Analyzing determinants of long-rotation plantation decisions by local households in Quang Tri Province, Vietnam with Bayesian Networks
Document Type
Article
Publication Date
3-2024
Department
College of Forest Resources and Environmental Science
Abstract
Vietnam is one of the most dynamic furniture industries in the world. However, the domestic raw wood is struggling to meet the demands of the booming furniture industry in quantity and quality. Long-rotation plantations are expected to be a potential solution to improve local livelihoods and mitigate climate change impacts. In this study, we used binary logistic regression to analyze four groups of factors that affect the adoption of long-rotation plantations, including household characteristics, socio-economic factors, biophysical and technical factors, and institutional and policy factors using data collected from 315 households in Vinh Linh and Cam Lo districts, Quang Tri province, Vietnam. We also developed a Bayesian Network model to identify key drivers influencing small-scale forest planters' adoption of long-rotation plantations. The study results indicated that FSC participation, assurance of seedling source, understanding of the long-rotation timber market, and distance from house to plantation site positively influence households' decision on long-rotation plantation. In contrast, the lack of capital in years 4 to 5 and the typhoon impact rate negatively affect long-rotation plantations. The research findings suggest that supporting policies that provide forest planters with better access to FSC projects, low-interest credit systems, and better-quality planting material and equipment could encourage local households to adopt long-rotation plantations in the coming years.
Publication Title
Land Use Policy
Recommended Citation
Dinh Le, H.,
Thi Mai Anh, T.,
Thi Hai Hien, V.,
Thi Van, L.,
&
Thi Mai, N.
(2024).
Analyzing determinants of long-rotation plantation decisions by local households in Quang Tri Province, Vietnam with Bayesian Networks.
Land Use Policy,
138.
http://doi.org/10.1016/j.landusepol.2023.107029
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p2/408