IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v14y2024i8p1339-d1453995.html
   My bibliography  Save this article

Adoption of Fertilizer-Reduction and Efficiency-Increasing Technologies in China: The Role of Information Acquisition Ability

Author

Listed:
  • Caiyan Yang

    (Business School, Central South University of Forestry and Technology, Changsha 410004, China
    Institute of Green Development of Hunan Province, Changsha 410004, China)

  • Weihong Huang

    (Business School, Central South University of Forestry and Technology, Changsha 410004, China
    Institute of Green Development of Hunan Province, Changsha 410004, China)

  • Yu Xiao

    (College of Economics and Management, Huazhong Agricultural University, Wuhan 430070, China)

  • Zhenhong Qi

    (College of Economics and Management, Huazhong Agricultural University, Wuhan 430070, China)

  • Yan Li

    (Wuhan Agricultural Technology Extension Centre, Wuhan 430012, China)

  • Kun Zhang

    (Business School, Central South University of Forestry and Technology, Changsha 410004, China
    Institute of Green Development of Hunan Province, Changsha 410004, China)

Abstract

Reducing fertilizer use and increasing its efficiency will improve the quality of farmland and resource conservation. These are necessary steps to achieving green development in agriculture. Nevertheless, fertilizer-reduction and efficiency-increasing technologies (FREITs) remain limited. To improve the situation, 538 farmers in Jiangsu and Hubei Provinces were surveyed with the goal of measuring the information acquisition ability (IAA) of farmers using an Item Response Theory (IRT) model. A model of improved technology selection was employed in conjunction with an IV-probit model to examine the impacts of IAA on farmers’ adoption of FREITs. The results showed that 34.76% of the surveyed farmers had adopted FREITs, with 12.45% and 26.02% having adopted Soil Testing and Formula Fertilization Technology (STFFT) and Organic Fertilizer Replacement Technology (OFRT), respectively. Second, farmers who used more information access channels had greater IAA, which significantly improved their adoption of FREITs. Third, participation in technical training and an increased degree of technical understanding increased the probability of farmers adopting FREITs. The results remained robust after accounting for endogeneity and correlation. Consequently, enhancing farmers’ IAA, organizing technical training, and improving technical publicity will promote the adoption of FREITs.

