Mingxin Lin

Dr. Mingxin Lin

orcid

Research Focus & Metrics

Academic Career Length

4Years (2023-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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7 April 2025 in Land
Verified
Journal Article
Open access
PDF file
MLMingxin Lin
Mingxin Lin
MWMengyao Wang
Mengyao Wang
YLYong Lu
Yong Lu
GZGuodong Zhou
Guodong Zhou
WSWanting S
Wanting S
JYJia You
Jia You
Synergizing agricultural heritage conservation with tourism utilization is pivotal for sustainable regional development. Using a difference-in-differences (DID) method and entropy weight method (EWM), this study comparatively analyzed the economic resilience of two UNESCO agricultural heritage sites in China: the Wujiang Silk Culture System and the Longji Terraces in Longsheng, from 2019 to 2023. The results revealed that heritage certification significantly promotes tourism growth, increasing revenue in Wujiang by 12.5% and visitor numbers in Longsheng by 18.3%. However, the resilience mechanisms varied distinctly between the sites: Wujiang displayed a market-driven resilience pattern characterized by effective cultural tourism integration, whereas Longsheng remained vulnerable due to resource dependency and infrastructural constraints. Further, Wujiang’s robust policy framework involving heritage conservation, tourism development, and ecological compensation fostered sustained resilience, albeit facing long-term challenges such as potential cultural commodification. This research contributes theoretically by quantifying the resilience disparities via spatial econometric analyses, identifying market-institution drivers, and proposing a “Four-Dimensional Optimization Matrix”, integrating value activation, infrastructure enhancement, industrial symbiosis, and adaptive governance. Practically, it provides tailored policy insights for improving resilience, avoiding over-commercialization, and promoting sustainable tourism practices applicable globally, particularly in developing economies managing heritage sites.

23 June 2024 in Land
Verified
Journal Article
Open access
PDF file
MLMingxin Lin
Mingxin Lin
ZWZuomin Wen
Zuomin Wen
In the management of national parks, the principal–agent relationship is key to efficient and effective management. Based on multi-task principal–agent theory, this study examines the dual functions of central government incentives and guidance and the objectives of local National Park Administration offices in environmental conservation and reasonable resource utilization. First, this study constructs a multi-task principal–agent model for central and local governments within the national park management system and identifies effective contractual mechanisms. Second, this study examines the relationship between the intensity of central government incentives and the ecological conservation atmosphere coefficient. Third, by integrating the three stages of national park management system advancement, this study explores the central government’s incentive strategies at different stages. The findings indicate that local governments receive limited ecological conservation support, underscoring the need for long-term central government incentives. The findings also confirm that the effective management of national parks by local governments can only be achieved by eliminating external uncertainties, reducing the variable costs of innovative advancements, and controlling risk aversion in local National Park Administration processes. In addition, this study includes empirical data for sensitivity analyses to understand the robustness of the model under different scenarios. This study offers valuable insights and practical suggestions for enhancing national park management.

28 July 2024 in Systems
Verified
Journal Article
Open access
PDF file
LZLingwei Zhuang
Lingwei Zhuang
ZWZuomin Wen
Zuomin Wen
MLMingxin Lin
Mingxin Lin
SWSijia Wang
Sijia Wang
XHXiaoxiao Hu
Xiaoxiao Hu
To address the complexities of national park management within China, this study investigated the evolutionary game between central and local governments in the context of Sanjiangyuan National Park, to explore strategic behavior and goal displacement issues. This research dissected the interplay and strategy evolution between governmental levels, considering the diverse interests, policy interpretations, and resource allocations that often lead to strategic misalignments. Employing an evolutionary game theory framework, we integrated a literature review and numerical simulations to delineate the dynamics of central–local governmental interactions. Our results underscore the pivotal role of strategic alignment in ensuring ecological conservation and socioeconomic development. The findings reveal that under certain conditions, characterized by minimization of rent-seeking behavior, cost-effective management, and risk mitigation, an evolutionarily stable strategy promoting optimal park management can emerge. This study concludes that a cooperative framework, underpinned by aligned incentives and strategic coherence between governmental levels, is critical for sustainable management of national parks. It contributes to understanding of governance models in national parks, offers insights into policy formulation and implementation within the ongoing environmental reform initiatives in China, reveals the behavioral strategies within national park management systems, and supports policy recommendations for enhancing governance quality and management efficiency.

23 October 2026 in Land
Verified
Journal Article
Open access
PDF file
MLMingxin Lin
Mingxin Lin
MWMengyao Wang
Mengyao Wang
YLYong Lu
Yong Lu
GZGuodong Zhou
Guodong Zhou
WSWanting S
Wanting S
JYJia You
Jia You
The Journal retracts the article “Synergizing Conservation and Tourism Utilization in Agricultural Heritage Sites: A Comparative Analysis of Economic Resilience in Wujiang and Longsheng, China”

1 January 2023
Verified
Conference Paper
Closed access
HQHao Qin
Hao Qin
LSLingzhi Shan
Lingzhi Shan
XTXueqing Tao
Xueqing Tao
MLMingxin Lin
Mingxin Lin
LXLeiyun Xu
Leiyun Xu
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