To integrate information across organizational boundaries, different actors operating in the same industry may decide to develop new digital platforms, in order to enable new business ecosystems with other companies. In Publications I–IV, my co-authors and I approach the early stages of this decision-making, planning, and negotiating process.
For that purpose, we rely upon various streams of IS literature that propose different but related theoretical lenses, which are clarified and compared in this section.
2.2.1 Digital platforms
The scientific literature on digital platforms is extensive and originates from different research streams, such as strategic management, marketing, economics, SE, and IS (Tiwana, Konsynski and Bush, 2010; Rolland, Mathiassen and Rai, 2018; Bazarhanova, 2020; Hein et al., 2020). Gawer (2014) and Rolland et al. (2018) have outlined the following perspectives on platform research, each with its own set of contrasting assumptions about the constitutive elements and evolution of platforms:
- The technological, technical, or engineering perspective originates from physical product and software product development (Rolland, Mathiassen and Rai, 2018). It approaches digital platforms as technical artifacts (de Reuver, Sørensen and Basole, 2018) or extensible codebases of purposefully designed software architecture (Gawer, 2014), which provide a relatively stable core functionality as well as interfaces to integrate complementary modules with high variability (Tiwana, Konsynski and Bush, 2010).
- The economic perspective portrays digital platforms as two-sided or multi-sided markets (Gawer, 2014; de Reuver, Sørensen and Basole, 2018). It focuses on the business models empowered by network effects among different groups of consumers, whose interactions are mediated by the platform and who otherwise would be unable to transact with one another (Gawer, 2014).
- The organizational perspective approaches platforms as evolving organizations or meta-organizations (Gawer, 2014). It emphasizes the innovation practices and governance mechanisms of different actors, who loosely organize themselves around the same technical assets and commonly agreed social arrangements in order to develop complementary products or services (Rolland, Mathiassen and Rai, 2018; Bazarhanova, 2020; Hein et al., 2020).
Existing studies have suggested the need for better integration of platform research contributions under the organizational perspective. I support this view, and in this thesis, I adopt the sociotechnical definition of digital platforms as an assemblage of extensible technical artifacts of hardware and software, which provide core functionality and control arrangements, together with their associated organizational practices and standards (de Reuver, Sørensen and Basole, 2018, pp. 126-127). Furthermore, I refer to industry(-wide) platforms, which enable one or more firms to co-create innovative products, technologies, or services, in contrast to company-specific or product platforms, which are used by individual firms to organize internal resources and develop their own derivative products (Gawer and Cusumano, 2014).
Different mechanisms of platform ownership and governance have been described in previous studies (Tiwana, Konsynski and Bush, 2010; de Reuver, Sørensen and Basole, 2018; Saadatmand, Lindgren and Schultze, 2019). Platform ownership refers to whether the proprietary of the platform is a single firm or multiple firms (not to be confused with open source versus closed software architecture), whereas platform governance refers to the distribution of the decision-making authority, the rights, and the responsibilities for the platform. Thus, platform ownership and control are two distinct attributes of platform governance (Tiwana, Konsynski and Bush, 2010).
According to Gawer (2014), the agents interacting with a platform can be classified into one focal leader or owner and multiple complementors or third-party contributors that act on the periphery. Platform governance entails the partitioning and balance of power between these two types of actors (Tiwana, Konsynski and Bush, 2010). Consequently, one of the major challenges frequently identified in the IS literature on platform governance is the platform owners’ establishment of formal and informal control mechanisms to ensure that complementors remain aligned with what is in the best interest of the platform and at the same time, avoid imposing excessive constraints on the complementors, which would hinder the desired level of generativity or contributions to the platform (Constantinides, Henfridsson and Parker, 2018).
From another point of view, Eisenmann (2008) categorizes the organizations typically involved in platform development into two roles: sponsors, who control the technology and participation rights, and providers, who mediate the interactions between and among users. Either role can be served by one or multiple firms. Hein (2020) argues that platform ownership is not only about the legal entity that formally owns the platform but also about the effective control and the distribution of power in the ecosystem, which can be centralized (i.e., single owner/firm) or decentralized (i.e., multiple owners/consortia).
2.2.2 Digital infrastructures
Digital infrastructures are shared, unbounded, open, heterogeneous and evolving sociotechnical systems, composed of a set of different IT capabilities and various communities of designers, operators, and users (Hanseth and Lyytinen, 2010, p. 4; see also Tilson, Lyytinen and Sørensen, 2010, pp. 748-749). This term has been adopted as a way of conceptualizing interconnected system collectives rather than standalone IS and allows researchers to shift their focus of analysis from a single organization to entire networks (Henfridsson and Bygstad, 2013).
According to Hanseth and Lyytinen (2010), digital infrastructures have a more complex and dynamic design than software platforms or applications. It has also been proposed that digital platforms are always created and cultivated on top of a digital infrastructure (Constantinides, Henfridsson and Parker, 2018). Since platforms are managed centrally by one (or more) owner (owners), who enable new IT capabilities for themselves or for others through boundary resources and APIs, the architectural design and functional specifications of digital platforms tend to be (semi-)closed to meet the needs of various heterogeneous and growing user communities.
