g., those testing and reporting bugs, or those writing documentation) may also contribute as providers, and product users constitute consumers (Fitzgerald, 2006).2 Highlighting an instance, Helmond (2015) described how Facebook evolved into a platform by enabling exchange between third-party developers creating apps and its users, and Tiwana (2015) studied Mozilla Firefox, a web browser, which allows third-party developers to create add-ons that are used by consumers downloading the browser.

However, organizations platformizing operations through open organizational boundaries go beyond technology products.3 For example, Chen et al. (2016) highlighted how consumer-to-consumer platforms—eBay and—built on a decentralized model of retailing wherein buyers directly connect with the sellers. Similarly, Greenwood and Wattal (2017) emphasized ride-sharing platforms, wherein rides are offered directly by vehicle owners to ride seekers. Table 2 illustrates different types of platformization based on the type of organizational offerings. For nontechnological products, the exchange dynamics—and the associated providers and consumers—may vary across industries. For example, in the restaurant industry, OpenTable has platformized reservations, enabling culinary exchanges between restaurant owners (providers) and restaurant patrons (consumers).

Table 2. Platformizing Organizations With Different Offerings

Offerings for Consumers

Example of Platformized Organization

Traditional Organizational Activity

Platform-based Organizational Activity


Nontechnology Offerings, Inc. (Amazon)

Business-to-consumer e-commerce, representing an organization selling its products over the Internet.

Platformized organizations (e.g., Amazon, eBay) play the role of intermediaries between sellers and buyers, supporting the exchange between third-party sellers and consumers.

Chen et al. (2016)

Uber Technologies, Inc. (Uber)

Taxi companies own cars that are used to give rides to customers, with proprietary and closed software applications used to sell the offerings.

Platformizing ride-sharing, Uber uses software applications to promote third-party providers (drivers), unlike taxi companies that contract drivers and manage vehicles. Platformized organization focuses upon enabling on-demand, near-real-time digital services, allowing vehicle owners to manage rides.

Greenwood and Wattal (2017)

Technology Offerings (Peripheral)

Facebook, Inc. (Facebook)—Application

Organizations do not allow the external creation of peripheral products (extensions). All the functionalities of the software application are created centrally by the organization, with little or no external contributions (e.g., Myspace).

External contributors have access to the application to create peripheral products (extensions). For example, Facebook shares access to users’ data (e.g., Facebook Graph API) with other organizations to facilitate the development of peripheral products (extensions).

Ellison (2008), Helmond (2015)

Apple (iOS), Microsoft (Xbox)—Operating Systems

The creation of new software services (e.g., those related to healthcare, fitness, and finance) restricted to the organization owner of the operating system.

Organizations open their technical architecture, allowing external organizations and individuals to create various peripheral offerings or extensions (e.g., shopping apps, and education apps on Apple iOS).

Cennamo and Santalo (2013), Kapoor and Agarwal (2017), Megerian (2007), Tiwana (2015)

Technology Offerings (Core)

Mozilla Foundation (Firefox)

Creators of applications (e.g., Microsoft—Internet Explorer) build the core with no external contribution.

Organizations invite external contributors to several tasks (e.g., software development, bug reporting, and documentation writing) to enhance the quality of the core application (e.g., Firefox).

Fitzgerald (2006)

Linux Foundation (Linux)

Organizations focus on creating internally the core of proprietary operating systems (e.g., Windows) that provide basic services to operate a handset.

The core software application is publicly shared, allowing the creation of variants of the product following users’ needs.

Economides and Katsamakas (2006)

In the retailing industry, organizations like eBay and Amazon have platformized enabling the exchange of products (e.g., books) between the sellers (providers) and buyers (consumers; Chen et al., 2016). In the transportation industry, organizations like Uber and Lyft have created a platform that enables the exchange of rides between car owners (providers) and prospective riders (consumers; Greenwood & Wattal, 2017). Similarly, social media organization and video- or picture-sharing platforms (e.g., YouTube, Instagram) define text, video, or pictures as the main content of the exchange, with platforms that enable exchange between providers—those creating and uploading videos or pictures—and consumers, who are the viewers of content. Overall, platformization is the process of facilitating direct exchanges—aligning decision rights and economic returns across consumers and providers—after clearly identifying the roles of providers and consumers. More discussion of the business model, including the revenue model and incentive alignment, is presented in the section about why organizations platformize.

Why Do Organizations Platformize?

Why should organizations platformize? Answering the question is important to help organizations discern when platformizing is likely to create value and whether they should platformize at all. Often, research highlights that the underlying reason platformization engenders value is to create network externalities. Providers or consumers, or both, see more significant benefits as a larger number of others join or use the platform. When providers or consumers realize externalities, network effects manifest, changing the marginal utility for existing stakeholders (Katz & Shapiro, 1985; Rochet & Tirole, 2006). That is, platformization influences the benefits of organizational offerings for providers or consumers using the platform. Organizations create value by engendering the network effects through the platform model. For example, network effects may manifest in organizational product development, creating economies of scale or scope. Drawing on a systematic literature review, Thomas et al. (2014) indicated that achieving economies of scale and scope is an important goal of platform ecosystems (Bresnahan & Greenstein, 1999) and product family platforms (Krishnan & Gupta, 2001).

In technology product platforms, through open initiatives (e.g., Open Handset Alliance and Linux Foundation), economies of scale and scope manifest as platformizing by the organization facilitates the creation of product variants by opening the core platform, through open-source licenses (e.g., Android and Linux). Karhu, Gustafsson, and Lyytinen (2018) indicated that organizations exploit the resources shared under open-source licenses to create proprietary competing products. They underline the example of Amazon, which exploited the Android core—using the Android Open Source Project (AOSP)—to create its proprietary Fire OS platform. In general, as organizational activities like product development are distributed over a range of specialized (often community-focused) external actors, platform owners benefit from lower costs of product development (Bresnahan & Greenstein, 1999; Jones, 2003; Krishnan & Gupta, 2001; Muffatto, 1999; Robertson & Ulrich, 1998; Sawhney, 1998). For example, Apple reduces development costs associated with the creation of mobile apps by sharing iOS resources with third-party developers through APIs.

Literature also underlines complexities in leveraging network effects. First, the network effects may be negative (or positive) if existing users derive a lower (or higher) marginal utility (Tiwana, 2013). A negative marginal utility was seen in the case of Facebook’s use by millennials and younger generations, who quit the platform when they found it uncool to share a platform with their parents (Sweney & De Liz, 2018).4 While not common, a negative marginal utility can manifest in organizational settings. For example, a negative marginal utility may arise if the level of differentiation of services and products offered on the platform diminishes, as external organizations join the platform (Evans, 2009). Second, organizations platformizing operations may have to discern the appropriate type of network effect. Specifically, network effects arising due to platformization may be either direct or indirect, with two variants for each, based on the relative benefit and contributions from platform sides (see Table 3). That is, network effects may be direct or indirect depending on the side5 of the platformized organization’s stakeholders being affected when an additional individual stakeholder uses or joins the platform.

