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  4. Concept for Effective Identification and Initiation of Startup Investments for the Digital Transformation of Manufacturing Companies
 
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2023
Conference Paper
Title

Concept for Effective Identification and Initiation of Startup Investments for the Digital Transformation of Manufacturing Companies

Abstract
The digital transformation is fundamentally disrupting established business models and existing value chains at an accelerating pace. Faced with multidimensional and inevitable changes, many incumbent companies lack necessary competences, processes, and structures to actively transform their business with sufficient speed and extent. While successful tech-companies therefore consequently rely on startup acquisitions, investments or cooperations, most incumbent manufacturing companies are not successful in systematically leveraging external corporate venturing as a catalyst for their digital transformation. Several reasons may already be found in the early phases of an investment. This applies especially to the identification of suitable startups, the determination of the potential value contribution of an investment, and the effective initiation of startup investments. Against this background, this paper presents a concept for effectively identifying and initiating external corporate venturing initiatives for the digital transformation of manufacturing companies. Thus, existing approaches in literature are discussed and analyzed to derive the requirements for developing a concept, which enables effectively identifying suitable startups for digital transformation objectives and subsequently initiating an investment. Based on these findings, the methodology and its sub-models are derived.
Author(s)
Schuh, Günther  
TH Aachen -RWTH-, Werkzeugmaschinenlabor -WZL-  
Schenk, Leonard P.  
Fraunhofer-Institut für Produktionstechnologie IPT  
Mainwork
IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2023  
Conference
International Conference on Industrial Engineering and Engineering Management 2023  
DOI
10.1109/IEEM58616.2023.10406396
Language
English
Fraunhofer-Institut für Produktionstechnologie IPT  
Keyword(s)
  • Digital transformation

  • Companies

  • Transforms

  • Manufacturing

  • Object recognition

  • Investment

  • Business

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