List of figures
List of tables
List of abbreviations
1 Introduction
1.1 Research field and relevance
1.2 Research question and approach
1.3 Outline
2 Theory
2.1 Platform-centric ecosystems
2.1.1 Product platforms
2.1.2 Industry platforms
2.1.3 Multi-sided platforms
2.1.4 Complementary innovation
2.1.5 Platform architecture
2.1.6 Platform participants
2.1.7 Platform dynamics
2.2 Platform management
2.2.1 Platform strategies
2.2.2 Platform organization and governance
3 Towards an integrated view: the determinants of platform-centric ecosystems and their implications for complementary innovation
3.1 Platform strategy
3.1.1 Degree of openness
3.1.2 Market organization for complementors
3.2 Platform organization
3.2.1 Verticality
3.2.2 Internal and interfirm organization
3.3 Platform architecture
3.3.1 Modularity
3.3.2 Technical boundary resources
3.4 Complementary asset position
3.5 Appropriability regime
3.6 Industry architecture
4 Examining complementary innovation in platform-centric ecosystems: in-depth case study research on ARM and AWS
4.1 Research methodology
4.1.1 Research design
4.1.2 Data collection and analysis
4.2 ARM, the next Intel? How the ‘fab-less’ and ‘chip-less’ licensor of processor IP designs created a leading semiconductor platform ecosystem
4.2.1 Company and platform ecosystem overview
4.2.2 Platform strategy
4.2.3 Platform organization
4.2.4 Platform architecture
4.2.5 Complementary asset position
4.2.6 Appropriability regime
4.2.7 Industry architecture
4.3 AWS, beyond e-retailing: how the online bookstore Amazon built a leading platform and partner ecosystem for cloud computing services
4.3.1 Company and platform ecosystem overview
4.3.2 Platform strategy
4.3.3 Platform organization
4.3.4 Platform architecture
4.3.5 Complementary asset position
4.3.6 Appropriability regime
4.3.7 Industry architecture
5 Discussion
5.1 Theoretical implications
5.2 Managerial implications
6 Conclusion
6.1 Summary of findings
6.2 Limitations and future research
6.3 Concluding remarks
References
Appendix
Figure 1: Schematic representation of a platform-centric ecosystem
Figure 2: An integrated framework of the determinants of platform-centric ecosystems that influence complementary innovation
Figure 3: ARM’s platform ecosystem and partnership relations
Figure 4: AWS‘s cloud computing platform and partner ecosystem
Figure 4: AWS’s cloud computing platform and partner ecosystem
Table 1: Platform strategies with corresponding trade-offs and licensing forms
Table 2: Firm and industry-level determinants of platform-centric ecosystems and their implications for complementary innovation
Table 3: List of secondary qualitative data sources for the case studies
Table 4: The characteristics of ARM’s platform-centric ecosystem and their implications for complementary innovation
Table 5: The characteristics of AWS’s platform-centric ecosystem and their implications for complementary innovation
illustration not visible in this excerpt
In the introductory chapter, an overview of the research field and its relevance for theory and practice are first provided (Section 1.1). After that follows the identification of the research gap and the motivation for the research question and integrated research approach (Section 1.2). The outline of the thesis is presented at the end of this chapter (Section 1.3).
Managers in strategy and organization for innovation are increasingly confronted with the challenge to compete on the basis of complex technology platforms. Prominent examples, such as Microsoft Windows (operating systems), Google (Internet search engines), Facebook (online social networks), Sony PlayStation (video game consoles), Visa (payment cards), Wal-Mart (retail), Tesla Motors (electric cars) or Life Technologies (genome sequencing), demonstrate that platforms are pervasive in many industries (Evans et al., 2006; Gawer & Cusumano, 2002, 2014; Gawer, 2009c; Iansiti & Levien, 2004b; Shapiro & Varian, 1999a, 1999b; Tiwana, 2014). In fact, platforms represent one of three configuration models through which firms innovate (Baldwin & von Hippel, 2011) and generate value (Stabell & Fjeldstad, 1998).1 Thus, platforms are both a mechanism for value creation through innovation and value capture through appropriation (Jacobides et al., 2006; Teece, 1986). Their economic importance is substantial: in terms of market value, 60 of the 100 largest companies worldwide earn more than half of their income in platform markets (Eisenmann, 2007).
The emergence of platforms reflects the growing interdependency between products and services and the increasing dispersion of innovation activities among many different actors, especially in rapidly evolving high-tech industries (Gawer & Cusumano, 2002). It has been widely acknowledged in management theory and practice that in order to successfully commercialize innovations and create value for end users, platforms have to be embedded in an interrelated array of organizations, including suppliers, complementors, customers, competitors and institutions. Thereby, platforms constitute the foundation upon which a vast and diverse web of firms, commonly defined as a ‘business ecosystem’, develop and provide complementary products and services (Evans et al., 2006; Gawer & Cusumano, 2002, 2014; Gawer, 2009a; Iansiti & Levien, 2004a, 2004b; Shapiro & Varian, 1999a, 1999b; Teece, 1986; Tiwana, 2014).
While the question of how platform owners can stimulate research and development (R&D) activities by complementors has been tackled in the academic literature and evolved to a promising research field, a coherent concept of the managerial levers is still missing. Up to now, research on platform ecosystems has typically examined the determinants of complementary innovation separately and focused on, for example, platform strategy (e.g. Almirall & Casadesus-Masanell, 2010; West, 2003), platform organization (e.g. Kapoor & Lee, 2013; Venkatraman & Lee, 2004) or platform architecture (e.g. Langlois & Robertson, 1992, 1995). Other academics have established managerial frameworks for platform leadership (e.g. Cusumano & Gawer, 2002; Gawer & Cusumano, 2002, 2008) and value appropriation from innovation (e.g. Jacobides et al., 2006; Teece, 1986), which already incorporate firm and industry-level influences on external innovation more systematically. Yet, this field of research lacks a unified view of what drives the propensity to innovate by platform complementors. Management scholars have emphasized the imperative for a coherent and multidisciplinary research approach towards the influencing factors on innovators in platform ecosystems as well (Gawer & Cusumano, 2014; Gawer, 2009c). This motivates the following research question: “What firm-level and industry-level determinants of platform-centric ecosystems encourage or impede complementary innovation by third-party organizations?” Accordingly, the main objective of this thesis is to conceptualize an integrated view of the defining elements of platform ecosystems and their implications for the innovation orientation of complementors. In addition, this thesis aims to test and build on the proposed theoretical framework empirically.
