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.
Advances in Social Media Research: Past, Present and Future
2017785 citationsKawaljeet Kaur Kapoor, Kuttimani Tamilmani et al.Information Systems Frontiersprofile →
Understanding consumer adoption of mobile payment in India: Extending Meta-UTAUT model with personal innovativeness, anxiety, trust, and grievance redressal
2020560 citationsPushp P. Patil, Kuttimani Tamilmani et al.International Journal of Information Managementprofile →
Consumer use of mobile banking (M-Banking) in Saudi Arabia: Towards an integrated model
2018403 citationsAbdullah M. Baabdullah, Ali Abdallah Alalwan et al.International Journal of Information Managementprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Pushp P. Patil
Since
Specialization
Citations
This map shows the geographic impact of Pushp P. Patil'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 Pushp P. Patil with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pushp P. Patil more than expected).
This network shows the impact of papers produced by Pushp P. Patil. 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 Pushp P. Patil. The network helps show where Pushp P. Patil may publish in the future.
Co-authorship network of co-authors of Pushp P. Patil
This figure shows the co-authorship network connecting the top 25 collaborators of Pushp P. Patil.
A scholar is included among the top collaborators of Pushp P. Patil 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 Pushp P. Patil. Pushp P. Patil is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
All Works
8 of 8 papers shown
1.
Patil, Pushp P., Kuttimani Tamilmani, Nripendra P. Rana, & Vishnupriya Raghavan. (2020). Understanding consumer adoption of mobile payment in India: Extending Meta-UTAUT model with personal innovativeness, anxiety, trust, and grievance redressal. International Journal of Information Management. 54. 102144–102144.560 indexed citations breakdown →
2.
Baabdullah, Abdullah M., Ali Abdallah Alalwan, Nripendra P. Rana, Pushp P. Patil, & Yogesh K. Dwivedi. (2019). An integrated model for m-banking adoption in Saudi Arabia. International Journal of Bank Marketing. 37(2). 452–478.94 indexed citations
Patil, Pushp P., et al.. (2018). The Role of Trust and Risk in Mobile Payments Adoption: A Meta-Analytic Review. Journal of the Association for Information Systems. 129.21 indexed citations
5.
Baabdullah, Abdullah M., Ali Abdallah Alalwan, Nripendra P. Rana, Hatice Kizgin, & Pushp P. Patil. (2018). Consumer use of mobile banking (M-Banking) in Saudi Arabia: Towards an integrated model. International Journal of Information Management. 44. 38–52.403 indexed citations breakdown →
Kapoor, Kawaljeet Kaur, Kuttimani Tamilmani, Nripendra P. Rana, et al.. (2017). Advances in Social Media Research: Past, Present and Future. Information Systems Frontiers. 20(3). 531–558.785 indexed citations breakdown →
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.