Table 3. Network Effects in Two-Sided Platforms

The Beneficiary of the Network Effect



The Contributor to the Network


Direct: More developers (providers) increase the value of the platform for other developers as they create developer communities providing mutual support through knowledge sharing (see Dawande, Johar, Kumar, & Mookerjee, 2008; Ozer & Vogel, 2015). For example, iOS developers collaborate via several online developer communities, such as the iOS developer forum.

Indirect: More providers on the platform (e.g., employers on LinkedIn, video creators on YouTube, app developers on Apple) increase the value of the platform for consumers (e.g., job seekers on LinkedIn, viewers on YouTube, and app users on Apple; Hagiu, 2007). For example, more professionals looking for jobs join LinkedIn if a larger number of jobs are posted.


Indirect: More consumers on the platform (e.g., Uber riders on Uber, app users on Apple) increase the value of the platform for providers (e.g., Uber drivers on Uber, app developers on Apple; Rochet & Tirole, 2003). For example, Uber drivers generate more revenues if more riders book through the platform.

Direct: The value of the platform (e.g., telephone service) for consumers rises as the number of other consumers increase (Farrell & Saloner, 1986; Katz & Shapiro, 1985). For example, a Facebook user is likely to value Facebook more when the number of Facebook users increases. The benefits of connecting with other Facebook users justify how Facebook generates value.

First, when the contributor to the platform and beneficiary of the platform are from the same side6—providers or consumers—the network effects are characterized as direct effects (see Table 1; Clements, 2004; Varian & Shapiro, 1999). For example, in social networking platforms, direct effects manifest as the addition of new end-users increases the value of social networking for other end-users (Gawer & Cusumano, 2014). That is, adding a new consumer of the organizational platform’s offering increases the value of other consumers of the organizational platform’s offerings. Direct effects also manifest when platformizing organizations leverage distributed innovation (Ciborra, 1996; Kogut & Kulatilaka, 1994). Specifically, the organization realizes direct network effects because it benefits from additional external developers’ contributing their expertise for product development. Contributions by diverse developers enhance overall project expertise, creating value for the organizations by catalyzing technology product development, a dynamic seen in the case of development of the iOS platform (see Qiu, Gopa, & Hann, 2017) and Firefox (Tiwana, 2015). In general, direct network effects among developers enable platform owners to take advantage of external actors’ expertise and innovation capabilities to catalyze the creation of complementary products and services (Boudreau, 2010, 2012; Gawer, 2009; Meyer & Lehnerd, 1997; Nambisan & Sawhney, 2011; Wheelwright & Clark, 1992).

Second, when the beneficiaries and contributors are from different sides (e.g., consumers and providers, or providers and consumers), platforms realize indirect network effects (Clements, 2004; Varian & Shapiro, 1999). For example, indirect network effects manifest between advertisers and users, as a new user increases the organization’s value for advertisers (Gawer & Cusumano, 2014). Indirect network effects enhance efficiency, as is seen in various e-commerce platforms. With increasing sellers and consumers of, both sides harness the indirect network effects due to economies of scale, as sellers get access to large consumer base at less cost and consumers get the benefits of lower prices (say, due to smaller shipping charges) because Amazon can negotiate better contracts (say, with shipping companies).

As the number of providers grows, platformized organizations reduce transaction costs related to searching, bargaining, and operations. Falling costs fuel additional platform growth. Because of more significant network effects, platformized organizations realize greater market reach (Eisenmann, Parker, & Van Alstyne, 2006; Rochet & Tirole, 2006). For example, as of 2017, Uber claimed to have 750,000 drivers in the United States, which significantly increased the population’s access to transportation (O’Brien, 2017). Similarly, as of 2019, Airbnb provided more than 6 million listings covering more than 100,000 cities worldwide. Besides the indirect network effects of ride-sharing and home-sharing, indirect network effects lead to reduced costs and platform growth in other contexts, including crowdfunding (e.g., Kickstarter), e-commerce (e.g., Amazon), and dating (e.g., Tinder). In summary, the realization of network effects explains the enormous value created by platform owners, sometimes leading to winner-take-all dynamics (Rochet & Tirole, 2003).

How Do Organizations Platformize?

Previous research has outlined various dynamics that have to be managed by organizations that are platformizing operations. Consistent with the broader information systems (IS) literature, the emerging literature outlines two broad classes of dynamics—technical and organizational (Leonardi & Barley, 2008; Orlikowski, 1992, 2000).

Technical Architecture for Platformization

Literature underlines that platformizing organizations must build effective technical architecture. The technical architecture facilitates collaborative innovation activities and social interactions among producers and consumers through technical instruments, such as online discussion space, and toolkits (Faraj & Shimizu, 2018). In general, platformizing organizations become efficient through their technical architecture, such as built-in advanced search mechanisms and adequate pricing algorithms (Hagiu, 2007; Rochet & Tirole, 2006). Lianos and Motchenkova (2013) focused on technical architecture enabling search capabilities—the ability to provide relevant search results—highlighting its role in establishing two-sided or multisided platforms. Beyond enabling search, technical architecture helps match providers with consumers. For example, Uber increases transaction efficiency through pricing and matching algorithms, and Netflix matches users with movies through intelligent recommendation algorithms. Through advanced technical architecture, Facebook offers targeted advertising services to improve the ability of partners to reach potential consumers (Facebook users). Indeed, Chen et al. (2016) and Wu (2015) emphasized the importance of matching effectiveness between advertisers and publishers for market efficiency and revenue generation on Taobao. And Cramer and Krueger (2016) explained how, in the ride-sharing industry, UberX drivers’ high capacity utilization rate is a direct consequence of matching and pricing abilities. Uber uses geolocalization of drivers and riders to power its real-time matching algorithms, improving the ride-sharing experience for both.

In platformizing, technology capabilities are an important enabler of efficient transactions between providers and consumers. For example, Uber’s capabilities for dynamic pricing match supply with demand, increasing transaction efficiency (Cramer & Krueger, 2016). Further, technical architecture may enable external actors (i.e., third-party developers) to create complementary products and services, as has been seen across various platformized software development organizations, such as Microsoft (Cennamo, Ozalp, & Kretschmer, 2018), Mozilla Foundation (Tiwana, 2015), Apple (Kapoor & Agarwal, 2017), and Google (Foerderer, Kude, Mithas, & Heinzl, 2018). However, because of intense competition, a platformized organization has to build technical architecture that can evolve quickly. The continual evolution of technical architecture is challenging because of the underlying complexity.

Beyond the core architecture, platformized organizations manage a platform ecosystem comprised of various complements—such as add-ons, apps, and plug-ins—that link with the core platform (Gawer, 2014; Tiwana et al., 2010). The technical architecture enables the creation, integration, and performance of these complements, as complementary services extend core architecture’s functionalities (Ghazawneh & Henfridsson, 2011; Tiwana et al., 2010). As the numbers of complements and the associated digital services increase, the platform ecosystem becomes more complex, making it harder to maintain and evolve. Because evolvability is a core technical goal, researchers underline ways to enhance it. Notably, previous research has highlighted various characteristics of the underlying technical architecture. For example, de Reuver, Sorensen, and Basole (2018) argued that technologies evolve faster due to homogenization of data, reprogrammability, and self-referentiality (see also Yoo, Henfridsson, & Lyytinen, 2010).

