IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v12y2023i6p1215-d1168886.html
   My bibliography  Save this article

Influence of Agricultural Technology Extension and Social Networks on Chinese Farmers’ Adoption of Conservation Tillage Technology

Author

Listed:
  • Jiabin Xu

    (College of Economics and Management, Northeast Agricultural University, Harbin 150030, China
    These authors contributed equally to this work and should be considered co-first authors.)

  • Zhaoda Cui

    (School of Economics, Shandong University of Technology, Zibo 255000, China
    These authors contributed equally to this work and should be considered co-first authors.)

  • Tianyi Wang

    (College of Economics and Management, Northeast Agricultural University, Harbin 150030, China)

  • Jingjing Wang

    (College of Economics and Management, Northeast Agricultural University, Harbin 150030, China)

  • Zhigang Yu

    (College of Economics and Management, Northeast Agricultural University, Harbin 150030, China)

  • Cuixia Li

    (College of Economics and Management, Northeast Agricultural University, Harbin 150030, China)

Abstract

Agricultural technology extension and social networks are the essential components of formal and informal institutions, respectively, and their influence on agricultural production has been the focus of academics. This article takes conservation tillage technology as an example, based on simple random unduplicated sampling, and uses survey data of 781 farmers in Heilongjiang, Henan, Shandong, and Shanxi provinces of China. This article empirically tests the interaction effects and heterogeneity of agricultural technology extension and social networks on farmers’ adoption of conservation tillage technology and analyzes their substitution effect or complementary effect. The results showed the following: (1) From a single dimension, both agricultural technology extension and social networks can significantly promote farmers’ adoption of conservation tillage technology, and the promotion effect of agricultural technology extension is greater. The average probability of farmers who accept agricultural technology extension and social networks adopting conservation tillage technology increases by 36.49% and 7.09%, respectively. (2) There is a complementary effect between agricultural technology extension and social networks in promoting farmers’ adoption of conservation tillage technology. The two functions complement and support each other, and this complementary effect is more evident in social networks’ reciprocity. (3) Further analysis reveals that the interaction effect between agricultural technology extension and social networks has significant group differences, technology type differences, and regional differences in farmers’ adoption of conservation tillage technology. Therefore, to facilitate the extension and application of conservation tillage technology, efforts need to be made in both agricultural technology extension and social networks, fully leveraging the complementary effects of the two. In addition, differentiated policies and measures should be adopted according to local conditions, and precise policies should be implemented for different groups and technologies.

