Artificial intelligence investment and renewable energy for environmental sustainability in ASEAN-5 under the foreign direct investment threshold
ASEAN-5における環境持続可能性のための人工知能投資と再生可能エネルギー：外国直接投資の閾値の下で (AI 翻訳)
Thanh Phuc Nguyen, Trang Thi-Thuy Duong
🤖 gxceed AI 要約
日本語
本研究は、ASEAN-5諸国における経済成長、人工知能投資、再生可能エネルギー消費、環境悪化の非線形な関係を、外国直接投資(FDI)を閾値変数として分析した。パネル平滑移行回帰(PSTR)モデルを用いた結果、FDIが低い水準では経済成長が環境悪化を促進する一方、AI投資と再生可能エネルギーの効果は限定的であった。しかし、FDIが閾値を超えると、AI投資と再生可能エネルギーが環境改善に有意に寄与することが示された。
English
This study examines nonlinear relationships among economic growth, AI investment, renewable energy, and environmental degradation in ASEAN-5, using FDI as a threshold variable. A Panel Smooth Transition Regression (PSTR) model finds that under low FDI, economic growth worsens the environment while AI and renewable energy have little effect. Above the FDI threshold, AI investment and renewable energy significantly reduce environmental damage.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本企業がASEAN諸国に進出する際、FDIの水準によって環境対策の効果が異なることを示唆する。低FDI国では再生可能エネルギーやAI投資の効果が限定的だが、一定の投資規模を超えると環境改善に寄与するため、投資判断に有用な知見を提供する。
In the global GX context
This study adds to the global literature on the FDI-environment nexus by highlighting threshold effects. For emerging economies, the results suggest that attracting FDI beyond a certain level can amplify the environmental benefits of AI and renewable energy investments, informing policy design for sustainable development.
👥 読者別の含意
🔬研究者:This paper provides empirical evidence of nonlinear FDI thresholds in the energy-environment relationship, useful for researchers studying sustainable development and international investment.
🏢実務担当者:Corporations investing in ASEAN with sustainability goals can use these findings to calibrate their green technology strategies based on local FDI levels.
🏛政策担当者:ASEAN policymakers should consider FDI thresholds when designing incentives for AI and renewable energy to maximize environmental benefits.
📄 Abstract（原文）
This study examines the nonlinear and regime-dependent interactions among economic growth, artificial intelligence investment, renewable energy consumption, and environmental degradation in the ASEAN-5 nations, with foreign direct investment (FDI) acting as a pivotal transition variable. The application of a Panel Smooth Transition Regression (PSTR) paradigm yields compelling evidence against linearity and endorses a single-threshold specification across many environmental variables, such as carbon emissions, carbon intensity, and greenhouse gas emissions. The results indicate that the environmental effects of economic and technological factors differ markedly among FDI regimes. Under low-FDI conditions, economic expansion is associated with greater environmental deterioration, whereas the impacts of investment in artificial intelligence and renewable energy are minimal and statistically insignificant. Conversely, when foreign direct investment surpasses a certain threshold, the dynamics change significantly. Economic growth increasingly harms the environment, whilst investment in technology and renewable energy begins to significantly alleviate environmental damage. These results underscore the dual function of FDI as both a catalyst that exacerbates the environmental costs of economic growth and a driver of green technologies and innovation. This study elucidates threshold-driven nonlinearities, thereby advancing the existing literature on sustainable development and offering significant policy insights for emerging economies striving to reconcile economic growth with environmental sustainability.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1007/s43621-026-03998-wfirst seen 2026-07-24 05:37:00
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