Notably, two key characteristics—modularity and interoperability—are found to enhance technical architectures’ evolvability. First, modularity represents the degree to which the interacting components of a complex system are independent (Sanchez & Mahoney, 1996). The modularity forms the foundation for decoupling. Decoupling enables recombination, because providers can combine platform technologies with third-party technologies to create and deliver value through innovation (Benlian et al., 2018). Various technical architectural designs are associated with greater modularity, such as web services and XML (Tiwana et al., 2010). Modularity is crucial for evolvability. Changes in complements to core technical architecture may be beyond the firm’s direct control. However, changes in one complement may have unpredictable ramifications throughout the platform ecosystem, affecting other complements’ performance. Evolvability of the ecosystem depends closely on the technical architecture’s ability to limit any adverse ripple effects, and modularity makes components independent, isolating them from the changes elsewhere in the platform ecosystem (Baldwin & Woodard, 2009). Further, Yoo et al. (2010) proposed that a modular architecture increases flexibility—by creating differences in degree—while a layered modular architecture creates generativity—by producing differences in kind. Differences in degree represent variants created by substituting components (e.g., lenses) of a specific product (e.g., camera). Further, differences in kind represent product variants that are product agnostic (e.g., Google Maps can be used as a bundle with cars, mobile phones, computers, and televisions; Yoo et al., 2010).

Beyond modularity, evolvability depends on interoperability. The interoperability of technical architecture facilitates the evolvability of a platform’s technical architecture by enabling the development of complementary innovations. For example, external developers working on products across domains—such as cars, televisions, computers, and mobile phones—use APIs to enhance the product’s interoperability with Google Maps. Previous research has identified various aspects that enhance interoperability. Specifically, achieving interoperability may require the standardization of interfaces through which complements access the technical architecture. Standards are design rules about how to access technical infrastructure (Schilling, 2000). Further, platformized organizations use various boundary resources to enhance interoperability. Boundary resources may include APIs and software development kits (Dal Bianco, Myllärniemi, Komssi, & Raatikainen, 2014; Eaton et al., 2015; Gawer, 2014). Digital technologies’ characteristics, such as homogenous data and self-referentiality, allow organizations to create fluid boundary resources (Yoo et al., 2010). Platformizing organizations build boundary resources that help their technical architecture evolve faster due to greater interoperability with other technologies and platforms.

Organizational Mechanisms: Governance and Incentive Alignment

In addition to building technical architecture, platformizing requires the enactment of effective governance mechanisms and the alignment of incentives between providers and consumers.

Building Governance Mechanisms

Platformizing requires that organizations use appropriate governance mechanisms. A significant aspect of the governance of platforms is to manage the interactions between providers and consumers through the creation of values and rules (Huber, Kude, & Dibbern, 2017). Notably, platform-based organizations regulate interactions among providers and consumers (Altman & Tripsas, 2015). For example, in accordance with iOS developer guidelines (e.g., user privacy protection guidelines), Apple uses several approval procedures to approve a new app (Song, Xue, Rai, & Zhang, 2018). Appropriate governance mechanisms are an effective means for addressing conflicts arising in interactions on the platform ecosystem (Wareham, Fox, & Cano Giner, 2014). For example, to avoid oversupply and hypercompetition, control mechanisms must be put into place to limit the number of complements in the market. In general, governance mechanisms must define appropriate levels of control and openness for managing providers’ contributions (Tiwana et al., 2010). Appropriate controls ensure desirable behaviors (Goldbach, Benlian, & Buxmann, 2018; Tiwana, 2013, 2015; Wiesche, Schermann, & Krcmar, 2011). Platformized organizations with goals to be more flexible in addressing consumers’ needs intend to offer more autonomy to providers, in turn reducing their level of control on the platform. However, they are faced with a trade-off. To limit governance costs, platformized organizations enhance standardization. Increased standardization tends to reduce the providers’ autonomy, in turn increasing the platformized organization’s level of control on the platform.

Prior research on platforms has identified two main types of control mechanisms—formal and informal control mechanisms (Benlian, Hilkert, & Hess, 2015; Tiwana, 2013). Formal platform control mechanisms include output control and process control (Tiwana, 2015). First, output controls formally define the rules. For example, in accordance with iOS developer guidelines (e.g., user privacy protection guidelines), as noted previously, Apple uses several approval procedures to approve a new app (Song et al., 2018). Alternatively, platformized organizations may formally control the contributions of providers through process control mechanisms. Ghazawneh and Henfridsson (2013) focused on platform resources for distributed innovation, highlighting how resourcing and securing mechanisms can help platform owners maintain control over third-party development. For example, Apple influences the development of apps by providing tools (e.g., Xcode) and best practices and guidelines (e.g., usability and user interface guidelines) for developing an iOS app (Ghazawneh & Henfridsson, 2013). Finally, platformized organizations may use clan control. Clan control is an informal mechanism that focuses on creating values, norms, and shared beliefs that guide providers (Tiwana, 2015). For example, platformizing organizations specify values related to creativity (Qiu et al., 2017) and trust (Hurni & Huber, 2014; Perrons, 2009). Such informal controls may be less costly to implement because they require less involvement by platformized organizations.

With suitable levels of control, platformized organizations define appropriate levels of openness. The level of openness influences the participation of external actors (Eisenmann et al., 2009; Ondrus, Gannamaneni, & Lyytinen, 2015; Parker & Van Alstyne, 2018). A high level of openness enhances providers’ access to an organizational platform. Limiting openness restricts providers’ involvement and may hinder the evolvability of the technical architecture. For example, previous research suggests that low platform openness reduces the diversity and growth of activities of external actors (Benlian et al., 2015; Boudreau, 2010). Notably, previous research has highlighted that organizations can open access to external providers, allowing them to contribute to the platform core (e.g., Linux) or the platform complements (e.g., iOS apps; Boudreau, 2010; Karhu et al., 2018). In summary, platformizing organizations require appropriate governance mechanisms to orchestrate exchange interactions between providers and consumers.

