IDEAS home Printed from https://ideas.repec.org/a/bla/growch/v54y2023i1p326-345.html
   My bibliography  Save this article

Spatial differentiation and factors influencing the benefits of industrial poverty alleviation in villages

Author

Listed:
  • Tian He
  • Rui Yuan Chen
  • Zi Yi Wang
  • Ping Jun Sun
  • Man Jiang Shi
  • Lin Xiong
  • Yuan Li Liu
  • He Ping Liao

Abstract

Industrial poverty alleviation is one of the most important aspects of targeted poverty alleviation. Identifying the mechanism influencing the spatial differentiation of the benefits of industrial poverty alleviation plays an essential role in optimising an industrial layout for poverty alleviation, consolidating poverty alleviation achievements, and revitalising rural industries. This study examined the spatial distribution characteristics and influencing factors of the benefits of industrial poverty alleviation at the village level using the household data collected from Jiangjin District, Chongqing, China. The results show that the benefits of industrial poverty alleviation presented obvious spatial differentiation in the villages with the overall performance being high in the north and low in the south and decreasing from the south of the county to the north and south. Spatially, there was a significant positively correlated agglomeration effect. High‐value agglomeration areas were concentrated in the north with the characteristics of ‘one centre and two subcentres’. However, low‐value and outlier agglomeration effects were not obvious, presenting sporadic distribution. Seven major factors affect industrial poverty alleviation in Jiangjin District, including average altitude and land transfer rate. The interaction between any two of the seven factors has a more significant impact than that of a single factor.

Suggested Citation

  • Tian He & Rui Yuan Chen & Zi Yi Wang & Ping Jun Sun & Man Jiang Shi & Lin Xiong & Yuan Li Liu & He Ping Liao, 2023. "Spatial differentiation and factors influencing the benefits of industrial poverty alleviation in villages," Growth and Change, Wiley Blackwell, vol. 54(1), pages 326-345, March.
  • Handle: RePEc:bla:growch:v:54:y:2023:i:1:p:326-345
    DOI: 10.1111/grow.12658
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/grow.12658
    Download Restriction: no

