TY - JOUR
T1 - Government subsidy portfolio for the R&D and adoption of emerging green technologies considering firm learning
AU - Hua, Jiawen
AU - Lin, Jun
AU - Wang, Kai
AU - Jing, Fei
N1 - Publisher Copyright:
© The Author(s), under exclusive licence to Associazione Italiana di Ricerca Operativa, The Belgian Operational Research Society, and Société Française de Recherche Opérationnelle et d'Aide à la Décision 2025.
PY - 2025
Y1 - 2025
N2 - Global investment in emerging green technologies reached US$2.1 trillion in 2024, and government subsidies accounted for a significant portion of this investment. This study examines the optimization of the government subsidy portfolio, including the investment subsidy during research and development (R&D) periods and the adoption subsidy during usage periods, to inspire firms’ investment in and adoption of green technologies. The study focuses on the interplay between the government’s subsidy policies and the firm’s decisions regarding the R&D investment and adoption time of green technologies. The findings indicate that it is optimal for the government to subsidize only when the green technology’s initial unit production cost is not too low and/or the firm’s learning rate is not too large. Therefore, policymakers should exercise deliberation in green technologies’ inherent characteristics when formulating subsidy strategies. A noteworthy discovery is the perfect substitutability between the initial adoption subsidy coefficient and the investment subsidy rate in the government's optimal subsidy portfolio. This leads to multiple viable subsidy combinations, each with different regulatory expenditure. Specifically, the optimal subsidy portfolio that minimizes the amount of regulatory expenditure is the one containing a large investment subsidy paired with a comparatively small adoption subsidy that decreases over time. Therefore, policymakers can strike a trade-off between investment subsidies and adoption subsidies, thereby enhancing social welfare while concurrently curtailing regulatory expenditure. Finally, considering complexities across different industries, such as constrained R&D investment capacity in the energy industry and cost reduction phenomenon in the traditional manufacturing industry, this study investigates extended models to reinforce the validity of our conclusions.
AB - Global investment in emerging green technologies reached US$2.1 trillion in 2024, and government subsidies accounted for a significant portion of this investment. This study examines the optimization of the government subsidy portfolio, including the investment subsidy during research and development (R&D) periods and the adoption subsidy during usage periods, to inspire firms’ investment in and adoption of green technologies. The study focuses on the interplay between the government’s subsidy policies and the firm’s decisions regarding the R&D investment and adoption time of green technologies. The findings indicate that it is optimal for the government to subsidize only when the green technology’s initial unit production cost is not too low and/or the firm’s learning rate is not too large. Therefore, policymakers should exercise deliberation in green technologies’ inherent characteristics when formulating subsidy strategies. A noteworthy discovery is the perfect substitutability between the initial adoption subsidy coefficient and the investment subsidy rate in the government's optimal subsidy portfolio. This leads to multiple viable subsidy combinations, each with different regulatory expenditure. Specifically, the optimal subsidy portfolio that minimizes the amount of regulatory expenditure is the one containing a large investment subsidy paired with a comparatively small adoption subsidy that decreases over time. Therefore, policymakers can strike a trade-off between investment subsidies and adoption subsidies, thereby enhancing social welfare while concurrently curtailing regulatory expenditure. Finally, considering complexities across different industries, such as constrained R&D investment capacity in the energy industry and cost reduction phenomenon in the traditional manufacturing industry, this study investigates extended models to reinforce the validity of our conclusions.
KW - Adoption subsidy
KW - Emerging green technologies
KW - Game theory
KW - Investment subsidy
KW - Learning-by-doing effect
UR - https://www.scopus.com/pages/publications/105017560066
U2 - 10.1007/s10288-025-00601-2
DO - 10.1007/s10288-025-00601-2
M3 - 文章
AN - SCOPUS:105017560066
SN - 1619-4500
JO - 4OR
JF - 4OR
ER -