Aligning Incentives

Platformizing redefines the exchange model between providers and consumers and requires alignment of incentives between the two. To enable effective exchange, organizations align incentives, focusing on both providers’ and consumers’ interests. Aligning providers’ incentives enables an organization to attract their contributions. Incentives alignment is crucial to promote collective or individual identification (Wareham et al., 2014). For example, the establishment of status might encourage providers to contribute to the greater collective cause in the ecosystem. However, rewards and recognition of individual accomplishments might increase individual identification. Providers may bear costs while contributing to the platform. For example, developers face a learning curve as they learn about a newer operating system or programming language. Reducing development costs enables platforms to attract new external developers and retain existing ones (Anderson et al., 2014). Also, incentives need to be aligned to ensure that consumers continue to use the platform. Because of low switching costs, consumers may not stay with the platform for long. To retain them, organizations may use alternate revenue models. For example, Lerner (2014) indicated that platform participants can monetize user data through targeted advertising, offering products and services cheaply or free (Sokol & Comerford, 2016). In general, to align interests and incentives between providers and consumers, a platformized organization can follow either pricing-based or non-pricing-based mechanisms. Pricing-based approaches include financial subsidies, revenue-sharing mechanisms, or memberships. Platformized organizations may use these approaches to attract providers and consumers or to ensure high-quality contributions or greater participation from them, respectively. In the payment card markets, usage and membership pricing is prevalent (Rochet & Tirole, 2006). Payment card users value markets wherein many merchants are members, while merchants value markets wherein consumers are active users. Alternatively, the fee-based mechanisms are complex, and organizations platformizing operations have to consider various trade-offs. Sur, Lee, and Kim (2019) focused on the platform’s and providers’ payoffs by determining the optimal revenue-sharing rates between the two. Zhang, Cao, and He (2019) contrasted revenue-sharing contracts wherein the platform gets a portion of the manufacturer (provider) revenue with a fixed-fee contract. They found that the platform’s choice of a revenue-sharing contract or a fixed-fee contract can have important implications for consumers’ welfare, as providers under a fixed-fee contract are more likely to create high-quality product than they are under a revenue-sharing contract. Moreover, Foros, Kind, and Shaffer (2017) demonstrated that Apple’s agency model, wherein content providers are subject to a fixed revenue-sharing rule (a 70/30 split, with 70% for the content provider and 30% for Apple), can be detrimental for consumers because it may lead to higher prices.

Indeed, aligning incentives through pricing strategy is crucial for platform success. Liu (2010) indicated the pricing strategy as one reason why Nintendo lost its dominant market position during the console war between Nintendo 64 and Sony’s PlayStation. Focusing on higher quality, Nintendo asked game publishers (the providers) to pay a high royalty fee. However, Sony sought to attract more game publishers through low fees. Also, while charging fees, platformizing organizations might provide financial subsidies through temporary prices and discounts, at times selling below the marginal costs, as is done by gaming platforms during product launches (Parker & Van Alstyne, 2014). Indeed, choosing an optimal revenue strategy is not easy. Although previous examples characterize paid exchanges between providers and consumers, many offerings may be (monetarily) freely accessible (Chen et al., 2016). Offering the service for free may perform better than a revenue-based strategy, facilitating greater participation from providers and consumers. For example, often, social media organizations enable nonmonetary exchanges between providers and consumers. Focusing on free information goods, Parker and Van Alstyne (2000) showed that firms can generate profits when providing information goods for free due to positive network externalities.

Besides pricing-based approaches, platformized organizations rely on non-pricing-based approaches to align incentives between providers and consumers. Price may not always be an effective mechanism for coordination, calling for the platform-based organization to regulate access and interactions among providers and consumers (Boudreau & Hagiu, 2009). As an example of using a non-price-based approach, granting intellectual property rights (IPR) is known to encourage developer participation. A platform organization may share the IPR of dedicated resources with other organizations or even forfeit them (Karhu et al., 2018). For example, MontaVista shares ownership of its products with software developers (Boudreau, 2010). Other platformized organizations might choose to release resources with an open-source license, encouraging participation from developers keen to use the product. For example, common incentives to promote user innovation include the lead-user method to identify attractive user innovations, toolkits to outsource product design to users, and crowdsourcing to create innovation contests (Franke & Luthje, 2020).

Often, organizational strategies also help align incentives. Additional nonmonetary incentives may include innovation investments, quality, and advertising (Rysman, 2009). For example, advertising for providers influences the value of the platform for consumers. Huang, Ceccagnoli, Forman, and Wu (2013) indicated that independent software vendors (ISVs) are more likely to join a platform creating complementary products and services when they have strong IPR (e.g., patents and copyrights) and downstream capabilities (e.g., trademarks). Platform multihoming—allowing complements to operate on multiple and sometimes competing platforms (Cennamo et al., 2018)—enables greater participation by external developers, as it reduces development costs and switching barriers across competing platforms (see Armstrong & Wright, 2007; Cennamo et al., 2018; Eisenmann et al., 2006; Katz & Shapiro, 1994). In general, complementary innovation occurs under various forms, including bilateral partnership (e.g., SAP quality certification process; Ceccagnoli, Forman, Huang, & Wu, 2012), innovation contests (e.g., coding contests; see Boudreau, Lacetera, & Lakhani, 2011), and open participation (e.g., Google developer program; Wareham et al., 2014). Studying complementor’s success, Li and Agarwal (2016) concluded that platform integration between Facebook and Instagram has an overall positive effect on the complementary market as it increases market demand for those providing offerings on these platforms. Another important aspect influencing performance is platform envelopment—whereby one platform bundles key features from another, typically smaller, platform, making the latter irrelevant to the market (Eisenmann, Parker, & Van Alstyne, 2011). Envelopment is a well-known method for new entrants to compete with an incumbent platform.


Platformization is an important aspect of the economy that is engendering new organizational strategies while disrupting traditional business models across different industries, such as software development, transportation, and entertainment, among others. Altman and Tripsas (2015) suggested that the transition from a product-based business model to a platform-based business model is complex. Therefore, widespread platformization warrants a better scientific understanding, as the core tenets enabling organizations to platformize are still equivocal. To unravel these tenets, this article synthesizes previous research studying platforms that enable the exchange of products, information, and service offerings. Specifically, the article builds a nomological network around platformizing research, by addressing three core questions: What is platfomization? How do organizations platformize? Why do organizations platformize?

To answer the first question, platfomization is defined as the process of identifying providers and consumers and increasing the directness of exchange between or among the two. To answer why organizations may want to platformize requires understanding the role of network effects. Organizations are driven by creating a positive network effect that engenders efficiency gains. Finally, to answer how organizations platformize requires considering technical and organizational factors. First, organizations have to build a technical architecture that enables exchange; the technical architecture includes various factors that enhance modularity and interoperability, for continued evolvability of the technical platform. Second, to facilitate effective exchange, organizational mechanisms—governance and incentive alignment mechanisms—are required.

The answers to these questions extend the understanding of platforms. Most previous research has examined platforms from a technical or economic perspective, but by specifically focusing on different facets of platformization and integrating them, this article offers an organizational perspective on platformizing. That is, it synthesizes findings most relevant for mainstream organizations keen to platformize. For organizational scholars, this review contributes by providing conceptual clarity about platformization, offering an inclusive definition. Prior literature indicates that the existence of distinct and nonoverlapping definitions of platform compromises conceptual clarity (de Reuver et al., 2018). Platforms have been defined differently from separate views (i.e., the technical view or the economic view; Schreieck et al., 2016). By presenting a definition of platformization from an organizational perspective, this article incorporates the nuanced findings from both technical and economic views. Furthermore, the discussion connects disparate findings related to the economic and technical aspects by describing platformization mechanisms in organizations.

