IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v13y2023i11p2118-d1276423.html
   My bibliography  Save this article

Spatial Correlation Network Structure of and Factors Influencing Technological Progress in Citrus-Producing Regions in China

Author

Listed:
  • Yumeng Gu

    (College of Economics and Management, Huazhong Agriculture University, Wuhan 430070, China
    Institute of Horticultural Economics, Huazhong Agriculture University, Wuhan 430070, China
    Hubei Rural Development Research Center, Wuhan 430070, China)

  • Chunjie Qi

    (College of Economics and Management, Huazhong Agriculture University, Wuhan 430070, China
    Institute of Horticultural Economics, Huazhong Agriculture University, Wuhan 430070, China)

  • Yu He

    (College of Economics and Management, Huazhong Agriculture University, Wuhan 430070, China
    Institute of Horticultural Economics, Huazhong Agriculture University, Wuhan 430070, China
    Hubei Rural Development Research Center, Wuhan 430070, China)

  • Fuxing Liu

    (College of Economics and Management, Huazhong Agriculture University, Wuhan 430070, China
    Hubei Rural Development Research Center, Wuhan 430070, China)

  • Beige Luo

    (Yiling District Administration for Rural Revitalization, Yichang 443100, China)

Abstract

In this study, the transcendental logarithmic cost function model was used to measure the rate of technological progress in seven major mandarin-producing regions and seven major tangerine-producing regions in China from 2006 to 2021. The modified gravity model was used to establish spatial correlation networks. The social network analysis method was used to analyze the characteristics of the overall network structure and the individual network structure of the spatial correlation networks of citrus-production technology progress, and the quadratic assignment procedure was used to analyze the factors influencing the spatial network. The results show the production of Chinese mandarins and tangerines is in the stage of technological progress in general, but the rate of progress is slowing down gradually, and the rate of mandarin-production technology progress is higher than that of tangerine-production technology progress. In terms of the overall network structure characteristics, the spatial networks of technological progress related to Chinese mandarin and tangerine production are becoming increasingly dense and complex, with obvious spatial spillover effects, but the network structure is relatively loose, and the polarization of the tangerine network is more serious. In terms of individual network structure characteristics, the relatively economically developed eastern regions have a higher status in terms of the spatial correlation network and a stronger role in controlling and dominating the resource elements needed for citrus-production technology progress. Education, informatization, economic development, innovation support, and financial support are important factors influencing the formation of the spatial association network of citrus-production technology progress in China.

Suggested Citation

  • Yumeng Gu & Chunjie Qi & Yu He & Fuxing Liu & Beige Luo, 2023. "Spatial Correlation Network Structure of and Factors Influencing Technological Progress in Citrus-Producing Regions in China," Agriculture, MDPI, vol. 13(11), pages 1-20, November.
    • Handle: RePEc:gam:jagris:v:13:y:2023:i:11:p:2118-:d:1276423
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/13/11/2118/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2077-0472/13/11/2118/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Christensen, Laurits R & Jorgenson, Dale W & Lau, Lawrence J, 1973. "Transcendental Logarithmic Production Frontiers," The Review of Economics and Statistics, MIT Press, vol. 55(1), pages 28-45, February.
    2. Christensen, Laurits R & Jorgenson, Dale W & Lau, Lawrence J, 1975. "Transcendental Logarithmic Utility Functions," American Economic Review, American Economic Association, vol. 65(3), pages 367-383, June.
    3. Mao, Weining & Koo, Won W., 1997. "Productivity growth, technological progress, and efficiency change in chinese agriculture after rural economic reforms: A DEA approach," China Economic Review, Elsevier, vol. 8(2), pages 157-174.
    4. K. J. Arrow, 1971. "The Economic Implications of Learning by Doing," Palgrave Macmillan Books, in: F. H. Hahn (ed.), Readings in the Theory of Growth, chapter 11, pages 131-149, Palgrave Macmillan.
    5. Yumeng Gu & Chunjie Qi & Fuxing Liu & Quanyong Lei & Yuchao Ding, 2023. "Spatiotemporal Evolution and Spatial Convergence Analysis of Total Factor Productivity of Citrus in China," Agriculture, MDPI, vol. 13(6), pages 1-14, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yueyuan Yang & Chunjie Qi & Yumeng Gu & Guozhu Fang, 2024. "Use Efficiency, Reduction Potential, and Effects of Fertilizers on Carbon Emissions in China’s Major Citrus Regions," Agriculture, MDPI, vol. 14(11), pages 1-19, November.

