Academic Journal of Business & Management, 2025, 7(12); doi: 10.25236/AJBM.2025.071218.
Ziyang Liu, Qing Xia, Yuanru Xue, Huan Liang, Chaojun Mao, Mengdie Zhang
School of Economics, Guangzhou City University of Technology, Guangzhou, China
With the acceleration of agricultural modernization and rural revitalization, the production dilemma of smallholders has become increasingly prominent. As an innovative application of the sharing economy in the agricultural field, the intelligent agricultural machinery sharing model has become an important way to reduce the production costs of smallholders and improve the level of mechanization. Taking Houshan Village Cooperative in Baihe Town, Kaiping City, Guangdong Province as a typical case, this study finds through case analysis that the model converts fixed costs into variable costs through "asset-light operation", optimizes resource allocation relying on intelligent platforms, and lowers the participation threshold with the support of policy subsidies, thus significantly reducing the costs of machinery purchase, operation and maintenance, and operation for smallholders. The research shows that intelligent agricultural machinery sharing not only directly reduces the explicit expenditures in the production cost structure, but also indirectly optimizes implicit costs by expanding the service area of a single machine to improve operation efficiency and reduce resource waste. Finally, optimization paths are proposed from three aspects: improvement of technology and skills, rational allocation of resources, and precision of policies, providing theoretical support and practical reference for the organic connection between smallholders and modern agriculture.
Intelligent Agricultural Machinery Sharing; Smallholder Economy; Production Cost; Sharing Model
Ziyang Liu, Qing Xia, Yuanru Xue, Huan Liang, Chaojun Mao, Mengdie Zhang. The Impact of Intelligent Agricultural Machinery Sharing Model on Production Costs of Smallholder Economy: A Case Study of Houshan Village Cooperative in Kaiping City. Academic Journal of Business & Management (2025), Vol. 7, Issue 12: 139-144. https://doi.org/10.25236/AJBM.2025.071218.
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