By focusing on mainstream organizations, this article extends the broad IS strategy research that discusses the different ways that organizations gain competitive advantage. Previous IS research has used various strategic frameworks, such as the capability view (see Pavlou & El Sawy, 2010; Setia & Patel, 2013; Setia, Venkatesh, & Joglekar, 2013; Teece, Pisano, & Shuen, 1997) or the resource-based view (see Bharadwaj, 2000; Mata, Fuerst, & Barney, 1995; Oh & Pinsonneault, 2007; Wade & Hulland, 2004), strategy-conduct performance (Domowitz, Hubbard, & Petersen, 1986; Porter, 1985), positioning-based logic (see Porter, 1980, 1996, 2001), and opportunity-based logic (see Schumpeter, 1934, 1950). More recently, platformization has emerged as a major paradigm-shifting strategy, as organizations go beyond merely focusing on effectively selecting or deploying resources within closed boundaries or managing their environments. This article extends the previous research in IS strategy by outlining how and why organizations platformize. By including nontechnology products, the article also extends previous research that has predominantly focused on technology products to highlight platform dynamics for software development. Overall, the article extends IS research by elaborating on the notion of platformization from an organizational strategy perspective, outlining platformization as a strategic initiative to leverage network effect, by managing with open boundaries.

Furthermore, the article unravels various platform dynamics that extend the business value of IT research, contributing a better understanding of value creation. Previous research has enhanced understanding of digital strategies that create value across organizational domains, such as new product or innovation development (see Pavlou & El Sawy, 2006) or customer service (Setia et al., 2013). This work has been extended by the focus on platformization: for example, platformization has changed the way organizations develop innovations. Previous research has examined the role of IT in creating a competitive advantage by reconfiguring business processes, mostly within a focal organization’s boundary (Pavlou & El Sawy, 2006). Related research examining open-source innovations has examined how organizations may leverage external developers (Setia et al., 2012; Setia, Bayus, & Rajagopalan, 2020). Organizations are keen to leverage open forms for innovating, and researchers have highlighted issues required for developing open-source innovations (Fitzgerald, 2006). This article extends the domains of these works by outlining the dynamics in a special model of innovation that leverages platforms. Notably, it emphasizes dynamics that may help organizations leverage platforms for catalyzing the quantity and quality of technology products and other innovations.

Platformization also has implications for IS researchers interested in the use of digital technologies for customer service or e-commerce. Previous IS research has highlighted various dynamics in these domains. For example, Ray, Muhanna, and Barney (2005) examined how IT brings strategic values to provide quality customer service, and Setia et al. (2013) discussed localized IT impacts on the organization’s sensing and responding capabilities and customer service performance. Previous research in the domain has used traditional strategy frameworks to study dynamics within the boundaries of the organization. However, service and e-commerce dynamics are now being platformized by various organizations, such as Amazon, Uber, and Google. Recent research has begun to highlight these customer service dynamics. For example, Lusch and Nambisan (2015) focused on service-dominant logic, highlighting the value of IT in facilitating collaborative innovation creation in ecosystems and platforms. By highlighting core platform dynamics—such as the development of technical architecture, service exchange, governance mechanisms, and incentive alignment—that organizations platformizing service offerings may leverage, this article contributes to the emerging body of work.

Future research has opportunities to examine many interesting questions. First, research could examine organizational mechanisms that help platformize business models. Notably, research can identify the most influential contingency factors that reinforce or hinder an organization’s pursuit of platformization. Second, research could examine differences in the process of platformizing. Are there certain paths that lead to more effective platformization? Also, researchers could focus on the stage of platformization and examine the types of governance mechanisms and technology infrastructure that are most appropriate in different stages of platformization. Finally, researchers have started to link the transition to platformization with organizational identity (Altman & Tripsas, 2015). Future research could examine the nature of change in organizational identity, identifying the dimensions of organizational identity that are most likely to change and the ones that are likely to remain unchanged despite evolution of the business model due to platformization. Research could also examine if there are important interdependencies across organizational identities that transform due to platformization.

Finally, this article has practical implications for managers keen to build platforms. Platformization has important implications for entrepreneurs because it catalyzes the creation of businesses, generating and delivering value to end-users or consumers through the provisioning of core infrastructure (Nambisan et al., 2018). Further, as platformization has become popular among mainstream organizations with nontechnology offerings, the dynamics described here can help practitioners enact platform business models. Because previous works have focused largely on understanding the platformization of technology products, the findings reviewed here offer a strong theoretical foundation for nontechnology organizations, offering them core tenets for platformizing operations. By answering the what, how, and why of platformization, the article offers organizations a roadmap for platformization, outlining the basic elements a platform encompasses, the key steps in platformizing, and the potential business value platformization may bring.

In summary, this article contributes to efforts to untangle important dynamics of platforms, integrating technical and economic aspects of platforms from an organizational perspective. It provides an integrated understanding that can guide future research on organizational issues related to platformization.


