Study on the Identification and Evaluation of Digital Business Models of State-Owned Power Company
- DOI
- 10.2991/978-94-6463-676-5_22How to use a DOI?
- Keywords
- Business model evaluation; Digital business; Stata
- Abstract
This study takes a state-owned energy enterprise as an example to calculate the business model, and explains the detailed calculation process of applying the business model identification and evaluation model by using STATA. Based on the constructed evaluation index system for business model identification and selection, this study adopts the improved hierarchical analysis method and the comprehensive evaluation method based on gray system whitening weight function to establish the evaluation model, which can realize the comprehensive evaluation of new business models. In this study, from the business models in the three major fields of energy industry service, energy consumption service and asset operation of future grid enterprises, four business models such as big data service of electric power equipment are selected as research objects, and each business model is evaluated. The results suggests that the integrated energy service and PV cloud should be prioritized.
- Copyright
- © 2025 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Dongfang Zhang AU - Penghui Liu AU - Yang Yang AU - Mengyuan Qi AU - Xiaole Lin AU - Yibin Yu AU - Xiaoyu Fan PY - 2025 DA - 2025/04/15 TI - Study on the Identification and Evaluation of Digital Business Models of State-Owned Power Company BT - Proceedings of the 2024 6th Management Science Informatization and Economic Innovation Development Conference (MSIEID 2024) PB - Atlantis Press SP - 212 EP - 220 SN - 2352-5428 UR - https://doi.org/10.2991/978-94-6463-676-5_22 DO - 10.2991/978-94-6463-676-5_22 ID - Zhang2025 ER -