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Exploring the Role of Agricultural Services in Production Efficiency in Chinese Agriculture: A Case of the Socialized Agricultural Service System

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  • Tao Chen

    (School of Economics and Management, Yangtze University, Jingzhou 434023, China
    Changjiang Economics Belt Research and Development Institute, Yangtze University, Jingzhou 434023, China)

  • Muhammad Rizwan

    (School of Economics and Management, Yangtze University, Jingzhou 434023, China
    Changjiang Economics Belt Research and Development Institute, Yangtze University, Jingzhou 434023, China)

  • Azhar Abbas

    (Institute of Agricultural and Resource Economics, University of Agriculture, Faisalabad 38040, Pakistan)

Abstract

In recent decades, the Chinese government launched a socialized agricultural service system to help smallholders quickly modernize. This system helps farmers adopt modern-day farming operations to meet ever-increasing food and fiber requirements. The present study was conducted to analyze the impacts of this system on agricultural production efficiency. To this end, the Hubei province of China was selected, and the required data were retrieved from the Hubei Statistical Yearbook and Rural Statistical Yearbook for the years 2008 to 2019. The entropy method was applied to measure the extent of the adoption of socialized and individual agricultural services, while a data envelopment analysis (DEA) was used for measuring production efficiency. Grey correlation and regression analyses were carried out to analyze the association between production efficiency and agricultural service availability/uptake and the determinants of the former, respectively. The results illustrate that the agricultural socialized service level has increased. Specifically, the service levels of agricultural mechanization and financial insurance increased most rapidly in terms of individual services with the largest numbers of adopters. Science and technology and material services were found to exhibit the most significant relationships with the production efficiency of farmers. The results indicate a greater role of service provision in moderate-to-high-scale development, leading to land productivity and thereby improving agricultural production efficiency. The results also imply a higher demand for socialized agricultural services among farmers considering the value-added potential of such an integrated system with greater spillover options for achieving self-sufficiency in agriculture and ensuring food security.