To approximate both objectives, the integrated research approach is divided into two building blocks. First, an extensive literature review is performed with the purpose to provide a conceptual foundation to answer the research question. Research findings on platform ecosystems are drawn from the extant literature in highly ranked journals in strategic management, industrial organization and information systems as well as from leading scholars in their academic fields. These contributions are then integrated into a comprehensive theoretical model. Second, case study research is adopted for the empirical part of the thesis to gain a deeper understanding of the causal links within the multilayered platform-complementor setting (Yin, 2013). However, certain technology platforms and their widespread ecosystems have been extensively studied by academics, in particular video game consoles (e.g. Hagiu, 2009b; Schilling, 2003; Venkatraman & Lee, 2004; Zhu & Iansiti, 2012), the ‘Wintel’ platform2 (e.g. Bresnahan & Greenstein, 1999; Casadesus-Masanell & Yoffie, 2007; West, 2003) and Intel’s microprocessor ecosystem (e.g. Gawer & Cusumano, 2002, 2014; Gawer & Henderson, 2007; Perrons, 2009). Hence, this thesis contributes to theory by gaining new insights from examining two independent platform ecosystems that do not operate at the forefront of the high-tech industry, namely Advanced RISC Machines (ARM) and Amazon Web Services (AWS). Both platform examples were chosen with the purpose to replicate and extend the developed framework by investigating how ARM and AWS facilitate the development of third-party complements (Creswell, 2013; Eisenhardt, 1989; Saunders et al., 2009; Yin, 2013).
An answer to the research question is elaborated in a four-step approach. In Chapter 2, the theoretical foundation is provided, describing the underlying concepts of platform-centric ecosystems and platform management. Chapter 3 aims to integrate the relevant literature on the determinants of platform ecosystems and their impact on complementary innovation. In Chapter 4, the proposed framework is applied to a case study of ARM and AWS, two current platform examples in the information and communications technology (ICT) industry. Chapter 5 discusses the main contributions of the integrated research approach and distills the learnings from the empirical inquiry for academics and practitioners alike. Finally, Chapter 6 concludes this thesis and gives an outlook for future research.
In setting a common theoretical understanding of platform-centric ecosystems, the first part of the literature review defines the terms of reference for the framework development in Chapter 3 (Section 2.1). Platform strategies and platform organization and governance, two central dimensions of platform management, are discussed in the second part of this chapter (Section 2.2).
First, this section provides an overview of the current state of the literature streams on platforms, their specificities, distinctions and similarities. In recapitulating platform theory, fundamental concepts are outlined, namely dominant designs, business ecosystems and network externalities. After delimitating the different platform archetypes and establishing a working definition (Section 2.1.1–2.1.3), the notion of complementary assets and innovation along with the dynamic capabilities approach will be covered (Section 2.1.4). The elements of platform architecture are the third cornerstone of this section (Section 2.1.5), which is followed by a short characterization of the main platform participants (Section 2.1.6). This section closes by introducing specific platform dynamics, above all the appropriability regime and industry architecture, that have strong implications for complementors3 (Section 2.1.7).
Over the past two decades the concept of platforms has been elaborated within three academic literature streams that originate from distinct empirical perspectives: product development, technology strategy and industrial economics. Researchers in the field of product development and operations management initially adopted the term ‘product platform’ as a set of assets, subsystems and interfaces with an underlying core technology that are shared across different product categories (Krishnan & Gupta, 2001; McGrath, 1995; Robertson & Ulrich, 1998) and that form a common basis to efficiently develop and produce a range of derivative products (Meyer & Lehnerd, 1997; Muffato & Roveda, 2002; Wheelwright & Clark, 1992a). This line of reasoning can be traced back to Marschak (1962), who describes such ‘systems’ as a principle guided combination of components. Gawer (2009a) and Gawer and Cusumano (2014) classify this type of platforms as ‘internal platforms’ since they are organized within firms. Well-known examples of intra-firm, component-based product platforms are Hewlett-Packard’s inkjet and laserjet printer series (Feitzinger & Lee, 1997) and Volkswagen’s modular construction kit for its various car brands (Wilhelm, 1997). An important extension of the product platform is the ‘supply-chain platform’ in which multiple suppliers provide intermediate goods and components to the platform owner for final assembly (Gawer & Cusumano, 2014; Gawer, 2009a). Supply-chain platforms are frequently observed in assembly industries, such as the automotive sector (Sako, 2003, 2009; Zirpoli & Caputo, 2002).
In technology strategy, the second research wave, Gawer (2009a) and Gawer and Cusumano (2002, 2014) define so-called ‘industry platforms’ as interdependent building blocks that serve as the foundation for external firms, loosely organized within a business ecosystem, to innovate and develop complementary products and services. The foundation itself can be composed of products, services or certain technologies. Similarly, Boudreau (2010) asserts that platforms are a set of components that are deployed in common across a product family and which organize the inter-firm development of complements. Since the functionality of different components is strongly interdependent, Gawer and Henderson (2007) emphasize that end-user demand is for the entire platform system and not for specific components. Further research on industry platforms was primarily conducted in the context of the ICT industry, studying computer platforms (Bresnahan & Greenstein, 1999; West, 2003), software platforms (Boudreau, 2012; Ceccagnoli et al., 2012; Evans et al., 2006; Huang et al., 2013; Taudes et al. 2000; Tiwana et al., 2010; Tiwana, 2014), the Internet platform (Greenstein, 2009) and, more broadly, IT platforms (Fichman, 2004; Gawer & Henderson, 2007; Iansiti & Levien, 2004b). In general, these studies suggest that industry platforms encourage complementary third-party innovation, which increases the overall value of the focal platform and consequently the value for its end users (Gawer & Cusumano, 2014; Gawer, 2009a). Microsoft Windows, Cisco networking systems and Intel semiconductors are well-established examples of high-tech industry platforms (Gawer & Cusumano, 2002, 2014).
Analogous to internal and supply-chain platforms, the design and strategic management of industry platforms aim at strengthening a company’s competitive advantage (Gawer, 2009a). A key distinction between these platform types is that industry platform leaders intend to stimulate and benefit from the innovation capabilities of external complementors, who do not necessarily enter into sale and purchase agreements to exchange goods or services. Also, the developers of complements are in principal neither located in the same supply chain nor are they involved in cross-ownership of shares with the platform owner (i.e. non-equity agreements). Another important difference pertains to the design of industry platforms as there is no ‘master designer’ or final assembler. The final construct is unknown ex ante and the end use of the industry platform’s product or service is not entirely predetermined. As a result, the scope for complementary innovation is embedded within the platform’s design rules and logic (Gawer & Cusumano, 2002, 2014; Gawer, 2009a).