  • Altman, E. J., & Tripsas, M. (2015). Product to platform transitions: Implications of organizational identity. In C. Shalley, M. Hitt, & J. Zhou (Eds.), Oxford handbook of creativity, innovation, and entrepreneurship: Multilevel linkages (pp. 379–394) Oxford, UK: Oxford University Press.
  • Anderson, E. G., Jr., Parker, G. G., & Tan, B. (2014). Platform performance investment in the presence of network externalities. Information Systems Research, 25(1), 152–172.
  • Angrist, J. D., Caldwell, S., & Hall, J. V. (2017). Uber vs. taxi: A drivers eye view (No. w23891). Cambridge, MA: National Bureau of Economic Research.
  • Armstrong, M., & Wright, J. (2007). Two-sided markets, competitive bottlenecks and exclusive contracts. Economic Theory, 32(2), 353–380.
  • Baldwin, C. Y., & Woodard, C. J. (2009). The architecture of platforms: A unified view. In A. Gawer (Ed.), Platforms, markets and innovation (pp. 19–44). Cheltenham, UK: Edward Elgar.
  • Bharadwaj, A. S. (2000). A resource-based perspective on information technology capability and firm performance: An empirical investigation. MIS Quarterly, 24(1), 169–196.
  • Bakos, Y., & Katsamakas, E. (2008). Design and ownership of two-sided networks: Implications for Internet platforms. Journal of Management Information Systems, 25(2), 171–202.
  • Benlian, A., Hilkert, D., & Hess, T. (2015). How open is this platform? The meaning and measurement of platform openness from the complementers’ perspective. Journal of Information Technology, 30(3), 209–228.
  • Benlian, A., Kettinger, W. J., Sunyaev, A., Winkler, T. J., & Guest Editors. (2018). The transformative value of cloud computing: A decoupling, platformization, and recombination theoretical framework. Journal of Management Information Systems, 35(3), 719–739.
  • Boudreau, K. (2010). Open platform strategies and innovation: Granting access vs. devolving control. Management Science, 56(10), 1849–1872.
  • Boudreau, K. J. (2012). Let a thousand flowers bloom? An early look at large numbers of software app developers and patterns of innovation. Organization Science, 23(5), 1409–1427.
  • Boudreau, K. J., & Hagiu, A. (2009). Platform rules: Multi-sided platforms as regulators. In A. Gawer (Ed.), Platforms, markets and innovation (pp. 163–191). Cheltenham, UK: Edward Elgar.
  • Boudreau, K. J., Lacetera, N., & Lakhani, K. R. (2011). Incentives and problem uncertainty in innovation contests: An empirical analysis. Management Science, 57(5), 843–863.
  • Bresnahan, T. F., & Greenstein, S. (1999). Technological competition and the structure of the computer industry. The Journal of Industrial Economics, 47(1), 1–40.
  • Ceccagnoli, M., Forman, C., Huang, P., & Wu, D. J. (2012). Cocreation of value in a platform ecosystem! The case of enterprise software. MIS Quarterly, 36(1), 263–290.
  • Cennamo, C. (2019). Competing in digital markets: A platform-based perspective. Academy of Management Perspectives.
  • Cennamo, C., & Santalo, J. (2013). Platform competition: Strategic trade-offs in platform markets. Strategic Management Journal, 34(11), 1331–1350.
  • Cennamo, C., Ozalp, H., & Kretschmer, T. (2018). Platform architecture and quality trade-offs of multihoming complements. Information Systems Research, 29(2), 461–478.
  • Chen, J., Fang, M., & Li, M. (2016). Advertising versus brokerage model for online trading platforms. MIS Quarterly, 40(3), 575–596.
  • Ciborra, C. U. (1996). The platform organization: Recombining strategies, structures, and surprises. Organization Science, 7(2), 103–118.
  • Clements, M. T. (2004). Direct and indirect network effects: Are they equivalent? International Journal of Industrial Organization, 22(5), 633–645.
  • Cramer, J., & Krueger, A. B. (2016). Disruptive change in the taxi business: The case of Uber. American Economic Review, 106(5), 177–182.
  • Dal Bianco, V., Myllärniemi, V., Komssi, M., & Raatikainen, M. (2014). The role of platform boundary resources in software ecosystems: A case study. In 11th working IEEE/IFIP Conference on Software Architecture, WICSA 2014, 7 April 2014–11 April 2014 (pp. 11–20). Sydney, NSW; Australia.
  • Dawande, M., Johar, M., Kumar, S., & Mookerjee, V. S. (2008). A comparison of pair versus solo programming under different objectives: An analytical approach. Information Systems Research, 19(1), 71–92.
  • de Reuver, M., Sørensen, C., & Basole, R. C. (2018). The digital platform: A research agenda. Journal of Information Technology, 33(2), 124–135.
  • Domowitz, I., Hubbard, R. G., & Petersen, B. C. (1986). Business cycles and the relationship between concentration and price-cost margins. The RAND Journal of Economics, 17, 1–17.
  • Eaton, B., Elaluf-Calderwood, S., Sorensen, C., & Yoo, Y. (2015). Distributed tuning of boundary resources: The case of Apple’s iOS service system. MIS Quarterly, 39(1), 217–243.
  • Economides, N., & Katsamakas, E. (2006). Two-sided competition of proprietary vs. open source technology platforms and the implications for the software industry. Management Science, 52(7), 1057–1071.
  • Ellison, N. B. (2008). Introduction: Reshaping campus communication and community through social network sites. In G. Salaway, J. Borreson, & M. R. Nelson (Vol. Ed.), The ECAR study of undergraduate students and information technology, Vol 8 (pp. 19–32). Educause Center for Applied Research. Boulder, CO: Educause.
  • Eisenmann, T. R., Parker, G., & Van Alstyne, M. (2006). Strategies for two sided markets. Harvard Business Review, 84(10), 92–101.
  • Eisenmann, T. R., Parker, G., & Van Alstyne, M. (2009). Opening platforms: How, when and why? In A. Gawer (Ed.), Platforms, markets and innovation (pp. 131–162). Cheltenham, UK: Edward Elgar.
  • Eisenmann, T. R., Parker, G., & Van Alstyne, M. (2011). Platform envelopment. Strategic Management Journal, 12, 1270–1285.
  • Evans, D. (2009). How catalysts ignite: The economics of platform-based start-ups. In A. Gawer (Ed.), Platforms, markets and innovation (pp. 99–130). Cheltenham, UK: Edward Elgar.
  • Faraj, S., & Shimizu, T. (2018). Online communities and knowledge collaborations. In R. Aldag (Ed.), Oxford research encyclopedia of business and management (pp. 1–18). Oxford, UK: Oxford University Press.
  • Farrell, J., & Saloner, G. (1986). In J. Miller (Ed.), Economic issues in standardization in Telecommunications and equity: Policy research issues (pp. 165–178). North-Holland.
  • Fitzgerald, B. (2006). The transformation of open source software. MIS Quarterly, 30(3), 587–598.
  • Foerderer, J., Kude, T., Mithas, S., & Heinzl, A. (2018). Does platform owner’s entry crowd out innovation? Evidence from Google photos. Information Systems Research, 29(2), 444–460.
  • Foros, Ø., Kind, H. J., & Shaffer, G. (2017). Apple’s agency model and the role of most-favored-nation clauses. The RAND Journal of Economics, 48(3), 673–703.
  • Franke, N., & Lüthje, C. (2020). User innovation. In Oxford research encyclopedia of business and management (pp. 1–32). Oxford, UK: Oxford University Press.
  • Gawer, A. (2009). Platforms, markets and innovation: An introduction. Cheltenham, UK: Edward Elgar.
  • Gawer, A. (2014). Bridging differing perspectives on technological platforms: Toward an integrative framework. Research Policy, 43(7), 1239–1249.
  • Gawer, A., & Cusumano, M. A. (2014). Industry platforms and ecosystem innovation. Journal of Product Innovation Management, 31(3), 417–433.
  • Ghazawneh, A., & Henfridsson, O. (2011). Micro-strategizing in platform ecosystems: A multiple case study. In 32nd International Conference on Information Systems 2011, ICIS 2011 (Vol. 5, pp. 4202-4220), 4 December 2011–7 December 2011. Shanghai, China.
  • Ghazawneh, A., & Henfridsson, O. (2013). Balancing platform control and external contribution in third-party development: The boundary resources model. Information Systems Journal, 23(2), 173–192.
  • Goldbach, T., Benlian, A., & Buxmann, P. (2018). Differential effects of formal and self-control in mobile platform ecosystems: Multi-method findings on third-party developers’ continuance intentions and application quality. Information & Management, 55(3), 271–284.
  • Greenwood, B. N., & Agarwal, R. (2016). Matching platforms and HIV incidence: An empirical investigation of race, gender, and socioeconomic status. Management Science, 62(8), 2281–2303.
  • Greenwood, B. N., & Wattal, S. (2017). Show me the way to go home: An empirical investigation of ride-sharing and alcohol-related motor vehicle fatalities. MIS Quarterly, 41(1), 163–187.
  • Hagiu, A. (2007). Merchant or two-sided platform? Review of Network Economics, 6(2), 115–133.
  • Hagiu, A., & Wright, J. (2014). Marketplace or reseller? Management Science, 61(1), 184–203.
  • Helmond, A. (2015). The platformization of the web: Making web data platform ready. Social Media + Society, 1(2), 2056305115603080.
  • Huang, P., Ceccagnoli, M., Forman, C., & Wu, D. J. (2013). Appropriability mechanisms and the platform partnership decision: Evidence from enterprise software. Management Science, 59(1), 102–121.
  • Huber, T. L., Kude, T., & Dibbern, J. (2017). Governance practices in platform ecosystems: Navigating tensions between cocreated value and governance costs. Information Systems Research, 28(3), 563–584.
  • Hurni, T., & Huber, T. (2014). The interplay of power and trust in platform ecosystems of the enterprise application software industry. In 22nd European Conference on Information Systems, ECIS 2014, 9 June 2014–11 June 2014. Tel Aviv, Israel.
  • Jones, N. (2003). Competing after radical technological change: The significance of product line management strategy. Strategic Management Journal, 24(13), 1265–1287.
  • Kapoor, R., & Agarwal, S. (2017). Sustaining superior performance in business ecosystems: Evidence from application software developers in the iOS and Android smartphone ecosystems. Organization Science, 28(3), 531–551.
  • Karhu, K., Gustafsson, R., & Lyytinen, K. (2018). Exploiting and defending open digital platforms with boundary resources: Android’s five platform forks. Information Systems Research, 29(2), 479–497.
  • Katz, M. L., & Shapiro, C. (1985). Network externalities, competition, and compatibility. American Economic Review, 75(3), 424–440.
  • Katz, M. L., & Shapiro, C. (1994). Systems competition and network effects. Journal of Economic Perspectives, 8(2), 93–115.
  • Khan, F. (2016). The Uberization of healthcare: The forthcoming legal storm over mobile health technology’s impact on the medical profession. Health Matrix, 26, 123–172.
  • Kogut, B., & Kulatilaka, N. (1994). Options thinking and platform investments: Investing in opportunity. California Management Review, 2, 52–71.
