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Aseem Kinra
Researcher at University of Bremen
Publications - 38
Citations - 593
Aseem Kinra is an academic researcher from University of Bremen. The author has contributed to research in topics: Supply chain & Supply chain management. The author has an hindex of 10, co-authored 36 publications receiving 357 citations. Previous affiliations of Aseem Kinra include Copenhagen Business School.
Papers
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Journal ArticleDOI
How the Blockchain Enables and Constrains Supply Chain Performance
Kim Sundtoft Hald,Aseem Kinra +1 more
TL;DR: In this paper, a structured literature review and a theory-driven approach are used to understand the enabling and constraining roles of blockchain technology (BCT) in managerial work practices and conceptualise the technology-performance relationship in supply chain management (SCM).
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Ripple effect quantification by supplier risk exposure assessment
TL;DR: A new model to assess the ripple effect of a supplier disruption, based on possible maximum loss, is developed, comprehensively combining features such as financial, customer, and operational performance impacts, consideration of multi-echelon inventory, disruption duration, and supplier importance.
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A macro-institutional perspective on supply chain environmental complexity
Aseem Kinra,Herbert Kotzab +1 more
TL;DR: In this article, the authors use the environment-strategy-performance (E-S-P) paradigm to understand the relevance of environment complexity facing supply chain operations, while proposing that an environmental analysis best represents a multi-criteria decision-making problem.
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The impact of distance, national transportation systems and logistics performance on FDI and international trade patterns: Results from Asian global value chains
Tilo Halaszovich,Aseem Kinra +1 more
TL;DR: In this paper, the authors provide theoretical arguments and empirical evidence that national transportation systems moderate the effects of different dimensions of (between-) country distance on international trade and FDI performance.
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An Unstructured Big Data Approach for Country Logistics Performance Assessment in Global Supply Chains
TL;DR: A new and unconventional approach for logistics system performance assessment is explored, and a new potential for textual big data analytic applications in supply chain management is demonstrated.