    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. Wilson, E.J. & Chaudhri, D.P., 2000. "Endogeneity, Knowledge and Dynamics of Long Run Capitalist Economic Growth," Economics Working Papers wp00-03, School of Economics, University of Wollongong, NSW, Australia.
    2. Valeria Costantini & Francesco Crespi & Elena Paglialunga, 2019. "Capital–energy substitutability in manufacturing sectors: methodological and policy implications," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 9(2), pages 157-182, June.
    3. Wang, Lan-Hsun & Liao, Shu-Yi & Huang, Mao-Lung, 2022. "The growth effects of knowledge-based technological change on Taiwan’s industry: A comparison of R&D and education level," Economic Analysis and Policy, Elsevier, vol. 73(C), pages 525-545.
    4. Dongyeol Lee & Hyunjoon Lim, 2017. "Multiple Thresholds In The Nexus Between Working Hours And Productivity," Contemporary Economic Policy, Western Economic Association International, vol. 35(4), pages 716-734, October.
    5. Lundmark, Robert, 2008. "Empirical specification of cost reductions associated with accumulated knowledge in the Swedish kraft paper industry," Forest Policy and Economics, Elsevier, vol. 10(7-8), pages 460-466, October.
    6. Rodolfo Cermeño & Sirenia Vázquez, 2009. "Technological Backwardness in Agriculture: Is it Due to Lack of R&D, Human Capital, and Openness to International Trade?," Review of Development Economics, Wiley Blackwell, vol. 13(4), pages 673-686, November.
    7. de Graaff, Thomas & Rietveld, Piet, 2007. "Substitution between working at home and out-of-home: The role of ICT and commuting costs," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(2), pages 142-160, February.
    8. Chen, Zhuo & Song, Shunfeng, 2008. "Efficiency and technology gap in China's agriculture: A regional meta-frontier analysis," China Economic Review, Elsevier, vol. 19(2), pages 287-296, June.
    9. Wijetunga, Chatura Sewwandi, 2023. "Rice Production Structures in Sri Lanka: The Normalized Translog Profit Function Approach," Asian Journal of Agriculture and Rural Development, Asian Economic and Social Society (AESS), vol. 6(02), January.
    10. Harabi, Najib, 1994. "Technischer Fortschritt in der Schweiz: Empirische Ergebnisse aus industrieökonomischer Sicht [Technischer Fortschritt in der Schweiz:Empirische Ergebnisse aus industrieökonomischer Sicht]," MPRA Paper 6725, University Library of Munich, Germany.
    11. Matsuyama, Kiminori, 2017. "Beyond CES: Three Alternative Classes of Flexible Homothetic Demand Systems," CEPR Discussion Papers 12210, C.E.P.R. Discussion Papers.
    12. Brox, James A., 2003. "The impact of free trade with the United States on the pattern of Canadian consumer spending and savings," The North American Journal of Economics and Finance, Elsevier, vol. 14(1), pages 69-87, March.
    13. Koenig, Michael & Hsieh, Chih-Sheng & Liu, Xiaodong & Zimmermann, Christian, 2018. "Superstar Economists: Coauthorship networks and research output," CEPR Discussion Papers 13239, C.E.P.R. Discussion Papers.
    14. He, Yongda & Lin, Boqiang, 2019. "Heterogeneity and asymmetric effects in energy resources allocation of the manufacturing sectors in China," Energy, Elsevier, vol. 170(C), pages 1019-1035.
    15. Kurt Kratena & Mark Sommer & Gerhard Streicher & Simone Salotti & Juan Manuel Valderas Jaramillo, 2017. "FIDELIO 2: Overview and Theoretical Foundations of the Second Version of the Fully Interregional Dynamic Econometric Long-term Input-Output Model for the EU 27," WIFO Studies, WIFO, number 61880, March.
    16. repec:ags:aaea20:304636 is not listed on IDEAS
    17. Jesus Felipe & John S.L. McCombie, 2013. "The Aggregate Production Function and the Measurement of Technical Change," Books, Edward Elgar Publishing, number 1975.
    18. Antimiani, Alessandro & Costantini, Valeria & Paglialunga, Elena, 2015. "The sensitivity of climate-economy CGE models to energy-related elasticity parameters: Implications for climate policy design," Economic Modelling, Elsevier, vol. 51(C), pages 38-52.
    19. Saad Labyad & Mehdi Senouci, 2018. "Deriving multiple-input production and utility functions from elasticities of substitution functions ," Working Papers hal-01866275, HAL.
    20. Chatura Sewwandi Wijetunga, 2016. "Rice production structures in Sri Lanka: The normalized translog profit function approach," Asian Journal of Agriculture and rural Development, Asian Economic and Social Society, vol. 6(2), pages 21-35, February.
    21. Xiaoling Wang & Jatin Nathwani & Chunyou Wu, 2016. "Visualization of International Energy Policy Research," Energies, MDPI, vol. 9(2), pages 1-14, January.

    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:gam:jagris:v:13:y:2023:i:11:p:2118-:d:1276423. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.