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Designing value architectures for emerging technologies

  • The business model has emerged as a construct to understand how firms drive innovation through emerging technologies. It is defined as the ‘architecture of the firm’s value creation, delivery and appropriation mechanisms’ (Foss & Saebi, 2018, p. 5). The architecture is characterized by complex functional interrelations between activities that are conducted by various actors, some within and some outside of the firm. In other words, a firm’s value architecture is embedded within a wider system of actors that all contribute to the output of the value architecture. The question of what drives innovation within this system and how the firm can shape and navigate this innovation is an essential question within innova- tion management research. This dissertation is a compendium of four individual research articles that examine how the design of a firm’s value architecture can fa- cilitate system-wide innovation in the context of Artificial Intelligence and Block- chain Technology. The first article studies how firms use BlockchainThe business model has emerged as a construct to understand how firms drive innovation through emerging technologies. It is defined as the ‘architecture of the firm’s value creation, delivery and appropriation mechanisms’ (Foss & Saebi, 2018, p. 5). The architecture is characterized by complex functional interrelations between activities that are conducted by various actors, some within and some outside of the firm. In other words, a firm’s value architecture is embedded within a wider system of actors that all contribute to the output of the value architecture. The question of what drives innovation within this system and how the firm can shape and navigate this innovation is an essential question within innova- tion management research. This dissertation is a compendium of four individual research articles that examine how the design of a firm’s value architecture can fa- cilitate system-wide innovation in the context of Artificial Intelligence and Block- chain Technology. The first article studies how firms use Blockchain Technology to design a governance infrastructure that enables innovation within a platform ecosystem. The findings propose a framework for blockchain-enabled platform ecosystems that address the essential problem of opening the platform to allow for innovation while also ensuring that all actors get to capture their share of the value. The second article analyzes how German Artificial Intelligence startups design their business models. It identifies three distinct types of startup with dif- ferent underlying business models. The third article aims to understand the role of a firm’s value architecture during the socio-technical transition process of Arti- ficial Intelligence. It identifies three distinct ways in which Artificial Intelligence startups create a shared understanding of the technology. The last article exam- ines how corporate venture capital units configure value-adding services for their venture portfolios. It derives a taxonomy of different corporate venture capital types, driven by different strategic motivations. Ultimately, this dissertation provides novel empirical insights into how a firm’s value architecture determines it’s role within a wider system of actors and how that role enables the firm to facilitate innovation. In that way, it contributes to both business model and innovation management literature.show moreshow less

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Metadaten
Author details:Jessica Schmeiss
Subtitle (English):empirical insights on the role of the firm in system-wide innovation
Reviewer(s):Katharina HölzleORCiDGND, Thomas SchildhauerGND
Publication type:Doctoral Thesis
Language:English
Publication year:2019
Publishing institution:Universität Potsdam
Granting institution:Universität Potsdam
Date of final exam:2019/12/17
Release date:2020/01/29
Tag:Artificial Intelligence; Blockchain; Business Model; Ecosystem; Emerging Technologies; Innovationmanagment
Number of pages:135
Organizational units:Wirtschafts- und Sozialwissenschaftliche Fakultät / Wirtschaftswissenschaften
DDC classification:3 Sozialwissenschaften / 33 Wirtschaft / 330 Wirtschaft
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