The concept of industry platforms is to some extent related to the ‘dominant design’ paradigm (Gawer & Cusumano, 2014), which reflects the path dependent emergence of an industry standard for a particular technology among competing alternative standards (Abernathy & Utterback, 1978; Abernathy, 1978; Utterback & Abernathy, 1975). However, the concepts differ with regard to the emergence of standards and adoption of technologies. According to Gawer and Cusumano (2014), industry platforms are ‘manageable objects’ upon which platform owners can proactively affiliate complementors and end users to create network effects and positive feedback cycles that lead to platform adoption. On the other hand, designs become dominant along an evolutionary trajectory that is predominantly industry-driven without any firm-specific agent. In industries that are characterized by network externalities, technology adoption is largely driven by the availability of complementary goods that benefits and attracts users. A growing installed base of users in turn attracts complement developers (Katz & Shapiro, 1986; Shapiro & Varian, 1999a, 1999b). Therefore, technologies with a scant supply of complements and a minor installed base, as compared to competing technology paths, might be locked out from the market and fail to become a dominant design (Schilling, 1998, 2002, 2003, 2009). As an aggravating factor, until a (platform) standard emerges, technological uncertainty often deters end users and complementors from long-term investments due to potentially high switching costs (Katz & Shapiro, 1994; Venkatraman & Lee, 2004).
Conceptually, the notion of industry platforms builds on the construct of ‘business ecosystems’, which has been established and refined by Moore (1993, 1996, 1998, 2006). “In a business ecosystem, companies co-evolve capabilities around a new innovation: they work cooperatively and competitively to support new products, satisfy customer needs, and eventually incorporate the new round of innovations” (Moore, 1993, p. 76). By definition, business ecosystems source and coordinate complementary innovation within a diverse community of suppliers, customers, competitors, complementors and other stakeholders (Moore, 1998, 2006). For example, in 2004 Microsoft’s software ecosystem comprised 38,338 member organizations in different domains, ranging from system integrators to independent software vendors (ISVs) and business consultants (Iansiti & Levien, 2004a, 2004b). These communities are characterized by an interconnected and interdependent web of loosely coupled companies. In such a highly networked structure, a central hub serves as an access point and regulator for outside complementors, also referred to as a ‘keystone firm’ (Iansiti & Levien, 2004a, 2004b), ‘hub firm’ (Nambisan & Sawhney, 2007, 2011), ‘ecosystem leader’ (Moore, 1993, 1996, 1998, 2006) and ‘platform leader’ (Cusumano & Gawer, 2002; Gawer & Cusumano, 2002, 2008, 2014). Contrary to vertical structures, the links between ecosystem firms are not defined by transactions and transfer of ownership but instead by access to and usage of resources and services to develop new complements (Rifkin, 2000). Hence, the coordination of interdependent complementary activities rests on the choice of the organizational form by the members, such as contracting, alliances and hierarchical relationships (Kapoor & Lee, 2013), and the structure of the interorganizational linkages between them, i.e. their overlap and embeddedness (Venkatraman & Lee, 2004).
Gawer and Cusumano (2002) conclude that the availability of innovative complements in business ecosystems that center around technology platforms increases the value of the whole system. In the same way, Iansiti & Levien (2004a, 2004b) pronounce that the health of the ecosystem depends, among other things, on the variety of the members that create value. Put differently, as soon as complementors face innovation challenges, the leadership position and competitive advantage of an ecosystem’s technology erodes (Adner & Kapoor, 2010). In this context, ‘platform-centric ecosystems’ (PCEs) comprise a technological foundation, provided and managed by the platform leader, upon which an interrelated array of third-party organizations build complements that enhance the platform’s attractiveness (Gawer & Cusumano, 2002, 2014; Gawer, 2009a).
More recently, the emerging literature in industrial economics emphasizes the intermediary function of platforms to enable transactions in double-sided or multi-sided markets between two or more customer groups, respectively. ‘Multi-sided platforms’ (MSPs) endorse the interaction between different and mutually appealing end user groups, typically buyers and sellers, by providing each side distinct products or services which are priced separately and are often cross-subsidized. The platform’s pricing structure (i.e. membership and licensing fees, royalties and fixed costs) constitutes the main decision variable to maximize platform profits, attract interdependent categories of users, control platform access and encourage platform adoption. This form of user interdependence gives rise to indirect network externalities, which means that platform access is valued higher by one user group, the larger the size of the other user category (Armstrong, 2006; Caillaud & Jullien, 2003; Evans, 2003; Hagiu, 2006, 2009b; Parker & Van Alstyne, 2005; Rochet & Tirole, 2003, 2006; Rysman, 2009; Weyl, 2010). In a similar vein, indirect network externalities confront companies with the ‘chicken-and-egg’ problem, a sequential coordination conundrum that implies that in order to attract vendors, the platform should have a large installed base of end users, who are, however, only willing to participate if they are confident that many vendors will be available (Caillaud & Jullien, 2003; Evans, 2003). Often-cited examples of MSPs include credit cards, shopping malls, newspapers, television channels, web browsers and video game consoles (Armstrong, 2006; Rochet & Tirole, 2003, 2006). This type of platforms has also been labeled ‘platform-mediated networks’ (Eisenmann et al., 2006, 2009; Eisenmann, 2008).
Whereas indirect network effects are an important similarity of MSPs and industry platforms, MSPs that solely promote exchange or trade without the possibility for external innovators to provide complements, such as dating bars or web sites, do not fit the concept of industry platforms (Gawer & Cusumano, 2014; Gawer, 2009a). Overall, this literature stream is limited by focusing too narrowly on arm’s length pricing as the key strategic lever to intermediate complementors and users (Boudreau & Hagiu, 2009) and by revealing little insights into platform emergence and evolution (Gawer & Cusumano, 2014; Gawer, 2009a). Thus, scholars in industrial organization research have begun to examine non-price instruments of MSPs to answer questions such as how to incentivize complementary innovation more systematically. In particular, the analysis has been extended to start-up platform strategies for entrepreneurs (Evans, 2009), platform openness strategies (Eisenmann et al., 2006 2009; Eisenmann, 2008; Rysman, 2009), platform extension and expansion strategies (Hagiu, 2009a) and platform regulation mechanisms (Boudreau & Hagiu, 2009).
As noted previously, network externalities are peculiar to MSPs and industry platforms and can be generally divided into two subcategories. In markets characterized by direct network externalities, the value of a product increases with the number of users owning a compatible good in the same network, like telephones. Indirect network externalities arise in (platform) markets with a focal product and complementary goods, in which a larger user base attracts more complementors and vice versa. A prominent example are personal computers (PCs) and software. This relationship has a self-reinforcing effect on users’ choice and specialization of complementors, which economists describe as increasing returns to scale.4 Inherently, the virtuous cycle leads to de facto standardization of a single technology5 or compatible complements that sponsor competing technologies until one alternative becomes dominant (Farrell & Saloner, 1985, 1986; Katz & Shapiro, 1985, 1986, 1994).6
For the purpose of this thesis, a two-part working definition is adopted. Henceforth, platforms are defined as the technological foundation to enable complementary third-party innovation in PCEs (Gawer & Cusumano, 2002, 2014; Gawer, 2009a) and to mediate interactions between complementors and end users to exploit indirect network effects (Armstrong, 2006; Caillaud & Jullien, 2003; Evans, 2003; Rochet & Tirole, 2003, 2006). Thereby, this thesis synthesizes and integrates the established findings in both literature streams, technology strategy (i.e. industry platforms) and industrial economics (i.e. MSPs), to gain a more coherent understanding of platform-based complementary innovation by independent ecosystem members.
