Seokbeom Kwon

559 total citations
33 papers, 394 citations indexed

About

Seokbeom Kwon is a scholar working on Economics and Econometrics, Management of Technology and Innovation and Strategy and Management. According to data from OpenAlex, Seokbeom Kwon has authored 33 papers receiving a total of 394 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Economics and Econometrics, 14 papers in Management of Technology and Innovation and 9 papers in Strategy and Management. Recurrent topics in Seokbeom Kwon's work include Innovation Policy and R&D (15 papers), Intellectual Property and Patents (10 papers) and Innovation and Knowledge Management (9 papers). Seokbeom Kwon is often cited by papers focused on Innovation Policy and R&D (15 papers), Intellectual Property and Patents (10 papers) and Innovation and Knowledge Management (9 papers). Seokbeom Kwon collaborates with scholars based in United States, Japan and South Korea. Seokbeom Kwon's co-authors include Jan Youtie, Alan L. Porter, Philip Shapira, Kazuyuki Motohashi, Alan C. Marco, Gregg E. A. Solomon, Stephen Carley, Nils C. Newman, Zhinan Wang and Xiaoyu Liu and has published in prestigious journals such as Science, PLoS ONE and Research Policy.

In The Last Decade

Seokbeom Kwon

27 papers receiving 382 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Seokbeom Kwon United States 13 125 98 78 62 55 33 394
Sanjay Arora United States 8 104 0.8× 100 1.0× 124 1.6× 34 0.5× 18 0.3× 15 408
Gonzalo Ordóñez–Matamoros Colombia 11 75 0.6× 108 1.1× 77 1.0× 43 0.7× 16 0.3× 35 379
Surya Mahdi United Kingdom 8 132 1.1× 203 2.1× 130 1.7× 60 1.0× 31 0.6× 10 416
Ad Notten Netherlands 5 55 0.4× 46 0.5× 43 0.6× 47 0.8× 19 0.3× 9 300
Thomas Durand France 9 55 0.4× 70 0.7× 136 1.7× 57 0.9× 9 0.2× 30 387
Luciano Kay United States 8 139 1.1× 122 1.2× 112 1.4× 31 0.5× 10 0.2× 16 343
Borja González‐Albo Spain 7 36 0.3× 23 0.2× 49 0.6× 102 1.6× 18 0.3× 24 323
Seongkyoon Jeong United States 12 180 1.4× 143 1.5× 237 3.0× 116 1.9× 4 0.1× 20 586
Iwan von Wartburg Switzerland 7 195 1.6× 229 2.3× 189 2.4× 18 0.3× 9 0.2× 11 516
Gavin Clarkson United States 7 85 0.7× 71 0.7× 85 1.1× 21 0.3× 3 0.1× 22 281

Countries citing papers authored by Seokbeom Kwon

Since Specialization
Citations

This map shows the geographic impact of Seokbeom Kwon'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 Seokbeom Kwon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Seokbeom Kwon more than expected).

Fields of papers citing papers by Seokbeom Kwon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Seokbeom Kwon. 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 Seokbeom Kwon. The network helps show where Seokbeom Kwon may publish in the future.

Co-authorship network of co-authors of Seokbeom Kwon

This figure shows the co-authorship network connecting the top 25 collaborators of Seokbeom Kwon. A scholar is included among the top collaborators of Seokbeom Kwon 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 Seokbeom Kwon. Seokbeom Kwon is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Kwon, Seokbeom & Alan L. Porter. (2025). Use of exclusive data for corporate research on machine learning and artificial intelligence: Implications for innovation and competition policy. Technology in Society. 81. 102820–102820. 1 indexed citations
2.
Kwon, Seokbeom. (2025). Competition or diversion? Effect of public sharing of data on research productivity of data provider. Research Policy. 54(9). 105308–105308.
3.
Ko, Hoo Sang & Seokbeom Kwon. (2024). Prominence of corporate science in quantum computing research. Technological Forecasting and Social Change. 212. 123949–123949.
4.
Kwon, Seokbeom. (2024). Transfer of university patents and its impact on follow-on invention. Science and Public Policy. 51(3). 450–462.
5.
Motohashi, Kazuyuki, et al.. (2024). Impact of national university patenting on innovation: Researcher analysis in Japan. Technology in Society. 81. 102806–102806.
6.
Kwon, Seokbeom. (2024). Underappreciated government research support in patents. Science. 385(6712). 936–938.
7.
Kwon, Seokbeom. (2022). Interdisciplinary knowledge integration as a unique knowledge source for technology development and the role of funding allocation. Technological Forecasting and Social Change. 181. 121767–121767. 17 indexed citations
8.
Youtie, Jan, et al.. (2021). The Impact of I-Corps on Accelerating Venture Discontinuation in a Southeastern US University. Science and Public Policy. 48(4). 474–487. 1 indexed citations
9.
Kwon, Seokbeom & Alan C. Marco. (2021). Can antitrust law enforcement spur innovation? Antitrust regulation of patent consolidation and its impact on follow-on innovations. Research Policy. 50(9). 104295–104295. 33 indexed citations
10.
Kwon, Seokbeom. (2020). The prevalence of weak patents in the United States: A new method to identify weak patents and the implications for patent policy. Technology in Society. 64. 101469–101469. 5 indexed citations
11.
Kwon, Seokbeom. (2020). How does patent transfer affect innovation of firms?. Technological Forecasting and Social Change. 154. 119959–119959. 27 indexed citations
12.
Kwon, Seokbeom, et al.. (2019). Research addressing emerging technological ideas has greater scientific impact. Research Policy. 48(9). 103834–103834. 42 indexed citations
13.
Kwon, Seokbeom, et al.. (2019). Defensive Patent Aggregators as Shields against Patent Assertion Entities? Theoretical and Empirical Analysis. Technological Forecasting and Social Change. 151. 119745–119745. 5 indexed citations
14.
Porter, Alan L., Stephen Carley, Caitlin Cassidy, et al.. (2019). Measuring Interdisciplinary Research Categories and Knowledge Transfer: A Case Study of Connections between Cognitive Science and Education. Perspectives on Science. 27(4). 582–618. 2 indexed citations
15.
Porter, Alan L., Nils C. Newman, Stephen Carley, et al.. (2018). National nanotechnology research prominence. Technology Analysis and Strategic Management. 31(1). 25–39. 13 indexed citations
16.
Kwon, Seokbeom, Gregg E. A. Solomon, Jan Youtie, & Alan L. Porter. (2017). A measure of knowledge flow between specific fields: Implications of interdisciplinarity for impact and funding. PLoS ONE. 12(10). e0185583–e0185583. 26 indexed citations
17.
Shapira, Philip, Seokbeom Kwon, & Jan Youtie. (2017). Tracking the emergence of synthetic biology. Scientometrics. 112(3). 1439–1469. 69 indexed citations
18.
Kwon, Seokbeom & Kazuyuki Motohashi. (2016). How institutional arrangements in the National Innovation System affect industrial competitiveness: A study of Japan and the U.S. with multiagent simulation. Technological Forecasting and Social Change. 115. 221–235. 26 indexed citations
19.
Huang, Ying, et al.. (2015). Analyzing collaboration networks and developmental patterns of nano-enabled drug delivery (NEDD) for brain cancer. Beilstein Journal of Nanotechnology. 6. 1666–1676. 9 indexed citations
20.
Kwon, Seokbeom & Kazuyuki Motohashi. (2014). Effect of Non-Practicing Entities on Innovation Society and Policy: An Agent Based Model and Simulation. SSRN Electronic Journal. 2 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.

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2026