Studies on innovative energy startups’ topological roles and their correlation with success: based on temporal networks
IntroductionInnovative energy startups are expediting the energy transition through the adoption of emerging technologies, including blockchain, fintech, artificial intelligence, and crowdfunding. However, existing research primarily focuses on technological capabilities at the startup level and mac...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-07-01
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| Series: | Frontiers in Physics |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fphy.2025.1610832/full |
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| Summary: | IntroductionInnovative energy startups are expediting the energy transition through the adoption of emerging technologies, including blockchain, fintech, artificial intelligence, and crowdfunding. However, existing research primarily focuses on technological capabilities at the startup level and macro-level national applications to explore the current state of innovative energy adoption. In contrast, limited attention has been paid to analyzing the role attributes of innovative energy startups and their correlations with potential success, which are critical for understanding their development trajectories within the energy market.MethodsThis study develops a temporal investment information network for global energy startups, drawing on data from energy enterprises worldwide between 2005 and 2024. The research examines the role attributes of startups and explores the temporal topological characteristics of the network. We propose a success evaluation model based on the features of successful startups to assess the potential of innovative energy startups.Results and DiscussionThe findings indicate that, despite their relatively small market share, innovative energy startups exert significant influence. Notably, successful startups typically exhibit higher betweenness centrality and lower closeness centrality. Moreover, factors such as network degree, centrality, and government administrative capacity play crucial roles in determining the success of innovative energy startups. In the evaluation model constructed using these factors, network structural characteristics contribute the most, achieving an evaluation accuracy of 0.984. This study provides valuable insights for policymakers evaluating innovative energy development trends and for investors assessing the potential of startups. |
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| ISSN: | 2296-424X |