Complementary innovation in PCEs, as discussed in this thesis, is embedded within the notions of complementary assets and autonomous innovation. It also relates to organizational design theory and the dynamic capabilities approach, since firm boundaries and the locus of innovation are central factors of whether innovation occurs inside a company or externally in collaboration with like-minded partners.
In his landmark paper on profiting from innovation (PFI), Teece (1986) suggests that commercial success of an innovation depends on the company’s complementary asset position, the appropriability regime conditions and the current state of the dominant design trajectory.7 Complementary assets can consist of downstream capabilities (e.g. manufacturing, marketing and after-sales support), tangible resources (e.g. intellectual property (IP) rights) and intangible resources (e.g. access to distribution channels and service networks). Furthermore, Teece differentiates between generic, specialized and co-specialized complementary assets. Generic assets, such as manufacturing facilities, need not be adjusted for the projected innovation and can be applied in many different settings. Specialized and co-specialized assets are context-related in that they exhibit unilateral and bilateral dependence on the innovation, respectively.8 In particular, access to (co-)specialized complementary assets is critical to appropriate the profits from innovation, since companies hardly own all relevant assets to introduce new technologies (Teece, 1986). Likewise, co-specialization is essential in platform markets, where platform owners are usually not equipped with the required resources and capabilities to develop differentiated complements themselves (Teece, 2007). As a result, the development and commercialization of technological innovations require organizations to span firm boundaries and to coordinate various interdependent innovation activities. By establishing interorganizational linkages to obtain access to complementary asset owners and developers, horizontal and vertical collaboration becomes crucial. It is well recognized in the literature that contractual arrangements, such as licensing, constitute an effective approach to gain access to co-specialized assets. In contrast, vertical integration, i.e. the ownership of all necessary complementary assets, is considered as excessive, costly and often impracticable, above all for rapidly evolving technologies. Hence, the scope of the firm boundaries, determined by the level of integration, is a key strategic instrument for the innovating firm (Jorde & Teece, 1989, 1990; Teece, 1986).
The argument presented above holds for different innovation types. Formally, innovation involves the search for new combinations of resources and the development of novel products and processes (Schumpeter, 1934). It is cumulative in nature as it follows prior paths (Dosi, 1988). For the purpose of this thesis, technological innovation is further split into systematic and autonomous innovation. Systematic innovations demand tight coordination and adjustments across subsystems of components, creating entirely new technological opportunities and requirements. Autonomous innovations do not alter the component structure and fit seamlessly into existing systems and standards, enhancing products and processes (Chesbrough & Teece, 1996; Teece, 1984, 1996). Systematic innovation corresponds to platform innovation, which entails the creation of a new technological foundation, such as a (next generation) Microsoft Windows OS. Autonomous innovation relates to the concept of ‘complementary innovation’ in PCEs, which circumscribes the development of diverse complements by third-party organizations to meet heterogeneous user needs and to leverage indirect network effects that tie the platform-based technology and its complements together.9 Returning to the preceding example, complements are video games and software applications provided by ecosystem developers (Cusumano & Gawer, 2002; Gawer & Cusumano, 2002, 2008, 2014; Gawer, 2009a). While systematic or platform innovation necessitates a highly integrated organizational design to maintain close coordination and control, autonomous or complementary innovation can be organized within decentralized and contractual relationships around proven technologies. In both circumstances, firms must form relations with other companies to access complementary assets and capabilities that are regularly located outside their boundaries, as discussed before (Jorde & Teece, 1989, 1990; Teece, 1986).
Since the PFI framework is a strategic decision making tool for how to capture innovation rents by orchestrating idiosyncratic and co-specialized assets, it is regarded as a prolongation of the resource-based view (Teece, 2006). However, the notion of ‘co-specialization’ later became a centerpiece of the dynamic capabilities approach, which identifies the sources of sustainable competitive advantage at the enterprise level. According to theory, managers have “to integrate, build, and reconfigure internal and external competences to address rapidly changing environments” (Teece et al., 1997, p. 516). Since dynamic capabilities involve recombining resources to create new value (Eisenhardt & Martin, 2000), complementary innovation can be regarded as a dynamic capability. Therefore, the defined competences that effectuate sustainable competitive advantage, specifically a firm’s organizational and managerial processes, its technology, IP and complementary asset position as well as its technological (path) opportunities (Teece & Pisano, 1994; Teece et al., 1997), are important elements to understand how complementary innovation can be encouraged or impeded in PCEs. In addition, the orchestration of co-specialized assets within business ecosystems, which promotes collaboration and system-wide innovation, is fundamental to dynamic capabilities theory (Teece, 2006, 2007).
One of the main research questions in the field of technology innovation examines the implications of product architecture on innovation (Abernathy & Utterback, 1978; Baldwin & Clark, 2000; Christensen, 1992; K. B. Clark, 1985; Henderson & Clark, 1990; Ulrich, 1995).10 Within this literature stream, platform architecture is recognized as a primary driver of the nature and distribution of complementary innovation in business ecosystems (Baldwin & Clark, 2000; Baldwin & Woodard, 2009; Gawer & Cusumano, 2002; Gawer & Henderson, 2007; Iansiti & Levien, 2004b; Langlois & Robertson, 1992). Platform architecture is rooted in Simon's (1962) early work on ‘complex systems’, which are defined as hierarchical and decomposable systems that consist of interacting and interdependent subsystems. Similarly, platform architecture is partitioned into a hierarchically ordered core and peripheral components that are complementary to each other and connected through interfaces (Baldwin & Woodard, 2009; Tushman & Murmann, 1998). Gawer and Cusumano (2002) attribute the design logic of the overall system and its component interfaces to the platform architecture as well. While changes in the tightly coupled core subsystems, i.e. the platform, have system-wide effects, shifts in the weakly linked peripheral subsystems, i.e. the complements, have less pronounced implications for other components (Baldwin & Woodard, 2009; Tushman & Murmann, 1998).11 For that reason, design rules generally specify stability and low variability for the technical core and support high variety in the complements (Baldwin & Woodard, 2009).12
Platform architecture further ranges on a continuum from highly integral to highly modular archetypes (Baldwin & Clark, 2000; Schilling, 2000; Ulrich, 1995). In an integral architecture, the functional component-layers and interfaces are fully encapsulated to work exclusively with specific, tightly coupled components (Ulrich, 1995). Thus, an integral platform is closed with respect to external innovators to capture higher sales from proprietary (sub)systems and to realize coordination advantages for systematic innovation (Langlois & Robertson, 1992). An example of an integral architecture are computers prior to 1965, when every new mainframe had to be designed from scratch since their layout was distinct and incompatible. The situation changed dramatically following IBM’s launch of the modular System/360 mainframe architecture. In a modular design structure, the components are functionally interdependent within the platform but are structurally independent across the platforms’ subsystems (Baldwin & Clark, 1997, 2000). In other words, modularity implies that components can be separated and recombined since they are independent from one another but compatible with the overall platform system. This flexibility in turn allows to mix and match different components and achieve a multitude of new configurations that meet heterogeneous user demands (Langlois & Robertson, 1992; Langlois, 1992; Sanchez & Mahoney, 1996; Sanchez 1995; Schilling, 2000).