Suggested Citation

  • Jiabin Xu & Zhaoda Cui & Tianyi Wang & Jingjing Wang & Zhigang Yu & Cuixia Li, 2023. "Influence of Agricultural Technology Extension and Social Networks on Chinese Farmers’ Adoption of Conservation Tillage Technology," Land, MDPI, vol. 12(6), pages 1-23, June.
    • Handle: RePEc:gam:jlands:v:12:y:2023:i:6:p:1215-:d:1168886
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/12/6/1215/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-445X/12/6/1215/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Patrick S. Ward & Valerien O. Pede, 2015. "Capturing social network effects in technology adoption: the spatial diffusion of hybrid rice in Bangladesh," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 59(2), pages 225-241, April.
    2. Hongpeng Guo & Wenkai Zhao & Chulin Pan & Guijie Qiu & Shuang Xu & Shun Liu, 2022. "Study on the Influencing Factors of Farmers’ Adoption of Conservation Tillage Technology in Black Soil Region in China: A Logistic-ISM Model Approach," IJERPH, MDPI, vol. 19(13), pages 1-16, June.
    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. Hausmann, Ricardo & Rodrik, Dani, 2003. "Economic development as self-discovery," Journal of Development Economics, Elsevier, vol. 72(2), pages 603-633, December.
    5. Brian W. Gould & William E. Saupe & Richard M. Klemme, 1989. "Conservation Tillage: The Role of Farm and Operator Characteristics and the Perception of Soil Erosion," Land Economics, University of Wisconsin Press, vol. 65(2), pages 167-185.
    6. Lan Anh Hoang & Jean-Christophe Castella & Paul Novosad, 2006. "Social networks and information access: Implications for agricultural extension in a rice farming community in northern Vietnam," Agriculture and Human Values, Springer;The Agriculture, Food, & Human Values Society (AFHVS), vol. 23(4), pages 513-527, December.
    7. Timothy G. Conley & Christopher R. Udry, 2010. "Learning about a New Technology: Pineapple in Ghana," American Economic Review, American Economic Association, vol. 100(1), pages 35-69, March.
    8. Munshi, Kaivan, 2004. "Social learning in a heterogeneous population: technology diffusion in the Indian Green Revolution," Journal of Development Economics, Elsevier, vol. 73(1), pages 185-213, February.
    9. Haibo Ruan & Jun Chen & Chao Wang & Wendong Xu & Jiayi Tang, 2022. "Social Network, Sense of Responsibility, and Resident Participation in China’s Rural Environmental Governance," IJERPH, MDPI, vol. 19(11), pages 1-23, May.
    10. George W. Norton & Jeffrey Alwang, 2020. "Changes in Agricultural Extension and Implications for Farmer Adoption of New Practices," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 42(1), pages 8-20, March.
    11. Baozhi Li & Ni Zhuo & Chen Ji & Qibiao Zhu, 2022. "Influence of Smartphone-Based Digital Extension Service on Farmers’ Sustainable Agricultural Technology Adoption in China," IJERPH, MDPI, vol. 19(15), pages 1-14, August.
    12. Nawab Khan & Ram L. Ray & Hazem S. Kassem & Farhat Ullah Khan & Muhammad Ihtisham & Shemei Zhang, 2022. "Does the Adoption of Mobile Internet Technology Promote Wheat Productivity? Evidence from Rural Farmers," Sustainability, MDPI, vol. 14(13), pages 1-15, June.
    13. Anat Barnir & Ken A. Smith, 2002. "Interfirm Alliances in the Small Business: The Role of Social Networks," Journal of Small Business Management, Taylor & Francis Journals, vol. 40(3), pages 219-232, July.
    14. Tripp, Robert & Wijeratne, Mahinda & Piyadasa, V. Hiroshini, 2005. "What should we expect from farmer field schools? A Sri Lanka case study," World Development, Elsevier, vol. 33(10), pages 1705-1720, October.
    15. Isabel Lambrecht & Bernard Vanlauwe & Miet Maertens, 2016. "Agricultural extension in Eastern Democratic Republic of Congo: does gender matter?," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 43(5), pages 841-874.
    16. Hongbin Liu & Mengyao Wu & Xinhua Liu & Jiaju Gao & Xiaojuan Luo & Yan Wu, 2021. "Simulation of Policy Tools’ Effects on Farmers’ Adoption of Conservation Tillage Technology: An Empirical Analysis in China," Land, MDPI, vol. 10(10), pages 1-23, October.
    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. Xinran Hu & Bin Xiao & Zhihui Tong, 2024. "Technological Integration and Obstacles in China’s Agricultural Extension Systems: A Study on Disembeddedness and Adaptation," Sustainability, MDPI, vol. 16(2), pages 1-20, January.
    2. Yang Guo & Meiling Cui & Zhigang Xu, 2023. "Spatial Characteristics of Transfer Plots and Conservation Tillage Technology Adoption: Evidence from a Survey of Four Provinces in China," Agriculture, MDPI, vol. 13(8), pages 1-15, August.
    3. Yihan Chen & Wen Xiang & Minjuan Zhao, 2024. "Impacts of Capital Endowment on Farmers’ Choices in Fertilizer-Reduction and Efficiency-Increasing Technologies (Preferences, Influences, and Mechanisms): A Case Study of Apple Farmers in the Province," Agriculture, MDPI, vol. 14(1), pages 1-25, January.
    4. Zhiwu Yang & Jinling Bu & Jiahan Qi & Qing Liu & Yan Song, 2024. "Does Land Approval Facilitate Conservation Tillage? An Examination through the Lens of Straw-Returning Technology," Land, MDPI, vol. 13(5), pages 1-18, April.
    5. Daisong Yu & Xiao Hai & Zixuan Wang & Haipeng Chen, 2024. "Abatement Effects of Agricultural Non-Point Pollution from Land System Reforms: A Case Study of the Farmland “Three Rights Separation” Reform in China," Agriculture, MDPI, vol. 14(6), pages 1-19, June.

