Digital Twins (DT) are an emerging trend in diversified industrial sectors and their value chains. This study aims to explore current DT applications within SCs, focusing on sustainable inbound and outbound logistics and identifying key enablers that will facilitate the successful adoption of DTs in SCs. Using the PEO model and employing the PRISMA framework, this study screened articles from the Scopus database to explore the existing knowledge related to this topic. A steep increase in articles related to DTs over the past 10 years indicates that there is growing attention in exploring and leveraging this technology for various applications. The successful adoption of DTs is driven by several key factors, including advanced technological infrastructure; standardized processes; continuous improvement; knowledge workers; technologies like IoT, IIoT, AR/VR; and managerial support.

Digital Twins provide comprehensive capabilities to solve critical logistics problems such as visibility, monitoring, optimization, prediction, and simulation. This study explores the existing DT readiness assessment models in SCs and logistics, discovers their limitations, and proposes a conceptual model based on an organization’s internal and external attributes to strategize DT implementation in logistic functions. The results showed that the existing readiness assessment models have weaknesses and drawbacks, motivating the researchers to develop a new logistic DT readiness assessment model. This study identified six main organizational dimensions directly affecting measuring overall logistics’ DT readiness, which are management readiness, personnel readiness, information readiness, organization readiness, product readiness, and process flow readiness. Their relationship is mediated by Technology Integration and moderated by Supply Chain Complexity, which was tested using partial least squares structural equation modeling to show the importance of strategizing DT implementation in logistics.