IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v13y2022i1p51-d1013445.html
   My bibliography  Save this article

A Study on the Utilization Rate and Influencing Factors of Small Agricultural Machinery: Evidence from 10 Hilly and Mountainous Provinces in China

Author

Listed:
  • Hongbo Li

    (School of Management, Jiangsu University, Zhenjiang 212013, China)

  • Lewei Chen

    (School of Management, Jiangsu University, Zhenjiang 212013, China)

  • Zongyi Zhang

    (China Institute for Agricultural Equipment Industry Development, Jiangsu University, Zhenjiang 212013, China)

Abstract

Hilly and mountainous areas are weak places for the development of agricultural mechanization in China. The way to improve the utilization rate of small agricultural machinery widely used in hilly and mountainous areas is of positive significance for optimizing resource allocation efficiency of agricultural production and ensuring food security supply. Taking microtillers as a representative tool, this study systematically analyzed the main factors affecting the utilization rate of small agricultural machines and its influencing mechanism. Then, based on the survey data of 4905 farmers in 100 counties in 10 hilly and mountainous provinces of China, empirical analysis was carried out by some econometric models, such as censored regression and the mediating effect model. Results show the following.: (1) Among farmers in hilly and mountainous areas, the average use time of each microtiller is 218.41 h per year. (2) Age, social identity, terrain conditions, crop types, land area, the number of microtillers, the number of large tractors, and the machinery purchase subsidy policy are the significant factors affecting the utilization rate of microtillers. (3) The increase of cultivated land area not only directly improves the utilization rate of microtillers, but also indirectly improves the utilization rate of microtillers due to the increase in quantity.

