Evolutionary Game Analysis of Low-Carbon Transition in the Steel Industry Under Demand-Side Constraints: A Simulation Based on Empirical Data
需要側制約下における鉄鋼業の低炭素移行に関する進化ゲーム分析：実証データに基づくシミュレーション (AI 翻訳)
Yang Miao, Yu Tian, Qin-Yu Chen, Xinqi Yu
🤖 gxceed AI 要約
日本語
本論文は、中国の「ダブルカーボン」目標の下、需要側の制約（消費者選好など）が政府と企業の戦略的相互作用に与える影響を進化ゲームモデルで分析。浙江省の鉄鋼業の実証データを用いてシミュレーションし、現在のパラメータでは理想均衡に自発的に収束しない「ガバナンスの行き詰まり」を発見。消費者の低炭素選好が行き詰まりを打破し、政府の規制負担を軽減する重要な外部要因であることを示した。感度分析により規制政策と市場需要の相乗効果の臨界閾値を特定し、政府誘導・市場駆動・需要側駆動の協働ガバナンスメカニズムを提案している。
English
This paper constructs an evolutionary game model to analyze how demand-side constraints (consumer low-carbon preferences) influence the strategic interaction between governments and firms under China's Dual Carbon targets. Using empirical data from the steel industry in Zhejiang Province, simulations reveal a "governance deadlock" where the system fails to spontaneously converge to the ideal equilibrium. Consumer preference intensity is identified as a key external force that can break the deadlock and reduce government regulatory burden. Sensitivity analysis identifies critical thresholds for synergy between regulatory policies and market demand, leading to policy recommendations for a collaborative governance mechanism.
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
中国の鉄鋼業に焦点を当てているが、日本の鉄鋼業の低炭素移行にも示唆を与える。特に需要側の消費者選好が政策効果に与える影響は、日本でもグリーン購入法やカーボンプライシング議論と関連して重要。進化ゲームモデルの手法は、日本の産業政策分析にも応用可能。
In the global GX context
While focused on China's steel industry, this paper offers insights for global steel decarbonization by highlighting the role of demand-side constraints and consumer preferences in breaking governance deadlocks. The evolutionary game approach with empirical calibration provides a methodological contribution to analyzing industry transitions under policy and market interactions.
👥 読者別の含意
🔬研究者:This paper provides a novel evolutionary game framework calibrated with empirical data that can be applied to other industrial sectors or countries for analyzing demand-side policy mechanisms.
🏢実務担当者:Steel industry and energy transition professionals can leverage the insights on how consumer preferences and government incentives interact to design more effective decarbonization strategies.
🏛政策担当者:The findings on critical thresholds for policy-market synergy can inform the design of demand-side regulations and green public procurement policies.
📄 Abstract（原文）
Under the constraints of China’s “Dual Carbon” targets, promoting green consumption has emerged as a critical market-based strategy to drive industrial decarbonization and achieve sustainable development. However, the existing literature primarily focuses on supply-side government regulation, leaving the mechanism of how demand-side constraints influence the strategic interaction between the government and enterprises under-explored. To bridge this gap, this paper constructs an evolutionary game model incorporating performance-based government incentives, consumer low-carbon preferences, and corporate abatement costs. Unlike theoretical models with hypothetical parameters, this study calibrates the simulation parameters using empirical data from the steel industry in Zhejiang Province, a pilot zone for China’s ecological civilization construction. The simulation results indicate that: First, under the current empirical parameters, the system fails to spontaneously converge to the ideal equilibrium state, highlighting a “governance deadlock”; second, consumer preference intensity serves as a vital external force that can effectively break this deadlock and reduce the government’s regulatory burden; and finally, sensitivity analysis reveals the critical thresholds for the synergistic effect between regulatory policies and market demand. Based on these findings, policy recommendations are proposed to foster a collaborative governance mechanism integrating government guidance, market-driven approaches, and demand-side driving forces.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.3390/su18041951first seen 2026-05-05 21:50:36
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