Modularity can be accomplished by increasing the decomposition of a platform system, as conceptualized by Simon (1962), and through the standardization of interfaces at the component boundaries. As part of the design rules, interface specifications are defined in advance by the platform architect and serve as an access point and technical regulation guideline to which all ecosystem developers have to obey. Since codified interfaces specify how components have to be designed physically and interact functionally with the technical platform core, they ensure the interoperability between different platform components (Baldwin & Clark, 2000).13 Consequently, interfaces in a modular system create a set of loosely coupled components (Sanchez & Mahoney, 1996; Weick, 1976). Moreover, modularity in platform architecture induces modularity in the structure of the intrafirm and interfirm organization (Sanchez & Mahoney, 1996; Sanchez, 1995; Staudenmayer et al., 2005) as well as in the industry architecture (Langlois & Robertson, 1992; Langlois, 1992). A good illustration of a modular platform architecture is presented by MacCormack and Iansiti (2009), who analyze Microsoft’s software componentization and how its community of complementary software developers leveraged the firm’s accessible code libraries.
To this point, in reviewing the literature on platform theory, three distinct participants in PCEs have been mentioned: platform leaders, also denoted as platform owners (Cusumano & Gawer, 2002; Gawer & Cusumano, 2002, 2008, 2014), complementors, who can simultaneously be platform suppliers, competitors and customers (Brandenburger & Nalebuff, 1997; Moore, 1998, 2006), and end users (Caillaud & Jullien, 2003; Evans, 2003; Rochet & Tirole, 2003, 2006). However, the scope of tasks and responsibilities assumed by these individual participants in PCEs differ with regard to the platform strategy set out by the platform leader. Since platform strategy varies from fully closed to completely open, extensive restrictions may curtail the participation of third-party organizations (Eisenmann et al., 2009).14
A useful role typology within the context of platform strategy in MSPs has been provided by Eisenmann et al. (2009). The authors refine the role of the platform leader by distinguishing between the platform sponsor and platform provider, whose function can be assumed by one firm or shared by several companies depending on the platform strategy. Whereas the platform sponsor owns the IP rights (IPRs) and controls platform participation and technology development, the platform provider intermediates end users and complementors, serving as their focal point of contact. For example, Apple sponsors and provides its iOS and iPhone within one platform, while Microsoft distributes its proprietary Windows OS in bundles with multiple PC hardware manufacturers (Eisenmann et al., 2009).
Apart from the endogenous attributes of platforms, specifically the architecture, strategy and organization, PCEs and complementary innovation therein are influenced and shaped by broader environmental dynamics that are largely exogenous in nature. Above all, these platform dynamics comprise the appropriability regime, the industry architecture, platform integration and multi-homing costs.
The ‘appropriability regime’ concept was introduced within the PFI framework of Teece (1986) as one of the three factors that determine an innovator’s capability to secure returns from innovations.15 The two key dimensions of the appropriability regime are the legal protection mechanisms, provided by formal de jure rights such as patents, copyrights, trade secrets and non-disclosure agreements, and the technical barriers to product imitation, which are raised through higher knowledge tacitness and complicating reverse engineering. Based on the characteristics of both dimensions, the protection of intellectual property offered by the regime can be categorized on a continuum from weak to strong across different countries and industries. In weak appropriability regimes, legal protection is not formalized or ineffective and technology imitation is rather simple. Conversely, strong appropriability regimes rest on high enforceability of formal IPRs and innovations that are hard to replicate (Pisano & Teece, 2007; Teece, 1986).16 Moreover, Teece (2006) recognizes that technologies that evolve to an industry standard further raises the barriers to imitation for rivals. Pisano and Teece (2007) also infer that appropriability regimes are not fixed. Instead, they change over time and can be proactively weakened and strengthened.
The architecture of an industry delineates the division of labor between co-specialized industry participants. It structures the relationships and interactions among those firms, including their organizational boundaries and degree of co-specialization (Jacobides et al., 2006). Jacobides et al. (2006) extend the notion of ‘co-specialization’ developed by Teece (1986) and identify two independent drivers of co-specialization: complementarity of products and services (see Section 2.1.4) and mobility in assets. Segments of a platform ecosystem where mobility is low (i.e. few asset alternatives and high asset switching costs) are called ‘bottlenecks’, which determine the general innovation direction and the division of surplus based on their superior bargaining position. From a dynamic perspective, industry architectures gradually emerge and stabilize as technological capabilities and interfaces develop (Jacobides & Winter, 2005). Interfaces, which govern the division of labor and interfirm organization, facilitate the formation of co-specialized firms (Jacobides et al., 2006). As technologies progress and interfaces become more codified, vertical specialization and product modularity increases (Fixson & Park, 2008), shifting the locus of innovation to the component level. In contrast, vertical integration is prevalent for integral architectures where innovation occurs at the system level (Pisano & Teece, 2007). To exemplify, the computer industry was historically highly integrated, both in terms of the technology design and value chain. With the advent of the modular PC architecture and standardized interfaces, the computer industry disintegrated into modular clusters and co-specialized companies emerged, such as Microsoft, Intel and Dell (Baldwin & Clark, 2000; Jacobides et al., 2006). As pointed out previously, the interdependency between technology and industry architecture has been examined by different scholars (Baldwin & Clark, 2000; Henderson & Clark, 1990; Langlois & Robertson, 1992; Langlois, 1992). Similar to the appropriability regime, firms can employ various instruments to strategically shape their industry architecture (Baldwin & Clark, 1997, 2000; Chesbrough, 2003; Iansiti & Levien, 2004b; Jacobides et al., 2006; Pisano & Teece, 2007; Shapiro & Varian, 1999b).
