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.
Countries citing papers authored by Maryann P. Feldman
Since
Specialization
Citations
This map shows the geographic impact of Maryann P. Feldman'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 Maryann P. Feldman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maryann P. Feldman more than expected).
Fields of papers citing papers by Maryann P. Feldman
This network shows the impact of papers produced by Maryann P. Feldman. 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 Maryann P. Feldman. The network helps show where Maryann P. Feldman may publish in the future.
Co-authorship network of co-authors of Maryann P. Feldman
This figure shows the co-authorship network connecting the top 25 collaborators of Maryann P. Feldman.
A scholar is included among the top collaborators of Maryann P. Feldman 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 Maryann P. Feldman. Maryann P. Feldman is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Feldman, Maryann P., Dieter F. Kogler, & David L. Rigby. (2013). rKnowledge: The Spatial Diffusion of rDNA Methods. RePEc: Research Papers in Economics.2 indexed citations
8.
Yusuf, Shahid, Kaoru Nabeshima, Martín Kenney, et al.. (2008). Growing Industrial Clusters in Asia : Serendipity and Science. World Bank Publications.34 indexed citations
9.
Feldman, Maryann P. & Janet Bercovitz. (2006). Entrepreneurial Universities and Technology Transfer: A Conceptual Framework for Understanding Knowledge-Based Economic Development. SSRN Electronic Journal.105 indexed citations
10.
Buchman, Timothy G., Jonathan Dushoff, Paul R. Ehrlich, et al.. (2006). Battling bad behavior. 20(2). 51–57.2 indexed citations
11.
Feldman, Maryann P.. (2005). Science and Innovation: Rethinking the Rationales for Funding and Governance. Journal of Economic Literature. 43(3). 848–849.12 indexed citations
12.
Feldman, Maryann P., et al.. (2005). Reinforcing Interactions Between The Advanced Technology Program And The States Volume 2: Case Studies Of Technology Pioneering Start-Up Companies And Their Use Of State And Federal Programs. RePEc: Research Papers in Economics.1 indexed citations
13.
Francis, Johanna L., Janet Bercovitz, & Maryann P. Feldman. (2005). Creating a Cluster While Building a Firm: Entrepreneurs and the Formation of Industrial Clusters. SSRN Electronic Journal.15 indexed citations
14.
Aharonson, Barak S., et al.. (2004). Borrowing from Neighbors: The location Choice of Entrepreneurs.2 indexed citations
15.
Feldman, Maryann P. & Johanna L. Francis. (2003). Fortune Favors the Prepared Region: The Case of Entrepreneurship and the Capitol Region Biotechnology Cluster. SSRN Electronic Journal.15 indexed citations
16.
Feldman, Maryann P.. (2002). The Internet Revolution and the Geography of Innovation. SSRN Electronic Journal.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.