Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Resilience: the concept, a literature review and future directions
2011972 citationsRan Bhamra, Samir Dani et al.International Journal of Production Researchprofile →
Supply chain risk management and artificial intelligence: state of the art and future research directions
2018559 citationsGeorge Baryannis, Sahar Validi et al.International Journal of Production Researchprofile →
Supply chain risk management: present and future scope
2012312 citationsAbhijeet Ghadge, Samir Dani et al.The International Journal of Logistics Managementprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Samir Dani's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Samir Dani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Samir Dani more than expected).
This network shows the impact of papers produced by Samir Dani. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Samir Dani. The network helps show where Samir Dani may publish in the future.
Co-authorship network of co-authors of Samir Dani
This figure shows the co-authorship network connecting the top 25 collaborators of Samir Dani.
A scholar is included among the top collaborators of Samir Dani based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Samir Dani. Samir Dani is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Baryannis, George, Sahar Validi, Samir Dani, & Grigoris Antoniou. (2018). Supply chain risk management and artificial intelligence: state of the art and future research directions. International Journal of Production Research. 57(7). 2179–2202.559 indexed citations breakdown →
Ghadge, Abhijeet & Samir Dani. (2015). Information based approach for disaster risk management. University of Huddersfield Repository (University of Huddersfield).2 indexed citations
Ghadge, Abhijeet, Samir Dani, Michael Chester, & Roy Kalawsky. (2012). A Systems Approach for Modelling Supply Chain Risks. SSRN Electronic Journal.
13.
Ghadge, Abhijeet, Samir Dani, & Roy Kalawsky. (2012). Supply Chain Risk Management: Present and Future Scope. Figshare.1 indexed citations
14.
Ghadge, Abhijeet, Samir Dani, & Roy Kalawsky. (2012). Supply chain risk management: present and future scope. The International Journal of Logistics Management. 23(3). 313–339.312 indexed citations breakdown →
15.
Bhamra, Ran, Samir Dani, & Kevin Burnard. (2011). Resilience: the concept, a literature review and future directions. International Journal of Production Research. 49(18). 5375–5393.972 indexed citations breakdown →
16.
Ghadge, Abhijeet, Samir Dani, & Roy Kalawsky. (2010). A Framework for Managing Risks in the Aerospace Supply Chain Using Systems Thinking. SSRN Electronic Journal.4 indexed citations
Ghadge, Abhijeet, Samir Dani, & Roy Kalawsky. (2010). Managing risks in next generation supply chains: a systems approach. University of Huddersfield Repository (University of Huddersfield).1 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.