IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i4p2982-d1060162.html
   My bibliography  Save this article

The Effect of Social Network on Controlled-Release Fertilizer Use: Evidence from Rice Large-Scale Farmers in Jiangsu Province, China

Author

Listed:
  • Ruoxi Ma

    (School of Business, East China University of Science and Technology, Shanghai 200237, China)

  • Shangguang Yang

    (School of Business, East China University of Science and Technology, Shanghai 200237, China)

Abstract

The reduction and efficiency of fertilizer use has been a recent focus of governments and scholars. As a new agricultural technology, controlled-release fertilizer can not only increase yield and save labor, but also improve efficiency and reduce the use of fertilizer, thus promoting sustainable agricultural development. Drawing on a sample of 231 farmers of Jiangsu Province, China, this paper applies a probit model to assess the adoption behavior of controlled-release fertilizer by large-scale households in terms of three dimensions of social network, i.e., communication intensity, trust level, and network size, specifically exploring how science popularization influences their adoption intention, and comparing the heterogeneity of impact that social network has on the adoption intention of farmers when the information is obtained adequately or not. The empirical results demonstrate that: (1) At the early stage of technology diffusion, the size of social network has a positive effect on farmers’ cognition of controlled-release fertilizer, and the communication intensity with neighboring farmers has a positive effect on the adoption behavior of controlled-release fertilizer; (2) Farmers’ adoption intention of controlled-release fertilizer is significantly influenced by their original knowledge of new technology and science popularization; (3) When the information is sufficient, the social network of large-scale households has no significant effect on their willingness to adopt. Therefore, in promoting controlled-release fertilizer, the government should highlight the synergistic effect of farmers’ cognition and science popularization activities, fully consider the characteristics of farmers’ social network, facilitate the infrastructure of rural informatization, and regulate the agricultural promotion networks so that farmers can obtain sufficient and effective information.

Suggested Citation

  • Ruoxi Ma & Shangguang Yang, 2023. "The Effect of Social Network on Controlled-Release Fertilizer Use: Evidence from Rice Large-Scale Farmers in Jiangsu Province, China," Sustainability, MDPI, vol. 15(4), pages 1-16, February.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:4:p:2982-:d:1060162
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/4/2982/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/4/2982/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Adnan, Nadia & Nordin, Shahrina Md & Ali, Murad, 2018. "A solution for the sunset industry: Adoption of Green Fertiliser Technology amongst Malaysian paddy farmers," Land Use Policy, Elsevier, vol. 79(C), pages 575-584.
    2. Foster, Andrew D & Rosenzweig, Mark R, 1995. "Learning by Doing and Learning from Others: Human Capital and Technical Change in Agriculture," Journal of Political Economy, University of Chicago Press, vol. 103(6), pages 1176-1209, December.
    3. Margarita Genius & Phoebe Koundouri & Céline Nauges & Vangelis Tzouvelekas, 2014. "Information Transmission in Irrigation Technology Adoption and Diffusion: Social Learning, Extension Services, and Spatial Effects," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 96(1), pages 328-344.
    4. Brick, Kerri & Visser, Martine, 2015. "Risk preferences, technology adoption and insurance uptake: A framed experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 118(C), pages 383-396.
    5. JunJie Wu & Bruce A. Babcock, 1998. "The Choice of Tillage, Rotation, and Soil Testing Practices: Economic and Environmental Implications," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(3), pages 494-511.
    6. Shikuku, Kelvin Mashisia, 2019. "Information exchange links, knowledge exposure, and adoption of agricultural technologies in northern Uganda," World Development, Elsevier, vol. 115(C), pages 94-106.
    7. Elaine M. Liu, 2013. "Time to Change What to Sow: Risk Preferences and Technology Adoption Decisions of Cotton Farmers in China," The Review of Economics and Statistics, MIT Press, vol. 95(4), pages 1386-1403, October.
    8. Ndiritu, S. Wagura & Kassie, Menale & Shiferaw, Bekele, 2014. "Are there systematic gender differences in the adoption of sustainable agricultural intensification practices? Evidence from Kenya," Food Policy, Elsevier, vol. 49(P1), pages 117-127.
    9. Bekele Shiferaw & Tewodros Kebede & Menale Kassie & Monica Fisher, 2015. "Market imperfections, access to information and technology adoption in Uganda: challenges of overcoming multiple constraints," Agricultural Economics, International Association of Agricultural Economists, vol. 46(4), pages 475-488, July.
    10. Arieli, Itai & Babichenko, Yakov & Peretz, Ron & Young, H. Peyton, 2020. "The speed of innovation diffusion in social networks," LSE Research Online Documents on Economics 102538, London School of Economics and Political Science, LSE Library.
    11. B. L. Gardner & G. C. Rausser (ed.), 2001. "Handbook of Agricultural Economics," Handbook of Agricultural Economics, Elsevier, edition 1, volume 1, number 2.
    12. Wanglin Ma & Awudu Abdulai & Renan Goetz, 2018. "Agricultural Cooperatives and Investment in Organic Soil Amendments and Chemical Fertilizer in China," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 100(2), pages 502-520.
    13. B. L. Gardner & G. C. Rausser (ed.), 2001. "Handbook of Agricultural Economics," Handbook of Agricultural Economics, Elsevier, edition 1, volume 1, number 1.
    14. Elchanan Mossel & Allan Sly & Omer Tamuz, 2015. "Strategic Learning and the Topology of Social Networks," Econometrica, Econometric Society, vol. 83(5), pages 1755-1794, September.
    15. Itai Arieli & Yakov Babichenko & Ron Peretz & H. Peyton Young, 2020. "The Speed of Innovation Diffusion in Social Networks," Econometrica, Econometric Society, vol. 88(2), pages 569-594, March.
    16. Georgina Moreno & David L. Sunding, 2005. "Joint Estimation of Technology Adoption and Land Allocation with Implications for the Design of Conservation Policy," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 87(4), pages 1009-1019.
    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. Qinghai Zhang & Jiabei Wang, 2023. "Spatial Differentiation and Driving Factors of Traditional Villages in Jiangsu Province," Sustainability, MDPI, vol. 15(14), pages 1-15, July.