  • Krishnan, V., & Gupta, S. (2001). Appropriateness and impact of platform-based product development. Management Science, 47(1), 52–68.
  • Lee, H. L., Padmanabhan, V., & Whang, S. (1997). Information distortion in a supply chain: The bullwhip effect. Management Science, 43(4), 546–558.
  • Leonardi, P. M., & Barley, S. R. (2008). Materiality and change: Challenges to building better theory about technology and organizing. Information and Organization, 18(3), 159–176.
  • Li, Z., & Agarwal, A. (2016). Platform integration and demand spillovers in complementary markets: Evidence from Facebook’s integration of Instagram. Management Science, 63(10), 3438–3458.
  • Lianos, I., & Motchenkova, E. (2013). Market dominance and search quality in the search engine market. Journal of Competition Law & Economics, 9(2), 419–455.
  • Liu, H. (2010). Dynamics of pricing in the video game console market: Skimming or penetration? Journal of Marketing Research, 47(3), 428–443.
  • Lusch, R. F., & Nambisan, S. (2015). Service innovation: A service-dominant logic perspective. MIS Quarterly, 39(1), 155–176.
  • Mantena, R., & Saha, R. L. (2012). Co-opetition between differentiated platforms in two-sided markets. Journal of Management Information Systems, 29(2), 109–140.
  • Mata, F. J., Fuerst, W. L., & Barney, J. B. (1995). Information technology and sustained competitive advantage: A resource-based analysis. MIS Quarterly, 19(4), 487–505.
  • Meyer, M. H., & Lehnerd, A. P. (1997). The power of product platforms. New York: The Free Press.
  • Muffatto, M. (1999). Introducing a platform strategy in product development. International Journal of Production Economics, 60–61, 145–153.
  • Nambisan, S., & Sawhney, M. (2011). Orchestration processes in network-centric innovation: Evidence from the field. Academy of Management Perspectives, 25(3), 40–57.
  • Nambisan, S., Siegel, D., & Kenney, M. (2018). On open innovation, platforms, and entrepreneurship. Strategic Entrepreneurship Journal, 12(3), 354–368.
  • Nieborg, D. B., & Helmond, A. (2019). The political economy of Facebook’s platformization in the mobile ecosystem: Facebook Messenger as a platform instance. Media, Culture & Society, 41(2), 196–218.
  • Oh, W., & Pinsonneault, A. (2007). On the assessment of the strategic value of information technologies: Conceptual and analytical approaches. MIS Quarterly, 31(2), 239–265.
  • Ondrus, J., Gannamaneni, A., & Lyytinen, K. (2015). The impact of openness on the market potential of multi-sided platforms: A case study of mobile payment platforms. Journal of Information Technology, 30(3), 260–275.
  • Orlikowski, W. J. (1992). The duality of technology: Rethinking the concept of technology in organizations. Organization Science, 3(3), 398–427.
  • Orlikowski, W. J. (2000). Using technology and constituting structures: A practice lens for studying technology in organizations. Organization Science, 11(4), 404–428.
  • Ozer, M., & Vogel, D. (2015). Contextualized relationship between knowledge sharing and performance in software development. Journal of Management Information Systems, 32(2), 134–161.
  • Parker, G. G., & Van Alstyne, M. W. (2000). Internetwork externalities and free information goods. In Proceedings of the 2nd ACM Conference on Electronic Commerce, Minneapolis Minnesota USA, October 2000 (pp. 107–116). New York, NY, United States: Association for Computing Machinery.
  • Parker, G., & Van Alstyne, M. W. (2014). Platform strategy. The Palgrave Encyclopedia of Strategic Management. In M. Augier & D. J. Teece (Eds.), ISBN 978-1-137-49190-9. Palgrave Macmillan UK, 2016 (Working Paper No. 2439323). Boston University School of Management Research Paper.
  • Parker, G., & Van Alstyne, M. (2018). Innovation, openness, and platform control. Management Science, 64(7), 3015–3032.
  • Parker, G., Van Alstyne, M., & Jiang, X. (2017). Platform ecosystems: How developers invert the firm. MIS Quarterly, 41(1), 255–266.
  • Pavlou, P. A., & El Sawy, O. A. (2006). From IT leveraging competence to competitive advantage in turbulent environments: The case of new product development. Information Systems Research, 17(3), 198–227.
  • Pavlou, P. A., & El Sawy, O. A. (2010). The third hand: IT-enabled competitive advantage in turbulence through improvisational capabilities. Information Systems Research, 21(3), 443–471.
  • Perrons, R. K. (2009). The open kimono: How Intel balances trust and power to maintain platform leadership. Research Policy, 38(8), 1300–1312.
  • Porter, M. E. (1980). Competitive strategy. New York, NY: Free Press.
  • Porter, M. E. (1985). Competitive advantage. New York, NY: Free Press.
  • Porter, M. E. (1996). Competitive advantage, agglomeration economies, and regional policy. International Regional Science Review, 19(1-2), 85–90.
  • Porter, M. E. (2001). Strategy and the Internet. Harvard Business Review, 79(3), 62–78.
  • Qiu, Y., Gopal, A., & Hann, I. H. (2017). Logic pluralism in mobile platform ecosystems: A study of indie app developers on the iOS app store. Information Systems Research, 28(2), 225–249.
  • Ray, G., Muhanna, W. A., & Barney, J. B. (2005). Information technology and the performance of the customer service process: A resource-based analysis. MIS Quarterly, 29(4), 625–652.
  • Robertson, D., & Ulrich, K. (1998). Planning for product platforms. Sloan Management Review, 39(4), 19–31.
  • Rochet, J. C., & Tirole, J. (2003). Platform competition in two-sided markets. Journal of the European Economic Association, 1(4), 990–1029.
  • Rochet, J. C., & Tirole, J. (2006). Externalities and regulation in card payment systems. Review of Network Economics, 5(1), 1–14.
  • Rysman, M. (2009). The economics of two-sided markets. Journal of Economic Perspectives, 23(3), 125–143.
  • Sanchez, R., & Mahoney, J. T. (1996). Modularity, flexibility, and knowledge management in product and organization design. Strategic Management Journal, 17(S2), 63–76.
  • Sawhney, M. S. (1998). Leveraged high-variety strategies: From portfolio thinking to platform thinking. Journal of the Academy of Marketing Science, 26(1), 54–61.
  • Schilling, M. A. (2000). Toward a general modular systems theory and its application to interfirm product modularity. Academy of Management Review, 25(2), 312–334.
  • Schreieck, M., Wiesche, M., & Krcmar, H. (2016). Design and governance of platform ecosystems—Key concepts and issues for future research. In Proceedings of Twenty-Fourth European Conference on Information Systems (ECIS), 12 June 2016–15 June 2016, Bogazici University, Istanbul, Turkey.
  • Schumpeter, J. A. (1934). The theory of economic development. Cambridge, MA: Harvard University Press.
  • Schumpeter, J. A. (1950). The march into socialism. The American Economic Review, 40(2), 446–456.
  • Setia, P., Bayus, B., & Rajagopalan, B. (2020). The takeoff of open source software: A signaling perspective based on community activities. MIS Quarterly, 44(3), 1439–1458.
  • Setia, P., & Patel, P. C. (2013). How information systems help create OM capabilities: Consequents and antecedents of operational absorptive capacity. Journal of Operations Management, 31(6), 409–431.
  • Setia, P., Rajagopalan, B., Sambamurthy, V., & Calantone, R. (2012). How peripheral developers contribute to open-source software development. Information Systems Research, 23(1), 144–163.
  • Setia, P., Venkatesh, V., & Joglekar, S. (2013). Leveraging digital technologies: How information quality leads to localized capabilities and customer service performance. MIS Quarterly, 37(2), 565–590.
  • Sokol, D. D., & Comerford, R. (2016). Antitrust and regulating big data. George Mason Law Review, 23, 1129–1162.
  • Song, P., Xue, L., Rai, A., & Zhang, C. (2018). The ecosystem of software platform: A study of asymmetric cross-side network effects and platform governance. MIS Quarterly, 42(1), 121–142.
  • Sur, M., Lee, D. J., & Kim, K. T. (2019). Optimal revenue sharing in platform markets: A Stackelberg model. Journal of Revenue and Pricing Management, 18(4), 1–15.
  • Teece, D. J., Pisano, G., & Shuen, A. (1997). Dynamic capabilities and strategic management. Strategic Management Journal, 18(7), 509–533.
  • Thomas, L. D., Autio, E., & Gann, D. M. (2014). Architectural leverage: Putting platforms in context. Academy of Management Perspectives, 28(2), 198–219.
  • Tiwana, A. (2013). Platform ecosystems: Aligning architecture, governance, and strategy. Waltham, MA: Morgan Kaufmann.
  • Tiwana, A. (2015). Platform desertion by app developers. Journal of Management Information Systems, 32(4), 40–77.
  • Tiwana, A., Konsynski, B., & Bush, A. A. (2010). Research commentary—Platform evolution: Coevolution of platform architecture, governance, and environmental dynamics. Information Systems Research, 21(4), 675–687.
  • Vachon, S., & Klassen, R. D. (2006). Extending green practices across the supply chain: The impact of upstream and downstream integration. International Journal of Operations & Production Management, 26(7), 795–821.
  • Varian, H., & Shapiro, C. (1999). Information rules: A strategic guide to the network economy. Boston, MA: Harvard Business School Press.
  • Wade, M., & Hulland, J. (2004). The resource-based view and information systems research: Review, extension, and suggestions for future research. MIS Quarterly, 28(1), 107–142.
  • Wareham, J., Fox, P. B., & Cano Giner, J. L. (2014). Technology ecosystem governance. Organization Science, 25(4), 1195–1215.
  • Wheelwright, S. C., & Clark, K. B. (1992). Revolutionizing product development: Quantum leaps in speed, efficiency, and quality. New York: Free Press.
  • Wiesche, M., Schermann, M., & Krcmar, H. (2011). Understanding the role of information technology for organizational control design: Risk control as new control mechanism. In M. Nüttgens, A. Gadatsch, K. Kautz, I. Schirmer, & N. Blinn (Eds.), IFIP WG 8.6 International Working Conference on Governance and Sustainability in Information Systems—Managing the transfer and diffusion of IT (pp. 135–152). Hamburg, Germany: Springer.
  • Wu, C. (2015). Matching value and market design in online advertising networks: An empirical analysis. Marketing Science, 34(6), 906–921.
  • 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.
  • Zervas, G., Proserpio, D., & Byers, J. W. (2017). The rise of the sharing economy: Estimating the impact of Airbnb on the hotel industry. Journal of Marketing Research, 54(5), 687–705.
  • Zhang, J., Cao, Q., & He, X. (2019). Contract and product quality in platform selling. European Journal of Operational Research, 272(3), 928–944.
  • Zhu, F., & Iansiti, M. (2012). Entry into platform-based markets. Strategic Management Journal, 33(1), 88–106.


