Falk Freese

PhD Candidate

Falk Freese

PhD Candidate

Falk Freese is a PhD Candidate at Kühne Logistics University in the field of Computer Science in Logistics under the supervision of Prof. Dr. André Ludwig and Prof. Dr. Kai Hoberg. He is conducting research at the intersection of supply chain management and information systems.

Falk Freese received his Master’s degree in Information Systems from the University of Bamberg in 2018. In his master thesis, he empirically investigated the adoption of cryptocurrencies and user resistance behavior. Falk completed his Bachelor’s degree in Information Systems at the FOM University of Applied Sciences for Economics and Management in Nuremberg with a specialization in web engineering. 

In addition to his academic education, Falk gained practical experience as a consultant for software tests.
 

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DOI: https://doi.org/10.1080/13675567.2024.2324895 

Abstract: Digital twins, due to digitalisation, are increasingly adopted across industries. The supply chain industry, with its process-driven nature, collaboration of multiple stakeholders and dependability on real-time events, demands unique characteristics for the implementation of digital twins. While these twins can enhance supply chain transparency and responsiveness, there is a lack of an application framework. The aim of this paper is to address this absence of a specialised application framework. The framework outlines multiple layers, dimensions, and stakeholder-technology dependencies for early-phase adoption. It is designed to guide planners and operators of supply chains in planning, implementing, and introducing new supply chain digital twins. Using the design science approach as a research methodology, the framework is informed by literature and expert interviews. Its validity is confirmed through further expert evaluations, and the study concludes with key insights and guidelines derived from the framework.

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DOI: https://doi.org/10.1007/978-3-030-86800-0_23 

Abstract: Transparency of supply chains is important. A more transparent supply chain would help to react in real-time by detecting and solving many issues e.g. production interruptions and delivery bottlenecks. A supply chain digital twin can help to increase the transparency and create an overall more robust and flexible supply chain. With real-time data streams from sensors, a digital twin allows simulation, monitoring, and controlling and provides information about its real-world counterpart. Based on a literature review approach, we analyze academic and industrial application and use cases to identify the current state-of-the-art of supply chain digital twins. Subsequently we develop a classification scheme for supply chain digital twins. The classification scheme provides six different dimensions like scope, actor, asset, flow reference object, performance measurement, and supply chain process that are relevant for digital twins in the context of supply chain.

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Academic Positions

2018 – 2019 Researcher, University of Hamburg, Germany

 

Professional Experience

2015 – 2018        Working Student for Process Engineering X-Ray Products at Siemens Healthcare, Forchheim, Germany
2012 – 2015     Consultant for Software Tests at imbus AG, Möhrendorf, Germany

Education

Since 2019 PhD Candidate at Kühne Logistics University, Hamburg, Germany
2018 Master of Science in Information Systems, University of Bamberg, Germany
2015 Bachelor of Science in Information Systems, FOM University of Applied Sciences for Economics and Management in Nuremberg, Germany
2012 Apprenticeship as a Computer Science Expert, Subject Area: Software Development, Nuremberg Chamber of Commerce and Industry, Germany