Quantifying the Benefits of Digital Supply Chain Twins—A Simulation Study in Organic Food Supply Chains

Tom Binsfeld and Benno Gerlach
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Tom Binsfeld: Chair of Logistics, Berlin University of Technology, 10623 Berlin, Germany
Benno Gerlach: Chair of Logistics, Berlin University of Technology, 10623 Berlin, Germany

Logistics, 2022, vol. 6, issue 3, 1-23

Abstract: Background : Digital supply chain twins (DSCT) are gaining increased attention in academia and practice and their positive impact on logistics and supply chain management (LSCM) performance is often highlighted. Still, LSCM executives are hesitant regarding DSCT implementation. One reason is the difficulty of making a reasonable cost–benefit comparison, because the benefits of using a DSCT are rarely quantified. Moreover, there seems to be no method of quantifying these benefits as of today. Methods : This article builds upon an extensive simulation study of a constructed organic food supply chain (FSC), containing as many as 40 simulation experiments. In this simulation study, three volatility scenarios in the FSC were simulated and their effects on LSCM performance were measured. Subsequently, dynamic simulation experiments were run to emulate DSCT use. The benefits of using a DSCT were then quantified using a newly developed approach. Results : A conclusive method for quantifying the benefits of using a DSCT is presented and validated. Moreover, the performance evaluation of using a DSCT for the multi-echelon inventory management of an organic FSC is given. Conclusions : The study leads towards a method for quantifying the use of DSCTs that is of importance for research and practice alike. For managers, it additionally provides an exemplary application of said method in the context of organic FSCs.

Keywords: digital supply chain twins; logistics and supply chain management; digital twin; logistics; supply chain management; organic food supply chains; agent-based simulation; discrete event simulation (search for similar items in EconPapers)
JEL-codes: L8 L80 L81 L86 L87 L9 L90 L91 L92 L93 L98 L99 M1 M10 M11 M16 M19 R4 R40 R41 R49 (search for similar items in EconPapers)
Date: 2022
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