Background: Digital supply chain twins (DSCT) are gaining increased attention in academia and practice as they emerge as one of the most important trends in logistics and supply chain management (LSCM). Still, there seems to be no common understanding of the term in scientific literature. Moreover, the broad field of LSCM allows for a multitude of feasible application areas and use cases, yet there exists no conclusive list of them as to date. Methods: This study builds upon a systematic literature review of 66 DSCT articles to identify application areas of DSCT in LSCM as well as specific use cases and their respective intended benefits. Results: To start with, the study derives a unified definition of DSCTs, including possible scopes of applications. Afterwards, five application areas of DSCT in LSCM are synthesized as well as 14 individual use cases and their respective intended benefits. Conclusions: The study leads towards a conceptual clarification of DSCT that is of importance for research and practice alike. For managers it additionally provides up-to-date use cases to guide DSCT applications in practice.

Both modern multi- and intermodal supply chains pose a significant challenge to control and maintain while offering numerous optimization potential. Digital Twins have been proposed to improve supply chains. However, as of today, they are only used for certain parts of the entire supply chain. This paper presents an initial framework for a holistic Digital Supply Chain Twin (DSCT) capable of including an entire multimodal supply chain. Such a DSCT promises to enable several improvements all across the supply chain while also be capable of simulating and evaluate several different scenarios for the supply chain. Therefore, the DSCT will not only be able to optimize multi- and intermodal supply chains but also makes them potentially more robust by identifying possible issues early on. This paper discusses the major requirements that such a DSCT must fulfil to be useful and how several information technologies that matured in recent years or are about the mature are the key enablers to fulfil these requirements. Finally, a suggested high-level architecture for such a DSCT is presented as a first step towards the realization of a DSCT, as presented in this work

Fighting counterfeit drugs in pharma logistics networks, is one of the most important challenges in the industry. In order to contribute to the UN Sustainable Development Goal of “global health and well-being” the integration of counterfeit substances and drugs has to be stopped but is still causing significant human and economic damage. Although the problem is known for decades no approach is known that eradicates the problem. Blockchain technology is promoted as a potential solution to counterfeit drugs since it combines the properties of tamper-proof data storage and secure information transfer but its’ application in the pharma industry is still lacking behind the theoretical potential. This study seeks to assess the applicability of blockchain technology to tackle drug counterfeiting in pharma networks and to develop an implementation framework that outlines industry-specific implementation barriers and mitigation measures as well as their interdependencies. Building on nine interviews with industry experts, Grounded Theory was applied. Accordingly, the interview results were condensed into a theory by applying a three-stage coding process. Building on this analysis, an implementation framework for blockchain technology to tackle drug counterfeiting in the pharma industry is developed. The framework explains the enablers, barriers, and implementation strategies as well as the relation between them. It is shown that blockchain implementation is not hindered by a lack of technological maturity, but mostly by opposing incentive mechanisms of stakeholders involved.

Digital Supply Chain Twins (DSCT) are gaining more and more attention both in science and in practices. They are considered to be one of the most disruptive technologies in logistics and supply chain management. In the literature, there are a variety of DSCT benefits in the case of planning and control a logistics system. Some of these potentials could also be highly suitable for the use case of sustainable and resource-efficient logistics, which, however, have been insufficiently explored in research so far. This paper will investigate to what extent the DSCT can be used to enable sustainable network planning and which potentials the DSCT implies for the predictive planning within logistics systems. Building on a literature review and interviews with industry experts a case study was conducted at a business partner in the automotive industry.

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