R
Ravi Shankar
Researcher at Indian Institute of Technology Delhi
Publications - 751
Citations - 23389
Ravi Shankar is an academic researcher from Indian Institute of Technology Delhi. The author has contributed to research in topics: Supply chain & Supply chain management. The author has an hindex of 66, co-authored 672 publications receiving 19326 citations. Previous affiliations of Ravi Shankar include International Institute of Information Technology, Hyderabad & Korean Ocean Research and Development Institute.
Papers
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Analysis of interactions among the barriers of reverse logistics
V. Ravi,Ravi Shankar +1 more
TL;DR: In this article, the authors analyze the interaction among the major barriers, which hinder or prevent the application of reverse logistics in automobile industries, using Interpretive Structural Modeling (ISM) to understand the mutual influences among the barriers.
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Modeling the metrics of lean, agile and leagile supply chain: An ANP-based approach
TL;DR: The paper explores the relationship among lead-time, cost, quality, and service level and the leanness and agility of a case supply chain in fast moving consumer goods business and the justification of the framework is presented, which encapsulates the market sensitiveness, process integration, information driver and flexibility measures of supply chain performance.
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Selection of logistics service provider: An analytic network process (ANP) approach
Sanjay Jharkharia,Ravi Shankar +1 more
TL;DR: In this paper, the authors present a comprehensive methodology for the selection of a logistic service provider, which consists of two parts: (i) preliminary screening of the available providers, and (ii) analytic network process (ANP)-based final selection.
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Modeling agility of supply chain
TL;DR: In this paper, using interpretive structural modeling, interrelationships of the variables, influencing supply chain agility, have been derived, and these variables have been categorized according to their driving power and dependence.
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Supply chain risk mitigation: modeling the enablers
TL;DR: There exists a group of enablers having a high driving power and low dependence requiring maximum attention and of strategic importance while another group consists of those variables which have high dependence and are the resultant actions.