  • 1. Greenwood and Agarwal (2016) observed that, in Florida, after the introduction of Craigslist—a platform where people connected for casual sex—the incidence rate of HIV increased heterogeneously across race and socioeconomic status. Moreover, Greenwood and Wattal (2017) found a drop in alcohol-related motor vehicle fatalities after the implementation of Uber Black and UberX in California.

  • 2. As an instance, the gaming platforms (e.g., Xbox) selectively platformize the peripheral software—gaming apps—rather than platformizing the development of the core gaming platform itself (e.g., Xbox, Xbox OS; see Kapoor & Agarwal, 2017; Tiwana, 2015). For the creators of gaming apps–exchange happens between (a) developers and nondevelopers–providers in the platform model, and (b) game players–consumers. The developers on the core gaming platform may not be providers (unless they interact with community developers participating on the platform).

  • 3. Technological products are information technology (IT) artefacts, such as software and hardware. Examples of technological products include phone platforms (e.g., iPhone), mobile operating system (OS) platforms (e.g., iOS), and gaming platforms (e.g., Xbox). However, nontechnological products are any products whose creation does not involve software or hardware development. Examples of nontechnological products include music and videos.

  • 4. According to the recent Pew Research Center Survey, 51% of American teenagers between 13 and 17 years old use Facebook. The survey results show a big shift from results obtained in 2014–2015, when 71% of teenagers were reportedly Facebook users (Seth, 2019).

  • 5. Platforms may be two-sided or multisided, with each side representing a distinct group of users. For example, the two sides may be buyers and sellers in e-commerce sites (such as, men and women in dating sites (such as, or employers and employees in job search sites (such as, or, more generally, providers and consumers. In other research domains, notably in economics, in-depth discussions have highlighted the two-sided or multisided nature of nontechnological platforms, as well. For example, Rysman (2009) articulated the economics of two-sided markets in some select industries and discussed key platform strategies, including pricing, openness, innovation investment, quality, and advertising.

  • 6. Side may be conceptualized as a set of stakeholders.