An evolutionary model based on Lotka-Volterra equations for the symbiotic evolution of Macao’s diversified industrial ecosystem

Crafting a balanced and diversified industrial development strategy has become a critical issue for refining Macao’s industrial structure in response to the challenge of declining tax revenue. For which, ensuring symbiosis between various sectors is essential. However, the complexities of such interindustry relationships, particularly those involving the four policy-supported emerging industries, remain unclear. In view of this, this study constructs a symbiotic evolutionary model of the multi-industry ecosystem in Macao to empirically analyze the symbiotic ecological evolution of various industries from 2012 to 2024. The results reveal that the symbiotic evolution of Macao’s industrial ecology is currently in an early development stage. Under policy guidance, emerging industries can promote the symbiotic benefits of multiple industries, but it will take some time to achieve the ideal model of mutually beneficial symbiosis between emerging and traditional industries. Among them, the banking industry provides additional network space for improving multiple industries’ symbiosis, integration, and collaboration and alleviating unreasonable resource competition between various industries. In addition, Macao’s policy guidance will significantly accelerate the pace of the multi-industry ecological niche development. Although it may have an impact on short-term tax revenue, it will considerably benefit Macao’s long-term economic development. This study provides valuable insights for Macao to develop moderately diversified economic development policies and establish an industrial symbiosis environment.

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Publication Details

Journal
Sustainable Futures
Published
2025-09-25
DOI
https://doi.org/10.1016/j.sftr.2025.101336
Citations
2
Primary Topic
Sustainable Industrial Ecology
Type
article
Field-Weighted Citation Impact
2.48
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article

An evolutionary model based on Lotka-Volterra equations for the symbiotic evolution of Macao’s diversified industrial ecosystem

Peng He, Man Jin
2 citations
Sustainable Futures
Sustainable Industrial Ecology
2.48
article

An evolutionary model based on Lotka-Volterra equations for the symbiotic evolution of Macao’s diversified industrial ecosystem

Peng He, Man Jin
article en
2 citations

Abstract

Crafting a balanced and diversified industrial development strategy has become a critical issue for refining Macao’s industrial structure in response to the challenge of declining tax revenue. For which, ensuring symbiosis between various sectors is essential. However, the complexities of such interindustry relationships, particularly those involving the four policy-supported emerging industries, remain unclear. In view of this, this study constructs a symbiotic evolutionary model of the multi-industry ecosystem in Macao to empirically analyze the symbiotic ecological evolution of various industries from 2012 to 2024. The results reveal that the symbiotic evolution of Macao’s industrial ecology is currently in an early development stage. Under policy guidance, emerging industries can promote the symbiotic benefits of multiple industries, but it will take some time to achieve the ideal model of mutually beneficial symbiosis between emerging and traditional industries. Among them, the banking industry provides additional network space for improving multiple industries’ symbiosis, integration, and collaboration and alleviating unreasonable resource competition between various industries. In addition, Macao’s policy guidance will significantly accelerate the pace of the multi-industry ecological niche development. Although it may have an impact on short-term tax revenue, it will considerably benefit Macao’s long-term economic development. This study provides valuable insights for Macao to develop moderately diversified economic development policies and establish an industrial symbiosis environment.

Sustainable FuturesVol. 10
Chaohu University (CN), Tsinghua University (CN)
Openalex Percentile: Top 9%
Sustainable Industrial Ecology
2.48
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