Suggested Citation

  • Hongbo Li & Lewei Chen & Zongyi Zhang, 2022. "A Study on the Utilization Rate and Influencing Factors of Small Agricultural Machinery: Evidence from 10 Hilly and Mountainous Provinces in China," Agriculture, MDPI, vol. 13(1), pages 1-25, December.
    • Handle: RePEc:gam:jagris:v:13:y:2022:i:1:p:51-:d:1013445
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/13/1/51/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2077-0472/13/1/51/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yuan Liu & Long Shao & Wanzhang Wang & Jinfan Chen & Heng Zhang & Yue Yang & Baichen Hu, 2022. "Study on Fugitive Dust Control Technologies of Agricultural Harvesting Machinery," Agriculture, MDPI, vol. 12(7), pages 1-22, July.
    2. Hongyun Zheng & Wanglin Ma & Xiaoshi Zhou, 2021. "Renting-in cropland, machinery use intensity, and land productivity in rural China," Applied Economics, Taylor & Francis Journals, vol. 53(47), pages 5503-5517, October.
    3. Zheng, Hongyun & Ma, Wanglin & Zhou, Xiaoshi, 2021. "Effects of Renting-in Cropland on Machinery Use Intensity and Land Productivity: Evidence from Rural China," 2021 Conference, August 17-31, 2021, Virtual 315084, International Association of Agricultural Economists.
    4. Jean‐Paul Chavas & Giorgia Rivieccio & Salvatore Di Falco & Giovanni De Luca & Fabian Capitanio, 2022. "Agricultural diversification, productivity, and food security across time and space," Agricultural Economics, International Association of Agricultural Economists, vol. 53(S1), pages 41-58, November.
    5. Fischer, Sabine & Wollni, Meike, 2018. "The role of farmers’ trust, risk and time preferences for contract choices: Experimental evidence from the Ghanaian pineapple sector," Food Policy, Elsevier, vol. 81(C), pages 67-81.
    6. Powell, James L., 1984. "Least absolute deviations estimation for the censored regression model," Journal of Econometrics, Elsevier, vol. 25(3), pages 303-325, July.
    7. Hong, Yu & Heerink, Nico & van der Werf, Wopke, 2020. "Farm size and smallholders’ use of intercropping in Northwest China," Land Use Policy, Elsevier, vol. 99(C).
    8. Hironori Yagi & Tsuneo Hayashi, 2021. "Machinery utilization and management organization in Japanese rice farms: Comparison of single‐family, multifamily, and community farms," Agribusiness, John Wiley & Sons, Ltd., vol. 37(2), pages 393-408, April.
    9. Yuewen Huo & Songlin Ye & Zhou Wu & Fusuo Zhang & Guohua Mi, 2022. "Barriers to the Development of Agricultural Mechanization in the North and Northeast China Plains: A Farmer Survey," Agriculture, MDPI, vol. 12(2), pages 1-14, February.
    10. Xiuhao Quan & Reiner Doluschitz, 2021. "Factors Influencing the Adoption of Agricultural Machinery by Chinese Maize Farmers," Agriculture, MDPI, vol. 11(11), pages 1-11, November.
    11. Meng Qu & Kai Zhao & Renhui Zhang & Yuan Gao & Jing Wang, 2022. "Divergence between Willingness and Behavior of Farmers to Purchase Socialized Agricultural Services: From a Heterogeneity Perspective of Land Scale," Land, MDPI, vol. 11(8), pages 1-21, July.
    12. Karin Larsén, 2010. "Effects of machinery‐sharing arrangements on farm efficiency: evidence from Sweden," Agricultural Economics, International Association of Agricultural Economists, vol. 41(5), pages 497-506, September.
    13. Xi Yu & Xiyang Yin & Yuying Liu & Dongmei Li, 2021. "Do Agricultural Machinery Services Facilitate Land Transfer? Evidence from Rice Farmers in Sichuan Province, China," Land, MDPI, vol. 10(5), pages 1-14, April.
    14. Richard H. Thaler, 2016. "Behavioral Economics: Past, Present, and Future," American Economic Review, American Economic Association, vol. 106(7), pages 1577-1600, July.
    15. Skeels, Christopher L. & Vella, Francis, 1999. "A Monte Carlo investigation of the sampling behavior of conditional moment tests in Tobit and Probit models," Journal of Econometrics, Elsevier, vol. 92(2), pages 275-294, October.
    16. Alessia Cogato & Andrea Pezzuolo & Claus Grøn Sørensen & Roberta De Bei & Marco Sozzi & Francesco Marinello, 2020. "A GIS-Based Multicriteria Index to Evaluate the Mechanisability Potential of Italian Vineyard Area," Land, MDPI, vol. 9(11), pages 1-17, November.
    17. Bryon J. Parman & Allen M. Featherstone & Brian K. Coffey, 2017. "Estimating product-specific and multiproduct economies of scale with data envelopment analysis," Agricultural Economics, International Association of Agricultural Economists, vol. 48(4), pages 523-533, July.
    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. Lewei Chen & Zongyi Zhang & Hongbo Li & Xinpu Zhang, 2023. "Maintenance Skill Training Gives Agricultural Socialized Service Providers More Advantages," Agriculture, MDPI, vol. 13(1), pages 1-17, January.
