Scholarlink

<p>This study examines how the staged evolution of sustainable intelligence affects firms’ carbon performance. Existing research typically assumes that sustainable intelligence can steadily improve carbon performance along a path of technological upgrading, yet this assumption overlooks the mismatch between technological conditions and resource requirements in the construction machinery industry. From a stage based perspective, this study combines panel regression and an evolutionary game model to analyze shifts in the relative weights of underlying digital technologies across stages among 178 A-share listed construction machinery firms from 2009 to 2022. The findings show that sustainable intelligence is a stage progressive process constrained by structural conditions, that its effect on firms’ carbon performance is realized mainly through servitization transformation, and that environmental subsidies are more effective than environmental penalties in both short term incentives and long term evolution. This study uncovers the internal constraints embedded in the staged evolution of sustainable intelligence and offers a new explanation for why continued technological progress in the green transition does not necessarily translate into synchronous improvements in carbon performance.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Stage evolution of sustainable intelligence and corporate carbon performance: mediation of servitization and heterogeneity of environmental regulations

  • 期刊论文

  • 发表日期：

    2026年6月16日

查看全文
  • Jing Han,
  • Ruiming Lu,
  • Yueyue Wang,
  • Zenghui Liu

摘要

This study examines how the staged evolution of sustainable intelligence affects firms’ carbon performance. Existing research typically assumes that sustainable intelligence can steadily improve carbon performance along a path of technological upgrading, yet this assumption overlooks the mismatch between technological conditions and resource requirements in the construction machinery industry. From a stage based perspective, this study combines panel regression and an evolutionary game model to analyze shifts in the relative weights of underlying digital technologies across stages among 178 A-share listed construction machinery firms from 2009 to 2022. The findings show that sustainable intelligence is a stage progressive process constrained by structural conditions, that its effect on firms’ carbon performance is realized mainly through servitization transformation, and that environmental subsidies are more effective than environmental penalties in both short term incentives and long term evolution. This study uncovers the internal constraints embedded in the staged evolution of sustainable intelligence and offers a new explanation for why continued technological progress in the green transition does not necessarily translate into synchronous improvements in carbon performance.