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- ZeitschriftenartikelThe Effects of Digital Technology on Opportunity Recognition(Business & Information Systems Engineering: Vol. 64, No. 1, 2022) Kreuzer, Thomas; Lindenthal, Anna-Katharina; Oberländer, Anna Maria; Röglinger, MaximilianRecognizing opportunities enabled by digital technology (DT) has become a competitive necessity in today’s digital world. However, opportunity recognition is a major challenge given the influence of DT, which not only disperses agency across various actors, but also blurs boundaries between customers, companies, products, and industries. As a result, traditional entrepreneurship knowledge needs to be rethought and the effects of DT on opportunity recognition need to be better understood. Drawing from opportunity recognition theory – as one of the central theories in the entrepreneurship domain – this study builds on a structured literature review to identify and explain three direct as well as three transitive effects of DT on opportunity recognition. These effects have been validated with real-world cases as well as interviews with academics and practitioners. In sum, this study contributes to descriptive and explanatory knowledge on the evolution from traditional to digital entrepreneurship. As a theory for explaining, the findings extend opportunity recognition theory by illuminating how and why DT influences opportunity recognition. This supports research and practice in investigating and managing opportunities more effectively.
- ZeitschriftenartikelPathways to Developing Digital Capabilities within Entrepreneurial Initiatives in Pre-Digital Organizations(Business & Information Systems Engineering: Vol. 64, No. 1, 2022) Keller, Robert; Ollig, Philipp; Rövekamp, PatrickTo enable new digital business models, pre-digital organizations launch entrepreneurial initiatives. However, in developing the required digital capabilities, pre-digital organizations often face challenges as they are marked by the ways they have historically established their organizational identity. Research on how pre-digital organizations can develop digital capabilities remains scarce. This study draws on a single case study to illustrate potential pathways for the development of digital capabilities. Two key characteristics are identified: the source of digital capability development and the set-up of the actors involved. The authors synthesize four possible pathway manifestations, discuss the dynamic nature of pathway combinations, and suggest that managing a portfolio of pathways may be crucial for pre-digital organizations. Therefore, the study contributes to a better understanding of digital transformation in pre-digital organizations. Furthermore, it provides guidance for practitioners to reflect on when deciding which pathways to follow.
- ZeitschriftenartikelOfferings That are "Ever-in-the-Making"?(Business & Information Systems Engineering: Vol. 64, No. 1, 2022) Lehmann, Julian; Recker, JanDigital ventures are entrepreneurial young firms that introduce new digital artifacts that are "ever-incomplete" and "perpetually-in-the-making" onto the market. The study examines how six digital ventures continued to develop their digital market offerings post launch. Three key designing mechanisms are identified that explain continuous post-launch product development in digital ventures: deploying complementary digital objects, architectural amplification, and porting. The study discusses how these mechanisms advance our understanding of how digital technologies change entrepreneurial processes and outcomes.
- ZeitschriftenartikelAI Startup Business Models(Business & Information Systems Engineering: Vol. 64, No. 1, 2022) Weber, Michael; Beutter, Moritz; Weking, Jörg; Böhm, Markus; Krcmar, HelmutWe currently observe the rapid emergence of startups that use Artificial Intelligence (AI) as part of their business model. While recent research suggests that AI startups employ novel or different business models, one could argue that AI technology has been used in business models for a long time already—questioning the novelty of those business models. Therefore, this study investigates how AI startup business models potentially differ from common IT-related business models. First, a business model taxonomy of AI startups is developed from a sample of 100 AI startups and four archetypal business model patterns are derived: AI-charged Product/Service Provider, AI Development Facilitator, Data Analytics Provider, and Deep Tech Researcher. Second, drawing on this descriptive analysis, three distinctive aspects of AI startup business models are discussed: (1) new value propositions through AI capabilities, (2) different roles of data for value creation, and (3) the impact of AI technology on the overall business logic. This study contributes to our fundamental understanding of AI startup business models by identifying their key characteristics, common instantiations, and distinctive aspects. Furthermore, this study proposes promising directions for future entrepreneurship research. For practice, the taxonomy and patterns serve as structured tools to support entrepreneurial action.
- ZeitschriftenartikelDigital Entrepreneurship: What is New if Anything?(Business & Information Systems Engineering: Vol. 64, No. 1, 2022) Steininger, Dennis M.; Kathryn Brohman, M.; Block, Jörn H.
- ZeitschriftenartikelEras of Digital Entrepreneurship(Business & Information Systems Engineering: Vol. 64, No. 1, 2022) Kollmann, Tobias; Kleine-Stegemann, Lucas; Cruppe, Katharina; Then-Bergh, ChristinaWhile recent research continues to emphasize the importance of digital entrepreneurship, the historical terminology of this field is often overlooked. Digital entrepreneurship tends to be considered a new phenomenon despite emerging in the early 1990s. Building on a scoping literature review, this study analyzes 1354 publications that use nine different terms interchangeably to describe the phenomenon of digital entrepreneurship. Based on the number of publications per year, three eras in the historical development of digital entrepreneurship research are outlined. Digital technologies are identified as external enablers, and certain practical events are considered to be influencing factors. The results show that recent research has not adequately recognized the contributions of previous publications and that the understanding of digital entrepreneurship is quite similar with regard to the terms used and over time. This study shows how emerging digital technologies, such as artificial intelligence, blockchain technology, and big data analytics, might shape the future of digital entrepreneurship research. The study occupies the intersection between entrepreneurship and information systems literature and its main contribution is to provide new insights into the eras of digital entrepreneurship from the past to the present and into the future.
- ZeitschriftenartikelInterview with Frank Petry on "Digital Entrepreneurship: Opportunities, Challenges, and Impacts"?(Business & Information Systems Engineering: Vol. 64, No. 1, 2022) Steininger, Dennis M.
- ZeitschriftenartikelUniversal Wallets(Business & Information Systems Engineering: Vol. 64, No. 1, 2022) Jørgensen, Kim Peiter; Beck, Roman