Research on data driven dynamic mechanism of energy enterprise investment: based on system dynamics simulation

Under the background of global energy transformation and the integration of digital economy, energy enterprises’ digital investment faces the challenges of uncertain return cycle and lack of data asset pricing mechanism. By constructing a system dynamics model, this paper reveals the dynamic mechanism of data-driven digital investment decision-making of energy enterprises. The research shows that: the value of data assets forms a self reinforcing cycle through the return reinvestment loop, and its scale expansion is regulated by the dynamic balance between the cost constraint and the value inhibition loop; The improvement of market risk perception, the robustness of the trading market, the increase of energy policy intensity and the weakening of peer competition can significantly improve the cumulative profits of enterprises; Adaptive investment strategy has more advantages than fixed investment strategy, but the timing of strategy transformation needs to be accurately controlled. The simulation results provide a basis for enterprises to optimize the data investment path. It is suggested to build a data-driven dynamic investment system, deepen the operation of data assets, and call on the policy side to improve the data factor market system and incentive measures, so as to jointly promote the strategic transformation of energy enterprises to data centers.

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Publication Details

Journal
Energy Informatics
Published
2025-08-22
DOI
https://doi.org/10.1186/s42162-025-00573-x
Primary Topic
Innovation Diffusion and Forecasting
Type
article
Field-Weighted Citation Impact
0.00

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article

Research on data driven dynamic mechanism of energy enterprise investment: based on system dynamics simulation

Hongtao Zhu, Yue Zhu, Yuan Qiao
Energy Informatics
Innovation Diffusion and Forecasting
article

Research on data driven dynamic mechanism of energy enterprise investment: based on system dynamics simulation

Hongtao Zhu, Yue Zhu, Yuan Qiao
article en

Abstract

Under the background of global energy transformation and the integration of digital economy, energy enterprises’ digital investment faces the challenges of uncertain return cycle and lack of data asset pricing mechanism. By constructing a system dynamics model, this paper reveals the dynamic mechanism of data-driven digital investment decision-making of energy enterprises. The research shows that: the value of data assets forms a self reinforcing cycle through the return reinvestment loop, and its scale expansion is regulated by the dynamic balance between the cost constraint and the value inhibition loop; The improvement of market risk perception, the robustness of the trading market, the increase of energy policy intensity and the weakening of peer competition can significantly improve the cumulative profits of enterprises; Adaptive investment strategy has more advantages than fixed investment strategy, but the timing of strategy transformation needs to be accurately controlled. The simulation results provide a basis for enterprises to optimize the data investment path. It is suggested to build a data-driven dynamic investment system, deepen the operation of data assets, and call on the policy side to improve the data factor market system and incentive measures, so as to jointly promote the strategic transformation of energy enterprises to data centers.

Energy InformaticsVol. 8(1)
Inner Mongolia University of Finance and Economics (CN)
Natural Science Foundation of Inner Mongolia
Affordable and clean energy
Openalex Percentile: Top 74%
Innovation Diffusion and Forecasting
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Research on data driven dynamic mechanism of energy enterprise investment: based on system dynamics simulation — Hongtao Zhu, Yue Zhu, et al. · Energy Informatics (2025) | TGRS Research Map | TGRS