    2. Yangxiao Lu & Suhao Wei, 2024. "Outsourcing of Agricultural Machinery Operation Services and the Sustainability of Farmland Transfer Market: Promoting or Inhibiting?," Sustainability, MDPI, vol. 16(22), pages 1-19, November.
    3. Andrés Langebaek R. & Diego Vásquez E., 2007. "Determinantes de la actividad innovadora en la industria manufacturera colombiana," Borradores de Economia 433, Banco de la Republica de Colombia.
    4. Simons, Andrew M., 2022. "What is the optimal locus of control for social assistance programs? Evidence from the Productive Safety Net Program in Ethiopia," Journal of Development Economics, Elsevier, vol. 158(C).
    5. Mark Ottoni Wilhelm, 2008. "Practical Considerations for Choosing Between Tobit and SCLS or CLAD Estimators for Censored Regression Models with an Application to Charitable Giving," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(4), pages 559-582, August.
    6. Junpeng Li & Puneet Vatsa & Wanglin Ma, 2024. "Flush toilet use and its impact on health and non‐health expenditures," Journal of International Development, John Wiley & Sons, Ltd., vol. 36(4), pages 2022-2046, May.
    7. Wanglin Ma & Huanguang Qiu & Dil Bahadur Rahut, 2023. "Rural development in the digital age: Does information and communication technology adoption contribute to credit access and income growth in rural China?," Review of Development Economics, Wiley Blackwell, vol. 27(3), pages 1421-1444, August.
    8. Daniel Pollmann & Thomas Dohmen & Franz Palm, 2020. "Robust Estimation of Wage Dispersion with Censored Data: An Application to Occupational Earnings Risk and Risk Attitudes," De Economist, Springer, vol. 168(4), pages 519-540, December.
    9. Martinson Ankrah Twumasi & Bright Senyo Dogbe & Ernest Kwarko Ankrah & Zhao Ding & Yuansheng Jiang, 2023. "Assessing Financial Literacy and Farmland Abandonment Relationship in Ghana," Agriculture, MDPI, vol. 13(3), pages 1-18, February.
    10. Huaquan Zhang & Zhenyao Yang & Yidan Wang & Martinson Ankrah Twumasi & Abbas Ali Chandio, 2023. "Impact of Agricultural Mechanization Level on Farmers’ Health Status in Western China: Analysis Based on CHARLS Data," IJERPH, MDPI, vol. 20(5), pages 1-20, March.
    11. Ma, Wanglin & Vatsa, Puneet & Zheng, Hongyun & Rahut, Dil Bahadur, 2022. "Nonfarm employment and consumption diversification in rural China," Economic Analysis and Policy, Elsevier, vol. 76(C), pages 582-598.
    12. Daniel Pollmann & Thomas Dohmen & Franz Palm, 2020. "Dispersion estimation; Earnings risk; Censoring; Quantile regression; Occupational choice; Sorting; Risk preferences; SOEP; IABS," ECONtribute Discussion Papers Series 028, University of Bonn and University of Cologne, Germany.
    13. Darryl Holden, 2011. "Testing for heteroskedasticity in the tobit and probit models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(4), pages 735-744, November.
    14. Adane Tufa & Arega Alene & Hambulo Ngoma & Paswel Marenya & Julius Manda & Md Abdul Matin & Christian Thierfelder & David Chikoye, 2024. "Willingness to pay for agricultural mechanization services by smallholder farmers in Malawi," Agribusiness, John Wiley & Sons, Ltd., vol. 40(1), pages 248-276, January.
    15. Liu, Yan & Heerink, Nico & Li, Fan & Shi, Xiaoping, 2022. "Do agricultural machinery services promote village farmland rental markets? Theory and evidence from a case study in the North China plain," Land Use Policy, Elsevier, vol. 122(C).
    16. Pradhan, Jaya Prakash, 2010. "R&D strategy of small and medium enterprises in India: Trends and determinants," MPRA Paper 20951, University Library of Munich, Germany.
    17. Yang, Wei & Vatsa, Puneet & Ma, Wanglin & Zheng, Hongyun, 2023. "Does mobile payment adoption really increase online shopping expenditure in China: A gender-differential analysis," Economic Analysis and Policy, Elsevier, vol. 77(C), pages 99-110.
    18. Hyowon Kim & Dong Soo Kim & Greg M. Allenby, 2020. "Benefit Formation and Enhancement," Quantitative Marketing and Economics (QME), Springer, vol. 18(4), pages 419-468, December.
    19. Héctor Manuel Zárate S., 2005. "Cambios en la estructura salarial: una historia desde la regresión cuanfílica," Monetaria, CEMLA, vol. 0(4), pages 339-364, octubre-d.
    20. Peracchi, Franco, 2002. "On estimating conditional quantiles and distribution functions," Computational Statistics & Data Analysis, Elsevier, vol. 38(4), pages 433-447, February.

    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:13:y:2022:i:1:p:51-:d:1013445. 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.