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<p>Establishing a Regional Marine Innovation Ecosystem (<i>RMIE</i>) is crucial for advancing China’s maritime power strategy. Concurrently, developing a competitive <i>RMIE</i> serves as a strategic lever to enhance the global competitiveness of China’s marine science sector. However, research on the competitiveness of <i>RMIE</i> is limited. To this end, this study constructs an evaluation index system based on ecological niche theory to assess the competitiveness of <i>RMIE</i> in China from 2008 to 2020. The findings indicate generally fluctuating upward trends in <i>RMIE’s</i> competitiveness, with Shandong, Jiangsu, and Guangdong showing relatively strong positions. Notably, there are significant intra-regional imbalances and inter-regional asynchrony in <i>RMIE’s</i> competitiveness across China’s three major marine economic circles. Recognizing that forecasting <i>RMIE</i> competitiveness can inform policy formulation, this paper proposes a systematic multivariate grey interval prediction model that incorporates spatial proximity effects. This model effectively captures the interval and uncertainty characteristics of <i>RMIE’s</i> competitiveness while considering spatial relationships among regions. Results from comparative analysis, robustness tests, and sensitivity analysis demonstrate its superior applicability and forecasting accuracy. Additionally, interval forecasts and scenario analyses suggest that <i>RMIE</i> competitiveness will maintain stable growth, although unbalanced and unsynchronized development is likely to persist. Overall, the approach developed for evaluating and forecasting <i>RMIE</i> competitiveness offers valuable insights for effective policy formulation.</p>

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Evaluation and forecast of the regional marine innovation ecosystem’s competitiveness: A systematic multivariate grey interval model with spatial proximity effects

  • 期刊论文

  • 发表日期：

    2026年2月13日

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  • Xuemei Li,
  • Na Li,
  • Song Ding

摘要

Establishing a Regional Marine Innovation Ecosystem (RMIE) is crucial for advancing China’s maritime power strategy. Concurrently, developing a competitive RMIE serves as a strategic lever to enhance the global competitiveness of China’s marine science sector. However, research on the competitiveness of RMIE is limited. To this end, this study constructs an evaluation index system based on ecological niche theory to assess the competitiveness of RMIE in China from 2008 to 2020. The findings indicate generally fluctuating upward trends in RMIE’s competitiveness, with Shandong, Jiangsu, and Guangdong showing relatively strong positions. Notably, there are significant intra-regional imbalances and inter-regional asynchrony in RMIE’s competitiveness across China’s three major marine economic circles. Recognizing that forecasting RMIE competitiveness can inform policy formulation, this paper proposes a systematic multivariate grey interval prediction model that incorporates spatial proximity effects. This model effectively captures the interval and uncertainty characteristics of RMIE’s competitiveness while considering spatial relationships among regions. Results from comparative analysis, robustness tests, and sensitivity analysis demonstrate its superior applicability and forecasting accuracy. Additionally, interval forecasts and scenario analyses suggest that RMIE competitiveness will maintain stable growth, although unbalanced and unsynchronized development is likely to persist. Overall, the approach developed for evaluating and forecasting RMIE competitiveness offers valuable insights for effective policy formulation.