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<p>The rapid growth of the digital economy has transformed new energy enterprises, making resilience efficiency crucial for meeting Carbon Peak and Carbon Neutrality targets. This study analyzes 48 A-share listed new energy companies from 2018 to 2023, treating digitalization as an exogenous variable. Using an entropy dynamic range directional model (RDM) directional distance function (DDF) data envelopment analysis (DEA), we assess the resilience efficiency across adaptive recovery, defensive resistance, and transformative learning dimensions. The sample is further divided into photovoltaic, wind power, hydropower, energy storage, new energy vehicle, and new energy battery industries to analyze resilience efficiency at the industry level. We also examine resilience efficiency in the production, storage, and application sectors, aiming to clarify the differences between the upstream, midstream, and downstream sectors of the new energy industrial chain. The findings are as follows: (1) Overall, new energy enterprises exhibit high resilience efficiency, but with significant variation across companies. Among the six industries, hydropower shows the highest efficiency, while energy storage has the lowest, with notable fluctuations over the years. The resilience efficiency in energy storage is significantly lower than in the production and application sectors. (2) Digitalization boosts resilience efficiency, with varying impacts across new energy industries. Photovoltaics saw the largest improvement (20%), followed by new energy vehicles and energy storage (over 15%), and hydropower (9%). Wind power and new energy batteries showed minimal gains, under 1%. (3) Across all dimensions, industries’ adaptive recovery capacity generally surpasses their defensive resistance and transformative learning capacities. Based on these findings, we recommend tailored policies to guide new energy enterprises through digital transformation, boosting their resilience. We also suggest specific measures to strengthen their defensive resistance and transformative learning capacities.</p>

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The resilience efficiency in the Chinese new energy production, storage, and application industries: a digital transformation perspective through dynamic range directional model directional distance function data envelopment analysis

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月1日

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  • Yanan Sun,
  • Miaoyi Li,
  • Anqi Li,
  • Yuanjing Wu,
  • Wesley Hu,
  • Li Ji

摘要

The rapid growth of the digital economy has transformed new energy enterprises, making resilience efficiency crucial for meeting Carbon Peak and Carbon Neutrality targets. This study analyzes 48 A-share listed new energy companies from 2018 to 2023, treating digitalization as an exogenous variable. Using an entropy dynamic range directional model (RDM) directional distance function (DDF) data envelopment analysis (DEA), we assess the resilience efficiency across adaptive recovery, defensive resistance, and transformative learning dimensions. The sample is further divided into photovoltaic, wind power, hydropower, energy storage, new energy vehicle, and new energy battery industries to analyze resilience efficiency at the industry level. We also examine resilience efficiency in the production, storage, and application sectors, aiming to clarify the differences between the upstream, midstream, and downstream sectors of the new energy industrial chain. The findings are as follows: (1) Overall, new energy enterprises exhibit high resilience efficiency, but with significant variation across companies. Among the six industries, hydropower shows the highest efficiency, while energy storage has the lowest, with notable fluctuations over the years. The resilience efficiency in energy storage is significantly lower than in the production and application sectors. (2) Digitalization boosts resilience efficiency, with varying impacts across new energy industries. Photovoltaics saw the largest improvement (20%), followed by new energy vehicles and energy storage (over 15%), and hydropower (9%). Wind power and new energy batteries showed minimal gains, under 1%. (3) Across all dimensions, industries’ adaptive recovery capacity generally surpasses their defensive resistance and transformative learning capacities. Based on these findings, we recommend tailored policies to guide new energy enterprises through digital transformation, boosting their resilience. We also suggest specific measures to strengthen their defensive resistance and transformative learning capacities.