Managing the Dynamics of Platforms and Ecosystems

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    Visualizing the Evolution of the AI Ecosystem
    ( 2021-01-05) Basole, Rahul
    This study examines the evolution of the complex, emerging artificial intelligence (AI) ecosystem. Grounded in multiple theories, we introduce a conceptual framework that maps emerging ecosystem dynamics in terms of firm funding and exits. Using a curated dataset of nearly 10,000 ventures and 31,000+ funding/exit activities, we visualize the trajectory of 15 core technology segments of the AI ecosystem as connected scatterplots and compute several salient path measures for each, including path length, velocity, number of loops, and L-shapes. Our visual analysis reveals several path patterns across the four quadrants of our framework and highlights the evolutionary growth and consolidation across segments. We discuss our findings in terms of initial conditions (market size, funding, technology hype), platformication, and geographic concentration. Our study contributes to our data-driven understanding of ecosystem dynamics.
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    The Emergence and Dynamics of Electronic Health Records – A Longitudinal Case Analysis of Multi-Sided Platforms from an Interoperability Perspective
    ( 2021-01-05) Stegemann, Lars ; Gersch, Martin
    Emerging health record platforms are interesting examples of the ongoing process of digitalization and the great opportunities they provide for innovation and additional services. Incumbent players are under increasing pressure from new entrants to offer their customers a user experience they have become familiar with through platforms such as Apple and Google. The emergence of the digital German health record is shown as a case-study, harnessing a longitudinal database and adopting a process-sensitive perspective. Important events are structured into individual episodes and phases and discussed in-depth. The study shows how platform owners of health records respond to changes in the highly regulated healthcare system and its digitalization in Germany. Contrasting with extant knowledge about interoperability as a relevant precondition for platforms, our study shows the important role played by interoperability as a design parameter for emerging platforms, which results in seven interoperability challenges for respective stakeholders.
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    The Effects of Control Mechanisms on Complementors’ Behavioral Intentions: An Empirical Study of Reward-Based Crowdfunding Platforms
    ( 2021-01-05) Croitor, Evgheni ; Werner, Dominick ; Benlian, Alexander
    Although Information Systems research has been increasingly exploring the role of control mechanisms on digital platforms, empirical research on the effects of control mechanisms on complementors’ behavioral intentions in platform ecosystems is sparse. Control mechanisms refer to measures employed by platform providers to influence desirable behaviors of complementors and thus to manage dynamics, growth, and evolution of their digital platforms. Drawing on IS control literature and goal attainment theory, we conducted an online survey with 116 complementors from two major reward-based crowdfunding platforms, Kickstarter and Indiegogo. Our findings reveal that input control (self control) decreases (increases) complementors’ intention to stay on their respective digital platform. Furthermore, we shed light on the role of complementors’ perceived effort, perceived usefulness and satisfaction in shaping these relationships. Thus, our findings contribute to the literature on digital platforms in general and control mechanisms in particular.
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    Taxonomy of Digital Platforms: A Business Model Perspective
    ( 2021-01-05) Staub, Nicola ; Haki, Kazem ; Aier, Stephan ; Winter, Robert
    Digital platforms (DPs) – technical core artifacts augmented by peripheral third-party complementary resources – facilitate the interaction and collaboration of different actors through highly-efficient resource matching. As DPs differ significantly in their configurations and applications, it is important from both a descriptive and a design perspective to define classes of DPs. As an intentionally designed artifact, every classification pursues a certain purpose. In this research, the purpose is to classify DPs from a business model perspective, i.e. to identify DP clusters that each share a similar business model type. We follow Nickerson et al.’s (2013) method for taxonomy development. By validating the conceptually derived design dimensions with ten DP cases, we identify platform structure and platform participants as the major clustering constituent characteristics. Building on the proposed taxonomy, we derive four DP archetypes that follow distinct design configurations, namely business innovation platforms, consumer innovation platforms, business exchange platforms and consumer exchange platforms.
