The Willingness and Affecting Factors Underlying Forest Farmers’ Socialization Method to Control Forest Biological Disasters
Year: 2025
Type: article
Study design: Observational Study
Abstract: Amid urbanization, many forest farmers have migrated for work, leading to a shortage of young labor in forestry. Socialized prevention and control (SPC) measures have emerged as a new forestry model. By integrating forestland property rights theory, SPC economic principles, and collaborative disaster governance, this study compares the econometrics methods of seemingly unrelated regression (SUR) and structural equation models (SEMs) to address correlation and endogeneity issues. It aims to understand forest farmers’ willingness to pay for SPC services, purchase forest insurance, and join as forest rangers. The findings offer theoretical and practical insights that address current challenges and rationalize SPC promotion costs, filling gaps in the existing literature. The results indicate that high-quality foresters with more home-planted forests are more inclined to hire SPC companies, while better-educated farmers are less likely to purchase forest insurance. Western forest farmers, highly reliant on forests, show greater willingness to become rangers under village committee organization. Farmers organized by committees or with prevention experience suggest SPC costs around USD $65/ha and forest premiums at USD $5/ha, with high-quality farmers proposing a ranger salary of USD $190/month. Recommendations include collecting SPC funds from farmers and supplementing through local finances; enhancing the forest insurance system; monitoring SPC companies; and recruiting young, skilled rangers.
Source: Sustainability
DOI: 10.3390/su17093850
Institutions: Chinese Academy of Forestry, Tongji University
Language: English
Topic: Forest Management and Policy
Subfield: Global and Planetary Change
Field: Environmental Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,896
Awards: G4722026989, G5439764188, G6148843143
OpenAlex ID: W4409767300