In the case of digital infrastructures, the evolution is constantly negotiated and distributed among different actors or user communities (Hanseth and Lyytinen, 2010).
This process is built around the notion that digital infrastructures are never complete and emerge or evolve through generativity, which is defined as self-contained systems’
capability to create or produce new outputs, structures, or behaviors without any input from the system’s originator (Tilson, Lyytinen and Sørensen, 2010). Generativity is enabled by the permanence of an installed base, which represents the status quo or the shared stable core functions and components, both technical and social, which can be currently found in a digital infrastructure (Lyytinen, Sørensen and Tilson, 2017). The installed base is the starting point for changing or extending the infrastructure (i.e., anything new must be compatible with it). When the inertia of the installed base reduces its usefulness for users who require new functionalities, these users may employ persuasive tactics and gain the momentum for adapting, re-organizing, and growing the digital infrastructure (Hanseth and Lyytinen, 2010).
In summary, the main feature that sets digital platforms and infrastructures apart constitutes their control mechanisms (Hanseth and Lyytinen, 2010; de Reuver, Sørensen and Basole, 2018). On one hand, the IS literature on platforms portrays evolution and integration as processes managed by the platform owner, which can be a single organization or a consortium of firms, through sets of assets that can be extended by complementors or external innovators. On the other hand, IS literature portrays the evolution and integration of digital infrastructures as a permanent and often unpredictable process of generativity, which may occur as the users’ response to the inertia of the installed base.
In Publication II, we use the concepts of digital infrastructures and IOIS interchangeably, but there are some key differences between them. Although the concept of digital infrastructures is very broad, it does not specify if the integration reach of systems and data is intra-organizational or cross-organizational. Therefore, a software platform managed by a single organization can still be built on top of a digital infrastructure but does not fit under the category of IOIS.
2.2.3 Ecosystems
Ecosystems constitute a key concept in the studies about the emergence and evolution of digital platforms (de Reuver, Sørensen and Basole, 2018; Bazarhanova, 2020). In IS literature, the term “ecosystem” is a metaphor used to characterize organizations as living entities that evolve over time. It refers to a group of distinct yet interdependent actors that are interlinked by common interests and depend on one another’s activities, which are usually organized around a set of shared artifacts on a central digital platform (Selander, Henfridsson and Svahn, 2013; Jacobides, Cennamo and Gawer, 2018).
Ecosystems bring the researcher’s attention to the changes in the digital artifacts and in the organizations around them, turning both into a single and more captivating object of inquiry than just the platform alone (Bazarhanova, 2020).
Guggenberger et al. (2020) conducted a structured review of IS literature on ecosystems and identified the following types:
- Business ecosystems focus on the interdependencies among actors that
complement one another’s capabilities through cooperation and competition, in order to offer value propositions that can satisfy customer needs, with or without a platform-based technological architecture (Kapoor, 2018).
- Platform ecosystems focus on the technological infrastructure consisting of various modules that enable external innovation, through boundary resources such as APIs, software development kits (SDKs), or integrated development environments (IDEs), whereas the evolving ecosystem brings together software owners/vendors, complementors, and users (Tiwana, Konsynski and Bush, 2010;
Ghazawneh and Henfridsson, 2013).
- Service ecosystems focus on the collaborative creation (i.e., co-creation) of new value-adding services among different interconnected actors that continuously integrate resources and whose relationships are regulated through shared institutional logics, standards, and digital technologies (Vargo and Lusch, 2011;
Eaton et al., 2015).
- Innovation ecosystems draw on the premises of business ecosystems and service ecosystems but with greater emphasis on the steps of the value-capturing process, such as the combination of the firms’ individual value propositions, the exploitation of business opportunities, and the creation of desirable customer-facing solutions (Dattée, Alexy and Autio, 2018).
- Software ecosystems focus on the interactions of actors around a standard technological platform and on business-related aspects, such as revenue models or user satisfaction (Basole and Park, 2019).
The multiple similarities and overlaps among ecosystem types (Aksenova et al., 2019) make it difficult to establish a clear-cut distinction among them. Basole and Park (2019) found that prior studies refer to at least three common elements of most ecosystems: (1) a central software artifact or technological platform; (2) the exchange of various forms of value, such as financial value, information, or knowledge; and (3) the relationships among actors.
Since in this thesis, I focus on socio-organizational aspects of integration, I do not analyze in depth the technical artifacts (i.e., software applications and algorithms) at the core or periphery of any specific digital platform. Instead, I generally analyze and discuss the artifacts that enable the collaboration among ecosystem actors at a higher level of abstraction than the programming code. Furthermore, the data collected for Publications I–IV come primarily from semi-structured interviews with practitioners rather than from software development and testing activities. Consequently, this thesis aligns more closely with and contributes to the streams of IS literature on business ecosystems, service ecosystems, and especially innovation ecosystems, which describe ecosystems as networks of companies that cooperate with the goal of jointly creating (“co-creating”) new value for their customers (Aksenova et al., 2019; Guggenberger et al., 2020).