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Seokbeom Kwon

Korea Advanced Institute of Science and Technology · 経営学

研究室紹介

Professor Seokbeom Kwon's research lab focuses on the dynamics of innovation, knowledge transfer, and science policy in science-driven industries. The lab investigates how interdisciplinary research, regulatory environments, and institutional frameworks influence the translation of scientific discoveries into technological applications. Key research directions include identifying knowledge-flow mediating research, measuring technological emergence, and analyzing the impact of data sharing and regulatory uncertainty on innovation outcomes.

interdisciplinary researchtechnological emergenceregulatory uncertaintydata sharinginnovation policy

Research Overview

Papers
47
Total Citations
568
Papers (5y)
17
Primary Field
経営学

Research Output Trend

Figures are computed from collected data and may differ slightly.

Publications per year (5y)
17total
2021
2022
2023
2024
2025
Citations per year (5y)
129total
20212022202320242025

Selected Papers

15
1
Article|53 citations·2019
Research addressing emerging technological ideas has greater scientific impact
Seokbeom Kwon, Xiaoyu Liu, Alan L. Porter, Jan Youtie
SJR Q1Research Policy
Management Science and Operations ResearchDecision Sciences
2
Article|43 citations·2021
Can antitrust law enforcement spur innovation? Antitrust regulation of patent consolidation and its impact on follow-on innovations
Seokbeom Kwon, Alan C. Marco
SJR Q1Research Policy
Management of Technology and InnovationBusiness, Management and Accounting
3
Article|38 citations·2016
How institutional arrangements in the National Innovation System affect industrial competitiveness: A study of Japan and the U.S. with multiagent simulation
Seokbeom Kwon, Kazuyuki Motohashi
SJR Q1Technological Forecasting and Social Change
Strategy and ManagementBusiness, Management and Accounting
4
Article|35 citations·2020
How does patent transfer affect innovation of firms?
Seokbeom Kwon
SJR Q1Technological Forecasting and Social Change
Management of Technology and InnovationBusiness, Management and Accounting
5
Article|32 citations·2017
A measure of knowledge flow between specific fields: Implications of interdisciplinarity for impact and funding
Seokbeom Kwon, Gregg E. A. Solomon, Jan Youtie, Alan L. Porter
SJR Q1PLoS ONEOA

Encouraging knowledge flow between mutually relevant disciplines is a worthy aim of research policy makers. Yet, it is less clear what types of research promote cross-disciplinary knowledge flow and whether such research generates particularly influential knowledge. Empirical questions remain as to how to identify knowledge-flow mediating research and how to provide support for this research. This study contributes to addressing these gaps by proposing a new way to identify knowledge-flow mediat

Statistics, Probability and UncertaintyDecision Sciences
6
Article|25 citations·2022
Interdisciplinary knowledge integration as a unique knowledge source for technology development and the role of funding allocation
Seokbeom Kwon
SJR Q1Technological Forecasting and Social Change
Economics and EconometricsEconomics, Econometrics and Finance
7
Article|21 citations·2016
Navigating the innovation trajectories of technology by combining specialization score analyses for publications and patents: graphene and nano-enabled drug delivery
Seokbeom Kwon, Alan L. Porter, Jan Youtie
SJR Q1Scientometrics
Management of Technology and InnovationBusiness, Management and Accounting
8
Article|18 citations·2021
Incentive or disincentive for research data disclosure? A large-scale empirical analysis and implications for open science policy
Seokbeom Kwon, Kazuyuki Motohashi
SJR Q1International Journal of Information Management
Statistics, Probability and UncertaintyDecision Sciences
9
Article|14 citations·2020
Interdisciplinary knowledge combinations and emerging technological topics: Implications for reducing uncertainties in research evaluation
Seokbeom Kwon, Jan Youtie, Alan L. Porter
SJR Q1Research Evaluation

Abstract This article puts forth a new indicator of emerging technological topics as a tool for addressing challenges inherent in the evaluation of interdisciplinary research. We present this indicator and test its relationship with interdisciplinary and atypical research combinations. We perform this test by using metadata of scientific publications in three domains with different interdisciplinarity challenges: Nano-Enabled Drug Delivery, Synthetic Biology, and Autonomous Vehicles. Our analysi

Information Systems and ManagementDecision Sciences
10
Article|9 citations·2020
The prevalence of weak patents in the United States: A new method to identify weak patents and the implications for patent policy
Seokbeom Kwon
SJR Q1Technology in Society
Management of Technology and InnovationBusiness, Management and Accounting
11
Article|8 citations·2022
How does regulatory uncertainty shape the innovation process? Evidence from the case of nanomedicine
Seokbeom Kwon, Jan Youtie, Alan L. Porter, Nils C. Newman
SJR Q1The Journal of Technology Transfer
Economics and EconometricsEconomics, Econometrics and Finance
12
Article|7 citations·2025
Use of exclusive data for corporate research on machine learning and artificial intelligence: Implications for innovation and competition policy
Seokbeom Kwon, Alan L. Porter
SJR Q1Technology in Society
Economics and EconometricsEconomics, Econometrics and Finance
13
Article|7 citations·2019
Defensive Patent Aggregators as Shields against Patent Assertion Entities? Theoretical and Empirical Analysis
Seokbeom Kwon, Matej Drev
SJR Q1Technological Forecasting and Social Change
Management of Technology and InnovationBusiness, Management and Accounting
14
Article|5 citations·2021
Chasing two hares at once? Effect of joint institutional change for promoting commercial use of university knowledge and scientific research
Seokbeom Kwon, Kazuyuki Motohashi, Kenta Ikeuchi
SJR Q1The Journal of Technology TransferOA
Statistics, Probability and UncertaintyDecision Sciences
15
Preprint|4 citations·2020
Incentive or Disincentive for Disclosure of Research Data? A Large-Scale Empirical Analysis and Implications for Open Science Policy
Seokbeom Kwon, Motohashi Kazuyuki
RePEc: Research Papers in Economics

The incentive for scientists to disclose their research data hinges on the extent to which data disclosure brings academic credit (the credit effect) compared to the dissipation of academic credit through intensified scientific competition (the competition effect). In this study, we examine the net effect on the academic credit received by research publications of data-providing researchers publicly disclosing research data. To accomplish this, we compared the citation impact of scientific journ

Statistics, Probability and UncertaintyDecision Sciences

Research Areas

Management of Technology and InnovationEconomics and EconometricsStatistics, Probability and UncertaintyStrategy and ManagementMolecular BiologyInformation Systems and Management

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