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Ravi Anupindi

Researcher at University of Michigan

Publications -  46
Citations -  4421

Ravi Anupindi is an academic researcher from University of Michigan. The author has contributed to research in topics: Supply chain & Artifact-centric business process model. The author has an hindex of 23, co-authored 42 publications receiving 4097 citations. Previous affiliations of Ravi Anupindi include Northwestern University & Carnegie Mellon University.

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Coordination and Flexibility in Supply Contracts with Options

TL;DR: It is shown that credit for returns offered by the supplier does not always coordinate the channel and credits for returns are useful only on a subset of the feasibility region under which channel coordination is achievable with linear prices.
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Diversification under supply uncertainty

TL;DR: In this article, the authors address the operational issue of quantity allocation between two uncertain suppliers and its effects on the inventory policies of the buyer, and derive the optimal ordering policies that minimize the total ordering, holding and penalty costs with backlogging.
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Creating mutual value: Lessons learned from ventures serving base of the pyramid producers

TL;DR: In this paper, the authors assess how business ventures serving the base of the pyramid (BoP) producers address local constraints and create mutual value, using a case study methodology, sixty-four ventures are analyzed to identify the constraints faced by BoP producers.
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Single-Period Multiproduct Inventory Models with Substitution

TL;DR: In a limited computational study using two products, the benefits of solving for the optimal quantities when substitution is considered at the ordering stage over similar computations without considering substitution while ordering are illustrated.
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A General Framework for the Study of Decentralized Distribution Systems

TL;DR: A "coopetitive" framework for the sequential decisions of inventory and allocation of stocks is developed and it is shown that there exists an allocation mechanism that achieves the first-best solution for inventory deployment and allocation.