Influencing Factors of International Trade in Food Resources: Land, Economic, and Social Features
ABSTRACT International food resource trade serves as a critical mechanism for ensuring global food security and promoting worldwide economic development, which involves multidimensional interactions spanning land, economic, and social factors. Utilizing panel data from 40 countries (2003–2023), this study establishes an evaluation index system for international food resource trade based on agricultural endowments, economic development, and geographic characteristics. QAP analysis was employed to systematically investigate the primary influencing factors of international food resource trade. Results indicate that per capita arable land area, national GDP, trade structure, and legal safeguards exert sustained and significantly positive effects on international food resource trade. Geographical distance between countries and population size demonstrates statistically insignificant impacts. Policy regimes—particularly disparities and uncertainties in tariff rates—impede international food resource trade. In conclusion, countries should strengthen cooperation to refine trade policies and legal frameworks through strategic alignment of food resource trade. Proactively establishing international food trade platforms will enhance the efficient allocation of global food resources and facilitate collective responses to global food security challenges.
Authors
- Kunlin Zhu (ORCID: https://orcid.org/0009-0008-7126-195X)
- Xu Guo (ORCID: https://orcid.org/0000-0001-7014-450X)
- Ľuboš Smutka (ORCID: https://orcid.org/0000-0001-5385-1333)
- László Vasa (ORCID: https://orcid.org/0000-0002-3805-0244)
- Fang Liu (ORCID: https://orcid.org/0000-0003-3271-1846)
- Jiangtao Gao
Institutions
- Henan University of Technology (CN)
- Rural Development Institute (CN)
- Jiangxi Academy of Agricultural Sciences (CN)
- Mendel University in Brno (CZ)
- Jiangxi University of Finance and Economics (CN)
- Jiangxi Agricultural University (CN)
- Széchenyi István University (HU)
Publication Details
- Journal
- Land Degradation and Development
- Published
- 2025-10-09
- DOI
- https://doi.org/10.1002/ldr.70235
- Citations
- 1
- Primary Topic
- Smart Systems and Machine Learning
- Type
- article
- Field-Weighted Citation Impact
- 1.49