How to improve the performance of port adaptation investment? An independent cascade evolution model for port adaptation investment
Extreme weather events driven by climate change highlight the urgent need for port adaptation investments, which are often under-prioritized in favor of enhancing operational capacity. This study proposes an independent cascade evolution model aimed at optimizing the performance of port adaptation investments. Utilizing the independent cascade evolution model based on evolutionary game, the study investigates the national propagation of such investments. Data collection provides insights into the current performance levels and trends in port adaptation investment. The analysis results indicate that integrating disaster and environmental adaptation investments significantly increases national participation. Adaptation investment performance exhibits a "barrel effect," where the overall performance is limited by its weakest component. There is a positive correlation between initial investment size and performance, which eventually turns negative as investments grow. Moderate competition among ports enhances investment performance. Based on these findings, the study recommends several strategies to enhance port adaptation investment performance: prioritizing the stability of environmental adaptations, addressing the "barrel effect" by ensuring balanced investment across all necessary adaptation areas and recognizing and adapting to different stages of investment development. This study provides valuable guidance for port adaptation investments and supports national policy-making efforts to address the impacts of climate change on port infrastructure.
Authors
- Liang Wang (ORCID: https://orcid.org/0000-0002-4063-6842)
- Haoxin Peng
Publication Details
- Journal
- Regional Studies in Marine Science
- Published
- 2025-03-14
- DOI
- https://doi.org/10.1016/j.rsma.2025.104128
- Citations
- 1
- Primary Topic
- Maritime Ports and Logistics
- Type
- article
- Field-Weighted Citation Impact
- 1.24