    File URL: https://libkey.io/10.1111/grow.12658?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Vijaya, Ramya M. & Lahoti, Rahul & Swaminathan, Hema, 2014. "Moving from the Household to the Individual: Multidimensional Poverty Analysis," World Development, Elsevier, vol. 59(C), pages 70-81.
    2. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wen-Min Lu & Qian Long Kweh & Chung-Wei Wang, 2021. "Integration and application of rough sets and data envelopment analysis for assessments of the investment trusts industry," Annals of Operations Research, Springer, vol. 296(1), pages 163-194, January.
    2. Franz R. Hahn, 2007. "Determinants of Bank Efficiency in Europe. Assessing Bank Performance Across Markets," WIFO Studies, WIFO, number 31499.
    3. Alperovych, Yan & Hübner, Georges & Lobet, Fabrice, 2015. "How does governmental versus private venture capital backing affect a firm's efficiency? Evidence from Belgium," Journal of Business Venturing, Elsevier, vol. 30(4), pages 508-525.
    4. Chen, Ya & Pan, Yongbin & Liu, Haoxiang & Wu, Huaqing & Deng, Guangwei, 2023. "Efficiency analysis of Chinese universities with shared inputs: An aggregated two-stage network DEA approach," Socio-Economic Planning Sciences, Elsevier, vol. 90(C).
    5. Kristiaan Kerstens & Jafar Sadeghi & Ignace Van de Woestyne, 2020. "Plant capacity notions in a non-parametric framework: a brief review and new graph or non-oriented plant capacities," Annals of Operations Research, Springer, vol. 288(2), pages 837-860, May.
    6. Ashrafi, Ali & Seow, Hsin-Vonn & Lee, Lai Soon & Lee, Chew Ging, 2013. "The efficiency of the hotel industry in Singapore," Tourism Management, Elsevier, vol. 37(C), pages 31-34.
    7. Juan Aparicio & Jesus T. Pastor & Jose L. Sainz-Pardo & Fernando Vidal, 2020. "Estimating and decomposing overall inefficiency by determining the least distance to the strongly efficient frontier in data envelopment analysis," Operational Research, Springer, vol. 20(2), pages 747-770, June.
    8. Espinoza-Delgado, José & Silber, Jacques, 2018. "Multi-dimensional poverty among adults in Central America and gender differences in the three I’s of poverty: Applying inequality sensitive poverty measures with ordinal variables," MPRA Paper 88750, University Library of Munich, Germany.
    9. Qin, Quande & Li, Xin & Li, Li & Zhen, Wei & Wei, Yi-Ming, 2017. "Air emissions perspective on energy efficiency: An empirical analysis of China’s coastal areas," Applied Energy, Elsevier, vol. 185(P1), pages 604-614.
    10. Atris, Amani Mohammed & Goto, Mika, 2019. "Vertical structure and efficiency assessment of the US oil and gas companies," Resources Policy, Elsevier, vol. 63(C), pages 1-1.
    11. Chen, Yufeng & Ni, Liangfu & Liu, Kelong, 2021. "Does China's new energy vehicle industry innovate efficiently? A three-stage dynamic network slacks-based measure approach," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    12. Mohammad Nourani & Qian Long Kweh & Evelyn Shyamala Devadason & V.G.R. Chandran, 2020. "A decomposition analysis of managerial efficiency for the insurance companies: A data envelopment analysis approach," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 41(6), pages 885-901, September.
    13. Honma, Satoshi, 2012. "Environmental and economic efficiencies in the Asia-Pacific region," MPRA Paper 43361, University Library of Munich, Germany.
    14. Bao Jiang & Enxin Chi & Jian Li, 2022. "Uncertain Data Envelopment Analysis for Cross Efficiency Evaluation with Imprecise Data," Mathematics, MDPI, vol. 10(13), pages 1-9, June.
    15. Jia Li & Yahong Zheng & Bing Liu & Yanyi Chen & Zhihang Zhong & Chenyu Dong & Chaoqun Wang, 2024. "The Synergistic Relationship between Low-Carbon Development of Road Freight Transport and Its Economic Efficiency—A Case Study of Wuhan, China," Sustainability, MDPI, vol. 16(7), pages 1-22, March.
    16. Yongqi Feng & Haolin Zhang & Yung-ho Chiu & Tzu-Han Chang, 2021. "Innovation efficiency and the impact of the institutional quality: a cross-country analysis using the two-stage meta-frontier dynamic network DEA model," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3091-3129, April.
    17. Eder, Andreas, 2024. "The effect of land fragmentation on risk and technical efficiency of crop farms," FORLand Working Papers 31 (2024), Humboldt University Berlin, DFG Research Unit 2569 FORLand "Agricultural Land Markets – Efficiency and Regulation".
    18. Zhuang Miao & Tomas Baležentis & Zhihua Tian & Shuai Shao & Yong Geng & Rui Wu, 2019. "Environmental Performance and Regulation Effect of China’s Atmospheric Pollutant Emissions: Evidence from “Three Regions and Ten Urban Agglomerations”," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 74(1), pages 211-242, September.
    19. Yu-Chuan Chen & Yung-Ho Chiu & Tzu-Han Chang & Tai-Yu Lin, 2023. "Sustainable Development, Government Efficiency, and People’s Happiness," Journal of Happiness Studies, Springer, vol. 24(4), pages 1549-1578, April.
    20. Ruijing Zheng & Yu Cheng & Haimeng Liu & Wei Chen & Xiaodong Chen & Yaping Wang, 2022. "The Spatiotemporal Distribution and Drivers of Urban Carbon Emission Efficiency: The Role of Technological Innovation," IJERPH, MDPI, vol. 19(15), pages 1-22, July.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:growch:v:54:y:2023:i:1:p:326-345. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0017-4815 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.