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<p>Effective taxation planning can significantly impact profitability and competitiveness in the dynamic energy market. This may include utilizing incentives for renewable energy projects, managing value-added tax on energy products, and navigating cross-border energy transition tax implications. Hence, to elucidate how accounting and taxation planning influence the performance of New Energy Enterprises amid the ongoing energy transition, this research gathered and synthesized financial metrics from a pool of 100 publicly listed new energy enterprises. The data were tracked from the CSMAR (China Stock Market Accounting Research) database to form the basis of the study, spanning from 2012 to 2020. The study utilized pooled regression analysis to ascertain the impact of factors including capital intensity, effective tax rate, tax savings, and company size on the financial performance of new energy enterprises. This study utilizes an Improved Bi-GRU and LinkNet (IBi-LinkNet) model to classify planning methodologies pertinent to accounting and taxation in emerging energy enterprises, particularly amidst the ongoing energy transition via input features. The IBi-LinkNet model combines the Improved Bi-GRU’s capacity to handle time-series data with LinkNet’s capability to extract spatial features, allowing for a more thorough examination of accounting and taxation methods in the energy industry during the transition. Notably, fine-tuning the Improved Bi-GRU model’s weights is conducted via the Coati updated Zebra Optimization Algorithm (CuZOA). The CuZOA is an optimization approach that fine-tunes the weights of the IBi-LinkNet model, improving classification accuracy and efficiency while minimizing computational costs and processing time. The result indicates that Effective tax rates, Capital intensity, and Tax savings substantially influence the performance of new energy enterprises. The outcomes generated from this analysis offer valuable insights into the strategic decisions and operational practices that can optimize financial performance and sustainability within the burgeoning new energy sector, thereby contributing to informed decision-making and strategic planning for stakeholders in this rapidly evolving industry landscape.</p>

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Planning methods for accounting and taxation in new energy enterprises in the context of energy transition

  • 期刊论文

  • 发表日期：

    2025年5月29日

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  • Su Zheng

摘要

Effective taxation planning can significantly impact profitability and competitiveness in the dynamic energy market. This may include utilizing incentives for renewable energy projects, managing value-added tax on energy products, and navigating cross-border energy transition tax implications. Hence, to elucidate how accounting and taxation planning influence the performance of New Energy Enterprises amid the ongoing energy transition, this research gathered and synthesized financial metrics from a pool of 100 publicly listed new energy enterprises. The data were tracked from the CSMAR (China Stock Market Accounting Research) database to form the basis of the study, spanning from 2012 to 2020. The study utilized pooled regression analysis to ascertain the impact of factors including capital intensity, effective tax rate, tax savings, and company size on the financial performance of new energy enterprises. This study utilizes an Improved Bi-GRU and LinkNet (IBi-LinkNet) model to classify planning methodologies pertinent to accounting and taxation in emerging energy enterprises, particularly amidst the ongoing energy transition via input features. The IBi-LinkNet model combines the Improved Bi-GRU’s capacity to handle time-series data with LinkNet’s capability to extract spatial features, allowing for a more thorough examination of accounting and taxation methods in the energy industry during the transition. Notably, fine-tuning the Improved Bi-GRU model’s weights is conducted via the Coati updated Zebra Optimization Algorithm (CuZOA). The CuZOA is an optimization approach that fine-tunes the weights of the IBi-LinkNet model, improving classification accuracy and efficiency while minimizing computational costs and processing time. The result indicates that Effective tax rates, Capital intensity, and Tax savings substantially influence the performance of new energy enterprises. The outcomes generated from this analysis offer valuable insights into the strategic decisions and operational practices that can optimize financial performance and sustainability within the burgeoning new energy sector, thereby contributing to informed decision-making and strategic planning for stakeholders in this rapidly evolving industry landscape.