As platforms advance, complementary and adjacent technological functionalities within the ecosystem are often integrated into the focal platform. The reasons for platform integration are manifold, notably to create new innovations (Henderson & Clark, 1990; Iansiti, 1998), to expand PCEs (Iansiti & Levien, 2004b), to maintain control over crucial platform architecture decisions (Gawer & Cusumano, 2002; Gawer & Henderson, 2007) and to benefit from network externalities and absorb switching costs (Eisenmann et al., 2011). The concept of ‘platform integration’ is closely linked to ‘technological convergence’ (Langlois & Robertson, 1992; Tiwana et al., 2010) and ‘platform envelopment’ (Eisenmann et al., 2011, 2006). Evolutionary, the trajectory of PCEs is affected by the development of new complements and substitutes. Thus, over time, a PCE’s technological functionality tends to converge with those of adjacent and unrelated ecosystems. The resulting technological convergence gives rise to envelopment opportunities (Tiwana et al., 2010). Envelopment occurs when a platform leader bundles its own functionalities with the features of an adjacent platform, thereby leveraging their overlapping user and developer base and technical components. For instance, Microsoft has enveloped RealNetworks’ streaming media service and Netscape’s web browser by bundling Windows 95 with the in-house Windows Media Player and Internet Explorer (Eisenmann et al., 2011).
In an environment of incompatible platforms, complementors can choose to affiliate with a single platform (i.e. single-homing) or multiple platforms (i.e. multi-homing) (Armstrong, 2006). This strategic decision, which is primarily driven by the strength of network effects, the overlap of the user base and prospective multi-homing costs (Eisenmann et al., 2011), shapes the evolution of PCEs. Homing costs are the total costs that a complementor incurs to establish and secure platform membership, comprising adoption, operating and opportunity costs (Tiwana et al., 2010). Figure 1 graphically summarizes the elements of a PCE and their interrelations as discussed in this section.
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Figure 1: Schematic representation of a platform-centric ecosystem
Source: adapted from Baldwin and Clark (2000) and Tiwana et al. (2010)
In the second part of the theory chapter, the fundamentals of platform management are outlined. First, platform strategy is defined in terms of openness and the respective trade-off between appropriability and adoption (Section 2.2.1). Also, horizontal, vertical and leadership strategies as well as the strategic forms of complementor licensing are briefly described. Second, platform organization and the related concepts of PCE design and governance are examined (Section 2.2.2). In this respect, distinct ecosystem features are delineated, in particular the nature of the relationships between ecosystem firms, platform boundary resources and regulation mechanisms.
Platform strategies as discussed in the extant literature are distinguished based on the degree of platform openness along a control continuum from completely proprietary to completely open. Platform openness can be understood as the propensity of platform owners to share platform technologies with outside innovators (Schilling, 2009; West, 2003) and effectively reduce access, use and commercialization restrictions (Boudreau, 2010). In that regard, openness is related to the concept of ‘open innovation’, which intends to leverage external ideas and knowledge to accelerate value-added innovations around (platform) technologies (Chesbrough, 2003). The boundaries of openness are tightly coupled to the property rights position of the platform owner (Katz & Shapiro, 1986, 1994). Proprietary or closed platform systems are wholly owned and controlled by one or more platform sponsors (West, 2003). Their integrated technology is protected by formal IPRs (Cohen et al., 2000) and incompatible with third-party components (Schilling, 2009). In contrast, open platforms have no IP protection. Their ownership and control are relinquished by making the technology accessible to the public (Boudreau, 2010; West, 2003). In between those pure play strategies, hybrid strategies pursue the objective to open up parts of the platform by waiving specific control rights and by placing technology in the public domain under certain restrictions (West, 2003). Therefore, partially open platforms differ greatly in terms of the technical components which are opened, the diffusion of IPRs and the licensing agreements with third-party organizations (Boudreau, 2010).
The diversity of platform strategies reflects the tension and trade-off between appropriability and adoption. Proprietary strategies enable the platform owner to appropriate a large portion of the innovation returns and amortize development costs faster due to high barriers to entry and imitation. On the other hand, by sharing economic benefits with ecosystem firms and facilitating market entry, open platforms stimulate adoption. Open source strategies are particularly beneficial if industries are characterized by strong network externalities and if adoption requires the co-specialization of interfirm assets (West, 2003). In addition, diffusion is encouraged as complementors and end users do not risk to be locked into the dominant position of a single platform owner (Katz & Shapiro, 1994; Shapiro & Varian, 1999a). However, openness minimizes the possibilities to appropriate returns (West, 2003).
Another important strategic conception for managing platform openness has been elaborated by Eisenmann et al. (2009), who examine horizontal and vertical platform strategies. More precisely, horizontal strategies pursue the interoperability with competing platforms, the licensing of secondary platform providers and the joint development of a platform’s technology with additional platform sponsors. Vertical strategies, by contrast, directly affect complementors and involve choices regarding backward compatibility with prior platform generations, the granting of exclusive platform access rights and the integration of complements into the platform.
Beside platform openness, there are other noteworthy contributions in the strategy research field of platforms. In their seminal work on complementary innovation, Gawer and Cusumano (2002) have proposed a framework of four interrelated levers for formulating and implementing platform leadership strategies. First, the scope of the firm defines which complements are produced in-house and which are developed externally. Second, the design of the platform architecture determines the modules and interfaces that are accessible by outside innovators. Third, a platform owner has to decide whether the relationships with complementors should be more collaborative or competitive in nature. Finally, the internal organization has to be aligned to manage internal and external conflicts that arise from conflicting corporate goals, such as for-profit and not-for-profit objectives (Gawer & Cusumano, 2002).
One of the fundamental implementation topics within platform strategy and openness are the different forms of technology and IP licensing.17 Arm’s-length licensing serves as a means for contracting complementors (West, 2003) and is considered to be highly relevant for platform adoption (Schilling, 1998, 2003, 2009; West, 2003). Specifically, open platform strategies favor liberal licensing (Schilling, 2009; West, 2003). In the software industry, free software and open source licenses are frequently adopted, such as GNU General Public Licenses for the distribution of Linux, which largely prohibit the commercialization of software enhancements (West, 2003). Partly open platforms necessitate selective licensing in the form of hybrid agreements that combine proprietary and open source licensing elements (Schilling, 2009; West, 2003). A good illustration is Microsoft’s Windows OS, where ISVs are permitted to develop and sell complementary software unless the functionality of the OS will be compromised. As part of a proprietary platform strategy, limited licensing is often employed for the development of complements. For example, in the video game industry external developers provide games while console producers, like Sony (PlayStation), retain considerable control and approval rights (Schilling, 2009). An overview of the platform strategies and related concepts is presented in Table 1.
Table 1: Platform strategies with corresponding trade-offs and licensing forms
Source: adapted from West (2003) and Schilling (2009)
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Teece (1986) accentuated that the configuration and scope of the firm boundaries, a crucial aspect of the PCE design, is of strategic relevance for firms that necessitate (co-)specialized complementary assets to commercialize an innovation. Conceptually, organizational boundaries represent the firm’s degree of vertical and horizontal integration and the position in an industry (Teece et al., 1997). A useful definition of the organization of a platform’s ecosystem can be inferred from Jacobides and Billinger (2006), who designate the ‘vertical architecture’ as the firm’s location in the value chain, the interfaces between the internal and external suppliers (and complementors) as well as the vertical and horizontal linkages therein. Farrell et al. (1998) elaborated opposing types of vertical organization on a spectrum from closed to open. A closed organization of PCEs is characterized by vertical integration and system-based competition that requires secrecy and close contractual relationships with a small set of complementors. In contrast, PCEs that are open to all ecosystem firms are non-integrated and broadly licensable IP stimulates competition around compatible, mix and match components (Farrell et al., 1998). In essence, a platform leader can choose whichever organization form of complementors is most effective for the platform strategy and architecture and delivers the highest value to end users. This entails the decision of whether or not to develop complements internally, integrate into the complementary market or contract external complementors (Farrell & Weiser, 2003).