Suggested Citation

  • Tao Chen & Muhammad Rizwan & Azhar Abbas, 2022. "Exploring the Role of Agricultural Services in Production Efficiency in Chinese Agriculture: A Case of the Socialized Agricultural Service System," Land, MDPI, vol. 11(3), pages 1-18, February.
  • Handle: RePEc:gam:jlands:v:11:y:2022:i:3:p:347-:d:759500
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    as
    1. Jialing Yu & Jian Wu, 2018. "The Sustainability of Agricultural Development in China: The Agriculture–Environment Nexus," Sustainability, MDPI, vol. 10(6), pages 1-17, May.
    2. Hazell, Peter & Poulton, Colin & Wiggins, Steve & Dorward, Andrew, 2010. "The Future of Small Farms: Trajectories and Policy Priorities," World Development, Elsevier, vol. 38(10), pages 1349-1361, October.
    3. Li, Nan & Jiang, Yuqing & Mu, Hailin & Yu, Zhixin, 2018. "Efficiency evaluation and improvement potential for the Chinese agricultural sector at the provincial level based on data envelopment analysis (DEA)," Energy, Elsevier, vol. 164(C), pages 1145-1160.
    4. Belton, Ben & Win, Myat Thida & Zhang, Xiaobo & Filipski, Mateusz, 2021. "The rapid rise of agricultural mechanization in Myanmar," Food Policy, Elsevier, vol. 101(C).
    5. Christopher Saina & Florence Murgor & Daniel Kipkosgei Murgor, 2013. "Climate Change and Food Security," Chapters, in: Steven Silvern & Stephen Young (ed.), Environmental Change and Sustainability, IntechOpen.
    6. Tongwei Qiu & Biliang Luo, 2021. "Do small farms prefer agricultural mechanization services? Evidence from wheat production in China," Applied Economics, Taylor & Francis Journals, vol. 53(26), pages 2962-2973, June.
    7. Paudel, Gokul P. & KC, Dilli Bahadur & Rahut, Dil Bahadur & Khanal, Narayan P. & Justice, Scott E. & McDonald, Andrew J., 2019. "Smallholder farmers' willingness to pay for scale-appropriate farm mechanization: Evidence from the mid-hills of Nepal," Technology in Society, Elsevier, vol. 59(C).
    8. Xiaoshi Zhou & Wanglin Ma & Gucheng Li & Huanguang Qiu, 2020. "Farm machinery use and maize yields in China: an analysis accounting for selection bias and heterogeneity," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 64(4), pages 1282-1307, October.
    9. Liu, Yansui, 2018. "Introduction to land use and rural sustainability in China," Land Use Policy, Elsevier, vol. 74(C), pages 1-4.
    10. Qianqian Chen & Ruifa Hu & Yiduo Sun & Chao Zhang, 2020. "How Does Rural–Urban Migration Experience Affect Arable Land Use? Evidence from 2293 Farmers in China," Land, MDPI, vol. 9(11), pages 1-17, October.
    11. Liang, Liang & Wu, Jie & Cook, Wade D. & Zhu, Joe, 2008. "Alternative secondary goals in DEA cross-efficiency evaluation," International Journal of Production Economics, Elsevier, vol. 113(2), pages 1025-1030, June.
    12. Qian, Long & Lu, Hua & Gao, Qiang & Lu, Hualiang, 2022. "Household-owned farm machinery vs. outsourced machinery services: The impact of agricultural mechanization on the land leasing behavior of relatively large-scale farmers in China," Land Use Policy, Elsevier, vol. 115(C).
    13. Yunju, Li & Kahrl, Fredrich & Jianjun, Pan & Roland-Holst, David & Yufang, Su & Wilkes, Andreas & Jianchu, Xu, 2012. "Fertilizer use patterns in Yunnan Province, China: Implications for agricultural and environmental policy," Agricultural Systems, Elsevier, vol. 110(C), pages 78-89.
    14. Fei, Rilong & Lin, Ziyi & Chunga, Joseph, 2021. "How land transfer affects agricultural land use efficiency: Evidence from China’s agricultural sector," Land Use Policy, Elsevier, vol. 103(C).
    15. Muhammad Rizwan & Ping Qing & Abdul Saboor & Muhammad Amjed Iqbal & Adnan Nazir, 2020. "Production Risk and Competency among Categorized Rice Peasants: Cross-Sectional Evidence from an Emerging Country," Sustainability, MDPI, vol. 12(9), pages 1-15, May.
    16. Dehua Zhang & Haiqing Wang & Sha Lou & Shen Zhong, 2021. "Research on grain production efficiency in China’s main grain producing areas from the perspective of financial support," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-16, March.
    17. Qiang Hou & Meiou Wang & Xue Zhou, 2018. "Improved DEA Cross Efficiency Evaluation Method Based on Ideal and Anti-Ideal Points," Discrete Dynamics in Nature and Society, Hindawi, vol. 2018, pages 1-9, April.
    18. Grundy, Michael J. & Bryan, Brett A. & Nolan, Martin & Battaglia, Michael & Hatfield-Dodds, Steve & Connor, Jeffery D. & Keating, Brian A., 2016. "Scenarios for Australian agricultural production and land use to 2050," Agricultural Systems, Elsevier, vol. 142(C), pages 70-83.
    19. D K Despotis, 2002. "Improving the discriminating power of DEA: focus on globally efficient units," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(3), pages 314-323, March.
    20. Sungmook Lim & Joe Zhu, 2015. "DEA Cross Efficiency Under Variable Returns to Scale," International Series in Operations Research & Management Science, in: Joe Zhu (ed.), Data Envelopment Analysis, edition 127, chapter 3, pages 45-66, Springer.
    21. Li, Zongzhang & Liu, Xiaomin, 2009. "The Effects of Rural Infrastructure Development on Agricultural Production Technical Efficiency: Evidence from the Data of Second National Agricultural Census of China," 2009 Conference, August 16-22, 2009, Beijing, China 51028, International Association of Agricultural Economists.
    22. Dolgonosov, Boris M., 2016. "Knowledge production and world population dynamics," Technological Forecasting and Social Change, Elsevier, vol. 103(C), pages 127-141.
    23. Sungmook Lim & Joe Zhu, 2015. "DEA cross-efficiency evaluation under variable returns to scale," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 66(3), pages 476-487, March.
    24. Liang Liang & Jie Wu & Wade D. Cook & Joe Zhu, 2008. "The DEA Game Cross-Efficiency Model and Its Nash Equilibrium," Operations Research, INFORMS, vol. 56(5), pages 1278-1288, October.
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