Research on the Key Factors of the Follow-up Development of the Northwest Relocation Poverty Alleviation and Resettlement Area: Taking Baoan Town, Shaanxi as an Example
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摘要: 易地扶贫搬迁是一项持续性的任务，做好易地扶贫搬迁安置区后续发展工作是巩固西北地区脱贫攻坚成果的重要内容。本研究根据现有文献经验，识别易地扶贫搬迁安置区后续发展的影响因素，并结合陕西省商洛市洛南县保安镇2016—2018年的面板数据，运用RM-BP-DEMATEL方法，从基础设施、公共服务设施、住房建设、组织建设和产业发展五方面对易地扶贫搬迁安置区后续发展的关键影响因素进行提取。结果显示：搬迁安置区入住率、党员乡贤在农村基层党组织中的比例、自来水入户率，以及产业项目个数是易地扶贫搬迁安置区后续发展的关键影响因素。建议加强基层组织建设、完善公共服务配套、注重产业发展，为易地扶贫搬迁安置区后续发展提质增效。Abstract: Relocation for poverty alleviation is a continuous task. Implementing follow-up development of resettlement areas for poverty alleviation and relocation is an important part of consolidating the achievements of poverty alleviation in Northwest China. Based on the existing literature experience, this study identifies factors affecting the subsequent development of relocation areas for poverty alleviation and resettlement, and combines the panel data of Baoan Town, Shaanxi Province from 2016 to 2018, and uses the RM-BP-DEMATEL method to analyze infrastructure and public service facilities. It extract the key influencing factors for the follow-up development of resettlement areas for poverty alleviation and relocation from the perspective of infrastructure construction, public service construction, housing construction, organizational construction and industrial development. The results show that the occupancy rate of the relocation resettlement area, the proportion of party members Xiangxian in the rural grassroots party organizations, the rate of tap water entry and the number of industrial projects are the key influencing factors for the subsequent development of the relocation resettlement area. It is recommended to strengthen the construction of grassroots organizations, improve the supporting facilities of public services, and focus on industrial development, so as to improve the quality and efficiency of the follow-up development of the relocation resettlement areas.
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[1] 新华社评论员. 脱贫摘帽是新奋斗的起点[N]. 新华每日电讯,2021-03-02(2). [2] 邢成举. 搬迁扶贫与移民生计重塑:陕省证据[J]. 改革, 2016(10):65-73 [3] Zhu N, Luo X. The impact of migration on rural poverty and inequality:a case study in china[J]. Agricultural Economics, 2010,42(2):191-204. [4] 赵双, 李万莉. 我国易地扶贫搬迁的困境与对策:一个文献综述[J]. 社会保障研究,2018(2):106-112. [5] 刘伟, 徐洁, 黎洁. 连片特困地区易地扶贫搬迁对农户多维贫困的影响研究[J]. 干旱区资源与环境,2019,33(3):13-20. [6] 郑品芳, 刘长庚. 贫困户精准识别困境及识别机制构建[J]. 经济地理,2018,38(4):176-182. [7] 胡联, 汪三贵. 我国建档立卡面临精英俘获的挑战吗?[J]. 管理世界,2017(1):89-98. [8] 何得桂, 党国英. 西部山区易地扶贫搬迁政策执行偏差研究——基于陕南的实地调查[J]. 国家行政学院学报,2015(6):121-125. [9] 贺立龙, 郑怡君, 胡闻涛. 如何提升易地搬迁脱贫的精准性及实效——四川省易地扶贫搬迁部分地区的村户调查[J]. 农村经济,2017(10):80-85. [10] Rogers S, Xue T. Resettlement and climate change vulnerability:Evidence from rural China[J]. Global Environmental Change,2015,35(8):62-69. [11] 郭俊华, 赵培. 西北地区易地移民搬迁扶贫——既有成效、现实难点与路径选择[J]. 西北农林科技大学学报(社会科学版),2019,19(4):69-77. [12] 马良灿, 陈淇淇. 易地扶贫搬迁移民社区的治理关系与优化[J]. 云南大学学报(社会科学版),2019,18(3):110-117. [13] 吕建兴, 曾小溪, 汪三贵. 扶持政策、社会融入与易地扶贫搬迁户的返迁意愿——基于5省10县530户易地扶贫搬迁的证据[J]. 南京农业大学学报(社会科学版),2019,19(3):29-40, 156. [14] Chen Y, Li J, Li Y, et al. RM-DEMATEL:a new methodology to identify the key factors in PM 2.5[J]. Environmental Science & Pollution Research,2015,22(8):6372-6380. [15] Li Y, Liu J, Bao Q, et al. A new method of mapping relations from data based on artificial neural network[J]. International Journal of System Assurance Engineering and Management, 2014,5(4):544-553. [16] 崔强, 徐鑫, 匡海波. 基于RM-DEMATEL的交通运输低碳化能力影响因素分析[J]. 管理评论,2018,30(1):210-220. [17] Liu J, Li Y, Sadiq R, et al. Quantifying influence of weather indices on pm2.5 based on relation map[J]. Stochastic Environmental Research and Risk Assess ment,2014,28(6):1323-1331. [18] 毛健, 赵红东, 姚婧婧. 人工神经网络的发展及应用[J]. 电子设计工程,2011,19(24):62-65 [19] Tang Z, Fishwick PA. Feedforward neural nets as models for time seriesforecasting[J]. ORSA J Comput,1991,5(4):374-385. [20] Funahashi K I. On the approximate realization of continuous mappings by neural networks[J]. Neural Networks, 1989,2(3):183-192. -
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