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Impact of Different Models of Relocating Coal Mining Villages on the Livelihood Resilience of Rural Households—A Case Study of Huaibei City, Anhui Province

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  • Jing Wang

    (School of Public Policy and Management, China University of Mining and Technology, Xuzhou 221116, China)

  • Peijun Wang

    (School of Public Policy and Management, China University of Mining and Technology, Xuzhou 221116, China
    Research Center for Land Use and Ecological Security Governance in Mining Area, China University of Mining and Technology, Xuzhou 221116, China
    Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China)

  • Chunbo Zhu

    (School of Public Policy and Management, China University of Mining and Technology, Xuzhou 221116, China)

  • Yue Wang

    (School of Public Policy and Management, China University of Mining and Technology, Xuzhou 221116, China)

  • Zixiao Zhou

    (School of Public Policy and Management, China University of Mining and Technology, Xuzhou 221116, China)

Abstract

Applying the livelihood resilience theory to the relocation of coal mining villages, the present study explored the levels and the factors hindering livelihood resilience among farmers under different relocation models. This has important implications for enhancing the livelihood resilience of farmers during coal mining relocation and promoting rural revitalization in coal mining areas. Based on the livelihood resilience framework and the actual conditions of mining areas, we formulated an evaluation index system, employed the stratified mean square deviation method to determine weights, used the comprehensive index method to assess the livelihood resilience level, and investigated the obstacles to livelihood resilience among farmers under different relocation models using the random forest model. The results indicate the following: first, the overall livelihood resilience level in the coal mining relocation area of Huaibei City is low and is not significantly different among the four types, with the ranking being as follows: central village agglomeration type > township-centered village construction type > mining-village combination type > suburban community type. Significant differences exist in the indicators and dispersion levels of the resilience dimensions of buffering capacity, self-organization ability, and learning ability among farmers under different relocation models. Second, factors such as household deposits, labor force quantity, social networks, and participation in village collective meetings significantly affect the livelihood resilience level of farmers. However, the degree of influence varies under different relocation models. Third, improvements such as increasing employment opportunities, investing in education resources, and building social networks are necessary to improve farmers’ livelihoods under the four types of relocation models.

Suggested Citation

  • Jing Wang & Peijun Wang & Chunbo Zhu & Yue Wang & Zixiao Zhou, 2023. "Impact of Different Models of Relocating Coal Mining Villages on the Livelihood Resilience of Rural Households—A Case Study of Huaibei City, Anhui Province," Land, MDPI, vol. 12(12), pages 1-18, December.
    • Handle: RePEc:gam:jlands:v:12:y:2023:i:12:p:2169-:d:1300393
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    References listed on IDEAS

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    1. Xueping Li & Xingmin Shi, 2022. "Smallholders’ Livelihood Resilience in the Dryland Area of the Yellow River Basin in China from the Perspective of the Family Life Cycle: Based on GeoDetector and LMG Metric Model," Land, MDPI, vol. 11(9), pages 1-19, August.
    2. Rijan Bhakta Kayastha & Woo-Kyun Lee & Nischal Shrestha & Sonam Wangyel Wang, 2023. "Assessing the Livelihood Vulnerability of Nomads to Changing Climate in the Third Pole Region of Nepal," Land, MDPI, vol. 12(5), pages 1-14, May.
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    4. Tiziana Pagnani & Elisabetta Gotor & Francesco Caracciolo, 2021. "Adaptive strategies enhance smallholders’ livelihood resilience in Bihar, India," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 13(2), pages 419-437, April.
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