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    Positioning Strategies in Emerging Industrial Ecosystems for Industry 4.0
    ( 2021-01-05) Piller, Frank ; Van Dyck, Marc ; Lüttgens, Dirk ; Diener, Kathleen
    Many incumbents have the ambition to become ecosystem leaders when transitioning an established business model into a platform-based one. Prior research predominately has studied established consumer markets. Our study extends the empirical knowledge on ecosystem dynamics with a focus on platforms providing services based on (shared) industrial data. In a longitudinal study, we investigate factors influencing this transition and study in particular how industrial incumbents balance value creation and capture during ecosystem emergence. In this stage, managing openness is a key strategic decision. While openness is required for value creation, the complexity and physicality of the industrial setting hampers value capture. We identify control points to manage the tension between value creation & capture and derive different transition journeys. Lastly, we propose that in industrial markets, multiple platforms can co-exist in the same ecosystem, complementing the established "winner-takes-all" paradigm. Our research identifies situations where incumbents intentionally forfeit a leadership position in favor of joining an alliance-driven ecosystem
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    Moving beyond the Build-or-Join Decision: A Multiple Case Study on Multi-Platform Strategies of Incumbent Firms
    ( 2021-01-05) Hermes, Sebastian ; Guhl, Rebekka ; Schreieck, Maximilian ; Weking, Jörg ; Krcmar, Helmut
    Companies that operate digital platforms are growing rapidly. Theoretical and empirical research has largely explored digital platforms in the context of digital-native companies. Only a small set of research explores how incumbent firms transition into the platform economy. However, this stream of research has studied incumbents under the assumption that they can either build a platform or join an existing platform. In contrast, the results of our multiple case study demonstrate that incumbents pursue multiple platform strategies simultaneously and that their strategic options range from building and joining a platform over investing in and acquiring a platform to using white-label platforms. The white-label strategy uses the platform technology of a white-label platform owner to match the users of the incumbent with the complementors of the white-label platform. Based on the results, which further illustrate the motivations to pursue each strategy, we discuss strategic differences between asset-heavy and asset-light incumbents.
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    Developing Multi-Sided Markets in Dynamic Electronic Commerce Ecosystems - Towards a Taxonomy of Digital Marketplaces
    ( 2021-01-05) Wulfert, Tobias ; Seufert, Sarah ; Leyens, Christian
    Multi-sided markets (MSMs) have proven to be a successful business model in the dynamic electronic commerce environment. There exists a variety of MSMs differing in their provided features and services for their participants. Existing taxonomies often focus on value creation and business-to-business transactions. We apply Nickerson et al.’s taxonomy development approach. We especially incorporated aspects of orchestrating the distinct market sides and governance dimensions. The developed taxonomy for MSMs consists of 21 dimensions and 99 characteristics in total. We have applied our taxonomy to 44 MSMs and identified asymmetries between the market sides concerning Monetization, Network Effect Amplifiers and Provided Services. We emphasize that the taxonomy is not only an artifact for classifying the current situation of an MSM but can also be used by MSM owners to derive directions for the future development. We illustrated how these developments can be conducted by examples for five dimensions of our taxonomy.
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    Conceptualizing and Analyzing Business Ecosystem Service Offerings
    ( 2021-01-05) Betz, Christian ; Jung, Reinhard
    Business ecosystems are dynamic structures of various actors who co-create value. By combining complementary and substitute services, these actors create integrated offerings. This paper proposes a conceptual model which supports the analysis of ecosystems by de- composing the offering into distinct modules. Each module represents a beneficiary-provider duality with a specific value proposition and activities to be performed. It further describes, how different service modules con- tribute and may change the network-level purpose. The research follows design science and was facilitated in a consortium setup to integrate practitioners’ insights. The paper contributes by developing design principles for a service configuration model, identifying relevant activities to describe service creation, providing a logic to configure distinct services into a whole, and introducing the concept of substitutes into the discussion.
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    A Taxonomy for Data Ecosystems
    ( 2021-01-05) Gelhaar, Joshua ; Groß, Tobias ; Otto, Boris
    In the increasingly interconnected business world, economic value is less and less created by one company alone but rather through the combination and enrichment of data by various actors in so-called data ecosystems. The research field around data ecosystems is, however, still in its infancy. With this study, we want to address this issue and contribute to a deeper understanding of data ecosystems. Therefore, we develop a taxonomy for data ecosystems which is grounded both theoretically through the linkage to the scientific knowledge base and empirically through the analyses of data ecosystem use cases. The resulting taxonomy consists of key dimensions and characteristics of data ecosystems and contributes to a better scientific understanding of this concept. Practitioners can use the taxonomy as an instrument to further understand, design and manage the data ecosystems their organizations are involved in.
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    Introduction to the Minitrack on Managing the Dynamics of Platforms and Ecosystems
    ( 2021-01-05) Russell, Martha ; Rothe, Hannes ; Huhtamäki, Jukka