    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. Li, Qi & Li, Kai, 2021. "Re-examining the Effect of Social Embeddedness on Technology Diffusion from the Perspective of Scale Differentiation— A Case Study from China," 2021 ASAE 10th International Conference (Virtual), January 11-13, Beijing, China 329394, Asian Society of Agricultural Economists (ASAE).
    2. Nakano, Yuko & Tsusaka, Takuji W. & Aida, Takeshi & Pede, Valerien O., 2015. "The Impact of Training on Technology Adoption and Productivity of Rice Farming in Tanzania: Is Farmer-to-Farmer Extension Effective?," Working Papers 90, JICA Research Institute.
    3. Nakano, Yuko & Tsusaka, Takuji W. & Aida, Takeshi & Pede, Valerien O., 2018. "Is farmer-to-farmer extension effective? The impact of training on technology adoption and rice farming productivity in Tanzania," World Development, Elsevier, vol. 105(C), pages 336-351.
    4. Elisabeth SADOULET, 2016. "Review of Theories of Learning for Adopting," Working Papers P163, FERDI.
    5. Sriroop Chaudhuri & Mimi Roy & Louis M. McDonald & Yves Emendack, 2021. "Reflections on farmers’ social networks: a means for sustainable agricultural development?," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(3), pages 2973-3008, March.
    6. Mekonnen, Dawit K. & Dorfman, Jeffrey H., 2017. "Synergy and Learning Effects of Informal Labor-Sharing Arrangements," World Development, Elsevier, vol. 99(C), pages 1-14.
    7. Johannes Binswanger & Manuel Oechslin, 2015. "Disagreement and Learning about Reforms," Economic Journal, Royal Economic Society, vol. 0(584), pages 853-886, May.
    8. Kazushi Takahashi & Yukichi Mano & Keijiro Otsuka, 2018. "Spillovers as a Driver to Reduce Ex-post Inequality Generated by Randomized Experiments: Evidence from an Agricultural Training Intervention," Working Papers 174, JICA Research Institute.
    9. Yanbing Wang & Niklas Möhring & Robert Finger, 2023. "When my neighbors matter: Spillover effects in the adoption of large‐scale pesticide‐free wheat production," Agricultural Economics, International Association of Agricultural Economists, vol. 54(2), pages 256-273, March.
    10. Saule Burkitbayeva & Emma Janssen & Johan Swinnen, 2020. "Technology Adoption, Vertical Coordination in Value Chains, and FDI in Developing Countries: Panel Evidence from the Dairy Sector in India (Punjab)," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 57(2), pages 433-479, September.
    11. repec:lic:licosd:41019 is not listed on IDEAS
    12. Faruque-As-Sunny & Zuhui Huang & Taonarufaro Tinaye Pemberai Karimanzira, 2018. "Investigating Key Factors Influencing Farming Decisions Based on Soil Testing and Fertilizer Recommendation Facilities (STFRF)—A Case Study on Rural Bangladesh," Sustainability, MDPI, vol. 10(11), pages 1-24, November.
    13. 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.
    14. Janssen, Emma & Swinnen, Johan, 2019. "Technology adoption and value chains in developing countries: Evidence from dairy in India," Food Policy, Elsevier, vol. 83(C), pages 327-336.
    15. Burkitbayeva, Saule & Janssen, Emma & Swinnen, Johan, 2021. "Regulations, Value Chains and Food Standards in Developing Countries: Panel Data Evidence from India," International Journal on Food System Dynamics, International Center for Management, Communication, and Research, vol. 12(04), December.
    16. Takahashi, Kazushi & Mano, Yukichi & Otsuka, Keijiro, 2019. "Learning from experts and peer farmers about rice production: Experimental evidence from Cote d’Ivoire," World Development, Elsevier, vol. 122(C), pages 157-169.
    17. Vaiknoras, Kate A. & Larochelle, Catherine & Birol, Ekin & Asare-Marfo, Dorene & Herrington, Caitlin, 2017. "The Roles of Formal and Informal Delivery Approaches in Achieving Fast and Sustained Adoption of Biofortified Crops: Learnings from the Iron Bean Delivery Approaches in Rwanda," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258288, Agricultural and Applied Economics Association.
    18. 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.
    19. Mary Thuo & Alexandra Bell & Boris Bravo-Ureta & Michée Lachaud & David Okello & Evelyn Okoko & Nelson Kidula & Carl Deom & Naveen Puppala, 2014. "Effects of social network factors on information acquisition and adoption of improved groundnut varieties: the case of Uganda and Kenya," Agriculture and Human Values, Springer;The Agriculture, Food, & Human Values Society (AFHVS), vol. 31(3), pages 339-353, September.
    20. Li, Kai & Li, Qi, 2022. "Social embeddedness and agricultural technology diffusion from the perspective of scale differentiation – a case study from China," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 26(1), August.
    21. 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.

    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:jlands:v:12:y:2023:i:6:p:1215-:d:1168886. 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.