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How Does Information Acquisition Ability Affect Farmers’ Green Production Behaviors: Evidence from Chinese Apple Growers

Author

Listed:
  • Zheng Li

    (College of Economics and Management, Northwest A&F University, Yangling 712100, China
    These authors contributed equally to this work.)

  • Disheng Zhang

    (College of Economics and Management, Northwest A&F University, Yangling 712100, China
    These authors contributed equally to this work.)

  • Xiaohuan Yan

    (College of Economics and Management, Northwest A&F University, Yangling 712100, China
    Western Rural Development Research Center, Northwest A&F University, Yangling 712100, China)

Abstract

Green production is crucial in promoting sustainable agricultural practices, ensuring food safety, and protecting the rural ecological environment. Farmers, as the main decision makers of agricultural production, and their green production behaviors (GPBs), directly determine the process of agricultural green development. Based on the survey data of 656 apple growers in Shaanxi and Gansu provinces in 2022, this paper uses a graded response model to measure the information acquisition ability (IAA) of farmers and constructs an ordered Logit model to empirically explore the influence mechanisms of IAA, green benefit cognition (GBC), and new technology learning attitude (NTLA) on farmers’ GPBs. The results show the following: (1) IAA has a significantly positive impact on the adoption of GPBs by farmers, and farmers with a high IAA are more conscious to adopt green production technologies; (2) in the process of IAA affecting farmers’ adoption of GPBs, GBC plays a positive mediating role; (3) NTLAs have a positive moderating effect on the process of GBC affecting farmers’ GPB adoption; (4) there are generational, educational and regional differences in the impact of IAA on farmers’ GPBs. Policy makers should improve rural information facilities, strengthen agricultural technology promotion and training, improve farmers’ IAA and benefit awareness level, and formulate relevant policies to mobilize farmers’ enthusiasm for learning new technologies.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jagris:v:14:y:2024:i:5:p:680-:d:1383930
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    References listed on IDEAS

    as
    1. 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.
    2. Chalmers, R. Philip, 2012. "mirt: A Multidimensional Item Response Theory Package for the R Environment," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i06).
    3. Zhou, Xinyao & Zhang, Yongqiang & Sheng, Zhuping & Manevski, Kiril & Andersen, Mathias N. & Han, Shumin & Li, Huilong & Yang, Yonghui, 2021. "Did water-saving irrigation protect water resources over the past 40 years? A global analysis based on water accounting framework," Agricultural Water Management, Elsevier, vol. 249(C).
    4. Ma, Jun & Gao, Huixian & Cheng, Changgao & Fang, Zhou & Zhou, Qin & Zhou, Haiwei, 2023. "What influences the behavior of farmers' participation in agricultural nonpoint source pollution control?—Evidence from a farmer survey in Huai'an, China," Agricultural Water Management, Elsevier, vol. 281(C).
    5. 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.
    6. 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.
    7. Khataza, Robertson R.B. & Doole, Graeme J. & Kragt, Marit E. & Hailu, Atakelty, 2018. "Information acquisition, learning and the adoption of conservation agriculture in Malawi: A discrete-time duration analysis," Technological Forecasting and Social Change, Elsevier, vol. 132(C), pages 299-307.
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