Factors influencing contract farming disputes and dispute resolution intentions: Evidence from an emerging Southeast Asian country
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DOIhttp://dx.doi.org/10.21511/ppm.23(2).2025.21
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Article InfoVolume 23 2025, Issue #2, pp. 302-318
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Creative Commons Attribution 4.0 International License
The objective of this study is to explore the factors that contribute to disputes in contract farming and to understand the motivations behind selecting a dispute resolution method. Data for this study were obtained through in-depth interviews and group discussions with 15 lawyers, as well as surveys conducted among 525 respondents, comprising 323 farmers and 202 agribusiness representatives in the Central Coast region of Vietnam. The results of the partial least squares structural equation modeling (PLS-SEM) indicate that all research hypotheses are supported. The factors influencing the occurrence of disputes in contract farming agreements, ranked in ascending order of impact, are contract content, social influence, price volatility, risk perception, environmental uncertainty, and legal understanding. Additionally, these factors indirectly affect the intention to resolve disputes through courts, commercial arbitration, and mediation via the mediating role of contract farming disputes. Furthermore, the study reveals that when contract farming disputes arise, the preferred order of dispute resolution methods is courts, followed by commercial arbitration, and finally, mediation. This empirical analysis also provides evidence of significant differences in perceptions between two groups – farmers and agribusiness enterprises – regarding the intention to resolve disputes through courts and the impact of environmental uncertainty on contract farming disputes. The findings enrich empirical research on contract farming dispute resolution in emerging countries with conditions similar to those of Vietnam.
Acknowledgment
This study is the result of collaboration between a group of scientists from the University of Law, Hue University, and School of Business and Economics, Duy Tan University. The authors would like to acknowledge the support and facilitation provided by both institutions for the publication of this research.
- Keywords
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JEL Classification (Paper profile tab)M10, K12, J43, J52
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References41
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Tables7
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Figures2
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- Figure 1. Model and hypotheses
- Figure 2. PLS-SEM testing
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- Table 1. Reliability assessment of the scale
- Table 2. Discriminant reliability among heterotrait-monotrait ratio
- Table 3. Predictive ability of the model
- Table 4. f2, inner VIF, direct impacts
- Table 5. Multigroup analysis
- Table A1. Descriptive statistics of samples
- Table B1. Measurement summary
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