Linking Macro Policy Shifts to Technology Evolution: Integrating a Difference-in-Differences Model with Patent Keyword Networks

Macro policies such as the Paris Agreement are key external drivers of research and development (R&D) planning. Measuring their impact and reflecting the resulting technological changes in the R&D process are essential for sustaining competitive advantage. This study proposes a methodology for measuring the association between macro-level policy shifts and micro-level technological change. The proposed methodology integrates a difference-in-differences (DID) model with a patent keyword network to construct a technology change index that captures the emergence of new technological elements, the formation of new relationships, and changes in the intensity of existing relationships. A case study examining the impact of the Paris Agreement on the battery industry reveals heterogeneous policy sensitivity across different battery technologies—a heterogeneity that holds under both a covariate-adjusted and a covariate-free specification, although which technology carries the largest differential depends on that choice—and identifies, for each technology, the technological elements associated with post-policy innovation. These elements are further classified into firm-specific proprietary components and shared foundational components, providing insights for technology development strategies. By linking macro-level policy shocks to micro-level technological evolution, the proposed approach provides strategic implications for firms’ R&D planning and supports more targeted technology and innovation policies.

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Publication Details

Journal
Systems
Published
2026-10-04
DOI
https://doi.org/10.3390/systems14101247
Primary Topic
Intellectual Property and Patents
Type
article
Field-Weighted Citation Impact
0.00
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article

Linking Macro Policy Shifts to Technology Evolution: Integrating a Difference-in-Differences Model with Patent Keyword Networks

Byungun Yoon, Taeyeoun Roh, Hyejin Jang
Systems
Intellectual Property and Patents
article

Linking Macro Policy Shifts to Technology Evolution: Integrating a Difference-in-Differences Model with Patent Keyword Networks

Byungun Yoon, Taeyeoun Roh, Hyejin Jang
article en

Abstract

Macro policies such as the Paris Agreement are key external drivers of research and development (R&D) planning. Measuring their impact and reflecting the resulting technological changes in the R&D process are essential for sustaining competitive advantage. This study proposes a methodology for measuring the association between macro-level policy shifts and micro-level technological change. The proposed methodology integrates a difference-in-differences (DID) model with a patent keyword network to construct a technology change index that captures the emergence of new technological elements, the formation of new relationships, and changes in the intensity of existing relationships. A case study examining the impact of the Paris Agreement on the battery industry reveals heterogeneous policy sensitivity across different battery technologies—a heterogeneity that holds under both a covariate-adjusted and a covariate-free specification, although which technology carries the largest differential depends on that choice—and identifies, for each technology, the technological elements associated with post-policy innovation. These elements are further classified into firm-specific proprietary components and shared foundational components, providing insights for technology development strategies. By linking macro-level policy shocks to micro-level technological evolution, the proposed approach provides strategic implications for firms’ R&D planning and supports more targeted technology and innovation policies.

SystemsVol. 14(10)
Dongguk University (KR), Hankuk University of Foreign Studies (KR)
Openalex Percentile: Top 7%
Intellectual Property and Patents
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Linking Macro Policy Shifts to Technology Evolution: Integrating a Difference-in-Differences Model with Patent Keyword Networks — Byungun Yoon, Taeyeoun Roh, et al. · Systems (2026) | TGRS Research Map | TGRS