    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. Mao, Hui & Zhou, Li & Ying, RuiYao & Pan, Dan, 2021. "Time Preferences and green agricultural technology adoption: Field evidence from rice farmers in China," Land Use Policy, Elsevier, vol. 109(C).
    2. Mao, Hui & Quan, Yurong & Fu, Yong & Chen, Shaojian, 2022. "Risk preferences, productive investment and straw return technology adoption by farmers in China," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322087, Agricultural and Applied Economics Association.
    3. Khushbu Mishra & Abdoul G. Sam & Gracious M. Diiro & Mario J. Miranda, 2020. "Gender and the dynamics of technology adoption: Empirical evidence from a household‐level panel data," Agricultural Economics, International Association of Agricultural Economists, vol. 51(6), pages 857-870, November.
    4. Kazushi Takahashi & Rie Muraoka & Keijiro Otsuka, 2020. "Technology adoption, impact, and extension in developing countries’ agriculture: A review of the recent literature," Agricultural Economics, International Association of Agricultural Economists, vol. 51(1), pages 31-45, January.
    5. Wu, Haixia & Ge, Yan & Li, Jianping, 2023. "Uncertainty, time preference and households’ adoption of rooftop photovoltaic technology," Energy, Elsevier, vol. 276(C).
    6. Jia, Xiangping, 2009. "Synergistic Green and White Revolution: Evidence from Kenya and Uganda," 2009 Conference, August 16-22, 2009, Beijing, China 51367, International Association of Agricultural Economists.
    7. Abdul Nafeo Abdulai & Awal Abdul-Rahaman & Gazali Issahaku, 2021. "Adoption and diffusion of conservation agriculture technology in Zambia: the role of social and institutional networks," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 23(4), pages 761-780, October.
    8. Ward, Patrick S. & Bell, Andrew R. & Droppelmann, Klaus & Benton, Tim G., 2018. "Early adoption of conservation agriculture practices: Understanding partial compliance in programs with multiple adoption decisions," Land Use Policy, Elsevier, vol. 70(C), pages 27-37.
    9. Arslan, Aslihan & Belotti, Federico & Lipper, Leslie, 2017. "Smallholder productivity and weather shocks: Adoption and impact of widely promoted agricultural practices in Tanzania," Food Policy, Elsevier, vol. 69(C), pages 68-81.
    10. Charlotte Fabri & Michail Tsagris & Michele Moretti & Steven Van Passel, 2024. "Adaptation to climate change: The irrigation technology mix of Italian farmers," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 46(2), pages 781-802, June.
    11. Kaywana Raeburn & Sonia Laszlo & Jim Warnick, 2023. "Resolving ambiguity as a public good: experimental evidence from Guyana," Theory and Decision, Springer, vol. 95(1), pages 79-107, July.
    12. Jean‐Paul Chavas & Céline Nauges, 2020. "Uncertainty, Learning, and Technology Adoption in Agriculture," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 42(1), pages 42-53, March.
    13. Wu, Haixia & Li, Jianping & Ge, Yan, 2022. "Ambiguity preference, social learning and adoption of soil testing and formula fertilization technology," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    14. Emmanuel Benjamin & Matthias Blum, 2015. "Participation of smallholders in carbon-certified small-scale agroforestry: A lesson from the rural Mount Kenyan region," Economics Working Papers 15-03, Queen's Management School, Queen's University Belfast.
    15. Mao, Hui & Chai, Yujia & Shao, Xiaoxuan & Chang, Xue, 2024. "Digital extension and farmers' adoption of climate adaptation technology: An empirical analysis of China," Land Use Policy, Elsevier, vol. 143(C).
    16. Yongfeng Tan & Apurbo Sarkar & Airin Rahman & Lu Qian & Waqar Hussain Memon & Zharkyn Magzhan, 2021. "Does External Shock Influence Farmer’s Adoption of Modern Irrigation Technology?—A Case of Gansu Province, China," Land, MDPI, vol. 10(8), pages 1-16, August.
    17. Atsede Desta Tegegne & Marianne Penker, 2016. "Determinants of rural out-migration in Ethiopia: Who stays and who goes?," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 35(34), pages 1011-1044.
    18. B Kelsey Jack, "undated". "Market Inefficiencies and the Adoption of Agricultural Technologies in Developing Countries," CID Working Papers 50, Center for International Development at Harvard University.
    19. Sauer, Johannes & Zilberman, David, 2009. "Innovation Behaviour At Farm Level – Selection And Identification," 83rd Annual Conference, March 30 - April 1, 2009, Dublin, Ireland 51073, Agricultural Economics Society.
    20. Ihle, R. & Amikuzuno, J. & von Cramon-Taubadel, S. & Zorya, S., 2010. "Grenzeffekte in der Marktintegration bei Mais in Ostafrika: Einsichten aus einem semi-parametrischen Regressionsmodell," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 45, March.

    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:jsusta:v:15:y:2023:i:4:p:2982-:d:1060162. 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.