Suggested Citation

  • Caiyan Yang & Weihong Huang & Yu Xiao & Zhenhong Qi & Yan Li & Kun Zhang, 2024. "Adoption of Fertilizer-Reduction and Efficiency-Increasing Technologies in China: The Role of Information Acquisition Ability," Agriculture, MDPI, vol. 14(8), pages 1-18, August.
    • Handle: RePEc:gam:jagris:v:14:y:2024:i:8:p:1339-:d:1453995
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/14/8/1339/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2077-0472/14/8/1339/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Oriana Bandiera & Imran Rasul, 2006. "Social Networks and Technology Adoption in Northern Mozambique," Economic Journal, Royal Economic Society, vol. 116(514), pages 869-902, October.
    2. Yakubu Abdul-Salam & Euan Phimister, 2017. "Efficiency Effects of Access to Information on Small-scale Agriculture: Empirical Evidence from Uganda using Stochastic Frontier and IRT Models," Journal of Agricultural Economics, Wiley Blackwell, vol. 68(2), pages 494-517, June.
    3. Fred D. Davis & Richard P. Bagozzi & Paul R. Warshaw, 1989. "User Acceptance of Computer Technology: A Comparison of Two Theoretical Models," Management Science, INFORMS, vol. 35(8), pages 982-1003, August.
    4. Lori Beaman & Ariel BenYishay & Jeremy Magruder & Ahmed Mushfiq Mobarak, 2021. "Can Network Theory-Based Targeting Increase Technology Adoption?," American Economic Review, American Economic Association, vol. 111(6), pages 1918-1943, June.
    5. Saha Atanu & H. Alan Love & Robert Schwart, 1994. "Adoption of Emerging Technologies Under Output Uncertainty," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 76(4), pages 836-846.
    6. Mengling Tian & Ruifeng Liu & Jian Wang & Jiahao Liang & Yefan Nian & Hengyun Ma, 2023. "Impact of Environmental Values and Information Awareness on the Adoption of Soil Testing and Formula Fertilization Technology by Farmers—A Case Study Considering Social Networks," Agriculture, MDPI, vol. 13(10), pages 1-22, October.
    7. Shoumin Yue & Ying Xue & Jie Lyu & Kangkang Wang, 2023. "The Effect of Information Acquisition Ability on Farmers’ Agricultural Productive Service Behavior: An Empirical Analysis of Corn Farmers in Northeast China," Agriculture, MDPI, vol. 13(3), pages 1-26, February.
    8. Kristina Beethem & Sandra T. Marquart-Pyatt & Jennifer Lai & Tian Guo, 2023. "Navigating the information landscape: public and private information source access by midwest farmers," Agriculture and Human Values, Springer;The Agriculture, Food, & Human Values Society (AFHVS), vol. 40(3), pages 1117-1135, September.
    9. Yazeed Abdul Mumin & Awudu Abdulai & Renan Goetz, 2023. "The role of social networks in the adoption of competing new technologies in Ghana," Journal of Agricultural Economics, Wiley Blackwell, vol. 74(2), pages 510-533, June.
    10. Ding Xiuling & Lu Qian & Li Lipeng & Apurbo Sarkar, 2023. "The Impact of Technical Training on Farmers Adopting Water-Saving Irrigation Technology: An Empirical Evidence from China," Agriculture, MDPI, vol. 13(5), pages 1-20, April.
    11. Feder, Gershon & Just, Richard E & Zilberman, David, 1985. "Adoption of Agricultural Innovations in Developing Countries: A Survey," Economic Development and Cultural Change, University of Chicago Press, vol. 33(2), pages 255-298, January.
    12. Foyuan Kuang & Jiatong Li & Jianjun Jin & Xin Qiu, 2023. "Do Green Production Technologies Improve Household Income? Evidence from Rice Farmers in China," Land, MDPI, vol. 12(10), pages 1-15, September.
    13. Yazeed Abdul Mumin & Awudu Abdulai, 2022. "Social networks, adoption of improved variety and household welfare: evidence from Ghana," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 49(1), pages 1-32.
    14. Just, Richard E. & Zilberman, David, 1988. "The effects of agricultural development policies on income distribution and technological change in agriculture," Journal of Development Economics, Elsevier, vol. 28(2), pages 193-216, March.
    15. Makaiko G. Khonje & Julius Manda & Petros Mkandawire & Adane Hirpa Tufa & Arega D. Alene, 2018. "Adoption and welfare impacts of multiple agricultural technologies: evidence from eastern Zambia," Agricultural Economics, International Association of Agricultural Economists, vol. 49(5), pages 599-609, September.
    16. Weihong Huang & Caiyan Yang & Ke Liu & Rui Min, 2023. "Information Acquisition Ability and Farmers’ Herd Behavior in Rice–Crayfish Coculture System Adoption," Agriculture, MDPI, vol. 13(10), pages 1-15, September.
    17. Makaiko G. Khonje & Christone Nyondo & Lemekezani Chilora & Julius H. Mangisoni & Jacob Ricker‐Gilbert & William J. Burke, 2022. "Exploring adoption effects of subsidies and soil fertility management in Malawi," Journal of Agricultural Economics, Wiley Blackwell, vol. 73(3), pages 874-892, September.
