Under the energy transition, resource-based enterprises face the challenge of value reassessment, and traditional valuation models are ineffective due to neglecting data assets. This study adopts empirical methods to explore the impact and pathway of data asset information disclosure on market response through regression analysis, robustness testing, mechanism testing, moderation effects, and heterogeneity analysis. The results show that there is a significant positive relationship between data asset information disclosure and market response, and the regression coefficients are significant at the 1% level; Robustness testing (replacing independent variables, dependent variable windows, sub samples) enhances the reliability of the results; Endogeneity testing eliminates interference; Mechanism verification confirms the transmission effect of investor, analyst, and media attention; The moderation effect shows that the readability of annual reports is most significantly moderated during the data collection stage; Heterogeneity analysis shows that market reactions are more prominent in various stages of data assetization (especially in the analysis stage), high competitive industries, high-tech and high quality internal control enterprises. This study constructs a value reassessment framework for data asset information disclosure from the perspective of energy transition, revealing market response mechanisms and group differences, providing support for theoretical development and practical applications, and promoting resource-based enterprises to achieve sustainable value creation in the energy revolution and digital economy.

Zinuo Wang. Value Reassessment Logic of Resource-Based Enterprises in the Context of Energy Transition. International Journal of Social Sciences and Economic Management (2026), Vol. 7, Issue 1: 144-153. https://doi.doi.org/10.3807/IJSSEM.2026.070115.

[1] LEADING THE ENERGY TRANSITION[J]. Australian Mining, 2025(3):117. 4.

[2] Zhou X, Qi M, Tian Y,et al. Influence Mechanism of Data-Driven Dynamic Capability of Foreign Trade SMEs Based on the Perspective of Digital Intelligence Immunity[J]. Sustainability, 2025, 17(15):6750.

[3] Ding X, Li G, Tang Y,et al. A Survey on Data Asset Value Change Estimation and Appreciation with Data Governance[J]. Big Data Mining and Analytics, 2025, 8(6):1369-1387. DOI:10. 26599/BDMA. 2025. 9020034.

[4]  Ding X, Li G, Tang Y,et al. A Survey on Data Asset Value Change Estimation and Appreciation with Data Governance[J]. Big Data Mining and Analytics, 2025, 8(6):1369-1387. DOI:10. 26599/BDMA. 2025. 9020034.

[5] Ye, J. (2025). Design of a Non-Invasive Brain Computer Interface System for Handwritten Text Based on L2 Regularization and Attention Supervision Paradigm, and Optimization of EEG Signal Decoding. International Journal of Big Data Intelligent Technology, 2025, 6 (1), 126, 134.

[6] Zhen Zhong. Big Data Engineering and Intelligent Analysis Framework for Compliance Investigation. Academic Journal of Computing & Information Science (2025), Vol. 8, Issue 11: 107-115

[7] Wu, W. (2025, June). Construction and optimization of intelligent gateway software management platform based on jenkins cluster management under cloud edge integration architecture in industrial internet of things. In International Conference on 6G Communications Networking and Signal Processing (pp. 633-645). Singapore: Springer Nature Singapore.

[8] Wu, L. (2025, December). Design and Application of Automatic Data Set Generation Tool Based on KLEE in Embedded Memory Management Performance Test Framework. In 2025 IEEE 17th International Conference on Computational Intelligence and Communication Networks (CICN) (pp. 1111-1117). IEEE.

[9] Truong, T. H. (2026). Research on Risks and Countermeasures of Enterprise E-Commerce Transformation in the Cross-Border E-Commerce Environment.

[10] Qi, Y. (2025, October). Research on Privacy Protection of AI Models in Big Data Using Differential Privacy Technology. In 2025 2nd International Conference on Software, Systems and Information Technology (SSITCON) (pp. 1-5). IEEE.

[11] Truong, T. H. (2025). Research on the Application of Digital Healthcare Platforms in Chronic Disease Management. Advances in Computer and Communication, 6(5).

[12] Hong, Y. (2025). Architecture Design and Performance Optimization of a Large-scale Online Simulation Platform for Business Decision-making. Advances in Computer and Communication, 6(4).

[13] Huang, J. (2025, September). Performance Evaluation Index System and Engineering Best Practice of Production-Level Time Series Machine Learning System. In 2025 International Conference on Intelligent Communication Networks and Computational Techniques (ICICNCT) (pp. 01-07). IEEE.

[14] Hong, Y. (2026). Research on Warehouse Capacity Optimization Methods Based on Predictive Modeling. Engineering Advances, 6(1).

[15] Ye, J. (2025). Optimization and Application of Gesture Classification Algorithm Based on EMG. Journal of Computer, Signal, and System Research, 2(5), 41-47.

[16] Huang, J. (2026). Practice of Public Space Optimization and Functional Enhancement in Cultural Architecture. European Journal of Engineering and Technologies, 2(1), 9-21.

[17] Ye, J. (2025). Optimization of Neural Motor Control Model Based on EMG Signals. International Journal of Engineering Advances, 2(4), 1-8.

[18] Zhang, X. (2025). Optimization and Implementation of Time Series Dimensionality Reduction Anti-fraud Model Integrating PCA and LSTM under the Federated Learning Framework. Procedia Computer Science, 262, 992-1001.

[19] Huang, J. (2025, August). Research on Multi-Model Fusion Machine Learning Demand Intelligent Forecasting System in Cloud Computing Environment. In 2025 2nd International Conference on Intelligent Algorithms for Computational Intelligence Systems (IACIS) (pp. 1-7). IEEE.

[20] Hui, X. (2026). Research on the Design and Optimization of Automated Data Collection and Visual Dashboard in the Medical Industry. Journal of Computer, Signal, and System Research, 3(1), 27-34.

[21] Wang, Y. (2026). Research on Optimization of Neuromuscular Rehabilitation Program Based on Physiological Assessment. European Journal of AI, Computing & Informatics, 2(1), 21-30.

[22] Liu, Y. (2026). The Application of Data-Driven Financial Risk Management in Multinational Enterprises. Economics and Management Innovation, 3(1), 20-26.

[23] Hua, X. (2024, November). Design and Implementation of a Game QoE Monitoring and Evaluation System Driven by Network Traffic Analysis. In International Conference on Cognitive based Information Processing and Applications (pp. 149-161). Singapore: Springer Nature Singapore.

[24] Zhou, Y. (2024, November). Construction of a Multi-factor Quantitative Stock Selection System for the New Energy Industry Based on Microservices Architecture and Machine Learning Components. In International Conference on Cognitive based Information Processing and Applications (pp. 163-174). Singapore: Springer Nature Singapore.