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Given the hype around the cryptocurrency Bitcoin, blockchain technology (BCT) has also received considerable attention outside the financial sector. Multiple applications of BCT in supply chain management (SCM) are discussed in business practice and there is increasing interest in this topic within the academic community. In this paper, we intend to combine these two perspectives on BCT in SCM to summarize a current state of the art and to derive avenues for further research. For this purpose, a comprehensive framework of use case clusters of BCT in SCM is developed according to the distinctive features of BCT. The framework is used to analyze 53 applications of BCT in SCM which are derived from a systematic literature review and a secondary dataset of blockchain-driven innovations in SCM. We identify five emerging use case clusters of BCT in SCM which clearly extend the scope beyond frequently mentioned applications such as product tracking and tracing.

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Economic Value Added (EVA s ) and corresponding value driver trees are prevalent frameworks of value-based management to measure and analyse shareholder value creation. However, they are explanatory models from an operations research perspective and do not provide decision support for performance optimisation. In this paper, we develop a comprehensive value-based decision framework for mid-term sales and operations planning (S&OP) in the supply chain implementing EVA as the objective function. The pivotal element of our framework is a decision-oriented extension of EVA-based value driver trees bridging the gap to the decision variables of S&OP as the operational performance levers. We utilise a numerical example to highlight the significant improvement potential due to the value-based optimisation approach. Working capital management emerges as the major mid-to shortterm value driver in the supply chain.