While hierarchical or integrated control structures are designated to strengthen internal coordination of complementary activities, contractual relationships rely on the coordination capabilities of the market (Teece et al., 1997). As indicated previously, the platform architecture stipulates the necessary level of coordination and is thus closely connected to platform organization. In general, the principal design logic for an integral architecture is the vertically integrated structure, as opposed to the modular architecture, which induces vertical disintegration in PCEs (Yoo et al., 2010).
Inherently, the interrelations between platform owners and complementors can be collaborative and competitive, or a mix of both (Boudreau & Lakhani, 2009; Economides & Katsamakas, 2006; Gawer & Cusumano, 2002). Collaborative relationships are based on trust and transparency as well as on sharing efforts and innovation returns by following common goals, as illustrated in the case of the Intel Architecture Lab (IAL) (Gawer & Cusumano, 2002).18 In competitive PCEs, however, third-party organizations, and possibly platform owners, develop substitutable complements and maximize their own utility, such as in the video game industry and Apple’s application ecosystem (Boudreau & Lakhani, 2009; Gawer & Cusumano, 2002).
Aside from verticality, platform organization is further specified in terms of the governance structure. Tiwana et al. (2010, p. 679) define platform governance as “who makes what decision about a platform” and study the concept from a decision rights, control and IP ownership perspective. First, the partitioning of decision rights allocates the authority to make decisions regarding component design, functionality and interfaces between the platform owner and the complementors. Another characteristic of governance is control, which is either exercised or relinquished to achieve certain outcomes. In general, output controls specify the requirements for complementary products whereas input controls govern which complements can be distributed by third-parties alongside the platform. A final aspect that delineates platform governance is the diffusion of ownership of IPRs in PCEs and whether they are proprietary to the platform owner or shared between several firms (Tiwana et al., 2010).
A key governance challenge in PCEs is to maintain sufficient platform control while transferring enough authority and innovation capabilities to outside complementors (Ghazawneh & Henfridsson, 2010, 2011, 2013; Tiwana et al., 2010). As noted in the literature, these conflicting objectives can be aligned through platform boundary resources, which facilitate the distribution of development capabilities at the interface between the platform owner and complementors (Ghazawneh & Henfridsson, 2010, 2011, 2013). Boundary resources can be technical and social in nature (Yoo et al., 2010). Technical boundary resources of software platforms typically comprise application programming interfaces (APIs) and software development kits (SDKs) to provide access to the platform’s functionalities and modules. Social boundary resources, on the other hand, regulate the interactions between the platform owner and the complementors through incentives, guidelines and documentation, IPRs and arm’s length agreements (Ghazawneh & Henfridsson, 2010, 2011, 2013).
Closely related to platform governance are platform regulation mechansims. Boudreau and Hagiu (2009) exemplify that platform leaders can choose from a multitude of instruments to regulate complementary innovation in PCEs, including contractual, technological, informational, investment and pricing instruments. For instance, the ownership of property rights confers ‘bouncer’s rights’ (Strahilevitz, 2006) on platform leaders to control access, set the licensing terms and exclude outsiders from PCEs (Boudreau & Hagiu, 2009). Other scholars have studied formal and informal organizational mechanisms to commit to and ensure the stability of the role allocation and firm boundaries in PCEs, which are a centerpiece of the following framework conceptualization (Gawer & Cusumano, 2002; Gawer & Henderson, 2007).
The aim of this chapter is to elucidate complementary innovation in PCEs and integrate the respective determinants into a comprehensive framework. Thereby, this chapter establishes the conceptual foundation to answer the research question raised in the introduction, i.e. what firm-level and industry-level determinants of PCEs encourage or impede complementary innovation by third-party organizations? Based on an extensive review of platform research in the strategic management, industrial organization and information systems literature, this thesis suggests to integrate four endogenous and two exogenous constituents of PCEs and their defining elements into a cohesive theoretical model.
Correspondingly, the structure of this chapter is as follows. Section 3.1 examines the links between (1) platform strategy and complementary innovation, specifically the influences of (1a) the degree of openness and (1b) market organization for complementors. (2) Platform organization is studied in Section 3.2, including the effects of (2a) vertical (dis)integration and (2b) the internal and interfirm organization. Section 3.3 takes a closer look at the inferences from (3) platform architecture and, in particular, (3a) modularity and the provision of (3b) technical boundary resources. The importance of (4) the complementary asset position of ecosystem firms and their endowment with (4a) downstream capabilities are discussed in Section 3.4. The underlying components of (5) the appropriability regime – (5a) legal protection mechanisms and (5b) technical barriers to imitation of complements – are analyzed in Section 3.5. Finally, Section 3.6 explains the relevance of (6) the industry architecture, notably (6a) the division of labor and (6b) co-specialization among ecosystem firms.
A schematic overview of the outlined structure and proposed framework is presented in Figure 2. At the end of this chapter, Table 2 summarizes the implications for complementary innovation in PCEs and the authors who contributed to theory. Furthermore, to enable a better and faster understanding of the framework’s main propositions, a synthesis of the main inferences for complementors is provided in the beginning of each section, followed by a more detailed analysis.
Figure 2: An integrated framework of the determinants of platform-centric ecosystems that influence complementary innovation
Source: Author’s own analysis
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The following section discusses the innovation behavior of independent firms in PCEs in relation to platform strategy. As one of the defining elements, (1a) the degree of openness dictates platform control and the discovery and diversity of complements. (1b) The market organization for complementors constitutes the second building block and centers on the competitive structure of PCEs in terms of market conflicts, platform pricing, complementor heterogeneity and profit distribution.
Determining the optimal level of platform openness and the respective form of technology licensing constitute one of the primary firm-level drivers of complementary innovation in PCEs (Almirall & Casadesus-Masanell, 2010; Boudreau, 2010, 2012; Economides & Katsamakas, 2006; Eisenmann et al., 2009; Gawer & Cusumano, 2002, 2014; Greenstein, 2009; Iansiti & Levien, 2004b; Laursen & Salter, 2006; Parker & Van Alstyne, 2008, 2014; Schilling, 2009; West, 2003). The decision of whether or not to open up the platform and hence innovation for external developers requires the definition of the platform owner’s complementary activity scope (Gawer & Cusumano, 2002) and involves a set of trade-offs (Almirall & Casadesus-Masanell, 2010; Boudreau, 2010; West, 2003). In principal, proprietary platforms restrict third-party participation and development, while (partly) open platform strategies facilitate and incentivize outside innovators to build complements (Almirall & Casadesus-Masanell, 2010; Boudreau, 2010, 2012; Economides & Katsamakas, 2006; Gawer & Cusumano, 2014; Laursen & Salter, 2006; West, 2003). Thus, the underlying effect of platform openness of drawing in heterogeneous and specialized knowledge and a large diversity of complements from external sources is consistent with related research on open innovation (Chesbrough, 2003; von Hippel, 2005).