    18. Zhiyun Zhou & Haoling Liao & Hua Li, 2023. "The Symbiotic Mechanism of the Influence of Productive and Transactional Agricultural Social Services on the Use of Soil Testing and Formula Fertilization Technology by Tea Farmers," Agriculture, MDPI, vol. 13(9), pages 1-26, August.
    19. Wozniak, Gregory D, 1993. "Joint Information Acquisition and New Technology Adoption: Late versus Early Adoption," The Review of Economics and Statistics, MIT Press, vol. 75(3), pages 438-445, August.
    20. 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.
    21. David Roodman, 2011. "Fitting fully observed recursive mixed-process models with cmp," Stata Journal, StataCorp LP, vol. 11(2), pages 159-206, June.
    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. Arslan, Cansın & Wollni, Meike & Oduol, Judith & Hughes, Karl, 2022. "Who communicates the information matters for technology adoption," World Development, Elsevier, vol. 158(C).
    2. 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.
    3. Zheng Li & Disheng Zhang & Xiaohuan Yan, 2024. "How Does Information Acquisition Ability Affect Farmers’ Green Production Behaviors: Evidence from Chinese Apple Growers," Agriculture, MDPI, vol. 14(5), pages 1-17, April.
    4. Fisher, Monica & Holden, Stein T. & Katengeza, Samson P., 2017. "Adoption of CA technologies among Followers of Lead Farmers: How Strong is the Influence from Lead Farmers?," CLTS Working Papers 7/17, Norwegian University of Life Sciences, Centre for Land Tenure Studies, revised 21 Oct 2019.
    5. Fafchamps, Marcel & Islam, Asad & Malek, Mohammad Abdul & Pakrashi, Debayan, 2020. "Can referral improve targeting? Evidence from an agricultural training experiment," Journal of Development Economics, Elsevier, vol. 144(C).
    6. 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.
    7. Adane Hirpa Tufa & Arega D. Alene & Julius Manda & Shiferaw Feleke & Tesfamichael Wossen & M. G. Akinwale & David Chikoye & Victor Manyong, 2021. "The poverty impacts of improved soybean technologies in Malawi," Agrekon, Taylor & Francis Journals, vol. 60(3), pages 297-316, July.
    8. Yoko Kijima, 2022. "Long-term and spillover effects of rice production training in Uganda," Journal of Development Effectiveness, Taylor & Francis Journals, vol. 14(4), pages 395-415, October.
    9. Islam, Asadul & Ushchev, Philip & Zenou, Yves & Zhang, Xin, 2019. "The Value of Information in Technology Adoption," IZA Discussion Papers 12672, Institute of Labor Economics (IZA).
    10. Weihong Huang & Caiyan Yang & Ke Liu & Rui Min, 2023. "Information Acquisition Ability and Farmers’ Herd Behavior in Rice–Crayfish Coculture System Adoption," Agriculture, MDPI, vol. 13(10), pages 1-15, September.
    11. 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.
    12. Bahinipati, Chandra Sekhar & Viswanathan, P.K., 2019. "Incentivizing resource efficient technologies in India: Evidence from diffusion of micro-irrigation in the dark zone regions of Gujarat," Land Use Policy, Elsevier, vol. 86(C), pages 253-260.
    13. Mamadou Sissoko & Melinda Smale & Annick Castiaux & Veronique Theriault, 2019. "Adoption of New Sorghum Varieties in Mali Through a Participatory Approach," Sustainability, MDPI, vol. 11(17), pages 1-15, September.
    14. Sadick Mohammed & Awudu Abdulai, 2022. "Do Egocentric information networks influence technical efficiency of farmers? Empirical evidence from Ghana," Journal of Productivity Analysis, Springer, vol. 58(2), pages 109-128, December.
    15. Pronti, Andrea & Auci, Sabrina & Berbel, Julio, 2024. "Water conservation and saving technologies for irrigation. A structured literature review of econometric studies on the determinants of adoption," Agricultural Water Management, Elsevier, vol. 299(C).
    16. Zhang, Biao & Fu, Zetian & Wang, Jieqiong & Zhang, Lingxian, 2019. "Farmers’ adoption of water-saving irrigation technology alleviates water scarcity in metropolis suburbs: A case study of Beijing, China," Agricultural Water Management, Elsevier, vol. 212(C), pages 349-357.
    17. Simtowe, Franklin & Kassie, Menale & Diagne, Aliou & Asfaw, Solomon & Shiferaw, Bekele & Silim, Said & Muange, Elijah, 2011. "Determinants of Agricultural Technology Adoption: The Case of Improved Pigeonpea Varieties in Tanzania," Quarterly Journal of International Agriculture, Humboldt-Universitaat zu Berlin, vol. 50(4), pages 1-21.
    18. Wuepper, David & Sauer, Johannes & Kleemann, Linda, 2014. "Sustainable intensification of pineapple farming in Ghana: Training and complexity," Kiel Working Papers 1973, Kiel Institute for the World Economy (IfW Kiel).
    19. 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.
    20. Tisorn Songsermsawas & Kathy Baylis & Ashwini Chhatre & Hope Michelson, 2014. "Can Peers Improve Agricultural Productivity?," CESifo Working Paper Series 4958, CESifo.

    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:14:y:2024:i:8:p:1339-:d:1453995. 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.