In their most recent examination of platform leaders and PCE-related innovation in high-tech sectors, Gawer and Cusumano (2014) notice that openness, although varying in degree, facilitates the external development of a wide range of complements by reducing the barriers and costs of entry. The authors reemphasize that to successfully create and orchestrate an ecosystem of complementors, platform leaders have to act consistently across their established framework levers on platform leadership (see Section 2.2.1) and need to define the scope of the internal and external complementary innovation activities (Gawer & Cusumano, 2002).
In studying the strategic trade-off between appropriability and adoption in the computer industry, West (2003) finds that hybrid and open source strategies enable third-party suppliers to develop interoperable software and hardware that are not envisioned by the platform owner. Congruently, Almirall and Casadesus-Masanell (2010) assert that by devolving some control over the technology path through opening the platform, unforeseen platform features will be discovered by independent complementors. However, as a second consequence, the interests of the platform architect and outside firms will drift apart, since they generally pursue their own, unaligned objectives. This opposing effect is conceived as the trade-off between (complementary) discovery and (goal) divergence.
In the same way, Boudreau (2010) expands West’s theoretical model and postulates that platform openness induces the trade-off between diversity and control.19 According to the author, opening a platform attracts innovation activities of various contributors, which increases the diversity of complements. In his research study on handheld computing devices, the author distinguishes between restrictive forms of granting access to complementors (hybrid strategies) and relinquishing control over the platform technology (open strategy). The empirical estimates indicate an inverted-U correlation between platform access and complementary innovation, suggesting that fairly limited licensing policies result in higher outside hardware development rates than closed and open license policies (Boudreau, 2010). Similarly, based on a statistical analysis of U.K. manufacturing firms, Laursen and Salter (2006) observe an inverted-U relationship between the breadth of external search activities, defined as the variety of outside innovators, and the performance of incremental innovation. The authors conclude that openness broadens the innovation ecosystem and the set of technological opportunities available to improve existing platform standards. Although the particular reasons that shape the innovation functions in both studies are part of a different debate, they imply that platform openness for complementary innovation can be optimized. Following Parker and Van Alstyne (2008, 2014), platform owners can improve openness as long as complementors add further value.
The causal link between the number of outside innovators and diversity of complements is also recognized in a more recent inquiry by Boudreau (2012), in which independent application software providers for handheld devices are analyzed. The author highlights that in order to increase the variety of compatible and value-added applications, it is necessary to build an ecosystem of heterogeneous developers. In addition, the strategic distinctions between proprietary and open platforms have been investigated in a game-theoretic model by Economides and Katsamakas (2006) to derive conclusions about pricing and profitability for OS platforms, such as Microsoft Windows (proprietary) and Linux (open source). The scholars infer that the assortment of third-party software is greater for open platforms even if the owner of a proprietary platform subsidizes external developers.
Other scholars point out as well that increasing the number of IP licensees leads to a higher variety of downstream products and services (e.g. Rey & Salant, 2012). A more restrictive vertical strategic option to stimulate third-party investments is to grant category exclusivity, by which only one specific complementor is permitted to develop complements for a certain platform segment (Eisenmann et al., 2009). Alternatively, by pursuing a horizontal strategy and licensing additional platform providers and competitors, platform owners can spur market momentum and user mobilization that attract external developers to provide complements for their platform technology (Eisenmann et al., 2009; Hill, 1997).
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1 Other viable models of innovation are ‘producer innovation’ and ‘open collaborative innovation’ (Baldwin &von Hippel, 2011). Further prevalent forms of value creation are the ‘value chain’ and ‘value shop’ (Stabell &Fjeldstad, 1998).
2 ‘Wintel’ is the term used for the dominating personal computer architecture based on Microsoft’s operating system (OS) Windows and Intel microprocessors.
3 The term ‘complementors’ describes third-party developers, providers and suppliers of complementary products and services within the meaning of Brandenburger and Nalebuff (1997). According to the authors, two products are complementary if demand for one good increases sales for the other. Thus, customers value a product more when they can purchase complements.
4 Increasing returns to scale are typical for ‘winner-take-all markets’ where one technology emerges as the industry standard (Eisenmann et al., 2006; Hill, 1997; Schilling, 2002).
5 See for example the ‘Wintel’ standard for PCs (West &Dedrick, 2000; West, 2003).
6 In several industries, standards compete over years as currently in the mobile computing market (Apple iOS vs. Google Android). For a more detailed discussion see Schilling (2002).
7 The ‘appropriability regime’ concept is examined in Section 2.1.7 on platform dynamics.
8 Compare Nambisan and Sawhney (2011), who examine the relevance of ‘leverageable assets’ for innovation. Such assets increase in value as more firms share and use them in ecosystems.
9 Complementary innovation has been termed and first studied by Annabelle Gawer (2000).
10 A good definition of a product architecture is provided by Ulrich (1995).
11 The specific relations between complements refer to Simon's (1962, p. 474) “theory of nearly decomposable systems, in which the interactions among the subsystems are weak, but not negligible.”
12 In elaborating on platform projects, Wheelwright and Clark (1992b, p. 96) observe that the architecture of a platform “enables other features to be added or existing features to be removed.”
13 The architecture of industry platforms and MSPs is identical and based on the same design elements, i.e. decomposition, modularity and design rules (Baldwin &Woodard, 2009).
14 Platform strategy is reviewed in more detail in Section 2.2.1 of this thesis.
15 The other two factors, the complementary asset position and dominant design paradigm, are discussed in Section 2.1.4 and 2.1.2, respectively.
16 The effectiveness of different appropriability mechanisms, such as patents and trade secrets, is empirically studied in the U.S. manufacturing sector by Cohen et al. (2000).
17 As mentioned in Section 2.1.2, equity agreements (e.g. alliances, joint ventures, mergers and acquisitions) are not considered in studying complementary innovation by independent firms.
18 See Section 3.2.2 for a detailed discussion of the IAL’s role for building interfirm trust.
19 Several scholars have documented that the diffusion of property rights diminishes the coherence of the platform and may result in the loss of control over the architecture and technology trajectory (Almirall &Casadesus-Masanell, 2010; Boudreau, 2010; Iansiti &Levien, 2004b; Schilling, 2000).
